Online Appendix for: Consumption Reponses to In-Kind Transfers: Evidence from the Introduction of the Food Stamp Program

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Online Appendix for: Consumption Reponses to In-Kind Transfers: Evidence from the Introduction of the Food Stamp Program Hilary W. Hoynes University of California, Davis and NBER hwhoynes@ucdavis.edu and Diane Whitmore Schanzenbach Harris School of Public Policy University of Chicago schanzenbach@uchicago.edu American Economic Journal: Applied Economics

On-line Appendix In our paper, we examine the impact of the food stamp program on food expenditures. In this Appendix, we provide supplemental estimates to those provided in the published paper. Appendix Table 1 provides descriptive statistics for the three samples used in the paper: (1) all nonelderly families, (2) nonelderly families where the head has less than or equal to 12 years of education, and (3) families with children headed by a single woman (female heads of household). In the main paper (Figure 4) we present trends in the weighted percent of counties that have food stamp programs in place for four illustrative states: California, Florida, Massachusetts, and North Carolina. Appendix Figure 1a/1b presents the same figures for all 50 states. In the main paper, we present county regressions of FSP implementation dates on county pretreatment characteristics (Table 1). Appendix Figure 2 provides scatter plots of each of six county characteristics (x-axis) against the county FSP implementation date (y-axis). For guidance, we also provided the univariate linear regression line (weighted by the county population) for each panel. These figures show that the magnitude of the association between the county characteristics and the food stamp start date is weak and there is an enormous amount of variation that is not explained by the characteristics. The expansion of the food stamp program took place during a time of great change in the U.S. system of government support. In the main paper, we address this by controlling for the county level transfer variables. Another, more direct approach, is to examine the impact of the FSP on family government transfer income. In particular, with the PSID we can measure income of the head and wife from AFDC, other welfare income (SSI, General Assistance), and social security. We present estimates for the nonelderly low education sample using the specification in Table 5, column 1. The results of that exercise, presented in Appendix Table 2, show no significant impact of the FSP on other sources of income support. 2

Appendix Table 3 provides robustness results for our main model. The main triple difference estimates for the sample of lower education nonelderly families (<=12 years of education) are given in Table 5, column (1). In this table we re-estimate this model for two alternative samples. First, we drop the observations with allocated (imputed) dependent variables. Second, we add back in the observations we trimmed from the sample. In our main estimates, we trim observations with unusual values for food expenditures. In particular, we drop observations where the ratio of food spending to income exceeds 0.85, where total annual food expenditures were less than $100 (in 2005 dollars) or where annual family income was less than $500 (in 2005 dollars). 3

Appendix Figure 1a: Percent of Counties with Food Stamp Program 1961-1975, By State Weighted % of Counties in State with FSP 0 50 100 0 50 100 0 50 100 0 50 100 0 50 100 AL AR AZ CA CO CT DC DE FL GA HI IA ID IL IN KS KY LA MA MD ME MI MN MO 61 64 67 70 73 76 MS MT NC ND NE 61 64 67 70 73 76 61 64 67 70 73 76 61 64 67 70 73 76 61 64 67 70 73 76 61 64 67 70 73 76 Years 1961-1975 Source: Authors tabulations of food stamp administrative data (U.S. Department of Agriculture, various years). Counties weighted by 1960 population. 4

Appendix Figure 1b: Percent of Counties with Food Stamp Program 1961-1975, By State Weighted % of Counties in State with FSP 0 50 100 0 50 100 0 50 100 0 50 100 0 50 100 NH NJ NM NV NY OH OK OR PA RI SC SD TN TX UT VA VT WA WI WV 61 64 67 70 73 76 61 64 67 70 73 76 61 64 67 70 73 76 61 64 67 70 73 76 WY 61 64 67 70 73 76 Years 1961-1975 Source: Authors tabulations of food stamp administrative data (U.S. Department of Agriculture, various years). Counties weighted by 1960 population. 5

Appendix Figure 2: 1960 County Characteristics and County Food Stamp Start Date (a) Percent Black (b) Log of Population 0 20 40 60 80 Percent Black, 1960 6 8 10 12 14 16 Log of Population, 1960 (c) Percent with Income<$3,000 (d) Percent Urban 0 20 40 60 80 Percent w ith Income<$3,000, 1960 0 20 40 60 80 100 Percent Urban, 1960 (e) Percent of Land in Farming (f) Percent Age >65 0 20 40 60 80 100 Percent of Land in Farming, 1960 0 5 10 15 20 25 Percent of Population >65, 1960 Note: Each graph provides a scatterplot of a 1960 county characteristic (x-axis) against the food stamp start date (yaxis) where the points are weighted by the 1960 county population. The graphs also contain the linear fit where the regression is weighted by 1960 county population. 1960 County characteristics are from the 1960 City and County Databook and the FSP implementation dates are from U.S. Department of Agriculture (various years). 6

Appendix Table 1: Descriptive Statistics for Estimation Sample All Nonelderly Singles and Families Nonelderly, Head <=12 Female Headed Households # nonmissing # nonmissing # nonmissing obs. Mean Min Max obs. Mean Min Max obs. Mean Min Max FSP participation 39,623 0.066 0 1 30,905 0.087 0 1 6,002 0.297 0 1 Real food at home 39,623 6737 0 35347 30,905 6657 0 35347 6,002 5902 0 24131 log(real food at home) 39,243 8.64 2.63 10.47 30,541 8.64 2.63 10.47 5,788 8.52 3.87 10.09 Any meals out 39,623 0.766 0 1 30,905 0.704 0 1 6,002 0.560 0 1 Real all food 39,623 8179 122.8 40200 30,905 7914 123 40063 6,002 7197 175 35378 log(real all food) 39,623 8.86 4.8 10.6 30,905 8.84 4.81 10.60 6,002 8.75 5.2 10.5 Food at home / Income 39,623 0.171 0 0.849 30,905 0.189 0 0.849 6,002 0.259 0 0.849 All food / Income 39,623 0.179 0.003 3.620 30,905 0.196 0.003 3.620 6,002 0.287 0.009 2.140 Real family income 39,623 59643 769 503346 30,905 51956 769 439860 6,002 32625 824 308554 Log(real family income) 39,623 10.77 6.64 13.13 30,905 10.65 6.64 12.99 6,002 10.19 6.71 12.64 County FSP implemented 39,623 0.864 0 1 30,905 0.864 0 1 6,002 0.884 0 1 Urban county 39,623 0.605 0 1 30,905 0.580 0 1 6,002 0.650 0 1 Female headed household 39,623 0.215 0 1 30,905 0.236 0 1 6,002 1 1 1 Education<12 years 39,623 0.327 0 1 30,905 0.475 0 1 6,002 0.481 0 1 Education=12years 39,623 0.361 0 1 30,905 0.525 0 1 6,002 0.380 0 1 Education>12 years 39,623 0.312 0 1 30,905 0.000 0 0 6,002 0.140 0 1 White 39,623 0.856 0 1 30,905 0.822 0 1 6,002 0.635 0 1 Number of children 39,623 1.27 0 13 30,905 1.30 0 5 6,002 2.12 1 11 Number of adults 39,623 1.97 1 14 30,905 1.99 1 4 6,002 1.47 1 8 State unemployment rate 39,623 6.19 2 12.5 30,905 6.11 2 12.5 6,002 6.33 2 12.5 County % black, 1960 39,623 9.62 0 81.3 30,905 9.83 0 81.3 6,002 12.30 0 62.1 County % urban, 1960 39,623 70.03 0 100 30,905 66.90 0 100 6,002 74.59 0 100 County % farmland, 1960 39,623 44.89 0 239.8 30,905 45.71 0 239.8 6,002 41.78 0 126.6 County % $3,000, 1960 39,623 20.92 5.5 74.4 30,905 22.08 5.5 74.4 6,002 20.51 5.5 68 County % <5 years, 1960 39,623 11.26 5.6 18.2 30,905 11.20 5.6 18.2 6,002 11.22 6.7 18.2 County %>65 years, 1960 39,623 9.27 1 24.9 30,905 9.38 1 24.9 6,002 9.22 2.8 24.9 log(1960 county population) 39,623 12.28 7.72 15.61 30,905 12.14 7.72 15.61 6,002 12.62 7.72 15.61 County per cap ret. and dis. payments 39,623 994.2 112.4 2969.3 30,905 1004.2 112.4 2969.3 6,002 1013.9 172.8 2609.4 County per cap medical payments 39,623 226.6 35.0 690.8 30,905 224.5 35.0 690.8 6,002 237.3 37.0 686.7 County per cap cash PA payments 39,623 226.7 0.0 1086.8 30,905 226.4 0 1086.8 6,002 272.2 15.6 1086.8 Note: PSID interview years 1969-1972 and 1974-1978. No food data is available in 1973 and 1968 is dropped due to inconsistencies in variable definitions. Observations from Alaska are dropped because of missing data on food stamp program start date and observations with unusual expenditure values are dropped (annual food expenditures less than $100, annual family income less than $500, or income share on food greater than 0.85). All outcome variables correspond to annual measures taken as of the interview (in spring of the interview year). For details on sample selection see text and notes to Table 3. 7

Appendix Table 2: Impact of Food Stamp Introduction on Family Transfer Income (2005 dollars) Nonelderly low education singles and families (1) (2) AFDC income (2005$) County FSP Implemented X 69 511 Group participation rate (1107) (1057) Number of Observations 34295 34295 R Squared 0.27 0.29 Other cash welfare (2005$) County FSP Implemented X 723 656 Group participation rate (677) (635) Number of Observations 31319 31319 R Squared 0.13 0.14 Social Security Income (2005$) County FSP Implemented X -4553-4740 Group participation rate (2,429)* (2,362)** Number of Observations 31319 31319 R Squared 0.15 0.15 Demographics, group fixed effects X X 1960 Cty Vars * Linear Time X X Per Capita Cty Transfers X Year Fixed Effects (main and x Pg) X X County Fixed Effects X X State x Linear Time X X Pg x Other Covariates (except Area Fixed Effects) X X Notes: Each parameter is from a separate regression of the outcome variable on a dummy variable equal to 1 if the county-year observation had a food stamp program in place by January of the year prior to the interview year interacted with a group specific food stamp participation rate. The sample includes nonelderly low educated households. See notes to Tables 3 & 5 for more details on sample. All control variables are defined as in Table 5, column 1. See the notes to that table for more details. All outcome variables correspond to annual measures for the year prior to the interview and are expressed in real 2005 dollars. Estimates are weighted using the PSID weight and clustered on county. Standard errors are in parentheses and ***, **, and * indicate that the estimates are significant at the 1%, 5% and 10% levels. 8

Appendix Table 3: Impact of Food Stamp Introduction on Total Food Expenditures, Nonelderly Low Educated Sample Robustness Checks Log of Cash Food Expenditures at Home (non-food stamps) Any Meals Out (0/1) Log of Total Food Expenditures (including food stamps) A. Main estimates County FSP Implemented x Pg -0.043 0.101 0.208 (0.105) (0.101) (0.096)** County FSP Implemented 0.000-0.014-0.005 (0.022) (0.022) (0.020) Number of Observations 30,541 30,905 30,905 R Squared 0.54 0.26 0.52 B. Drop allocated observations County FSP Implemented x Pg -0.055 0.083 0.173 (0.110) (0.100) (0.103)* County FSP Implemented 0.004-0.014-0.001 (0.022) (0.021) (0.022) Number of Observations 28,849 30,578 28,830 R Squared 0.54 0.26 0.51 C. Add in trimmed observations County FSP Implemented x Pg -0.037 0.093 0.218 (0.102) (0.099) (0.095)** County FSP Implemented 0.000-0.013 0.001 (0.022) (0.022) (0.020) Number of Observations 31,253 32,164 31,931 R Squared 0.53 0.25 0.51 Notes: Each parameter is from a separate regression of the outcome variable on a dummy variable equal to 1 if the county-year observation had a food stamp program in place by January of the year prior to the interview year interacted with a group specific food stamp participation rate. The sample includes nonelderly low educated households. See notes to Tables 3 & 5 for more details on sample. All control variables are defined as in Table 5, column 1. See the notes to that table for more details. Panel A repeats the estimates for Table 5, column 1. Panel B re-estimates this model dropping all observations where the dependent variable is allocated (imputed). Panel C re-estimates the models after adding back in the trimmed observations. (In the main sample, we drop observations with annual food expenditures less than $100 in 2005 $, annual family income less than $500 in 2005 $, or income share on food greater than 0.85). Estimates are weighted using the PSID weight and clustered on county. Standard errors are in parentheses and ***, **, and * indicate that the estimates are significant at the 1%, 5% and 10% levels. 9