The Home Mortgage Interest Deduction and Migratory

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Insurance over the Great Recession∗

Danny Yagan

Abstract

The home mortgage interest deduction (HMID) encourages homeownership and larger

mortgages, which may impede migration when house prices fall. This paper investigates

the degree to which the HMID reduced workers’ insurance against local variation in the

employment effects of the Great Recession via impeded migration to strong local labor

markets. Utilizing variation in the HMID at state borders and comparing similar individuals across space, I find that individuals lacked insurance against enduring employment

effects of Great Recession local shocks, but I do not find significant evidence that state

HMIDs hindered that insurance by impeding migration. I therefore do not find evidence

in this context that “dynamic” distortions of the HMID via impeded migration magnified

any of its “static” distortions to economic activity. However, estimates are uncertain and

leave room for future work.

Introduction

The home mortgage interest deduction (HMID) is the single largest U.S. tax expenditure other

than the exclusion of employer-provided health insurance. Over 35 million households claim

the federal HMID (Brady, Cronin and Houser 2003), and the HMID is estimated to cost the

U.S. government over $75 billion in foregone tax revenue in 2016 (U.S. Treasury Department

2015). The HMID reduces households’ net cost of debt-financed home purchases, relative to

other purchases of goods and services. The tax expenditure can increase home ownership, the

size and quality of purchased homes, and the average share of each home purchase financed by

debt rather than by down payments (Hendershott and Pryce 2006, Poterba and Sinai 2011).

People who own homes with large mortgages may migrate at lower rates when house prices

decline because they face larger moving costs: paying off “underwater mortgages” whose balance

exceeds the home’s current market price (Ferreira, Gyourko and Tracy 2010).

∗

Email: yagan@berkeley.edu. The opinions expressed in this paper are those of the author alone and do not

necessarily reflect the views of the Internal Revenue Service or the U.S. Treasury Department. This work is

a component of a larger project examining the effects of tax expenditures on the budget deficit and economic

activity. The tax data were accessed under IRS contract TIRNO-12-P-00374.

Analyses of the effects of the HMID on the U.S. economy have typically focused on static

effects: its effect on a given year’s tax revenue (e.g. Poterba and Sinai 2011, U.S. Treasury

Department 2015), distortions between housing and other forms of consumption (Aaron 1972,

Rosen 1979, 1985, Mills 1987, Poterba 1984, 1992), and the quantity and price of housing at

a given point in time (Hilber and Turner 2014). This paper estimates a dynamic effect of the

HMID: the degree to which the HMID impeded adjustment to the Great Recession by impeding

migration. The Great Recession had dramatically different effects across space; for example,

America’s sixth largest city (Phoenix, Arizona) suffered a large decline in employment while

America’s seventh largest city (San Antonio, Texas) suffered only a small decline. Migration

is the primary way that the U.S. labor market adjusts to local employment shocks (Blanchard

and Katz 1992, Bound and Holzer 2000), and the option to migrate to stronger labor markets

is a primary way that the U.S. economy could have insured the original residents of places

like Phoenix against especially adverse employment losses. But by encouraging people to buy

houses and to buy houses with larger mortgages, the HMID may have impeded migration and

thus impeded adjustment (Molloy, Smith and Wozniak 2011).

I investigate this dynamic distortion channel with a novel empirical strategy. I first estimate

the effect of the HMID on migration over the Great Recession using variation in home mortgage

interest (HMI) deductibility at the state level. Specifically, I use selected de-identified data from

U.S. tax records to examine workers living in 2007 in the 110 local labor markets—defined as

Tolbert and Sizer’s (1996) Commuting Zones (CZ)—that straddle the borders of two or more

states, 66 CZs of which allow for different degrees of HMI deductibility on either side of the

border. For example, Arkansas allows HMI deductibility from state personal income taxes while

Texas has no broad-based personal income tax, and the Texarkana CZ comprises counties on

either side of the Arkansas-Texas border. I further attempt to hold all else equal by comparing

very similar workers across borders: those who are the same age, earned the same amount, and

worked in the same industry in 2006, just in different locales. I then compare the 2007-2015

migration rates of people who had claimed the federal HMID on the Arkansas side of the border

in 2006 to the migration rates of people who claimed the federal HMID on the Texas side of

the border in 2006 within firms (and similarly for other CZs). These people had very similar

skills and lived in the same CZ and so were subject to similar labor market conditions and

had revealed similar preferences for where in the United States to live, but faced very different

incentives to purchases houses with large mortgages.

After estimating the effect of state HMIDs on 2007-2015 migration, I then estimate the

value of migration in escaping the incidence of especially severe Great Recession local shocks.

This analysis utilizes cross-CZ variation in the severity of the 2007-2009 recession while continuing to utilize within-industry variation in similar workers’ locations to hold all else equal. I

investigate the limited extent of “migratory insurance”—which I define as the degree to which

2015 employment differs across workers based on where they were living in 2007—given all existing adjustment mechanisms. I conduct several robustness checks to ensure the validity of the

comparisons, as well as correlations that investigate a role for underwater mortgages and the

HMID. I then assess the likelihood that extra migration unleashed by a hypothetical removal

of the HMID could indeed have improved migratory insurance.

The remainder of the paper is organized as follows. Section 2 presents background on the

HMID and details the empirical strategy. Section 3 introduces the tax data. Section 4 presents

estimates of the effect of the HMID on migration rates since the Great Recession. Section

5 presents an analogous analysis of mortgage holding, the key HMID effect channel. Section

6 documents the enduring need for migratory insurance in spite of other existing adjustment

mechanisms. Section 7 assesses the degree to which the HMID hindered migratory insurance

since the Great Recession. Section 8 concludes.

The HMID and the Empirical Strategy

This section details the home mortgage interest deduction (HMID) and this paper’s empirical

strategy based on state-level variation in the HMID and within-industry comparisons.

2.1

Background on the HMID

Since the beginning of the federal income tax, Congress has permitted households to deduct

interest payments on personal loans from their federal taxable income. The Tax Reform Act

of 1986 eliminated the federal deductibility of many interest payments on consumer loans such

as credit card payments but retained the deductibility of interest payments on mortgages with

certain mild restrictions. To a first approximation at the federal level, homeowners can deduct

interest payments on mortgages on first and second homes that total up to $1 million, as well

as interest payments on home equity loans that total up to $100,000 (see IRS Publication 936

for full details). Hence, the vast majority of U.S. homeowners may deduct all of their interest

payments from their federal taxable income.

Home mortgage interest (HMI) deductibility at the state level varies considerably (ITEP

2011). Twenty-six states generally follow federal rules for HMI deductibility from state taxable

income. Another five states and the District of Columbia follow federal rules but apply stricter

limitations to the value and type of mortgage interest payments that can be deducted. Ten

states do not allow any HMI deductions. Finally, nine states do not assess a broad-based

personal income tax, instead raising revenue from other sources such as sales taxes that do

not subsidize HMI. Table 1 lists all states in these categories and their associated top personal

income tax rates, an easy-to-compare measure of the relative value of HMI deductibility across

states.

The value of the HMID depends on the personal income tax rate that would otherwise be

paid on the income that was deducted. To be concrete using an example that will surface later

in the section, consider a married-filing-jointly household in Arkansas that earns $75,000 in

gross income in a given year and pays $10,000 in deductible mortgage interest in that year.

Arkansas allows the HMID and taxes residents’ income above $50,000 at a rate of 7%, so the

household saves $10, 000 × 7% = $700 in taxes thanks to HMI deductibility.1 Hence, HMI

deductibility is more valuable when tax rates are higher.

2.2

Empirical Strategy

The central question of this paper is whether the HMID reduced Americans’ migration-based

insurance (“migratory insurance”) against local variation in the Great Recession. Empirically

identifying the effect of the HMID requires variation in HMI deductibility or the value of HMI

deductibility and the ability to compare similar people subject to different deductibility while

holding all else equal. Two leading sources of variation are problematic. First, because this

paper focuses on a single time period, variation in the value of the HMID over time—such

as when personal tax rates change or when inflation rates change as in Glaeser and Shapiro

(2003)—is not useful. Second, taxpayers at different income levels are different in numerous

ways that may affect migratory insurance over the Great Recession independent of the value

of HMI deductibility, so comparing migratory insurance across taxpayers of different income

levels would likely be problematic.

Instead, this paper utilizes variation in HMI deductibility across state borders and holds

all else equal by comparing workers within industries and firms. As detailed in the previous

subsection, some states permit HMI deductibility while other states do not. Figure 1A displays

this variation graphically. The states in white do not allow the HMID (either explicitly, or

implicitly because they lack broad-based personal income taxes). The states in colors allow

the HMID; the colors plot the top state personal tax rate in such states, so the HMID is more

valuable in states with darker colors.

Because migration rates can vary across states for reasons other than the HMID, I focus on

small geographical areas that are economically connected but straddle state borders. The local

area concept I use in this paper is called the Commuting Zone (CZ)—geographic units designed

by Tolbert and Sizer (1996) to approximate U.S. local labor markets. Specifically, they used

commuting patterns reported in the 1990 Census to divide the united States in 741 areas that

This example calculation ignores the fact that, in the absence of deducting HMI, the household could take

the standard deduction of $4,000, so the first $4,000 in itemized deductions do not in fact represent net tax

savings. This is an appropriate shortcut for this example because states allow numerous other deductions such

as for real estate taxes that could exceed the $4,000 standard deduction on their own.

share strong commuting ties relative to nearby areas. Statistically, they are aggregations of

counties; in rural areas, they may include only one or two counties, while in urban areas, they

may include several. CZs have been used recently in economics research by Autor, Dorn and

Hanson (2013) among others.

I utilize variation within the 66 CZs in the continental United States that straddle the

border of two states or more states that differ in HMID deductibility. Figure 1B displays those

66 CZs. They are distributed broadly across the United States. For concreteness, Figure 2

zooms in on the Texarkana CZ, which comprises Texarkana, Arkansas, Texarkana, Texas, and

surrounding counties. Arkansas allows HMI deductibility while Texas does not. Using this CZ

as an example, this compares 2007-2015 outcomes among people who at the beginning of 2007

(i.e. before the recession) lived in the Texarkana CZ on the Arkansas side of the border, relative

to people who at the beginning of 2007 lived in the Texarkana CZ but on the Texas side of the

border. By focusing on such within-CZ differences in migration rates, I hope to hold constant

numerous factors that may independently influence migration.

Upon estimating the effect of the HMID on migration, I then estimate the effect of migration

on adjustment to the Great Recession. As discussed in the introduction and documented below,

a striking feature of the Great Recession is that it yielded dramatic variation in employment

shocks across space. Migration is the key adjustment mechanism by which workers can escape

the incidence of large and enduring local shocks: workers in heavily-shocked places may be able

to move to lightly-shocked places and compete for employment there. Since CZ’s approximate

self-contained local labor markets, I focus on employment shock variation at the CZ level and

estimate the degree to which the 2007 residents of heavily-shocked CZ’s were able to diffuse

their CZ’s shocks across workers nationwide by migrating and finding employment in other CZs.

To the extent that 2007 location affects 2015 employment and thus that migratory insurance

is incomplete, I estimate the degree to which greater migration from a hypothetical removal of

the HMID may have enabled greater insurance.

It is instructive to note that, using the kinds of designs I have just described, one cannot

estimate the direct effect of the HMID on adjustment to the Great Recession and instead must

do so in the two specified stages. The effect of the HMID is identified only from within-CZ

differences, while the effect of migration on adjustment to the Great Recession is identified only

from cross-CZ differences. These differences stem from the sources of identifying variation.

HMI deductibility varies across states, so the best hope of holding all else equal derives from

narrow comparisons across state borders, such as within CZs. In contrast, local employment

shocks are in principle shocks to entire local labor markets, so there is little credible variation

in local employment shocks within CZ’s.

Data

I implement this paper’s empirical design using selected de-identified data from federal income

tax records spanning 1999-2015. All analyses were conducted at secure government facilities and

on datasets stripped of unmasked personal identifiers. The sample construction is summarized

as follows; additional details are listed in the Data Appendix.

3.1

Analysis Samples

I implement the paper’s empirical design using selected de-identified data from federal income

tax records spanning 1999-2015. I construct five samples as follows. All five samples are

balanced panels of individuals.

Random Sample. The main sample comprises a 2% random sample from what I call the

full sample. The full sample comprises all American citizens aged 30-49 (“working age”) on

January 1, 2007, who had not died by December 31, 2015, and who had a valid payee ZIP code

on at least one information return that indicates continental U.S. residence in January 2007.

The age restriction confines the 1999-2015 employment analysis to those older than schooling

age and younger than retirement age. Birth, death, and citizenship data are drawn from Social

Security Administration (SSA) records housed alongside tax records.2 Restricting attention to

those alive in 2015 excludes analysis of mortality effects, likely a conservative choice (Sullivan

and Von Wachter 2009). I describe geocoded information returns in the next subsection. I

randomly sample individuals from the full sample using the last two digits of the individual’s

masked identification number, yielding the “full analysis sample” of 1,357,974 people working

across 722 CZs. 3 Restricting to CZs that straddle a state border leaves me with a “random

border analysis sample” of 233,530 workers in 115 CZs. Since only 66 CZs straddle state borders

with different HMI deductability on either side, regressions in the border analysis sample derive

identifying variation from 66 CZs, not 115.

Retail Chain Sample. The retail chain sample comprises individuals in the full sample

whose main employer in 2006 was a retail chain firm and who lived outside of the local area

of the retail chain firm’s headquarters. It is constructed as follows. For every individual in

the full sample with a 2006 W-2 form, I attempt to link the masked employer identification

number (EIN) on the individual’s highest-paying 2006 W-2 to at least one business return in

Citizenship is recorded as of December 2016. Results are very similar when not conditioning on citizenship

status. Conditioning on citizenship reduces the possibility that 2007 residents are employed in other countries

but appear non-employed in U.S. tax data.

The sample is smaller than the universe of CZs for three main reasons: the age range restrictions, mismatches

between W-2 EIN and business return EIN, and conservative removal of workers at firm headquarters and those

not in the continental United States; see the Data Appendix for more details.

the universe of business income tax returns 1999-2007.4 I use the North American Industry

Classification System (NAICS) code on the business income tax return to restrict attention to

workers whose 2006 firms operated in the two-digit-NAICS retail trade industries (44 or 45), e.g.

Walmart and Safeway.5 I further exclude employees living in 2007 in the CZ of their employer’s

headquarters, using the workers’ payee ZIP codes across their information returns (see the next

subsection) and the filing ZIP code on business income tax returns and mapping these ZIP

codes to Commuting Zones (CZs, the local area concept defined in the next subsection). Then

to identify CZs in which the 2006 firms operated, I further restrict to firms with at least ten

2006 employees living in each of at least five CZs and restrict to the firms’ employees living in

2007 in those CZs.6 This procedure yields a retail chain sample of 866,038 individuals at 524

retail firms.7 Then analogously to how I created the random border analysis sample, I create

a “retail border analysis sample” comprising 147,334 individuals in 110 CZs. Unlike firms in

manufacturing and other industries, retail firms employ workers to perform identical tasks in

many different locales. I therefore assume that workers with similar demographics were as

good as randomly assigned across 2007 local areas conditional on their 2006 retail firms and

the amount they earned at their 2006 firms.

Mass Layoffs Sample. The mass layoffs sample comprises individuals in the full sample who

separated from an employer during a mass-layoff event in either 2008 or 2009, after having

worked for the employer during the prior three calendar years inclusive of the separation year.

It is constructed as follows, closely adhering to the sampling frame of Davis and Von Wachter

(2011) except that I define an employer as an EIN-CZ pair rather than an EIN.8 Using the

universe of W-2s and linking W-2 payee (residential) ZIP codes to CZs, I compute annual

employment counts at the EIN-CZ level. For an employer to qualify as having a mass-layoff

event in year t ∈ {2008, 2009}, the employer must satisfy the following conditions: it had

at least 50 employees in t − 1; employment contracted by 30% to 99% from t − 1 to t + 1;

employment in t − 1 was no greater than 130% of t − 2 employment; and t + 2 employment was

less than 90% of t−1 employment.9 The mass layoffs sample comprises all 1,001,543 individuals

in the full sample who received a W-2 with positive earnings in years t − 2 through year t from

Many firms’ workers cannot be linked to a business income tax return; see the next subsection.

Accessed data lacked firm names. I do not know which specific firms survived the sample restrictions. These

example firms and their industry codes were found on Yahoo Finance.

As in other U.S. administrative data (e.g. Census’s Longitudinal Employer Household Dynamics, see Walker

2013), specific establishments of multi-establishment firms are not directly identified in federal tax data.

The sample is smaller than the universe of retail chain workers for four main reasons: the age restriction,

the de facto exclusion of workers at independently owned franchises, mismatches between W-2 EIN and business

return EIN, and removal of workers at firm headquarters.

An EIN may be a firm or a division of a firm.

The 99% threshold protects against EIN changes yielding erroneous mass-layoff events. The last two criteria

exclude temporary employment fluctuations. A firm that initially qualifies as having mass-layoff events in both

2008 and 2009 is assigned a 2008 event only.

a mass-layoff employer but not in t + 1.

3.2

Variable Definitions

I now define variables. Year refers to calendar year unless otherwise specified. Variables are

available 1999-2015.

1. Outcomes.

2007-2015 migration is defined as a worker possessing a 2015 CZ that is different from her

2007 CZ. 2007 CZ is the CZ corresponding to the payee (residential) ZIP code that appears

most frequently for the individual in 2006 among the approximately thirty types of information returns (filed mandatorily by institutions on behalf of an individual, including W-2s).10

Information returns are typically issued in January of the following year, so the ZIP code on a

individual’s 2006 information return typically refers to the individual’s location as of January

2007. 2015 CZ is defined analogously to 2015 CZ, except that if an individual lacks an information return in 2014, I impute CZ using information return ZIP code from the most recently

preceding year in which the individual received an information return. 2007 state denotes the

state with most or all of the 2007 CZ’s population. A mover is someone who migrated between

2007 and 2015.

2007 state deductability of mortgage interest equals zero if the worker’s 2007 state (defined

analogously to 2007 CZ–i.e corresponding to the worker’s payee ZIP code that appears most

frequently across the worker’s 2006 information returns) does not allow mortgage interest deductability from state personal income taxes or if the state lacks a personal income tax. It equals

one if worker’s 2007 state allows full deductability of mortgage interest from the state personal

income tax. When defined “inclusively”, I code partial-deductability states as one; when defined “exclusively”, I code partial-deductability states as zero. See Table 1 for deductability by

state.11

2007 top rate deductability of mortgage interest equals 2007 state deductability of mortgage

interest, multiplied by the worker’s 2007 state’s personal income tax rate. 2006 mortgage holder

is a binary indicator for whether a Form 1098 information return was issued on the worker’s

behalf by a mortgage servicer in 2006.12

Employment in a given year is an indicator for whether an individual has positive Form

Numerous activities trigger information returns including formal and independent contractor employment;

SSA or UI benefit receipt; mortgage interest payment; business or other capital income; retirement account

distribution; education and health savings account distribution; debt forgiveness; lottery winning; and college

attendance. A comparison to external data suggests that 98.2% of the U.S. population appeared on some form

submitted to the IRS in 2003 (Mortenson, Cilke, Udell and Zytnick 2009).

For standard errors, I cluster on the 2007 state with most or all of the worker’s 2007 CZ’s population,

following earlier work.

A mortgage servicer is required to file a Form 1098 on behalf of any individual from whom the servicer

receives at least $600 in mortgage interest on any one mortgage during the calendar year.

W-2 earnings or Form 1099-MISC independent contractor earnings (both filed mandatorily by

the employer) in the year. Employment is thus a measure of having been employed at any

time during the year. Note that this annual employment measure differs from the conventional

point-in-time (survey reference week) measure used by the Bureau of Labor Statistics.

Earnings in a given year represents labor income and equals the sum of an individual’s

Form W-2 earnings and Form 1099-MISC independent contractor earnings. All dollar values

are measured in 2015 dollars, adjusting for inflation using the headline consumer price index

(CPI-U) and are top-coded at $500,000 after inflating. DI receipt is an indicator for whether

the individual has positive Social Security Disability Insurance income (SSDI) in the year

as recorded on Form 1099-SSA information returns filed mandatorily by the Social Security

Administration. SSDI is the main disability insurance program in the United States. UI

receipt is an indicator for whether the individual has positive unemployment insurance benefit

income in the year as recorded on Form 1099-G information returns filed mandatorily by state

governments.

2. Great Recession Local Shock. Each individual’s Great Recession local shock equals

the percentage-point change in the individual’s 2007 CZ’s unemployment rate from 2007 to 2009.

Annual CZ unemployment rates are computed by aggregating monthly population-weighted

county-level unemployment rates from the monthly Bureau of Labor Statistics Local Area

Unemployment Statistics series to the CZ-month level, then averaging evenly within CZ-years

across months.

3. Covariates. Age is defined as of January 1 of the year, using date of birth from SSA

records housed alongside tax records. Following Autor, Dorn, Hanson and Song (2014), an

individual had high labor force attachment if she earned at least $10,382 in 2015 dollars—the

compensation for 1,600 hours of work at the 2004 federal minimum wage in 2015 dollars—of

earnings in each of the four years 2003-2006. An individual had no labor force attachment if she

had zero earnings in any year 2003-2006. Female is an indicator for being recorded as female in

SSA records. 1040 filer is an indicator for whether the individual appeared as either a primary

or secondary filer on a Form 1040 tax return in tax year 2006. Married is an indicator for

whether the individual was either the primary or secondary filer on a married-filing-jointly or

married-filing-separately 1040 return in tax year 2006. Number of kids equals the number of

children (zero, one, or two-or-more) living with the individual as recorded on the individual’s

2006 1040 if the individual was a 1040 filer and zero otherwise. Mortgage holder is an indicator

for whether a Form 1098 information return was issued on the individual’s behalf by a mortgage

servicer in 2006.13 Birth state is derived from SSA records and, for immigrants, equals the state

of naturalization.

A mortgage servicer is required to file a Form 1098 on behalf of any individual from whom the servicer

receives at least $600 in mortgage interest on any one mortgage during the calendar year.

2006 industry equals the four-digit NAICS industry code on the business income tax return

of an individual’s highest-paying 2006 Form W-2, whenever a match can be made between

the masked EIN on the W-2 and the masked EIN on the business income tax return. Fourdigit NAICS codes are quite narrow, distinguishing for example between restaurants and bars.

As displayed below in summary stats and similar to parallel work (Kline, Petkova, Williams

and Zidar 2017, Mogstad, Lamadon and Setzler 2017), almost half of all W-2 earners could

not be matched—likely because the employer is a government entity (which does not file an

income tax return, covering 15-20% of employment) or because the firm uses a different EIN

(e.g. a non-tax-filing subsidiary) to pay workers from the one that appears on the firm’s tax

return. For the construction of fixed effects, I assign individuals with missing industry to their

own exclusive industry; I assign non-W-2-earning contractors to their own exclusive industry;

and I assign the non-employed to their own exclusive industry. I show below that results are

nearly unchanged when restricting the sample to the non-employed and those with a valid W-2

industry, for whom the correct industry is universally observed.

2006 age-earnings-industry fixed effects are interactions between age (measured in one-year

increments), 2006 industry, and sixteen bins of the individual’s 2006 earnings (in 2015 dollars

inflated by the CPI-U) from the individual’s highest-paying employer.14 2006 firm equals the

masked employer identification number on the individual’s highest-paying 2006 W-2. 2006

age-earnings-firm fixed effects are constructed analogously to 2006 age-earnings-industry fixed

effects. Other controls are used only for robustness checks and are defined when used.

3.3

Summary Statistics

Table 2 reports summary statistics for the five data samples used in both the main analyses and

the robustness checks: a random 2% sample of the full population and satisfy the restrictions

described above, a random 2% “border” sample that restricts the full population sample to

those who live in CZs that straddle two states, the retail chain sample (all non-headquarters

workers for identifiable retail chain firms in 2006), the border retail sample, and the mass

layoffs sample (all workers who separated from a firm in a 2008 or 2009 mass layoff). By the

characteristics described in the table, the border samples and the full analysis samples are

broadly similar. Compared to the random sample of the full population, the retail sample is

poorer, more female, is less likely to get married, have kids, or own homes. 15 The mass layoffs

The main result below is nearly identical when using Local CPI 2—the more aggressive of the Moretti (2013)

local price deflators—to locally deflate 2006 earnings before binning. Chosen to create roughly even-sized bins,

the bin minimums are: $0, $2,000, $4,000, $6,000, $8,000, $10,000, $15,000, $20,000, $25,000, $30,000, $35,000,

$40,000, $45,000, $50,000, $75,000, and $100,000.

The mortgage holder shares in the border and full analysis samples are lower than the U.S. adult home

ownership rate: the sample is younger and poorer than the U.S. as a whole, the mortgage holder share excludes

home owners without a mortgage, and mortgages held only in the name of a worker’s spouse or other third

sample, in contrast, is richer and more male than the random sample, but still less likely to get

married or have kids.

Effect of the HMID on Migration

In this section, I use the state-border empirical strategy in the random 2% border sample to

estimate the effect of the HMID on 2007-2015 migration. I first estimate the effect of the HMID

on migration using a reduced-form specification that puts no structure on the nature or strength

of the mechanism by which a tax subsidy to mortgage interest affects migration. I then apply a

series of robustness checks, first applying rich controls to the reduced-form estimates, allowing

partial HMID states to be misclassified and allowing mortgage interest tax subsidies to have

a linear effect on migration. As a further robustness check, I rerun this analysis on the retail

border sample, which has the additional benefit of comparing especially similar workers.

4.1

Main Results

To estimate the effect of the HMID on migration using the state-border empirical strategy, I

estimate regressions in the border analysis sample of the form:

M IGRAT EDi = βHM IDST AT Es(i2007) + Xi2007c(i2007) γ,

(4.1)

where M IGRAT EDi is an indicator for whether worker i migrated across CZs between 2007

and 2015, HM IDs(i2007) is an indicator for whether i was living in 2007 in an HMID-eligible

state, and Xi2007r(i,2007) is a vector of individual-level and CZ-level covariates. The coefficient

β̂ is the coefficient of interest: the estimated effect of living in an HMID-eligible state in 2007

on whether the worker migrated 2007-2015.

Table 3A displays the main results: estimated effects of living in an HMID-eligible state in

2007 on 2007-2015 migration, under successively larger sets of controls. HMID-eligible states

are defined inclusively: partial deductibility states are classified as allowing HMI deductibility.

Column 1 has no controls. Column 2 adds age fixed effects, Column 3 uses fixed effects of age

interacted with earnings bins, and Column 4 further interacts these age-earnings with industry

fixed effects based on NAICS code. These age-earnings-industry fixed effects in Column 4

represent my preferred specification, and all subsequent columns control for these effects while

adding additional controls that one might concerned about, such as gender and marital status.

Column 1 shows that, in the cross section, workers who lived in 2007 in a state that permits

HMID deductibility are estimated to have been 2.425 percentage points more likely to have

party are not included here.

migrated 2007-2015. This estimate is statistically significant and has the unexpected sign,

which would be consistent with the HMID increasing migratory insurance. The point estimate

is fairly insensitive to additional controls, except for CZ size, which is added in Column 9.

Controlling for CZ size reduces the coefficient to 1.739, which implies that populous CZs are

disproportionally located in states with HMID and that people in populous CZs were more likely

to have moved. The additional controls in Table 3A do, however, highlight the weakness of the

main result. Several columns, including my preferred estimate in Column 4, are statistically

insignificant at the 95% confidence level, meaning that one cannot say with confidence that

there is an effect of being in an HMID state on migration. In fact, the data do not reject a

negative effect of the HMID on 2007-2009 migration under reasonable specifications.

4.2

Robustness to State Misclassification

The main results in Table 3A classify states as HMI deductible or nondeductible states inclusively: partial deductibility states are classified as allowing HMI deductibility. However, it is

possible that the near-zero estimates of Table 3A are attenuated toward zero because of misclassification: perhaps partial deductibility states have such muted effects of home ownership and

mortgage leverage that they are effectively the same as non-deductible states. Table 3B therefore defines deductibility exclusively: partial deductibility states are classified as not allowing

HMI deductibility and thus lumped in with states that either do not allow HMI deductibility

in their personal income tax or do not have a personal income tax at all.

Table 3B shows that the exclusive definition does indeed somewhat alter the point estimates, though no more so than adding controls did in Table 3A. It also points to a cautious

interpretaion of the point estimates based on the size of the 95% confidence intervals. The

confidence interval on the coefficient in Column 15, for instance, is [−0.26, 4.52], which again

means that living in a (full) HMID state could increase migration, decrease migration or have

no impact on migration at all.

4.3

Robustness to Linear Specifications

The results of Table 3 use a simple binary classification of HMI deductibility. Despite its

simplicity, the binary specification could lack statistical power relative to a specification that

allows for larger effects of among states with larger HMI deductibility. Table 4 therefore replicates Table 3 using the continuous measure of HMI deductibility of the worker’s 2007 top rate

deductibility of mortgage interest.16

Though many workers are not in the top state income tax bracket, this measure is simple and readily

available.

Table 4 yields point estimates that are intermittently significant at the 95% level. Consistent

with Table 3, there is little difference in the estimates in Panel A and Panel B, implying that

the classification of partial HMID states is not particularly important.

Figure 3A non-parametrically presents the result in Table 4A Column 4. It is constructed

by regressing 2007-2015 migration and 2007 top rate deductibility of mortgage interest on the

controls underlying Column 4, computing residuals, adding back their means for interpretation,

and plotting means of the 2007-2015 migration residuals within twenty equal-sized bins of

the 2007 top rate deductibility residuals. Overlaid is the best-fit line estimated by regressing

the 2007-2015 migration residuals on the 2007 top rate deductibility residuals, whose slope of

course equals the 0.295 reported in Table 4A Column 4. As one can see from the graph, the

marginally significant result under the linear specification does not appear to be masking a

visually obvious non-linear relationship, further suggesting that there is indeed no statistically

significant relationship between these two variables.

Table 4B Column 15 presents analogous results using the exclusively defined measure of

state HMI deductibility. Like Table 4A, Table 4B reports positive estimates are that are

still statistically insignificant. Therefore the null results of Table 3 are robust to the linear

specifications presented in Table 4.

Effect of the HMID on Mortgage Holding

The previous section found no conclusive evidence of the HMID on 2007-2015 migration due

to substantial statistical noise. If it had, one would have expected this effect to flow through

the mechanism of home ownership. The HMID encourages people to take on mortgages and

buy homes, and owning a home in a given area increases the likelihood that people will stay

in that area. This section focuses on determining whether the first link in that logical chain

holds, looking at whether the people living in states with HMID were indeed more likely to own

homes in 2006. As in the previous section, I use a wide range of robustness checks on both the

2% random border sample and the retail border sample in order to present a complete picture

of the data.

Table 5 replicates Table 3 for the outcome of owning a mortgage in 2006.17 Estimates using

the inclusive definition of HMI deductibility reveal a near-zero relationship between deductibility

and mortgage holding. Depending on controls, the point estimate of this effect was either

positive or negative. In the preferred specification, workers living in 2007 in a state offering

deductibility of mortgage interest were insignificantly 0.426 percentage points less likely to hold

Recall that although location is measured in 2007 and mortgage holding is measured in 2006, these outcomes

are actually simultaneous: both 2007 location and 2006 mortgage holding are measured using 2006 information

returns.

a mortgage. The standard error 1.213 is substantial, implying a substantial 95% confidence

interval [−2.88, 2.03]. Thus subject to statistical uncertainty, I find no evidence that residents

of HMI deductible states have higher rates of holding a mortgage.

Table 5B shows similar results when using the exclusive definition of HMI deductibility,

though the point estimate for my preferred specification is now positive (although still statistically insignificant). Residents of states with HMI deductibility are 0.266 percentage points

more likely to hold a mortgage. However, the standard error remains large at 0.731 percentage

points. I therefore fail to find a statistically significant positive relationship between binary

HMI deductibility and mortgage holding.

Turning to the continuous measure of HMI deductibility, Table 6 replicates Table 4 for

the mortgage holding outcome. Like the previous tables, I continue to find near-zero and

statistically insignificant results. Defining HMI deductibility inclusively, Column 4 reports that

residents of states with one-percentage-point higher HMI deductibility were 0.043 percentage

points less likely to hold a mortgage, with a standard error of 0.164. Defining HMI deductibility

exclusively, Column 15 reports that residents of states with one-percentage-point higher HMI

deductibility were 0.093 percentage points more likely to hold a mortgage, with a standard

error of 0.088. Thus the two panels of Table 6 both find no statistically significant relationship.

Figure 3B non-parametrically presents the result in Table 6A Column 4, using the same

method as Figure 3A. Here, one can see that the slightly negative relationship, but the standard

error shows that this result is completely statistically insignificant.

Thus across specifications, I find no statistically significant relationship between HMI deductibility and mortgage holding. This sheds light on interpreting the previous section’s lack

of a statistically significant effect of HMI deductibility on migration. It may indeed be the

case that a tax policy that causes people to buy a house or take out a larger mortgage also

causes them to migrate less. However, it appears that the HMID may not in fact be such a

mortgage-holding-inducing policy.

Robustness to Inter-firm Heterogeneity in Workers

Although I have thus far failed to find conclusive effects in either direction of the impact of

HMID on migration in response to the Great Recession, it is possible that these effects are

masked by inter-firm heterogeneity in workers. It is possible, for instance, that different firms

within the same industry hire workers of different average skill level, or that some workers

develop specialized skills that make them valuable only to a specific firm, and that that firm

is located only in a certain area. To address potential selection issues, I used my retail border

analysis sample and repeated the analysis that I did for the random 2% border sample, with

the full suite of controls.

The results are displayed in Tables 7 through 10, with Table 7 corresponding to Table 3,

Table 8 corresponding to Table 4 and so on. The results are broadly similar, both for the main

analysis and the robustness checks. As with the 2% random sample, the point estimates for the

coefficients of interest in Tables 7 and 8 are all positive for Panels A and B, though with greater

statistical precision that rejects a substantial negative effect. Tables 9 and 10, like Tables 5 and

6 for the 2% random sample, show statistically insignificant point estimates.

Figure 4 is analogous to Figure 3. Figure 4A corresponds to Table 8 Column 5 and Figure

4B corresponds to Tablel 10 Column 5. As with its companion figure, Figure 4A serves to

show that there are no non-linearities masking a more significant relationship, and 4B shows a

nominally negative, but statistically insignificant relationship.

The Enduring Need for Migratory Insurance

The previous sections found no significant negative effect of HMI deductibility on 2007-2015

migration rates. However, these effects were estimated with error, failing to reject the possibility

that the effect could be negative and substantial. In particular, I estimated a 95%-confidence

upper bound of the reduction in migration rates due to HMI deductibility (on average across

states with HMI deductibility versus states without HMI deductibility) equal to 0.22 percentagepoints-lower migration rates in the preferred specification (recall Table 3A, Column 4). If

migration was exceptionally valuable in avoiding the incidence of local variation in the Great

Recession, then the 95%-confidence upper bound effect of HMI deductibility on migratory

insurance may yet be large. This section investigates whether there was an enduring need for

migratory insurance in the first place, or whether employment rates had converged across space

through existing mechanisms.

7.1

Main Effects

Figure 5A plots the time series of estimated effects of living in 2007 in a relatively severely

shocked CZ, conditional on the main controls in the full analysis sample. The plotted 2015

data point is this subsection’s main result and equals β̂ estimated in:

EM P LOY EDi2015 = βSEV EREc(i2007) + Xi2007c(i2007) γ,

(7.1)

where EM P LOY EDi2015 is an indicator for whether worker i was employed in 2015,

SEV EREc(i2007) is an indicator for whether i was living in 2007 in a relatively severely shocked

CZ, and Xi2007r(i,2007) is 2006 age-x-earnings-x-industry fixed effects. For other years t, plotted

data points equal the same coefficient from a regression of EM P LOY EDit on the exact same

right-hand-side values in the exact same sample. 95% confidence intervals are plotted in vertical

lines unadjusted for multiple hypotheses, based on standard errors clustered at the 2007-state

level.

The 2015 data point shows that living in 2007 in a relatively severely shocked CZ is estimated to have caused a 0.393 percentage-point reduction in employment rates, relative to those

who in 2007 were living in a relatively mildly shocked CZ (see Table 11 Column 4). The estimate is very significantly different from zero. The mean 2015 employment rate in this sample

is 79.1%, so this estimated effect is equal to a 0.41% difference in employment rates. The plotted time series of estimated zero effects 1999-2007 constitute placebo tests corroborating the

identifying assumption that conditional on controls, severe- CZ status is as good as randomly

assigned. Panels B and C of Figure 5 re-enforce the conclusion of a significant and enduring

employment impact from Great Recession local shocks. Panel B shows that there is a roughly

linear relationship between Great Recession local shocks and relative employment in 2015 net

of controls. Panel C repeats the analysis in Panel A for earnings and shows a similar enduring

drop.

Table 11 Column 4 displays this main 2015 effect plotted in the Panel A, along with similar

effects under different controls. 18 All specifications in columns 1-8 display similarly negative

and significant results, regardless of controls. Column 6 shows that the employment impacts

were monotonically worse with increasing local shocks, and Columns 9-11 show consistent

results using alternate measures of employment impact.

As a robustness check, Table 12 repeats the analysis for the retail sample. These estimates

are also uniformly negative and statistically significant. Figure 6A is the retail analog for Figure

5A, and similarly, the 2015 data point corresponds to Table 12 Column 5.19

7.2

Robustness

Table 13 presents several robustness checks of the impact of Great Recession local shocks on

employment in 2015, with all its implications for HMID and migratory insurance. Taking

Table 13 Column 4 as a starting point, Columns 2 through 5 add a suite of individual level

controls. Columns 6-9 control for CZ-level characteristics. Column 6 controls an individual’s

2007 CZ’s size, equal to the CZ’s total employment in 2006 as reported in Census’s County

Business Patterns (CBP). Column 7 controls an individual’s 2007 CZ’s size growth, equal

to the CZ’s log change in CBP employment from 2000 to 2006. Column 8 controls for an

See Appendix Table 2 for Great Recession local shock by CZ.

Table 2 showed that the main and retail chain samples differ demographically, and I find impact heterogeneity across demographic groups. I therefore reweight the retail chain sample to match the main sample as

in DiNardo, Fortin and Lemieux (1996) along 2007 CZ, gender, five-year age bin, and 2006 earnings bins.

individual’s 2007 CZ’s share of workers who work outside of the CZ, computed from the 20062010 American Community Surveys. Column 9 controls for an individual’s 2007 CZ’s state’s

maximum unemployment insurance duration over years 2007-2015. Column 10 controls for the

individual’s 2007 state’s 2015 minimum wage minus that state’s 2007 minimum wage. Column

11 restricts the sample to the 2006 non-employed and 2006 workers with a valid industry code

(i.e. excluding contractors and W-2 earners without industry). Column 12 further restricts the

sample by excluding individuals employed in construction or manufacturing in 2006. Column 13

instruments the individual’s Great Recession local shock using the mean of the Great Recession

local shock in the individual’s birth state. Throughout all of this, the estimates remain negative

and significant.

Table 14 provides a finer look at the year-by-year impacts of Great Recession local shocks

in 2007. It displays results for migration and various labor market outcomes. These outcomes

include those in Column 8, the individual’s unemployment insurance benefits, and Column 9,

the individual’s Social Security Disability Insurance benefits in year t. This pair of outcomes is

discussed more in the next subsection. The estimates for migration are positive, but insignificant

and the estimates for the basic employment measure are negative and significant. The estimates

for other measures vary in significance. Migration rates were slightly higher out of severely

shocked CZs than other CZs: 18.2% out of most-shocked-quintile CZs and 16.5% out of leastshocked-quintile CZs. However, Columns 4 and 7 reveal no statistically significant evidence that

migration enabled individuals in severely shocked areas to find employment and earnings at

higher levels in other CZs. This suggests that any extra migration unleashed by a hypothetical

removal of the HMID may not have substantially improved migratory insurance. 20

7.3

Tests for Worker-Scarring Mechanisms

If living in 2007 in a relatively severely shocked CZ “scarred” workers by reducing their human

capital or raising their reservation wages, their employment may be persistently low even if they

were to move to a stronger local labor market. That is, the enduring employment impact of

2007 location could be specific to the worker rather than specific to the worker’s 2015 location,

meaning that migration would not help the worker escape incidence. I therefore test for leading

candidates of worker-specific effects; if I find strong effects, then additional migration likely

could not have provided substantially more insurance.

A first potential worker-specific channel is disability insurance. Severe Great Recession

local shocks may have induced workers to supplement their income with Social Security Disability Insurance (“DI”)—a typically permanent location-independent income stream—thereby

permanently raising their reservation wages and reducing their employment independent of

Appendix Table 1 replicates Table 14 in the years leading up to the great recession.

current location (Autor and Duggan 2003, Maestas, Mullen and Strand 2013). One can estimate an upper bound on the contribution of DI receipt to the main employment result, under

the weak monotonicity assumption that the treatment (living in 2007 in a relatively severely

shocked area) did not make anyone in the analysis sample less likely to go on DI. The estimated

upper bound on the DI mechanism equals the estimated effect on an indicator for 2015 employment (the main result) minus the estimated effect on an indicator for whether the worker

was employed in 2015 or was on DI in 2015. Table 15 Column 2 displays the result: living

in 2007 in a relatively severely shocked area is estimated to have caused workers to be 0.27

percentage-points less likely to be employed or on DI on 2015. Subtracting this effect from the

main −0.393 percentage-point effect on employment, 32.6% of the incrementally non-employed

relatively severely shocked natives were on DI by 2015, and thus 32.6% is the estimated upperbound contribution of transition to DI to the enduring employment impact. To the extent that

incremental transition to DI was a response to a lack of employment rather than a cause of it,

transition to DI explains no more than 32.6% of the employment impact and potentially less.

The tight upper-bound on the DI contribution is reflected in the statistically zero impact of

living in 2007 in a relatively severely shocked area on 2015 DI receipt (Column 1).

A second potential worker-specific channel is more workers being laid off—following a long

line of work documenting long-term earnings losses after layoff (Ruhm 1991, Jacobson, LaLonde

and Sullivan 1993, Neal 1995, Couch and Placzek 2010). I proxy for layoff using unemployment

insurance (UI) receipt.21 Table 15 Column 6 shows that living in 2007 in a relatively severely

shocked area caused workers to be 1.43 percentage points more likely to have received UI by

2015 (i.e. at any point 2007-2015), but this effect is significant, but small relative to the

sample-wide mean of 25.6 percentage points. This suggests that higher rates of layoff cannot

explain relatively severely shocked natives’ lower 2015 employment rates. Column 8 shows

that controlling for UI receipt by 2015 barely changes the employment effect estimate. This

is of course not quasi-experimental since layoff is endogenous. But if one assumes that the

laid-off relatively severely shocked natives were equal or stronger on unobservables than laid-off

relatively mildly shocked CZ natives—as would be expected of incremental layoffs in a layoffsand-lemons model (Gibbons and Katz 1991)—then these columns indicate that higher layoffs

do not explain the employment results.

A third potential worker-specific channel is general human capital decay after long nonemployment spells. Table 15 column 6 indicates that Great Recession local shocks caused

individuals to be more likely to spend at least one year 2007-2014 completely non-employed.

Column 10 shows that the individual’s employment history 2007-2012 explains nearly the entire

2015 employment impact. Columns 3-5 and Figure 6B reveal similar impacts in the mass

Kawano and LaLumia (2017) show that UI-tax-data-based unemployment rates are close in both level and

trend to official Bureau-of-Labor-Statistics unemployment rates 1999-2011 (correlation 0.94).

layoffs sample, which comprises quite similar workers who were laid off into local labor markets

that were more likely (severely shocked CZs) or less likely (other CZs) to lead to a long nonemployment spell. These results are consistent with the worker-specific channel of general

human capital decay.

Overall, the findings rule out some candidate worker-scarring mechanisms, but general human capital decay via prolonged non-employment is consistent with the results. However, this

worker-scarring mechanism is not the only mechanism consistent with the results. The results

are also consistent with persistently low local labor demand, under which laid-off workers have

not experienced human capital decay but have experienced either a decline in their local wages

or cannot obtain desired employment at prevailing local wages. Under persistently low local

labor demand, more migration could indeed have provided more insurance: the local areas

rather than the workers can be thought of as scarred. Further distinguishing mechanisms is a

valuable area for future work.

7.4

Heterogeneity of Effects

I close by estimating whether subgroups of workers that had higher migration rates also had

attenuated employment effects and thus greater insurance. Figure 7A plots point estimates and

95% confidence intervals for several worker subgroups defined by pre-2007-determined characteristics in the full analysis sample. Each row reports results from estimating equation 7.1

with the main controls on a different subsample: the full analysis sample, by gender, by 2006

earnings bin, by labor force attachment, by 2006 age group, by 2006 marital status, by 2006

number of kids, and by 2006 mortgage holding status. Rates of 2007-2015 migration of the

analyzed subsample are listed in the far right of each row. Comparison of subgroup migration

rates to subgroup differences presents a surprising result: the effect of 2007 location is not

smaller for more mobile subgroups. The finding is most salient for mortgage-holding versus

non-mortgage-holding comparison. Mortgage holders had migration rates of only 13% while

non-mortgage-holders had 18% migration rates. Yet the two subgroups experienced similar

(such that their confidence intervals overlap) 2015 employment effects of living in 2007 in a

relatively severely shocked CZ, and if anything, it would appear that the mortgage holders

experienced slightly smaller employment effects. These subgroups could of course be different

along other dimensions, but this is suggestive evidence that greater migration may not have

provided greater insurance against local variation in Great Recession local shocks. Figure 7B

plots point estimates and 95% confidence intervals for the same groups, only this time for 2006

earnings. Results are broadly similar.

Conclusion

This paper has investigated whether the home mortgage interest deduction (HMID)—the

second-largest U.S. tax expenditure—substantially impeded insurance against Great Recession local labor demand shocks by impeding residents’ migration. Utilizing a novel empirical

design based on variation in home mortgage interest deductibility across state borders and

comparing similar workers within firms, I find no significant effect of the HMID on migration

2007-2015. However, the statistical uncertainty permits considerable negative effects if affected

residents indeed lacked insurance and if existing migration was indeed a beneficial insurance

mechanism. I find substantial under-insurance against local variation in the Great Recession:

the 2007 residents of severely affected areas were substantially less like to be employed in 2015

than the 2007 residents of mildly affected areas. However, a direct analysis of the insurance

benefit of migration reveals no statistically significant evidence that out-migration from severely

affected areas was a beneficial insurance mechanism, though with large standard errors. Hence,

it remains possible that the HMID hindered adjustment to the Great Recession by hindering

migration, but the analysis failed to find significant evidence of it. The results nevertheless

inform future work.

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Data Appendix

This appendix section provides additional data details.

First, the universe of business tax returns used is the universe of C-corporate (Form 1120),

S-corporate (Form 1120S), and partnership (Form 1065) tax returns. Businesses that file other

types of tax returns employ a small share of U.S. workers.

Second, Form 1099-MISC data on independent contractor employment are missing in 1999.

Results are very similar when omitting 1999 data.

Third, many retail chain firms are missing from the retail border and chain samples, both

because of subsidiaries and franchises and also because a (likely small) number of firms outsource

their W-2 administration to third-party payroll administration firms that list their own EINs

on W-2s. Nevertheless, the retail chain sample includes very large nationwide chains.

Fourth and also specific to the retail border and chain samples, the filing ZIP code on a

firm’s business income tax return typically but not always refer to the business’s headquarters

ZIP code. Excluding workers at the business’s headquarters is useful because headquarters

workers may perform systematically different tasks than workers at other establishments and

thus may possess different human capital even conditional on baseline earnings. I therefore

conservatively exclude firms’ workers living in the CZ with the largest number of the firm’s

workers living there, as well as the CZ with the largest number of the firm’s workers living

there as a share of the total number of workers living there.

Fifth and also specific to the retail border and chain samples, I consider a firm to have

operated in a CZ in 2006 if it employed at least ten stably located workers who lived in the

CZ—defined as individuals of any age and citizenship with a W-2 from the firm in all years

2005-2007 and the same residential CZ in all years 2005-2007 based on those W-2s’ payee

(residential) ZIP codes. It is necessary to define CZ operations using more than one year of

W-2 data because W-2 payee ZIP code refers to the worker’s ZIP code in January of the year

after employment. That feature implies that almost all firms would appear to have operations

in every large CZ if one were to use only 2006 W-2s to identify CZ operations, since many

workers move to large cities.

Figure 1: HMI Tax Subsidy Rates across U.S. States

A. HMI Tax Subsidy Rates by State

B. CZs that Straddle States with Different HMI Subsidies

Notes: Panel A plots HMI (home mortgage interest) tax subsidy rates by state, equal to zero for states that do

not allow HMI deductions or lack a personal income tax, and equal to the top state marginal personal income

tax rate for states that do allow HMI deductions. Panel B highlights the 66 Commuting Zones (CZs) that

straddle borders between at least two states with different HMI subsidies.

Figure 2: Example of a CZ Utilized in the HMID Cross-Border Design

Notes: Commuting Zones (CZs) are collections of counties that correspond to relatively self-contained local labor

markets. This paper estimates the effect of the HMI deduction on migration rates by comparing migration rate

differences across state borders in the CZs that straddle the border between at least two states that have different

HMI subsidy rates. The Texarkana CZ is one such CZ. The main cities in the Texarkana CZ are Texarkana,

Texas, and Texarkana, Arkansas. The CZ encompasses these two cities’ counties and nearby counties. Arkanasas

allows for HMI deductibility from state personal income taxes, while Texas does not have a state personal income

tax from which HMI could be deducted.

Figure 3: 2% Random Sample Visualizations

Migration rate (%)

A. 2007-2015 Migration Rates versus HMID Tax Subsidy Rates

HMID tax expenditure subsidy

Mortgage holding rate (%)

B. 2006 Mortgage Holding versus HMID Tax Subsidy Rates

HMID tax expenditure subsidy

Notes: Panel A non-parametrically depicts the relationship between workers’ 2007-2015 migration rates and

their 2007 state’s HMID tax subsidy. It does so by regressing migration rates and HMID tax subsidy on the main

controls, computing residuals, added back their means for interpretation, and plotting means of the migration

rate residuals within twenty equal-sized bins of the HMID tax subsidy residuals. Overlaid is the best-fit line

(slope 0.295, standard error 0.152). Panel B is the analogous figure showing the relationship between workers’

2006 mortgage holding and their 2007 state’s HMID tax subsidy. Overlaid is the best-fit line (slope −0.043,

standard error 0.164).

Figure 4: Retail Sample Visualizations

Migration rate (%)

A. 2007-2015 Migration Rates versus HMID Tax Subsidy Rates

HMID tax expenditure subsidy

Mortgage holding rate (%)

B. 2006 Mortgage Holding versus HMID Tax Subsidy Rates

HMID tax expenditure subsidy

Notes: Panel A non-parametrically depicts the relationship between workers’ 2007-2015 migration rates and

their 2007 state’s HMID tax subsidy. It does so by regressing migration rates and HMID tax subsidy on the main

controls, computing residuals, added back their means for interpretation, and plotting means of the migration

rate residuals within twenty equal-sized bins of the HMID tax subsidy residuals. Overlaid is the best-fit line

(slope 0.328, standard error 0.127). Panel B is the analogous figure showing the relationship between workers’

2006 mortgage holding and their 2007 state’s HMID tax subsidy. Overlaid is the best-fit line (slope −0.147,

standard error 0.156).

Figure 5: Employment and Earnings Impacts of Great Recession Local Shocks

.25

-.25

-.5

2015

2014

2013

2012

2011

2010

C. Earnings Impact of Great

Recession Local Shocks

-500

2015

2014

2013

2012

2011

2010

2009

2008

2007

2006

2005

2004

2003

2002

Great Recession local shock

2001

2000

1999

-1500

-1000

-7

-7.5

-8

-8.5

-9

2015 relative employment (pp)

-6.5

Effect of Great Recession local shock ($)

500

B. Non-Parametric Visualization

of the 2015 Impact

2009

2008

2007

2006

2005

2004

2003

2002

2001

2000

1999

-.75

Effect of Great Recession local shock (pp)

A. Employment Impact of Great Recession Local Shocks

Notes: Panel A plots regression estimates of the effect of Great Recession local shocks on annual relative

employment conditional on 2006 age-earnings-industry fixed effects in the main sample (a 2% random sample).

Each year t’s outcome is year-t relative employment: the individual’s year-t employment (binary employment

status) minus the individual’s mean 1999-2006 annual employment. 95% confidence intervals are plotted around

estimates, clustering on 2007 state. For reference, the 2015 data point (the paper’s main estimate) implies that

a 1-percentage-point higher Great Recession local shock caused individuals to be 0.393 percentage points less

likely to be employed in 2015. Panel B non-parametrically depicts the relationship underlying the Panel A

2015 data point. It is produced by regressing Great Recession local shocks on 2006 age-earnings-industry fixed

effects, computing residuals, adding back their means for interpretation, and plotting means of the 2015 relative

employment within twenty equal-sized bins of the shock residuals. Overlaid is the best-fit line, whose slope is

equal to panel A 2015 data point. Panel C replicates panel A for the outcome of year-t relative earnings: the

individual’s year-t earnings minus the individual’s mean 1999-2006 annual earnings.

Figure 6: Employment Impacts in Special Samples

-.2

-.4

2011

2012

2013

2014

2015

2011

2012

2013

2014

2015

2010

2009

2008

2007

2006

2005

2004

2003

2002

2001

2000

1999

-.6

Effect of Great Recession local shock (pp)

A. Retail Chain Sample

-.5

-1

2010

2009

2008

2007

2006

2005

2004

2003

2002

2001

2000

-1.5

1999

Effect of Great Recession local shock (pp)

B. Mass Layoffs Sample

Notes: Panel A replicates Figure 5A in the retail chain sample (all non-headquarters workers for identifiable

retail chain firms in 2006). Panel B replicates Figure 5A in the mass layoffs sample (all workers who separated

from a firm in a 2008 or 2009 mass layoff). See the notes to Figure 5A for specification details.

Figure 7: Impact Heterogeneity

A. Employment

Subgroup

Migration Rate

Overall

16%

Earnings $0

Earnings $1-$15k

Earnings $15k-$45k

Earnings $45k+

16%

20%

16%

15%

No LF attachment

Low LF attachment

High LF attachment

18%

21%

14%

Age 30-34

Age 35-39

Age 40-44

Age 45-49

21%

17%

14%

13%

Men

Women

17%

16%

Single

Married

19%

14%

0 kids

1 kid

2+ kids

20%

15%

13%

Mortgage holder

Non-mortgage-holder

13%

18%

-1

-.75

-.5

-.25

.25

.75

Estimated employment impact of Great Recession local shocks (pp)

B. Earnings

Subgroup

Migration Rate

Overall

16%

Earnings $0

Earnings $1-$15k

Earnings $15k-$45k

Earnings $45k+

16%

20%

16%

15%

No LF attachment

Low LF attachment

High LF attachment

18%

21%

14%

Age 30-34

Age 35-39

Age 40-44

Age 45-49

21%

17%

14%

13%

Men

Women

17%

16%

Single

Married

19%

14%

0 kids

1 kid

2+ kids

20%

15%

13%

Mortgage holder

Non-mortgage-holder

13%

18%

-12

-8

-4

Estimated earnings impact of Great Recession local shocks (%)

Notes: Panel A plots coefficients and 95% confidence intervals of the impact of Great Recession local shocks on 2015 relative

employment—overall (equal to the 2015 data point in Figure 5A) and by subgroup. All estimates derive from the specification

underlying the 2015 data point in Figure 5A. Subgroup estimates restrict the sample to the specified subgroup defined by gender,

2006 earnings, 2007 age, 2006 marital status, 2006 number of kids, or 2006 mortgage holding. Non-1040-filers are classified here as

single and childless. Standard errors are clustered by 2007 state. Subgroup migration rates are superimposed on the right, where

migration is defined as one’s 2015 CZ being different from one’s 2007 CZ. Panel B replicates panel A for 2015 earnings expressed in

multiples of mean annual earnings 1999-2006: 2015 earnings divided by mean annual 1999-2006 earnings. This quantity is top-coded

at the 99th percentile, and individuals with zero 1999-2006 earnings are assigned the top code if 2015 earnings were positive and

assigned 0 otherwise. The overall estimate is -0.0355 (standard error 0.0094), implying that a 1-percentage-point-higher Great

Recession local shock reduced the average individual’s 2015 earnings by 3.55% of her pre-recession earnings.

TABLE 1

Home Mortgage Interest Deductability at the State Level

State

Home Mortgage Interest Deductability

Top Personal Income Tax Rate

Alabama

Alaska

Arizona

Arkansas

California

Colorado

Connecticut

Delaware

D.C.

Florida

Georgia

Hawaii

Idaho

Illinois

Indiana

Iowa

Kansas

Kentucky

Louisiana

Maine

Maryland

Massachusetts

Michigan

Minnesota

Mississippi

Missouri

Montana

Nebraska

Nevada

New Hampshire

New Jersey

New Mexico

New York

North Carolina

North Dakota

Ohio

Oklahoma

Oregon

Pennsylvania

Rhode Island

South Carolina

South Dakota

Tennessee

Texas

Utah

Vermont

Virginia

Washington

West Virginia

Wisconsin

Wyoming

Full

None

Full

Partial

Full

None

Full

Partial

None

Full

Partial

Full

None

Full

None

Full

None

Full

Partial

Full

None

Full

None

Full

None

Partial

Full

None

Partial

None

5.00%

0.00%

4.54%

7.00%

12.30%

4.63%

6.70%

6.75%

8.95%

0.00%

6.00%

11.00%

7.40%

5.00%

3.40%

8.98%

4.90%

6.00%

8.00%

5.75%

5.25%

4.25%

7.85%

5.00%

6.00%

6.90%

6.84%

0.00%

8.97%

4.90%

8.82%

7.75%

3.99%

5.93%

5.25%

9.90%

3.07%

5.99%

7.00%

0.00%

5.00%

8.95%

5.75%

0.00%

6.50%

7.75%

0.00%

Notes - For each state, this table specifies whether the state allows full (i.e. equal to the federal level), partial (less than the

federal level but still positive), or no deductibility of home mortgage interest. This table also lists each state's top personal

income tax rate.

TABLE 2

Summary Statistics

Random 2% Border Sample

Outcomes (in 2015)

Employed (%)

Earnings (2015 $)

DI receipt (%)

UI receipt sometime 2007-2014 (%)

Personal characteristics (in 2006, 2007)

Female (%)

Retail Border Sample

Random 2% Sample

Retail Chain Sample

Mass Layoffs Sample

Mean

(1)

Std. Dev.

(2)

Mean

(3)

Std. Dev.

(4)

Mean

(5)

Std. Dev.

(6)

Mean

(7)

Std. Dev.

(8)

Mean

(9)

Std. Dev.

(10)

80.0

47,089

6.7

25.7

40.0

61,180

25.0

43.7

81.9

32,253

7.2

27.9

38.5

41,901

25.9

44.9

79.1

47,587

6.2

25.6

40.7

63,784

24.2

43.6

81.8

33,381

6.9

28.3

38.5

44,557

25.3

45.0

84.1

48,204

6.0

52.2

36.5

62,830

23.8

50.0

49.4

50.0

61.2

48.7

49.3

50.0

60.8

48.8

44.5

49.7

Earnings (2015 $)

44,808

52,182

32,219

35,266

45,652

55,122

33,424

36,708

52,511

55,336

Age

Aged 30-34 (%)

Aged 35-39 (%)

Aged 40-44 (%)

Aged 45-49 (%)

40.0

21.9

24.4

26.0

27.6

5.7

41.4

43.0

43.9

44.7

39.2

26.7

25.0

24.4

24.0

5.8

44.2

43.3

42.9

42.7

39.9

22.2

24.5

26.0

27.3

5.7

41.5

43.0

43.9

44.6

39.2

27.0

25.0

24.3

23.6

5.8

44.4

43.3

42.9

42.5

39.7

23.8

25.0

25.5

25.7

5.7

42.6

43.3

43.6

43.7

22.7

14.9

62.8

41.9

35.6

48.4

15.1

24.3

60.6

35.8

42.9

48.9

10.0

16.4

73.6

29.9

37.1

44.1

No Labor Force Attachment (%)

Low Labor Force Attachment (%)

High Labor Force Attachment (%)

Married (%)

91.4

28.0

93.2

25.2

62.8

48.3

52.2

50.0

52.9

49.9

0 kids (%)

1 kid (%)

2+ kids (%)

3954.0

5.3

12.2

4889.4

22.4

32.7

2607.5

100.0

0.0

4390.5

0.0

36.2

22.6

41.2

48.0

41.8

49.2

41.8

22.9

35.4

49.3

42.0

47.8

40.6

23.4

36.0

49.1

42.3

48.0

1040 filer (%)

25.3

43.5

0.0

91.2

28.3

93.1

25.3

93.8

24.1

Mortgage holder (%)

0.0

0.2

0.0

38.3

48.6

25.9

43.8

38.4

48.6

Retail trade (NAICS 44,45) (%)

Construction/manufacturing (NAICS 23,31-33) (%)

Other observed industry (%)

Contractor (%)

Non-employed (%)

10.9

439.1

0.0

31.1

144.6

0.0

442.1

0.0

138.9

0.0

5.2

11.9

25.9

4.2

11.5

22.3

32.4

43.8

20.1

31.9

100.0

0.0

4.7

17.7

34.9

0.0

21.2

38.2

47.7

0.0

Great Recession local shock (pp)

0.0

4.6

1.5

4.8

1.5

5.0

1.5

Number of individuals

Number of 2007 CZs

233,530

115

147,334

110

1,357,974

722

865,954

655

1,001,543

668

Notes - This table lists summary statistics for the paper's five samples: the random 2% border sample, the retail border sample, the 2% random sample, the retail chain sample (all non-headquarters workers for identifiable retail chain firms in 2006), and the

mass layoffs sample (all workers who separated from a firm in a 2008 or 2009 mass layoff). Earnings is the sume of W-2 wage earnings and 1099-MISC independent contractor earnings in the calendar year, in 2015 dollars and top-coded at $500,000.

Employed is an indicator for having positive earnings. DI receipt is an indicator for having positive 1099-SSA disability insurance income in the calendar year. UI receipt sometime 2007-2014 is an indicator for having positive 1099-G unemployment insurance

benefit income at some point 2007-2014. Age is measured on January 1, 2007. Married is an indicator for filing a married-filing-jointly or married-filing-separately 1040 for tax year 2006. Number of kids is the number of current dependent kids currently living

with the worker as listed on the filed 1040. 1040 filer is an indicator for having appeared as a primary or secondary filer on a Form 1040 for tax year 2006. Displayed marriage and number of kids statistics are restricted to 1040 filers; in regressions controlling

for marriage or number of kids fixed effects, non-1040-filers are included as a separate group. Mortgage holder is an indicator for having positive mortgage payment listed on a Form 1098 in 2006 (mortgages held only in the name of a worker's spouse or other

third party are not included here). Industry categories are based on the North American Industrial Classification System code on the business income tax return based on matching the individual's highest-paying 2006 W2 to the universe of business returns.

Almost half of W-2 earners could not be matched and individuals who only had 1099-MISC independent contractor earnings are not matched; in fixed effect regressions, unmatched 2006 W-2 earners, contractors, and the non-employed are assigned to three

separate industries. 2007 CZ derives from the worker's January 2007 residential location as reflected most commonly on her 2006 information returns. The Great Recession local shock equals the 2009 unemployment rate in the individual's 2007 CZ minus the

2007 unemployment rate in that CZ as reported by the Bureau of Labor Statistics Local Area Unemployment Statistics.

TABLE 3

Effect of Home Mortgage Interest Deduction on Migration

Binary Indicator of Home Mortgage Interest Deductibility at the State Level in 2% Random Border Sample

A. Inclusive Definition of HMI Deductibility States

Outcome:

2007 state deductability of mortgage interest

(pp)

(1)

(pp)

(2)

2.425

(1.170)

2.311

(1.147)

Age FEs

Age-Earnings FEs

Age-Earnings-Industry FEs

Gender

Number of kids

Married

Home ownership

CZ size

CZ pre-2007 size growth

Cross-CZ commuting

Indicator for individual migration between 2007 and 2014

(pp)

(3)

(4)

(5)

(6)

(7)

(8)

(9)

(pp)

(10)

(pp)

(11)

2.311

(1.138)

2.210

(1.201)

2.218

(1.193)

2.131

(1.190)

2.169

(1.207)

2.193

(1.201)

1.739

(1.024)

2.253

(1.137)

2.379

(1.043)

233,530

0.00

233,530

0.01

233,530 233,530 233,530 233,530 233,530 233,530 233,530

0.02

0.18

233,530

0.18

233,530

0.18

Migration rate (%)

Estimate divided by migration rate (%)

15.1

16.07

15.1

15.31

15.1

15.31

15.1

11.52

15.1

14.93

15.1

15.76

(pp)

(12)

(pp)

(13)

Indicator for individual migration between 2007 and 2014

(pp)

(14)

(15)

(16)

(17)

(18)

(19)

(20)

(pp)

(21)

(pp)

(22)

2.317

(1.159)

2.219

(1.136)

2.230

(1.126)

B. Exclusive Definition of HMI Deductibility States

Outcome:

2007 state deductability of mortgage interest

Age FEs

Age-Earnings FEs

Age-Earnings-Industry FEs

Gender

Number of kids

Married

Home ownership

CZ size

CZ pre-2007 size growth

Cross-CZ commuting

Migration rate (%)

Estimate divided by migration rate (%)

15.1

14.64

15.1

14.69

15.1

14.12

15.1

14.37

15.1

14.53

2.130

(1.181)

2.143

(1.172)

2.105

(1.177)

2.122

(1.190)

2.140

(1.185)

1.797

(0.887)

2.212

(1.091)

2.301

(1.005)

233,530

0.00

15.1

15.35

233,530

0.01

15.1

14.70

233,530 233,530 233,530 233,530 233,530 233,530 233,530

0.02

0.18

15.1

14.77

14.11

14.20

13.94

14.06

14.18

11.90

Notes - This table estimates the effect of state deductibility of the home mortgage interest (HMI) deduction on 2007-2014 migration. Panel A categorizes

state HMI deductibility inclusively: states that permit only partial deductibility are categorized as allowing deductions when defining the 2007 state

deductability of mortgate interest binary indicator. Panel B categorizes state HMI deductibility exclusively: states that permit only partial deductibility are

categorized as not allowing deductions. See the text for additional details.

233,530

0.18

15.1

14.66

233,530

0.18

15.1

15.25

TABLE 4

Effect of Home Mortgage Interest Deduction on Migration

Continuous Measure of Home Mortgage Interest Deductibility at the State Level in 2% Random Border Sample

A. Inclusive Definition of HMI Deductibility States

Outcome:

2007 top rate deductability of mortgage interest

(pp)

(1)

(pp)

(2)

Indicator for individual migration between 2007 and 2014

(pp)

(3)

(4)

(5)

(6)

(7)

(8)

(9)

(pp)

(10)

(pp)

(11)

0.324

(0.148)

0.307

(0.145)

0.305

(0.144)

Age FEs

Age-Earnings FEs

Age-Earnings-Industry FEs

Gender

Number of kids

Married

Home ownership

CZ size

CZ pre-2007 size growth

Cross-CZ commuting

Migration rate (%)

Estimate divided by migration rate (%)

Migration rate (%)

Estimate divided by migration rate (%)

0.278

(0.152)

0.288

(0.153)

0.293

(0.152)

0.225

(0.127)

0.292

(0.153)

0.315

(0.130)

233,530

0.00

233,530 233,530 233,530 233,530 233,530 233,530 233,530 233,530

0.01

0.02

0.18

15.1

1.95

15.1

1.96

15.1

1.84

15.1

1.91

15.1

1.94

233,530

0.18

233,530

0.18

15.1

2.15

15.1

2.04

15.1

2.02

15.1

1.49

15.1

1.93

15.1

2.09

(pp)

(12)

(pp)

(13)

Indicator for individual migration between 2007 and 2014

(pp)

(14)

(15)

(16)

(17)

(18)

(19)

(20)

(pp)

(21)

(pp)

(22)

0.321

(0.155)

0.305

(0.152)

0.306

(0.151)

Age FEs

Age-Earnings FEs

Age-Earnings-Industry FEs

Gender

Number of kids

Married

Home ownership

CZ size

CZ pre-2007 size growth

Cross-CZ commuting

0.295

(0.150)

B. Exclusive Definition of HMI Deductibility States

Outcome:

2007 top rate deductability of mortgage interest

0.295

(0.152)

0.296

(0.158)

0.297

(0.157)

0.289

(0.160)

0.295

(0.160)

0.299

(0.159)

0.251

(0.114)

0.305

(0.155)

0.318

(0.133)

233,530

0.00

15.1

2.13

233,530 233,530 233,530 233,530 233,530 233,530 233,530 233,530

0.01

0.02

0.18

15.1

2.02

2.03

1.96

1.97

1.91

1.96

1.98

1.66

233,530

0.18

15.1

2.02

233,530

0.18

15.1

2.10

Notes - This table replicates Table 3 except that it replaces the binary independent variable measuring HMI deductibility with a continuous measure. The continuous

measure equals the binary measure times the state's top marginal income tax rate. See the text for additional details.

TABLE 5

Effect of Home Mortgage Interest Deduction on Mortgage Holding

Binary Indicator of Home Mortgage Interest Deductibility at the State Level in 2% Random Border Sample

A. Inclusive Definition of HMI Deductibility States

Outcome:

2007 state deductability of mortgage interest

(pp)

(1)

(pp)

(2)

(pp)

(3)

Indicator for individual mortgage holding in 2006

(pp)

(4)

(5)

(6)

(7)

(8)

(pp)

(9)

(pp)

(10)

(pp)

(11)

0.345

(0.920)

0.491

(0.906)

-0.310

(1.279)

-0.426

(1.213)

-0.331

(0.976)

-0.289

(1.175)

-0.316

(1.163)

0.000

(0.000)

-0.837

(0.949)

-0.362

(0.933)

-0.364

(0.971)

Age FEs

Age-Earnings FEs

Age-Earnings-Industry FEs

Gender

Number of kids

Married

Home ownership

CZ size

CZ pre-2007 size growth

Cross-CZ commuting

Migration rate (%)

Estimate divided by migration rate (%)

233,530

0.00

233,530 233,530 233,530 233,530 233,530 233,530 233,530 233,530

0.01

0.19

0.32

0.36

0.33

1.00

0.32

39.5

0.87

39.5

1.24

39.5

-0.79

(pp)

(12)

(pp)

(13)

2007 state deductability of mortgage interest

1.149

(1.229)

1.271

(1.186)

Age FEs

Age-Earnings FEs

Age-Earnings-Industry FEs

Gender

Number of kids

Married

Home ownership

CZ size

CZ pre-2007 size growth

Cross-CZ commuting

Migration rate (%)

Estimate divided by migration rate (%)

39.5

-0.84

39.5

-0.73

39.5

-0.80

233,530

0.32

39.5

0.00

39.5

-2.12

39.5

-0.92

39.5

-0.92

(pp)

(14)

Indicator for individual mortgage holding in 2006

(pp)

(15)

(16)

(17)

(18)

(19)

(pp)

(20)

(pp)

(21)

(pp)

(22)

0.364

(0.785)

0.266

(0.731)

0.418

(0.547)

0.321

(0.780)

0.301

(0.775)

0.000

(0.000)

-0.059

(0.560)

0.299

(0.545)

0.422

(0.525)

B. Exclusive Definition of HMI Deductibility States

Outcome:

39.5

-1.08

233,530

0.32

233,530

0.00

39.5

2.90

233,530 233,530 233,530 233,530 233,530 233,530 233,530 233,530

0.01

0.19

0.32

0.36

0.33

1.00

0.32

39.5

3.22

0.92

0.67

1.06

0.81

0.76

0.00

-0.15

233,530

0.32

39.5

0.76

233,530

0.32

39.5

1.07

Notes - This table replicates Table 3 for the outcome of whether a worker held a mortgage in 2006, defined as the worker having received a Form 1098 in 2006. See Table

3 and the text for additional details.

TABLE 6

Effect of Home Mortgage Interest Deduction on Mortgage Holding

Continuous Measure of Home Mortgage Interest Deductibility at the State Level in 2% Random Border Sample

A. Inclusive Definition of HMI Deductibility States

Outcome:

2007 top rate deductability of mortgage interest

(pp)

(1)

(pp)

(2)

(pp)

(3)

Indicator for individual mortgage holding in 2006

(pp)

(4)

(5)

(6)

(7)

(8)

(pp)

(9)

(pp)

(10)

(pp)

(11)

0.015

(0.097)

0.037

(0.097)

-0.027

(0.171)

-0.043

(0.164)

-0.036

(0.140)

-0.017

(0.155)

-0.025

(0.153)

0.000

(0.000)

-0.113

(0.140)

-0.053

(0.138)

-0.027

(0.135)

Age FEs

Age-Earnings FEs

Age-Earnings-Industry FEs

Gender

Number of kids

Married

Home ownership

CZ size

CZ pre-2007 size growth

Cross-CZ commuting

Migration rate (%)

Estimate divided by migration rate (%)

233,530

0.00

233,530 233,530 233,530 233,530 233,530 233,530 233,530 233,530

0.01

0.19

0.32

0.36

0.33

1.00

0.32

39.5

0.04

39.5

0.09

39.5

-0.07

(pp)

(12)

(pp)

(13)

2007 top rate deductability of mortgage interest

0.178

(0.151)

0.197

(0.145)

Age FEs

Age-Earnings FEs

Age-Earnings-Industry FEs

Gender

Number of kids

Married

Home ownership

CZ size

CZ pre-2007 size growth

Cross-CZ commuting

Migration rate (%)

Estimate divided by migration rate (%)

39.5

-0.09

39.5

-0.04

39.5

-0.06

233,530

0.32

39.5

0.00

39.5

-0.29

39.5

-0.13

39.5

-0.07

(pp)

(14)

Indicator for individual mortgage holding in 2006

(pp)

(15)

(16)

(17)

(18)

(19)

(pp)

(20)

(pp)

(21)

(pp)

(22)

0.108

(0.092)

0.093

(0.088)

0.112

(0.070)

0.104

(0.093)

0.096

(0.093)

0.000

(0.000)

0.035

(0.074)

0.076

(0.074)

0.124

(0.078)

B. Exclusive Definition of HMI Deductibility States

Outcome:

39.5

-0.11

233,530

0.32

233,530

0.00

39.5

0.45

233,530 233,530 233,530 233,530 233,530 233,530 233,530 233,530

0.01

0.19

0.32

0.36

0.33

1.00

0.32

39.5

0.50

0.27

0.23

0.28

0.26

0.24

0.00

0.09

233,530

0.32

39.5

0.19

233,530

0.32

39.5

0.31

Notes - This table replicates Table 4 for the outcome of whether a worker held a mortgage in 2006, defined as the worker having received a Form 1098 in 2006. See Table

4 and the text for additional details.

TABLE 7

Effect of Home Mortgage Interest Deduction on Migration

Binary Indicator of Home Mortgage Interest Deductibility at the State Level in Retail Border Sample

A. Inclusive Definition of HMI Deductibility States

Outcome:

2007 state deductability of mortgage interest

(pp)

(1)

(pp)

(2)

(pp)

(3)

2.917

(0.927)

2.881

(0.924)

2.854

(0.959)

Age FEs

Age-Earnings FEs

Age-Earnings-Industry FEs

Age-Earnings-Firm FEs

Gender

Number of kids

Married

Home ownership

CZ size

CZ pre-2007 size growth

Cross-CZ commuting

Indicator for individual migration between 2007 and 2014

(pp)

(4)

(5)

(6)

(7)

(8)

(9)

(3)

(4)

(5)

2.884

2.589

2.587

2.445

2.449

2.537

(1.023) (0.957) (0.964) (0.990) (0.978) (0.955)

(pp)

(10)

(pp)

(11)

(pp)

(12)

2.475

(0.780)

2.577

(0.925)

2.782

(0.778)

147,334

0.00

147,334 147,334 147,334 147,334 147,334 147,334 147,334 147,334

0.01

0.02

0.06

0.27

147,334

0.27

147,334

0.27

147,334

0.27

Migration rate (%)

Estimate divided by migration rate (%)

17.6

16.56

17.6

16.35

17.6

16.20

17.6

16.37

17.6

14.69

17.6

14.68

(pp)

(13)

(pp)

(14)

(pp)

(15)

(pp)

(16)

(pp)

(17)

3.319

(0.992)

3.269

(1.001)

3.222

(1.026)

3.218

(1.072)

17.6

13.88

17.6

13.90

17.6

14.40

17.6

14.05

17.6

14.63

17.6

15.79

(pp)

(18)

(pp)

(19)

(pp)

(20)

(pp)

(21)

(pp)

(22)

(pp)

(23)

(pp)

(24)

2.837

(1.006)

2.847

(1.013)

2.731

(1.031)

2.756

(1.024)

2.813

(1.000)

2.918

(0.879)

2.928

(0.933)

3.084

(0.860)

B. Exclusive Definition of HMI Deductibility States

Outcome:

2007 state deductability of mortgage interest

(6)

Age FEs

Age-Earnings FEs

Age-Earnings-Industry FEs

Age-Earnings-Firm FEs

Gender

Number of kids

Married

Home ownership

CZ size

CZ pre-2007 size growth

Cross-CZ commuting

Migration rate (%)

Estimate divided by migration rate (%)

147,334

0.00

17.6

18.84

147,334 147,334 147,334 147,334 147,334 147,334 147,334 147,334

0.01

0.02

0.06

0.27

17.6

18.55

18.29

18.26

16.10

16.16

15.50

15.64

15.97

Notes - This table replicates Table 3 in the retail border sample. See Table 3 and the text for additional details.

147,334

0.27

17.6

16.56

147,334

0.27

17.6

16.62

147,334

0.27

17.6

17.51

TABLE 8

Effect of Home Mortgage Interest Deduction on Migration

Continuous Measure of Home Mortgage Interest Deductibility at the State Level in Retail Border Sample

A. Inclusive Definition of HMI Deductibility States

Outcome:

2007 top rate deductability of mortgage interest

(pp)

(1)

(pp)

(2)

(pp)

(3)

Indicator for individual migration between 2007 and 2014

(pp)

(4)

(5)

(6)

(7)

(8)

(9)

(pp)

(10)

(pp)

(11)

(pp)

(12)

0.363

(0.128)

0.357

(0.126)

0.360

(0.129)

0.370

(0.135)

Age FEs

Age-Earnings FEs

Age-Earnings-Industry FEs

Age-Earnings-Firm FEs

Gender

Number of kids

Married

Home ownership

CZ size

CZ pre-2007 size growth

Cross-CZ commuting

Migration rate (%)

Estimate divided by migration rate (%)

0.328

(0.127)

0.327

(0.128)

0.306

(0.134)

0.308

(0.132)

0.322

(0.128)

0.296

(0.099)

0.309

(0.132)

0.351

(0.105)

147,334

0.00

147,334 147,334 147,334 147,334 147,334 147,334 147,334 147,334

0.01

0.02

0.06

0.27

17.6

2.06

17.6

2.03

17.6

2.04

17.6

2.10

17.6

1.86

17.6

1.86

(pp)

(13)

(pp)

(14)

(pp)

(15)

(pp)

(16)

(pp)

(17)

0.459

(0.145)

0.451

(0.146)

0.450

(0.146)

0.454

(0.149)

147,334

0.27

17.6

1.75

17.6

1.83

17.6

1.68

17.6

1.76

17.6

1.99

(pp)

(18)

(pp)

(19)

(pp)

(20)

(pp)

(21)

(pp)

(22)

(pp)

(23)

(pp)

(24)

0.390

(0.145)

0.391

(0.146)

0.373

(0.151)

0.380

(0.149)

0.388

(0.145)

0.399

(0.127)

0.399

(0.145)

0.421

(0.124)

(6)

Age FEs

Age-Earnings FEs

Age-Earnings-Industry FEs

Age-Earnings-Firm FEs

Gender

Number of kids

Married

Home ownership

CZ size

CZ pre-2007 size growth

Cross-CZ commuting

Migration rate (%)

Estimate divided by migration rate (%)

147,334

0.27

17.6

1.74

B. Exclusive Definition of HMI Deductibility States

Outcome:

2007 top rate deductability of mortgage interest

147,334

0.27

147,334

0.00

17.6

2.61

147,334 147,334 147,334 147,334 147,334 147,334 147,334 147,334

0.01

0.02

0.06

0.27

17.6

2.56

2.55

2.58

2.21

2.22

2.12

2.15

2.20

Notes - This table replicates Table 4 in the retail border sample. See Table 4 and the text for additional details.

147,334

0.27

17.6

2.26

147,334

0.27

17.6

2.26

147,334

0.27

17.6

2.39

TABLE 9

Effect of Home Mortgage Interest Deduction on Mortgage Holding

Binary Indicator of Home Mortgage Interest Deductibility at the State Level in Retail Border Sample

A. Inclusive Definition of HMI Deductibility States

Outcome:

2007 state deductability of mortgage interest

(pp)

(1)

(pp)

(2)

(pp)

(3)

Indicator for individual mortgage holding in 2006

(pp)

(4)

(5)

(6)

(7)

(8)

(9)

(pp)

(10)

(pp)

(11)

(pp)

(12)

-0.311

(1.450)

-0.268

(1.469)

-0.788

(1.636)

-1.052

(1.461)

Age FEs

Age-Earnings FEs

Age-Earnings-Industry FEs

Age-Earnings-Firm FEs

Gender

Number of kids

Married

Home ownership

CZ size

CZ pre-2007 size growth

Cross-CZ commuting

-1.204

(1.259)

-1.219

(1.330)

-0.994

(1.162)

-0.948

(1.109)

0.000

(0.000)

-1.412

(1.028)

-1.262

(0.845)

-1.243

(1.077)

147,334

0.00

147,334 147,334 147,334 147,334 147,334 147,334 147,334 147,334

0.01

0.21

0.25

0.42

0.43

0.42

1.00

147,334

0.42

147,334

0.42

147,334

0.42

Migration rate (%)

Estimate divided by migration rate (%)

26.1

-1.19

26.1

-1.03

26.1

-3.02

26.1

-4.04

26.1

-4.62

26.1

-4.67

(pp)

(13)

(pp)

(14)

(pp)

(15)

(pp)

(16)

(pp)

(17)

0.530

(0.971)

0.586

(0.997)

-0.250

(1.104)

-0.495

(0.951)

26.1

-3.81

26.1

-3.63

26.1

0.00

26.1

-5.42

26.1

-4.84

26.1

-4.77

(pp)

(18)

(pp)

(19)

(pp)

(20)

(pp)

(21)

(pp)

(22)

(pp)

(23)

(pp)

(24)

-0.566

(0.793)

-0.497

(0.808)

-0.411

(0.753)

-0.433

(0.759)

0.000

(0.000)

-0.688

(0.791)

-0.699

(0.522)

-0.535

(0.664)

B. Exclusive Definition of HMI Deductibility States

Outcome:

2007 state deductability of mortgage interest

(6)

Age FEs

Age-Earnings FEs

Age-Earnings-Industry FEs

Age-Earnings-Firm FEs

Gender

Number of kids

Married

Home ownership

CZ size

CZ pre-2007 size growth

Cross-CZ commuting

Migration rate (%)

Estimate divided by migration rate (%)

147,334

0.00

26.1

2.03

147,334 147,334 147,334 147,334 147,334 147,334 147,334 147,334

0.01

0.21

0.25

0.42

0.43

0.42

1.00

26.1

2.25

-0.96

-1.90

-2.17

-1.91

-1.58

-1.66

0.00

Notes - This table replicates Table 5 in the retail border sample. See Table 5 and the text for additional details.

147,334

0.42

26.1

-2.64

147,334

0.42

26.1

-2.68

147,334

0.42

26.1

-2.05

TABLE 10

Effect of Home Mortgage Interest Deduction on Mortgage Holding

Continuous Measure of Home Mortgage Interest Deductibility at the State Level in Retail Border Sample

A. Inclusive Definition of HMI Deductibility States

Outcome:

2007 top rate deductability of mortgage interest

(pp)

(1)

(pp)

(2)

(pp)

(3)

0.015

(0.200)

0.022

(0.201)

-0.078

(0.206)

Age FEs

Age-Earnings FEs

Age-Earnings-Industry FEs

Age-Earnings-Firm FEs

Gender

Number of kids

Married

Home ownership

CZ size

CZ pre-2007 size growth

Cross-CZ commuting

Migration rate (%)

Estimate divided by migration rate (%)

Indicator for individual mortgage holding in 2006

(pp)

(4)

(5)

(6)

(7)

(8)

(9)

(3)

(4)

(5)

-0.119

-0.147

-0.155

-0.115

-0.111

0.000

(0.182) (0.156) (0.167) (0.144) (0.136) (0.000)

(pp)

(12)

-0.203

(0.142)

-0.170

(0.124)

-0.142

(0.132)

147,334

0.00

147,334 147,334 147,334 147,334 147,334 147,334 147,334 147,334

0.01

0.21

0.25

0.42

0.43

0.42

1.00

26.1

0.06

26.1

0.08

26.1

-0.30

26.1

-0.46

26.1

-0.56

26.1

-0.59

(pp)

(13)

(pp)

(14)

(pp)

(15)

(pp)

(16)

(pp)

(17)

0.175

(0.129)

0.184

(0.131)

0.021

(0.136)

-0.019

(0.115)

147,334

0.42

147,334

0.42

147,334

0.42

26.1

-0.44

26.1

-0.43

26.1

0.00

26.1

-0.78

26.1

-0.65

26.1

-0.54

(pp)

(18)

(pp)

(19)

(pp)

(20)

(pp)

(21)

(pp)

(22)

(pp)

(23)

(pp)

(24)

-0.033

(0.098)

-0.025

(0.100)

-0.008

(0.092)

-0.018

(0.094)

0.000

(0.000)

-0.078

(0.113)

-0.073

(0.078)

-0.018

(0.099)

(6)

Age FEs

Age-Earnings FEs

Age-Earnings-Industry FEs

Age-Earnings-Firm FEs

Gender

Number of kids

Married

Home ownership

CZ size

CZ pre-2007 size growth

Cross-CZ commuting

Migration rate (%)

Estimate divided by migration rate (%)

(pp)

(11)

B. Exclusive Definition of HMI Deductibility States

Outcome:

2007 top rate deductability of mortgage interest

(pp)

(10)

147,334

0.00

26.1

0.67

147,334 147,334 147,334 147,334 147,334 147,334 147,334 147,334

0.01

0.21

0.25

0.42

0.43

0.42

1.00

26.1

0.71

0.08

-0.07

-0.13

-0.10

-0.03

-0.07

0.00

Notes - This table replicates Table 6 in the retail border sample. See Table 6 and the text for additional details.

147,334

0.42

26.1

-0.30

147,334

0.42

26.1

-0.28

147,334

0.42

26.1

-0.07

TABLE 11

2015 Impacts of Great Recession Local Shocks

A. 2015 Employment

Outcome relative to pre-2007 mean:

Great Recession local shock

Employed in 2015

(pp)

(1)

(pp)

(2)

(pp)

(3)

(pp)

(4)

-0.412

(0.112)

-0.425

(0.112)

-0.417

(0.099)

-0.393

(0.097)

(pp)

(5)

Most severely shocked quintile

-1.746

(0.471)

Fourth shock quintile

-1.144

(0.434)

Third shock quintile

-0.793

(0.356)

Second shock quintile

-0.181

(0.320)

Age FEs

Age-Earnings FEs

Age-Earnings-Industry FEs

Unemployment persistence in 2007 CZ

Unemployment persistence in 2015 CZ

(pp)

(6)

(pp)

(7)

-0.366

(0.089)

-0.364

(0.089)

(6)

0.00

(7)

0.00

(8)

0.01

1,357,974

0.07

1,357,974

0.07

1,357,974

0.07

1,357,974

0.07

Outcome mean

Absolute outcome mean

Std. dev. of Great Recession local shocks

Interquartile range of G.R. local shocks

-7.23

79.1

1.49

2.31

-7.23

79.1

1.49

2.31

-7.23

79.1

1.49

2.31

-7.23

79.1

1.49

2.31

-7.23

79.1

1.49

2.31

-7.23

79.1

1.49

2.31

-7.23

79.1

1.49

2.44

B. Additional Outcomes and Controls

Cumulative

employment 2009Outcome relative to pre-2007 mean:

2015

Earnings in 2015

Cumulative

earnings 20092015

(pp)

(8)

($)

(9)

($)

(10)

(pp)

(11)

(pp)

(12)

(pp)

(13)

-2.700

(0.516)

-997

(168)

-6,212

(919)

-0.364

(0.100)

-0.480

(0.133)

-0.378

(0.112)

Rust CZ × Great Recession local shock

0.067

(0.192)

-0.035

(0.148)

Other CZ × Great Recession local shock

0.094

(0.250)

Great Recession local shock

Age-Earnings-Industry FEs

Manufacturing share

Outcome mean

Absolute outcome mean

Std. dev. of Great Recession local shocks

Interquartile range of G.R. local shocks

Employed in 2015

1,357,974

0.07

1,357,974

0.11

1,357,974

0.13

1,357,974

0.07

1,357,974

0.07

1,357,974

0.07

-40.5

563.9

1.49

2.31

6,249

47,587

1.49

2.31

27,646

317,011

1.49

2.31

-7.23

79.1

1.49

2.31

-7.23

79.1

1.49

2.31

-7.23

79.1

1.49

2.31

Notes – All columns except column 5 report coefficient estimates of the effect of Great Recession local shocks on post-recession outcomes in the main sample. Column 5 divides indviduals into

quintiles based on their Great Recession local shocks and reports coefficients on indicators of shock quintiles, relative to the least shocked quintile. Age fixed effects are birth year indicators.

Earnings fixed effects are indicators for sixteen bins in the individual's 2006 earnings. Industry fixed effects are indicators for the individual's 2006 four-digit NAICS industry. Local unemployment

persistence equals the 2015 LAUS unemployment rate minus the 2007 LAUS unemployment rate in either the individual's 2007 CZ or the individual's 2015 CZ. The columns-1-7 outcome is 2015

relative employment: the individual's 2015 employment (indicator for any employment in 2015) minus the individual's mean 1999-2006 employment. The column 8 outcome equals the sum of the

individual's 2009-2015 employment minus seven times the individual's mean 1999-2006 employment. The column 9 outcome equals the individual's 2015 earnings minus the individual's mean

1999-2006 earnings. The column 10 outcome equals the sum of the individual's 2009-2015 earnings minus seven times the individual's mean 1999-2006 earnings. Column 11 controls for the

2000 manufacturing share of employment in the individual's 2007 CZ, computed in County Business Patterns. Columns 11 and 12 control for indicators (not shown) and interactions of a rust-CZ

indicator and an other-CZ indicator, based on the individual's 2007 CZ. A rust CZ is a CZ with an above-median manufacturing share; an other CZ is a CZ with a below-median manufacturing

share and an above median 2006-2009 change in housing net worth from Mian and Sufi (2014). The coefficient for column 11 is -0.358 when controlling for a quartic in the manufacturing share.

The absolute outcome mean equals the outcome mean before subtracting the pre-recession mean. Standard errors are clustered by 2007 state. For reference, column 4 indicates that a 1percentage-point higher Great Recession local shock caused individuals to be 0.393 percentage points less likely to be employed in 2015.

TABLE 12

2015 Impacts of Great Recession Local Shocks ‒ Retail Chain Sample

A. Main Specifications

Outcome relative to pre-2007 mean:

Great Recession local shock

Employed in 2015

(pp)

(1)

(pp)

(2)

(pp)

(3)

(pp)

(4)

(pp)

(5)

-0.414

(0.118)

-0.426

(0.119)

-0.398

(0.102)

-0.407

(0.094)

-0.359

(0.080)

(pp)

(6)

Most severely shocked quintile

-1.496

(0.308)

Fourth shock quintile

-1.416

(0.298)

Third shock quintile

-0.968

(0.288)

Second shock quintile

-0.366

(0.298)

Age FEs

Age-Earnings FEs

Age-Earnings-Industry FEs

Age-Earnings-Firm FEs

Unemployment persistence in 2007 CZ

Unemployment persistence in 2015 CZ

(pp)

(7)

(pp)

(8)

-0.340

(0.063)

-0.339

(0.061)

865,954

0.00

865,954

0.00

865,954

0.02

865,954

0.03

865,954

0.07

865,954

0.15

865,954

0.15

865,954

0.15

Outcome mean

Absolute outcome mean

Std. dev. of Great Recession local shocks

Interquartile range of G.R. local shocks

-9.80

81.8

1.49

2.31

-9.80

81.8

1.49

2.31

-9.80

81.8

1.49

2.31

-9.80

81.8

1.49

2.31

-9.80

81.8

1.49

2.31

-9.80

81.8

1.49

2.31

-9.80

81.8

1.49

2.31

-9.80

81.8

1.49

2.44

Earnings in 2015

($)

(10)

Cumulative

earnings 20092015

($)

(11)

(pp)

(12)

Employed in 2015

(pp)

(13)

(pp)

(14)

-422

(134)

-2,777

(606)

-0.365

(0.081)

-0.589

(0.111)

-0.405

(0.095)

Rust CZ × Great Recession local shock

0.258

0.144

0.069

0.115

Other CZ × Great Recession local shock

0.414

0.251

B. Additional Outcomes and Controls

Cumulative

employment 2009Outcome relative to pre-2007 mean:

2015

(pp)

(9)

Great Recession local shock

Age-Earnings-Firm FEs

Manufacturing share

-2.504

(0.430)

865,954

0.15

865,954

0.21

865,954

0.23

865,954

0.15

865,954

0.15

865,954

0.15

Outcome mean

Absolute outcome mean

Std. dev. of Great Recession local shocks

Interquartile range of G.R. local shocks

-51.5

590.0

1.49

2.31

2,356

33,381

1.49

2.31

8,381

225,554

1.49

2.31

-9.80

81.8

1.49

2.31

-9.80

81.8

1.49

2.31

-9.80

81.8

1.49

2.31

Notes – This table replicates Table 11 in the retail chain sample. See the notes to that table for details. Firm is an indicator for the individual's 2006 firm (a retail chain firm).

TABLE 13

Robustness of the 2015 Employment Impacts

Outcome relative to pre-2007 mean:

Great Recession local shock

Main controls

Gender

Number of kids

Married

Home ownership

CZ size

CZ pre-2007 size growth

Cross-CZ commuting

Max UI duration 2007-2015

Minimum wage change 2007-2015

Employed in 2015

(pp)

(1)

(pp)

(2)

(pp)

(3)

(pp)

(4)

(pp)

(5)

(pp)

(6)

(pp)

(7)

(pp)

(8)

(pp)

(9)

(pp)

(10)

(pp)

(11)

(pp)

(12)

(pp)

(13)

-0.393

(0.097)

-0.394

(0.096)

-0.344

(0.090)

-0.344

(0.093)

-0.397

(0.098)

-0.439

(0.093)

-0.412

(0.098)

-0.381

(0.095)

-0.404

(0.095)

-0.399

(0.096)

-0.400

(0.115)

-0.397

(0.129)

-0.477

(0.125)

Exclude if invalid industry code

Exclude if construction/manufacturing

Instrumented with birth state shock

Outcome mean

Absolute outcome mean

Std. dev. of G.R. local shocks

Interquartile range of G.R. local shocks

1,357,974

(6)

1,357,974

0.08

1,357,974

(7)

1,357,974

0.08

1,357,974

(8)

1,357,974

0.07

1,357,974

0.07

1,357,974

0.07

1,357,974

0.07

1,357,974

0.07

741,165

0.11

579,553

0.10

1,357,974

0.07

-7.23

79.1

1.49

2.31

-7.23

79.1

1.49

2.31

-7.23

79.1

1.49

2.31

-7.23

79.1

1.49

2.31

-7.23

79.1

1.49

2.31

-7.23

79.1

1.49

2.31

-7.23

79.1

1.49

2.31

-7.23

79.1

1.49

2.31

-7.23

79.1

1.49

2.31

-7.23

79.1

1.49

2.31

-7.20

73.9

1.49

2.31

-6.69

70.8

1.49

2.31

-7.23

79.1

1.49

2.31

Notes – This table adds controls, sample restrictions, or instruments to the specification underlying Table 11 column 4, reprinted here in column 1. Column 2 controls for the individual's gender. Column 3 controls for the individual's 2006 number of kids

(fixed effets for 0, 1, or 2+ kids). Column 4 controls for the individual's 2006 marital status. Column 5 controls for individual's 2006 home ownership status. Colums 6-10 control for CZ-level characteristics. Column 6 controls for the individual's 2007 CZ's

size, equal to the CZ's total employment in 2006 as reported in Census's County Business Patterns (CBP). Column 7 controls for the individual's 2007 CZ's size growth, equal to the CZ's log change in CBP employment from 2000 to 2006. Column 8

controls for the individual's 2007 CZ's share of workers who work outside of the CZ, computed from the 2006-2010 American Community Surveys. Column 9 controls for the individual's 2007 state's maximum unemployment insurance duration over years

2007-2015. Column 10 controls for the individual’s 2007 state’s 2015 minimum wage minus that state’s 2007 minimum wage. Column 11 excludes 2006 W-2 earners without an industry code and 2006 contractors and thus restricts the sample to those for

whom 2006 industry is correctly measured: 2006 W-2 earners with a valid industry code and the 2006 nonemployed. Column 12 further excludes individuals employed in construction or manufacturing in 2006. Column 13 instruments the individual's Great

Recession local shock using the mean of the Great Recession local shock in the individual's birth state. Standard errors are clustered by 2007 state.

TABLE 14

Time Series of Adjustment Margins

Employed

Migrated

outside 2007

Employed in

2007 CZ

Employed

outside 2007

Earnings

Earnings in

2007 CZ

Earnings

outside 2007

(pp)

(1)

(pp)

(2)

(pp)

(3)

(pp)

(4)

UI income

SSDI income

($)

(5)

($)

(6)

($)

(7)

($)

(8)

($)

(9)

Effect in 2007

0.087

(0.106)

0.000

0.087

(0.106)

0.000

-205

(115)

-205

(115)

14.3

(12.2)

-3.8

(8.9)

Effect in 2008

-0.099

(0.079)

0.036

(0.119)

-0.098

(0.077)

-0.001

(0.006)

-508

(108)

-480

(108)

-28

(11)

36.3

(15.6)

-3.4

(9.4)

Effect in 2009

-0.349

(0.080)

0.109

(0.208)

-0.321

(0.077)

-0.028

(0.012)

-750

(129)

-687

(127)

-63

(18)

94.0

(32.1)

0.5

(11.8)

Effect in 2010

-0.403

(0.074)

0.209

(0.272)

-0.367

(0.074)

-0.037

(0.017)

-807

(131)

-736

(125)

-71

(30)

83.9

(32.1)

2.6

(13.0)

Effect in 2011

-0.387

(0.072)

0.248

(0.296)

-0.339

(0.071)

-0.048

(0.022)

-840

(119)

-745

(105)

-94

(35)

43.1

(24.3)

7.5

(13.7)

Effect in 2012

-0.373

(0.075)

0.244

(0.334)

-0.324

(0.076)

-0.049

(0.026)

-890

(141)

-784

(117)

-106

(45)

19.9

(20.1)

9.8

(15.2)

Effect in 2013

-0.434

(0.089)

0.180

(0.382)

-0.365

(0.091)

-0.069

(0.032)

-960

(147)

-810

(108)

-149

(56)

7.7

(16.3)

13.0

(17.0)

Effect in 2014

-0.360

(0.100)

0.134

(0.422)

-0.322

(0.101)

-0.038

(0.031)

-968

(197)

-799

(135)

-169

(84)

-3.0

(9.9)

15.7

(17.7)

Effect in 2015

-0.393

(0.097)

0.073

(0.456)

-0.338

(0.100)

-0.055

(0.042)

-997

(168)

-786

(108)

-211

(101)

-5.9

(8.9)

19.6

(18.8)

Outcome (relative or

absolute):

Notes – This table expands on the specifications of Table 11 column 4 and column 9, whose results are reprinted here in the bottom rows of columns 1 and 5. Each cell reports the

coefficient on the Great Recession local shock variable from a separate regression in which the outcome uses the post-recession year indicated in the row, instead of exclusively using

2015 as in Table 2. Every regression uses the same 1,357,974 observations underlying Table 2. The column 1 outcome of relative employment is defined in Table 2, varying the postrecession year between 2007 and 2015. The column 2 outcome is an indicator for out-migration, equal to the individual's year-t CZ being different from her 2007 CZ. Columns 3 and 4

separate the column 1 outcome for year t into two outcomes: employment in year t in the individual's 2007 CZ and employment in year t outside the individual's 2007 CZ, each minus

mean 1999-2006 employment. The column 5 outcome is defined in Table 2. Columns 7 and 8 separate the column 5 outcome analogously to columns 3-4. The column 8 outcome is

the individual's unemployment insurance benefits in year t . The column 9 outcome is the individual's Social Security Disability Insurance benefits in year t . Standard errors are

clustered by 2007 state. See Appendix Table 1 for pre-trends.

TABLE 15

Additional Outcomes

A. Disability Insurance Receipt in Main Sample

B. Employment Impacts in Mass Layoffs Sample

SSDI receipt in

2015

(pp)

(1)

2015 relative

employment-orSSDI-receipt

(pp)

(2)

2015 relative

employment

(pp)

(3)

2015 relative

employment

(pp)

(4)

2015 relative

employment

(pp)

(5)

Great Recession local shock

0.071

(0.145)

-0.265

(0.099)

-0.577

(0.126)

-0.628

(0.118)

-0.605

(0.125)

Main controls

Exclude if invalid industry code

Exclude if construction/manuf.

1,357,974

0.12

1,357,974

0.09

1,001,543

0.11

573,493

0.17

396,377

0.15

6.22

-2.28

84.06

-10.12

84.12

-10.45

83.11

-9.85

83.20

UI receipt sometime

2007-2014

2015 relative

employment-or-UIreceipt-sometime2007-2014

2015 relative

employment

Relative nonemployment 20072014

2015 relative

employment

2013-2015 relative

employment

(pp)

(6)

(pp)

(7)

(pp)

(8)

(pp)

(9)

(pp)

(10)

(pp)

(11)

1.431

(0.418)

-0.019

(0.121)

-0.354

(0.099)

0.487

(0.122)

-0.057

(0.111)

-0.285

(0.101)

Outcome:

Outcome mean

Absolute outcome mean

C. Layoffs and Nonemployment in Main Sample

Outcome:

Great Recession local shock

UI receipt sometime 2007-2014

Main controls

Employment 2007-2012

Outcome mean

Absolute outcome mean

-2.734

(0.142)

1,357,974

0.16

1,357,974

0.06

1,357,974

0.08

1,357,974

0.08

1,357,974

0.26

1,357,974

0.07

25.6

-2.8

83.6

-7.2

79.1

3.0

-7.2

79.1

-1.2

85.2

Notes – The table reports estimates of the specification in Table 11 column 4 with alternative outcomes, samples, and/or controls. Column 1 replicates the main

specification using the outcome of an indicator for 2015 receipt of Social Security Disability Insurance. Column 2 replicates the main specification using the outcome of

an indicator for 2015 employment or 2015 SSDI receipt, minus the individual's mean employment 1999-2006. Column 3 replicates the main specification and columns 45 replicate Table 13 columns 11-12 in the mass layoffs sample. Column 6 replicates the main specification using the outcome of an indicator for unemployment

insurance (UI) benefit receipt at some point 2007-2014. Column 7 replicates column 2 but uses UI receipt 2007-2014 in place of 2015 SSDI receipt. Column 8 replicates

the main specification, controlling for UI receipt sometime 2007-2014. Column 9 replicates the main specification using the outcome of an indicator for having any year of

nonemployment 2007-2014, minus an indicator for having any year of nonemployment 1999-2006. Column 10 replicates the main specification while controlling for

indicators of employment in each year 2007-2012. Column 11 replicates the main specification using the outcome of an indicator for employment in any year 2013-2015,

minus the individual's mean employment 1999-2006. Standard errors are clustered by 2007 state.

APPENDIX TABLE 1

Adjustment Margins Pre-Trends

Employed

Migrated

outside 2000

Employed in

2000 CZ

Employed

outside 2000

Earnings

Earnings in

2000 CZ

Earnings

outside 2000

(pp)

(1)

(pp)

(2)

(pp)

(3)

(pp)

(4)

UI income

SSDI income

($)

(5)

($)

(6)

($)

(7)

($)

(8)

($)

(9)

Effect in 2000

-0.036

(0.083)

0.000

-0.036

(0.083)

0.000

(66)

0.6

(6.2)

0.4

(3.9)

Effect in 2001

-0.094

(0.045)

-0.036

(0.166)

-0.093

(0.044)

-0.001

(0.003)

-74

(46)

-67

(42)

-7

(6)

10.6

(9.2)

0.3

(4.6)

Effect in 2002

-0.068

(0.018)

-0.047

(0.280)

-0.060

(0.017)

-0.008

(0.004)

-56

(26)

-47

(23)

-9

(5)

9.7

(15.4)

0.7

(5.4)

Effect in 2003

-0.044

(0.029)

-0.005

(0.361)

-0.036

(0.031)

-0.008

(0.007)

-26

(21)

-17

(20)

-10

(6)

10.2

(15.9)

0.6

(5.8)

Effect in 2004

0.031

(0.039)

0.077

(0.437)

0.030

(0.036)

0.001

(0.009)

(36)

(30)

-5

(12)

11.0

(11.9)

0.3

(6.6)

Effect in 2005

0.083

(0.061)

0.151

(0.526)

0.070

(0.053)

0.013

(0.010)

(66)

(57)

-1

(22)

6.8

(11.5)

-0.1

(7.3)

Effect in 2006

0.228

(0.135)

0.252

(0.612)

0.189

(0.116)

0.039

(0.020)

-15

(118)

(94)

-16

(36)

9.1

(13.1)

0.4

(9.1)

Outcome (relative or

absolute):

Notes – This table replicates Table 14 for years 2000-2006 and where each individual's Great Recession local shock equals the 2007-2009 percentage-point unemployment rate

change in the individual's 2000 CZ. See the notes to Table 14 for details.

APPENDIX TABLE 2

CZ-Level Means and Estimates

Mortgage

holding rate

Migration rate

2015

employment

rate

100

200

301

302

401

402

500

601

602

700

800

900

1001

1002

1100

1201

1202

1203

1204

1301

1302

1400

1500

1600

1701

1702

1800

1900

2000

2100

2200

2300

2400

2500

2600

2700

2800

2900

3001

3002

3003

3101

3102

3201

3202

3203

3300

3400

3500

3600

3700

3800

3901

4001

4002

4003

4102

4103

4200

4301

4302

4401

4402

4501

4502

4601

4602

4701

4702

4800

4901

4902

34.934

34.886

27.682

38.913

39.444

29.195

38.540

37.500

32.298

35.556

37.182

42.845

38.393

36.771

40.668

33.333

28.516

35.283

31.818

29.968

32.553

35.011

36.235

34.004

41.714

30.405

32.075

38.431

39.601

33.276

33.183

37.132

40.964

37.074

29.131

35.963

27.613

33.982

27.545

26.531

37.332

32.553

33.516

35.294

27.155

30.383

36.196

33.655

37.803

30.160

31.339

31.074

32.692

32.558

31.515

27.036

28.892

30.000

38.292

30.612

37.118

31.838

35.889

25.126

24.839

37.875

34.266

24.924

29.250

23.395

36.588

35.501

11.180

17.443

9.343

15.027

15.229

15.862

14.953

16.327

22.671

16.167

16.242

17.138

25.000

16.147

17.109

23.188

20.703

19.686

21.970

14.196

15.603

23.210

19.369

13.894

16.850

15.878

19.707

23.098

22.794

21.160

16.066

15.625

14.919

23.694

15.332

18.469

17.160

21.401

19.760

20.408

13.416

16.159

20.330

17.647

17.241

20.649

14.145

12.824

13.533

15.615

16.451

11.211

14.194

14.729

15.557

20.847

22.754

17.714

16.159

23.129

23.362

10.999

17.129

15.578

10.921

12.807

10.490

14.286

17.733

23.602

19.206

18.428

75.990

73.158

65.398

77.826

79.646

74.943

79.081

70.918

77.329

74.333

76.690

80.479

74.405

72.049

79.003

71.015

74.219

75.416

72.727

71.609

75.638

74.730

76.659

79.250

80.467

78.378

77.149

77.569

81.098

76.792

78.529

81.526

81.558

81.328

79.557

74.896

73.373

74.838

76.048

70.068

79.372

77.752

73.077

70.588

64.655

74.041

76.507

73.907

78.179

75.401

77.702

74.549

79.945

75.969

78.811

77.199

75.749

79.143

78.734

78.912

72.489

65.991

73.083

61.307

57.602

74.659

67.133

75.684

75.868

74.741

76.824

77.778

2015 mean

earnings

Residualized

shock

Employment

effect

33,701.93

30,354.65

26,237.57

41,178.64

41,551.73

29,813.81

38,866.46

25,289.45

27,103.95

33,756.25

36,041.41

50,136.20

36,232.13

29,371.88

38,007.98

31,773.86

28,322.27

35,401.41

30,493.29

28,407.33

31,431.28

33,138.24

38,650.96

33,887.00

51,477.81

30,266.29

34,604.89

36,087.00

43,301.13

31,021.75

28,581.81

38,249.03

48,695.93

42,796.29

29,324.41

35,246.99

33,179.74

36,895.31

28,728.07

24,490.89

40,242.86

36,948.13

31,640.96

38,192.68

23,403.13

31,708.43

44,511.75

40,941.56

44,732.08

32,976.11

39,078.48

39,676.41

36,072.76

36,195.82

36,859.53

35,118.54

34,151.31

34,774.08

43,187.26

30,270.42

33,534.48

27,415.66

32,517.84

23,662.71

22,266.31

27,777.81

25,412.81

30,100.32

31,403.92

27,854.33

33,095.92

33,433.75

5.40

7.00

5.89

5.17

5.52

7.89

6.11

7.00

5.23

6.67

8.39

6.45

5.11

7.87

8.01

6.08

5.78

5.07

6.86

7.79

6.12

4.67

5.95

6.80

4.83

6.90

4.58

5.07

3.75

5.31

4.94

4.07

4.43

3.85

5.85

2.80

3.55

2.99

7.04

4.08

2.59

3.94

3.89

3.72

3.80

3.77

2.88

2.36

2.46

2.45

2.53

2.75

3.20

3.08

2.71

2.98

2.70

2.68

2.30

4.95

2.16

4.67

4.71

3.96

3.27

5.19

5.83

4.76

3.92

3.95

6.24

9.20

-2.71

-2.82

-4.93

-1.37

0.24

-4.01

-0.64

-5.44

0.55

-5.08

-3.18

0.26

-2.94

-4.08

-1.19

-1.91

-3.25

-2.52

-3.16

-6.00

-3.14

-4.11

-0.79

-1.21

0.53

-2.04

-1.34

-1.81

-0.78

0.42

-1.64

-0.18

-0.47

-0.14

0.06

-3.05

-4.16

-3.03

-1.26

-8.58

-1.18

-1.50

-2.18

-7.74

-7.47

-4.54

-0.98

-4.10

-1.83

-1.61

-0.18

-2.25

0.80

-4.82

-1.81

-0.10

-4.99

-1.59

-2.30

0.13

-4.41

-5.26

-3.55

-7.90

-9.67

0.64

-7.31

-0.70

-2.09

-1.73

-1.83

-0.34

Percentage

Earnings effect earnings effect

-1591.9

-2221.3

-1881.4

-657.3

623.5

-3451.4

-1827.0

-5864.3

-1736.3

-3825.5

-2816.9

-1132.8

554.7

-1664.6

-5004.3

-2063.0

-3591.5

-2325.0

-1649.6

-3074.3

-3958.3

-2615.3

-1116.1

-3969.3

-324.3

-3890.4

502.3

-1790.5

234.8

-3068.8

-3550.5

-318.1

-1015.6

1679.7

-1139.5

-731.3

1902.1

638.2

2494.9

-2629.7

-197.6

2065.7

-1773.8

-57.2

-1798.1

-2359.5

3162.0

2170.1

1706.8

-1322.5

1740.7

1705.1

1071.0

-1569.8

535.5

1019.9

-1071.9

1462.7

-70.8

1714.2

194.9

-2112.8

-1961.5

-1740.9

-6198.2

-931.0

-1982.7

296.8

-2282.9

-783.9

-3990.1

-670.8

-15.24

-26.17

-20.72

-12.31

1.16

-40.07

-18.08

-47.67

-15.64

-38.32

-28.99

-12.76

-25.93

-14.79

-22.45

32.57

-38.70

-13.37

-17.86

-47.81

-37.34

-29.12

-14.07

-25.98

-5.85

-43.70

-10.96

-16.83

-8.97

-25.81

-31.68

-18.81

-4.34

4.77

-42.83

-33.50

-39.36

-10.36

35.29

-27.48

-18.24

-28.69

-51.62

-10.19

-49.10

-32.40

-1.67

-4.49

-2.76

-12.35

-1.97

-15.50

-1.50

-19.00

-11.40

-12.34

-21.90

-19.80

-13.91

17.58

-18.74

-32.49

-23.53

-26.67

-66.19

-9.16

-53.67

-14.68

-56.91

-19.95

-37.92

18.62

Alternative

employment

effect

-1.82

-2.32

-5.82

-0.52

-0.20

-2.08

0.50

-3.65

2.65

-3.44

-1.92

0.88

-3.25

-3.14

0.45

-2.87

-1.27

-1.56

-3.02

-4.93

-1.25

-3.35

-0.46

0.52

0.34

1.69

-0.82

-0.36

0.79

1.10

1.53

2.33

0.70

0.98

2.54

-1.54

-1.98

-2.36

-0.44

-5.33

-0.07

0.88

-3.56

-3.50

-7.96

-3.11

0.35

-4.13

-0.86

-1.03

0.88

-2.24

2.61

-2.25

0.50

1.52

-3.06

1.10

-1.27

2.15

-4.31

-7.07

-2.71

-8.73

-14.35

-0.50

-6.43

-0.48

-0.93

-0.96

0.04

1.81

Alternative

earnings effect

Percentage

earnings

change

Alternative

percentage

earnings

change

-2538.5

-4818.1

-3395.6

-1034.4

-410.6

-4115.2

-1554.1

-5971.3

-2621.1

-3730.8

-2719.5

-597.0

-2469.0

-2489.4

-4483.7

70.5

-6932.9

-2550.8

-7164.8

-3886.1

-4603.0

-4032.5

-2405.8

-5318.1

225.8

-3298.0

-2148.3

-2728.0

-239.9

-3525.1

-3801.8

391.3

-887.5

402.8

-2633.4

-3158.8

532.1

-1587.3

-112.5

-4402.8

-1389.9

425.3

-6881.0

-2586.2

-5945.3

-2599.8

2419.8

-417.2

399.8

-3798.5

564.0

-1649.9

-160.0

856.6

-541.4

-1100.7

-2105.4

551.6

-839.0

834.6

-1567.1

-4019.3

-1748.0

-5859.9

-10238.8

-3874.6

-3755.1

-1493.0

-3596.1

-3207.4

-4643.3

-2676.3

11.15

5.69

10.75

12.73

14.45

0.42

7.96

-8.07

2.68

0.62

4.55

12.91

16.90

5.38

-1.03

6.42

0.57

8.54

7.35

4.00

1.67

8.09

11.39

2.01

14.84

-2.82

12.90

9.96

15.90

2.79

1.37

12.44

12.09

19.64

9.82

11.21

18.81

19.05

24.91

7.73

15.91

25.43

11.47

36.43

5.33

5.59

23.23

27.34

22.41

14.99

25.14

23.36

19.94

10.08

16.98

22.16

10.43

17.24

16.69

21.73

14.12

7.38

7.10

9.94

-11.24

10.52

5.70

14.14

10.21

15.02

2.83

9.38

1.61

-7.39

5.81

1.66

2.18

-5.67

1.04

-11.62

-0.61

-4.11

-1.98

1.79

-1.95

0.33

-7.50

8.16

-12.63

0.79

-15.04

-2.64

-5.91

-3.46

-0.68

-7.50

4.45

-4.13

-1.41

-0.98

3.59

-3.57

-4.90

6.59

0.64

5.59

1.70

-2.93

9.81

2.86

9.07

-2.80

1.51

10.87

-9.66

22.77

-9.79

-1.62

11.60

7.23

7.93

0.06

12.10

2.57

8.60

8.00

5.56

9.08

1.06

9.21

3.94

13.18

2.45

-1.00

2.24

-1.86

-23.29

-3.71

-2.64

4.91

-1.22

1.04

-5.93

-0.80

Mortgage

holding rate

Migration rate

2015

employment

rate

4903

5000

5100

5201

5202

5300

5401

5402

5500

5600

5700

5800

5900

6000

6100

6200

6301

6302

6401

6402

6501

6502

6600

6700

6800

6900

7000

7100

7200

7300

7400

7500

7600

7700

7800

7900

8000

8100

8201

8202

8300

8401

8402

8501

8502

8503

8601

8602

8701

8702

8800

8900

9001

9002

9003

9100

9200

9301

9302

9400

9500

9600

9701

9702

9800

9900

10000

10101

10102

10200

10301

10302

10400

10501

35.784

35.467

30.074

33.579

39.591

30.189

36.173

34.500

40.297

41.731

38.411

37.316

36.513

40.861

33.333

38.728

37.270

31.858

38.754

39.858

41.232

35.067

35.465

40.842

34.484

39.221

39.644

42.150

42.173

41.617

39.066

38.638

39.154

34.059

36.584

36.162

32.135

37.261

28.912

38.603

37.091

37.859

32.558

25.532

34.706

31.339

30.377

33.608

30.698

31.360

37.495

38.069

33.474

35.714

34.718

42.975

34.801

36.878

33.172

42.405

32.964

39.586

33.193

23.954

35.169

36.279

33.501

41.860

36.727

30.931

33.478

36.904

32.689

34.442

15.686

14.690

16.605

19.188

15.846

19.623

13.893

16.250

21.918

16.496

18.046

18.879

27.443

13.426

15.499

12.254

20.472

19.027

13.420

16.745

31.754

14.258

17.801

20.063

27.180

24.275

19.413

22.702

25.459

22.531

23.695

26.057

20.906

25.972

27.764

25.240

20.507

17.266

20.748

16.591

12.715

16.718

27.907

26.950

16.471

20.804

15.849

25.155

33.023

17.325

25.143

17.359

17.684

25.000

15.727

18.210

18.324

22.700

17.676

22.468

18.542

19.695

25.140

17.490

22.881

22.584

30.080

16.279

17.455

21.625

19.565

18.722

16.048

19.240

72.549

76.705

67.159

71.956

80.196

74.528

77.064

73.750

78.653

79.046

75.662

77.876

76.779

77.417

70.984

75.023

73.491

74.336

77.676

74.057

69.194

75.915

74.931

77.387

75.581

75.574

77.249

75.983

77.150

76.806

78.741

75.376

78.022

74.650

74.224

77.491

75.793

79.674

73.810

78.260

77.001

78.976

79.070

65.957

76.471

75.268

76.038

78.557

74.264

77.412

76.835

76.538

74.526

73.512

76.855

78.734

75.284

77.046

75.303

77.468

72.742

77.335

77.941

73.384

78.672

78.553

75.151

79.070

80.727

78.506

75.217

77.048

76.969

74.822

2015 mean

earnings

Residualized

shock

Employment

effect

27,682.08

31,395.51

28,334.61

24,757.23

44,354.85

29,662.44

36,519.85

27,900.85

36,820.51

48,502.11

36,493.19

33,576.88

34,999.20

44,164.83

32,561.95

35,061.51

27,196.21

30,036.58

39,045.11

29,198.58

30,626.30

34,256.91

34,227.23

42,864.31

35,027.02

36,626.19

45,736.25

45,125.02

39,133.72

39,151.82

42,679.62

33,584.33

42,894.50

29,565.97

33,442.63

39,718.42

29,966.48

39,847.69

30,165.19

42,701.80

39,220.38

39,853.57

26,846.72

28,208.89

30,271.05

32,280.52

31,114.41

39,709.49

31,869.78

34,019.50

39,928.45

38,110.86

29,782.13

29,189.41

28,726.88

51,480.12

29,994.22

37,193.19

31,255.36

38,889.12

32,117.41

38,690.89

36,843.93

25,104.18

39,826.19

40,929.33

35,390.84

31,056.86

37,084.83

35,142.19

27,868.26

36,136.02

33,414.28

30,611.29

10.67

4.15

5.97

5.44

4.90

2.66

6.03

6.70

7.24

5.23

6.39

7.45

5.12

5.71

7.52

6.77

7.49

5.54

5.36

6.67

7.17

7.03

6.50

6.44

6.78

6.36

7.07

6.14

6.45

6.69

5.94

5.62

7.58

4.58

5.46

4.46

7.69

4.96

5.35

3.98

5.61

8.54

5.79

5.22

6.92

5.16

4.14

5.83

4.66

4.25

5.37

6.93

6.57

5.31

7.49

4.53

6.29

5.99

8.76

6.92

4.55

5.54

5.86

4.18

5.34

5.84

5.25

4.62

6.18

5.72

3.69

4.62

-4.02

-1.94

-7.01

-4.51

-0.74

-2.12

-2.81

-4.02

-1.47

-0.89

-4.50

-1.87

-2.54

-3.15

-6.24

-1.42

-3.24

-4.17

-1.91

-2.87

-3.12

-1.64

-1.92

-1.39

-2.13

-1.92

1.94

0.09

0.02

-1.77

0.04

-2.97

-2.45

-4.01

-2.43

-0.65

-3.44

-1.26

-2.69

-1.02

-2.12

-1.12

1.59

-5.02

-8.42

-3.33

0.97

0.17

-4.73

-0.85

-0.94

-3.81

-3.11

-6.22

-0.29

0.32

-1.51

-0.84

-2.34

-0.86

-5.82

-2.57

-2.12

-3.05

0.20

-1.93

-2.58

-1.13

4.73

-1.76

-1.56

-2.33

-2.87

-2.14

Percentage

Earnings effect earnings effect

-5289.3

-4389.2

-1600.5

-3778.9

-1606.4

-2594.3

-2733.8

-2901.1

-2528.4

390.3

-1169.3

-2092.8

983.4

-1621.1

-1813.9

297.2

-3407.3

-4276.7

-441.2

-2875.3

-4800.2

-1992.0

-2299.1

-1684.6

-648.4

-4095.6

241.0

-1290.0

-2553.9

-2757.9

-1340.9

-3381.2

-1294.7

-3702.2

-3756.0

2473.7

-3725.9

-1272.4

-1580.8

336.9

-1003.5

732.3

-2913.9

-1425.8

-3779.6

-1274.3

905.2

946.6

-1391.9

403.0

-2076.0

-2588.8

-3893.7

-5322.6

-1944.4

-1631.1

-3046.5

-1586.9

-4095.0

-4716.9

-2747.8

-2247.7

-618.4

-5135.2

1628.9

198.1

1437.9

-3791.7

723.4

-2092.9

-2693.1

-184.9

1246.0

-2551.6

-51.54

-31.06

-53.84

-32.51

-17.81

-39.09

-12.16

-27.25

-18.42

-2.86

-35.66

-23.60

-4.03

-11.93

-36.07

0.75

-49.76

-46.93

-21.29

-36.95

-36.34

-21.65

-15.06

-14.22

-10.72

-20.19

12.97

5.83

-9.50

-15.61

-3.40

-28.41

-10.10

-35.42

-23.12

4.14

-32.31

-19.90

-13.03

-10.47

-19.51

-7.64

-21.12

-43.83

-73.68

-17.47

5.50

-4.12

-18.17

-21.61

-17.08

-22.01

-24.90

-51.24

-37.57

-2.49

-31.85

-3.70

-34.28

-11.03

-36.60

-18.51

-14.84

-27.72

-17.22

-10.87

-9.44

-8.18

11.74

-23.76

-33.33

-10.29

5.53

-23.70

Alternative

employment

effect

-3.77

-0.77

-7.98

-4.03

0.36

-2.01

-1.36

-1.79

0.69

-0.39

-3.05

0.24

-0.94

-2.03

-5.12

-1.71

-1.96

-2.09

-0.52

-0.16

-4.34

-1.00

-2.19

-0.75

-1.68

-1.35

-1.10

-1.12

-0.80

-1.04

-0.07

-1.49

-1.15

-1.90

-2.17

0.52

-1.80

0.46

-1.75

-0.12

-0.71

0.83

4.10

-5.37

-2.23

-2.02

0.61

2.44

-3.77

1.49

-1.14

-2.73

-2.75

-4.66

0.18

-0.62

-1.72

-0.83

-1.93

-0.01

-4.66

-1.42

-0.98

-1.97

-0.44

-0.67

-1.99

2.25

3.76

0.47

0.92

-1.16

-1.67

-0.45

Alternative

earnings effect

Percentage

earnings

change

Alternative

percentage

earnings

change

-5324.3

-5455.8

-3266.6

-3536.2

-2452.1

-5553.5

-2981.6

-3671.2

-1760.9

127.1

-1765.6

-823.0

1124.5

-1813.2

-3295.4

-1276.0

-3921.7

-3801.8

-806.3

-3774.2

-4210.6

-2167.6

-2751.2

-1702.0

-1914.8

-4967.8

-1332.2

-1919.5

-4221.3

-2618.6

-2180.9

-4008.9

-1497.1

-5350.5

-5558.1

1019.7

-4031.0

-1499.7

-1836.9

-499.0

-378.9

967.9

-4048.1

-29.5

-4168.1

-3107.9

155.2

-2411.7

-3798.0

-1310.3

-2837.3

-2506.0

-4220.3

-6686.5

-3604.3

-1184.9

-3474.2

-1193.6

-4927.3

-4031.3

-5067.4

-2038.6

-1886.8

-4071.8

-1370.7

-707.9

-215.3

-2882.8

-4129.4

-3938.6

-854.9

-2106.5

-448.6

-4259.9

-8.44

1.19

11.06

-6.77

12.58

7.99

5.42

2.31

6.07

15.00

6.62

7.38

17.18

10.62

6.89

16.14

-0.01

1.81

13.18

3.40

-0.55

6.51

5.98

11.02

12.27

1.33

16.27

9.27

5.74

5.29

11.55

2.35

12.31

0.62

0.66

21.90

1.83

10.87

9.02

16.00

11.11

16.48

1.06

13.79

5.80

13.90

19.13

18.16

11.29

15.15

9.15

10.04

3.57

-2.34

5.77

12.29

4.62

11.17

2.12

2.36

4.28

8.12

14.03

-4.56

19.45

15.11

18.41

1.56

17.40

9.15

-2.00

13.43

20.16

7.25

-12.78

-8.51

2.74

-7.89

0.53

-7.98

-1.92

-3.53

0.43

3.09

-2.54

5.41

12.35

0.04

-3.77

4.00

-1.86

-1.39

3.91

-2.68

-4.75

-0.73

-1.67

1.17

1.18

-8.04

1.09

-1.11

-8.48

-2.32

-0.85

-6.06

1.35

-7.05

-10.07

9.06

-3.27

1.62

3.07

2.93

4.93

9.16

-1.10

21.71

-2.45

1.58

13.16

0.22

-1.79

3.25

-2.00

1.21

-4.13

-12.61

-3.98

1.51

-1.45

3.72

-6.42

-5.40

-9.23

1.41

3.58

-4.64

1.13

3.55

4.97

-4.11

-3.25

-2.05

1.39

0.10

7.20

-4.50

Mortgage

holding rate

Migration rate

2015

employment

rate

10502

10600

10700

10801

10802

10900

11001

11002

11101

11102

11201

11202

11203

11301

11302

11303

11304

11401

11402

11403

11500

11600

11700

11800

11900

12001

12002

12100

12200

12301

12302

12401

12402

12501

12502

12600

12701

12702

12800

12901

12902

12903

13000

13101

13102

13103

13200

13300

13400

13501

13502

13600

13700

13800

13900

14000

14100

14200

14300

14400

14500

14600

14700

14801

14802

14900

15000

15100

15200

15300

15400

15500

15600

15700

31.510

30.962

39.256

34.297

27.530

38.033

36.911

31.579

41.366

33.058

31.442

23.718

28.804

46.318

41.253

38.550

42.563

42.750

47.566

40.876

42.461

42.872

42.768

42.439

40.529

35.496

36.614

41.639

43.085

44.118

40.686

37.640

40.652

39.598

37.011

38.320

40.631

32.028

40.746

40.021

37.295

39.152

37.909

40.903

35.443

41.311

35.315

39.415

41.838

40.479

43.532

39.362

39.496

38.710

40.276

37.907

41.587

41.141

36.023

38.047

34.431

38.876

38.638

37.917

32.609

38.544

37.876

41.566

39.641

35.054

37.868

32.616

33.412

31.002

20.573

16.597

14.791

17.751

17.814

26.096

14.132

15.205

17.324

18.733

14.303

17.949

13.043

23.981

15.114

19.847

17.420

16.761

14.607

15.328

16.565

12.009

17.599

17.724

15.312

21.947

19.685

17.140

12.147

16.880

17.647

14.888

25.870

14.845

22.776

16.393

12.659

15.658

15.746

16.580

16.393

18.454

23.337

10.887

17.300

15.100

13.054

14.534

12.361

14.563

13.963

16.363

18.718

16.897

17.491

15.964

14.885

16.030

16.250

16.667

16.129

15.613

11.744

17.917

14.783

15.097

13.357

14.273

12.719

10.860

13.605

13.079

11.806

14.367

77.083

74.477

76.670

74.779

70.040

75.274

76.447

75.731

76.069

76.033

70.095

57.692

62.228

82.349

81.270

76.336

81.335

77.966

83.146

79.197

80.257

79.137

80.617

78.537

79.321

74.618

78.346

80.017

80.877

78.645

78.922

77.809

75.652

81.312

76.868

79.713

81.648

71.530

80.387

78.318

71.721

77.307

75.924

81.593

80.591

83.191

76.573

81.359

84.628

80.192

83.573

80.644

79.565

81.413

80.667

79.818

82.575

81.502

78.523

78.788

81.501

80.952

82.461

83.333

80.870

80.475

81.107

82.103

81.659

78.280

78.005

78.974

79.103

74.480

2015 mean

earnings

Residualized

shock

Employment

effect

32,462.92

34,065.88

44,814.62

36,217.16

32,492.85

37,967.34

38,666.05

32,421.69

38,374.89

35,671.13

29,157.96

24,396.40

25,074.79

53,969.89

55,916.95

33,925.67

68,761.66

38,333.91

37,709.17

30,036.13

39,369.83

48,384.06

46,329.87

35,985.63

40,067.65

30,039.08

32,231.07

42,337.05

43,338.17

36,593.87

33,029.91

32,137.51

29,842.35

41,643.80

32,996.98

34,386.66

49,173.90

28,424.43

37,613.20

40,675.92

26,141.22

34,444.48

32,491.31

44,693.30

32,861.86

35,078.72

35,321.15

36,246.71

40,320.62

42,329.57

36,799.56

39,810.83

34,917.42

35,790.78

37,579.37

36,053.67

41,560.23

47,936.72

35,866.56

35,551.44

37,571.59

38,292.43

40,925.12

34,775.89

31,890.20

44,052.99

39,545.37

42,431.08

46,656.14

35,749.11

31,895.07

34,201.91

37,115.25

33,093.01

4.22

8.97

6.51

7.88

8.09

5.13

7.20

10.07

6.59

6.09

3.85

4.09

3.00

3.40

3.82

4.11

3.06

4.29

5.37

3.90

6.68

7.27

4.93

4.49

5.37

6.71

5.03

4.92

5.83

5.37

4.91

6.45

5.80

5.50

8.23

6.89

4.48

6.14

5.51

4.52

6.90

5.76

5.70

4.76

6.11

6.91

4.53

6.25

5.76

6.23

8.67

6.38

10.87

7.73

8.10

5.39

6.49

4.60

6.63

5.26

5.62

3.78

4.05

4.72

4.00

5.42

5.56

4.62

3.67

4.48

5.47

5.61

3.75

4.97

0.69

-4.41

-2.43

-4.68

-6.31

-2.88

-2.15

1.29

-2.86

-2.62

-2.89

-5.13

-9.96

-0.81

0.04

-3.59

0.58

-2.63

2.67

0.80

-0.74

-0.59

-1.59

-0.12

-1.33

-1.11

-0.25

-0.60

0.19

-1.63

-0.06

-2.52

-2.25

-0.67

-3.17

-2.08

0.14

-4.96

-1.14

-1.16

-5.22

-1.09

-3.16

0.45

1.87

1.95

-1.59

-1.35

0.92

-2.26

1.34

0.75

-0.08

-0.43

-0.18

-1.61

0.53

0.41

-3.08

-2.37

1.75

0.42

1.13

1.12

0.82

0.02

0.37

-1.25

0.52

-0.17

-2.35

-1.32

-0.30

-4.11

Percentage

Earnings effect earnings effect

-950.3

-1842.7

122.1

-3070.2

-467.6

706.0

9.0

44.1

-1667.0

1860.4

-904.4

-2353.8

-4940.2

-292.8

1881.4

-5589.5

3015.2

501.7

-1892.8

-4663.8

-2871.5

-2487.3

-540.5

1243.6

-2153.5

-1373.4

-3904.5

-1805.5

-2127.6

-3654.7

-1558.7

-589.3

-2245.3

-1929.4

-2795.0

-3223.5

-280.5

-3915.9

-2582.6

-2399.5

-4337.5

-1820.8

-2325.1

590.6

-3962.5

-307.8

-487.0

-3652.8

-149.9

-2073.3

-2386.2

-1512.3

-4068.6

-3142.9

-4950.5

-2135.1

-1387.3

-1282.1

-4429.2

-3130.4

-989.6

304.1

-1318.4

-2571.5

-1000.1

-1911.3

497.8

-1956.9

43.2

505.3

-822.8

77.8

2600.5

-1635.2

9.19

-32.20

-12.39

-30.60

-35.39

-18.01

-18.63

-15.37

-16.70

-18.32

-45.30

-58.87

-66.65

-6.52

5.72

-36.46

12.38

-29.96

-7.00

4.71

-8.38

-4.43

-14.79

-14.00

-13.05

-12.71

-19.52

-8.64

-5.20

-12.78

0.24

-11.97

6.48

-7.36

-13.91

-23.26

-4.66

-46.24

-8.17

-14.66

-25.56

-14.31

-19.38

-7.12

-33.57

-15.53

-11.85

-17.84

-8.09

-15.57

-4.37

-3.56

-12.63

-29.48

-15.13

-12.71

-14.88

-7.45

-1.88

-7.80

-8.06

-1.85

-15.49

-23.01

-16.68

-3.07

-1.10

-16.18

4.15

-2.24

-12.28

-1.65

12.56

-25.43

Alternative

employment

effect

1.38

-2.94

-2.14

-4.61

-5.85

-2.05

-1.22

0.76

-2.47

-1.51

-3.75

-13.56

-11.32

-0.23

0.50

-1.29

-0.70

0.50

5.85

0.75

1.26

-0.03

1.06

1.93

1.59

0.33

1.56

1.00

1.89

1.36

2.59

1.21

0.22

1.09

-1.89

-0.74

1.56

-3.19

0.38

-0.33

-4.03

-0.53

-0.87

2.02

2.11

3.84

-1.08

1.35

4.08

-0.06

3.79

2.32

0.99

1.56

0.91

2.53

1.45

-1.11

-0.14

2.60

1.97

3.17

5.22

3.22

0.72

2.78

2.01

1.23

0.29

1.87

1.44

-2.64

Alternative

earnings effect

Percentage

earnings

change

Alternative

percentage

earnings

change

-1907.3

-2849.4

-1180.8

-4579.1

-2657.7

-133.2

-1717.5

-2149.1

-3603.5

784.3

-2940.4

-6499.7

-6597.2

-275.8

2369.2

-5892.9

3044.1

391.6

-227.9

-5569.6

-1336.8

492.6

1386.5

1742.5

-818.7

-454.2

-2535.7

209.1

310.1

-1909.5

910.0

123.4

-1988.7

-1064.1

-1942.4

-2060.6

1156.4

-4941.6

-1756.4

-1698.9

-4500.1

-1597.3

-2573.4

1136.4

-2682.1

-631.6

-1721.9

-2995.9

940.2

-536.9

-1599.1

-734.5

-3259.1

-1007.5

-2969.1

-1514.1

-140.4

165.5

-4143.4

-2727.5

-997.7

280.2

-867.5

-3516.8

-842.8

-1290.7

1257.6

17.8

1052.2

-255.8

-1023.1

-919.1

2680.4

-2417.8

14.78

6.02

15.29

10.28

12.28

16.44

15.95

11.35

11.22

21.15

11.94

17.93

-1.94

16.06

18.69

-2.83

22.40

14.18

7.34

-0.93

6.27

7.50

10.65

15.80

9.14

8.27

-0.57

10.06

6.90

1.30

6.34

8.52

3.24

9.16

-0.11

4.47

13.84

3.95

4.85

9.58

0.20

4.94

6.90

15.44

5.13

10.98

15.49

3.03

12.62

7.49

3.61

9.40

1.49

1.71

-0.24

6.18

7.87

12.03

4.92

5.60

11.51

15.30

10.61

8.08

9.25

10.72

15.88

7.86

14.46

15.62

11.36

13.19

22.74

9.75

5.47

-3.86

1.31

-4.18

-0.03

6.69

3.13

-0.39

-2.54

8.45

0.19

-1.27

-11.68

0.87

6.01

-11.03

5.84

6.79

5.20

-10.81

1.70

4.73

6.93

12.93

5.77

8.80

-2.59

5.92

4.11

-1.18

8.71

8.30

2.09

2.08

-4.43

-0.12

5.91

-4.93

-0.79

1.95

-3.35

-1.65

1.27

7.26

0.05

3.34

4.72

-3.11

6.48

2.69

-0.33

2.99

-2.63

1.67

-2.97

1.08

3.09

4.38

-2.59

-0.09

5.28

7.45

3.01

-1.63

1.83

1.09

10.46

3.97

6.54

7.13

5.91

4.11

16.67

2.05

Mortgage

holding rate

Migration rate

2015

employment

rate

15800

15900

16000

16100

16200

16300

16400

16500

16600

16701

16702

16703

16801

16802

16901

17000

17100

17200

17300

17400

17501

17502

17600

17700

17800

17900

18000

18100

18201

18202

18300

18400

18500

18600

18700

18800

18900

19000

19100

19200

19300

19400

19500

19600

19700

19800

19901

19902

19903

20001

20002

20003

20100

20200

20301

20302

20401

20500

20600

20700

20800

20901

20902

21001

21002

21003

21004

21101

21102

21201

21202

21301

21302

21400

32.215

40.866

37.961

38.006

35.383

38.599

38.474

36.225

37.840

38.676

34.904

31.282

33.535

31.606

34.485

26.821

32.747

37.288

35.231

40.633

36.530

42.346

40.834

37.284

33.585

35.841

38.199

34.334

33.333

39.474

35.097

33.530

32.024

37.273

38.065

39.846

39.961

42.817

41.584

42.009

39.910

28.494

42.769

35.709

40.691

44.621

37.742

40.746

22.170

39.921

35.507

38.965

40.870

41.180

38.153

38.045

38.849

38.067

43.137

39.966

37.254

40.339

38.015

48.205

48.447

34.711

43.478

37.900

44.040

44.054

46.914

38.796

49.429

47.765

20.638

14.455

13.950

15.442

8.091

8.954

13.035

11.580

14.004

15.679

12.827

12.308

15.559

13.990

12.824

13.064

13.802

17.175

14.930

14.713

11.989

20.172

20.781

10.576

14.221

13.274

8.810

15.085

13.589

10.526

16.435

12.633

16.306

10.987

12.814

12.825

12.963

14.680

11.752

12.381

15.969

14.140

13.494

14.708

11.050

16.376

15.880

17.177

21.226

16.008

21.014

10.627

13.442

13.129

17.068

18.776

12.144

11.386

13.402

17.538

13.489

11.429

11.864

17.436

19.255

16.529

19.732

16.895

21.523

20.541

17.284

15.826

20.555

17.208

72.819

81.783

78.739

82.534

80.259

81.529

80.928

80.159

78.929

75.958

77.400

75.385

72.961

67.358

74.485

58.497

74.089

80.000

79.699

80.411

78.279

80.973

79.947

81.263

78.064

79.204

81.499

80.478

78.746

81.579

78.180

77.804

78.782

82.141

81.281

79.596

82.261

82.276

83.203

83.221

80.202

76.188

77.856

77.769

79.770

82.037

79.275

79.893

76.887

77.734

71.015

74.114

80.212

82.649

79.518

82.208

80.308

80.904

82.962

78.921

80.146

80.111

80.387

80.000

73.913

80.992

80.602

81.963

84.768

88.649

90.123

86.835

86.460

84.323

2015 mean

earnings

Residualized

shock

Employment

effect

32,308.16

49,815.99

35,153.76

39,935.55

36,870.85

47,702.74

37,208.84

37,011.35

39,852.07

32,570.34

39,565.65

35,003.46

33,056.14

29,945.66

38,293.74

24,573.80

35,329.57

35,162.60

33,746.66

41,157.79

37,055.87

45,346.01

48,162.00

41,632.20

35,468.00

37,871.50

43,790.28

39,134.10

32,308.81

36,476.57

35,937.45

36,069.51

34,263.06

47,161.57

40,410.16

41,088.18

36,751.02

48,163.76

44,834.45

45,537.26

51,091.10

59,504.25

56,571.34

62,417.45

53,662.38

52,038.75

36,111.42

40,140.92

26,733.78

35,016.26

24,919.06

30,180.93

39,192.15

46,729.50

34,123.83

38,683.05

47,763.92

62,874.81

50,766.03

39,752.66

43,752.34

59,676.44

39,259.55

33,756.04

34,485.98

24,288.71

37,792.54

34,715.02

34,721.65

45,219.05

46,655.12

44,187.70

48,038.87

47,255.09

3.70

3.89

6.29

3.70

3.45

3.05

6.35

4.13

4.18

3.97

1.97

3.32

2.99

3.50

2.63

4.21

3.45

4.27

4.11

4.76

3.53

4.53

3.76

3.61

3.72

3.78

3.52

3.74

3.92

8.03

3.70

3.48

3.92

3.13

4.23

3.83

3.82

4.22

4.12

3.96

3.64

4.02

4.76

4.60

4.08

4.89

4.76

4.21

2.79

3.35

3.44

3.54

3.50

2.68

3.34

2.48

5.40

3.49

3.02

2.35

3.44

3.53

3.37

4.12

5.15

5.36

3.52

3.50

4.02

3.88

2.59

3.10

3.83

3.69

-4.70

0.28

-2.82

1.16

1.36

1.42

-0.22

0.40

-1.29

1.59

-0.17

-1.87

-3.33

-3.51

-3.35

-12.11

-3.98

-0.79

-0.30

-1.13

-2.70

1.00

-0.16

0.82

1.33

-0.69

0.59

1.08

-0.64

4.85

0.14

-0.61

-0.28

0.41

2.11

0.83

1.63

0.34

1.93

0.28

0.67

0.91

0.51

0.13

-0.40

-0.69

1.52

0.97

-0.34

-2.02

-3.71

-0.41

2.28

-0.10

1.49

-0.26

1.70

1.43

-0.79

0.06

0.55

0.57

-0.16

-3.47

3.88

-0.19

3.18

3.11

5.84

10.50

4.70

5.55

1.80

Percentage

Earnings effect earnings effect

-886.7

-199.1

-2165.2

267.5

862.4

2829.5

-979.7

1581.9

-27.4

748.0

2715.9

3112.7

-92.1

-510.9

-1105.9

-6115.1

-978.6

-2279.1

-1084.4

-1719.1

-21.4

-3428.8

1495.3

631.0

857.3

-1303.9

860.0

1656.7

-545.4

2410.4

-413.9

-379.7

797.9

1944.6

3842.7

167.7

27.6

-1006.0

313.5

184.0

-1156.0

-670.4

-2439.1

-1064.8

313.5

-2207.9

-1938.4

-3268.1

-1787.2

-863.9

-1516.0

-663.8

-672.8

4318.5

447.5

1421.1

139.2

3392.0

-77.2

23.9

-299.0

45.9

1529.1

-3313.3

-1304.9

-2838.4

1114.4

2463.4

-2141.8

2813.7

9954.7

5581.2

4984.4

3444.8

-35.21

3.95

-19.55

14.81

-0.04

10.63

-7.57

1.10

-15.19

24.87

7.69

-20.94

-23.52

-55.69

-4.63

-51.91

-32.68

-13.68

-16.86

-12.39

-38.32

24.53

2.02

-4.11

6.41

-30.35

-0.65

3.92

-12.83

32.96

-4.58

-3.03

6.76

-0.45

19.61

9.80

-0.34

-8.98

4.94

-5.86

8.56

22.25

15.43

13.52

3.04

-7.18

-20.42

-15.13

-12.01

-12.17

-9.16

-32.41

-20.46

19.86

10.91

-12.64

-4.67

17.85

6.95

-22.34

-6.69

7.19

0.41

-23.79

-29.08

6.56

-36.34

-1.65

-11.70

42.91

105.55

26.07

34.14

18.55

Alternative

employment

effect

-4.26

1.72

0.33

2.29

2.59

2.56

1.94

2.28

-0.07

-1.60

-0.12

-0.73

-1.95

-6.38

-2.96

-13.56

-2.73

1.14

1.45

0.24

0.21

1.66

0.72

1.98

1.71

0.89

1.97

1.90

1.15

4.02

0.54

-0.49

0.62

1.89

2.26

1.08

2.74

1.71

2.88

2.04

0.30

-2.29

-0.59

-1.72

-0.06

0.68

1.18

2.45

4.02

1.35

-1.73

-0.74

1.65

4.66

2.24

3.96

0.50

1.14

3.14

1.16

0.54

0.05

2.07

4.29

-1.68

8.23

3.00

4.07

5.79

7.46

12.60

6.82

6.55

4.34

Alternative

earnings effect

Percentage

earnings

change

Alternative

percentage

earnings

change

-2159.7

1384.5

-1566.3

1205.0

419.0

2687.3

-959.3

774.6

222.8

-155.3

1092.4

1013.6

-1919.9

-5121.9

-991.1

-8065.7

-1839.7

-2024.6

-1472.3

-1704.9

-1219.5

-3601.1

1372.1

601.4

-568.5

-856.4

1342.0

653.2

-1191.2

-904.2

-1243.7

-2221.0

-16.0

2500.7

3016.0

-172.1

-151.7

-478.1

422.5

168.4

163.5

-563.5

-172.4

-116.7

706.4

-1392.3

-2576.4

-3165.9

-1594.3

-1424.4

-2294.1

-3375.5

123.6

4481.8

-1454.2

1746.1

1290.9

4630.4

1616.2

887.0

328.2

1135.0

938.4

-2632.3

-732.1

-1630.1

1109.9

1208.7

-1606.2

3198.7

9317.9

6131.4

5115.7

5202.8

12.45

16.02

6.63

15.54

18.02

21.05

9.83

17.90

13.96

18.49

25.00

21.95

15.91

12.18

13.39

-3.49

15.17

3.69

5.48

8.93

12.36

6.50

17.92

15.52

13.00

10.17

15.10

18.37

13.09

18.79

14.23

13.16

16.01

18.42

24.77

14.30

13.59

11.65

13.95

14.39

12.24

16.01

8.02

13.67

16.41

10.09

6.65

1.59

2.52

10.80

12.18

10.64

10.62

22.93

14.30

15.09

14.64

21.43

12.35

11.24

13.19

13.59

16.28

-1.72

10.57

-1.12

15.03

20.59

6.11

21.38

36.11

27.28

23.48

20.94

3.81

7.69

1.55

9.36

9.88

2.42

8.01

6.41

7.93

11.30

9.49

5.86

-7.57

5.92

-12.13

5.62

-2.92

-2.56

-0.84

2.63

-3.66

6.32

6.46

3.33

3.41

7.43

7.33

5.23

1.99

5.82

0.14

7.84

9.04

13.51

5.27

5.72

1.61

4.19

3.56

2.80

2.20

0.66

1.93

4.44

-0.71

-3.97

-6.31

-0.69

2.69

11.55

-2.30

5.16

14.60

3.95

7.64

5.81

10.36

5.54

5.40

4.86

3.42

6.32

-3.95

14.06

4.42

7.38

10.35

1.71

12.32

29.74

19.18

13.67

14.17

Mortgage

holding rate

Migration rate

2015

employment

rate

21501

21502

21600

21701

21702

21801

21802

21900

22001

22002

22100

22200

22300

22400

22500

22601

22602

22700

22800

22900

23000

23100

23200

23301

23302

23400

23500

23600

23700

23801

23802

23900

24000

24100

24200

24300

24400

24500

24600

24701

24702

24801

24802

24900

25000

25101

25102

25103

25104

25105

25200

25300

25401

25402

25500

25601

25602

25701

25702

25800

25900

26001

26002

26101

26102

26106

26107

26201

26301

26304

26410

26412

26501

26503

46.769

43.627

43.349

46.142

39.297

42.901

39.711

42.011

43.300

42.857

41.634

44.713

37.557

43.715

44.935

44.516

41.776

43.528

41.627

40.750

40.625

42.033

36.253

33.492

35.230

42.603

38.713

36.860

35.849

40.200

37.572

40.438

41.940

39.385

36.778

40.337

40.750

35.971

34.049

41.946

40.462

34.877

40.390

40.496

38.621

38.492

40.214

36.308

38.693

30.996

37.997

37.888

38.384

36.646

37.768

34.158

31.544

34.276

27.893

30.100

34.527

43.925

43.363

38.760

39.583

36.885

28.221

38.498

29.703

39.645

33.094

33.913

35.393

45.111

12.094

22.059

18.310

15.036

19.489

16.049

13.718

19.749

13.200

28.571

20.177

14.194

16.031

13.884

10.915

13.255

17.434

11.974

10.663

13.089

14.890

15.992

13.625

16.152

16.630

16.105

17.099

12.799

15.780

14.087

15.607

13.210

16.281

12.289

16.869

12.125

15.159

28.777

12.730

12.077

25.434

15.531

14.162

15.238

14.345

22.619

18.231

19.692

23.116

23.985

14.138

16.563

15.488

25.466

13.609

13.736

22.819

12.956

15.727

19.901

12.240

14.953

13.122

18.992

18.229

23.770

23.926

14.217

15.842

21.893

14.388

24.348

18.539

16.270

85.041

78.922

81.377

86.714

85.942

83.025

84.477

84.381

85.300

82.468

85.630

87.509

85.191

85.929

86.307

84.809

82.566

84.574

84.894

83.421

84.191

84.649

86.375

80.285

85.996

85.487

82.901

80.717

82.676

82.572

87.572

82.911

81.503

82.949

81.003

79.672

80.492

76.978

70.245

81.005

71.676

85.014

82.948

81.250

81.655

76.984

76.139

72.923

71.357

69.004

75.700

75.569

75.926

70.807

84.098

78.663

79.195

75.265

71.217

70.896

76.674

84.112

81.071

82.171

79.688

79.508

79.755

84.505

75.248

83.136

83.453

79.130

89.326

88.414

2015 mean

earnings

Residualized

shock

Employment

effect

59,872.83

35,779.75

40,600.79

56,961.25

39,090.98

38,961.38

34,374.01

41,560.57

42,348.58

34,571.40

51,324.88

50,016.98

41,093.97

44,222.40

45,985.91

43,274.30

34,869.24

41,248.84

39,784.48

40,361.26

39,868.75

50,800.62

38,957.62

33,161.13

37,404.92

50,102.26

41,863.66

33,399.35

34,354.89

43,059.60

36,046.95

45,847.93

41,992.92

48,731.11

39,955.93

55,253.72

40,605.41

34,347.42

28,809.14

47,115.95

26,228.65

34,051.97

42,863.64

42,003.69

37,911.62

34,796.54

28,111.50

27,019.08

30,766.03

25,839.94

36,270.72

29,496.12

37,855.56

34,678.89

40,194.44

32,589.76

32,861.28

30,924.85

24,726.21

27,082.82

33,502.68

40,680.07

41,273.74

31,482.26

29,155.24

35,693.61

34,587.48

50,417.26

33,274.03

45,558.62

45,861.76

47,784.98

45,322.12

51,125.79

3.40

4.00

3.81

2.69

2.92

3.92

3.79

2.97

2.67

3.40

2.74

2.66

4.13

4.74

3.69

3.46

4.05

4.02

3.01

3.02

3.51

2.73

3.46

5.21

4.67

3.97

4.76

4.55

4.78

4.12

3.67

6.09

5.21

3.81

5.60

5.25

7.30

2.63

4.70

4.56

5.04

3.07

3.51

4.83

3.84

4.32

4.26

2.36

2.80

2.82

4.64

4.71

4.10

3.05

4.50

3.63

3.66

3.13

2.17

5.02

2.33

1.76

3.55

4.85

3.53

2.25

2.21

1.01

0.39

0.86

0.87

1.00

2.08

2.54

2.14

-2.59

3.60

3.31

3.21

1.51

2.54

1.28

2.84

-0.26

2.18

1.92

4.29

1.42

2.49

1.69

4.44

1.14

3.82

1.69

5.64

1.46

4.85

1.16

2.66

2.37

1.48

0.13

1.03

1.69

3.56

0.43

-0.61

1.29

1.58

1.28

0.30

-2.98

-8.24

-0.80

-5.15

1.61

-0.83

-0.19

-0.51

-1.13

-0.20

-2.60

-3.99

-5.15

-3.28

-1.34

-1.44

-6.60

0.65

-1.31

0.20

-5.08

-3.65

-5.55

-2.38

1.24

0.25

0.37

-0.88

0.95

3.71

1.75

-7.83

0.98

0.71

-2.78

8.37

3.84

Percentage

Earnings effect earnings effect

3082.1

-1210.3

5686.0

7474.6

2007.1

2825.4

432.2

-835.9

3716.2

-1201.9

6462.6

1979.3

3768.4

-354.4

-699.4

-2474.2

354.9

193.8

-80.3

925.0

786.6

1284.8

1392.0

879.4

1164.5

-634.2

1998.9

363.4

-265.0

2593.3

-2071.9

704.6

-3174.4

-487.8

-1997.3

-1772.0

-2675.7

188.4

-4946.5

-1127.1

-6676.8

-469.2

-464.6

-662.4

1425.5

812.2

-1524.7

-3550.4

575.8

-2843.0

-2671.8

-3905.7

494.1

-4338.7

-447.8

-1944.3

-1527.6

-4475.2

-697.0

-3192.4

-1725.8

3719.6

3923.8

-572.3

-3787.3

2966.6

5962.2

11045.2

-1575.8

10721.2

10321.6

13326.5

5388.5

3947.4

11.27

8.29

37.05

15.03

11.39

-9.94

20.16

-10.85

6.40

7.45

23.03

-6.47

39.60

-11.60

0.45

-12.49

-0.48

-7.58

14.88

4.90

31.34

-3.68

3.48

-15.24

1.88

4.99

-2.30

-18.35

-28.67

2.83

-9.89

-8.99

-8.80

-1.38

-3.55

3.62

-2.94

-25.39

-51.55

-14.23

-59.93

4.86

-24.31

-12.00

-10.24

-39.92

-24.08

1.73

-55.87

-6.51

-13.97

-20.17

-32.19

-43.70

-13.48

-7.87

-40.87

-37.65

-25.71

-39.76

-37.27

8.03

4.44

-5.86

-32.52

-21.70

22.12

27.24

0.62

31.59

43.10

89.53

4.05

8.37

Alternative

employment

effect

3.73

-0.54

4.29

5.44

6.28

3.32

5.26

3.46

5.32

1.25

3.90

5.17

5.89

5.11

4.74

3.63

4.57

4.01

5.38

3.80

6.28

3.00

7.52

3.00

5.04

4.51

3.59

2.55

4.66

3.27

6.76

2.72

0.63

2.46

1.02

-0.15

1.20

-1.22

-6.17

0.94

-4.72

4.88

2.31

1.73

1.98

0.12

1.61

-1.20

-2.11

-5.44

-2.44

-0.40

-1.04

-4.26

2.71

0.37

3.81

-2.06

-2.70

-4.73

-1.53

3.35

2.63

2.97

2.23

1.30

4.73

4.15

-3.83

3.10

-1.63

9.81

5.80

Alternative

earnings effect

Percentage

earnings

change

Alternative

percentage

earnings

change

5410.6

845.1

6142.1

8930.6

2718.7

2352.0

462.6

486.5

3718.3

-2118.6

6018.5

4376.5

4230.3

1785.2

729.0

-688.9

306.9

1426.1

631.4

1296.5

355.1

2720.2

1312.0

785.3

2071.2

1517.5

3364.0

288.9

1.1

2433.0

-1349.3

525.4

-2229.5

831.4

-1562.7

-355.4

-2335.6

-781.1

-5569.5

137.6

-9464.2

-1281.5

1550.6

120.4

1198.4

1734.8

-3765.1

-4024.9

-2870.1

-5540.8

-4000.5

-4301.8

-391.8

-8962.4

-869.9

-3430.4

-1672.2

-4584.3

-2688.7

-4769.9

-2458.5

5293.0

3918.3

-425.3

-3726.5

1556.2

4330.1

10076.6

-2721.2

8711.8

7978.0

7380.9

3073.1

3705.6

20.07

6.15

27.88

31.01

23.11

17.96

12.46

10.05

24.32

4.60

33.56

19.71

22.12

11.27

11.55

6.99

11.58

11.78

11.39

15.19

12.63

16.91

16.39

11.77

15.52

15.11

19.91

10.49

11.70

20.92

6.97

19.60

3.64

12.34

9.55

11.93

6.71

17.42

-5.49

12.04

-9.57

11.61

13.28

12.58

17.42

17.72

4.46

-0.25

20.26

1.79

7.96

-1.58

16.84

6.02

12.94

9.64

11.00

1.43

9.98

4.10

12.62

25.52

24.34

10.77

1.87

24.65

39.84

51.11

8.82

50.52

46.95

70.46

29.60

23.98

12.05

4.02

22.30

21.69

14.24

10.88

8.53

5.87

14.36

-5.59

19.22

12.94

12.43

6.90

4.90

1.62

5.77

7.14

5.43

8.49

3.28

8.06

8.56

6.12

9.86

8.00

15.59

4.38

6.71

10.72

1.20

7.66

-2.55

4.70

1.82

2.11

-0.78

8.05

-12.02

4.06

-19.88

2.61

8.66

5.48

8.82

13.42

-4.64

-2.89

5.53

-7.13

-1.84

-4.81

7.70

-11.11

2.89

-0.38

6.08

-4.01

1.46

-5.58

1.96

20.67

15.72

6.20

-2.31

10.92

28.16

34.71

2.95

29.88

25.46

28.08

12.98

10.55

Mortgage

holding rate

Migration rate

2015

employment

rate

26504

26605

26701

26702

26703

26704

26801

26803

26901

26902

27005

27006

27101

27102

27201

27202

27301

27302

27401

27402

27501

27502

27503

27504

27601

27701

27702

27801

27802

27901

27902

27903

28001

28002

28101

28102

28201

28202

28301

28306

28401

28502

28608

28609

28702

28704

28800

28900

29003

29004

29005

29006

29104

29201

29203

29204

29301

29302

29303

29401

29402

29403

29501

29502

29503

29504

29505

29601

29602

29700

29800

29901

29902

30000

35.567

32.780

43.255

36.885

39.063

36.806

41.019

34.559

44.922

40.000

31.416

41.985

38.660

37.603

40.625

36.709

37.891

46.190

33.981

38.710

44.176

37.356

38.889

36.181

38.462

33.333

41.131

42.460

41.026

33.152

35.652

32.000

39.157

22.523

39.261

31.953

27.638

40.626

31.973

41.081

44.461

38.943

38.258

36.158

40.816

35.246

45.469

44.474

34.973

31.429

37.383

37.762

39.368

32.432

34.873

39.667

38.392

34.037

32.524

35.448

36.145

30.769

32.564

41.850

35.433

32.763

37.241

36.737

35.673

38.312

33.023

32.669

35.938

35.349

20.619

16.183

15.418

19.672

13.281

22.454

16.667

11.765

13.477

18.438

21.239

16.794

17.784

19.008

12.891

19.409

14.453

13.333

20.388

16.359

13.046

21.264

18.519

16.583

20.313

20.875

25.146

17.857

16.484

20.109

23.478

18.400

14.458

20.721

15.360

20.118

20.101

13.992

22.449

17.297

26.718

20.025

17.045

21.469

31.250

30.328

23.050

17.444

26.230

19.429

20.872

19.580

19.540

13.514

32.166

18.874

16.376

21.372

25.243

25.746

23.494

19.527

32.794

13.613

13.386

20.782

14.483

16.438

20.760

16.836

24.186

18.486

26.563

18.295

81.959

83.817

83.298

81.967

87.500

84.954

89.033

90.441

88.672

79.688

83.186

80.153

88.144

82.231

88.672

83.122

88.281

85.238

83.981

83.641

85.469

79.885

83.951

87.437

84.014

83.838

85.575

84.921

83.883

82.065

84.348

85.333

86.145

84.685

84.959

88.757

80.905

85.139

80.272

89.730

78.999

78.256

86.364

82.486

80.740

87.705

81.206

80.870

81.421

86.286

81.620

84.615

81.897

87.387

82.643

83.301

80.640

85.488

78.155

80.597

80.120

79.142

82.217

82.207

79.003

72.127

80.000

81.694

73.392

78.568

79.070

78.805

78.646

74.109

2015 mean

earnings

Residualized

shock

Employment

effect

40,216.10

42,913.07

37,526.18

37,942.20

41,268.45

47,788.17

51,292.94

40,883.52

39,438.81

33,853.62

33,534.81

39,921.69

39,500.65

44,721.81

43,795.08

36,647.26

39,500.39

38,019.73

32,898.21

35,839.94

53,159.91

30,753.22

39,389.27

40,838.98

38,447.22

34,717.33

42,334.89

41,057.47

36,988.69

36,255.16

37,021.47

36,992.92

45,572.54

35,502.13

45,457.03

38,876.88

31,830.97

49,228.93

36,768.13

42,657.97

44,177.98

35,572.35

37,792.01

36,956.79

43,107.98

41,589.65

48,596.63

55,343.48

39,174.16

31,662.37

35,184.88

43,230.73

40,377.63

36,218.66

39,087.20

41,577.52

41,982.60

39,428.14

35,041.39

34,497.34

33,874.15

35,897.65

39,763.86

49,075.18

35,369.81

27,531.89

31,597.03

38,505.45

27,951.22

34,289.42

30,711.06

32,122.40

29,042.89

33,110.96

3.33

1.48

3.05

1.02

2.29

1.33

1.78

1.23

2.57

4.20

2.24

2.36

2.62

2.28

2.20

2.09

3.32

3.80

1.98

3.48

2.63

2.86

2.04

1.87

2.30

2.46

2.93

1.49

1.79

2.29

1.99

1.67

2.08

2.20

1.83

1.85

3.25

1.83

1.86

1.51

3.69

3.28

1.54

1.64

4.11

1.87

3.41

3.64

0.99

2.12

1.78

1.42

2.12

1.53

2.00

2.11

4.07

2.50

2.99

3.83

2.04

3.79

3.14

3.69

4.22

3.74

2.68

3.03

5.51

4.65

4.67

3.34

3.07

3.21

0.93

4.69

3.65

3.20

5.13

0.73

4.88

8.89

7.42

6.11

3.32

0.01

8.60

0.58

7.13

0.73

7.26

3.42

2.48

2.61

1.79

1.52

-0.05

5.76

2.22

7.00

2.54

1.18

3.50

1.95

0.74

2.17

3.74

11.38

1.71

6.46

2.41

2.98

-0.09

9.03

-1.04

-0.48

5.54

1.69

1.01

3.20

0.75

0.10

4.11

7.28

0.83

2.26

0.16

5.73

0.49

1.28

0.06

3.54

-2.36

0.13

-2.27

-1.23

2.68

0.61

-1.56

-5.60

-3.56

-0.58

-5.94

0.03

1.44

0.16

1.16

-3.53

Percentage

Earnings effect earnings effect

-1922.5

3205.5

1514.8

5366.7

5683.6

5812.9

8134.5

9928.7

3017.0

609.5

-805.9

-2017.0

3609.5

5413.0

5042.9

1692.0

1667.5

2076.1

-721.7

-781.1

1832.4

-368.0

-1317.3

3472.5

908.8

2254.3

1608.3

-545.5

3160.2

3543.3

3865.8

920.9

3609.7

7111.7

2084.7

3286.1

-2873.6

3104.8

3057.3

2677.6

-1184.4

-587.6

2159.2

-1339.8

-4169.5

6031.1

-304.7

-1223.2

2188.4

-314.4

-1185.7

2385.7

2186.6

2165.4

2107.7

99.4

-1665.7

2102.3

-2101.1

-2959.8

-2845.2

575.7

274.3

-316.4

-519.1

-3129.7

-1031.3

-897.8

-3269.3

-1158.2

-1053.1

-1916.2

-1190.2

-510.4

-29.35

-3.94

13.92

14.14

88.32

11.89

33.46

21.27

29.06

20.46

-14.16

-51.12

76.06

4.50

10.84

7.51

23.34

6.82

-9.15

1.13

2.80

-7.06

-0.99

0.54

-3.08

4.49

5.14

3.90

13.75

31.38

25.48

-5.55

-14.30

3.09

3.38

4.99

-35.10

6.23

43.50

36.41

-5.92

-20.89

18.21

-8.08

-19.28

44.40

5.72

-2.13

-36.05

-0.88

-13.27

-7.41

13.50

1.91

3.33

3.39

-9.37

4.25

-10.03

3.19

5.16

-16.59

7.93

1.99

-7.66

-43.75

-18.05

-21.48

-29.39

-13.56

-26.67

-24.10

-6.48

-7.55

Alternative

employment

effect

3.30

4.62

7.05

5.12

6.25

3.34

7.93

10.76

10.43

5.09

5.49

2.99

10.50

3.31

10.59

4.21

9.86

5.93

6.54

4.83

3.58

3.16

3.32

9.01

4.77

7.50

4.62

4.10

5.91

3.44

6.91

5.67

6.75

10.81

3.94

9.41

5.61

4.11

3.25

10.41

-0.25

0.73

8.18

4.03

2.22

4.85

1.27

0.57

5.18

10.36

3.03

4.52

2.14

10.35

2.93

3.25

1.49

5.88

-0.93

2.72

-0.65

1.28

4.10

1.82

0.24

-4.20

-0.49

1.66

-2.15

1.80

4.17

2.06

3.41

-2.77

Alternative

earnings effect

Percentage

earnings

change

Alternative

percentage

earnings

change

-2775.9

2927.3

3050.5

4771.2

5115.2

4954.1

7408.5

8057.0

3520.7

463.7

-1120.0

-1369.9

2435.8

3930.4

5904.7

2765.9

740.2

3028.9

531.3

-705.4

2293.7

-1647.5

-115.1

974.8

791.4

1411.6

1277.1

-727.9

2093.5

666.4

3790.1

-358.7

5036.7

6584.3

2891.8

2356.9

-1972.1

3238.5

3590.2

2054.5

-165.8

-1521.4

2022.8

-682.5

-6486.2

4067.6

463.8

861.1

1001.0

-616.4

-102.7

339.2

1604.5

1418.7

324.3

676.2

-2550.3

4223.6

-2930.1

-4958.0

-2770.4

-1868.6

-525.7

789.3

-811.9

-4527.2

-1291.7

-52.4

-3596.9

-1891.8

-605.5

-2666.3

-1434.7

-1885.1

11.18

16.93

17.88

34.80

36.25

28.91

36.83

42.00

22.46

16.12

14.19

13.83

26.01

37.82

29.40

17.40

17.01

21.28

9.44

14.80

20.36

7.90

10.33

26.59

15.46

21.54

18.31

10.42

20.95

24.27

21.42

14.70

23.65

35.59

20.58

21.99

4.05

23.08

28.72

22.49

12.19

14.34

15.13

12.78

3.11

33.46

13.89

13.07

18.97

10.55

11.43

31.03

22.63

22.12

23.07

13.24

12.56

17.65

11.43

4.06

8.08

18.88

14.66

14.37

10.58

2.54

10.33

12.11

0.24

11.25

8.60

7.98

13.21

10.43

0.32

9.38

17.18

27.34

22.78

16.68

21.46

25.80

16.56

11.95

8.85

4.33

15.78

24.11

23.66

10.82

6.50

14.23

8.13

8.56

8.36

-3.07

7.58

10.68

5.65

12.01

6.51

-2.99

11.12

10.55

14.97

4.52

17.82

28.79

12.39

11.40

2.40

11.79

22.38

11.82

4.62

5.45

7.56

6.95

-11.79

13.96

4.79

4.72

8.91

4.23

7.05

11.26

12.43

14.52

7.50

5.61

0.20

16.56

1.90

-7.87

2.12

2.61

5.53

5.40

2.06

-5.46

3.91

5.45

-5.14

2.61

6.26

1.68

8.37

1.10

Mortgage

holding rate

Migration rate

2015

employment

rate

30100

30200

30300

30401

30402

30403

30501

30502

30601

30602

30604

30701

30801

30802

30901

30903

30904

30908

31001

31004

31006

31007

31101

31102

31201

31202

31301

31302

31303

31401

31402

31503

31600

31700

31800

31900

32000

32100

32201

32202

32301

32304

32305

32306

32401

32501

32601

32701

32702

32801

32802

32900

33000

33100

33200

33300

33400

33500

33601

33602

33700

33801

33802

33803

33901

33902

34001

34002

34201

34202

34203

34301

34303

34304

31.456

25.501

38.421

36.842

37.147

28.571

37.864

28.784

35.761

33.766

31.016

31.891

29.653

31.652

32.414

31.589

25.907

21.212

36.413

34.646

29.000

32.110

29.586

33.333

40.052

26.263

36.169

24.390

29.658

29.740

18.812

35.318

32.268

29.921

33.039

35.370

36.214

30.902

25.670

26.050

29.149

19.853

28.662

22.917

25.123

28.611

31.616

29.167

31.606

28.585

28.784

36.724

39.194

38.575

32.739

31.330

29.351

33.333

32.946

34.010

30.885

31.148

26.935

36.634

22.648

33.873

29.775

26.744

22.523

23.214

34.028

36.095

32.515

30.052

17.087

22.350

19.569

25.987

14.781

24.885

11.650

21.836

20.475

30.844

27.273

19.362

27.760

26.119

33.103

24.709

25.389

36.869

23.913

25.984

25.000

37.615

20.414

22.876

21.946

35.354

19.861

23.780

31.179

24.447

21.782

20.568

18.922

25.966

28.247

30.123

17.281

23.606

27.221

24.090

28.298

30.882

35.032

22.917

31.527

27.373

31.794

26.389

35.233

23.162

29.777

35.871

22.410

21.053

28.917

25.932

24.525

20.544

28.811

31.980

18.456

25.820

25.387

14.417

24.390

24.277

19.810

20.465

18.018

16.964

22.454

25.444

20.859

17.617

74.045

72.350

78.086

78.947

76.923

72.350

86.408

76.427

80.775

77.922

76.471

73.349

75.079

81.448

76.552

82.074

75.648

77.273

78.804

77.165

80.000

75.229

82.101

83.660

82.487

80.303

81.430

81.098

78.707

80.462

79.208

84.844

82.581

81.433

83.859

83.148

79.876

77.176

78.843

74.230

82.979

77.941

78.981

87.500

84.236

79.917

83.837

77.315

87.565

80.974

75.186

77.893

81.804

81.101

76.943

78.854

79.430

78.348

77.390

78.680

75.706

76.639

75.851

79.017

73.171

80.231

73.310

71.163

73.874

68.750

82.407

82.249

80.982

77.720

2015 mean

earnings

Residualized

shock

Employment

effect

32,706.53

30,847.53

46,951.68

39,461.67

44,663.35

33,247.76

39,591.14

35,634.69

40,643.74

31,484.29

35,022.75

37,334.17

43,498.98

45,614.73

34,668.99

45,518.21

52,158.80

33,635.24

39,370.89

36,465.83

30,096.95

38,280.69

47,907.34

49,854.90

59,752.69

43,258.04

47,910.39

39,222.57

34,452.83

58,961.32

43,300.94

43,756.83

39,184.87

47,452.57

49,580.92

60,954.78

59,767.70

47,320.59

38,982.35

44,358.03

43,772.20

39,120.13

44,056.96

39,962.53

42,659.08

39,712.13

41,073.60

41,423.05

46,150.71

41,526.24

44,302.01

41,913.00

53,087.49

58,913.29

40,330.46

43,997.01

41,956.28

39,441.55

37,724.41

37,132.41

35,340.38

38,225.51

30,409.50

43,981.62

29,100.52

43,811.43

29,953.84

27,993.75

28,101.07

26,239.57

32,612.73

38,332.07

38,198.60

35,511.98

3.13

2.19

2.69

2.81

3.00

3.56

3.22

1.43

3.16

2.98

7.76

3.16

4.59

2.11

1.97

2.09

3.60

1.64

1.17

1.69

1.84

1.83

3.60

2.77

3.38

2.91

2.76

3.39

2.23

3.84

5.84

4.02

4.12

3.11

2.34

3.78

3.43

4.25

3.36

3.21

2.83

3.22

3.92

3.10

3.36

2.56

3.40

2.92

2.70

2.85

2.84

2.33

3.60

3.61

3.36

3.59

3.71

3.17

2.01

2.02

2.48

2.68

2.38

1.96

2.56

3.13

2.60

3.07

1.72

1.85

2.10

3.53

4.06

3.84

-3.92

-3.58

-1.60

0.27

-1.23

-3.43

3.26

0.71

2.58

-1.06

-0.81

-1.40

-1.83

1.76

-2.09

2.56

-3.14

-1.18

-1.73

1.88

3.72

-3.90

3.95

8.56

1.12

3.77

0.66

-1.23

3.11

0.63

-0.87

5.84

5.47

2.03

2.06

2.43

1.55

-0.24

1.88

-0.97

3.64

0.96

-1.96

11.42

3.45

0.44

1.99

-1.15

10.41

1.70

1.72

-3.78

1.13

1.78

0.47

0.53

0.95

-0.51

-2.62

-3.05

-2.86

-1.42

-3.85

-0.80

-3.25

1.38

-3.96

-4.24

0.12

-2.31

2.76

0.39

-3.60

-2.41

Percentage

Earnings effect earnings effect

-1260.9

1922.6

3179.0

-649.3

2770.8

1335.5

-162.9

3219.5

4308.8

2500.1

3100.2

3670.0

6656.3

7696.8

2545.1

5755.4

7906.5

2676.8

1489.9

-2205.2

-2244.0

2540.6

7064.9

12496.7

3851.3

9334.5

4961.4

5242.9

304.3

17615.5

10380.0

4883.5

4131.9

8433.3

5889.0

9900.0

6532.8

7395.2

2904.3

7727.6

7293.2

3843.1

8066.1

9031.0

9317.4

3768.3

3605.2

5520.4

9155.4

4382.6

9692.8

3369.9

3037.8

2015.6

4601.3

4751.1

5608.4

19.6

1852.2

101.1

593.1

4787.9

-2278.4

3529.0

-572.6

2927.9

-1955.3

-1584.1

-2187.3

1814.6

2715.3

934.9

91.5

2490.8

-20.89

-2.05

-19.22

-19.68

4.58

-7.52

15.52

-0.10

16.31

-24.91

-50.71

4.28

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