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 of any of the affiliated institutions, data providers, or funders.
Background Background Hurricane Harvey (Aug-Sep 2017) stalled over Houston. Source: vox.com
Background Background Submerged 25–30% of Houston, $125 billion in damage
Background Background 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 to eliminate mortgage debt (Gallagher and Hartley, 2017) Minimal impacts on income and labor markets (McIntosh, 2008; Groen, Kutzbach and Polivka, 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 is modest and short-lived, even for the most severely impacted victims.” ~ Gallagher, Hartley and Rohlin (2018)
Motivation Motivation 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. The other is facing bankruptcy. ” ~ NPR report by Rebecca Hersher and Rober Benincasa (2019)
Motivation Motivation Rising inequalities in areas affected by disasters Wealth inequality tends to rise in areas affected by disasters, particularly in areas that receive more FEMA aid (e.g., Howell and Elliott, 2018)
Motivation Motivation 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 grants ◮ Avg. recipient grant = $7,300 (max $33,000) vs. $72,162 in damage for 1 ft of flooding ◮ Eligibility for home repair grants: verified losses > $17k but <50% of the market value of the home SBA disaster loans ◮ Avg. approved loan = $74,549; interest rate of 1.75%, 30 years for repayment ◮ Eligibility: (1) credit score; (2) debt-to-income (ability to repay) ⋆ Begley, Gurun, Purnanandam and Weagley (2018) show substantial inequalities in access to individual disaster loans from the SBA IRS disaster refunds ◮ 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
Motivation Motivation This paper Goal : Apply administrative credit data to the question of whether averages mask important heterogeneity in the financial effects of flooding Setting : Hurricane Harvey Affected a wide variety of income and racial groups, both inside and outside of the designated 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 in their Census block Test for differences in treatment effects on those who have more or less resources to absorb a wealth shock ◮ (a) initial financial condition; ◮ (b) location with respect to the floodplain (proxy for flood insurance)
Motivation Motivation Preview of results Consistent with earlier research, average effects of flooding are small and temporary
Motivation Motivation Preview of results Consistent with earlier research, average effects of flooding are small and temporary But, financially constrained homeowners experience considerably more financial distress (more bankruptcy, more delinquency) after flooding ◮ e.g., top-tercile flooding is associated with a 28% ↑ in bankruptcy rates in high owner-occupied, financially constrained areas relative to no-flood areas ◮ Mortgage eliminations , consistent with a lack of resources needed to rebuild
Motivation Motivation Preview of results Consistent with earlier research, average effects of flooding are small and temporary But, financially constrained homeowners experience considerably more financial distress (more bankruptcy, more delinquency) after flooding ◮ e.g., top-tercile flooding is associated with a 28% ↑ in bankruptcy rates in high owner-occupied, financially constrained areas relative to no-flood areas ◮ Mortgage eliminations , consistent with a lack of resources needed to rebuild Being in a floodplain and, hence, having a higher likelihood of flood insurance, largely mitigates negative effects
Motivation Motivation Preview of results Consistent with earlier research, average effects of flooding are small and temporary But, financially constrained homeowners experience considerably more financial distress (more bankruptcy, more delinquency) after flooding ◮ e.g., top-tercile flooding is associated with a 28% ↑ in bankruptcy rates in high owner-occupied, financially constrained areas relative to no-flood areas ◮ Mortgage eliminations , consistent with a lack of resources needed to rebuild Being in a floodplain and, hence, having a higher likelihood of flood insurance, largely mitigates negative effects Mechanism? Due, in part, to a regressive allocation of federal disaster assistance ◮ Not just SBA, FEMA grants also appear to be regressive
Identification Identification Data & Method Data NYFED/Equifax Consumer Credit Panel, Census Data, FEMA flood maps Method Treatment intensity difference-in-difference 8 � � � T k y ibt = b × D τ + α i + D τ + κ f ( A it ) + η ( C b × D τ ) + φ C b + ε ibt β τ τ = − 8 y ibt is quarterly outcome (bankruptcy, delinquency, mortgage debt) T b is the treatment intensity, WAvg. Flood Depth ; assigned according to block where that individual 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 did not flood ◮ Unconstrained vs. Constrained ◮ 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 T 1 b × P t 0.09 0.13 -0.01 0.17 0.02 0.21 (1.03) (1.25) (-0.05) (1.42) (0.17) (0.46) T 2 b × P t -0.05 -0.01 -0.13 0.04 -0.03 0.38 (-0.57) (-0.13) (-0.66) (0.35) (-0.18) (0.86) T 3 b × P t -0.02 0.01 0.13 -0.01 -0.37 0.07 (-0.18) (0.14) (0.61) (-0.06) (-1.46) (0.17) T 1 b × P t × Constrained b -0.1 -0.14 0.13 0.62** -0.88 (-0.57) (-0.52) (0.50) (2.17) (-1.00) T 2 b × P t × Constrained b -0.09 -0.15 0.11 0.15 0.01 (-0.49) (-0.57) (0.36) (0.38) (0.02) T 3 b × P t × Constrained b -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 represents 28% 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 delinquent β estimates of the effect of terciles of flooding relative to no flooding Sample: All LoEquity HiEquity LoEquity & FlP=0% LoEquity & FlP ≥ 50% T 1 b × P t -0.09 0.11 -0.01 0.05 -0.28 (-0.81) (1.30) (-0.04) (0.42) (-1.38) T 2 b × P t 0.14 0.09 -0.07 0.17 -0.50 (1.11) (0.63) (-0.36) (0.95) (-1.33) T 3 b × P t -0.01 0.11 0.04 -0.15 -0.30 (-0.09) (1.10) (0.19) (-0.64) (-1.44) T 1 b × P t × Constrained i 0.04 0.56 0.68 0.59 2.81 (0.11) (1.07) (1.59) (1.06) (1.41) T 2 b × P t × Constrained i 0.68** 0.96* 0.61 1.12* 1.54 (2.23) (1.98) (1.03) (1.90) (1.68) T 3 b × P t × Constrained i 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 delinquency share (17.7%) Constrained, mortgage-holders with little equity see a relative 1.4%pt (35%) ↑ in their pre-Harvey delinquency share Being outside the floodplain also has an amplifying effect on delinquency
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