2015
DOI: 10.3386/w20838
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Bounding the Labor Supply Responses to a Randomized Welfare Experiment: A Revealed Preference Approach

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Cited by 39 publications
(56 citation statements)
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References 25 publications
(45 reference statements)
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“…While the impact of the informality effects on tax collection can be informative (see for instance Bergolo and Cruces, 2014), measurement of the relevant elasticities is crucial for a full welfare analysis that quantifies the efficiency 3While AFAM's design implies a potential effect on the intensive margin of labor supply, we concentrate on the extensive margin of response. Unlike Kleven and Waseem (2013) or Kline and Tartari (2016), we are unable to measure (local) labor supply effects at the intensive margin since our data does not cover hours worked nor earnings (see Section 4). costs of social assistance programs.…”
Section: Introductionmentioning
confidence: 99%
“…While the impact of the informality effects on tax collection can be informative (see for instance Bergolo and Cruces, 2014), measurement of the relevant elasticities is crucial for a full welfare analysis that quantifies the efficiency 3While AFAM's design implies a potential effect on the intensive margin of labor supply, we concentrate on the extensive margin of response. Unlike Kleven and Waseem (2013) or Kline and Tartari (2016), we are unable to measure (local) labor supply effects at the intensive margin since our data does not cover hours worked nor earnings (see Section 4). costs of social assistance programs.…”
Section: Introductionmentioning
confidence: 99%
“…To mitigate the reliance on particular assumptions (e.g., on functional forms) in principle one could use revealed preference arguments to generate robust predictions from theory that are then used in design of an experiment. E.g., one could use results obtained by Pinto (2015) or Kline and Tartari (2016) to devise multiple treatment arms to test the implied restrictions. However, a model may not be necessary to enrich the experimental design to study underlying channels.…”
Section: Addressing the Issue Ex Ante Through The Design Of The Expermentioning
confidence: 99%
“…This is especially useful if the theory has explicit predictions about how the endogenous outcome responds to incentives. 35 This is pursued by Kline and Tartari (2016) However, as it is usually difficult to come by good instrumental variables, the real power of a well-designed RCT would be to manipulate sample selection directly.…”
Section: It Is Not Clear However That the Required Assumption Holdsmentioning
confidence: 99%
“…Such models have a surprisingly long history: early contributions include the analysis of linear regressions with mismeasured regressors by Frisch (1934) and the analysis of Cobb-Douglas production functions by Marschak and Andrews (1944). Now, partially identified models are common in virtually all parts of economics and econometrics: measurement error (Klepper and Leamer, 1984;Horowitz and Manski, 1995), missing data (Manski, 1989(Manski, , 1994Horowitz and Manski, 1998;Manski and Tamer, 2002), industrial organization (Tamer, 2003;Haile and Tamer, 2003;Ho and Pakes, 2014;Pakes et al, 2015), finance (Hansen and Jagannathan, 1991;Hansen et al, 1995), labor economics (Blundell et al, 2007;Kline et al, 2013;Kline and Tartari, 2015), program evaluation (Manski, 1990(Manski, , 1997Manski and Pepper, 2000;Heckman and Vytlacil, 2001;Bhattacharya et al, 2008Bhattacharya et al, , 2012Shaikh and Vytlacil, 2011), and macroeconomics (Faust, 1998;Canova and De Nicolo, 2002;Uhlig, 2005). The references above are far from exhaustive and simply illustrate the widespread popularity these types of models now enjoy in economics.…”
Section: Introductionmentioning
confidence: 99%