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- Figure 2: SNAP benefits per recipient and recipients per population by state, 2006-2015 (a) Benefits per recipient Farm Bill ARRA ARRA Ends 80 100 120 140 160 180 Benefits per recipient 2006m1 2008m1 2010m1 2012m1 2014m1 2016m1 Year-month Minimum 1st quartile Median 3rd quartile Maximum (b) Recipients per population Farm Bill ARRA ARRA Ends 0.05 0.10 0.15 0.20 0.25 Recipients per population 2006m1 2008m1 2010m1 2012m1 2014m1 2016m1 Year-month Minimum 1st quartile Median 3rd quartile Maximum Notes: This figure plots out the SNAP benefits per recipient and recipients per population, each for five states from 2006 to 2015, ranking states by their average SNAP benefits per recipient or recipients per population from 2006 to 2015 and picking the states at the minimum, 1st quartile, median, 3rd quartile, and maximum.
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- Figure 3: Percentage change in SNAP benefits per population due to the 2008 Farm Bill and the 2009 ARRA by state AL AZ AR CA CO CT DE DC FL GA ID IL IN IA KS KY ME MD MA MI MN MS MO MT NE NV NH NJ NM NY NC ND OK OR PA RI SC SD TN TX UT VT VA WA WV WI WY 15 20 25 5 10 15 20 25 Percentage change in benefits per population, Farm Bill Fitted values Percentage change in benefits per population, ARRA Notes: This figure plots out the percentage change in SNAP benefits per recipient for all states, excluding Ohio and Louisiana which were both outliers due to disaster relief events. The slope is negative and insignificant with a point estimate of-0.138 (0.098).
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- Figure 5: HCSUA and synthetic benefits per recipient, New Hampshire and Wyoming (a) HCSUA Farm BillARRA 300 400 500 600 Standard Utility Allowance 2005m1 2010m1 2015m1 Year-month NH (FB: 29.20%) WY (FB: -22.90%) (b) Synthetic benefits per recipient Farm BillARRA 90 100 110 120 130 140 Synthetic benefits per participant 2005m1 2010m1 2015m1 Year-month NH (FB: 20.05%, ARRA: 17.26%) WY (FB: 7.88%, ARRA: 18.99%) Notes: This figure plots out the heating and cooling standard utility allowance (HCSUA) and synthetic SNAP benefits per recipient from 2006-2015 for two states, New Hampshire and Wyoming, to illustrate how differential changes in the SUA lead to differential changes in synthetic benefits per recipient and synthetic benefits per population. Inside the parentheses behind each state, we show the percentage change of the HCSUA during the Farm Bill (FB) for Figure 5a, and the percentage change in synthetic benefits per population during the FB and the ARRA for Figure 5b.
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- Figure O3: Grocery store price indices by quantile of change in log synthetic benefits per population, 2006-2010 Farm Bill ARRA 1 1.05 1.1 1.15 Price Index 2006m1 2007m7 2009m1 2010m7 Year-month Above Median Below Median Notes: This figure plots the revenue-weighted average grocery store price indices by the quantile of change in log synthetic benefits per population for the first and second quantile, respectively. To obtain these quantiles, the total change in the log synthetic benefits per population during the Farm Bill and the ARRA for each state, residualized by control variables, is used to separate the states into quantiles. The first quantile denotes the 24 states with the largest changes in residualized log benefits per population, and the second quantile denotes the 24 states with the smallest changes.
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- Figures Figure 1: SNAP benefits per population by state, 2006-2015 Farm BillARRA ARRA Ends 0 10 20 30 40 Benefits per population 2006m1 2008m1 2010m1 2012m1 2014m1 2016m1 Year-month Minimum 1st quartile Median 3rd quartile Maximum Notes: This figure plots out the SNAP benefits per population for five states from 2006 to 2015, ranking states by their average SNAP benefits per population from 2006 to 2015 and picking the states at the minimum, 1st quartile, median, 3rd quartile, and maximum.
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- For Online Publication: Appendix A Comparisons with Contemporaneous Work There are at least two possible reasons why the conclusion of our paper differs from that of Jaravel (2018), a contemporaneous work which concludes that higher SNAP take-up rates among eligible households reduce inflation rates. At a high level, we differ in (1) data series and time period; (2) explanatory variation; and (3) methodology used to address endogeneity.
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Ganong, P. and J. B. Liebman (2018, November). The Decline, Rebound, and Further Rise in SNAP Enrollment: Disentangling Business Cycle Fluctuations and Policy Changes. American Economic Journal: Economic Policy 10(4), 153–176.
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- Lastly, not all eligible recipients participate in SNAP, hence varying the participation-rate series across states. Ganong and Liebman (2018) study the variation in the participation rate between 1994 and 2011, and note the participation rate showed a negative correlation with the unemployment rate between 2001 and 2007, but then showed a positive correlation during the Great Recession. They also note that variation in the unemployment rate can explain two thirds of the the participation rate variation, whereas BBCE rules explain 18%.
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- Log benefits p.p. refers to log benefits per population. Participation refers to the ratio of SNAP participants to population in each county fixed to the pre-period of 2006.
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- O Figures Figure O1: SNAP benefits as a proportion of total food-at-home sales in food stores, 2006-2014 .08 .1 .12 .14 .16 .18 SNAP Benefits to Food Store Sales 2006 2008 2010 2012 2014 Year Notes: This figure plots the ratio of SNAP benefits to total food-at-home sales at food stores, as defined by the USDA ERS, from 2006-2014 using data from the USDA ERS and FNS. Figure O2: Changes in maximum benefits (a) Maximum benefits, single-person household Farm BillARRA 150 160 170 180 190 200 Maximum benefits 2005m1 2010m1 2015m1 Year-month (b) Maximum benefits per participant by household size 120 140 160 180 200 Maximum benefits per participant 0 2 4 6 8 Household size Before Farm Bill Farm Bill ARRA Notes: This figure plots out the maximum benefits for a single-person household over time in Figure O2a, and the maximum benefits by household size before the Farm Bill, after the Farm Bill, and after the ARRA in Figure O2b.
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- Point Estimate (LTZ) CI (LTZ) Local to Zero Approach Notes: This figure plots the estimated coefficients and their confidence intervals against different levels of δ, the effect of the instrument on the outcome, under various methods in Conley et al. (2012). The three methodologies are the union of confidence interval approach with a support of [0, 0.08], the local-to-zero approach with a standard deviation of 0.02, which is our back-of-the-envelope estimate of δ, and the local-to-zero approach with a standard deviation of δ.
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- Table 4: SNAP participation and effect of SNAP-benefit changes on prices and real sales (1) (2) (3) (4) Specification OLS IV OLS IV VARIABLES Log price index Log real sales Log benefits p.p. 0.0165 0.0738*** 0.0466-0.0108 (0.0107) (0.0250) (0.0335) (0.104) x Participation rate 0.0774** 0.130*** 0.254** 0.265** (0.0329) (0.0371) (0.115) (0.128) Observations 382524 382524 382524 382524 R-squared 0.904 0.899 0.963 0.963 Prob > F 0.000 0.000 0.000 0.000 Number of units 7970 7970 7970 7970 Number of clusters 48 48 48 48 First stage F-stat 10.439 10.439 Notes: Robust standard errors are in parentheses, clustered by state. *** p<0.01, ** p<0.05, * p<0.1. Control variables as well as store and period fixed effects are included. Log benefits p.p. refers to log benefits per population. Participation rate refers to the ratio of SNAP participants to population in each county fixed to the pre-period of 2006.
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- Table N17: Incidence of an additional dollar of SNAP benefits for SNAP-ineligible goods MPC elasticity Pass-through elasticity Shift magnitude PS CS CS (SNAP) CS (non-SNAP) 0.1182 0.0898 0.009 0.098-0.1608-0.013-0.148 Notes: MPC elasticities are obtained from Section 4.2. A market conduct parameter of 0.5 is assumed using markups as shown in Hottman (2016). Demand elasticity is estimated using panel variation as described in Section 5.3. Proportion of SNAP sales of 0.168 is obtained from USDA data. Pass-through elasticity is obtained from Section 4.1 and the shift magnitude is the predicted pass-through elasticity obtained using equation (8) assuming a unit-subsidy pass-through rate of 1. Surplus calculations are changes in surplus per marginal dollar of SNAP disbursed. PS refers to producer surplus and CS refers to consumer surplus, CS(SNAP) and CS(non-SNAP) refers to consumer surplus for SNAP consumers and consumer surplus for non-SNAP consumers, respectively.
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- Whereas we examine both Nielsen Retail Scanner and Nielsen Consumer Panel prices over 2006-2015, Jaravel (2018) examine Nielsen Consumer Panel prices over 2004-2008. Whereas we focus on the intensive-margin variation in SNAP benefits using an IV approach, Jaravel (2018) focuses on the SNAP take-up rates by regressing 2004-2008 prices on 2001-2007 SNAP take-up rates among eligible households using a long-difference approach. One possible reason for the discrepancy is that both conclusions are valid and limited only by external validity: that is, mechanisms specific to each time period and/or each explanatory variation (intensive versus extensive) explain the difference.
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