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05.02.2013 - Jonathan Robinson

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Daily Needs, Income Targets and Labor Supply: Evidence from Kenya

Daily Needs, Income Targets and Labor Supply: Evidence from Kenya

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  • 1. Daily Needs, Income Targets and Labor Supply:Evidence from KenyaPascaline Dupas Jon RobinsonStanford UCSCMay 2, 2013Dupas and Robinson Needs, Targets and Labor Supply May 2, 2013
  • 2. IntroductionThe majority of people in developing countries are self-employedTypically means that they can set their own work hours.While this has many advantages, it also has the fundamentaldisadvantage of potentially generating vulnerability to self-controlissues.In particular, many of these jobs are physically demanding and tedious,so it might be tempting for workers to quit earlier in the day than theywould have plannedDupas and Robinson Needs, Targets and Labor Supply May 2, 2013
  • 3. IntroductionRecent work shows that workers with self-control problems demandexternal constraints to help them work as hard as they would likeIndian data processors (Kaur, Kremer and Mullainathan, 2010, 2013)Berkeley undergraduates (Augenblick, Niederle and Sprenger, 2013)But such external commitment devices are not typically presentoutside formal work arrangements or a laboratory setting.How do individuals free to set their own hours in low-skill, repetitiveoccupations motivate themselves to work hard day after day?Dupas and Robinson Needs, Targets and Labor Supply May 2, 2013
  • 4. This PaperMakes use of a unique dataset collected from daily passenger-levellogbooks among 257 Kenyan bicycle taxi driverscontext: physically demanding to to be carrying passengers in the hotsun - especially since many respondents self-report bad healthLike previous taxi cab papers, the log includes the pickup time, dropotime, and fare for each passengerBut also includes other key variablesMost importantly, whether the respondent had a particular need thatday and, if so, the monetary amount required to meet the need.ShocksDupas and Robinson Needs, Targets and Labor Supply May 2, 2013
  • 5. Preview of Results1. Cash needs vary substantially across daysVery sensitive to shocksSome of these are unexpected (illness, funerals)Some are expected (ROSCA payments or school fees due)Yet people put these o until the last daySuggests that people are present-biased in eortImportantly, the needs are uncorrelated with the (realized) wage rate2. Labor supply is sensitive to the needsAt day level, people work more on days when they have greater needsUsing passenger-level data, people are more likely to quit just afterreaching the needDupas and Robinson Needs, Targets and Labor Supply May 2, 2013
  • 6. Preview of Results3. Random cash payoutProvided random cash payments on randomly selected daysAfter work had startedNo eect on labor supply → on its own, completely consistent withneoclassical labor supply modelBut combined with other results, suggests that people set targets overlabor income specicallyAny explanation for overall results must reconcile thisMany alternatives would predict quitting (subsistence constraints, purehyperbolic discounting, limited attention, etc).We conjecture that people are either (1) loss averse around a targetpoint; (2) keeping to a personal rule of meeting targetsCant be easily undoneDupas and Robinson Needs, Targets and Labor Supply May 2, 2013
  • 7. Preview of Results4. Welfare costsImplications of behaviorNegative wage elasticity → people make less total income for the samehoursWill work some very long hour days → may harm health if very longhour days depletes health capitalSome eect on income, and some speculative evidence of eect onhealthDupas and Robinson Needs, Targets and Labor Supply May 2, 2013
  • 8. Related LiteratureMeasuring income targetshard to measure - only other direct evidence comes from a labexperiment by Abeler et al. (2011)Taxi cab literatureNYC cabs (Camerer et al. 1997; Farber 2005, 2008; Crawford andMeng 2011; Doran 2012), Singapore cabs (Chou 2002), Swiss bikemessengers (Fehr and Goette 2007), US fruit packers (Chang andGross 2012)Main dierence is direct need approachesCan incorporate need with some of these earlier approachesIntensive and extensive margins (Oettinger 1999; Goldberg 2012; Ginéet al. 2009)Dupas and Robinson Needs, Targets and Labor Supply May 2, 2013
  • 9. Related LiteratureSelf-control at workAugenblick et al. (2013) in lab, Kaur et al. (2013) with Indian dataentry workersas Kaur et al. (2013) note, self-control at work dierent than overconsumption or incomeResults for one very specic population, but is useful to consider sinceso many people in developing countries are self employedHigh eort costs, low ability to save, etc. might be similar in othersettingsDupas and Robinson Needs, Targets and Labor Supply May 2, 2013
  • 10. Outline1. Conceptual Framework2. Sample and Data3. Results4. Alternative Hypotheses5. Welfare Consequences6. Discussion ConclusionDupas and Robinson Needs, Targets and Labor Supply May 2, 2013
  • 11. Conceptual FrameworkConceptual framework is meant to just be for motivationTwo partsWorkers choose daily targetsGiven those targets, workers make labor supply decisionsWhy do workers have daily income targets?That targets are daily is likely driven by narrow bracketingWorkers focus on daily targets rather than optimizing subject to alifetime budget constraint as in MaCurdy (1981)Dupas and Robinson Needs, Targets and Labor Supply May 2, 2013
  • 12. TargetsSeveral possible interpretations of targetsTarget may be a reference pointCamerer et al. (1997), Köszegi and Rabin (2006) Crawford and Meng(2011), etc.Workers loss averse around this point so marginal utility of additionalincome decreases discontinuouslyAlternatively, once set, people use their target as a personal rule orinternal commitment devicei.e. Ainslie 1992; Bénabou and Tirole 2004If people know that they wont reach their goal, might as well not eventryImperfect recall about whether they made the goal on previous daysWant to keep to rule to avoid setting a precedentDupas and Robinson Needs, Targets and Labor Supply May 2, 2013
  • 13. Dealing with needsSome needs are unexpected, others are foreseeableSchool fees have xed due date in advanceSo do ROSCA paymentsIf workers face no other constraints, should save up to deal with theseover some time periodIf, however, they are present-biased in eort, they will procrastinate onthese for as long as possibleDupas and Robinson Needs, Targets and Labor Supply May 2, 2013
  • 14. Implications1. Workers will put o needs until they can no longer do so.2. Workers will work less on days in which their income target is lower.3. The hazard of quitting will increase after reaching the income target4. As in Camerer et al. (1997) and subsequent papers, workers willexhibit a negative wage elasticityIn addition, we would expect heterogeneity by certain baselinecharacteristicsEort costsAbility to saveDupas and Robinson Needs, Targets and Labor Supply May 2, 2013
  • 15. Outline1. Conceptual Framework2. Sample and Data3. Results4. Alternative Hypotheses5. Welfare Consequences6. Discussion ConclusionDupas and Robinson Needs, Targets and Labor Supply May 2, 2013
  • 16. Study Design OverviewProject took place from September to December 2009 in BusiaDistrict, Western KenyaSample of 257 bicycle-taxi drivers, locally called boda-bodasDupas and Robinson Needs, Targets and Labor Supply May 2, 2013
  • 17. Sampling FrameAugust 2009: Census of all bicycle-taxi drivers in 14 market centersscattered around the districtSince we needed respondents to keep logs, we excluded those whocouldnt write or who had less than 3 years of education (24% ofcensus)Left with 303 respondentsSuccessfully enrolled 257 (84%) into the nal sampleRemainder had moved, quit bike taxiing, or didnt consent to the heavydata collection requirementsDupas and Robinson Needs, Targets and Labor Supply May 2, 2013
  • 18. DataParticipants enrolled on a rolling basis from September to November2009Stayed in the study for up to three monthsBackground Surveydemographics, SES, health, time and risk preferences, loss aversionDaily diaries Daily Diaryrespondents self-reported their labor supply, income, health statuscrucially, rst question about special need for the dayWeekly survey Weekly Surveyday-by-day 1-week recall survey to the respondenttransfers to spouses, relatives or friends, savings, labor supply in otherjobs, more details on health shocksDupas and Robinson Needs, Targets and Labor Supply May 2, 2013
  • 19. DataMedian and mean number of log days lled per respondent: 47 days(min: 7, max: 90); total of 10,835 person-days in main specicationsAccompanying 1-week recall survey for 72% of the daysnot 100% because some weeks enumerators were not able to nd therespondent (e.g., if the respondent was away)Full data available for an average of 34 (mostly consecutive) days perstudy participantsDupas and Robinson Needs, Targets and Labor Supply May 2, 2013
  • 20. Baseline Characteristics(1) (2)Mean Std. Dev.Panel A. Demographic InformationAge 33.06 8.11Married 0.96 0.19Number of Children 3.40 2.27Education 6.78 2.22Value of Durable Goods Owned (in Ksh) 11097.76 8381.72Value of Animals Owned (in Ksh) 6933.44 9858.87Acres of land owned 1.42 1.44Total Bike-Taxi Income in Week Prior to Survey (in Ksh) 573.52 340.41Has another regular source of income 0.15 0.36If yes, income in average week from other income 576.43 524.80Has seasonal income 0.20 0.40If yes, income in normal season 6631.84 10702.20Number of observations 244Dupas and Robinson Needs, Targets and Labor Supply May 2, 2013
  • 21. Baseline Characteristics(1) (2)Mean Std. Dev.Panel B. Financial AccessParticipates in ROSCA 0.75 0.43If yes, number of ROSCAs 1.06 0.84If yes, ROSCA contributions in last year (in Ksh) 5972.35 7880.52Owns Bank Account 0.32 0.47Received gift/loan in past 3 months 0.24 0.43If yes, amount 0.29 0.45Gave gift/loan in past 3 months 2204.22 2348.50If yes, amount 1195.88 1877.05If needed 1,000 Ksh right away, would:Use savings 0.10 0.30Sell asset(s) 0.34 0.48Work more 0.12 0.32Get gift/loan from friends/ relatives 0.47 0.50Get loan from ROSCA 0.21 0.41Number of observations 244Dupas and Robinson Needs, Targets and Labor Supply May 2, 2013
  • 22. Baseline Characteristics(1) (2)Mean Std. Dev.Panel C. HealthHealth Problems Index (scale 1-5)11.97 0.68Average Score on Activities of Daily Living (scale 1-5)21.51 0.39Overall, how would you rate your health (scale 1-5)?32.59 0.73Missed work due to illness in past month 0.39 0.49If yes, number of days missed 2.20 1.80Early Bird: Starts work before 8am on median work day 0.51 0.50Number of observations 244Notes: Exchange rate was roughly 70 Ksh to US $1 during the study period.1The index refers to severity of pain and difficulty in performing activities of daily living.The index ranges between 1 and 5, where 1=none, 2=mild, 3=moderate, 4=severe and5=extreme. It is composed of 4 self-assessed measures shown in Table A1.2Average score across all activities shown in Table A1. Codes are the same as above.3Codes: 1-excellent, 2-good, 3-OK, 4-poor, 5-very poor.4The risky asset paid off 4 times the amount invested with probability 0.5, and 0 withprobability 0.5.5Time Consistent is a dummy equal to 1 if the respondent exhibits the same discountrate between today and 7 days from today. Present-Biased is a dummy equal to 1 if therespondent exhibits a higher discount rate between today and 2 days from today thanDupas and Robinson Needs, Targets and Labor Supply May 2, 2013
  • 23. Baseline Characteristics(1) (2)Mean Std. Dev.Panel D. Preferences for Risk, Time, and Loss AversionAmount invested (out of 100 Ksh) in Risky Asset456.19 26.02Time-consistent50.32 0.47Present-biased 0.13 0.34More Patient in Future than in Present 0.27 0.44Maximal Discount Rate in Present and in Future 0.29 0.45More loss averse: Refuses the 50-50 gamble (win 30 or lose 10) 0.28 0.45More loss averse: Refuses the 50-50 gamble (win 120 or lose 50) 0.58 0.50Number of observations 244Notes: Exchange rate was roughly 70 Ksh to US $1 during the study period.4The risky asset paid off 4 times the amount invested with probability 0.5, and 0 with probability0.5.5Time Consistent is a dummy equal to 1 if the respondent exhibits the same discount ratebetween today and 1 month from today. Present-Biased is a dummy equal to 1 if the respondentexhibits a higher discount rate today, and More Patient in Future than in Present is a dummyequal to 1 if the respondent is more patient in 1 month. Maximum Discount Rate in the Presentand in the Future is a dummy equal to 1 if a respondent always prefers 40 Ksh in the nearestperiod to 200 Ksh 2 days later.Dupas and Robinson Needs, Targets and Labor Supply May 2, 2013
  • 24. Baseline HealthTable A1. Baseline Health Level: Activities of Daily Living(1) (2) (3) (4) (5) (6)None Mild Moderate Severe Extreme No answerIn the past 30 days, did you have any bodily 0.30 0.40 0.19 0.04 0.02 0.05aches or pains?How much difficulty do you have in your daily 0.11 0.39 0.18 0.03 0.00 0.29life due to pain?In the past 30 days, how much discomfort 0.10 0.39 0.19 0.02 0.30 0.30did you have?Observations 244Dupas and Robinson Needs, Targets and Labor Supply May 2, 2013
  • 25. Summary Statistics from Logs(1) (2) (3) (4)Mean Std. Dev.# ofObservations(Individual-days)# of IndividualsA. Labor SupplyWorked today 0.74 0.44 12466 257If yes, total income (Ksh) 144.70 93.72 9192 257If yes, total hours 8.95 2.77 8583 256Received income from some other source 0.24 0.43 8159 248If yes, amount earned (Ksh) 79.59 485.39 1971 217If yes, hours 3.32 2.26 1990 217B. Is there something in particular that you need money for today?Yes 0.88 0.32 12466 257If yes, amount (Ksh) 203.74 340.44 10560 257C. Cash payoutsRespondent Sick 0.18 0.38 12461 257Somebody in household sick 0.10 0.29 12466 257School fees due 0.02 0.13 9732 256Funeral 0.05 0.21 9783 256Had to make repairs to bike 0.21 0.41 9658 255If yes, amount spent on repairs (Ksh) 77.63 92.65 2012 253Made a ROSCA contribution 0.15 0.36 10674 257Received a ROSCA payout 0.01 0.11 9759 256Dupas and Robinson Needs, Targets and Labor Supply May 2, 2013
  • 26. Summary Statistics from Logs(1) (2) (3) (4)Mean Std. Dev.# ofObservations(Individual-days)# of IndividualsD. Other Cash FlowsSomebody asked for money 0.02 0.14 9765 256If yes, respondent gave money 1.00 0.07 201 109Got money from somebody 0.02 0.14 9779 256Got money from spouse 0.01 0.10 9726 256Gave money to spouse 0.12 0.32 9721 256Made withdrawal from home savings 0.04 0.20 8469 249Made withdrawal from bank savings 0.01 0.09 3141 77Received lump sum payment from regular cus 0.01 0.11 9751 256E. Individual-level variablesEver rented bike 0.18 0.38 13417 255Ever got lump sum payment from regular cus 0.27 0.45 13443 256Dupas and Robinson Needs, Targets and Labor Supply May 2, 2013
  • 27. Outline1. Conceptual Framework2. Sample and Data3. Resultsa. Main Resultsb. Heterogeneityc. Lotteryd. Robustness4. Alternative Hypotheses5. Welfare Consequences6. Discussion ConclusionDupas and Robinson Needs, Targets and Labor Supply May 2, 2013
  • 28. Determinants of NeedsNit = βwit + Suitγu+ Seitγe+ Ditθ + µi + it (1)Nit is the daily need,Suit are unexpected shocks (such as sickness or funeral expenses)Seit are expected events which require cash (such as ROSCA paymentsor school fees coming due).We also include a measure of the realized wage rate (wit).We follow Camerer et al. (1997) and construct a realized wage that isexogenous to the individual by taking the average wage of all of theother respondents in that market center.Restrict to observations where we can construct thisInclude day of the week (Dit) dummies in the specication, since theseare predictable determinants of the wage.Worker xed eects, clustered at individual levelDupas and Robinson Needs, Targets and Labor Supply May 2, 2013
  • 29. Results: Determinant of Daily Need(1) (2) (3) (4)Amount of cashneed in Ksh (0 ifnone reported)Reports cashneed for thedayIf reports need:Cash amountWorkedWageRealized log local wage rate1-0.034 0.040 -0.045 0.137(0.020)* (0.022)* (0.023)* (0.027)***Cash NeedsSchool fees due 0.036 0.105 0.015 0.043(0.025) (0.023)*** (0.027) (0.031)ROSCA contribution due 0.011 0.090 -0.005 0.051(0.012) (0.015)*** (0.014) (0.016)***Funeral to attend 0.102 0.060 0.098 -0.108(0.049)** (0.015)*** (0.051)* (0.027)***Somebody in household is sick 0.059 0.038 0.058 -0.017(0.014)*** (0.010)*** (0.015)*** (0.013)Respondent sick 0.019 0.014 0.019 -0.359(0.012) (0.011) (0.014) (0.025)***Day of WeekMonday 0.018 0.058 0.011 0.038(0.013) (0.010)*** (0.014) (0.014)***Sunday -0.021 -0.101 -0.004 -0.417(0.014) (0.017)*** (0.016) (0.024)***Observations (individual-days) 10835 10835 9495 10835Number of IDs 257 257 257 257Mean of Dep. Var. 0.177 0.876 0.202 0.737Std. Dev. of Dep. Var 0.331 0.329 0.347 0.440Note: other day dummies omitted for space.Dupas and Robinson Needs, Targets and Labor Supply May 2, 2013
  • 30. When do people deal with needs?Some of the needs are unexpected (sickness, funerals)But some should be fully anticipatedSchool fees due on a standard scheduleROSCA meeting schedule is xedPeople could deal with these needs over several daysIf they procrastinate, though, they may leave these until the day theyneed the moneyDupas and Robinson Needs, Targets and Labor Supply May 2, 2013
  • 31. When do people deal with needs?(1) (2) (3) (4) (5) (6)Made ROSCA deposit 0.55 0.55(0.026)*** (0.027)***Will make ROSCA deposit -0.04tomorrow (0.018)**Will make ROSCA deposit -0.05in 2 days (0.014)***Paid school fees 0.56 0.59(0.044)*** (0.043)***Will pay school fees tomorrow 0.03(0.03)Will pay school fees in 2 days 0.02(0.02)Repaid loan 0.26 0.25(0.072)*** (0.068)***Will repay loan tomorrow 0.07(0.05)Will repay loan in 2 days 0.04(0.04)Observations 8773 7473 8802 7504 7821 6692Number of IDs 253 252 253 252 243 242Mean of dependent variable 0.19 0.19 0.03 0.03 0.01 0.01Reported need of:ROSCA payment School Fees Repaid a LoanDupas and Robinson Needs, Targets and Labor Supply May 2, 2013
  • 32. Needs and Labor SupplyTo be transparent, rst look cross-sectionally, then at day level, andthen nally within-dayDupas and Robinson Needs, Targets and Labor Supply May 2, 2013
  • 33. Results: Cross-Sectional (Hours)7.588.599.5#ofhoursworked0 100 200 300 400Cash need for the day (Ksh)Mean Quadratic fit180Dupas and Robinson Needs, Targets and Labor Supply May 2, 2013
  • 34. Results: Cross-Sectional (Income)0 100 200 300 400Cash need for the day (Ksh)Mean Quadratic fit100120140160180DailyIncome0 100 200 300 400Cash need for the day (Ksh)Notes: Each circle corresponds to an average across at least50 man-days. Size of circle indicates number of man-days.Dupas and Robinson Needs, Targets and Labor Supply May 2, 2013
  • 35. Across daysAcross day specicationLit = αNit + βwit + Sitγ + Ditθ + µi + it (2)where Lit is a measure of labor supplycontrol for other cash needs SitLabor Supply by Baseline characteristicsDupas and Robinson Needs, Targets and Labor Supply May 2, 2013
  • 36. Results: Labor Supply(1) (2) (3) (4)Has a need 0.19 0.023(0.022)*** (0.004)***If has a need: log (cash need) -0.009 0.012(0.008) (0.002)***Log (local wage rate) 0.116 0.113 0.058 0.060(0.026)*** (0.029)*** (0.007)*** (0.007)***Observations (individual-days) 12301 10434 12301 10434Number of IDs 256 256 256 256ID fixed effects Yes Yes Yes YesR-squared 0.20 0.16 0.12 0.10Mean of Dep. Var. 0.741 0.776 0.107 0.112Std. Dev. of Dep. Var 0.438 0.417 0.103 0.101Worked Today Total Income (in 1,000 Ksh)Dupas and Robinson Needs, Targets and Labor Supply May 2, 2013
  • 37. Results: Labor Supply(5) (6) (7) (8) (9) (10) (11) (12)Has a need -0.006 -0.002 -0.097 -0.005(0.004) (0.092) (0.113) (0.007)If has a need: log (cash need) 0.017 0.230 0.274 0.013(0.002)*** (0.039)*** (0.054)*** (0.004)***Log (local wage rate) 0.057 0.057 0.913 0.985 -0.598 -0.539 0.096 0.092(0.007)*** (0.007)*** (0.146)*** (0.141)*** (0.248)** (0.213)** (0.010)*** (0.012)***Observations (indiv-days) 9120 8099 9120 8099 8561 7633 8539 7613Number of IDs 256 256 256 256 256 256 256 256ID fixed effects Yes Yes Yes Yes Yes Yes Yes YesR-squared 0.03 0.05 0.04 0.05 0.03 0.03 0.02 0.03Mean of Dep. Var. 0.145 0.144 4.417 4.420 8.953 8.936 0.285 0.283Std. Dev. of Dep. Var 0.094 0.092 2.152 2.146 2.768 2.762 0.161 0.158Percent of day spentridingIf worked:Total income (in 1,000Ksh)Number of passengers Total hoursDupas and Robinson Needs, Targets and Labor Supply May 2, 2013
  • 38. Hazard regressionsqipt =10∑b=−10γbDibt + δHipt + ψH2ipt + ηNit + µi + ηt + ipt (3)qipt is a dummy for quitting after passenger p on date tHpt is hours worked up to that passengerNit is the goal amountDb is a dummy for being in income bin b (of width 20 Ksh)Minimum fare usually 10 Ksh, not very sensitive to bin widthIncludes individual and day xed eects, and errors are clustered at theindividual levelDupas and Robinson Needs, Targets and Labor Supply May 2, 2013
  • 39. Results: Hazard0.04.08.12.16.2Pr(quitting)-200 -160 -120 -80 -40 0 40 80 120 160Ksh from needCoefficient95% CIAll Cash Need AmountsBy GoalDupas and Robinson Needs, Targets and Labor Supply May 2, 2013
  • 40. Parametrizationqipt = α + γ1Oipt + β1Dipt + θ1Dipt ∗ Oipt + δHipt + ψH2ipt+ηNit + µi + ηt + ipt (4)Dipt is the distance from the targetOipt is a dummy for being over the targetAlso control for hours Hipt and H2iptDupas and Robinson Needs, Targets and Labor Supply May 2, 2013
  • 41. Results: RegressionDependent Variable = Quit After Passenger(1) (2) (3) (4) (5) (6) (7) (8)Coefficient on:CumulativeHours WorkedCumulativehours worked2Distancefrom needOver needDistancefrom need *over needMean of dep.var.N # IDsPanel A. Entire Sample-0.08 0.36 0.11 0.04 0.02 0.09 34984 257(0.04)** (0.04)*** (0.09) (0.01)*** (0.12)Dupas and Robinson Needs, Targets and Labor Supply May 2, 2013
  • 42. HazardNeed to check for composition eects since need amounts vary overdaysLooks similar for a given need amountAlso qualitatively similar when including respondent-day xed eectsBy denition, controls for the needMuch less power howeverDupas and Robinson Needs, Targets and Labor Supply May 2, 2013
  • 43. Needs, Income Expectations, and Hours ExpectationsAs discussed in Köszegi and Rabin (2006) and Crawford and Meng(2011), target is likely determined in part by income expectationsAppears also to have a need componentTo examine both together, we integrate our approach with Crawfordand Meng (2011)Proxy income expectations with average amount earned by respondenton that day of the weekSame for hoursDupas and Robinson Needs, Targets and Labor Supply May 2, 2013
  • 44. Needs, Income Expectations, and Hours Expectations(1) (2) (3) (4)Dependent variable = 1 if quit work for the dayCumulative Hours Worked -0.03 -0.07 -0.10 -0.12(Units = Hours / 10) (0.04) (0.04)* (0.04)*** (0.04)***Cumulative Hours Worked Squared 0.32 0.35(0.04)*** (0.04)***Cumulative Income Earned 0.16 0.06 0.63 0.46(Units = Ksh / 1,000) (0.10) (0.10) (0.11)*** (0.11)***Cumulative Income Earned Squared -0.78 -0.65(0.19)*** (0.19)***Cumulative Hours Estimated Target 0.08 0.07 0.08 0.07(0.01)*** (0.01)*** (0.01)*** (0.01)***Cumulative Income Estimated Target 0.03 0.03 0.02 0.02(0.01)*** (0.01)*** (0.01)*** (0.01)***Over need 0.04 0.03(0.01)*** (0.01)***Observations 40670 36070 40670 36070Number of bodas 257 257 257 257R-squared 0.15 0.16 0.15 0.16Mean of dependent variable 0.09 0.09 0.09 0.09Dupas and Robinson Needs, Targets and Labor Supply May 2, 2013
  • 45. Needs, Income Expectations, and Hours ExpectationsExpectations appear to matter as wellWhy then do we observe such a sharp break at the need?Needs and expectations are not correlatedDupas and Robinson Needs, Targets and Labor Supply May 2, 2013
  • 46. Needs and Targets(1) (2) (3) (4)Need amount (conditional on need) 0.003 0.000(0.003) (0.009)Need amount (imputing as 0 days without a need) 0.003 0.003(0.003) (0.009)Observations 31266 34556 30650 33879Number of bodas 257 257 256 256R-squared 0.04 0.04 0.03 0.03Mean of dependent variable 0.15 0.15 0.92 0.92Proxy Income Target Proxy Hours TargetDupas and Robinson Needs, Targets and Labor Supply May 2, 2013
  • 47. Using History of Hours / Income as Target Proxy0.05.1.15.2.25Pr(quitting)-200 -160 -120 -80 -40 0 40 80 120 160Ksh from Proxied TargetCoefficient95% CIProxying target with history of realized income on that week dayDupas and Robinson Needs, Targets and Labor Supply May 2, 2013
  • 48. Using History of Hours / Income as Target Proxy0.2.4.6Pr(quitting)-5 -4 -3 -2 -1 0 1 2 3 4Hours from Proxied TargetCoefficient95% CIProxying target with history of realized hours on that week dayDupas and Robinson Needs, Targets and Labor Supply May 2, 2013
  • 49. Outline1. Conceptual Framework2. Sample and Data3. Resultsa. Main Resultsb. Heterogeneityc. Lotteryd. Robustness4. Alternative Hypotheses5. Welfare Consequences6. Discussion ConclusionDupas and Robinson Needs, Targets and Labor Supply May 2, 2013
  • 50. Results: HeterogeneityBasic framework suggests heterogeneity based on severalcharacteristicsLoss aversionWould you take gamble if you had a 50% chance of winning 30 Kshand a 50% chance at losing 10 Ksh?Present-biasMore patient in future than in present in laboratory-type timepreference questionsDupas and Robinson Needs, Targets and Labor Supply May 2, 2013
  • 51. Results: HeterogeneitySavings dicultiesIf you needed 1,000 Ksh, how would you come up with money?Look at people who can use savings for at least part of thisMarginal eort costsNo direct measureLook at people who start work later in the day. Idea is that they arethe ones least able/willing to get started in morningNo evidence that needs vary by these characteristicsNeeds by Baseline CharacteristicsDupas and Robinson Needs, Targets and Labor Supply May 2, 2013
  • 52. Results: HeterogeneityFigure 3. Hazard Regressions by Subgroups-.10.1.2.3Pr(quitting)-200 -160 -120 -80 -40 0 40 80 120 160Ksh from needCan use savings to get 1k 95% CICant use savings to get 1k 95% CIHazard by using savings to get 1k0.1.2.3.4Pr(quitting)-200 -160 -120 -80 -40 0 40 80 120 160Ksh from needStarts work before 8 on average 95% CIStarts work after 8 on average 95% CIHazard by starting work before 8am on average-.10.1.2.3.4Pr(quitting)-200 -160 -120 -80 -40 0 40 80 120 160Ksh from needTime consistent 95% CIPresent biased 95% CIHazard by Time Consistency0.1.2.3.4Pr(quitting)-200 -160 -120 -80 -40 0 40 80 120 160Ksh from needMore loss averse 95% CILess loss averse 95% CIHazard by loss aversion levelDupas and Robinson Needs, Targets and Labor Supply May 2, 2013
  • 53. Results: HeterogeneityDependent Variable = Quit After Passenger(1) (2) (3) (4) (5) (6) (7) (8)Coefficienton:CumulativeHours WorkedCumulativehours worked2Distancefrom needOver needDistancefrom need *over needMean of dep.var.N # IDsPanel B. Heterogeneity Analysis based on Model PredictionsCan use savings if needed 1,000 KshNo -0.11 0.38 0.22 0.03 0.30 0.09 29839 213(0.04)** (0.04)*** (0.11)* (0.01)*** (0.16)*Yes -0.01 0.24 -0.07 0.03 -0.13 0.06 3365 24(0.10) (0.11)** (0.08) (0.02)* (0.11)[0.61] [0.26] [0.5] [0.92] [0.01***]Early birdNo -0.09 0.40 0.34 0.04 0.19 0.09 15987 126(0.05)* (0.05)*** (0.12)*** (0.01)*** (0.21)Yes -0.16 0.41 0.04 0.03 -0.03 0.09 18997 131(0.05)*** (0.05)*** (0.10) (0.01)*** (0.13)[0.06*] [0.71] [0.44] [0.76] [0.08*]Notes: For each dummy background characteristic, separate regressions are run for those who have the characteristic and forthose who dont. See text for more details on the specification. All regressions include individual fixed effects and controls forthe week the day of week. For each characteristic, the p-value for the test that coefficients are equal for those with and withoutthe characteristics are in square brackets.Dupas and Robinson Needs, Targets and Labor Supply May 2, 2013
  • 54. Results: HeterogeneityDependent Variable = Quit After Passenger(1) (2) (3) (4) (5) (6) (7) (8)Coefficienton:CumulativeHours WorkedCumulativehours worked2Distancefrom needOver needDistancefrom need *over needMean of dep.var.N # IDsPanel B. Heterogeneity Analysis based on Model PredictionsPresent biasedNo -0.10 0.36 0.09 0.04 0.04 0.09 29485 210(0.04)** (0.04)*** (0.09) (0.01)*** (0.13)Yes -0.09 0.45 0.25 0.04 -0.30 0.09 4285 31(0.05) (0.06)*** (0.15) (0.02)* (0.28)[0.65] [0.26] [0.48] [0.88] [0.29]More loss averseNo -0.12 0.39 0.12 0.05 -0.03 0.09 23877 172(0.05)** (0.04)*** (0.10) (0.01)*** (0.13)Yes -0.02 0.32 0.12 0.03 0.08 0.10 9544 68(0.08) (0.08)*** (0.18) (0.02)* (0.28)[0.26] [0.46] [0.13] [0.57] [0.83]Notes: For each dummy background characteristic, separate regressions are run for those who have the characteristic and forthose who dont. See text for more details on the specification. All regressions include individual fixed effects and controls forthe week the day of week. For each characteristic, the p-value for the test that coefficients are equal for those with and withoutthe characteristics are in square brackets.Dupas and Robinson Needs, Targets and Labor Supply May 2, 2013
  • 55. Outline1. Conceptual Framework2. Sample and Data3. Resultsa. Main Resultsb. Heterogeneityc. Lotteryd. Robustness4. Alternative Hypotheses5. Welfare Consequences6. Discussion ConclusionDupas and Robinson Needs, Targets and Labor Supply May 2, 2013
  • 56. LotteryWe created exogenous variation in non-labor income by holdingunannounced lotteries on random daysRespondents informed about lottery on same dayLottery = pick a prize card from a bag, at market centerOdds:50% chance 20 Ksh (control prize compensated for opportunitycost of time)25% chance 200 Ksh12.5% chance 250 Ksh12.5% chance 300 KshDupas and Robinson Needs, Targets and Labor Supply May 2, 2013
  • 57. LotterySizeable compared to median daily income from bicycle-taxi driving ofaround 150 KshCaveat: power somewhat limited - have only 563 lottery payouts over236 respondents (2.4 per respondent)Dupas and Robinson Needs, Targets and Labor Supply May 2, 2013
  • 58. Lottery Results(1) (2) (3) (4)WorkedTodayTotalincomeTotalhoursTimeended workWon big lottery prize today 0.011 0.005 0.093 -0.06(0.024) (0.005) (0.153) (0.105)Won big lottery prize yesterday 0.025 0.002 0.044 0.110(0.024) (0.003) (0.148) (0.102)Observations (individual-days) 10704 7926 7487 7540Number of IDs 256 256 256 256R-squared 0.24 0.21 0.04 0.01Mean of Dep. Var. 0.74 0.146 8.92 17.433Std. Dev. of Dep. Var 0.438 0.095 2.761 1.882Notes: Regressions are at the individual-day level. Standard errors are inparentheses, clustered at the individual level. Regressions include individual fixedeffects, all the variables shown in Table 3, and controls for the week the day ofweek.. ***, **, * indicates significance at 1, 5 and 10%. All monetary values in1,000 Ksh.If worked:Dupas and Robinson Needs, Targets and Labor Supply May 2, 2013
  • 59. LotteryLottery results suggest that, once set, targets are not undone byunexpected cash payoutsIf this heuristic really is how people solve a self-control issue, maybethis isnt so surprisingWould be very easily undoneFor example, a day with a ROSCA payment might be a day people quitearlyDupas and Robinson Needs, Targets and Labor Supply May 2, 2013
  • 60. Outline1. Conceptual Framework2. Sample and Data3. Resultsa. Main Resultsb. Heterogeneityc. Lotteryd. Robustness4. Alternative Hypotheses5. Welfare Consequences6. Discussion ConclusionDupas and Robinson Needs, Targets and Labor Supply May 2, 2013
  • 61. Robustness - Experimenter EectsExperimenter eects: did asking about needs make the need moresalient?Ideally have sample not asked about needs during same time periodWe dont have that, but did collect similar logs in 2006-2008 in Dupasand Robinson (2013)If asking about needs made them salient, expect greater variance indays worked in this sampleBut, nd comparable (and if anything, larger) within-worker variance inhours worked across days in that earlier sample: 2.74 compared to 2.16in the sample considered in the present paper.Dupas and Robinson Needs, Targets and Labor Supply May 2, 2013
  • 62. Robustness - PersistenceAnother approach: how persistent are eects?If having to record a daily cash need made otherwise perfectlyoptimizing people income targeting, wed expect this to be strongest atthe beginning of sample periodEventually people should go back to normal since there is an incomeloss to this kind of targetingHazard gives same pattern of results, with the same magnitude, at thebeginning and end of the data collection period.Dupas and Robinson Needs, Targets and Labor Supply May 2, 2013
  • 63. Robustness - Timing of needsPossible endogenous timing of needs: at some level, workers canchoose when to deal with some of these needs. Is this an issue?First, even if chosen, the needs would still mean something, from thehazard more about interpreting the mechanismSecond, some needs are not anticipated, yet behavior is the same forthose (sickness, funerals)However, there is strong evidence of procrastinationFewer needs on Sundays, more on MondaysPutting o expenses until the last possible moment(the timing though does suggest the reported needs match reality)Needs are not everything earning expectations matter tooDupas and Robinson Needs, Targets and Labor Supply May 2, 2013
  • 64. Outline1. Conceptual Framework2. Sample and Data3. Results4. Alternative Hypotheses5. Welfare Consequences6. Discussion ConclusionDupas and Robinson Needs, Targets and Labor Supply May 2, 2013
  • 65. Alternative HypothesesThey are other possible explanationLabor supply under subsistence constraints (i.e. Barzel and MacDonald1973; Basu and Van 1999; Jayachandran 2006; Bhalotra 2007; Halliday2012)Limited attentionRisk sharingOthers?We consider several such variantsDupas and Robinson Needs, Targets and Labor Supply May 2, 2013
  • 66. Labor supply with subsistence constraint1. People may use bike taxiing as a way to cover immediate cash needs,but may get higher returns to some other activity but the returns maynot be realized for some time (i.e. farming, other regular source ofincome)Unlikely since only 15% have other regular income and 20% haveseasonal incomeNevertheless, can also examine heterogeneity by these factors-.10.1.2.3.4Pr(quitting)-200 -160 -120 -80 -40 0 40 80 120 160Ksh from needHas other regular income 95% CIDoes not have other regular income 95% CIHazard by having other regular incomeDupas and Robinson Needs, Targets and Labor Supply May 2, 2013
  • 67. Labor supply with subsistence constraint2. People may have such severe savings problems that they drop o afterreaching need because marginal value of additional income is minimalPeople with savings problems do drop o more quicklyBut, having this type of extreme savings problem over even a day isinconsistent with other work, for example Dupas and Robinson 20133. Same as above but eort costs might be so extreme that people quitimmediately afterWould likely have to interact with present-bias or savings dicultiessince otherwise better in the long run to work more when wage is highand less overallDupas and Robinson Needs, Targets and Labor Supply May 2, 2013
  • 68. Limited attentionAnother alternative is that people have a limited attention constraintForget to deal with these things until the last possible momentPossible, but people do report wanting to save for these sorts of needsAlso not consistent with lottery paymentsDupas and Robinson Needs, Targets and Labor Supply May 2, 2013
  • 69. Risk sharingWorkers work in same area, may know who has needPerhaps they compete less hard if they know somebody else needs thecashSeems unlikelyIf health capital is depleted, this is dominated by a transfer systemIncome and needs both must be observableNeeds are really common: 88% of days. Not much scope for insurance.Check this by including average needs of others in the same marketi.e. control for days in which everybody has a needGet same resultsDupas and Robinson Needs, Targets and Labor Supply May 2, 2013
  • 70. Outline1. Conceptual Framework2. Sample and Data3. Results4. Alternative Hypotheses5. Welfare Consequences6. Discussion ConclusionDupas and Robinson Needs, Targets and Labor Supply May 2, 2013
  • 71. Welfare ImplicationsWhat eect does any of this have on outcomes?Two main things we can look atIncome. Basic implication is the worker will work more hours for thesame level of income than he would have if he substitutedintertemporally.Health. If the health costs of eort are convex, such that working verylong days can deplete health capital, people induced to work more byshocks may be in worse endline health.Dupas and Robinson Needs, Targets and Labor Supply May 2, 2013
  • 72. Eect on IncomePerfectly optimizing worker should work more on days in which wage ishighWorkers can observe this much better than we can in the dataWe construct a lower bound - what would impact on income be ifpeople worked same hours every dayConstruct average hours and multiple by daily wage rateLost income could be much larger if workers had a positive elasticityDupas and Robinson Needs, Targets and Labor Supply May 2, 2013
  • 73. CDF of Income gain from constant daily hourshis graph shows the cumulative distribution function, across all 256 individuals in our sample, of the variable potential %0.1.2.3.4.5.6.7.8.91%atorbelow-.1 -.05 0 .05 .1 .15 .2 .25 .3 .35 .4 .45 .5Potential % Income GainPotential Percentage Income Gain to Constant Fixed Daily HoursDupas and Robinson Needs, Targets and Labor Supply May 2, 2013
  • 74. Eect on IncomeLower bound: median = 2.5%, mean = 5.0%,Very large for some individualsInterestingly, negative for only about 10% of the sample.Is this big or small?Doesnt look like a life-changing amountBut, it is consistent with other studiesCamerer et al (1997) also nd about 5-10% increaseKaur et al. (2013): 6% eect on productivity for those who choose apositive targetAnother benchmark: de Mel et al. (2008) cash drops to Sri Lankanrms4.6-5.3% monthly return to capital, not reinvestedBaseline prots, inventories of 3,840 LKR and 26,530 LKRImplies a 14-16% increase in capital stock to increase prots by 5%Dupas and Robinson Needs, Targets and Labor Supply May 2, 2013
  • 75. Eect on HealthDoes the variance in hours induced by targeting have healthconsequences?Ideally want random variation in targets across individuals - we donthave thatInstead, just look cross-sectionallyNo endline measure of healthInstead, look at whether worker was sick in the last week of the logExamine how this measure varies with the total number of hoursworked, and the standard deviation of hours workedWould like to instrument this with shocks, but rst stage is too weakDupas and Robinson Needs, Targets and Labor Supply May 2, 2013
  • 76. Eect on Health(1) (2) (3) (4)Total hours workedLog (total hours over sample period) 0.03 0.03 0.01 0.01(0.03) (0.03) (0.03) (0.02)Log (std. deviation daily hours over sample period) 0.18 0.14 0.12 0.08(0.083)** (0.084)* (0.069)* (0.07)Baseline Health MeasuresHealth is worse than average at baseline 0.06 0.12(0.06) (0.049)**Missed work at least once due to sickness 0.09 0.02in month prior to baseline (0.06) (0.05)Observations (one per individual) 252 252 252 252R-squared 0.03 0.06 0.02 0.05Mean of Dep. Var. 0.25 0.25 0.15 0.15Std. Dev. of Dep. Var 0.43 0.43 0.36 0.36Missed work due to sicknessin last week of logsNotes: Column 1 presents means of the independent variables (standard deviations in parentheses). Columns 2 and3 report regression coefficients of the given dependent variable on the full set of independent variables (standarderrors are in parentheses, clustered at the individual level). Regressions include controls for the total number of dayscovered in the logbooks. ***, **, * indicates significance at 1, 5 and 10%.Sick in last week of logsTotal shocksDupas and Robinson Needs, Targets and Labor Supply May 2, 2013
  • 77. Overall impactAll of this is cross-sectional and ultimately only suggestiveBut, some evidence that the eects on income and health are notcompletely negligibleDupas and Robinson Needs, Targets and Labor Supply May 2, 2013
  • 78. Outline1. Conceptual Framework2. Sample and Data3. Results4. Alternative Hypotheses5. Welfare Consequences6. Discussion ConclusionDupas and Robinson Needs, Targets and Labor Supply May 2, 2013
  • 79. Wrapping upPeople have time-varying cash needs, and tend to quit just afterreaching their needSuggests a form of income targetingWork up to the needBehavior also determined by earnings expectations (as in previous work)Yet random cash payouts do not undue this behaviorOnce set for the day, targets appear to stickTargets therefore are over labor incomePeople appear to be loss averse over these target amounts, or see themas an internal commitment deviceHeterogeneity: people with savings problems, and people with higheort costs, are more likely to quit after reaching targetSome welfare eects on income and potentially healthDupas and Robinson Needs, Targets and Labor Supply May 2, 2013
  • 80. DiscussionWhy targets?As discussed in Camerer et al. (1997), could be a way to solveself-control problemspresent-biased workers may be tempted to quit too earlyEspecially relevant in a physical demanding job like bike taxiingsetting a target before work may help prevent succumbing to thattemptationBut why not just choose a very high target then?Must be real to aect behaviorWhy income and not hours?Prevents taking too many breaksPotentially more veriable to others, for instance spouse?Dupas and Robinson Needs, Targets and Labor Supply May 2, 2013
  • 81. Policy ImplicationsPossibly policy implicationsCommitment devices to control eort (i.e. Kaur et al. 2013)Modern work arrangements (i.e. Kaur et al. 2013)Some role for things that force people to smooth needs: ROSCApayments, micro loans paid back in regular installments, etc.Quite high ROSCA participation in our sampleSimilar to Bauer et al. (2012) who argue that women take out loans tobe forced to pay them back because they are present-biased in moneyAugenblick et al. (2012) show that UCB undergrads are morepresent-biased in eort than money.Dupas and Robinson Needs, Targets and Labor Supply May 2, 2013
  • 82. Policy ImplicationsPossibly policy implicationsSome evidence suggesting that micro entrepreneurs in developingcountries more similar (in terms of attitudes, cognitive ability,motivation, etc.) to wage workers than large business owners (i.e. deMel, McKenzie and Woodru 2010). These results suggest anotherchannel by which wage employment may be benecial.Though our evidence is from one small part of the world, these issuesmay be relevant for many in the developing world, since many peoplework in demanding jobs in which they can set their own hoursDupas and Robinson Needs, Targets and Labor Supply May 2, 2013
  • 83. ConclusionThank you!Dupas and Robinson Needs, Targets and Labor Supply May 2, 2013
  • 84. APPENDIX SLIDESDupas and Robinson Needs, Targets and Labor Supply May 2, 2013
  • 85. Daily Log (page 1)288 88 88 88 88 88 88A2.What is the amount that youneed?A3.Did you work as a boda bodatoday? (if yes, skip to A5)Kama LA ruka hadi A5A4.If yes, at what time did youstart?Ukishajibu RUKA HADI A6A5.Why didnt you work as aboda today?A6.Time tripstartedTime tripendedPricepaid(Ksh)Time tripstartedTime tripendedPricepaid(Ksh)Time tripstartedTime tripendedPricepaid(Ksh)Time tripstartedTime tripendedPricepaid(Ksh)Time tripstartedTime tripendedPricepaid(Ksh)Time tripstartedTimetripendedPricepaid(Ksh)Time tripstartedTime tripendedPricepaid(Ksh)1.Passenger 1 : : /= : : /= : : /= : : /= : : /= : : /= : : /=2.Passenger 2 : : /= : : /= : : /= : : /= : : /= : : /= : : /=3.Passenger 3 : : /= : : /= : : /= : : /= : : /= : : /= : : /=4.Passenger 4 : : /= : : /= : : /= : : /= : : /= : : /= : : /=5.Passenger 5 : : /= : : /= : : /= : : /= : : /= : : /= : : /=6.Passenger 6 : : /= : : /= : : /= : : /= : : /= : : /= : : /=7.Passenger 7 : : /= : : /= : : /= : : /= : : /= : : /= : : /=8.Passenger 8 : : /= : : /= : : /= : : /= : : /= : : /= : : /=9.Passenger 9 : : /= : : /= : : /= : : /= : : /= : : /= : : /=10.Passenger 10 : : /= : : /= : : /= : : /= : : /= : : /= : : /=11.Passenger 11 : : /= : : /= : : /= : : /= : : /= : : /= : : /=12.Passenger 12 : : /= : : /= : : /= : : /= : : /= : : /= : : /=13.Passenger 13 : : /= : : /= : : /= : : /= : : /= : : /= : : /=14.Passenger 14 : : /= : : /= : : /= : : /= : : /= : : /= : : /=1 2 34 5 67 _________________|_____|_____|:|_____|_____|/= /= /= /=|_____|_____|:|_____|_____|1 2 34 5 67 _________________1 2 34 5 67 _________________1 2 34 5 67 _________________1 2 34 5 67 _________________1 2 34 5 67 _________________Friday Saturday Sunday25-Nov 26-Nov 27-Nov1 = Yes 2 = No 1 = Yes 2 = No1 = Yes 2 = No1 = Yes 2 = No 1 = Yes 2 = No1 2 34 5 67 8 9/=10_____________10_____________ 10_____________ 10_____________ 10_____________ 10_____________ 10_____________Please tell us about all events related to your boda boda work you have had today|_____|_____|:|_____|_____| |_____|_____|:|_____|_____| |_____|_____|:|_____|_____| |_____|_____|:|_____|_____|A1. Is there something in particularthat you need money for today?1 = repair bike, 2 = pay for medicalexpenses, 3 = pay housing bill, 4 =pay back loan, 5 = pay schoolexpenses, 6 = contribute to burial, 7= contribute to ROSCA, 8 = buyfood, 9=make up for recent bigexpense, 10 = Other (describe), 88= nothing specialPassengers1 2 34 5 67 _________________HEPRO Diary Monday TuesdayPlease circle your answer, where applicable1 2 34 5 67 8 9Thursday1 2 34 5 67 8 91 2 34 5 67 8 91 2 34 5 67 8 923-Nov 24-NovWednesday28-Nov1 2 34 5 67 8 91 2 34 5 67 8 9/= /=1 = Yes 2 = No 1 = Yes 2 = NoDate 29-Nov1 = was sick, 2 = something in HHwas sick, 3 = had to do some otherwork, 4 = had to travel, 5 = went tochurch, 6 = no customers today, 7 =other (describe)SKIP TO B1 after circling ananswer|_____|_____|:|_____|_____|Dupas and Robinson Needs, Targets and Labor Supply May 2, 2013
  • 86. Daily Log (page 2)3Friday Saturday Sunday25-Nov 26-Nov 27-NovHEPRO Diary Monday Tuesday Thursday23-Nov 24-NovWednesday28-NovDate 29-Nov15.Passenger 15 : : /= : : /= : : /= : : /= : : /= : : /= : : /=16.Passenger 16 : : /= : : /= : : /= : : /= : : /= : : /= : : /=17.Passenger 17 : : /= : : /= : : /= : : /= : : /= : : /= : : /=18.Passenger 18 : : /= : : /= : : /= : : /= : : /= : : /= : : /=A7. When did you stop boda work?A8.In total, how much money did youearn in fares today?B1.Did it rain today?If NO, skip to C1.B2aIf yes, at what time did itstart?B2b When did the rain stop?C1. Were you feeling sick today?If NO, skip to D1.C2a. If yes, did you seek care andif so where? (circle all thatapply)88 = Did not seek care (→C3a)1 = hospital 2 = clinic3 = doctor4 = traditional healer5 = pharmacy6 = other (describe)C2b At what time did you seekcare?C3a. Did you take any medicine?C3b If yes, at what time did youtake the medicine?C4. Total Ksh spent on care /medicines for yourself today?D1.Is anyone in the householdsick today? If NO, end.D2.If yes, which family memberis sick? Circle all that apply1 = spouse, 2 = child, 3 = other(describe)D3.Total spent on medical care /medicines for family member(Please include money you gave toyour spouse to buy drugs)|_____|_____|:|_____|_____|1 = Yes 2 = No 1 = Yes 2 = No 1 = Yes 2 = No 1 = Yes 2 = No|_____|_____|:|_____|_____| |_____|_____|:|_____|_____| |_____|_____|:|_____|_____| |_____|_____|:|_____|_____| |_____|_____|:|_____|_____| |_____|_____|:|_____|_____| |_____|_____|:|_____|_____||_____|_____|:|_____|_____||_____|_____|:|_____|_____|88 12 34 56 ____________1 = Yes 2 = No 1 = Yes 2 = No 1 = Yes 2 = No 1 = Yes 2 = No 1 = Yes 2 = No|_____|_____|:|_____|_____| |_____|_____|:|_____|_____| |_____|_____|:|_____|_____| |_____|_____|:|_____|_____||_____|_____|:|_____|_____| |_____|_____|:|_____|_____| |_____|_____|:|_____|_____| |_____|_____|:|_____|_____| |_____|_____|:|_____|_____| |_____|_____|:|_____|_____|1 = Yes 2 = No 1 = Yes 2 = No1 = Yes 2 = No 1 = Yes 2 = No|_____|_____|:|_____|_____| |_____|_____|:|_____|_____| |_____|_____|:|_____|_____| |_____|_____|:|_____|_____| |_____|_____|:|_____|_____| |_____|_____|:|_____|_____| |_____|_____|:|_____|_____|/=/= /=1 = Yes 2 = No 1 = Yes 2 = No 1 = Yes 2 = No 1 = Yes 2 = No1 = Yes 2 = No 1 = Yes 2 = No|_____|_____|:|_____|_____| |_____|_____|:|_____|_____||_____|_____|:|_____|_____| |_____|_____|:|_____|_____|Please tell us about tyour health today. Circle your answer, where applicable/= /=/= /= /=/=Please tell us about the weather today. Circle your answer, where applicable|_____|_____|:|_____|_____| |_____|_____|:|_____|_____| |_____|_____|:|_____|_____|1 = Yes 2 = No 1 = Yes 2 = No 1 = Yes 2 = No|_____|_____|:|_____|_____|1 = Yes 2 = No88 12 34 56 ____________88 12 34 56 _____________88 12 34 56 ____________88 12 34 56 _____________88 12 34 56 ____________88 12 34 56 _____________/=/= /=/=/= /=/= /= /= /=1 23 _________________1 23 _________________1 23 _________________Please tell us briefly about any health issues your household is experiencing today. Circle your answer, where applicable.1 23_________________1 23_________________1 23_________________1 23 _________________/= /=1 = Yes 2 = No 1 = Yes 2 = No 1 = Yes 2 = No 1 = Yes 2 = No 1 = Yes 2 = NoBackDupas and Robinson Needs, Targets and Labor Supply May 2, 2013
  • 87. Weekly LogFO COMMENTS: _______________________________________________________________________________________________________________________________________12-Dec 13-DecMonday Tuesday Wednesday Thursday FridayHEPRO DiaryTarehe [Date]Saturday Sunday7-Dec 8-Dec 9-Dec 10-Dec 11-DecB1a.B2. 1 = Ndio 2 = La 1 = Ndio 2 = La 1 = Ndio 2 = La 1 = Ndio 2 = La 1 = Ndio 2 = La 1 = Ndio 2 = La 1 = Ndio 2 = LaB2a.B3. 1 = Ndio 2 = La 1 = Ndio 2 = La 1 = Ndio 2 = La 1 = Ndio 2 = La 1 = Ndio 2 = La 1 = Ndio 2 = La 1 = Ndio 2 = LaB3a.B3b.B4. 1 = Ndio 2 = La 1 = Ndio 2 = La 1 = Ndio 2 = La 1 = Ndio 2 = La 1 = Ndio 2 = La 1 = Ndio 2 = La 1 = Ndio 2 = LaB4a.B5. 1 = Ndio 2 = La 1 = Ndio 2 = La 1 = Ndio 2 = La 1 = Ndio 2 = La 1 = Ndio 2 = La 1 = Ndio 2 = La 1 = Ndio 2 = LaB5a.B6. 1 = Ndio 2 = La 1 = Ndio 2 = La 1 = Ndio 2 = La 1 = Ndio 2 = La 1 = Ndio 2 = La 1 = Ndio 2 = La 1 = Ndio 2 = LaB6a.B7. 1 = Ndio 2 = La 1 = Ndio 2 = La 1 = Ndio 2 = La 1 = Ndio 2 = La 1 = Ndio 2 = La 1 = Ndio 2 = La 1 = Ndio 2 = LaB7a.B8. 1 = Ndio 2 = La 1 = Ndio 2 = La 1 = Ndio 2 = La 1 = Ndio 2 = La 1 = Ndio 2 = La 1 = Ndio 2 = La 1 = Ndio 2 = LaB8a.B9. 1 = Ndio 2 = La 1 = Ndio 2 = La 1 = Ndio 2 = La 1 = Ndio 2 = La 1 = Ndio 2 = La 1 = Ndio 2 = La 1 = Ndio 2 = LaB9a.B10. 1 = Ndio 2 = La 1 = Ndio 2 = La 1 = Ndio 2 = La 1 = Ndio 2 = La 1 = Ndio 2 = La 1 = Ndio 2 = La 1 = Ndio 2 = LaB10a.B11. 1 = Ndio 2 = La 1 = Ndio 2 = La 1 = Ndio 2 = La 1 = Ndio 2 = La 1 = Ndio 2 = La 1 = Ndio 2 = La 1 = Ndio 2 = LaB11a.B12. 1 = Ndio 2 = La 1 = Ndio 2 = La 1 = Ndio 2 = La 1 = Ndio 2 = La 1 = Ndio 2 = La 1 = Ndio 2 = La 1 = Ndio 2 = LaB12a.B13. 1 = Ndio 2 = La 1 = Ndio 2 = La 1 = Ndio 2 = La 1 = Ndio 2 = La 1 = Ndio 2 = La 1 = Ndio 2 = La 1 = Ndio 2 = LaB13a.C1.1 = Ndio 2 = La 1 = Ndio 2 = La 1 = Ndio 2 = La 1 = Ndio 2 = La 1 = Ndio 2 = La 1 = Ndio 2 = La 1 = Ndio 2 = LaIf it was a loan, what did you offer as collateral?FO: write-in answer. If no collateral, mark with a dashIf YES, how much did you pay? If goods / services, listapproximate cash valueDid you receive money, goods or services as a gift or loanfrom a family member / friend?FO: do not include transfers to spouse./=/=/= /=/= /=If YES, how much did you contribute?If YES, how much did you pay?/=/= /=If YES, how much did you receive? If goods / services, listapproximate cash valueDid you make a withdrawal from the bank?Did you contribute to a burial / matanga?If YES, how much did you contribute?/= /=Did you receive a payment from a ROSCA?If YES, how much did you receive?Did you purchase a durable good?If YES, how much did you spend?Did you receive a payment from a regular customer?If YES, how much did you receive?Did you repay a loan?If YES, what amount did you repay?Did you withraw funds from your home savings?If YES, how much did you withdraw?Did you give money, goods or services to a friend orfamily member without being asked (as a gift)?/=/= /=/= /=/= /=/= /=/=/= /=/= /=/=/= /=/=/=Did you receive any money from your spouse?Did a family member / friend ask you for money, goods orservices as a gift or loan?FO: do not include transfers to spouse.If YES, how much did you withdraw?Did you take a loan from the bank?If YES, what was the amount of the loan?Did you make a contribution to a ROSCA?/=/=/= /= /= /= /= /=/=/=/= /=/=/= /= /=/= /=/=Please tell us about any intra-household transfers. FO: Ask each set of questions (e.g., C1 C1a) for each day of the week, then proceed to the next set of questions (e.g., C2 C2a)If YES, how much did you give?If goods / services, list approximate cash value/=/=/= /=/=/=/= /=/=/=/= /=/= /=/=/= /=/=/=/=/= /= /=/=/= /= /= /=/= /= /= /=/= /= /=/=/= /= /=/= /= /=BackDupas and Robinson Needs, Targets and Labor Supply May 2, 2013
  • 88. Labor supply by baseline characteristics(1) (2) (3) (4) (5) (6) (7) (8) (9)Coef ObsMean (Std.Dev.)when Ind.Var = 0Coef ObsMean (Std.Dev.) whenInd. Var =0Coef ObsMean (Std.Dev.) whenInd. Var =0Symptoms are worse than average -0.06 12237 0.89 -0.66 11645 0.89 -7.19 12237 0.89(0.02)*** [251] (0.31) (0.30)** [251] (0.31) (7.65) [251] (0.31)Missed work in month prior to -0.05 12133 0.87 -0.49 11546 0.87 -12.10 12133 0.87baseline (0.02)** [249] (0.33) (0.29)* [249] (0.34) (7.35) [249] (0.33)Loss averse -0.07 11870 0.89 -0.85 11286 0.89 -15.41 11870 0.89(0.03)*** [245] (0.31) (0.32)*** [245] (0.31) (7.26)** [245] (0.31)Present-biased 0.00 11866 0.89 -0.31 11285 0.89 14.61 11866 0.89(0.03) [243] (0.31) (0.39) [243] (0.31) (9.54) [243] (0.31)Can get 1,000 Ksh from savings -0.02 11832 0.88 -0.20 11251 0.88 49.81 11832 0.88(0.05) [243] (0.32) (0.54) [243] (0.32) (20.99)** [243] (0.32)In ROSCA -0.05 12172 0.88 -0.63 11582 0.88 10.83 12172 0.88(0.02)** [249] (0.33) (0.34)* [249] (0.33) (6.97) [249] (0.33)Has bank account -0.03 12166 0.89 -0.42 11576 0.89 7.06 12166 0.89(0.02) [249] (0.31) (0.32) [249] (0.31) (9.30) [249] (0.31)Rents bike 0.14 8844 0.88 2.56 8478 0.88 97.86 8844 0.88(0.02)*** [262] (0.32) (0.43)*** [262] (0.32) (27.51)*** [262] (0.32)Has seasonal income -0.02 12017 0.88 -0.47 11439 0.88 5.79 12017 0.88(0.03) [247] (0.32) (0.34) [247] (0.32) (8.64) [247] (0.32)Has other regular income -0.08 12211 0.89 -1.35 11624 0.89 -16.40 12211 0.89(0.03)** [250] (0.32) (0.34)*** [250] (0.32) (7.41)** [250] (0.32)Worked Today If yes, total hours If yes, total incomebackDupas and Robinson Needs, Targets and Labor Supply May 2, 2013
  • 89. Hazard by Goal Amount-.2-.10.1.2.3Pr(quitting)-200-160-120 -80 -40 0 40 80 120 160Ksh from needCoefficient95% CICash need is at most 50 Ksh-.2-.10.1.2.3Pr(quitting)-200-160-120 -80 -40 0 40 80 120 160Ksh from needCoefficient95% CICash need is at most 100 Ksh-.2-.10.1.2.3Pr(quitting)-200-160-120 -80 -40 0 40 80 120 160Ksh from needCoefficient95% CICash need is between 100 and 200 Ksh-.2-.10.1.2.3Pr(quitting)-200-160-120 -80 -40 0 40 80 120 160Ksh from needCoefficient95% CICash need is greater than 200 KshBackDupas and Robinson Needs, Targets and Labor Supply May 2, 2013
  • 90. Needs and baseline characteristics(1) (2) (3) (4) (5) (6) (7) (8) (9)Coef ObsMean (Std.Dev.)when Ind.Var = 0Coef ObsMean (Std.Dev.) whenInd. Var =0Coef ObsMean (Std.Dev.) whenInd. Var =0Symptoms are worse than average -0.06 12237 0.89 -0.66 11645 0.89 -7.19 12237 0.89(0.02)*** [251] (0.31) (0.30)** [251] (0.31) (7.65) [251] (0.31)Missed work in month prior to -0.05 12133 0.87 -0.49 11546 0.87 -12.10 12133 0.87baseline (0.02)** [249] (0.33) (0.29)* [249] (0.34) (7.35) [249] (0.33)Loss averse -0.07 11870 0.89 -0.85 11286 0.89 -15.41 11870 0.89(0.03)*** [245] (0.31) (0.32)*** [245] (0.31) (7.26)** [245] (0.31)Present-biased 0.00 11866 0.89 -0.31 11285 0.89 14.61 11866 0.89(0.03) [243] (0.31) (0.39) [243] (0.31) (9.54) [243] (0.31)Can get 1,000 Ksh from savings -0.02 11832 0.88 -0.20 11251 0.88 49.81 11832 0.88(0.05) [243] (0.32) (0.54) [243] (0.32) (20.99)** [243] (0.32)In ROSCA -0.05 12172 0.88 -0.63 11582 0.88 10.83 12172 0.88(0.02)** [249] (0.33) (0.34)* [249] (0.33) (6.97) [249] (0.33)Has bank account -0.03 12166 0.89 -0.42 11576 0.89 7.06 12166 0.89(0.02) [249] (0.31) (0.32) [249] (0.31) (9.30) [249] (0.31)Rents bike 0.14 8844 0.88 2.56 8478 0.88 97.86 8844 0.88(0.02)*** [262] (0.32) (0.43)*** [262] (0.32) (27.51)*** [262] (0.32)Has seasonal income -0.02 12017 0.88 -0.47 11439 0.88 5.79 12017 0.88(0.03) [247] (0.32) (0.34) [247] (0.32) (8.64) [247] (0.32)Has other regular income -0.08 12211 0.89 -1.35 11624 0.89 -16.40 12211 0.89(0.03)** [250] (0.32) (0.34)*** [250] (0.32) (7.41)** [250] (0.32)Worked Today If yes, total hours If yes, total incomebackDupas and Robinson Needs, Targets and Labor Supply May 2, 2013
  • 91. Hours and Shocks over sample periodTable A7. Relationship between hours and shocks over entire sample period(1) (2)Log (Sum of Total Hours)Log (Standard Deviation of TotalHour Across Days)Total number of times school fees due 0.10 0.01(0.055)* (0.02)Total number of times ROSCA contributions due -0.01 0.00(0.01) (0.00)Total number of times asked for money by somebody 0.03 0.05(0.06) (0.021)**Total number of times had to attend funeral -0.01 0.02(0.04) (0.01)Total number of times household member sick 0.01 0.00(0.01) (0.00)Total number of time respondent sick 0.00 0.01(0.02) (0.01)Observations 253 252Mean of dependent variable 10.01 3.99Standard deviation of dependent variable 0.94 1.05Notes: Standard errors in parentheses. *, **, and *** indicate significance at 10%, 5%, and 1% respectively.BackDupas and Robinson Needs, Targets and Labor Supply May 2, 2013