MWI_2009-2010_TPCS_v01_M DDI_MWI_2009-2010_TPCS_v01_M_WB Development Economics Data Group 2017-10-23 Nesstar Publisher Version 01 (October 2017) Time Preference & Cognition Survey 2009 - 2010 TPCS 2009 - 2010 MWI_2009-2010_TPCS_v01_M Xavier Giné Jessica Goldberg Dan Silverman Dean Yang Nesstar Publisher Microdata Library DECRG: Finance & Private Sector Development Other Household Survey [hh/oth] The baseline survey was conducted from January- February 2009, while the revisit was conducted in March - April 2010. The data accompanies the paper: Revising Commitments: Field Evidence on the Adjustment of Prior Choices. The very poor in developing countries often make intertemporal choices that seem at odds with their individual self-interest. We investigate these choices with a lab-in-the-field experiment in rural Malawi. We make two contributions. First, we construct a new dependent variable: revisions of prior choices regarding the allocation of future income. This allows us to directly examine intertemporal choice revision and its determinants. In particular, this dependent variable permits a novel test for the existence of self-control problems: we find that revisions of money allocations toward the present are positively correlated with present-bias as well as the (randomly assigned) closeness in time between the revision decision and disbursement. Second, we investigate other potential determinants of revision. We find little evidence that revisions of money allocations toward the present are associated with spousal preferences, household shocks or the financial sophistication of respondents. Malawi Rural Malawi - within 25 kilometres of the town of Mponela, Dowa District. Participants in our study were farmers under contract with (the subsidiaries of) two large tobacco companies in the 2008–9 growing season. The companies organised the farmers into clubs that range in size from 3 to 43 members. To facilitate timely revisiting, we limited our sample to those farmers located near a main trading centre in the town of Mponela (population 13,670), and who lived in six traditional authorities (TAs) in the Dowa and Ntchisi districts. To allow relatively easy access to participants and to facilitate their access to the cash disbursements, we included all farmers in these TAs that were 2008–9 members of clubs in which the median club member lives 25 kilometres or less from the disbursement office, located in Mponela. Sample survey data [ssd] Face-to-face [f2f] The questionnaires for the Time Preference & Cognition Survey 2009 - 2010 are organized into baseline and revisit questionnaires.These are available under the Related Materials tab. Microdata Library - Public use files, accessible to all The user of the data acknowledges that the original collector of the data, the authorized distributor of the data, and the relevant funding agency bear no responsibility for use of the data or for interpretations or inferences based upon such uses. GGSY_data.NSDstat GGSY_data.dta: This file contains data from an artefactual field experiment in Malawi that measures time preferences and revision behavior. The sample consists of several hundred wife-husband pairs in rural Malawi. Intertemporal choices are elicited by adapting Andreoni and Sprenger's (2012) convex time budget method, with large real stakes (roughly a month's wages). Subjects decide five potential allocations of money to be disbursed at two points, 61 or 91 days, in the future for the corresponding interest rates: 10%, 25%, 50%, 75%, and 100%. A subset of these subjects was revisited some time prior to the first disbursement at t=61 days and given the opportunity to revise their allocation between sooner or later. Dataset contains N=10,710 decisions (i.e., five allocations and associated interest rate for 2,142 subjects in the study). 2157 398 Nesstar 200801 GGSY_data_long.NSDstat The dataset “GGSY_data_long” contains the exact same data but in a different format. Participants are asked to make a series of 5 decisions, where the only variable that is changed is the interest rate. The dataset “GGSY_data_long” contains 10,710 observations, where each observation one of these decisions (2,142 individuals * 5 decisions = 10,710 observations). 10710 375 Nesstar 200801 sim_data.NSDstat Simulated data: This file is called by sim random.do 2157 29 Nesstar 200801 Respondent ID 2157 0 1234581011 3259365102 Household ID 2157 0 123458101 325936510 Days to first disbursement at revisit (target) 722 1435 2 16 2 60 3 43 4 63 5 41 6 44 7 41 8 30 9 50 10 58 11 43 12 54 13 43 14 42 15 53 16 57 Sysmiss 1435 Days to first disbursement at revisit (actual) 662 1495 0 16 0 1 1 2 2 54 3 40 4 53 5 32 6 50 7 35 8 32 9 42 10 57 11 40 12 50 13 44 14 30 15 48 16 52 Sysmiss 1495 Initial sooner allocation (value, MK) Initial allocation and total value of beans in sooner period 722 1435 0 2000 Initial later allocation (beans) Initial allocation and total value of beans in later period 722 1435 0 20 0 17 1 1 2 7 3 4 4 6 5 15 6 13 7 17 8 37 9 40 10 81 11 36 12 67 13 34 14 46 15 61 16 31 17 23 18 38 19 19 20 129 Sysmiss 1435 Initial later allocation (value, MK) Initial allocation and total value of beans in sooner period 722 1435 0 4000 Final sooner allocation (MK) 663 1494 0 2400 Final later allocation (MK) Final allocation of beans in later period 663 1494 0 4000 Expenditure in April on food 1314 843 0 100000 -77777 NOT APPLICABLE 0 -88 DON'T KNOW 0 0 37 100 1 150 1 200 4 220 1 240 1 250 1 300 10 350 3 400 9 410 1 450 3 500 38 510 1 550 1 600 21 640 1 650 2 660 1 700 11 750 5 800 30 850 1 900 8 950 4 1000 117 1100 2 1200 16 1250 1 1260 1 1300 2 1400 5 1500 70 1550 1 1600 5 1700 4 1760 1 1800 12 1900 2 1960 1 2000 221 2100 5 2180 1 2200 1 2250 1 2300 3 2400 5 2480 1 2500 35 2600 3 2620 1 2700 4 2750 1 2800 13 2850 2 2900 1 3000 154 3200 2 3280 2 3400 1 3420 1 3500 21 3600 3 3700 2 3800 4 4000 79 4200 2 4300 1 4400 1 4500 11 4700 1 4800 2 5000 113 5200 1 5600 1 6000 45 6400 1 6500 2 6700 1 6950 1 7000 14 7500 1 8000 18 8500 1 9000 4 9500 1 10000 40 11000 2 12000 6 15000 10 16000 1 20000 11 21000 1 23000 1 25000 3 30000 5 35000 1 40000 3 50000 3 70000 1 100000 1 Sysmiss 843 Expenditure in May on food 1314 843 0 50000 -77777 NOT APPLICABLE 0 -88 DON'T KNOW 0 0 49 100 2 200 3 220 1 300 8 350 1 360 1 400 14 450 1 500 46 560 1 600 16 700 11 750 3 800 13 900 11 950 1 1000 128 1100 5 1200 19 1250 1 1300 2 1400 3 1500 99 1600 7 1700 5 1800 8 1840 1 1960 1 2000 211 2100 5 2180 1 2250 1 2400 2 2500 78 2620 1 2700 3 2800 7 2850 2 2900 1 3000 137 3200 1 3280 2 3400 4 3500 30 3600 1 3650 1 3700 2 3750 1 3800 4 3900 1 4000 70 4500 11 4600 1 4700 1 4800 1 5000 103 5300 1 5500 2 5600 2 6000 42 6800 1 7000 16 7500 1 8000 22 9000 9 9500 1 10000 25 10425 1 11000 1 12000 6 13000 1 15000 10 16000 1 17250 1 20000 15 23000 1 25000 3 30000 2 40000 3 45000 1 50000 2 Sysmiss 843 Expenditure in June on food 1314 843 0 100000 -77777 NOT APPLICABLE 0 -88 DON'T KNOW 0 0 50 100 6 200 5 220 1 300 7 400 7 450 1 480 1 500 31 600 18 700 10 800 15 870 1 900 4 1000 116 1200 11 1300 4 1400 3 1480 1 1500 104 1600 2 1700 5 1750 1 1800 13 1900 1 2000 213 2100 3 2180 1 2200 1 2400 2 2500 77 2560 1 2600 6 2620 1 2700 1 2800 7 2850 1 2900 2 3000 168 3200 1 3280 1 3300 2 3400 3 3500 28 3600 1 3700 1 3800 2 4000 88 4200 3 4500 8 4600 1 5000 108 5500 1 6000 48 7000 23 7400 1 7500 1 7750 1 8000 23 9000 5 10000 20 10425 1 11000 5 12000 4 15000 13 16000 1 18000 3 20000 4 23000 1 25000 2 27000 1 30000 3 35000 1 50000 1 60000 1 100000 1 Sysmiss 843 Expenditure in July on food 1314 843 0 100000 -77777 NOT APPLICABLE 0 -88 DON'T KNOW 0 0 53 100 4 200 5 220 1 250 1 300 7 350 1 400 8 500 34 600 11 700 11 750 1 800 27 900 10 1000 92 1140 1 1200 6 1300 2 1400 1 1460 1 1500 108 1600 7 1640 1 1700 1 1800 17 1900 1 2000 222 2100 2 2180 1 2200 4 2250 1 2300 2 2400 1 2500 68 2560 1 2600 2 2620 1 2700 1 2800 7 2850 2 2900 1 3000 156 3050 1 3200 1 3280 1 3300 1 3400 3 3500 36 3700 2 3800 2 3880 1 4000 83 4200 2 4500 10 4600 1 4800 1 5000 113 5400 1 5500 2 6000 44 6500 3 7000 34 7500 1 8000 20 9000 11 9500 1 10000 21 10425 1 10500 1 11000 1 12000 3 13000 1 14000 1 15000 3 16000 1 18000 2 20000 7 23000 1 25000 3 30000 4 35000 1 50000 2 60000 1 100000 1 Sysmiss 843 Expenditure in August on food 1314 843 0 100000 Expenditure in April on medicine 1314 843 0 35000 -77777 NOT APPLICABLE 0 -88 DON'T KNOW 0 0 84 20 2 25 1 40 3 50 15 60 1 80 1 90 1 100 67 120 1 150 19 180 1 200 155 250 18 300 84 350 2 380 1 400 50 450 5 480 1 500 244 550 1 600 45 650 1 700 24 800 23 900 9 950 1 1000 120 1200 5 1300 2 1450 1 1500 52 1600 2 1700 4 1800 3 2000 115 2500 8 2800 2 3000 44 3500 3 4000 19 4500 2 5000 36 5500 1 6000 8 7000 5 8000 3 10000 13 12000 1 20000 3 35000 2 Sysmiss 843 Expenditure in May on medicine 1314 843 0 45000 -77777 NOT APPLICABLE 0 -88 DON'T KNOW 0 0 101 10 1 20 2 30 1 40 1 50 15 60 2 70 2 80 3 100 59 120 1 150 36 170 1 200 124 250 27 300 95 320 1 350 9 400 60 450 8 480 3 500 203 550 1 600 44 650 1 700 35 750 6 760 1 800 32 850 1 900 6 950 1 1000 121 1200 5 1300 2 1400 2 1500 46 1600 1 1800 4 2000 98 2200 1 2500 15 2800 1 2900 1 3000 47 3200 1 3500 8 3700 1 3800 1 4000 20 4500 1 5000 19 6000 9 6500 1 7000 4 8000 7 10000 7 11000 1 12000 1 15000 1 30000 2 40000 2 45000 1 Sysmiss 843 Expenditure in June on medicine 1314 843 0 45000 -77777 NOT APPLICABLE 0 -88 DON'T KNOW 0 0 109 20 1 30 1 50 19 60 1 80 2 100 45 150 28 180 1 200 110 250 27 300 87 330 1 350 11 390 1 400 59 410 1 450 3 500 200 550 2 600 53 650 1 700 52 750 1 800 50 850 1 900 12 1000 106 1100 1 1200 12 1300 5 1400 2 1500 54 1600 1 1700 2 1800 3 1900 1 2000 91 2300 1 2400 2 2500 17 2900 1 3000 46 3400 1 3500 7 4000 20 4300 1 4500 3 5000 18 5600 1 6000 13 7000 2 8000 7 9000 2 10000 6 12000 4 15000 1 40000 2 45000 2 Sysmiss 843 Expenditure in July on medicine 1314 843 0 60000 -77777 NOT APPLICABLE 0 -88 DON'T KNOW 0 0 119 20 2 40 2 50 12 70 2 80 1 90 2 100 52 150 28 200 99 250 20 280 1 300 94 350 10 360 2 370 1 400 61 450 3 500 186 550 2 600 59 650 1 700 42 750 3 800 53 850 1 900 13 950 2 1000 134 1100 1 1200 8 1300 4 1400 5 1500 47 1700 1 1800 1 1900 1 2000 75 2300 2 2400 1 2500 24 2700 1 2800 1 2900 1 3000 37 3100 1 3300 1 3400 1 3500 4 3600 1 3800 1 4000 25 4500 1 5000 17 5500 1 5600 1 6000 9 6500 2 7000 7 8000 4 9000 2 10000 10 11000 1 12000 2 15000 1 20000 1 35000 1 45000 1 50000 1 60000 1 Sysmiss 843 Expenditure in August on medicine 1314 843 -99999 70000 Expenditure in April on school fees 1314 843 0 305000 -77777 NOT APPLICABLE 0 -88 DON'T KNOW 0 0 1132 30 1 100 1 150 1 200 1 300 3 400 1 450 2 500 2 750 1 800 2 1000 3 1050 1 1200 1 1300 2 1500 10 1700 1 1740 1 1750 1 1800 1 1850 1 1900 1 2000 11 2100 1 2200 3 2250 2 2360 1 2400 1 2500 29 2700 1 2800 1 3000 13 3400 1 3500 3 3600 1 3800 2 4000 11 4060 2 4150 1 4400 1 4500 3 5000 6 5400 1 5500 1 6000 7 7000 1 7500 2 7800 1 8000 9 8250 1 8500 4 8700 2 8750 1 9000 1 9500 1 10000 2 11000 3 11500 2 11800 1 15000 1 24000 1 26000 3 26500 1 30000 1 50000 1 85000 1 305000 1 Sysmiss 843 Expenditure in May on school fees 1314 843 0 20000 -77777 NOT APPLICABLE 0 -88 DON'T KNOW 0 0 1237 100 1 150 1 200 1 250 1 300 3 450 2 500 1 800 2 1000 2 1500 1 1700 1 1800 2 2000 6 2050 2 2100 1 2140 1 2200 1 2250 1 2400 1 2500 10 2700 1 3000 3 3800 1 4000 3 4060 1 4400 1 4500 4 5000 2 6000 1 6500 1 7500 1 7550 1 7800 1 7950 1 8000 3 8500 2 8600 1 9500 2 10000 2 13200 1 15000 2 20000 1 Sysmiss 843 Expenditure in June on school fees 1314 843 0 56000 -77777 NOT APPLICABLE 0 -88 DON'T KNOW 0 0 1131 100 1 150 2 200 1 250 1 300 3 450 2 500 1 800 1 900 1 1000 5 1200 1 1300 1 1500 3 1550 1 1700 2 1750 1 1800 5 1850 1 1900 1 2000 12 2030 1 2050 1 2250 3 2300 1 2350 1 2400 2 2450 1 2500 17 2590 1 2600 3 2700 2 2800 1 3000 15 3400 1 3500 9 3600 1 3800 2 3900 1 4000 6 4060 1 4200 1 4400 1 4500 4 5000 7 5500 1 5700 1 6000 4 6500 3 6900 1 7000 3 7250 1 7500 1 7750 1 8000 16 8500 3 8950 1 9000 2 9800 1 10000 4 10200 1 11000 1 14000 1 15000 2 18000 1 24000 1 28000 1 30000 1 50000 1 56000 1 Sysmiss 843 Expenditure in July on school fees 1314 843 0 305000 -77777 NOT APPLICABLE 0 -88 DON'T KNOW 0 0 1184 100 1 150 2 200 1 250 1 300 3 450 2 500 2 1000 1 1200 1 1300 2 1500 9 1700 1 1740 1 1750 1 1800 2 1900 1 2000 7 2030 2 2050 2 2100 1 2200 2 2250 1 2500 16 2850 1 3000 9 3500 4 3800 1 4000 4 4200 1 4400 1 4500 2 5000 5 5400 1 5500 1 6000 4 7500 2 7800 1 8000 5 8500 4 8700 1 9000 3 9500 1 10000 5 11000 3 11500 1 11800 1 12000 2 26000 2 26500 1 85000 1 305000 1 Sysmiss 843 Expenditure in August on school fees 1314 843 0 85000 Expenditure in April on farm expenditures 1314 843 -99999 100000 -99999 1 -77777 NOT APPLICABLE 0 -88 DON'T KNOW 0 0 409 200 2 300 4 400 2 500 24 600 12 650 1 700 10 800 10 850 1 900 7 950 1 1000 61 1200 11 1300 2 1400 3 1500 42 1600 3 1700 3 1800 5 1900 1 2000 144 2250 1 2300 2 2400 1 2500 32 2700 2 2800 2 3000 121 3400 1 3500 15 3600 2 3950 1 4000 60 4500 5 4800 2 5000 106 5400 1 5500 1 5600 1 5700 1 5800 1 6000 41 6800 1 7000 20 7500 1 7800 1 8000 23 9000 10 10000 45 11000 1 12000 7 13000 1 13600 1 14000 2 15000 20 20000 11 25000 2 30000 4 35000 2 75000 1 95000 1 99000 1 100000 1 Sysmiss 843 Expenditure in May on farm expenditures 1314 843 -99999 100000 -99999 1 -77777 NOT APPLICABLE 0 -88 DON'T KNOW 0 0 347 150 1 200 1 250 2 280 1 300 4 400 4 500 24 600 9 650 1 700 6 750 1 800 12 900 1 1000 74 1100 1 1200 12 1300 2 1400 2 1500 59 1600 6 1650 1 1700 1 1800 7 2000 156 2100 2 2200 2 2300 1 2500 35 2600 1 2700 1 2800 1 2900 1 3000 130 3200 1 3500 18 3600 1 3700 1 4000 80 4200 1 4400 1 4500 9 4700 1 5000 99 5500 1 5700 1 5800 1 6000 45 6500 1 7000 22 7500 3 7700 1 8000 23 9000 10 10000 31 11000 3 12000 10 13000 1 14000 3 15000 20 18000 1 20000 8 24000 1 25000 1 30000 2 35000 1 50000 1 100000 1 Sysmiss 843 Expenditure in June on farm expenditures 1314 843 -99999 150000 -99999 1 -77777 NOT APPLICABLE 0 -88 DON'T KNOW 0 0 518 100 1 150 1 200 3 250 2 280 1 300 4 400 3 450 1 500 26 600 10 650 1 700 16 800 11 900 5 1000 94 1200 13 1300 1 1350 1 1400 2 1500 48 1700 6 1800 2 2000 106 2050 1 2500 28 2600 2 2800 1 3000 80 3400 2 3500 15 3600 1 3750 1 3800 2 4000 46 4500 3 4800 1 5000 93 5300 2 5500 2 5600 1 6000 29 6500 1 7000 21 7500 4 8000 21 8700 1 9000 7 10000 21 10500 1 11000 1 12000 4 13000 4 15000 8 16000 1 20000 10 22000 1 25000 2 30000 9 32000 1 35000 1 37000 1 40000 1 44200 1 60000 1 70000 1 100000 1 105000 1 150000 1 Sysmiss 843 Expenditure in july on farm expenditures 1314 843 -99999 205000 -99999 1 -77777 NOT APPLICABLE 0 -88 DON'T KNOW 0 0 602 200 7 250 1 300 3 350 1 400 2 450 1 500 26 600 8 700 13 750 1 800 10 900 9 1000 72 1200 5 1400 1 1500 56 1600 2 1700 2 1800 7 1900 1 2000 90 2200 1 2300 2 2500 23 2700 2 2800 3 2950 1 3000 74 3500 11 4000 42 5000 62 5500 2 5800 1 6000 26 6300 1 7000 18 7500 4 8000 20 8500 1 9000 10 9500 1 10000 19 10500 1 11000 1 11500 1 12000 6 13000 1 14000 1 15000 14 15700 1 17000 1 18000 1 18450 1 19000 1 20000 17 25000 2 30000 4 31000 1 32000 1 35000 2 37000 1 40000 2 45000 2 50000 6 205000 1 Sysmiss 843 Expenditure in August on farm expenditures 1314 843 -99999 300000 Expenditure in April on transport 1314 843 -99999 50000 -99999 2 -77777 NOT APPLICABLE 0 -88 DON'T KNOW 0 0 203 150 1 200 17 250 2 300 30 350 3 400 27 450 3 500 72 600 28 670 1 700 14 750 4 800 40 850 1 900 11 1000 152 1150 1 1200 23 1250 1 1300 1 1350 1 1400 5 1500 67 1600 6 1700 4 1800 9 2000 141 2300 1 2400 4 2500 35 2600 1 2800 4 2900 1 3000 113 3200 1 3500 11 3600 1 3700 1 3900 1 4000 62 4500 5 4900 1 5000 89 6000 29 6500 1 7000 15 7500 1 8000 20 9000 5 9500 1 10000 26 11500 1 12000 4 13000 1 15000 4 17000 1 25000 1 30000 2 50000 1 Sysmiss 843 Expenditure in May on transport 1314 843 -99999 50000 -99999 2 -77777 NOT APPLICABLE 0 -88 DON'T KNOW 0 0 226 100 5 150 1 200 10 250 2 300 23 350 4 400 17 450 3 470 1 500 75 600 28 650 1 700 16 750 2 800 37 900 11 950 1 1000 139 1100 1 1200 30 1300 2 1400 3 1500 84 1600 6 1650 1 1700 1 1800 7 2000 146 2060 1 2100 1 2200 1 2300 1 2400 2 2500 43 2600 2 2700 3 2800 4 2900 4 3000 101 3200 2 3400 1 3500 12 3600 1 3700 2 3800 1 4000 60 4500 7 5000 73 5250 1 5500 2 6000 25 6050 1 7000 14 7500 1 8000 15 9000 9 9600 1 10000 24 10500 1 12000 3 13000 1 15000 4 17000 1 20000 1 30000 1 35000 1 50000 1 Sysmiss 843 Expenditure in June on transport 1314 843 -99999 80000 -99999 2 -77777 NOT APPLICABLE 0 -88 DON'T KNOW 0 0 275 100 1 200 14 250 2 300 14 350 4 400 10 450 1 470 1 500 63 560 1 600 31 650 1 700 17 750 2 800 36 900 11 950 2 1000 148 1200 20 1300 6 1350 1 1400 5 1500 72 1600 8 1700 4 1800 7 1900 1 2000 163 2200 2 2300 1 2400 1 2500 38 2600 2 2800 2 3000 95 3300 1 3500 14 3800 2 4000 58 4300 1 4500 4 4600 1 4800 1 5000 74 6000 30 6400 1 6500 1 7000 12 7300 1 8000 14 9000 5 10000 16 10500 1 12000 1 14000 3 15000 3 20000 1 25000 2 40000 1 50000 1 80000 1 Sysmiss 843 Expenditure in July on transport 1314 843 -99999 50000 -99999 2 -77777 NOT APPLICABLE 0 -88 DON'T KNOW 0 0 335 80 1 100 1 150 1 170 1 200 8 250 2 300 19 350 2 400 23 450 1 500 66 600 27 700 13 750 4 760 1 770 1 800 36 850 1 900 10 950 4 1000 163 1100 1 1150 1 1200 9 1250 1 1300 3 1400 5 1500 83 1600 3 1700 5 1800 10 2000 141 2200 1 2400 1 2500 32 2600 2 2700 1 2800 2 3000 80 3200 1 3500 11 3800 1 4000 56 4500 2 4800 2 5000 47 5400 1 5500 1 5600 1 6000 26 6400 1 6500 2 7000 16 8000 14 8800 1 10000 12 11000 1 12000 3 13500 1 15000 3 20000 5 25000 1 40000 1 50000 1 Sysmiss 843 Expenditure in August on transport 1314 843 -99999 50000 Expenditure in April on other household items 1314 843 -99999 100000 -99999 9 -77777 NOT APPLICABLE 0 -88 DON'T KNOW 0 0 48 60 1 90 1 100 5 120 1 150 2 160 2 190 1 200 26 230 1 240 1 250 3 300 25 350 2 400 21 450 3 480 2 500 88 540 1 550 3 600 39 640 1 650 1 670 1 700 28 750 4 800 42 850 2 900 18 950 4 1000 116 1010 1 1050 1 1100 2 1150 2 1200 18 1250 1 1300 9 1400 8 1500 59 1600 11 1700 3 1800 8 1900 2 2000 153 2050 1 2100 1 2300 1 2500 31 2600 1 2700 1 2800 6 2900 1 3000 128 3500 10 3800 1 4000 53 4500 4 4800 1 5000 81 5500 1 6000 26 6500 1 7000 13 8000 23 9000 8 10000 55 11000 1 12000 3 14000 2 15000 22 20000 20 22000 1 25000 6 28000 1 30000 12 45000 2 50000 5 58000 1 62000 1 70000 2 80000 3 95000 1 100000 3 Sysmiss 843 Expenditure in May on other household items 1314 843 -99999 200000 -99999 9 -77777 NOT APPLICABLE 0 -88 DON'T KNOW 0 0 56 50 2 60 1 80 1 100 1 105 1 150 4 160 1 200 25 250 4 300 19 307 1 350 2 360 1 400 18 450 6 480 2 500 71 550 1 570 1 600 30 650 1 700 19 720 1 750 2 800 33 850 2 900 11 950 2 1000 110 1010 1 1100 4 1150 1 1200 23 1300 8 1350 1 1400 7 1500 72 1600 10 1700 2 1800 14 1950 1 2000 162 2050 1 2100 1 2200 2 2300 4 2400 1 2500 45 2600 1 2700 2 2800 5 3000 104 3200 2 3500 15 3800 2 4000 49 4080 1 4500 6 4800 1 5000 81 5500 1 5700 1 6000 29 6500 3 7000 23 7500 1 8000 33 9000 11 10000 54 11000 2 11500 1 12000 6 13000 2 14000 2 15000 23 16000 1 18000 2 20000 17 24000 1 25000 7 30000 8 33000 1 35000 1 40000 1 45000 1 48000 1 50000 4 60000 3 89000 1 90000 2 100000 2 120000 1 200000 1 Sysmiss 843 Expenditure in June on other household items 1314 843 -99999 200000 -99999 9 -77777 NOT APPLICABLE 0 -88 DON'T KNOW 0 0 54 60 2 70 1 100 2 105 1 150 4 180 1 200 18 250 5 300 21 350 1 400 14 450 4 480 1 500 50 520 1 550 1 600 31 650 1 700 21 750 2 800 28 900 19 950 2 1000 95 1100 4 1150 1 1200 10 1300 7 1350 1 1400 1 1500 77 1600 10 1700 7 1800 10 1900 2 2000 151 2100 1 2400 2 2500 40 2700 1 2800 1 3000 118 3100 1 3500 14 3600 1 3800 1 4000 56 4300 1 4500 2 4600 1 4700 1 5000 91 6000 43 6500 2 7000 25 8000 34 8500 2 9000 11 9400 1 10000 68 11000 2 12000 3 14000 4 15000 27 16000 3 17000 1 20000 35 20500 1 22000 1 25000 10 26000 1 30000 10 30900 1 35000 3 36000 1 40000 2 45000 1 48000 1 50000 5 60000 3 65000 1 70000 2 80000 3 85000 1 90000 1 100000 2 200000 1 Sysmiss 843 Expenditure in July on other household items 1314 843 -99999 160000 -99999 9 -77777 NOT APPLICABLE 0 -88 DON'T KNOW 0 0 66 60 1 100 6 150 4 160 1 190 1 200 19 250 3 300 14 350 2 400 17 450 3 480 1 500 58 550 2 600 17 700 19 750 2 800 30 895 1 900 21 950 1 980 1 1000 103 1100 2 1150 1 1200 18 1290 1 1300 8 1400 4 1500 80 1550 1 1600 7 1700 9 1750 1 1800 4 2000 116 2050 1 2300 3 2400 1 2500 52 2600 1 2700 2 2800 2 3000 114 3100 1 3300 1 3500 17 3600 1 3800 2 4000 61 4200 2 4500 7 4800 2 5000 89 5500 3 6000 24 6500 2 6700 1 7000 39 7500 1 8000 31 9000 18 9700 1 10000 61 10500 1 11000 10 12000 11 14000 1 15000 29 18000 2 19000 1 20000 23 24000 1 25000 4 28000 1 30000 11 35000 4 40000 5 48000 1 50000 8 60000 1 80000 4 100000 1 160000 1 Sysmiss 843 Expenditure in August on other household items 1314 843 -99999 200000 How many days in April did you have less than 3 meals? 1314 843 0 30 How many days in May did you have less than 3 meals? 1314 843 0 31 How many days in June did you have less than 3 meals? 1314 843 0 31 How many days in July did you have less than 3 meals? 1314 843 -9 31 How many days in August did you have less than 3 meals? 1314 843 -9 31 How many days in April did children have less than 3 meals? 1314 843 -7 31 How many days in May did children have less than 3 meals? 1314 843 -7 31 How many days in June did children have less than 3 meals? 1314 843 -7 31 How many days in July did children have less than 3 meals? 1314 843 -9 31 How many days in August did children have less than 3 meals? 1314 843 -9 99 Change in later consumption upon revisiting 663 1494 -4000 3000 Change in sooner consumption upon revisiting 663 1494 -2000 2100 revisions present biased 663 1494 0 1 0 438 1 225 Sysmiss 1494 revisions future biased 663 1494 0 1 0 456 1 207 Sysmiss 1494 (mean) qualflag 2142 15 0 1 0 2025 1 117 Sysmiss 15 (mean) rlspsdiffc_f_soon 2142 15 -20 19 (mean) imple_rbasis 2078 79 -166.6 123.529 (mean) timeprefA 2142 15 0 1 0 1077 1 1065 Sysmiss 15 (mean) commitmentsavings 2142 15 0 1 0 1347 1 795 Sysmiss 15 (mean) ordinarysavings 2142 15 0 1 0 1128 1 1014 Sysmiss 15 (mean) wealth_bline_M 2142 15 4 69502.5 Ln(baseline wealth) 2142 15 1.386 11.149 (mean) z13_day 2142 15 1 31 (mean) z13_month 2142 15 1 2 1 809 2 1333 Sysmiss 15 Male 2142 15 0 1 0 1072 1 1070 Sysmiss 15 (mean) numinvillage 2142 15 0 4000 Number of relatives in the village 2142 15 0 132 Have adequate maize 2142 15 0 1 0 1679 1 463 Sysmiss 15 (mean) maizemissing 2142 15 0 1 0 2139 1 3 Sysmiss 15 Less than 35 yrs old 2142 15 0 1 0 1621 1 521 Sysmiss 15 35-37 yrs old 2142 15 0 1 0 1058 1 1084 Sysmiss 15 (mean) older 2142 15 0 1 0 1605 1 537 Sysmiss 15 (mean) no_school 2142 15 0 1 0 1783 1 359 Sysmiss 15 Some primary school 2142 15 0 1 0 837 1 1305 Sysmiss 15 Primary school 2142 15 0 1 0 1819 1 323 Sysmiss 15 More than primary school 2142 15 0 1 0 1987 1 155 Sysmiss 15 Words recalled 2142 15 0 10 0 4 1 10 2 68 3 235 4 530 5 672 6 431 7 154 8 33 9 4 10 1 Sysmiss 15 (mean) wrdrecal_1sq 2142 15 0 100 (mean) wrdrecal_2 2142 15 0 9 0 60 1 53 2 195 3 479 4 611 5 453 6 216 7 60 8 12 9 3 Sysmiss 15 (mean) wrdrecal_2sq 2142 15 0 81 (mean) rm1_correct 2142 15 0 1 0 574 1 1568 Sysmiss 15 (mean) rm2_correct 2142 15 0 1 0 1239 1 903 Sysmiss 15 (mean) rm3_correct 2142 15 0 1 0 1341 1 801 Sysmiss 15 Raven's Tests correct 2142 15 0 3 0 294 1 772 2 728 3 348 Sysmiss 15 (mean) finlit_1 2142 15 0 1 0 1583 1 559 Sysmiss 15 (mean) finlit_dk_1 2142 15 0 1 0 1843 1 299 Sysmiss 15 (mean) finlit_2 2142 15 0 1 0 1437 1 705 Sysmiss 15 (mean) finlit_dk_2 2142 15 0 1 0 1873 1 269 Sysmiss 15 (mean) finlit_3 2142 15 0 1 0 1836 1 306 Sysmiss 15 (mean) finlit_dk_3 2142 15 0 1 0 1873 1 269 Sysmiss 15 Financial literacy questions correct 2142 15 0 3 0 1221 1 452 2 289 3 180 Sysmiss 15 (mean) finlit_dk_total 2142 15 0 3 0 1722 1 151 2 121 3 148 Sysmiss 15 (mean) presbias 2142 15 0 1 (mean) presbias_2 2142 15 0 1 (mean) futurebias 2142 15 0 1 (mean) futurebias_2 2142 15 0 1 (mean) consistent 2142 15 0 1 (mean) consistent_2 2142 15 0 1 (mean) fracpb 2142 15 0 1 (mean) fracfb 2142 15 0 1 (mean) fracconsis 2142 15 0 1 (mean) fracpb_2 2142 15 0 1 (mean) fracfb_2 2142 15 0 1 (mean) fracconsis_2 2142 15 0 1 (mean) havedemos 2142 15 1 1 1 2142 Sysmiss 15 (mean) a1 2142 15 18 95 (mean) a2 2142 15 -99 95 (mean) a4 2142 15 0 77 (mean) b1_100 2142 15 0 20 (mean) b1_110 2142 15 0 20 (mean) b2_100 2142 15 0 20 (mean) b2_125 2142 15 0 20 (mean) b3_100 2142 15 0 20 0 306 1 54 2 91 3 86 4 120 5 205 6 126 7 109 8 166 9 139 10 294 11 89 12 111 13 43 14 40 15 51 16 28 17 18 18 14 19 8 20 44 Sysmiss 15 (mean) b3_150 2142 15 0 20 0 44 1 8 2 14 3 18 4 28 5 51 6 40 7 43 8 111 9 89 10 294 11 139 12 168 13 108 14 125 15 205 16 120 17 86 18 91 19 54 20 306 Sysmiss 15 (mean) b4_100 2142 15 0 20 (mean) b4_175 2142 15 0 20 (mean) b5_100 2142 15 0 20 (mean) b5_200 2142 15 0 20 (mean) b6_100 2142 15 0 20 0 193 1 38 2 70 3 65 4 86 5 164 6 140 7 117 8 223 9 174 10 367 11 89 12 124 13 47 14 59 15 47 16 29 17 15 18 18 19 9 20 68 Sysmiss 15 (mean) b6_110 2142 15 0 20 0 68 1 9 2 18 3 15 4 29 5 47 6 58 7 46 8 125 9 90 10 367 11 174 12 223 13 117 14 140 15 164 16 86 17 65 18 70 19 38 20 193 Sysmiss 15 (mean) b7_100 2142 15 0 20 (mean) b7_125 2142 15 0 20 (mean) b8_100 2142 15 0 20 0 295 1 49 2 88 3 95 4 106 5 195 6 143 7 132 8 200 9 137 10 259 11 82 12 96 13 47 14 50 15 57 16 20 17 21 18 13 19 4 20 53 Sysmiss 15 (mean) b8_150 2142 15 0 20 0 53 1 4 2 13 3 21 4 20 5 57 6 50 7 47 8 96 9 82 10 259 11 137 12 200 13 132 14 143 15 195 16 106 17 95 18 88 19 49 20 295 Sysmiss 15 (mean) b9_100 2142 15 0 20 (mean) b9_175 2142 15 0 20 (mean) b10_100 2142 15 0 20 (mean) b10_200 2142 15 0 20 Implemented interest rate \{.1, .25, .5, .75, 1\} 2142 15 0.1 1 merge variable 2142 15 2 3 2 688 3 1454 Sysmiss 15 Indicator: death in the family 1314 843 0 1 0 1280 1 34 Sysmiss 843 change in total household expenditure 1454 703 -5100 21050 Shortfall in expected HH income (MK) 1454 703 -4302 13735 indiv own transfer card 2142 15 1 10 1 58 2 69 3 98 4 131 5 328 6 222 7 262 8 258 9 386 10 330 Sysmiss 15 indiv own tokens - sooner 2142 15 0 20 0 295 1 49 2 88 3 95 4 106 5 195 6 143 7 132 8 200 9 137 10 259 11 82 12 96 13 47 14 50 15 57 16 20 17 21 18 13 19 4 20 53 Sysmiss 15 indiv own tokens - later 2142 15 0 20 0 53 1 4 2 13 3 21 4 20 5 57 6 50 7 47 8 96 9 82 10 259 11 137 12 200 13 132 14 143 15 195 16 106 17 95 18 88 19 49 20 295 Sysmiss 15 indiv own in mk - sooner 2142 15 0 2000 indiv own in mk - later 2142 15 0 4000 (mean) b1_100 2142 15 0 20 (mean) b1_110 2142 15 0 20 (mean) b2_100 2142 15 0 20 (mean) b2_125 2142 15 0 20 (mean) b3_100 2142 15 -9 20 (mean) b3_150 2142 15 -9 20 (mean) b4_100 2142 15 -9 20 (mean) b4_175 2142 15 -9 20 (mean) b5_100 2142 15 -9 20 (mean) b5_200 2142 15 -9 20 (mean) b6_100 2142 15 -9 20 (mean) b6_110 2142 15 -9 20 (mean) b7_100 2142 15 0 20 (mean) b7_125 2142 15 0 20 (mean) b8_100 2142 15 0 20 0 295 1 49 2 88 3 95 4 107 5 196 6 142 7 131 8 203 9 137 10 255 11 81 12 95 13 50 14 49 15 58 16 20 17 21 18 13 19 4 20 53 Sysmiss 15 (mean) b8_150 2142 15 0 20 0 53 1 4 2 13 3 21 4 20 5 58 6 49 7 50 8 95 9 81 10 255 11 137 12 203 13 131 14 142 15 196 16 107 17 95 18 88 19 49 20 295 Sysmiss 15 (mean) b9_100 2142 15 0 20 (mean) b9_175 2142 15 0 20 (mean) b10_100 2142 15 -9 20 (mean) b10_200 2142 15 -9 20 (mean) qualflag 2142 15 0 1 0 2025 1 117 Sysmiss 15 (mean) timeprefA 2142 15 0 1 0 1077 1 1065 Sysmiss 15 (mean) wealth_bline_M 2142 15 4 69502.5 (mean) frac_posdcs 2142 15 0.125 1 (mean) relatives 2139 18 0 132 (mean) havemaize 2142 15 0 1 0 1674 1 468 Sysmiss 15 (mean) younger 2142 15 0 1 0 1618 1 524 Sysmiss 15 (mean) middleage 2142 15 0 1 0 1061 1 1081 Sysmiss 15 (mean) some_primary 2142 15 0 1 0 834 1 1308 Sysmiss 15 (mean) primary 2142 15 0 1 0 1820 1 322 Sysmiss 15 (mean) morethan_primary 2142 15 0 1 0 1985 1 157 Sysmiss 15 (mean) wrdrecal_1 2142 15 0 10 0 4 1 10 2 68 3 235 4 530 5 668 6 438 7 152 8 32 9 4 10 1 Sysmiss 15 (mean) ravens 2142 15 0 3 0 296 1 773 2 726 3 347 Sysmiss 15 (mean) finlit_total 2142 15 0 3 0 1220 1 455 2 291 3 176 Sysmiss 15 (mean) presbias 2142 15 0 1 (mean) presbias_2 2142 15 0 1 (mean) futurebias 2142 15 0 1 (mean) futurebias_2 2142 15 0 1 (mean) consistent 2142 15 0 1 (mean) consistent_2 2142 15 0 1 (mean) fracpb 2142 15 0 1 (mean) fracfb 2142 15 0 1 (mean) fracconsis 2142 15 0 1 (mean) fracpb_2 2142 15 0 1 (mean) fracconsis_2 2142 15 0 1 spouse's transfer card 2142 15 1 10 1 58 2 69 3 98 4 131 5 328 6 222 7 262 8 258 9 386 10 330 Sysmiss 15 spouse's tokens - sooner 2142 15 0 20 0 295 1 49 2 88 3 95 4 107 5 196 6 142 7 131 8 203 9 137 10 255 11 81 12 95 13 50 14 49 15 58 16 20 17 21 18 13 19 4 20 53 Sysmiss 15 spouse's tokens - later 2142 15 0 20 0 53 1 4 2 13 3 21 4 20 5 58 6 49 7 50 8 95 9 81 10 255 11 137 12 203 13 131 14 142 15 196 16 107 17 95 18 88 19 49 20 295 Sysmiss 15 spouse's in mk - sooner 2142 15 0 2000 spouse's in mk - later 2142 15 0 4000 gap in tokens 2142 15 -20 20 gap in mk 2142 15 -4000 4000 which surveys 2089 68 1 6 1 Baseline=1 ; Middle=0 ; Endline=1 500 2 Baseline=1 ; Middle=1 ; Endline=1 1462 3 Baseline=1 ; Middle=0 ; Endline=0 56 4 Baseline=1 ; Middle=1 ; Endline=0 63 5 Baseline=0 ; Middle=0 ; Endline=1 2 6 Baseline=0 ; Middle=1 ; Endline=1 6 7 Baseline=0 ; Middle=1 ; Endline=0 0 Sysmiss 68 Randomization Strat var 2081 76 12 23 0 Pilot 0 1 Chatoloma 2 (AO-FC/B) - Mar 4-5 0 2 Chatoloma 1 (AO-FC) - Mar 6-7 0 3 Chatoloma 1 (AO-B) - Mar 6-7 0 4 Chatoloma 1 (AO-B) - Mar 9-10 0 5 Chatoloma 1 (AO-FC) - Mar 9-10 0 6 Chisinga (AO-FC) - Mar 12-14 0 7 Chisinga (AO-B) - Mar 12-14 0 8 Chisinga (AO-B) - Mar 16 0 9 Kasungu Central (AO-FC) - Mar 17-20 0 10 Kasungu Central (AO-B) - Mar 17-20 0 11 Chamwabvi (AO-B) - Mar 23-25 0 12 Mponela (AO-FC) - Mar 27-28 82 13 Mponela (AO-B) - Mar 27-28 300 14 Dzoole (AO-FC) - Mar 31-April 2 68 15 Dzoole (AO-B) - Mar 31-April 2 179 16 Chisepo (LL-DF) - Apr 2-3 0 17 Nachisaka (LL-DF) - Apr 6-7 0 18 Chibvala (LL-DF) - Apr 9-10 0 19 Nachisaka (LL-DF) - Apr 14-15 0 20 Mponela (LL-DF) - Apr 16-17 441 21 Mndolera (LL-DF) - Apr 18-20 360 22 Madisi (LL-DF) - Apr 21-22 260 23 Bowe (LL-DF) - Apr 23 391 Sysmiss 76 [HS14d]0/1: fixed deposit account at OIBM 1952 205 0 1 11 .B 18 [HS14]0/1: Any fixed deposit account, non-OIBM 1970 187 0 1 0 1913 1 57 Sysmiss 187 [HS14]0/1: Any fixed deposit account, any bank 1970 187 0 1 0 1821 1 149 Sysmiss 187 Treatment Group 2089 68 0 6 0 Control 284 1 Ordinary, no raffle 320 2 Ordinary, public raffle 358 3 Ordinary, private raffle 334 4 Commitment, no raffle 237 5 Commitment, public raffle 295 6 Commitment, private raffle 261 Sysmiss 68 [TR](MK)Total transfers received 1970 187 0 200000 [TR](MK)Total transfers received;TRIM(0&99) 1970 187 0 29000 trimmed at 0 and 99 percentiles [TR](MK)transfers received, big gift<=Oct09 1970 187 0 70000 [TR](MK)transfers received, big gift<=Oct09;TRIM(0&99); 1970 187 0 10000 trimmed at 0 and 99 percentiles [TR](MK)Total transfers sent 1970 187 0 205000 [TR](MK)transfers sent, big gift<=Oct09 1970 187 0 201000 [TR](MK)transfers sent, big gift<=Oct09;TRIM(0&99); 1970 187 0 10000 trimmed at 0 and 99 percentiles abrlspsdiffc_f_soon 2142 15 0 20 0 1421 1 91 2 92 3 83 4 83 5 70 6 55 7 43 8 54 9 31 10 47 11 20 12 14 13 10 14 4 15 7 16 1 17 5 18 5 19 2 20 4 Sysmiss 15 spsdiffpos 2142 15 0 1 0 390 1 1752 Sysmiss 15 pos_abrlspsdiffc_f_soon 2142 15 0 19 0 1811 1 44 2 55 3 42 4 38 5 32 6 25 7 20 8 26 9 11 10 18 11 5 12 3 13 5 15 2 16 1 18 3 19 1 Sysmiss 15 actual lag squared 662 1495 0 256 pb lag interaction 662 1495 0 16 net transfers 1970 187 -162200 70000 ini_pb_sim 2142 15 0 1 0 1931 1 211 Sysmiss 15 fracpbothersim 2142 15 0 1 club registration number 2142 15 220525 902176 Commitment Savings respondent ID / Revising Commitment HH ID 2081 76 125145301 325936510 0/1:male RC voucher holder 2081 76 0 1 0 1016 1 1065 Sysmiss 76 0/1:treatment=tmrw/1month (vs 2m/3m) 2081 76 0 1 0 1417 1 664 Sysmiss 76 treatment:interest rate offered 2081 76 10 100 urea per acre 2137 20 0 300 spouse bias sooner in mk 2142 15 -2000 2000 spouse bias - sooner 2142 15 -1850 1850 Spouse minus own allocation to sooner (MK) 2142 15 -1833.333 1833.333 spouse bias - near 2142 15 -2000 2000 spouse bias - far 2142 15 -2000 2000 spouse bias imp 1458 699 -2000 2000 spouse bias non-imp far 1458 699 -1875 1875 1 treatment 2142 15 0 1 0 1822 1 320 Sysmiss 15 2 treatment 2142 15 0 1 0 1784 1 358 Sysmiss 15 3 treatment 2142 15 0 1 0 1808 1 334 Sysmiss 15 4 treatment 2142 15 0 1 0 1905 1 237 Sysmiss 15 5 treatment 2142 15 0 1 0 1847 1 295 Sysmiss 15 6 treatment 2142 15 0 1 0 1881 1 261 Sysmiss 15 Difference between Soon and Far:MK in two months, for r=0.1 2142 15 -2000 2000 Difference between Soon and Far:MK in two months, for r=0.25 2142 15 -2000 2000 Difference between Soon and Far:MK in two months, for r=0.50 2142 15 -2000 2000 Difference between Soon and Far:MK in two months, for r=0.75 2142 15 -2000 2000 Difference between Soon and Far:MK in two months, for r=1.00 2142 15 -2000 2000 pb all 2142 15 -2000 2000 pb non-imp 2142 15 -2000 2000 pb imp 2142 15 -2000 2000 Indicator of Present Bias for Implemented Interest Rate 2142 15 0 1 0 1340 1 802 Sysmiss 15 frac pb 2, imp 2142 15 0 1 0 1516 1 626 Sysmiss 15 Indicator: days to first disbursement (targeted) $\leq 6$ 722 1435 0 1 0 471 1 251 Sysmiss 1435 target lag 7-11 722 1435 0 1 0 500 1 222 Sysmiss 1435 target lag 12-16 722 1435 0 1 0 473 1 249 Sysmiss 1435 HH total bank-BL 2142 15 0 540 HH case-BL 2142 15 0 340 exp income-BL 2142 15 0 1377 exp rev-BL 2142 15 0 1335 from selling items-BL 2142 15 0 5882.9 from selling animals-BL 2142 15 0 1236 Baseline wealth (100s of MK) 2142 15 0.4 6950.25 (mean) younger 2140 17 0 1 0 1503 1 637 Sysmiss 17 (mean) middleage 2140 17 0 1 0 1019 1 1121 Sysmiss 17 (mean) a1 2140 17 18 87 (mean) younger 2142 15 0 1 0 1736 1 406 Sysmiss 15 (mean) middleage 2142 15 0 1 0 1098 1 1044 Sysmiss 15 (mean) a1 2142 15 20 95 spouse age 2142 15 18 95 own_sooner_far_imp 1458 699 0 2000 dummy C1 1 663 1494 -2000 2100 dummy C1 1 663 1494 -2000 2100 indicator present bias 2, int. rate=0.10 2142 15 0 1 0 1472 1 670 Sysmiss 15 indicator present bias 2, int. rate=0.25 2142 15 0 1 0 1497 1 645 Sysmiss 15 indicator present bias 2, int. rate=0.50 2142 15 0 1 0 1555 1 587 Sysmiss 15 indicator present bias 2, int. rate=0.75 2142 15 0 1 0 1545 1 597 Sysmiss 15 indicator present bias 2, int. rate=1.0 2142 15 0 1 0 1580 1 562 Sysmiss 15 Fraction present-biased, non-implemented interest rates 2142 15 0 1 indicator future bias 2, int. rate=0.10 2142 15 0 1 0 1546 1 596 Sysmiss 15 indicator future bias 2, int. rate=0.25 2142 15 0 1 0 1581 1 561 Sysmiss 15 indicator future bias 2, int. rate=0.50 2142 15 0 1 0 1559 1 583 Sysmiss 15 indicator future bias 2, int. rate=0.75 2142 15 0 1 0 1611 1 531 Sysmiss 15 indicator future bias 2, int. rate=1.0 2142 15 0 1 0 1659 1 483 Sysmiss 15 Fraction future-biased, non-implemented interest rates 2142 15 0 1 indicator present bias, int. rate=0.10 2142 15 0 1 0 1290 1 852 Sysmiss 15 indicator present bias, int. rate=0.25 2142 15 0 1 0 1296 1 846 Sysmiss 15 indicator present bias, int. rate=0.50 2142 15 0 1 0 1358 1 784 Sysmiss 15 indicator present bias, int. rate=0.75 2142 15 0 1 0 1338 1 804 Sysmiss 15 indicator present bias, int. rate=1.0 2142 15 0 1 0 1387 1 755 Sysmiss 15 Fraction of Present Bias for Non-Implemented Interest Rate 2142 15 0 1 spouse's bias, non-imp, wt 1458 699 -1880.808 1880.808 present bias - wt 2142 15 -2000 2000 present bias, non-imp, wt 2142 15 -2000 2000 frac pb, wt 2142 15 0 1 frac pb 2, non-imp, wt 2142 15 0 1 improreturn .10 2142 15 0 1 0 1862 1 280 Sysmiss 15 improreturn .25 2142 15 0 1 0 1811 1 331 Sysmiss 15 improreturn .50 2142 15 0 1 0 1786 1 356 Sysmiss 15 improreturn .75 2142 15 0 1 0 1625 1 517 Sysmiss 15 improreturn 1.0 2142 15 0 1 0 1484 1 658 Sysmiss 15 spouse_sooner_nonimpfar 1458 699 0 2000 own_sooner_nonimpfar 1458 699 0 2000 spouse_sooner_far_imp 1458 699 -900 2000 indicator: sb near, 0.10 2142 15 0 1 0 1173 1 969 Sysmiss 15 indicator: sb near, 0.25 2142 15 0 1 0 1171 1 971 Sysmiss 15 indicator: sb near, 0.50 2142 15 0 1 0 1167 1 975 Sysmiss 15 indicator: sb near, 0.75 2142 15 0 1 0 1158 1 984 Sysmiss 15 indicator: sb near, 1.0 2142 15 0 1 0 1189 1 953 Sysmiss 15 indicator: sb far, 0.10 2142 15 0 1 0 1179 1 963 Sysmiss 15 indicator: sb far, 0.25 2142 15 0 1 0 1169 1 973 Sysmiss 15 indicator: sb far, 0.50 2142 15 0 1 0 1161 1 981 Sysmiss 15 indicator: sb far, 0.75 2142 15 0 1 0 1177 1 965 Sysmiss 15 indicator: sb far, 1.0 2142 15 0 1 0 1189 1 953 Sysmiss 15 indicator: sb near2, 0.10 2142 15 0 1 0 1323 1 819 Sysmiss 15 indicator: sb near2, 0.25 2142 15 0 1 0 1292 1 850 Sysmiss 15 indicator: sb near2, 0.50 2142 15 0 1 0 1293 1 849 Sysmiss 15 indicator: sb near2, 0.75 2142 15 0 1 0 1279 1 863 Sysmiss 15 indicator: sb near2, 1.0 2142 15 0 1 0 1285 1 857 Sysmiss 15 indicator: sb far2, 0.10 2142 15 0 1 0 1302 1 840 Sysmiss 15 indicator: sb far2, 0.25 2142 15 0 1 0 1293 1 849 Sysmiss 15 indicator: sb far2, 0.50 2142 15 0 1 0 1274 1 868 Sysmiss 15 indicator: sb far2, 0.75 2142 15 0 1 0 1276 1 866 Sysmiss 15 indicator: sb far2, 1.0 2142 15 0 1 0 1285 1 857 Sysmiss 15 frac sb near 2142 15 0 1 frac sb far 2142 15 0 1 frac sb 2142 15 0 1 frac sb far, non-imp 1458 699 0 1 frac sb, non-imp 1458 699 0 1 frac sb near2 2142 15 0 1 frac sb, far2 2142 15 0 1 frac sb 2 2142 15 0 1 frac sb far2, non-imp 1458 699 0 1 frac sb 2, non-imp 1458 699 0 1 attrition 1 722 1435 0 1 0 662 1 60 Sysmiss 1435 attrition 2 722 1435 0 1 0 662 1 60 Sysmiss 1435 z13_month==2 2142 15 0 1 0 809 1 1333 Sysmiss 15 z13_month==3 2142 15 0 0 0 2142 Sysmiss 15 2 target lag 722 1435 0 1 0 662 1 60 Sysmiss 1435 3 target lag 722 1435 0 1 0 679 1 43 Sysmiss 1435 4 target lag 722 1435 0 1 0 659 1 63 Sysmiss 1435 5 target lag 722 1435 0 1 0 681 1 41 Sysmiss 1435 6 target lag 722 1435 0 1 0 678 1 44 Sysmiss 1435 7 target lag 722 1435 0 1 0 681 1 41 Sysmiss 1435 8 target lag 722 1435 0 1 0 692 1 30 Sysmiss 1435 9 target lag 722 1435 0 1 0 672 1 50 Sysmiss 1435 10 target lag 722 1435 0 1 0 664 1 58 Sysmiss 1435 11 target lag 722 1435 0 1 0 679 1 43 Sysmiss 1435 12 target lag 722 1435 0 1 0 668 1 54 Sysmiss 1435 13 target lag 722 1435 0 1 0 679 1 43 Sysmiss 1435 14 target lag 722 1435 0 1 0 680 1 42 Sysmiss 1435 15 target lag 722 1435 0 1 0 669 1 53 Sysmiss 1435 16 target lag 722 1435 0 1 0 665 1 57 Sysmiss 1435 Near:MK tommorrow, for r=0.10 2142 15 0 2000 Near:MK tommorrow, for r=0.25 2142 15 0 2000 Near:MK tommorrow, for r=0.50 2142 15 0 2000 Near:MK tommorrow, for r=0.75 2142 15 0 2000 Near:MK tommorrow, for r=1.00 2142 15 0 2000 Near:MK in a Month, for r=0.10 2142 15 0 2200 Near:MK in a Month, for r=0.25 2142 15 0 2500 Near:MK in a Month, for r=0.50 2142 15 0 3000 Near:MK in a Month, for r=0.75 2142 15 0 3500 Near:MK in a Month, for r=1.00 2142 15 0 4000 Near: change in later consumption for change in r, 0.1 to 0.25 2142 15 -2200 2500 dcn_25_10pos 2142 15 0 1 0 488 1 1654 Sysmiss 15 siznegn_25_10 2142 15 0 2500 Near: change in later consumption for change in r, 0.25 to 0.50 2142 15 -2500 3000 dcn_50_25pos 2142 15 0 1 0 345 1 1797 Sysmiss 15 siznegn_50_25 2142 15 0 3000 Near: change in later consumption for change in r, 0.50 to 0.75 2142 15 -3000 3500 dcn_75_50pos 2142 15 0 1 0 427 1 1715 Sysmiss 15 siznegn_75_50 2142 15 0 3500 Near: change in later consumption for change in r, 0.75 to 1.00 2142 15 -3500 4000 dcn_100_75pos 2142 15 0 1 0 383 1 1759 Sysmiss 15 siznegn_100_75 2142 15 0 4000 Near: # (of 4) positive changes in later consumption with increase in r 2142 15 0 4 0 5 1 65 2 350 3 728 4 994 Sysmiss 15 avesiznegn 2142 15 0 3500 Far:MK in two months, for r=0.10 2142 15 0 2000 Far:MK in two months, for r=0.25 2142 15 0 2000 Far:MK in two months, for r=0.50 2142 15 0 2000 Far:MK in two months, for r=0.75 2142 15 0 2000 Far:MK in two months, for r=1.00 2142 15 0 2000 Far:MK in three months, for r=0.10 2142 15 0 2200 Far:MK in three months, for r=0.25 2142 15 0 2500 Far:MK in three months, for r=0.50 2142 15 0 3000 Far:MK in three months, for r=0.75 2142 15 0 3500 Far:MK in three months, for r=1.00 2142 15 0 4000 Far: change in later consumption for change in r, 0.1 to 0.25 2142 15 -2200 2500 dcf_25_10pos 2142 15 0 1 0 467 1 1675 Sysmiss 15 Far: change in later consumption for change in r, 0.25 to 0.50 2142 15 -2500 3000 dcf_50_25pos 2142 15 0 1 0 364 1 1778 Sysmiss 15 Far: change in later consumption for change in r, 0.50 to 0.75 2142 15 -3000 3500 dcf_75_50pos 2142 15 0 1 0 425 1 1717 Sysmiss 15 Far: change in later consumption for change in r, 0.75 to 1.00 2142 15 -3500 4000 dcf_100_75pos 2142 15 0 1 0 378 1 1764 Sysmiss 15 Far: # (of 4) positive changes in later consumption with increase in r 2142 15 0 4 0 9 1 59 2 344 3 733 4 997 Sysmiss 15 # (of 8) positive changes in later consumption with increase in r 2142 15 1 8 1 6 2 13 3 42 4 158 5 301 6 460 7 492 8 670 Sysmiss 15 Fraction of decisions consistent with law of demand 2142 15 0.125 1 number sooner 2142 15 0 200 Fraction of tokens allocated to 2142 15 0 1.111 elasticity of consumption period 2 share with interest rate, for tomorrow at r = 2157 0 -6.667 6.667 elasticity of consumption period 2 share with interest rate, for tomorrow at r = 2157 0 -4 4 elasticity of consumption period 2 share with interest rate, for tomorrow at r = 2157 0 -4 4 elasticity of consumption period 2 share with interest rate, for tomorrow at r = 2157 0 -4 4 average of elasticity for tomorrow 2157 0 -1.414 1.667 elasticity of consumption period 2 share with interest rate, in two months at r 2157 0 -6.667 6.667 elasticity of consumption period 2 share with interest rate, in two months at r 2157 0 -4 4 elasticity of consumption period 2 share with interest rate, in two months at r 2157 0 -4 4 elasticity of consumption period 2 share with interest rate, in two months at r 2157 0 -4 4 average of elasticity in two months 2157 0 -1.433 1.667 elas_f_average - elas_n_average 2157 0 -2.333 2.828 merge var 2157 0 2 3 2 15 3 2142 Respondent ID 10710 0 1234581011 3259365102 Account type 10710 0 10 100 Household ID 10710 0 123458101 325936510 Days to first disbursement at revisit (target) 3610 7100 2 16 2 300 3 215 4 315 5 205 6 220 7 205 8 150 9 250 10 290 11 215 12 270 13 215 14 210 15 265 16 285 Sysmiss 7100 Days to first disbursement at revisit (actual) 3310 7400 0 16 0 5 1 10 2 270 3 200 4 265 5 160 6 250 7 175 8 160 9 210 10 285 11 200 12 250 13 220 14 150 15 240 16 260 Sysmiss 7400 Initial sooner allocation (value, MK) 3610 7100 0 2000 Initial later allocation (beans) 3610 7100 0 20 0 85 1 5 2 35 3 20 4 30 5 75 6 65 7 85 8 185 9 200 10 405 11 180 12 335 13 170 14 230 15 305 16 155 17 115 18 190 19 95 20 645 Sysmiss 7100 Initial later allocation (value, MK) 3610 7100 0 4000 Final sooner allocation (MK) 3315 7395 0 2400 Final later allocation (MK) 3315 7395 0 4000 Expenditure in April on food 6570 4140 0 100000 -77777 NOT APPLICABLE 0 -88 DON'T KNOW 0 0 185 100 5 150 5 200 20 220 5 240 5 250 5 300 50 350 15 400 45 410 5 450 15 500 190 510 5 550 5 600 105 640 5 650 10 660 5 700 55 750 25 800 150 850 5 900 40 950 20 1000 585 1100 10 1200 80 1250 5 1260 5 1300 10 1400 25 1500 350 1550 5 1600 25 1700 20 1760 5 1800 60 1900 10 1960 5 2000 1105 2100 25 2180 5 2200 5 2250 5 2300 15 2400 25 2480 5 2500 175 2600 15 2620 5 2700 20 2750 5 2800 65 2850 10 2900 5 3000 770 3200 10 3280 10 3400 5 3420 5 3500 105 3600 15 3700 10 3800 20 4000 395 4200 10 4300 5 4400 5 4500 55 4700 5 4800 10 5000 565 5200 5 5600 5 6000 225 6400 5 6500 10 6700 5 6950 5 7000 70 7500 5 8000 90 8500 5 9000 20 9500 5 10000 200 11000 10 12000 30 15000 50 16000 5 20000 55 21000 5 23000 5 25000 15 30000 25 35000 5 40000 15 50000 15 70000 5 100000 5 Sysmiss 4140 Expenditure in May on food 6570 4140 0 50000 -77777 NOT APPLICABLE 0 -88 DON'T KNOW 0 0 245 100 10 200 15 220 5 300 40 350 5 360 5 400 70 450 5 500 230 560 5 600 80 700 55 750 15 800 65 900 55 950 5 1000 640 1100 25 1200 95 1250 5 1300 10 1400 15 1500 495 1600 35 1700 25 1800 40 1840 5 1960 5 2000 1055 2100 25 2180 5 2250 5 2400 10 2500 390 2620 5 2700 15 2800 35 2850 10 2900 5 3000 685 3200 5 3280 10 3400 20 3500 150 3600 5 3650 5 3700 10 3750 5 3800 20 3900 5 4000 350 4500 55 4600 5 4700 5 4800 5 5000 515 5300 5 5500 10 5600 10 6000 210 6800 5 7000 80 7500 5 8000 110 9000 45 9500 5 10000 125 10425 5 11000 5 12000 30 13000 5 15000 50 16000 5 17250 5 20000 75 23000 5 25000 15 30000 10 40000 15 45000 5 50000 10 Sysmiss 4140 Expenditure in June on food 6570 4140 0 100000 -77777 NOT APPLICABLE 0 -88 DON'T KNOW 0 0 250 100 30 200 25 220 5 300 35 400 35 450 5 480 5 500 155 600 90 700 50 800 75 870 5 900 20 1000 580 1200 55 1300 20 1400 15 1480 5 1500 520 1600 10 1700 25 1750 5 1800 65 1900 5 2000 1065 2100 15 2180 5 2200 5 2400 10 2500 385 2560 5 2600 30 2620 5 2700 5 2800 35 2850 5 2900 10 3000 840 3200 5 3280 5 3300 10 3400 15 3500 140 3600 5 3700 5 3800 10 4000 440 4200 15 4500 40 4600 5 5000 540 5500 5 6000 240 7000 115 7400 5 7500 5 7750 5 8000 115 9000 25 10000 100 10425 5 11000 25 12000 20 15000 65 16000 5 18000 15 20000 20 23000 5 25000 10 27000 5 30000 15 35000 5 50000 5 60000 5 100000 5 Sysmiss 4140 Expenditure in July on food 6570 4140 0 100000 -77777 NOT APPLICABLE 0 -88 DON'T KNOW 0 0 265 100 20 200 25 220 5 250 5 300 35 350 5 400 40 500 170 600 55 700 55 750 5 800 135 900 50 1000 460 1140 5 1200 30 1300 10 1400 5 1460 5 1500 540 1600 35 1640 5 1700 5 1800 85 1900 5 2000 1110 2100 10 2180 5 2200 20 2250 5 2300 10 2400 5 2500 340 2560 5 2600 10 2620 5 2700 5 2800 35 2850 10 2900 5 3000 780 3050 5 3200 5 3280 5 3300 5 3400 15 3500 180 3700 10 3800 10 3880 5 4000 415 4200 10 4500 50 4600 5 4800 5 5000 565 5400 5 5500 10 6000 220 6500 15 7000 170 7500 5 8000 100 9000 55 9500 5 10000 105 10425 5 10500 5 11000 5 12000 15 13000 5 14000 5 15000 15 16000 5 18000 10 20000 35 23000 5 25000 15 30000 20 35000 5 50000 10 60000 5 100000 5 Sysmiss 4140 Expenditure in August on food 6570 4140 0 100000 Expenditure in April on medicine 6570 4140 0 35000 -77777 NOT APPLICABLE 0 -88 DON'T KNOW 0 0 420 20 10 25 5 40 15 50 75 60 5 80 5 90 5 100 335 120 5 150 95 180 5 200 775 250 90 300 420 350 10 380 5 400 250 450 25 480 5 500 1220 550 5 600 225 650 5 700 120 800 115 900 45 950 5 1000 600 1200 25 1300 10 1450 5 1500 260 1600 10 1700 20 1800 15 2000 575 2500 40 2800 10 3000 220 3500 15 4000 95 4500 10 5000 180 5500 5 6000 40 7000 25 8000 15 10000 65 12000 5 20000 15 35000 10 Sysmiss 4140 Expenditure in May on medicine 6570 4140 0 45000 -77777 NOT APPLICABLE 0 -88 DON'T KNOW 0 0 505 10 5 20 10 30 5 40 5 50 75 60 10 70 10 80 15 100 295 120 5 150 180 170 5 200 620 250 135 300 475 320 5 350 45 400 300 450 40 480 15 500 1015 550 5 600 220 650 5 700 175 750 30 760 5 800 160 850 5 900 30 950 5 1000 605 1200 25 1300 10 1400 10 1500 230 1600 5 1800 20 2000 490 2200 5 2500 75 2800 5 2900 5 3000 235 3200 5 3500 40 3700 5 3800 5 4000 100 4500 5 5000 95 6000 45 6500 5 7000 20 8000 35 10000 35 11000 5 12000 5 15000 5 30000 10 40000 10 45000 5 Sysmiss 4140 Expenditure in June on medicine 6570 4140 0 45000 -77777 NOT APPLICABLE 0 -88 DON'T KNOW 0 0 545 20 5 30 5 50 95 60 5 80 10 100 225 150 140 180 5 200 550 250 135 300 435 330 5 350 55 390 5 400 295 410 5 450 15 500 1000 550 10 600 265 650 5 700 260 750 5 800 250 850 5 900 60 1000 530 1100 5 1200 60 1300 25 1400 10 1500 270 1600 5 1700 10 1800 15 1900 5 2000 455 2300 5 2400 10 2500 85 2900 5 3000 230 3400 5 3500 35 4000 100 4300 5 4500 15 5000 90 5600 5 6000 65 7000 10 8000 35 9000 10 10000 30 12000 20 15000 5 40000 10 45000 10 Sysmiss 4140 Expenditure in July on medicine 6570 4140 0 60000 -77777 NOT APPLICABLE 0 -88 DON'T KNOW 0 0 595 20 10 40 10 50 60 70 10 80 5 90 10 100 260 150 140 200 495 250 100 280 5 300 470 350 50 360 10 370 5 400 305 450 15 500 930 550 10 600 295 650 5 700 210 750 15 800 265 850 5 900 65 950 10 1000 670 1100 5 1200 40 1300 20 1400 25 1500 235 1700 5 1800 5 1900 5 2000 375 2300 10 2400 5 2500 120 2700 5 2800 5 2900 5 3000 185 3100 5 3300 5 3400 5 3500 20 3600 5 3800 5 4000 125 4500 5 5000 85 5500 5 5600 5 6000 45 6500 10 7000 35 8000 20 9000 10 10000 50 11000 5 12000 10 15000 5 20000 5 35000 5 45000 5 50000 5 60000 5 Sysmiss 4140 Expenditure in August on medicine 6570 4140 -99999 70000 Expenditure in April on school fees 6570 4140 0 305000 -77777 NOT APPLICABLE 0 -88 DON'T KNOW 0 0 5660 30 5 100 5 150 5 200 5 300 15 400 5 450 10 500 10 750 5 800 10 1000 15 1050 5 1200 5 1300 10 1500 50 1700 5 1740 5 1750 5 1800 5 1850 5 1900 5 2000 55 2100 5 2200 15 2250 10 2360 5 2400 5 2500 145 2700 5 2800 5 3000 65 3400 5 3500 15 3600 5 3800 10 4000 55 4060 10 4150 5 4400 5 4500 15 5000 30 5400 5 5500 5 6000 35 7000 5 7500 10 7800 5 8000 45 8250 5 8500 20 8700 10 8750 5 9000 5 9500 5 10000 10 11000 15 11500 10 11800 5 15000 5 24000 5 26000 15 26500 5 30000 5 50000 5 85000 5 305000 5 Sysmiss 4140 Expenditure in May on school fees 6570 4140 0 20000 -77777 NOT APPLICABLE 0 -88 DON'T KNOW 0 0 6185 100 5 150 5 200 5 250 5 300 15 450 10 500 5 800 10 1000 10 1500 5 1700 5 1800 10 2000 30 2050 10 2100 5 2140 5 2200 5 2250 5 2400 5 2500 50 2700 5 3000 15 3800 5 4000 15 4060 5 4400 5 4500 20 5000 10 6000 5 6500 5 7500 5 7550 5 7800 5 7950 5 8000 15 8500 10 8600 5 9500 10 10000 10 13200 5 15000 10 20000 5 Sysmiss 4140 Expenditure in June on school fees 6570 4140 0 56000 -77777 NOT APPLICABLE 0 -88 DON'T KNOW 0 0 5655 100 5 150 10 200 5 250 5 300 15 450 10 500 5 800 5 900 5 1000 25 1200 5 1300 5 1500 15 1550 5 1700 10 1750 5 1800 25 1850 5 1900 5 2000 60 2030 5 2050 5 2250 15 2300 5 2350 5 2400 10 2450 5 2500 85 2590 5 2600 15 2700 10 2800 5 3000 75 3400 5 3500 45 3600 5 3800 10 3900 5 4000 30 4060 5 4200 5 4400 5 4500 20 5000 35 5500 5 5700 5 6000 20 6500 15 6900 5 7000 15 7250 5 7500 5 7750 5 8000 80 8500 15 8950 5 9000 10 9800 5 10000 20 10200 5 11000 5 14000 5 15000 10 18000 5 24000 5 28000 5 30000 5 50000 5 56000 5 Sysmiss 4140 Expenditure in July on school fees 6570 4140 0 305000 -77777 NOT APPLICABLE 0 -88 DON'T KNOW 0 0 5920 100 5 150 10 200 5 250 5 300 15 450 10 500 10 1000 5 1200 5 1300 10 1500 45 1700 5 1740 5 1750 5 1800 10 1900 5 2000 35 2030 10 2050 10 2100 5 2200 10 2250 5 2500 80 2850 5 3000 45 3500 20 3800 5 4000 20 4200 5 4400 5 4500 10 5000 25 5400 5 5500 5 6000 20 7500 10 7800 5 8000 25 8500 20 8700 5 9000 15 9500 5 10000 25 11000 15 11500 5 11800 5 12000 10 26000 10 26500 5 85000 5 305000 5 Sysmiss 4140 Expenditure in August on school fees 6570 4140 0 85000 Expenditure in April on farm expenditures 6570 4140 -99999 100000 -99999 5 -77777 NOT APPLICABLE 0 -88 DON'T KNOW 0 0 2045 200 10 300 20 400 10 500 120 600 60 650 5 700 50 800 50 850 5 900 35 950 5 1000 305 1200 55 1300 10 1400 15 1500 210 1600 15 1700 15 1800 25 1900 5 2000 720 2250 5 2300 10 2400 5 2500 160 2700 10 2800 10 3000 605 3400 5 3500 75 3600 10 3950 5 4000 300 4500 25 4800 10 5000 530 5400 5 5500 5 5600 5 5700 5 5800 5 6000 205 6800 5 7000 100 7500 5 7800 5 8000 115 9000 50 10000 225 11000 5 12000 35 13000 5 13600 5 14000 10 15000 100 20000 55 25000 10 30000 20 35000 10 75000 5 95000 5 99000 5 100000 5 Sysmiss 4140 Expenditure in May on farm expenditures 6570 4140 -99999 100000 -99999 5 -77777 NOT APPLICABLE 0 -88 DON'T KNOW 0 0 1735 150 5 200 5 250 10 280 5 300 20 400 20 500 120 600 45 650 5 700 30 750 5 800 60 900 5 1000 370 1100 5 1200 60 1300 10 1400 10 1500 295 1600 30 1650 5 1700 5 1800 35 2000 780 2100 10 2200 10 2300 5 2500 175 2600 5 2700 5 2800 5 2900 5 3000 650 3200 5 3500 90 3600 5 3700 5 4000 400 4200 5 4400 5 4500 45 4700 5 5000 495 5500 5 5700 5 5800 5 6000 225 6500 5 7000 110 7500 15 7700 5 8000 115 9000 50 10000 155 11000 15 12000 50 13000 5 14000 15 15000 100 18000 5 20000 40 24000 5 25000 5 30000 10 35000 5 50000 5 100000 5 Sysmiss 4140 Expenditure in June on farm expenditures 6570 4140 -99999 150000 -99999 5 -77777 NOT APPLICABLE 0 -88 DON'T KNOW 0 0 2590 100 5 150 5 200 15 250 10 280 5 300 20 400 15 450 5 500 130 600 50 650 5 700 80 800 55 900 25 1000 470 1200 65 1300 5 1350 5 1400 10 1500 240 1700 30 1800 10 2000 530 2050 5 2500 140 2600 10 2800 5 3000 400 3400 10 3500 75 3600 5 3750 5 3800 10 4000 230 4500 15 4800 5 5000 465 5300 10 5500 10 5600 5 6000 145 6500 5 7000 105 7500 20 8000 105 8700 5 9000 35 10000 105 10500 5 11000 5 12000 20 13000 20 15000 40 16000 5 20000 50 22000 5 25000 10 30000 45 32000 5 35000 5 37000 5 40000 5 44200 5 60000 5 70000 5 100000 5 105000 5 150000 5 Sysmiss 4140 Expenditure in july on farm expenditures 6570 4140 -99999 205000 -99999 5 -77777 NOT APPLICABLE 0 -88 DON'T KNOW 0 0 3010 200 35 250 5 300 15 350 5 400 10 450 5 500 130 600 40 700 65 750 5 800 50 900 45 1000 360 1200 25 1400 5 1500 280 1600 10 1700 10 1800 35 1900 5 2000 450 2200 5 2300 10 2500 115 2700 10 2800 15 2950 5 3000 370 3500 55 4000 210 5000 310 5500 10 5800 5 6000 130 6300 5 7000 90 7500 20 8000 100 8500 5 9000 50 9500 5 10000 95 10500 5 11000 5 11500 5 12000 30 13000 5 14000 5 15000 70 15700 5 17000 5 18000 5 18450 5 19000 5 20000 85 25000 10 30000 20 31000 5 32000 5 35000 10 37000 5 40000 10 45000 10 50000 30 205000 5 Sysmiss 4140 Expenditure in August on farm expenditures 6570 4140 -99999 300000 Expenditure in April on transport 6570 4140 -99999 50000 -99999 10 -77777 NOT APPLICABLE 0 -88 DON'T KNOW 0 0 1015 150 5 200 85 250 10 300 150 350 15 400 135 450 15 500 360 600 140 670 5 700 70 750 20 800 200 850 5 900 55 1000 760 1150 5 1200 115 1250 5 1300 5 1350 5 1400 25 1500 335 1600 30 1700 20 1800 45 2000 705 2300 5 2400 20 2500 175 2600 5 2800 20 2900 5 3000 565 3200 5 3500 55 3600 5 3700 5 3900 5 4000 310 4500 25 4900 5 5000 445 6000 145 6500 5 7000 75 7500 5 8000 100 9000 25 9500 5 10000 130 11500 5 12000 20 13000 5 15000 20 17000 5 25000 5 30000 10 50000 5 Sysmiss 4140 Expenditure in May on transport 6570 4140 -99999 50000 -99999 10 -77777 NOT APPLICABLE 0 -88 DON'T KNOW 0 0 1130 100 25 150 5 200 50 250 10 300 115 350 20 400 85 450 15 470 5 500 375 600 140 650 5 700 80 750 10 800 185 900 55 950 5 1000 695 1100 5 1200 150 1300 10 1400 15 1500 420 1600 30 1650 5 1700 5 1800 35 2000 730 2060 5 2100 5 2200 5 2300 5 2400 10 2500 215 2600 10 2700 15 2800 20 2900 20 3000 505 3200 10 3400 5 3500 60 3600 5 3700 10 3800 5 4000 300 4500 35 5000 365 5250 5 5500 10 6000 125 6050 5 7000 70 7500 5 8000 75 9000 45 9600 5 10000 120 10500 5 12000 15 13000 5 15000 20 17000 5 20000 5 30000 5 35000 5 50000 5 Sysmiss 4140 Expenditure in June on transport 6570 4140 -99999 80000 -99999 10 -77777 NOT APPLICABLE 0 -88 DON'T KNOW 0 0 1375 100 5 200 70 250 10 300 70 350 20 400 50 450 5 470 5 500 315 560 5 600 155 650 5 700 85 750 10 800 180 900 55 950 10 1000 740 1200 100 1300 30 1350 5 1400 25 1500 360 1600 40 1700 20 1800 35 1900 5 2000 815 2200 10 2300 5 2400 5 2500 190 2600 10 2800 10 3000 475 3300 5 3500 70 3800 10 4000 290 4300 5 4500 20 4600 5 4800 5 5000 370 6000 150 6400 5 6500 5 7000 60 7300 5 8000 70 9000 25 10000 80 10500 5 12000 5 14000 15 15000 15 20000 5 25000 10 40000 5 50000 5 80000 5 Sysmiss 4140 Expenditure in July on transport 6570 4140 -99999 50000 -99999 10 -77777 NOT APPLICABLE 0 -88 DON'T KNOW 0 0 1675 80 5 100 5 150 5 170 5 200 40 250 10 300 95 350 10 400 115 450 5 500 330 600 135 700 65 750 20 760 5 770 5 800 180 850 5 900 50 950 20 1000 815 1100 5 1150 5 1200 45 1250 5 1300 15 1400 25 1500 415 1600 15 1700 25 1800 50 2000 705 2200 5 2400 5 2500 160 2600 10 2700 5 2800 10 3000 400 3200 5 3500 55 3800 5 4000 280 4500 10 4800 10 5000 235 5400 5 5500 5 5600 5 6000 130 6400 5 6500 10 7000 80 8000 70 8800 5 10000 60 11000 5 12000 15 13500 5 15000 15 20000 25 25000 5 40000 5 50000 5 Sysmiss 4140 Expenditure in August on transport 6570 4140 -99999 50000 Expenditure in April on other household items 6570 4140 -99999 100000 -99999 45 -77777 NOT APPLICABLE 0 -88 DON'T KNOW 0 0 240 60 5 90 5 100 25 120 5 150 10 160 10 190 5 200 130 230 5 240 5 250 15 300 125 350 10 400 105 450 15 480 10 500 440 540 5 550 15 600 195 640 5 650 5 670 5 700 140 750 20 800 210 850 10 900 90 950 20 1000 580 1010 5 1050 5 1100 10 1150 10 1200 90 1250 5 1300 45 1400 40 1500 295 1600 55 1700 15 1800 40 1900 10 2000 765 2050 5 2100 5 2300 5 2500 155 2600 5 2700 5 2800 30 2900 5 3000 640 3500 50 3800 5 4000 265 4500 20 4800 5 5000 405 5500 5 6000 130 6500 5 7000 65 8000 115 9000 40 10000 275 11000 5 12000 15 14000 10 15000 110 20000 100 22000 5 25000 30 28000 5 30000 60 45000 10 50000 25 58000 5 62000 5 70000 10 80000 15 95000 5 100000 15 Sysmiss 4140 Expenditure in May on other household items 6570 4140 -99999 200000 -99999 45 -77777 NOT APPLICABLE 0 -88 DON'T KNOW 0 0 280 50 10 60 5 80 5 100 5 105 5 150 20 160 5 200 125 250 20 300 95 307 5 350 10 360 5 400 90 450 30 480 10 500 355 550 5 570 5 600 150 650 5 700 95 720 5 750 10 800 165 850 10 900 55 950 10 1000 550 1010 5 1100 20 1150 5 1200 115 1300 40 1350 5 1400 35 1500 360 1600 50 1700 10 1800 70 1950 5 2000 810 2050 5 2100 5 2200 10 2300 20 2400 5 2500 225 2600 5 2700 10 2800 25 3000 520 3200 10 3500 75 3800 10 4000 245 4080 5 4500 30 4800 5 5000 405 5500 5 5700 5 6000 145 6500 15 7000 115 7500 5 8000 165 9000 55 10000 270 11000 10 11500 5 12000 30 13000 10 14000 10 15000 115 16000 5 18000 10 20000 85 24000 5 25000 35 30000 40 33000 5 35000 5 40000 5 45000 5 48000 5 50000 20 60000 15 89000 5 90000 10 100000 10 120000 5 200000 5 Sysmiss 4140 Expenditure in June on other household items 6570 4140 -99999 200000 -99999 45 -77777 NOT APPLICABLE 0 -88 DON'T KNOW 0 0 270 60 10 70 5 100 10 105 5 150 20 180 5 200 90 250 25 300 105 350 5 400 70 450 20 480 5 500 250 520 5 550 5 600 155 650 5 700 105 750 10 800 140 900 95 950 10 1000 475 1100 20 1150 5 1200 50 1300 35 1350 5 1400 5 1500 385 1600 50 1700 35 1800 50 1900 10 2000 755 2100 5 2400 10 2500 200 2700 5 2800 5 3000 590 3100 5 3500 70 3600 5 3800 5 4000 280 4300 5 4500 10 4600 5 4700 5 5000 455 6000 215 6500 10 7000 125 8000 170 8500 10 9000 55 9400 5 10000 340 11000 10 12000 15 14000 20 15000 135 16000 15 17000 5 20000 175 20500 5 22000 5 25000 50 26000 5 30000 50 30900 5 35000 15 36000 5 40000 10 45000 5 48000 5 50000 25 60000 15 65000 5 70000 10 80000 15 85000 5 90000 5 100000 10 200000 5 Sysmiss 4140 Expenditure in July on other household items 6570 4140 -99999 160000 -99999 45 -77777 NOT APPLICABLE 0 -88 DON'T KNOW 0 0 330 60 5 100 30 150 20 160 5 190 5 200 95 250 15 300 70 350 10 400 85 450 15 480 5 500 290 550 10 600 85 700 95 750 10 800 150 895 5 900 105 950 5 980 5 1000 515 1100 10 1150 5 1200 90 1290 5 1300 40 1400 20 1500 400 1550 5 1600 35 1700 45 1750 5 1800 20 2000 580 2050 5 2300 15 2400 5 2500 260 2600 5 2700 10 2800 10 3000 570 3100 5 3300 5 3500 85 3600 5 3800 10 4000 305 4200 10 4500 35 4800 10 5000 445 5500 15 6000 120 6500 10 6700 5 7000 195 7500 5 8000 155 9000 90 9700 5 10000 305 10500 5 11000 50 12000 55 14000 5 15000 145 18000 10 19000 5 20000 115 24000 5 25000 20 28000 5 30000 55 35000 20 40000 25 48000 5 50000 40 60000 5 80000 20 100000 5 160000 5 Sysmiss 4140 Expenditure in August on other household items 6570 4140 -99999 200000 How many days in April did you have less than 3 meals? 6570 4140 0 30 How many days in May did you have less than 3 meals? 6570 4140 0 31 How many days in June did you have less than 3 meals? 6570 4140 0 31 How many days in July did you have less than 3 meals? 6570 4140 -9 31 How many days in August did you have less than 3 meals? 6570 4140 -9 31 How many days in April did children have less than 3 meals? 6570 4140 -7 31 How many days in May did children have less than 3 meals? 6570 4140 -7 31 How many days in June did children have less than 3 meals? 6570 4140 -7 31 How many days in July did children have less than 3 meals? 6570 4140 -9 31 How many days in August did children have less than 3 meals? 6570 4140 -9 99 Change in later consumption upon revisiting 3305 7405 -4000 3000 Change in sooner consumption upon revisiting 3290 7420 -2000 2100 revisions present biased 3315 7395 0 1 0 2190 1 1125 Sysmiss 7395 revisions future biased 3315 7395 0 1 0 2280 1 1035 Sysmiss 7395 (mean) qualflag 10710 0 0 1 0 10125 1 585 (mean) rlspsdiffc_f_soon 10710 0 -20 19 (mean) imple_rbasis 10390 320 -166.6 123.529 (mean) timeprefA 10710 0 0 1 0 5385 1 5325 (mean) commitmentsavings 10710 0 0 1 0 6735 1 3975 (mean) ordinarysavings 10710 0 0 1 0 5640 1 5070 (mean) wealth_bline_M 10710 0 4 69502.5 (mean) z13_day 10710 0 1 31 (mean) z13_month 10710 0 1 2 1 4045 2 6665 Male 10710 0 0 1 0 5360 1 5350 (mean) numinvillage 10710 0 0 4000 Number of relatives in the village 10710 0 0 132 Have adequate maize 10710 0 0 1 0 8395 1 2315 (mean) maizemissing 10710 0 0 1 0 10695 1 15 Less than 35 yrs old 10710 0 0 1 0 8105 1 2605 35-37 yrs old 10710 0 0 1 0 5290 1 5420 (mean) older 10710 0 0 1 0 8025 1 2685 (mean) no_school 10710 0 0 1 0 8915 1 1795 Some primary school 10710 0 0 1 0 4185 1 6525 Primary school 10710 0 0 1 0 9095 1 1615 More than primary school 10710 0 0 1 0 9935 1 775 Words recalled 10710 0 0 10 0 20 1 50 2 340 3 1175 4 2650 5 3360 6 2155 7 770 8 165 9 20 10 5 (mean) wrdrecal_1sq 10710 0 0 100 (mean) wrdrecal_2 10710 0 0 9 0 300 1 265 2 975 3 2395 4 3055 5 2265 6 1080 7 300 8 60 9 15 (mean) wrdrecal_2sq 10710 0 0 81 (mean) rm1_correct 10710 0 0 1 0 2870 1 7840 (mean) rm2_correct 10710 0 0 1 0 6195 1 4515 (mean) rm3_correct 10710 0 0 1 0 6705 1 4005 Raven's Tests correct 10710 0 0 3 0 1470 1 3860 2 3640 3 1740 (mean) finlit_1 10710 0 0 1 0 7915 1 2795 (mean) finlit_dk_1 10710 0 0 1 0 9215 1 1495 (mean) finlit_2 10710 0 0 1 0 7185 1 3525 (mean) finlit_dk_2 10710 0 0 1 0 9365 1 1345 (mean) finlit_3 10710 0 0 1 0 9180 1 1530 (mean) finlit_dk_3 10710 0 0 1 0 9365 1 1345 Financial literacy questions correct 10710 0 0 3 0 6105 1 2260 2 1445 3 900 (mean) finlit_dk_total 10710 0 0 3 0 8610 1 755 2 605 3 740 (mean) a1 10710 0 18 95 (mean) a2 10710 0 -99 95 (mean) a4 10710 0 0 77 (mean) b1_100 10710 0 0 20 0 1050 1 190 2 290 3 280 4 380 5 790 6 610 7 570 8 1230 9 805 10 1905 11 450 12 690 13 235 14 230 15 300 16 115 17 85 18 90 19 55 20 360 (mean) b1_110 10710 0 0 20 0 360 1 55 2 90 3 85 4 115 5 300 6 230 7 235 8 685 9 455 10 1905 11 805 12 1230 13 570 14 610 15 795 16 380 17 275 18 290 19 190 20 1050 (mean) b2_100 10710 0 0 20 0 1215 1 220 2 350 3 380 4 455 5 890 6 760 7 710 8 970 9 775 10 1455 11 495 12 595 13 275 14 250 15 330 16 90 17 70 18 110 19 45 20 270 (mean) b2_125 10710 0 0 20 0 270 1 45 2 110 3 70 4 95 5 325 6 250 7 275 8 595 9 495 10 1455 11 775 12 970 13 705 14 765 15 885 16 455 17 385 18 350 19 220 20 1215 (mean) b3_100 10710 0 0 20 0 1530 1 270 2 455 3 430 4 600 5 1025 6 630 7 545 8 830 9 695 10 1470 11 445 12 555 13 215 14 200 15 255 16 140 17 90 18 70 19 40 20 220 (mean) b3_150 10710 0 0 20 0 220 1 40 2 70 3 90 4 140 5 255 6 200 7 215 8 555 9 445 10 1470 11 695 12 840 13 540 14 625 15 1025 16 600 17 430 18 455 19 270 20 1530 (mean) b4_100 10710 0 0 20 0 1545 1 335 2 500 3 450 4 645 5 925 6 745 7 600 8 660 9 670 10 1260 11 425 12 560 13 310 14 230 15 175 16 155 17 90 18 135 19 20 20 275 (mean) b4_175 10710 0 0 20 0 275 1 20 2 135 3 90 4 155 5 175 6 230 7 310 8 560 9 425 10 1260 11 670 12 665 13 595 14 750 15 925 16 645 17 450 18 495 19 335 20 1545 (mean) b5_100 10710 0 0 20 0 2155 1 335 2 700 3 560 4 520 5 840 6 605 7 515 8 680 9 480 10 1215 11 405 12 440 13 175 14 245 15 265 16 110 17 70 18 90 19 60 20 245 (mean) b5_200 10710 0 0 20 0 245 1 60 2 90 3 70 4 110 5 265 6 240 7 175 8 445 9 405 10 1225 11 480 12 680 13 505 14 610 15 835 16 520 17 560 18 695 19 335 20 2160 (mean) b6_100 10710 0 0 20 0 965 1 190 2 350 3 325 4 430 5 820 6 700 7 585 8 1115 9 870 10 1835 11 445 12 620 13 235 14 295 15 235 16 145 17 75 18 90 19 45 20 340 (mean) b6_110 10710 0 0 20 0 340 1 45 2 90 3 75 4 145 5 235 6 290 7 230 8 625 9 450 10 1835 11 870 12 1115 13 585 14 700 15 820 16 430 17 325 18 350 19 190 20 965 (mean) b7_100 10710 0 0 20 0 1285 1 210 2 365 3 425 4 490 5 890 6 775 7 695 8 1115 9 735 10 1350 11 515 12 585 13 230 14 215 15 280 16 135 17 95 18 75 19 50 20 195 (mean) b7_125 10710 0 0 20 0 195 1 50 2 75 3 95 4 135 5 280 6 225 7 225 8 590 9 505 10 1355 11 725 12 1125 13 695 14 775 15 885 16 490 17 425 18 365 19 210 20 1285 (mean) b8_100 10710 0 0 20 0 1475 1 245 2 440 3 475 4 530 5 975 6 715 7 660 8 1000 9 685 10 1295 11 410 12 480 13 235 14 250 15 285 16 100 17 105 18 65 19 20 20 265 (mean) b8_150 10710 0 0 20 0 265 1 20 2 65 3 105 4 100 5 285 6 250 7 235 8 480 9 410 10 1295 11 685 12 1000 13 660 14 715 15 975 16 530 17 475 18 440 19 245 20 1475 (mean) b9_100 10710 0 0 20 0 1710 1 370 2 505 3 525 4 600 5 815 6 730 7 585 8 930 9 580 10 1100 11 480 12 540 13 205 14 205 15 235 16 175 17 110 18 95 19 45 20 170 (mean) b9_175 10710 0 0 20 0 170 1 45 2 95 3 110 4 175 5 235 6 205 7 205 8 545 9 475 10 1100 11 580 12 935 13 585 14 725 15 815 16 600 17 530 18 505 19 365 20 1710 (mean) b10_100 10710 0 0 20 0 2275 1 450 2 565 3 495 4 515 5 875 6 735 7 580 8 635 9 535 10 1215 11 330 12 340 13 175 14 215 15 205 16 100 17 70 18 135 19 50 20 215 (mean) b10_200 10710 0 0 20 0 215 1 50 2 135 3 70 4 100 5 205 6 215 7 175 8 335 9 330 10 1215 11 535 12 655 13 580 14 720 15 875 16 510 17 495 18 570 19 450 20 2275 Implemented interest rate \{.1, .25, .5, .75, 1\} 10710 0 0.1 1 merge variable 10710 0 2 3 2 3440 3 7270 Indicator: death in the family 6570 4140 0 1 0 6400 1 170 Sysmiss 4140 change in total household expenditure 7270 3440 -5100 21050 Shortfall in expected HH income (MK) 7270 3440 -4302 13735 indiv own transfer card 10710 0 1 10 1 290 2 345 3 490 4 655 5 1640 6 1110 7 1310 8 1290 9 1930 10 1650 indiv own tokens - sooner 10710 0 0 20 0 1475 1 245 2 440 3 475 4 530 5 975 6 715 7 660 8 1000 9 685 10 1295 11 410 12 480 13 235 14 250 15 285 16 100 17 105 18 65 19 20 20 265 indiv own tokens - later 10710 0 0 20 0 265 1 20 2 65 3 105 4 100 5 285 6 250 7 235 8 480 9 410 10 1295 11 685 12 1000 13 660 14 715 15 975 16 530 17 475 18 440 19 245 20 1475 indiv own in mk - sooner 10710 0 0 2000 indiv own in mk - later 10710 0 0 4000 (mean) b1_100 10710 0 0 20 0 1050 1 190 2 290 3 280 4 385 5 790 6 610 7 560 8 1230 9 810 10 1910 11 455 12 690 13 235 14 225 15 305 16 120 17 85 18 90 19 55 20 345 (mean) b1_110 10710 0 0 20 0 345 1 55 2 90 3 85 4 120 5 305 6 225 7 235 8 685 9 460 10 1910 11 810 12 1230 13 560 14 610 15 795 16 385 17 275 18 290 19 190 20 1050 (mean) b2_100 10710 0 0 20 0 1215 1 220 2 350 3 380 4 445 5 895 6 755 7 705 8 975 9 770 10 1465 11 485 12 600 13 270 14 265 15 330 16 90 17 70 18 110 19 50 20 265 (mean) b2_125 10710 0 0 20 0 265 1 50 2 110 3 70 4 95 5 325 6 265 7 270 8 600 9 485 10 1465 11 770 12 975 13 700 14 760 15 890 16 445 17 385 18 350 19 220 20 1215 (mean) b3_100 10710 0 -9 20 (mean) b3_150 10710 0 -9 20 (mean) b4_100 10710 0 -9 20 (mean) b4_175 10710 0 -9 20 (mean) b5_100 10710 0 -9 20 (mean) b5_200 10710 0 -9 20 (mean) b6_100 10710 0 -9 20 (mean) b6_110 10710 0 -9 20 (mean) b7_100 10710 0 0 20 0 1280 1 210 2 370 3 420 4 495 5 890 6 785 7 700 8 1135 9 725 10 1330 11 510 12 575 13 240 14 215 15 280 16 135 17 95 18 75 19 50 20 195 (mean) b7_125 10710 0 0 20 0 195 1 50 2 75 3 95 4 135 5 280 6 225 7 235 8 580 9 500 10 1335 11 715 12 1145 13 700 14 785 15 885 16 495 17 420 18 370 19 210 20 1280 (mean) b8_100 10710 0 0 20 0 1475 1 245 2 440 3 475 4 535 5 980 6 710 7 655 8 1015 9 685 10 1275 11 405 12 475 13 250 14 245 15 290 16 100 17 105 18 65 19 20 20 265 (mean) b8_150 10710 0 0 20 0 265 1 20 2 65 3 105 4 100 5 290 6 245 7 250 8 475 9 405 10 1275 11 685 12 1015 13 655 14 710 15 980 16 535 17 475 18 440 19 245 20 1475 (mean) b9_100 10710 0 0 20 0 1700 1 370 2 505 3 520 4 600 5 825 6 730 7 595 8 925 9 590 10 1105 11 480 12 535 13 205 14 205 15 235 16 175 17 105 18 95 19 45 20 165 (mean) b9_175 10710 0 0 20 0 165 1 45 2 95 3 105 4 175 5 235 6 205 7 205 8 540 9 475 10 1105 11 590 12 930 13 595 14 725 15 825 16 600 17 520 18 505 19 370 20 1700 (mean) b10_100 10710 0 -9 20 (mean) b10_200 10710 0 -9 20 (mean) qualflag 10710 0 0 1 0 10125 1 585 (mean) timeprefA 10710 0 0 1 0 5385 1 5325 (mean) wealth_bline_M 10710 0 4 69502.5 (mean) frac_posdcs 10710 0 0.125 1 (mean) relatives 10695 15 0 132 (mean) havemaize 10710 0 0 1 0 8370 1 2340 (mean) younger 10710 0 0 1 0 8090 1 2620 (mean) middleage 10710 0 0 1 0 5305 1 5405 (mean) some_primary 10710 0 0 1 0 4170 1 6540 (mean) primary 10710 0 0 1 0 9100 1 1610 (mean) morethan_primary 10710 0 0 1 0 9925 1 785 (mean) wrdrecal_1 10710 0 0 10 0 20 1 50 2 340 3 1175 4 2650 5 3340 6 2190 7 760 8 160 9 20 10 5 (mean) ravens 10710 0 0 3 0 1480 1 3865 2 3630 3 1735 (mean) finlit_total 10710 0 0 3 0 6100 1 2275 2 1455 3 880 (mean) presbias 10710 0 0 1 (mean) presbias_2 10710 0 0 1 (mean) futurebias 10710 0 0 1 (mean) futurebias_2 10710 0 0 1 (mean) consistent 10710 0 0 1 (mean) consistent_2 10710 0 0 1 (mean) fracconsis 10710 0 0 1 (mean) fracpb_2 10710 0 0 1 (mean) fracconsis_2 10710 0 0 1 spouse's transfer card 10710 0 1 10 1 290 2 345 3 490 4 655 5 1640 6 1110 7 1310 8 1290 9 1930 10 1650 spouse's tokens - sooner 10710 0 0 20 0 1475 1 245 2 440 3 475 4 535 5 980 6 710 7 655 8 1015 9 685 10 1275 11 405 12 475 13 250 14 245 15 290 16 100 17 105 18 65 19 20 20 265 spouse's tokens - later 10710 0 0 20 0 265 1 20 2 65 3 105 4 100 5 290 6 245 7 250 8 475 9 405 10 1275 11 685 12 1015 13 655 14 710 15 980 16 535 17 475 18 440 19 245 20 1475 spouse's in mk - sooner 10710 0 0 2000 spouse's in mk - later 10710 0 0 4000 gap in tokens 10710 0 -20 20 gap in mk 10675 35 -4000 4000 which surveys 10445 265 1 6 1 Baseline=1 ; Middle=0 ; Endline=1 2500 2 Baseline=1 ; Middle=1 ; Endline=1 7310 3 Baseline=1 ; Middle=0 ; Endline=0 280 4 Baseline=1 ; Middle=1 ; Endline=0 315 5 Baseline=0 ; Middle=0 ; Endline=1 10 6 Baseline=0 ; Middle=1 ; Endline=1 30 7 Baseline=0 ; Middle=1 ; Endline=0 0 Sysmiss 265 Randomization Strat var 10405 305 12 23 0 Pilot 0 1 Chatoloma 2 (AO-FC/B) - Mar 4-5 0 2 Chatoloma 1 (AO-FC) - Mar 6-7 0 3 Chatoloma 1 (AO-B) - Mar 6-7 0 4 Chatoloma 1 (AO-B) - Mar 9-10 0 5 Chatoloma 1 (AO-FC) - Mar 9-10 0 6 Chisinga (AO-FC) - Mar 12-14 0 7 Chisinga (AO-B) - Mar 12-14 0 8 Chisinga (AO-B) - Mar 16 0 9 Kasungu Central (AO-FC) - Mar 17-20 0 10 Kasungu Central (AO-B) - Mar 17-20 0 11 Chamwabvi (AO-B) - Mar 23-25 0 12 Mponela (AO-FC) - Mar 27-28 410 13 Mponela (AO-B) - Mar 27-28 1500 14 Dzoole (AO-FC) - Mar 31-April 2 340 15 Dzoole (AO-B) - Mar 31-April 2 895 16 Chisepo (LL-DF) - Apr 2-3 0 17 Nachisaka (LL-DF) - Apr 6-7 0 18 Chibvala (LL-DF) - Apr 9-10 0 19 Nachisaka (LL-DF) - Apr 14-15 0 20 Mponela (LL-DF) - Apr 16-17 2205 21 Mndolera (LL-DF) - Apr 18-20 1800 22 Madisi (LL-DF) - Apr 21-22 1300 23 Bowe (LL-DF) - Apr 23 1955 Sysmiss 305 [HS14d]0/1: fixed deposit account at OIBM 9760 950 0 1 11 .B 90 [HS14]0/1: Any fixed deposit account, non-OIBM 9850 860 0 1 0 9565 1 285 Sysmiss 860 [HS14]0/1: Any fixed deposit account, any bank 9850 860 0 1 0 9105 1 745 Sysmiss 860 Treatment Group 10445 265 0 6 0 Control 1420 1 Ordinary, no raffle 1600 2 Ordinary, public raffle 1790 3 Ordinary, private raffle 1670 4 Commitment, no raffle 1185 5 Commitment, public raffle 1475 6 Commitment, private raffle 1305 Sysmiss 265 [TR](MK)Total transfers received 9850 860 0 200000 [TR](MK)Total transfers received;TRIM(0&99) 9850 860 0 29000 trimmed at 0 and 99 percentiles [TR](MK)transfers received, big gift<=Oct09 9850 860 0 70000 [TR](MK)transfers received, big gift<=Oct09;TRIM(0&99); 9850 860 0 10000 trimmed at 0 and 99 percentiles [TR](MK)Total transfers sent 9850 860 0 205000 [TR](MK)transfers sent, big gift<=Oct09 9850 860 0 201000 [TR](MK)transfers sent, big gift<=Oct09;TRIM(0&99); 9850 860 0 10000 trimmed at 0 and 99 percentiles abrlspsdiffc_f_soon 10710 0 0 20 0 7105 1 455 2 460 3 415 4 415 5 350 6 275 7 215 8 270 9 155 10 235 11 100 12 70 13 50 14 20 15 35 16 5 17 25 18 25 19 10 20 20 spsdiffpos 10710 0 0 1 0 1950 1 8760 pos_abrlspsdiffc_f_soon 10710 0 0 19 0 9055 1 220 2 275 3 210 4 190 5 160 6 125 7 100 8 130 9 55 10 90 11 25 12 15 13 25 15 10 16 5 18 15 19 5 actual lag squared 3310 7400 0 256 pb lag interaction 3310 7400 0 16 net transfers 9790 920 -162200 70000 ini_pb_sim 10710 0 0 1 0 9655 1 1055 club registration number 10710 0 220525 902176 Commitment Savings respondent ID / Revising Commitment HH ID 10405 305 125145301 325936510 0/1:male RC voucher holder 10405 305 0 1 0 5080 1 5325 Sysmiss 305 0/1:treatment=tmrw/1month (vs 2m/3m) 10405 305 0 1 0 7085 1 3320 Sysmiss 305 treatment:interest rate offered 10405 305 10 100 urea per acre 10685 25 0 300 spouse biase - sooner - in mk 10510 200 -2000 2000 spouse bias - all - sooner 10705 5 -1850 1850 Spouse minus own allocation to sooner (MK) 10695 15 -1833.333 1833.333 spouse bias - near 10620 90 -2000 2000 spouse bias - far 10650 60 -2000 2000 spouse bias imp 7150 3560 -2000 2000 spouse bias non-imp far 7245 3465 -1875 1875 1 treatment 10710 0 0 1 0 9110 1 1600 2 treatment 10710 0 0 1 0 8920 1 1790 3 treatment 10710 0 0 1 0 9040 1 1670 4 treatment 10710 0 0 1 0 9525 1 1185 5 treatment 10710 0 0 1 0 9235 1 1475 6 treatment 10710 0 0 1 0 9405 1 1305 Difference between Soon and Far:MK in two months, for r=0.1 10625 85 -2000 2000 Difference between Soon and Far:MK in two months, for r=0.25 10620 90 -2000 2000 Difference between Soon and Far:MK in two months, for r=0.50 10645 65 -2000 2000 Difference between Soon and Far:MK in two months, for r=0.75 10670 40 -2000 2000 Difference between Soon and Far:MK in two months, for r=1.00 10670 40 -2000 2000 pb all 10705 5 -2000 2000 pb non-imp 10700 10 -2000 2000 pb imp 10650 60 -2000 2000 Indicator: days to first disbursement (targeted) $\leq 6$ 3610 7100 0 1 0 2355 1 1255 Sysmiss 7100 target lag 7-11 3610 7100 0 1 0 2500 1 1110 Sysmiss 7100 target lag 12-16 3610 7100 0 1 0 2365 1 1245 Sysmiss 7100 HH total bank-BL 10710 0 0 540 HH case-BL 10710 0 0 340 exp income-BL 10710 0 0 1377 exp rev-BL 10710 0 0 1335 from selling items-BL 10710 0 0 5882.9 from selling animals-BL 10710 0 0 1236 Baseline wealth (100s of MK) 10710 0 0.4 6950.25 (mean) younger 10700 10 0 1 0 7515 1 3185 Sysmiss 10 (mean) middleage 10700 10 0 1 0 5095 1 5605 Sysmiss 10 (mean) a1 10700 10 18 87 (mean) younger 10710 0 0 1 0 8680 1 2030 (mean) middleage 10710 0 0 1 0 5490 1 5220 (mean) a1 10710 0 20 95 spouse age 10710 0 18 95 own_sooner_far_imp 7290 3420 0 2000 dummy C1 1 3290 7420 -2000 2100 dummy C1 1 3290 7420 -2000 2100 indicator present bias 2, int. rate=0.10 10710 0 0 1 0 7360 1 3350 indicator present bias 2, int. rate=0.25 10710 0 0 1 0 7485 1 3225 indicator present bias 2, int. rate=0.50 10710 0 0 1 0 7775 1 2935 indicator present bias 2, int. rate=0.75 10710 0 0 1 0 7725 1 2985 indicator present bias 2, int. rate=1.0 10710 0 0 1 0 7900 1 2810 indicator future bias 2, int. rate=0.10 10710 0 0 1 0 7730 1 2980 indicator future bias 2, int. rate=0.25 10710 0 0 1 0 7905 1 2805 indicator future bias 2, int. rate=0.50 10710 0 0 1 0 7795 1 2915 indicator future bias 2, int. rate=0.75 10710 0 0 1 0 8055 1 2655 indicator future bias 2, int. rate=1.0 10710 0 0 1 0 8295 1 2415 indicator present bias, int. rate=0.10 10710 0 0 1 0 6450 1 4260 indicator present bias, int. rate=0.25 10710 0 0 1 0 6480 1 4230 indicator present bias, int. rate=0.50 10710 0 0 1 0 6790 1 3920 indicator present bias, int. rate=0.75 10710 0 0 1 0 6690 1 4020 indicator present bias, int. rate=1.0 10710 0 0 1 0 6935 1 3775 spouse's bias, non-imp, wt 7285 3425 -1880.808 1880.808 present bias - wt 10710 0 -2000 2000 present bias, non-imp, wt 10705 5 -2000 2000 improreturn .10 10710 0 0 1 0 9310 1 1400 improreturn .25 10710 0 0 1 0 9055 1 1655 improreturn .50 10710 0 0 1 0 8930 1 1780 improreturn .75 10710 0 0 1 0 8125 1 2585 improreturn 1.0 10710 0 0 1 0 7420 1 3290 spouse_sooner_nonimpfar 7290 3420 0 2000 own_sooner_nonimpfar 7290 3420 0 2000 spouse_sooner_far_imp 7280 3430 0 2000 indicator: sb near, 0.10 10710 0 0 1 0 5865 1 4845 indicator: sb near, 0.25 10710 0 0 1 0 5855 1 4855 indicator: sb near, 0.50 10710 0 0 1 0 5835 1 4875 indicator: sb near, 0.75 10710 0 0 1 0 5790 1 4920 indicator: sb near, 1.0 10710 0 0 1 0 5945 1 4765 indicator: sb far, 0.10 10710 0 0 1 0 5895 1 4815 indicator: sb far, 0.25 10710 0 0 1 0 5845 1 4865 indicator: sb far, 0.50 10710 0 0 1 0 5805 1 4905 indicator: sb far, 0.75 10710 0 0 1 0 5885 1 4825 indicator: sb far, 1.0 10710 0 0 1 0 5945 1 4765 indicator: sb near2, 0.10 10710 0 0 1 0 6615 1 4095 indicator: sb near2, 0.25 10710 0 0 1 0 6460 1 4250 indicator: sb near2, 0.50 10710 0 0 1 0 6465 1 4245 indicator: sb near2, 0.75 10710 0 0 1 0 6395 1 4315 indicator: sb near2, 1.0 10710 0 0 1 0 6425 1 4285 indicator: sb far2, 0.10 10710 0 0 1 0 6510 1 4200 indicator: sb far2, 0.25 10710 0 0 1 0 6465 1 4245 indicator: sb far2, 0.50 10710 0 0 1 0 6370 1 4340 indicator: sb far2, 0.75 10710 0 0 1 0 6380 1 4330 indicator: sb far2, 1.0 10710 0 0 1 0 6425 1 4285 frac sb near 10710 0 0 1 frac sb far 10710 0 0 1 frac sb 10710 0 0 1 frac sb far, non-imp 7290 3420 0 1 frac sb, non-imp 7290 3420 0 1 frac sb near2 10710 0 0 1 frac sb, far2 10710 0 0 1 frac sb 2 10710 0 0 1 frac sb far2, non-imp 7290 3420 0 1 frac sb 2, non-imp 7290 3420 0 1 attrition 1 3610 7100 0 1 0 3310 1 300 Sysmiss 7100 attrition 2 3610 7100 0 1 0 3310 1 300 Sysmiss 7100 z13_month==2 10710 0 0 1 0 4045 1 6665 z13_month==3 10710 0 0 0 0 10710 2 target lag 3610 7100 0 1 0 3310 1 300 Sysmiss 7100 3 target lag 3610 7100 0 1 0 3395 1 215 Sysmiss 7100 4 target lag 3610 7100 0 1 0 3295 1 315 Sysmiss 7100 5 target lag 3610 7100 0 1 0 3405 1 205 Sysmiss 7100 6 target lag 3610 7100 0 1 0 3390 1 220 Sysmiss 7100 7 target lag 3610 7100 0 1 0 3405 1 205 Sysmiss 7100 8 target lag 3610 7100 0 1 0 3460 1 150 Sysmiss 7100 9 target lag 3610 7100 0 1 0 3360 1 250 Sysmiss 7100 10 target lag 3610 7100 0 1 0 3320 1 290 Sysmiss 7100 11 target lag 3610 7100 0 1 0 3395 1 215 Sysmiss 7100 12 target lag 3610 7100 0 1 0 3340 1 270 Sysmiss 7100 13 target lag 3610 7100 0 1 0 3395 1 215 Sysmiss 7100 14 target lag 3610 7100 0 1 0 3400 1 210 Sysmiss 7100 15 target lag 3610 7100 0 1 0 3345 1 265 Sysmiss 7100 16 target lag 3610 7100 0 1 0 3325 1 285 Sysmiss 7100 c_n_soon 10710 0 0 2000 c_n_late 10710 0 0 4000 Near: change in later consumption for change in r, 0.1 to 0.25 10705 5 -2200 2500 dcn_25_10pos 10710 0 0 1 0 2440 1 8270 siznegn_25_10 10710 0 0 2500 Near: change in later consumption for change in r, 0.25 to 0.50 10710 0 -2500 3000 dcn_50_25pos 10710 0 0 1 0 1725 1 8985 siznegn_50_25 10710 0 0 3000 Near: change in later consumption for change in r, 0.50 to 0.75 10685 25 -3000 3500 dcn_75_50pos 10710 0 0 1 0 2135 1 8575 siznegn_75_50 10710 0 0 3500 Near: change in later consumption for change in r, 0.75 to 1.00 10680 30 -3500 4000 dcn_100_75pos 10710 0 0 1 0 1915 1 8795 siznegn_100_75 10710 0 0 4000 Near: # (of 4) positive changes in later consumption with increase in r 10710 0 0 4 0 25 1 325 2 1750 3 3640 4 4970 avesiznegn 10710 0 0 3500 c_f_soon 10710 0 0 2000 c_f_late 10710 0 0 4000 Far: change in later consumption for change in r, 0.1 to 0.25 10700 10 -2200 2500 dcf_25_10pos 10710 0 0 1 0 2335 1 8375 Far: change in later consumption for change in r, 0.25 to 0.50 10700 10 -2500 3000 dcf_50_25pos 10710 0 0 1 0 1820 1 8890 Far: change in later consumption for change in r, 0.50 to 0.75 10695 15 -3000 3500 dcf_75_50pos 10710 0 0 1 0 2125 1 8585 Far: change in later consumption for change in r, 0.75 to 1.00 10665 45 -3500 4000 dcf_100_75pos 10710 0 0 1 0 1890 1 8820 Far: # (of 4) positive changes in later consumption with increase in r 10710 0 0 4 0 45 1 295 2 1720 3 3665 4 4985 # (of 8) positive changes in later consumption with increase in r 10710 0 1 8 1 30 2 65 3 210 4 790 5 1505 6 2300 7 2460 8 3350 Adherence to law of demand ratio [0,1] 10710 0 0.125 1 number sooner 10710 0 0 200 Fraction of tokens allocated to 10710 0 0 1.111 present bias 10710 0 0 1 0 6669 1 4041 present bias 2 10710 0 0 1 0 7649 1 3061 future bias 10710 0 0 1 0 6968 1 3742 future bias 2 10710 0 0 1 0 7956 1 2754 whether consistent 10710 0 0 1 0 7783 1 2927 whether consistent 10710 0 0 1 0 5815 1 4895 frac present bias 10710 0 0 1 frac future bias 10710 0 0 1 frac consistent 10710 0 0 1 frac present bias 2 10710 0 0 1 frac future bias 2 10710 0 0 1 frac consistent 2 10710 0 0 1 havedemos 10710 0 1 1 1 10710 hhminc_n_soon 10710 0 0 2000 hhmaxc_n_soon 10710 0 0 2000 spsdiffc_n_soon 10710 0 -2000 2000 hhminc_f_soon 10710 0 0 2000 hhmaxc_f_soon 10710 0 0 2000 spsdiffc_f_soon 10710 0 -2000 2000 wealth_bline_M 10710 0 0.004 69.503 Ln(baseline wealth) 10710 0 -5.521 4.241 ln_c_n_soon 9211 1499 4.605 7.601 ln_c_n_late 10436 274 4.7 8.294 dln_c_n 8937 1773 -2.849 3.638 ln_c_f_soon 9168 1542 4.605 7.601 ln_c_f_late 10473 237 4.7 8.294 dln_c_f 8931 1779 -2.849 3.638 Interest rate (r) 10710 0 0.1 1 Respondent ID 2157 0 1234581011 3259365102 Household ID 2157 0 123458101 325936510 (mean) z13_month 2142 15 1 2 1 809 2 1333 Sysmiss 15 Male 2142 15 0 1 0 1072 1 1070 Sysmiss 15 Number of relatives in the village 2142 15 0 132 Have adequate maize 2142 15 0 1 0 1679 1 463 Sysmiss 15 Less than 35 yrs old 2142 15 0 1 0 1621 1 521 Sysmiss 15 35-37 yrs old 2142 15 0 1 0 1058 1 1084 Sysmiss 15 Some primary school 2142 15 0 1 0 837 1 1305 Sysmiss 15 Primary school 2142 15 0 1 0 1819 1 323 Sysmiss 15 More than primary school 2142 15 0 1 0 1987 1 155 Sysmiss 15 Words recalled 2142 15 0 10 0 4 1 10 2 68 3 235 4 530 5 672 6 431 7 154 8 33 9 4 10 1 Sysmiss 15 Raven's Tests correct 2142 15 0 3 0 294 1 772 2 728 3 348 Sysmiss 15 Financial literacy questions correct 2142 15 0 3 0 1221 1 452 2 289 3 180 Sysmiss 15 Implemented interest rate \{.1, .25, .5, .75, 1\} 2142 15 0.1 1 Indicator: death in the family 1314 843 0 1 0 1280 1 34 Sysmiss 843 Shortfall in expected HH income (MK) 1454 703 -4302 13735 2142 15 1 10 1 58 2 69 3 98 4 131 5 328 6 222 7 262 8 258 9 386 10 330 Sysmiss 15 (mean) younger 2142 15 0 1 0 1618 1 524 Sysmiss 15 (mean) middleage 2142 15 0 1 0 1061 1 1081 Sysmiss 15 (mean) some_primary 2142 15 0 1 0 834 1 1308 Sysmiss 15 (mean) primary 2142 15 0 1 0 1820 1 322 Sysmiss 15 (mean) morethan_primary 2142 15 0 1 0 1985 1 157 Sysmiss 15 (mean) wrdrecal_1 2142 15 0 10 0 4 1 10 2 68 3 235 4 530 5 668 6 438 7 152 8 32 9 4 10 1 Sysmiss 15 (mean) ravens 2142 15 0 3 0 296 1 773 2 726 3 347 Sysmiss 15 (mean) finlit_total 2142 15 0 3 0 1220 1 455 2 291 3 176 Sysmiss 15 Indicator: days to first disbursement (targeted) $\leq 6$ 722 1435 0 1 0 471 1 251 Sysmiss 1435 Baseline wealth (100s of MK) 2142 15 0.4 6950.25 2157 0 0 1 0 661 1 1496