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  • The Aggregate Effect of School Choice: Evidence from a Two-Stage Experiment in India

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  • The Aggregate Effect of School Choice: Evidence from a Two-Stage Experiment in India — Supplementary Data
    file This Article First published online February 27 2015 doi 10 1093 qje qjv013 Quarterly Journal of Economics August 1 2015 vol 130 no 3 1011 1066 Abstract Free Full Text HTML Free Full Text PDF Supplementary Data Search this journal Advanced Current Issue November 2015 130 4 Alert me to new issues The Journal About the journal Rights permissions We are mobile find out more Journals Career Network Click here to contact the Editorial Office Editorial Office Trina Ott Assistant Editor 1805 Cambridge Street Cambridge MA 02138 617 496 3293 qje admin editorialexpress com Published on behalf of President and Fellows of Harvard University Impact Factor 6 654 5 Yr impact factor 9 794 Editors Pol Antràs Robert J Barro Lawrence F Katz Andrei Shleifer View full editorial board Assistant Editor Trina Ott Alerting Services Email table of contents Email Advance Access CiteTrack XML RSS feed For Authors Services for authors Instructions to authors Submit now Self archiving policy for authors P56qQ0myhZIZ9qtHtIIeI0jcYDo8lVt6 true Looking for your next opportunity Looking for jobs Corporate Services What we offer Advertising sales Reprints Supplements Most Most Read The Impact of Jury Race in Criminal Trials The High Frequency Trading Arms Race Frequent Batch Auctions as a Market Design Response Where is the land of Opportunity The Geography of Intergenerational Mobility in the United States The Employment Effects of Credit Market Disruptions Firm level Evidence from the 2008 9 Financial Crisis The Real Costs of Credit Access Evidence from the Payday Lending Market View all Most Read articles Most Cited The Market for Lemons Quality Uncertainty and the Market Mechanism Job Market Signaling How Much Should We Trust Differences In Differences Estimates A Theory of Fairness Competition and Cooperation A Behavioral Model of Rational Choice View all Most Cited articles Online ISSN 1531 4650

    Original URL path: https://qje.oxfordjournals.org/content/130/3/1011/suppl/DC1 (2016-02-18)
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  • Working over Time: Dynamic Inconsistency in Real Effort Tasks
    Economics 2015 130 3 1067 1115 doi 10 1093 qje qjv020 First published online May 6 2015 Abstract Free Full Text HTML Free Full Text PDF Free Supplementary Data Supplementary Data All Versions of this Article qjv020v1 qjv020v2 130 3 1067 most recent Classifications Series Editor s Choice Article Services Article metrics Alert me when cited Alert me if corrected Find similar articles Similar articles in Web of Science Add to my archive Download citation Request Permissions Citing Articles Load citing article information Citing articles via CrossRef Citing articles via Scopus Citing articles via Web of Science Citing articles via Google Scholar Google Scholar Articles by Augenblick N Articles by Sprenger C Search for related content Related Content C91 Laboratory Individual Behavior D12 Consumer Economics Empirical Analysis D81 Criteria for Decision Making under Risk and Uncertainty Load related web page information Share Email this article CiteULike Delicious Facebook Google Mendeley Twitter What s this Search this journal Advanced Current Issue November 2015 130 4 Alert me to new issues The Journal About the journal Rights permissions We are mobile find out more Journals Career Network Click here to contact the Editorial Office Editorial Office Trina Ott Assistant Editor 1805 Cambridge Street Cambridge MA 02138 617 496 3293 qje admin editorialexpress com Published on behalf of President and Fellows of Harvard University Impact Factor 6 654 5 Yr impact factor 9 794 Editors Pol Antràs Robert J Barro Lawrence F Katz Andrei Shleifer View full editorial board Assistant Editor Trina Ott Alerting Services Email table of contents Email Advance Access CiteTrack XML RSS feed For Authors Services for authors Instructions to authors Submit now Self archiving policy for authors P56qQ0myhZIZ9qtHtIIeI0jcYDo8lVt6 true Looking for your next opportunity Looking for jobs Corporate Services What we offer Advertising sales Reprints Supplements Most Most Read

    Original URL path: https://qje.oxfordjournals.org/content/130/3/1067.abstract (2016-02-18)
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  • Working over Time: Dynamic Inconsistency in Real Effort Tasks
    minimum work of the experiment and set ω 10 for our effort analysis The variable mml math display inline mml mrow mml msub mml mi mathvariant bold 1 mml mi mml mrow mml mi t mml mi mml mo mml mo mml mn 0 mml mn mml mrow mml msub mml mrow mml math 1t 0 is an indicator for whether the sooner work date t is the present As before the parameter β captures the degree of present bias and the parameter δ captures long run discounting Maximizing equation 5 subject to equation 1 mml math display inline mml mrow mml msub mml mi e mml mi mml mrow mml mi t mml mi mml mo mml mo mml mi t mml mi mml mrow mml msub mml mo mml mo mml mi R mml mi mml mo mml mo mml msub mml mi e mml mi mml mrow mml mi t mml mi mml mo mml mo mml mi k mml mi mml mo mml mo mml mi t mml mi mml mrow mml msub mml mo mml mo mml mn 50 mml mn mml mrow mml math et t R et k t 50 yields an intertemporal Euler equation which can be rearranged to obtain mml math display block mml mrow mml mi l mml mi mml mi o mml mi mml mi g mml mi mml mo stretchy true mml mo mml mfrac mml mrow mml msub mml mi e mml mi mml mi t mml mi mml msub mml mo mml mo mml mi ω mml mi mml mrow mml mrow mml msub mml mi e mml mi mml mrow mml mi t mml mi mml mo mml mo mml mi k mml mi mml mrow mml msub mml mo mml mo mml mi ω mml mi mml mrow mml mfrac mml mo stretchy true mml mo mml mo mml mo mml mfrac mml mrow mml mi l mml mi mml mi o mml mi mml mi g mml mi mml mo stretchy true mml mo mml mi β mml mi mml mo stretchy true mml mo mml mrow mml mrow mml mi γ mml mi mml mo mml mo mml mn 1 mml mn mml mrow mml mfrac mml mo mml mo mml mo stretchy true mml mo mml msub mml mi mathvariant bold 1 mml mi mml mrow mml mi t mml mi mml mo mml mo mml mn 0 mml mn mml mrow mml msub mml mo stretchy true mml mo mml mo mml mo mml mfrac mml mrow mml mi l mml mi mml mi o mml mi mml mi g mml mi mml mo stretchy true mml mo mml mi δ mml mi mml mo stretchy true mml mo mml mrow mml mrow mml mi γ mml mi mml mo mml mo mml mn 1 mml mn mml mrow mml mfrac mml mo mml mo mml mi k mml mi mml mo mml mo mml mo stretchy true mml mo mml mfrac mml mn 1 mml mn mml mrow mml mi γ mml mi mml mo mml mo mml mn 1 mml mn mml mrow mml mfrac mml mo stretchy true mml mo mml mo mml mo mml mi l mml mi mml mi o mml mi mml mi g mml mi mml mo stretchy true mml mo mml mi R mml mi mml mo stretchy true mml mo mml mo mml mo mml mrow mml math log et ωet k ω log β γ 1 1t 0 log δ γ 1 k 1γ 1 log R 6 As before we assume an additive error structure and estimate the linear regression implied by equation 6 using two limit Tobit regression The parameters of interest are again recovered from nonlinear combinations of regression coefficients with standard errors calculated via the delta method Online Appendix A provides detailed discussion of identification for such choices 31 Table III columns 3 through 5 present two limit Tobit regressions with standard errors clustered on the individual level In column 3 the analyzed data are the allocations for job 1 Greek transcription We find an estimated cost parameter mml math display inline mml mrow mml mi γ mml mi mml mo mml mo mml mn 1 624 mml mn mml mo mml mo mml mo stretchy false mml mo mml mn 0 114 mml mn mml mo stretchy false mml mo mml mrow mml math γ 1 624 0 114 Abstracting from discounting a subject with this parameter would be indifferent between completing all 50 tasks on one work date and completing 32 tasks on both work dates 32 This suggests nonfungibility in the allocation of tasks as individuals do desire to smooth intertemporally A further indication of nonfungibility is that in contrast to the monetary choices only 31 percent of allocations are at budget corners and only 1 subject has zero interior allocations The weekly discount factor of mml math display inline mml mrow mml mi δ mml mi mml mo mml mo mml mn 0 993 mml mn mml mrow mml math δ 0 993 is similar to our findings for monetary discounting In column 3 of Table III we estimate an aggregate mml math display inline mml mrow mml mi β mml mi mml mo mml mo mml mn 0 900 mml mn mml mo mml mo mml mo stretchy false mml mo mml mn 0 037 mml mn mml mo stretchy false mml mo mml mrow mml math β 0 900 0 037 and reject the null hypothesis of dynamic consistency χ 2 1 7 36 p 01 In column 4 we obtain broadly similar conclusions for job 2 the modified Tetris games We aggregate over the two jobs in column 5 controlling for the job and again document that subjects are significantly present biased over effort 33 The results of column 5 indicate that discount rates measured in advance of the week 2 work date are around 0 percent a week while discount rates measured on the week 2 work date are around 11 percent a week We therefore confirm our nonparametric findings on effort choices Finally our implemented analysis allows us to compare present bias across effort and money with χ 2 tests based on seemingly unrelated estimation techniques We reject the null hypothesis that the β identified in column 5 over effort is equal to that identified for monetary discounting in column 1 χ 2 1 6 37 p 01 or column 2 χ 2 1 8 27 p 01 Subjects are significantly more present biased over effort than over money 34 III C Individual Analysis On aggregate we find that subjects are significantly more present biased over work than over money In this subsection we investigate behavior at the individual level to understand the extent to which present bias over effort and money is correlated within the individual To investigate individual level discounting parameters we run fixed effect versions of the regressions provided in columns 2 and 5 of Table III 35 These regressions assume no heterogeneity in cost or utility function curvature and recover individual parameter estimates of β e present bias for effort and β m present bias for money as nonlinear combinations of regression coefficients The methods for identifying individual discounting parameters are discussed in Online Appendix A 36 Online Appendix Tables A5 and A6 provide individual estimates of β e and β m along with a summary of allocation behavior for both effort and money for each subject 37 Figure VI presents individual estimates and their correlation First note that nearly 60 percent of subjects have an estimated β m close to 1 indicating dynamic consistency for monetary discounting choices This is in contrast to only around 25 percent of subjects with β e close to 1 The mean value for β m is 0 99 std dev 0 06 whereas the mean value for β e is 0 91 std dev 0 20 The difference between these measures is significant t 3 09 p 01 Second note that for the majority of subjects when they deviate from dynamic consistency in effort they deviate in the direction of present bias View larger version In this window In a new window Download as PowerPoint Slide Figure VI Individual Estimates of Present Bias Since correlational studies e g Ashraf Karlin and Yin 2006 Meier and Sprenger 2010 often use binary measures of present bias we define the variables Present Biased e and Present Biased m which take the value 1 if the corresponding estimate of β lies strictly below 0 99 and 0 otherwise We find that 56 percent of subjects have a Present Biased e of 1 while only 33 percent of subjects have a Present Biased m of 1 The difference in proportions of individuals classified as present biased over work and money is significant z 2 31 p 02 38 Two important questions with respect to our individual measures arise First how much do these measures correlate within individual The answer is important for understanding both the validity of studies relying on monetary measures and the potential consistency of preferences across domains Significant correlations would suggest that there may be some important preference related behavior uncovered in monetary discounting studies 39 Figure VI presents a scatterplot of β m and β e In our sample of 75 subjects with both complete monetary and effort discounting choices we find that β e and β m have almost zero correlation ρ 0 05 p 66 Additionally we find that the binary measures for present bias Present Biased e and Present Biased m are also uncorrelated ρ 0 11 p 33 40 The second question concerning our estimated parameters is whether they can be validated in sample That is given that β e and β m are recovered as nonlinear combinations of regression coefficients to what extent do these measures predict present biased allocations of tasks and money To examine this internal validity question we generate difference measures for allocations For effort choices we calculate the budget share of each allocation for week 2 effort The difference in budget shares between subsequent allocation and initial allocation is what we call a budget share difference 41 As budget shares are valued between 0 1 our difference measure takes values on the interval 1 1 Negative numbers indicate present biased behavior and values of 0 indicate dynamic consistency Each subject has 10 such effort budget share difference measures in block 1 The average budget share difference for effort is 0 049 std dev 0 115 indicating that subjects allocate around 5 percent less of their work budget to the sooner work date when allocating in the present 42 At the individual level 49 of 80 subjects have an average budget share difference of less than 0 13 have an average difference of exactly 0 and 18 have an average difference greater than 0 demonstrating a modal pattern of present bias A similar measure is constructed for monetary discounting choices Taking only the three week delay data at each value of P we take the difference between the future allocation week 4 versus week 7 prospective budget share and the present allocation week 1 versus week 4 or week 4 versus week 7 budget share This measure takes values on the interval 1 1 with negative numbers indicating present biased behavior Each subject has 10 such monetary budget share difference measures The average budget share difference for money is 0 029 std dev 0 134 43 At the individual level 28 of 75 subjects have an average budget share difference of less than 0 32 have an average difference of exactly 0 and 15 have an average difference greater than 0 demonstrating a modal pattern of dynamic consistency The nonparametric budget share difference measures are closely correlated with our parametric estimates at the individual level The correlation between β e and each individual s average budget share difference for effort is ρ 0 948 p 01 Of the 49 individuals with negative average budget share differences for effort 47 have estimates of β e 1 Of the 18 individuals with positive average budget share differences for effort all 18 have estimates of β e 1 Of the 13 individuals with zero average budget share differences for effort 11 have β e 1 and 2 have β e 1 003 The correlation between β m and each individual s average budget share difference for money is ρ 0 997 p 01 Of the 28 individuals with negative average budget share differences for money all 28 have estimates of β m 1 Of the 15 individuals with positive average budget share differences for money all 15 have estimates of β m 1 Of the 32 individuals with zero average budget share differences for money all 32 have β m 1 44 This apparent internal validity gives us confidence that our parameter estimates for present bias are indeed tightly linked with present biased data patterns appropriately capturing the behavior In the next section we move out of sample to investigate commitment demand The investigation of commitment demand is critical to ruling out potential alternative explanations for time inconsistency in effort allocations Our preferred explanation is the existence of a present bias in individual decision making However many alternative explanations exist for rationalizing these data patterns Chief among these alternatives are the existence of unanticipated shocks to the cost of performing tasks either in general or specific to tasks in week 2 resolving uncertainty between allocation times and subject exhaustion or error These alternative explanations are considered in detail in Online Appendix C Importantly we show in Online Appendix C that under none of these alternatives would we expect a clear link between the behavioral pattern of reallocating fewer tasks to the present and commitment demand This is in contrast to a model of present bias under the assumption of sophistication Sophisticated present biased individuals may have demand for commitment In the next section we document commitment demand on the aggregate level and link commitment to measured present bias III D Commitment In week 4 of our experiment subjects are offered a probabilistic commitment device Subjects are asked whether they prefer the allocation that counts to come from their week 4 allocations with probability 0 1 plus an amount X or with probability 0 9 plus an amount Y with either X 0 or Y 0 The second of these choices represents commitment and X Y is the price of commitment 45 We begin by analyzing the simple choice between commitment and flexibility at price zero X 0 and Y 0 and in subsection 1 we explore the value of commitment and choices when X or Y are not 0 In the simple choice where neither commitment nor flexibility were costly 59 percent 47 out of 80 of subjects choose to commit We define the binary variable Commit 1 which takes the value 1 if a subject chooses to commit in this decision Figure VII presents block 1 task allocation behavior separated by commitment choice in block 2 Immediately apparent from Figure VII is that experimental behavior separates along commitment choice Subjects who choose commitment in week 4 made substantially present biased task allocations in week 2 given their initial week 1 allocations Controlling for all task rate and task interactions subjects who choose commitment allocate 3 58 fewer tasks to the sooner work date when it is the present F 1 46 12 18 p 01 Subjects who do not demand commitment make more similar initial allocations and subsequent allocations of effort Controlling for all task rate and task interactions they only allocate 0 89 fewer tasks to the sooner work date when it is the present F 1 32 4 01 p 05 Furthermore subjects who demand commitment in week 4 altered their allocations by significantly more tasks than subjects who did not demand commitment F 1 79 5 84 p 02 46 View larger version In this window In a new window Download as PowerPoint Slide Figure VII Commitment Choice and Allocation Behavior Table IV generates a similar conclusion with parametric estimates In columns 3 and 4 we find that subjects who choose commitment in block 2 are significantly present biased over effort in block 1 χ 2 1 9 00 p 01 For subjects who do not choose commitment we cannot reject the null hypothesis of β 1 at conventional levels χ 2 1 2 64 p 10 Further we reject the null hypothesis of equal present bias across committers and non committers χ 2 1 4 85 p 03 47 View this table In this window In a new window Table IV Monetary and Real Effort Discounting by Commitment In columns 1 and 2 of Table VI we repeat this exercise predicting commitment choice for effort using present bias parameters from monetary decisions While subjects who demand commitment also seem directionally more present biased for monetary decisions than subjects who do not demand commitment the difference is not significant p 26 These findings indicate that present bias in effort is significantly related to future commitment choice Individuals who are present biased over effort are substantially more likely to choose commitment at price 0 An important caveat for this exercise is that correlation is far from perfect For example the raw correlation between β e and commitment choice is ρ 0 225 p 04 implying an R squared value of around 5 percent Substantial variance in the choice of commitment remains unexplained There are several potential reasons for this lack of explanatory power A natural first possibility is substantial naiveté Though our results suggest at least partial sophistication on average many subjects may be naive with respect to their dynamic inconsistency Furthermore among partially sophisticated individuals there may be limited correlation between behavior and beliefs such that individuals with both high and low values of β e may share similar beliefs as to their future behavior Third there may be uncertainty in the work environment uncontrolled by the researcher Even sophisticated present biased individuals may wish to remain flexible In a later subsection and Online Appendix D we discuss uncertainty and the benefits of flexibility in detail noting that the value of commitment is likely influenced by the unmodeled benefits of flexibility Fourth the allocation decisions may be subject to substantial noise leading at least partially to a misestimation of preferences and a misclassification of subjects Each of these forces may be at play to certain degrees reducing our ability to tightly measure present bias and the extent of sophistication However our finding of a significant present bias and a correlation between present bias and commitment demand points to at least partial sophistication for some subjects It is comforting for a theory of sophisticated present bias to find that present bias predicts commitment demand However the result is only meaningful if we can show that commitment places a binding constraint on subjects behavior Do individuals who demand commitment actually restrict their own activities forcing themselves to complete more work than they instantaneously desire 48 Given the nature of our commitment device commitment will bind whenever initial allocations differ from subsequent allocations Two such comparisons are considered First we consider the first block of the experiment when no commitment contract is available How many more tasks would subjects have been required to complete in week 2 had commitment been in place To answer this question we examine budget share differences for block 1 Noncommitters have a mean budget share difference of 0 018 clustered std err 0 009 allocating about 2 percentage points less of each budget to week 2 when deciding in the present In contrast committers have a mean budget share difference of mml math display inline mml mrow mml mo mml mo mml mn 0 072 mml mn mml mo mml mo mml mo stretchy false mml mo mml mn 0 020 mml mn mml mo stretchy false mml mo mml mrow mml math 0 072 0 020 allocating 7 percentage points less to week 2 when deciding in the present Although both values are significantly different from zero F 1 79 4 14 p 05 F 1 79 12 39 p 01 respectively the difference between the two is also statistically significant F 1 79 5 88 p 02 Hence had commitment been in place in week 2 and had subjects made the same choices committers would have been required to complete significantly more work than they instantaneously desired and would have been more restricted than noncommitters The same analysis can be done for block 2 focusing on required work in week 5 Noncommitters have a mean budget share difference of mml math display inline mml mrow mml mn 0 011 mml mn mml mo stretchy false mml mo mml mn 0 017 mml mn mml mo stretchy false mml mo mml mrow mml math 0 011 0 017 while committers have a mean difference of mml math display inline mml mrow mml mo mml mo mml mn 0 030 mml mn mml mo mml mo mml mo stretchy false mml mo mml mn 0 013 mml mn mml mo stretchy false mml mo mml mrow mml math 0 030 0 013 The difference for committers remains significantly different from zero F 1 79 5 57 p 02 and the difference between the two remains significant at the 10 percent level F 1 79 3 68 p 06 49 Hence in the presence of commitment in week 5 committed subjects are required to complete significantly more work than they instantaneously desire and are more restricted than noncommitted subjects We are aware of two prior exercises exploring the potential extent of present bias and its correlation with commitment demand Kaur Kremer and Mullainathan 2010 link the apparently present biased behavior of working harder on paydays with demand for a dominated wage contract wherein individuals choose a work target If the work target is not met an individual receives a low piece rate wage whereas if it is met or exceeded the individual receives a higher piece rate wage As the dominated wage contract can be viewed as a commitment to complete a certain amount of work this represents a potential link between commitment and present bias Commitment levels are chosen by individuals themselves and are set to around one sixth of daily production on average Calculations indicate that committing subjects would have missed their target with probability around 0 091 in the absence of commitment and do miss their target with commitment in place with probability 0 026 Hence commitment can viewed as binding in about 7 5 percent of cases effectively forcing an individual to do more work than they instantaneously desire Ashraf Karlan and Yin 2006 consider hypothetical intertemporal choices over money rice and ice cream and link those to take up of a savings commitment device The authors show that present bias in the hypothetical monetary decisions is significantly correlated at the 10 percent level with take up for women We contrast two dimensions of our study with these prior findings The first concerns the techniques used to measure dynamic inconsistency and the second is the extent to which subjects are bound by commitment As opposed to monetary discounting measures or dynamic inconsistency inferred from payday effects we attempt to measure discounting directly with intertemporal allocations of effort delivering identification As opposed to commitments with somewhat limited binding probabilities our committing subjects are clearly bound by commitment 1 The Value of Commitment A natural question is how much should subjects be willing to pay for commitment In Online Appendix A we present the value of commitment V as the utility difference between the discounted costs of commitment and flexibility Given our experimental structure we can only assess the monetary value of commitment Virtually nobody is willing to pay more than 0 25 for commitment with 91 percent of subjects preferring flexibility when the price of commitment is 0 25 Likewise nobody is willing to pay more than 0 25 for flexibility with 90 percent of subjects preferring commitment when the price of commitment is 0 25 Taking the midpoint of each person s price list switching interval the data thus imply a median valuation of 0 125 50 For committers and noncommitters the median valuation is 0 125 and 0 125 respectively What do these monetary valuations imply for the extent of V and correspondingly for the extent of sophistication In Online Appendix A we theoretically investigate the valuation of commitment through the lens of the partially sophisticated quasi hyperbolic model of O Donoghue and Rabin 2001 We recover the valuation of commitment V for stationary cost functions This analysis shows that the value of commitment is linked to the extent of sophistication which is governed by sophistication parameter mml math display inline mml mover accent true mml mi β mml mi mml mo mml mo mml mover mml math β reflecting an individual s assessment of their future present bias If mml math display inline mml mrow mml mover accent true mml mi β mml mi mml mo mml mo mml mover mml mo mml mo mml mn 1 mml mn mml mrow mml math β 1 an individual is perfectly naive and if mml math display inline mml mrow mml mover accent true mml mi β mml mi mml mo mml mo mml mover mml mo mml mo mml mi β mml mi mml mrow mml math β β an individual is perfectly sophisticated Values of mml math display inline mml mrow mml mover accent true mml mi β mml mi mml mo mml mo mml mover mml mo mml mo mml mo mml mo mml mi β mml mi mml mo mml mo mml mn 1 mml mn mml mo mml mo mml mrow mml math β β 1 correspond to partial sophistication That present bias is predictive of commitment demand at price 0 indicates at least partial sophistication on average mml math display inline mml mrow mml mover accent true mml mi β mml mi mml mo mml mo mml mover mml mo mml mo mml mn 1 mml mn mml mrow mml math β 1 The level of V can be calculated directly for the fully sophisticated benchmark of mml math display inline mml mrow mml mover accent true mml mi β mml mi mml mo mml mo mml mover mml mo mml mo mml mi β mml mi mml mrow mml math β β which implies a perfect forecast for present biased behavior Using the parameters estimates of Table IV columns 3 and 4 and the actual allocations at R 1 we can calculate the fully sophisticated value of commitment for committing and noncomitting subjects For committing subjects we calculate mml math display inline mml mrow mml msub mml mi V mml mi mml mrow mml mi C mml mi mml mo mml mo mml mn 1 mml mn mml mrow mml msub mml mo mml mo mml mn 1 23 mml mn mml mrow mml math VC 1 1 23 which can be expressed in equivalent number of tasks as mml math display inline mml mrow mml msup mml mi c mml mi mml mrow mml mo mml mo mml mn 1 mml mn mml mrow mml msup mml mo stretchy false mml mo mml mn 1 23 mml mn mml mo stretchy false mml mo mml mo mml mo mml mn 1 14 mml mn mml mrow mml math c 1 1 23 1 14 tasks For noncomitting subjects we calculate mml math display inline mml mrow mml msub mml mi V mml mi mml mrow mml mi C mml mi mml mo mml mo mml mn 0 mml mn mml mrow mml msub mml mo mml mo mml mo mml mo mml mn 2 06 mml mn mml mrow mml math VC 0 2 06 which can be expressed in equivalent number of tasks as 1 59 tasks To relate the value of roughly two tasks to money note that on average using minimum work completion rate subjects complete approximately 60 tasks per hour Assuming earnings of around 12 per hour and a constant task value a subject would be willing to complete one task for around 0 20 51 Hence the monetary value of commitment should be around 0 23 for committing subjects and the value of flexibility should be around 0 32 for noncommitting subjects These values compare favorably to the monetary valuations reported above Hence assuming complete sophistication and no additional benefits to flexibility we predict monetary commitment valuations reasonably close to the valuations expressed by subjects 52 We are hesitant to draw strong conclusions beyond the plausibility of sophistication from our commitment valuation data First given the ex post parameter estimates our elicitation procedure clearly was not optimized for fine price differentiations Second it is possible that subjects largely followed the money in the elicitation preferring either commitment or flexibility depending on which option provided additional payment A direct experiment precisely identifying mml math display inline mml mover accent true mml mi β mml mi mml mo mml mo mml mover mml math β is a clear next step that research in this vein should take III E Between Subjects Replication Exercise A key contribution of our data is the documentation of limited present bias in the domain of money and more substantial present bias in the domain of work One interpretation is that models of dynamic inconsistency are validated when tested in their relevant domain consumption and that choices over fungible monetary payments cannot easily speak to such models predictions However in our within subjects study several design choices were made that might muddy this interpretation First subjects faced different interest rates and forms of budget constraint for effort and for money 53 Second the delay lengths for money were three to six weeks whereas the delay lengths for effort were only one week Third subjects always completed their effort allocations prior to completing their monetary allocations Fourth present bias is identified for effort from only a dynamic choice while present bias is identified for money from a combination of static and dynamic choices 54 Fifth for effort one allocation was chosen to be the allocation that counts from the initial and subsequent allocations with an asymmetric probability while for money each allocation could be the allocation that counts with equal probability Further the week 4 monetary choices were paid separately from the week 1 choices Though each design choice has a natural motivation including our desire to replicate prior exercises one could potentially imagine them influencing the degree of dynamic inconsistency 55 To alleviate these concerns we conducted a between subjects replication exercise Two hundred subjects again from the UC Berkeley Xlab subject pool were randomized into two conditions one in which allocations were made for money and one in which allocations were made for Greek transcription In both conditions subjects selected into a four week study on decision making over time and were informed that their earnings would be approximately 60 if all aspects of the study were completed The main goal of the replication exercise is to keep allocation decisions identical with the only difference being whether allocations are over money or effort Mirroring our effort study in week 1 of the replication exercise subjects make allocations over weeks 2 and 3 In week 2 subjects again make allocations over weeks 2 and 3 All allocations are made on a study website either in the lab in week 1 or on any computer with Internet access in week 2 In week 2 one of the week 1 or week 2 decisions is chosen at random with each having equal probability and the corresponding allocation is implemented For both effort and money allocations are made using budgets of the form mml math display block mml mrow mml mi P mml mi mml msub mml mi a mml mi mml mn 2 mml mn mml msub mml mo mml mo mml msub mml mi a mml mi mml mn 3 mml mn mml msub mml mo mml mo mml mi m mml mi mml mo mml mo mml mrow mml math Pa2 a3 m where a 2 refers to an allocation of either effort or money to week 2 and a 3 refers to an allocation of either effort or money to week 3 For both effort and money mml math display inline mml mrow mml mi P mml mi mml mo mml mo mml mo mml mo mml mn 0 66 mml mn mml mo mml mo mml mn 0 8 mml mn mml mo mml mo mml mn 0 91 mml mn mml mo mml mo mml mn 0 95 mml mn mml mo mml mo mml mn 1 mml mn mml mo mml mo mml mn 1 05 mml mn mml mo mml mo mml mn 1 11 mml mn mml mo mml mo mml mn 1 25 mml mn mml mo mml mo mml mn 1 54 mml mn mml mo mml mo mml mrow mml math P 0 66 0 8 0 91 0 95 1 1 05 1 11 1 25 1 54 covering the interest rates used for both money and effort from our initial experiment For money mml math display inline mml mrow mml mi m mml mi mml mo mml mo mml mi mml mi mml mn 20 mml mn mml mrow mml math m 20 and for effort m 60 tasks such that units are easily matched by dividing by 3 Following our prior study minimum payments of 5 and minimum work of 10 tasks are implemented in weeks 1 2 and 3 We attempt to put precise time stamps on both the completion of tasks and the collection of money For effort subjects are told they must complete their tasks from the chosen allocation on a study website between 9 am and 6 pm on the relevant day in weeks 2 and 3 For money subjects are told they must collect their payments from the chosen allocation at the UC Berkeley Xlab between 9 am and 6 pm on the relevant day in weeks 2 and 3 To make the week 2 allocations as immediate as possible subjects are additionally told in advance they will have to either complete their week 2 tasks or collect their week 2 funds within two hours of making their week 2 allocations Online Appendix G has the full study instructions If subjects complete all aspects of the study including collecting their money or completing their tasks on each relevant date within the relevant time window they are eligible for a completion payment paid in the fourth week of the study For effort the completion payment is 60 with a noncompletion payment of 5 For money the completion payment is 30 with a noncompletion payment of 5 All payments including those from monetary allocations are made in cash at the Xlab by a single research assistant who remained in place from 9 am to 6 pm on the relevant dates All 200 subjects began the study on Thursday April 17 2014 Of these a total of 194 completed the study on Thursday May 1 2014 with 95 from the effort condition and 99 from the money condition In this between subjects design we can directly compare present bias across conditions Figure VIII plots the amount of money in Panel A out of 20 or the number of tasks in Panel B out of 60 and allocated to week 3 for each level of P Separate series are provided for when the allocation is made in week 1 and in week 2 Note that because the budget constraints are identical week 3 tasks are decreasing in P whereas week 3 money is increasing in

    Original URL path: https://qje.oxfordjournals.org/content/130/3/1067.full (2016-02-18)
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  • Working over Time: Dynamic Inconsistency in Real Effort Tasks

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  • Working over Time: Dynamic Inconsistency in Real Effort Tasks* — Working over Time: Dynamic Inconsistency in Real Effort Tasks — Supplementary Data
    May 6 2015 doi 10 1093 qje qjv020 Quarterly Journal of Economics August 1 2015 vol 130 no 3 1067 1115 Abstract Free Full Text HTML Free Full Text PDF Supplementary Data Supplementary Data Search this journal Advanced Current Issue November 2015 130 4 Alert me to new issues The Journal About the journal Rights permissions We are mobile find out more Journals Career Network Click here to contact the Editorial Office Editorial Office Trina Ott Assistant Editor 1805 Cambridge Street Cambridge MA 02138 617 496 3293 qje admin editorialexpress com Published on behalf of President and Fellows of Harvard University Impact Factor 6 654 5 Yr impact factor 9 794 Editors Pol Antràs Robert J Barro Lawrence F Katz Andrei Shleifer View full editorial board Assistant Editor Trina Ott Alerting Services Email table of contents Email Advance Access CiteTrack XML RSS feed For Authors Services for authors Instructions to authors Submit now Self archiving policy for authors P56qQ0myhZIZ9qtHtIIeI0jcYDo8lVt6 true Looking for your next opportunity Looking for jobs Corporate Services What we offer Advertising sales Reprints Supplements Most Most Read The Impact of Jury Race in Criminal Trials The High Frequency Trading Arms Race Frequent Batch Auctions as a Market Design Response Where is the land of Opportunity The Geography of Intergenerational Mobility in the United States The Employment Effects of Credit Market Disruptions Firm level Evidence from the 2008 9 Financial Crisis The Real Costs of Credit Access Evidence from the Payday Lending Market View all Most Read articles Most Cited The Market for Lemons Quality Uncertainty and the Market Mechanism Job Market Signaling How Much Should We Trust Differences In Differences Estimates A Theory of Fairness Competition and Cooperation A Behavioral Model of Rational Choice View all Most Cited articles Online ISSN 1531 4650 Print ISSN 0033 5533

    Original URL path: https://qje.oxfordjournals.org/content/130/3/1067/suppl/DC1 (2016-02-18)
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  • Supplementary Data
    are mobile find out more Journals Career Network Click here to contact the Editorial Office Editorial Office Trina Ott Assistant Editor 1805 Cambridge Street Cambridge MA 02138 617 496 3293 qje admin editorialexpress com Published on behalf of President and Fellows of Harvard University Impact Factor 6 654 5 Yr impact factor 9 794 Editors Pol Antràs Robert J Barro Lawrence F Katz Andrei Shleifer View full editorial board Assistant Editor Trina Ott Alerting Services Email table of contents Email Advance Access CiteTrack XML RSS feed For Authors Services for authors Instructions to authors Submit now Self archiving policy for authors P56qQ0myhZIZ9qtHtIIeI0jcYDo8lVt6 true Looking for your next opportunity Looking for jobs Corporate Services What we offer Advertising sales Reprints Supplements Most Most Read The Impact of Jury Race in Criminal Trials The High Frequency Trading Arms Race Frequent Batch Auctions as a Market Design Response Where is the land of Opportunity The Geography of Intergenerational Mobility in the United States The Employment Effects of Credit Market Disruptions Firm level Evidence from the 2008 9 Financial Crisis The Real Costs of Credit Access Evidence from the Payday Lending Market View all Most Read articles Most Cited The Market for Lemons Quality

    Original URL path: https://qje.oxfordjournals.org/content/130/3/1067/suppl/DC2 (2016-02-18)
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  • Site Selection Bias in Program Evaluation
    Article The Quarterly Journal of Economics 2015 130 3 1117 1165 doi 10 1093 qje qjv015 First published online March 18 2015 Abstract Free Full Text HTML Full Text PDF Supplementary Data Supplementary Data All Versions of this Article qjv015v1 qjv015v2 130 3 1117 most recent Classifications Article Services Article metrics Alert me when cited Alert me if corrected Find similar articles Similar articles in Web of Science Add to my archive Download citation Request Permissions Citing Articles Load citing article information Citing articles via CrossRef Citing articles via Scopus Citing articles via Web of Science Citing articles via Google Scholar Google Scholar Articles by Allcott H Search for related content Related Content C93 Field Experiments D12 Consumer Economics Empirical Analysis L94 Electric Utilities O12 Microeconomic Analyses of Economic Development Q41 Demand and Supply Load related web page information Share Email this article CiteULike Delicious Facebook Google Mendeley Twitter What s this Search this journal Advanced Current Issue November 2015 130 4 Alert me to new issues The Journal About the journal Rights permissions We are mobile find out more Journals Career Network Click here to contact the Editorial Office Editorial Office Trina Ott Assistant Editor 1805 Cambridge Street Cambridge MA 02138 617 496 3293 qje admin editorialexpress com Published on behalf of President and Fellows of Harvard University Impact Factor 6 654 5 Yr impact factor 9 794 Editors Pol Antràs Robert J Barro Lawrence F Katz Andrei Shleifer View full editorial board Assistant Editor Trina Ott Alerting Services Email table of contents Email Advance Access CiteTrack XML RSS feed For Authors Services for authors Instructions to authors Submit now Self archiving policy for authors P56qQ0myhZIZ9qtHtIIeI0jcYDo8lVt6 true Looking for your next opportunity Looking for jobs Corporate Services What we offer Advertising sales Reprints Supplements Most Most Read The Impact

    Original URL path: https://qje.oxfordjournals.org/content/130/3/1117.abstract (2016-02-18)
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