Cash Transfers and Consumption Smoothing in a Developing Country (Tables)

Tables Table 1: Expenditure statistics, 2005 and 2006 2006 2005 Mean SD Min Median Expenditure/capita (000s Rp) Food expenditure/capita (000s Rp) Non-food expenditure/capita (000s Rp) Education expenditure/capita (000s Rp) Health expenditure/capita (000s Rp) Below poverty line Quintile (nat’l) expenditure/capita Quintile (intra-province) expenditure/capita 315 162 153 11 11 0.10 3.23 3.21 292 93 234 60 67 0.30 1.38 1.39 52 30 8 0 0 0 1 1 Expenditure/capita (000s Rp) Food expenditure/capita (000s Rp) Non-food expenditure/capita (000s Rp) Education expenditure/capita (000s Rp) Health expenditure/capita (000s Rp) Below poverty line Quintile (nat’l) expenditure/capita Quintile (intra-province) expenditure/capita 185 121 65 2 10 0.25 2.25 2.36 93 60 49 6 83 0.43 1.21 1.27 49 32 9 0 0 0 1 1 Expenditure/capita (000s Rp) Food expenditure/capita (000s Rp) Non-food expenditure/capita (000s Rp) Education expenditure/capita (000s Rp) Health expenditure/capita (000s Rp) Below poverty line Quintile (nat’l) expenditure/capita Quintile (intra-province) expenditure/capita 178 115 63 3 5 0.28 2.12 2.28 90 54 50 8 11 0.45 1.16 1.25 31 17 9 0 0 0 1 1 159 104 50 0.4 2 0 2 2 Expenditure/capita (000s Rp) Food expenditure/capita (000s Rp) Non-food expenditure/capita (000s Rp) Education expenditure/capita (000s Rp) Health expenditure/capita (000s Rp) Below poverty line Quintile (nat’l) expenditure/capita Quintile (intra-province) expenditure/capita 323 180 142 7 13 0.14 3.23 3.24 272 119 197 27 55 0.35 1.41 1.42 54 38 10 0 0 0 1 1 252 150 86 0.4 2 0 3 3 Max Mean SD Min Median Max 31 20 0 0 0 0 1 1 272 155 108 0 2 0 3 3 4891 1141 4236 1660 3137 1 5 5 41 30 9 0 0 0 1 1 170 110 56 0 1 0 2 2 1817 422 1581 48 150 1 5 5 37 23 0 0 0 0 1 1 172 112 55 0 1 0 2 2 908 484 682 68 751 1 5 5 Non-recipients (N = 6604) 243 138 94 2 2 0 3 3 7702 2790 7071 2269 2607 1 5 5 356 182 174 8 10 0.11 3.28 3.26 300 104 228 41 62 0.31 1.37 1.38 D = 1 Recipients (N = 639) 165 110 52 0 1 0 2 2 843 761 423 220 1832 1 5 5 195 123 72 2 4 0.34 2.14 2.27 118 62 80 4 11 0.47 1.18 1.25 D = 2 Recipients (N = 1805) 945 645 576 220 178 1 5 5 192 124 68 2 5 0.31 2.11 2.27 92 57 51 5 22 0.46 1.12 1.22 Attritors (N = 771) 2927 1073 2497 563 750 1 5 5 Notes: See Appendix C for details on the panel construction. D = d recipients obtained d UCT disbursements by enumeration in early 2006. Attritors are those households which could be identified in the 2005 baseline survey but not in the subsequent rounds. Rp stands for Rupiah. The exchange rate fluctuated between 9, 500 Rp and 10, 500 Rp to the dollar between October 2005 and September 2006. All expenditure variables are household per capita expressed in Rupiah per month. The underlying food expenditure items are recorded for the week prior to enumeration and scaled up to the monthly level by the factor 30/7. The underlying non-food expenditure items are recorded for the year prior to enumeration and scaled down to the monthly level by the factor 1/12. Below poverty line is an indicator for whether or not the household’s total expenditures per capita fell below the district rural or urban poverty line in the given year. Per capita expenditure quintiles are computed separately within the full national sample and within the 31 provinces in which sample households reside. The 2005 quintiles are calculated including attritors. Table 2: Marginal Effects in the Propensity Score Model, P r(disbursementsh > 0|Xh ) Urban Area HH Head Female Land owned (hectares) Land owned2 (hectares) HH ever participate Rice for the Poor # children in school # children in school 2 Indicators for Household Size∈ {2, . . . , 12} Floor area coefficient (std. error) -0.138 0.609 -0.112 0.001 0.889 -0.101 0.024 — -0.006 (0.091) (0.110)∗∗∗ (0.036)∗∗∗ (0.000)∗∗∗ (0.075)∗∗∗ (0.063) (0.017) [0.222] (0.002)∗∗∗ Household composition (reference = share adult males, 10+ years) Share Female Children, 0-9 yrs 0.334 (0.289) Share Male Children, 0-9 yrs 0.491 (0.266)∗ Share Adult Females, 10+ yrs -0.090 (0.193) Primary household income source (reference = other) Trade/Retail -0.155 Financial/Real Estate -0.575 Agriculture 0.103 Mining -0.120 Manufacturing 0.198 Electricity/Gas/Water 0.422 Construction 0.307 (0.102) (0.186)∗∗∗ (0.075) (0.120) (0.117)∗ (0.669) (0.094)∗∗∗ coefficient (std. error) Housing status (reference = other) Own house -0.126 Lease house -0.172 Rent house -0.454 Free house -0.021 Official house -0.937 (0.102) (0.242) (0.252)∗ (0.207) (0.297)∗∗∗ Roof type (reference = other) Concrete roof Tile roof Shingle roof Iron roof Asbestos roof Fiber/Thatch roof -0.697 -0.378 -0.121 -0.185 -0.012 0.021 (0.473) (0.341) (0.368) (0.303) (0.464) (0.302) Floor type (reference = other) Brick wall Wood wall Bamboo wall Cement/Tile/Plaster floor Wood/Reed/Bamboo floor Earthen floor -0.205 0.218 0.542 -0.006 0.218 0.592 (0.259) (0.282) (0.287)∗ (0.473) (0.484) (0.481) (0.176) (0.166) (0.199) Souce of drinking water (reference = other) Bottled water -0.987 Pump water -1.092 Tap water -0.473 Protected well water -0.740 Unprotected well water -0.820 Protected spring water -1.072 Unprotected spring water -1.024 River water -0.840 Rain water -0.462 Buy drinking water -0.151 (0.474)∗∗ (0.252)∗∗∗ (0.295) (0.249)∗∗∗ (0.265)∗∗∗ (0.280)∗∗∗ (0.304)∗∗∗ (0.322)∗∗∗ (0.376) (0.179) -0.450 -0.681 0.352 0.028 (0.642) (0.763) (0.702) (0.639) Toilet disposal location (reference = other) Septic tank -0.321 Pond/Rice field -0.114 Lake, river, sea -0.106 Beach -0.105 (0.150)∗∗ (0.225) (0.169) (0.149) Constant 1.216 (0.895) Pseudo-R2 0.23 Household head education level (reference = no education) Primary -0.271 Junior secondary -0.558 Senior secondary -1.089 Higher -2.388 (0.115) (0.162)∗∗∗ (0.139)∗∗∗ (0.511)∗∗∗ Toilet facilities (reference = other) Own toilet Shared toilet Public toilet -0.254 -0.043 -0.031 Source of light (reference = other) PLN electricity Non-PLN electricity Pump lantern Oil lamp ∗∗ Notes: Significance levels: ∗ 10% ∗∗ 5% ∗ ∗ ∗ 1%. This table reports average marginal effects for the estimates of the propensity score model in equation (A.1) based on a logit specification. The sample includes the 9,048 households comprising the balanced constructed from Susenas 2005 and 2006. Standard errors are clustered by village. All variables are as reported in February-March 2005. The coefficients on the indicators for household size are suppressed, but the p-value = 0.222 for the joint significance of those indicators is reported in brackets. The regression also controls for province fixed effects. PLN is the state-run electricity firm. Table 3: Idiosyncratic vs. Spatial Variation in Staggering Fixed Effects Xh,t−1 controls Province No District No (1) (2) — — — — — — 0.053 0.171 0.240 Dependent variable H0 : β X = 0 F statistic [p-value] R2 Dependent variable (7) H0 : β X = 0 F statistic [p-value] R2 Subdistrict No Province Yes District Yes Subdistrict Yes (5) (6) 31.35 [< 0.001] 29.03 [< 0.001] 28.69 [< 0.001] 0.241 0.331 0.389 P r(disbursements > 0) (3) (4) P r(disbursements = 2 | disbursements > 0) (8) (9) (10) (11) (12) — — — — — — 3.01 [< 0.001] 1.81 [< 0.001] 0.90 [0.706] 0.266 0.810 0.895 0.327 0.821 0.898 Notes: disbursements denotes the number of disbursements received by Susenas enumeration in early 2006. Linear probability regressions for P r(disbursementshv = 2 | disbursementshv > 0) and P r(disbursements > 0) are based on the sample of recipient and all households, respectively. The F tests correspond to a test of the null the hypothesis that all household-specific variables included in the X vector have no relationship with these probabilities. The R2 are inclusive of the geographic fixed effects. There are 30 provinces, 339 districts, and 619 subdistricts. Table 4: Staggering is Orthogonal to Observable Differences Across Regions days since Feb. 2 (1) (2) (3) (4) (5) (6) (7) (8) -0.002 (0.002) -0.001 (0.002) 0.057 (0.039) -0.040 (0.037) 0.018 (0.032) 0.038 (0.052) 0.029 (0.056) -0.101 (0.083) -0.025 (0.086) -0.016 (0.034) -0.001 (0.002) 0.048 (0.040) -0.030 (0.037) -0.024 (0.041) 0.053 (0.051) 0.024 (0.055) -0.103 (0.083) -0.065 (0.091) -0.031 (0.035) -0.083 (0.047)∗ -0.001 (0.002) 0.043 (0.041) -0.024 (0.037) -0.021 (0.040) 0.031 (0.054) 0.009 (0.053) -0.104 (0.080) -0.065 (0.094) -0.009 (0.037) -0.087 (0.046)∗ 0.101 (0.058)∗ -0.001 (0.002) 0.043 (0.041) -0.026 (0.037) -0.024 (0.040) 0.037 (0.058) 0.012 (0.053) -0.101 (0.080) -0.064 (0.093) -0.011 (0.037) -0.086 (0.046)∗ 0.101 (0.057)∗ -0.044 (0.087) -0.001 (0.002) 0.045 (0.041) -0.026 (0.037) -0.019 (0.044) 0.041 (0.058) 0.013 (0.053) -0.106 (0.080) -0.061 (0.091) -0.010 (0.037) -0.090 (0.047)∗ 0.098 (0.058)∗ -0.049 (0.088) 0.076 (0.168) -0.001 (0.002) 0.038 (0.041) -0.021 (0.034) -0.019 (0.043) 0.029 (0.052) 0.022 (0.051) -0.117 (0.077) -0.060 (0.080) -0.023 (0.034) -0.097 (0.046)∗∗ 0.076 (0.057) -0.057 (0.090) 0.081 (0.156) -0.177 (0.093)∗ -0.004 (0.056) -0.248 (0.122)∗∗ -0.062 (0.079) -0.001 (0.090) -0.002 (0.002) 0.035 (0.041) -0.020 (0.033) -0.009 (0.040) 0.037 (0.051) 0.023 (0.050) -0.131 (0.075)∗ -0.073 (0.081) -0.030 (0.035) -0.108 (0.045)∗∗ 0.062 (0.055) -0.058 (0.086) 0.117 (0.154) -0.189 (0.093)∗∗ 0.007 (0.055) -0.240 (0.131)∗ -0.064 (0.079) 0.018 (0.093) 0.137 (0.090) 0.079 (0.086) 0.075 (0.095) -0.029 (0.105) 2,349 0.001 0.470 2,349 0.020 0.591 2,349 0.035 0.120 2,349 0.047 0.024 2,349 0.048 0.017 2,349 0.049 0.026 2,349 0.091 0.001 2,349 0.105 0.0002 log distance to subdistrict capital log distance to district capital log distance to Jakarta urban village village road paved village accessible only by water post office in village log distance to post office log district population, 2005 bank in subdistrict log mean HH exp./capita in district, 2005 rainfall shock, 2005 any mudslide, 2003-5 any flood, 2003-5 any earthquake, 2003-5 any fire 2003-5 any other disaster, 2003-5 President’s party 1st in village President’s party 2nd in village President’s party 3rd in village President’s party 4th in village Number of Households R2 H0 : β X = 0 [p-value] Notes: Significance levels: ∗ 10% ∗∗ 5% ∗ ∗ ∗ 1%. Linear probability regressions based on the sample of recipient households using the following specification: P r(disbursementshv = 2 | disbursementshv > 0) = γZv + υhv , where Zv is a vector of characteristics associated with the village v within which household h resides. Standard errors are clustered at the district level in all specifications. Distances to (sub)district capitals and post offices are based on actual travel distance; distance to Jakarta is great-circle. Further background on each of the variables can be found in Appendix C. Table 5: Baseline Estimates of Multi-valued Treatment Effects, Short- and Medium-Term Estimator τ10 : disbursement 1 τ21 : disbursement 2 τ20 ≡ τ21 + τ10 : disbursements 1+2 Reweighted Propensity Score Control(s) Xh Controls Number of Households R2 τ10 : disbursement 1 τ21 : disbursement 2 τ20 ≡ τ21 + τ10 : disbursements 1+2 Reweighted Propensity Score Control(s) Xh Controls Number of Households R2 OLS IPW (1) (2) -0.062 (0.027)∗∗ 0.049 (0.030)∗ Double Robust (Pbh ) (Xh ) (3) (4) Short-Term: 2005-2006 -0.091 -0.091 -0.090 ∗∗∗ ∗∗∗ (0.032) (0.030) (0.031)∗∗∗ 0.074 0.077 0.072 (0.035)∗∗ (0.032)∗∗ (0.032)∗∗ Control Function (5) -0.076 (0.030)∗∗ 0.076 (0.034)∗∗ -0.013 (0.014) -0.017 (0.020) -0.014 (0.020) -0.018 (0.018) 0.000 (0.019) No No No Yes No No Yes Yes No Yes No Yes Yes Yes No 9,011 0.045 9,011 0.100 9,011 0.104 9,011 0.181 9,011 0.119 -0.034 (0.040) 0.026 (0.045) Medium-Term: 2005-2007 -0.056 -0.066 -0.044 (0.038) (0.038)∗ (0.032) 0.028 0.032 0.009 (0.043) (0.043) (0.035) -0.027 (0.037) 0.028 (0.042) -0.008 (0.020) -0.028 (0.023) -0.034 (0.024) -0.034 (0.023) 0.001 (0.023) No No No Yes No No Yes Yes No Yes No Yes Yes Yes No 6,992 0.044 6,992 0.055 6,992 0.062 6,992 0.144 6,992 0.068 Notes: Significance levels: ∗ 10% ∗∗ 5% ∗ ∗ ∗ 1%. The dependent variable in all specifications is ∆log total monthly household expenditures per capita between 2005 and 2006/2007. In the top panel, the constant term in columns 1 and 2 (i.e., average non-recipient log expenditure growth, or κ in equation (1)) equals 0.107 and 0.109, respectively. In the bottom panel, the constant term equals 0.113 and 0.153 in columns 1 and 2, respectively. Columns 2-5 are estimated by weighted least squares where the weights for treatment households equal one and the weights for control households are given by the normalized estimated odds of treatment ω b = Pb/(1 − Pb), where the normalization is over the entire sample for the given time horizon. Using the Crump et al. (2009) procedure, we trim 37 households in the upper tail of the estimated propensity scores, Pb, and do the same in the OLS regressions for comparability. Column 3 controls linearly for the propensity score and column 5 for a fifth-order polynomial in the propensity score allowing it to vary by treatment and control. Column 4 controls for all covariates Xh used to estimate the propensity score. The coefficients on these additional terms in columns 3-5 are suppressed for presentational purposes. All columns include province fixed effects. Standard errors are clustered by village and computed over the entire two-step process using a block bootstrap with 1000 repetitions. Table 6: Heterogeneity by Time of Survey and Length of Delay Estimator enumerated in March f τ10 : disbursement 1 m τ10 : disbursement 1 × enumerated in March f : disbursement 2 τ21 m τ21 : disbursement 2 × enumerated in March f M arch m τ10 ≡ τ10 + τ10 f M arch m τ21 ≡ τ21 + τ21 f f M arch m m τ20 ≡ τ21 + τ10 + τ21 + τ10 F ebruary f f τ20 ≡ τ10 + τ21 Reweighted Propensity Score Control(s) Xh Controls Number of Households OLS IPW Double Robust (Pbh ) (Xh ) (3) (4) Control Function (5) (1) (2) 0.043 (0.024)∗ 0.003 (0.058) -0.085 (0.066) -0.004 (0.064) 0.071 (0.072) 0.045 (0.041) -0.042 (0.064) -0.064 (0.072) 0.046 (0.071) 0.037 (0.076) 0.050 (0.040) -0.041 (0.061) -0.065 (0.071) 0.052 (0.070) 0.033 (0.075) 0.038 (0.035) -0.026 (0.063) -0.083 (0.071) 0.014 (0.067) 0.076 (0.075) 0.053 (0.041) -0.029 (0.062) -0.059 (0.070) 0.056 (0.070) 0.027 (0.074) -0.082 (0.030)∗∗∗ 0.067 0.033)∗∗ -0.015 (0.015) -0.001 (0.032) -0.105 (0.037)∗∗∗ 0.083 (0.037)∗∗ -0.022 (0.021) 0.004 (0.049) -0.106 (0.036)∗∗∗ 0.085 (0.037)∗∗ -0.021 (0.020) 0.011 (0.048) -0.109 (0.033)∗∗∗ 0.090 (0.034)∗∗∗ -0.019 (0.019) -0.012 (0.043) -0.088 (0.034)∗∗∗ 0.083 (0.036)∗∗ -0.005 (0.020) 0.027 (0.050) No No No Yes No No Yes Yes No Yes No Yes Yes Yes No 9,011 9,011 9,011 9,011 9,011 Notes: Significance levels: ∗ 10% ∗∗ 5% ∗∗∗ 1%. Significance levels: ∗ 10% ∗∗ 5% ∗∗∗ 1%. The dependent variable in all specifications is ∆log household expenditures per capita between 2005 and 2006. The variable enumerated in March is an indicator for whether the household was enumerated in March (relative to February) 2006. All columns are estimated by weighted least squares where the weights for treatment households equal one and the weights for control households are given by the normalized estimated odds of treatment ω b = Pb/(1 − Pb). See Table 5 for further details on each of the estimators. All columns include province fixed effects. Standard errors are clustered by village and computed using a block bootstrap with 1000 repetitions. Table 7: Multi-valued Treatment Effects by Expenditure Group Growth Horizon Expenditure Group τ10 : disbursement 1 τ21 : disbursement 2 τ20 ≡ τ21 + τ10 : disbursements 1+2 Number of Households 2005-2006 food non-food (2) (3) total (1) 2005-2007 food non-food (5) (6) total (4) -0.076 (0.031)∗∗ 0.076 (0.034)∗∗ -0.094 (0.031)∗∗∗ 0.097 (0.034)∗∗∗ -0.046 (0.045) 0.037 (0.048) -0.017 (0.038) 0.023 (0.043) -0.030 (0.039) 0.068 (0.041)∗ 0.031 (0.056) -0.053 (0.060) 0.000 (0.019) 0.003 (0.019) -0.010 (0.025) 0.006 (0.026) 0.038 (0.026) -0.022 (0.039) 9,011 9,011 9,009 6,992 6,992 6,992 Notes: Significance levels: ∗ 10% ∗∗ 5% ∗ ∗ ∗ 1%. The dependent variable in all specifications is ∆log household expenditures per capita on the given commodity group between 2005 and 2006/2007. All columns are estimated by weighted least squares where the weights for treatment households equal one and the weights for control households are given by the normalized estimated odds of treatment ω b = Pb/(1 − Pb). All columns include a 5th order polynomial in the propensity scores that is allowed to vary by treatment and control. All columns include province fixed effects. Standard errors are clustered by village and computed using a block bootstrap with 1000 repetitions. Table 8: Multi-valued Treatment Effects by Expenditure Subgroup, 2005-2006 Expenditure Group grains (1) fish/meat/dairy (2) fruit/nuts/veg. (3) other food (4) outside prep. (5) τ10 : disbursement 1 -0.025 (0.045) 0.055 (0.054) -0.173 (0.063)∗∗∗ 0.125 (0.068)∗ -0.120 (0.043)∗∗∗ 0.122 (0.051)∗∗ -0.084 (0.040)∗∗ 0.085 (0.045)∗ -0.218 (0.071)∗∗∗ 0.160 (0.079)∗∗ 0.031 (0.034) -0.048 (0.035) 0.003 (0.030) 0.000 (0.023) -0.059 (0.041) 8,789 8,334 8,844 8,879 7,649 housing (6) transport/comm. (7) appliances (8) debt/taxes (9) educ./health (10) 0.012 (0.052) -0.031 (0.056) -0.285 (0.118)∗∗ 0.259 (0.132)∗∗ 0.006 (0.065) 0.119 (0.074) 0.083 (0.122) -0.149 (0.135) -0.149 (0.109) 0.191 (0.125) -0.020 (0.025) -0.026 (0.061) 0.125 (0.046)∗∗∗ -0.066 (0.059) 0.042 (0.065) 9,002 5,478 8,898 5,995 6,504 τ21 : disbursement 2 τ20 ≡ τ21 + τ10 : disbursements 1+2 Number of Households Expenditure Group τ10 : disbursement 1 τ21 : disbursement 2 τ20 ≡ τ21 + τ10 : disbursements 1+2 Number of Households Notes: Significance levels: ∗ 10% ∗∗ 5% ∗ ∗ ∗ 1%. The dependent variable in all specifications is ∆log household expenditures per capita on the given commodity group between 2005 and 2006/2007. All columns are estimated by weighted least squares where the weights for treatment households equal one and the weights for control households are given by the normalized estimated odds of treatment ω b = Pb/(1 − Pb). All columns include a 5th order polynomial in the propensity scores that is allowed to vary by treatment and control. All columns include province fixed effects. Standard errors are clustered by village and computed using a block bootstrap with 1000 repetitions. Table 9: Heterogeneity by Proximity to Financial Institutions Growth Horizon Estimator bank nearby u τ10 : disbursement 1 b τ10 : disbursement 1 × bank nearby u τ21 : disbursement 2 b τ21 : disbursement 2 × bank nearby banked u b τ10 ≡ τ10 + τ10 banked u b τ21 ≡ τ21 + τ21 banked u u b b τ20 ≡ τ21 + τ10 + τ21 + τ10 unbanked u u τ20 ≡ τ10 + τ21 Reweighted Propensity Score Controls Number of Households 2005-2006 2005-2007 OLS (1) IPW (2) Control Fn. (3) OLS (4) IPW (5) Control Fn. (6) 0.001 (0.026) -0.133 (0.047)∗∗∗ 0.104 (0.058)∗ 0.102 (0.054)∗ -0.087 (0.067) -0.027 (0.047) -0.165 (0.061)∗∗∗ 0.108 (0.069) 0.106 (0.057)∗ -0.065 (0.072) -0.013 (0.045) -0.140 (0.054)∗∗ 0.104 (0.064) 0.118 (0.057)∗∗ -0.078 (0.070) 0.003 (0.033) -0.142 (0.060)∗∗ 0.153 (0.077)∗∗ 0.067 (0.067) -0.066 (0.086) 0.022 (0.044) -0.144 (0.063)∗∗ 0.126 (0.079) 0.052 (0.071) -0.042 (0.089) 0.049 (0.042) -0.100 (0.058)∗ 0.112 (0.074) 0.058 (0.066) -0.051 (0.085) -0.027 (0.032) 0.015 (0.035) -0.014 0.015 -0.030 0.030 -0.057 (0.037) 0.041 (0.042) -0.016 (0.019) -0.058 (0.042) -0.036 (0.035) 0.040 (0.039) 0.004 (0.020) -0.023 (0.039) 0.012 (0.049) 0.002 (0.055) 0.014 (0.023) -0.074 (0.043)∗ -0.018 (0.047) 0.009 (0.054) -0.009 (0.026) -0.092 (0.050)∗ 0.012 (0.045) 0.007 (0.051) 0.019 (0.027) -0.042 (0.049) No No Yes No Yes Yes No No Yes No Yes Yes 8,923 8,923 8,923 6,966 6,966 6,966 Notes: Significance levels: ∗ 10% ∗∗ 5% ∗ ∗ ∗ 1%. The dependent variable in all specifications is ∆log household expenditures per capita between 2005 and 2006/2007. The variable, bank nearby, equals one if there are any banking institutions located in the given village’s subdistrict as reported in Podes 2005 (see Appendix C). Columns 2-3 and 5-6 are estimated by weighted least squares where the weights for treatment households equal one and the weights for control households are given by the normalized estimated odds of treatment ω b = Pb/(1 − Pb). Columns 3 and 6 additionally include a 5th order polynomial in the propensity scores that is allowed to vary by treatment and control. All columns include province fixed effects. Standard errors are clustered by village and computed using a block bootstrap with 1000 repetitions. Table 10: Robustness Checks τ10 disbursement 1 τ21 disbursement 2 τ20 ≡ τ10 + τ21 disbursements 1+2 No. of Households 1. baseline -0.076 (0.031)∗∗ 0.076 (0.034)∗∗ 0.000 (0.019) 9,011 2. controls for day of survey enumeration -0.070 (0.027)∗∗ 0.071 (0.031)∗∗ 0.001 (0.017) 9,011 3. district fixed effects -0.059 (0.024)∗∗ 0.057 (0.027)∗∗ -0.002 (0.016) 9,011 4. subdistrict fixed effects -0.038 (0.022)∗ 0.037 (0.024) -0.002 (0.014) 9,011 5. village fixed effects -0.039 (0.021)∗ 0.038 (0.024) -0.001 (0.015) 9,011 6. ln Cht trimmed at 1st and 99th percentile -0.085 (0.031)∗∗∗ 0.074 (0.034)∗∗ -0.011 (0.018) 8,833 7. ∆ ln Ch,t+1 trimmed at 1st and 99th percentile -0.052 (0.024)∗∗ 0.050 (0.027)∗ -0.002 (0.016) 8,832 8. ∆ ln Ch,t+1 deflated by regional poverty line -0.057 (0.033)∗ 0.066 (0.036)∗ 0.009 (0.019) 8,851 9. ∆ ln Ch,t+1 deflated by regional CPI -0.070 (0.029)∗∗ 0.069 (0.032)∗∗ -0.001 (0.017) 8,923 10. ∆ ln Ch,t+1 adjusted for adult-equivalence (total) -0.070 (0.030)∗∗ 0.071 (0.033)∗∗ 0.002 (0.018) 9,011 11. ∆ ln Ch,t+1 adjusted for adult-equivalence (food) -0.072 (0.028)∗∗ 0.072 (0.032)∗∗ 0.001 (0.018) 9,011 12. ∆ ln Ch,t+1 prorated annual durable expenditures -0.092 (0.034)∗∗∗ 0.083 (0.038)∗∗ -0.009 (0.020) 9,011 13. controls for other social program receipt -0.056 (0.031)∗ 0.073 (0.032)∗∗ 0.017 (0.025) 9,011 14. controls for change in health shocks/capita -0.078 (0.030)∗∗∗ 0.078 (0.033)∗∗ 0.001 (0.018) 9,011 15. controls for natural disasters, 2003-5 -0.084 (0.031)∗∗∗ 0.080 (0.033)∗∗ -0.003 (0.018) 8,785 16. controls for staggering covariates, Table 4 -0.074 (0.029)∗∗ 0.051 (0.032) -0.024 (0.029) 8,687 17. controls for pre-program enumerator visit -0.045 (0.038) 0.075 (0.032)∗∗ 0.030 (0.029) 9,011 Notes: Significance levels: ∗ 10% ∗∗ 5% ∗ ∗ ∗ 1%. Each row corresponds to a separate regression with log household expenditure per capita growth, ∆ ln C, as the dependent variable. The estimates are obtained by weighted least squares where the weights for treatment households equal one and the weights for control households are given by the normalized estimated odds of treatment ω b = Pb/(1 − Pb). All rows include a 5th order polynomial in the propensity scores that is allowed to vary by treatment and control. All rows include province fixed effects. Standard errors are clustered by village (except in rows 3 and 4, which cluster by the given geographic FE) and computed using a block bootstrap with 1000 repetitions. See Section 4.1 for details on the specifications and the Online Appendix for results using other estimators. Table 11: Intensive Margin Treatment Effects by Expenditure Group (1) (2) (3) (4) ∆ ln total expenditures/capita transfers per capita (000,000s Rupiah) 0.045 (0.008)∗∗∗ 0.044 (0.008)∗∗∗ 0.037 (0.009)∗∗∗ 0.064 (0.012)∗∗∗ ∆ ln f ood expenditures/capita transfers per capita (000,000s Rupiah) 0.045 (0.009)∗∗∗ 0.044 (0.009)∗∗∗ 0.039 (0.010)∗∗∗ 0.063 (0.013)∗∗∗ ∆ ln nonf ood expenditures/capita transfers per capita (000,000s Rupiah) Treatment Indicators Reweighted Propensity Score Polynomial Household Size Indicators Number of Households 0.046 (0.011)∗∗∗ 0.045 (0.012)∗∗∗ 0.036 (0.012)∗∗∗ 0.070 (0.019)∗∗∗ Yes No No No Yes Yes No No Yes Yes Yes No Yes Yes Yes Yes 9,011 9,011 9,011 9,011 Notes: Significance levels: ∗ 10% ∗∗ 5% ∗ ∗ ∗ 1%. Each cell corresponds to a separate regression. Transfers are rescaled to 100,000s of Rupiah (approximately 10 USD). Columns 2-4 are estimated by weighted least squares where the weights for treatment households equal one and the weights for control households are given by the normalized estimated odds of treatment ω b = Pb/(1− Pb). All include the treatment indicators and province fixed effects. Columns 3-4 include a 5th order polynomial in the propensity scores that is allowed to vary by treatment and control. Column 4 includes indicators for household size. Standard errors are clustered by village and computed using a block bootstrap with 1000 repetitions. Table 12: (Agricultural) Household Expenditures Respond to Transitory Rainfall Shocks rainfall shock (1) (2) (3) (4) (5) 0.030 (0.071) -0.049 (0.095) -0.005 (0.019) 0.125 (0.109) -0.043 (0.073) -0.055 (0.074) -0.029 (0.068) rural village rural village × rainfall shock agriculture primary income 0.018 (0.014) 0.220 (0.088)∗∗ agricultural primary income × rainfall shock own any agricultural land -0.001 (0.014) 0.170 (0.087)∗ own any agricultural land × rainfall shock own agricultural land (Ha) 0.001 (0.003) 0.063 (0.029)∗∗ own agricultural land (Ha) × rainfall shock rainfall shock + rainfall shock × covariate Number of Households R2 8,923 0.042 0.077 (0.084) 0.177 (0.095)∗ 0.114 (0.091) 8,923 0.043 8,923 0.045 8,923 0.044 8,923 0.045 Notes: Significance levels: ∗ 10% ∗∗ 5% ∗ ∗ ∗ 1%. The dependent variable in all specifications is ∆log total monthly household expenditures per capita between 2005 and 2006. The rainfall shock is the log deviation of the seasonal rainfall level in the district from the long-run (1952-2004) district mean. Standard errors clustered by district. All columns include province fixed effects. The interaction terms are as observed at baseline.