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A bayesian nonparametric causal model
 Journal of Statistical Planning and Inference
, 2012
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Asymmetric Incentives in Subsidies: Evidence from a LargeScale Electricity Rebate Program
, 2014
"... together research and curricular programs on energy business, policy and technology commercialization. ..."
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together research and curricular programs on energy business, policy and technology commercialization.
DISCUSSION PAPERS Identification of Causal Education Effects Using a Discontinuity in School Entry Tests: First Results from a Pilot Study∗
, 2011
"... We use a credible regression discontinuity design to estimate causal education effects. Pupils in the Swiss education system had to pass a centrally organized exam that classified them into different levels of secondary school, and that ultimately determined their educational degree. A major featur ..."
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We use a credible regression discontinuity design to estimate causal education effects. Pupils in the Swiss education system had to pass a centrally organized exam that classified them into different levels of secondary school, and that ultimately determined their educational degree. A major feature of this exam was the local randomization around the classification threshold due to the impossibility of strategic sorting. Our preliminary results suggest large and significant effects on earnings, political interest, and attitudes toward immigrants. The extension to a wider set of data is part of ongoing research. JEL Classification: D72, I21, J15, J31
A Service of zbw Approximate permutation tests and induced order statistics in the regression discontinuity design Approximate Permutation Tests and Induced Order Statistics in the Regression Discontinuity Design *
"... StandardNutzungsbedingungen: Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden. Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, ..."
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StandardNutzungsbedingungen: Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden. Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen. Sofern die Verfasser die Dokumente unter OpenContentLizenzen (insbesondere CCLizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. Abstract This paper proposes an asymptotically valid permutation test for a testable implication of the identification assumption in the regression discontinuity design (RDD). Here, by testable implication, we mean the requirement that the distribution of observed baseline covariates should not change discontinuously at the threshold of the socalled running variable. This contrasts to the common practice of testing the weaker implication of continuity of the means of the covariates at the threshold. When testing our null hypothesis using observations that are "close" to the threshold, the standard requirement for the finite sample validity of a permutation does not necessarily hold. We therefore propose an asymptotic framework where there is a fixed number of closest observations to the threshold with the sample size going to infinity, and propose a permutation test based on the socalled induced order statistics that controls the limiting rejection probability under the null hypothesis. In a simulation study, we find that the new test controls size remarkably well in most designs. Finally, we use our test to evaluate the validity of the design in Lee (2008), a wellknown application of the RDD to study incumbency advantage. Terms of use: Documents in
EI @ Haas WP 244 Asymmetric Incentives in Subsidies: Evidence from a LargeScale Electricity Rebate
, 2013
"... Many countries use substantial public funds to subsidize reductions in negative externalities. However, such subsidies create asymmetric incentives because increases in externalities remain unpriced. This paper examines implications of such asymmetric subsidy incentives by using a regression discont ..."
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Many countries use substantial public funds to subsidize reductions in negative externalities. However, such subsidies create asymmetric incentives because increases in externalities remain unpriced. This paper examines implications of such asymmetric subsidy incentives by using a regression discontinuity design in California’s electricity rebate program that provided a financial reward for energy conservation. Using householdlevel panel data from administrative records, I find preciselyestimated zero causal effects in coastal areas. In contrast, the incentive produced a 5 % consumption reduction in inland areas. Income and climate conditions significantly drive the heterogeneity. Asymmetric subsidy structures weaken incentives because consumers far from the rebate target show little response. The overall program cost is 17.5 cents per kWh reduction and $390 per ton of carbon dioxide reduction, which is unlikely to be
Randomization Inference in the Regression Discontinuity Design to Study the Incumbency Advantage in the U.S. Senate ∗
, 2012
"... We study whether the incumbent status of previously elected parties and politicians translates into an electoral or incumbency advantage in the U.S. Senate, using a regression discontinuity (RD) design that compares states where the Democratic Party barely won a Senate election to states where the D ..."
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We study whether the incumbent status of previously elected parties and politicians translates into an electoral or incumbency advantage in the U.S. Senate, using a regression discontinuity (RD) design that compares states where the Democratic Party barely won a Senate election to states where the Democratic party barely lost. Since the Senate has only one hundred seats up for election every six years, the number of close races is small and standard RD estimation techniques are illsuited for our problem. We develop a randomization inference framework that is appropriate for our small sample size, and show that the results obtained with our approach can be markedly different from results based on standard methods. Our framework is general and applicable to any RD design where small sample sizes constrain researchers ’ ability to make inferences, and is motivated by a recent strand of the literature that advocates interpreting RD designs as local randomized experiments. Our approach has two steps. The first is to select a window around the cutoff where a randomizationtype condition is assumed to hold. Researchers can choose this window based on substantive knowledge
Approximate Permutation Tests and Induced Order Statistics in the Regression Discontinuity Design ∗
, 2015
"... This paper proposes an asymptotically valid permutation test for a testable implication of the identification assumption in the regression discontinuity design (RDD). Here, by testable implication, we mean the requirement that the distribution of observed baseline covariates should not change discon ..."
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This paper proposes an asymptotically valid permutation test for a testable implication of the identification assumption in the regression discontinuity design (RDD). Here, by testable implication, we mean the requirement that the distribution of observed baseline covariates should not change discontinuously at the threshold of the socalled running variable. This contrasts to the common practice of testing the weaker implication of continuity of the means of the covariates at the threshold. When testing our null hypothesis using observations that are “close ” to the threshold, the standard requirement for the finite sample validity of a permutation test does not necessarily hold. We therefore propose an asymptotic framework where there is a fixed number of closest observations to the threshold with the sample size going to infinity, and propose a permutation test based on the socalled induced order statistics that controls the limiting rejection probability under the null hypothesis. In a simulation study, we find that the new test controls size remarkably well in most designs. Finally, we use our test to evaluate the validity of the design in Lee (2008), a wellknown application of the RDD to study incumbency advantage.
Published online in Wiley Online Library (wileyonlinelibrary.com) DOI: 10.1002/jae.2481 BAYESIAN FUZZY REGRESSION DISCONTINUITY ANALYSIS AND RETURNS TO COMPULSORY SCHOOLING
, 2015
"... This paper is concerned with the use of a Bayesian approach to fuzzy regression discontinuity (RD) designs for understanding the returns to education. The discussion is motivated by the change in government policy in the UK in April of 1947, when the minimum school leaving age was raised from 14 to ..."
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This paper is concerned with the use of a Bayesian approach to fuzzy regression discontinuity (RD) designs for understanding the returns to education. The discussion is motivated by the change in government policy in the UK in April of 1947, when the minimum school leaving age was raised from 14 to 15—a change that had a discontinuous impact on the probability of leaving school at age 14 for cohorts who turned 14 around the time of the policy change. We develop a Bayesian fuzzy RD framework that allows us to take advantage of this discontinuity to calculate the effect of an additional year of education on subsequent log earnings for the (latent) class of subjects that complied with the policy change. We illustrate this approach with a new dataset composed
Bayesian Fuzzy Regression Discontinuity Analysis and Returns to Compulsory Schooling
, 2013
"... This paper is concerned with the use of a Bayesian approach to fuzzy regression discontinuity (RD) designs for understanding the returns to education. The discussion is motivated by the change in government policy in the United Kingdom (UK) in April of 1947 when the minimum school leaving age was r ..."
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This paper is concerned with the use of a Bayesian approach to fuzzy regression discontinuity (RD) designs for understanding the returns to education. The discussion is motivated by the change in government policy in the United Kingdom (UK) in April of 1947 when the minimum school leaving age was raised from 14 to 15, a change that had a discontinuous impact on the probability of leaving school at age 14 for cohorts who turned 14 around the time of the policy change. We develop a Bayesian fuzzy RD framework that allows us to take advantage of this discontinuity to calculate the effect of an additional year of education on subsequent log earnings for the (latent) class of subjects that complied with the policy change. We illustrate this approach with a new data set composed from the UK General Household Surveys.