let the rich be flooded: the unequal impact of hurricane harvey … · 2020-05-29 · let the rich...

Let the Rich Be Flooded:The Unequal Impact of Hurricane Harvey

on Household Debt

Stephen Billings (U. Colorado Boulder)Emily Gallagher (U. Colorado Boulder & StL Fed)

Lowell Ricketts (StL Fed)

The views expressed here are those of the authors only. They do not represent the views ofany of the affiliated institutions, data providers, or funders.

Background Background

Hurricane Harvey (Aug-Sep 2017) stalled over Houston.

Source: vox.com


Submerged 25–30% of Houston, $125 billion in damage


Flooding under Harvey relative to 100 year floodplain

Source: USGS/FEMA

Motivation Motivation

Disconnect: academic literature vs. anecdotal reporting

Based on Katrina, academics view these events as having little effect on household finance

Mild, temporary jump in delinquency rates; homeowners used flood insurance payouts toeliminate mortgage debt (Gallagher and Hartley, 2017)

Minimal impacts on income and labor markets (McIntosh, 2008; Groen, Kutzbach andPolivka, 2017; Deryugina, Kawano and Levitt, 2018; Deryugina et al., 2018)

Consensus of the literature“These studies all conclude that the average net financial impact of a large natural disaster ismodest and short-lived, even for the most severely impacted victims.”~ Gallagher, Hartley and Rohlin (2018)


Disconnect: academic literature vs. anecdotal reporting

Meanwhile, reporters tell tales of complete financial devastation from flooding

Anecdotal reporting“Both families had to start over from nothing. But today, one family is financially stable. Theother is facing bankruptcy.”

~ NPR report by Rebecca Hersher and Rober Benincasa (2019)


Rising inequalities in areas affected by disasters

Wealth inequality tends to rise in areas affected by disasters, particularly in areas thatreceive more FEMA aid (e.g., Howell and Elliott, 2018)


Is Federal disaster assistance regressive?

Flood insurance (from the National Flood Insurance Program)

Mandatory for mortgage borrowers located in a 100-year floodplain

Avg. NFIP payout = $117,000.

For uninsured losses:

FEMA grantsI Avg. recipient grant = $7,300 (max $33,000) vs. $72,162 in damage for 1 ft of floodingI Eligibility for home repair grants: verified losses > $17k but <50% of the market value of the

home

SBA disaster loansI Avg. approved loan = $74,549; interest rate of 1.75%, 30 years for repaymentI Eligibility: (1) credit score; (2) debt-to-income (ability to repay)

F Begley, Gurun, Purnanandam and Weagley (2018) show substantial inequalities inaccess to individual disaster loans from the SBA

IRS disaster refundsI File an amended tax form citing property loss (benefits people with higher incomes and, thus,

greater tax liabilities)

⇒Suggests ↑ access to assistance if you inside the floodplain or are higher income, credit score


This paper

Goal: Apply administrative credit data to the question of whether averages mask importantheterogeneity in the financial effects of flooding

Setting: Hurricane Harvey

Affected a wide variety of income and racial groups, both inside and outside of thedesignated 100-year floodplain

Only 7% if variation in flooding is explained by geo-spacial and socio-economic factors

Method: Treatment intensity difference-in-difference design

Compare the credit outcomes of Houston residents according to degree of flooding intheir Census block

Test for differences in treatment effects on those who have more or less resources toabsorb a wealth shock

I (a) initial financial condition;I (b) location with respect to the floodplain (proxy for flood insurance)


Preview of results

Consistent with earlier research, average effects of flooding are small and temporary

But, financially constrained homeowners experience considerably more financialdistress (more bankruptcy, more delinquency) after flooding

I e.g., top-tercile flooding is associated with a 28% ↑ in bankruptcy rates in highowner-occupied, financially constrained areas relative to no-flood areas

I Mortgage eliminations, consistent with a lack of resources needed to rebuild

Being in a floodplain and, hence, having a higher likelihood of flood insurance, largelymitigates negative effectsMechanism? Due, in part, to a regressive allocation of federal disaster assistance

I Not just SBA, FEMA grants also appear to be regressive


Preview of results

Consistent with earlier research, average effects of flooding are small and temporaryBut, financially constrained homeowners experience considerably more financialdistress (more bankruptcy, more delinquency) after flooding






Preview of results




Being in a floodplain and, hence, having a higher likelihood of flood insurance, largelymitigates negative effects

Mechanism? Due, in part, to a regressive allocation of federal disaster assistanceI Not just SBA, FEMA grants also appear to be regressive


Preview of results






Identification Identification

Data & MethodData

NYFED/Equifax Consumer Credit Panel, Census Data, FEMA flood maps

Method

Treatment intensity difference-in-difference

yibt =

8∑τ=−8

βτ

(Tk

b × Dτ

)+ αi + Dτ + κf (Ait) + η (Cb × Dτ ) + φCb + εibt

yibt is quarterly outcome (bankruptcy, delinquency, mortgage debt)

Tb is the treatment intensity, WAvg. Flood Depth; assigned according to block where thatindividual lived in as of Q2 2017; in terciles of flooding

β: quarterly change in blocks of a given flood intensity relative to the blocks that didnot flood

I Unconstrained vs. ConstrainedI Inside vs. Outside 100-year floodplain (proxy for insurance)

Results Results

Block-level bankruptcy flag rate

Data source: Federal Reserve Bank of NY/Equifax Consumer Credit Panel

Results Results

Block-level bankruptcy flag rate

Sample All All Own<p50 Own≥p50 FlP=0% FlP ≥ 50%& Own≥p50 & Own≥p50

T1b × Pt 0.09 0.13 -0.01 0.17 0.02 0.21

(1.03) (1.25) (-0.05) (1.42) (0.17) (0.46)T2

b × Pt -0.05 -0.01 -0.13 0.04 -0.03 0.38(-0.57) (-0.13) (-0.66) (0.35) (-0.18) (0.86)

T3b × Pt -0.02 0.01 0.13 -0.01 -0.37 0.07

(-0.18) (0.14) (0.61) (-0.06) (-1.46) (0.17)T1

b × Pt × Constrainedb -0.1 -0.14 0.13 0.62** -0.88(-0.57) (-0.52) (0.50) (2.17) (-1.00)

T2b × Pt × Constrainedb -0.09 -0.15 0.11 0.15 0.01

(-0.49) (-0.57) (0.36) (0.38) (0.02)T3

b × Pt × Constrainedb -0.07 -0.65** 0.66** 1.48*** 0.08(-0.37) (-2.20) (2.28) (2.97) (0.10)

N 518,428 518,428 228,545 289,883 215,824 25,283

Heavy flooding & constraint is associated with a 0.66%pt rel. ↑ in bankruptcy rate, which represents28% of the avg. pre-Harvey bankruptcy rate in Constrained, owner-occupied blocks (2.4%).

Data source: Federal Reserve Bank of NY/Equifax Consumer Credit Panel

Results Results

Individual’s Share of debt that is severely delinquentβ estimates of the effect of terciles of flooding relative to no flooding

Sample: All LoEquity HiEquity LoEquity & FlP=0% LoEquity & FlP≥50%T1

b × Pt -0.09 0.11 -0.01 0.05 -0.28(-0.81) (1.30) (-0.04) (0.42) (-1.38)

T2b × Pt 0.14 0.09 -0.07 0.17 -0.50

(1.11) (0.63) (-0.36) (0.95) (-1.33)T3

b × Pt -0.01 0.11 0.04 -0.15 -0.30(-0.09) (1.10) (0.19) (-0.64) (-1.44)

T1b × Pt × Constrainedi 0.04 0.56 0.68 0.59 2.81

(0.11) (1.07) (1.59) (1.06) (1.41)T2

b × Pt × Constrainedi 0.68** 0.96* 0.61 1.12* 1.54(2.23) (1.98) (1.03) (1.90) (1.68)

T3b × Pt × Constrainedi 0.79** 1.38*** -0.36 1.75** 0.84

(2.28) (2.91) (-0.64) (2.16) (0.71)N 1,605,162 297,002 288,532 191,942 20,828

Effect is modest in the full sample: 0.8%pts represents 4.4% of the Constrained sample’s pre-Harvey delinquencyshare (17.7%)

Constrained, mortgage-holders with little equity see a relative 1.4%pt (35%) ↑ in their pre-Harvey delinquencyshare

Being outside the floodplain also has an amplifying effect on delinquency

Results Results

Mortgage debt after flooding (mortgage holders)β estimates of the effect of top-tercile flooding relative to no flooding

Discussion Discussion

Mechanism? Inequality in access to disaster assistanceFEMA registration data, Hurricane Harvey

Lower-income and minority areas get less in disaster assistance, controlling for insurance, flooddepth, and FEMA-assessd damage

Dependent var:

Share of blocks’ IndividualFEMA registrants Eligiblethat are granted Individual FEMA for

assistance assistance ($) SBA loanMedian Income (10k) 0.174*** 171.94*** 1.176***

(5.90) (9.34) (-21.01)Minority Share -0.085*** -0.69} -0.032***

(-23.70) (-0.37) (-7.37)Sample All Homeowners; assistance>0 Damage>0Y-mean 14.19 9,353 10.21N 32,659 62,485 150,339Controls: Flood insurance, property damage, share of housing units with damage, share of housing units registered with FEMA,

wgt. avg. flood depth, density, owner-occ. share.

A simultaneous 1σ ↓ in block income and 1σ ↑ in minority share would:I ↓ the prob. of a FEMA grant by 3%pts (21%)I ↓ a homeowner’s FEMA grant amount by $653 (7%)I Cut in half a FEMA registrant’s chances of an SBA loan


Conclusions

Allocating disaster assistance in a way that appears to be (unintentionally) regressive

Therefore, important to differentiate treatment effects by initial financial condition andfloodplain status

I Flooding has much more deleterious effects on the bankruptcy rates anddelinquencies and of homeowners that are Constrained

I A lack of resources to rebuild is potentially leading to forced home salesI Constrained vs. Unconstrained outcomes are much more equal inside the

floodplain, suggesting that flood insurance helps

Unless disaster assistance becomes less regressive, expect rising inequality in areasaffected by disasters


Begley, T.A., Gurun, U., Purnanandam, A.K., Weagley, D., 2018. Disaster lending: "fair" prices, but "unfair" access. Working paper.

Deryugina, T., Kawano, L., Levitt, S., 2018. The economic impact of hurricane katrina on its victims: Evidence from individual tax returns. American Economic Journal:Applied Economics 10, 202–233.

Gallagher, J., Hartley, D., 2017. Household finance after a natural disaster: The case of hurricane katrina. American Economic Journal: Economic Policy 9, 199–228.

Gallagher, J., Hartley, D., Rohlin, S., 2018. Weathering an unexpected financial shock: The role of cash grants on household finance and business growth following anatural disaster. Working paper.

Groen, J.A., Kutzbach, M.J., Polivka, A.E., 2017. Storms and jobs: The effect of hurricanes on individuals’ employment and earnings over the long term. U.S. Bureau ofLabor Statistics, Working paper.

Howell, J., Elliott, J.R., 2018. Damages Done: The Longitudinal Impacts of Natural Hazards on Wealth Inequality in the United States. Social Problems .

McIntosh, M.F., 2008. Measuring the labor market impacts of hurricane katrina migration: Evidence from houston, texas. American Economic Review 98, 54–57.

let the rich be flooded: the unequal impact of hurricane harvey … · 2020-05-29 · let the rich...

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