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David S. Lee

Bio: David S. Lee is an academic researcher from Princeton University. The author has contributed to research in topics: Regression discontinuity design & Wage. The author has an hindex of 36, co-authored 71 publications receiving 13720 citations. Previous affiliations of David S. Lee include National Bureau of Economic Research & Harvard University.


Papers
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TL;DR: In this article, the authors provide an introduction and user guide to regression discontinuity (RD) design for empirical researchers, including the basic theory behind RD design, details when RD is likely to be valid or invalid given economic incentives.
Abstract: This paper provides an introduction and "user guide" to Regression Discontinuity (RD) designs for empirical researchers. It presents the basic theory behind the research design, details when RD is likely to be valid or invalid given economic incentives, explains why it is considered a "quasi-experimental" design, and summarizes different ways (with their advantages and disadvantages) of estimating RD designs and the limitations of interpreting these estimates. Concepts are discussed using examples drawn from the growing body of empirical research using RD.

3,455 citations

Journal ArticleDOI
TL;DR: In this paper, the authors provide an introduction and user guide to regression discontinuity (RD) designs for empirical researchers, and discuss the advantages and disadvantages of estimating RD designs and the limitations of interpreting these estimates.
Abstract: This paper provides an introduction and “user guide” to Regression Discontinuity (RD) designs for empirical researchers. It presents the basic theory behind the research design, details when RD is likely to be valid or invalid given economic incentives, explains why it is considered a “quasi-experimental” design, and summarizes different ways (with their advantages and disadvantages) of estimating RD designs and the limitations of interpreting these estimates. Concepts are discussed using examples drawn from the growing body of empirical research using RD. ( JEL C21, C31)

2,687 citations

Journal ArticleDOI
TL;DR: In this article, the authors established the relatively weak conditions under which causal inferences from a regressiondiscontinuity analysis can be as credible as those from a randomized experiment, and hence under which the validity of the RD design can be tested by examining whether or not there is a discontinuity in any pre-determined (or baseline) variables at the RD threshold.

1,591 citations

Journal ArticleDOI
TL;DR: The authors empirically assesses the wage effects of the Job Corps program, one of the largest federally funded job training programs in the US Even with the aid of a randomized experiment, the impact of a training program on wages is difficult to study because of sample selection, a pervasive problem in applied micro-econometric research.
Abstract: This paper empirically assesses the wage effects of the Job Corps program, one of the largest federally funded job training programs in the US Even with the aid of a randomized experiment, the impact of a training program on wages is difficult to study because of sample selection, a pervasive problem in applied microeconometric research Wage rates are only observed for those who are employed, and employment status itself may be affected by the training program This paper develops an intuitive trimming procedure for bounding average treatment effects in the presence of sample selection In contrast to existing methods, the procedure requires neither exclusion restrictions nor a bounded support for the outcome of interest Identification results, estimators, and their asymptotic distribution are presented The bounds suggest that the program raised wages, consistent with the notion that the Job Corps raises earnings by increasing human capital, rather than solely through encouraging work The estimator is generally applicable to typical treatment evaluation problems in which there is nonrandom sample selection/attrition Copyright , Wiley-Blackwell

727 citations

Journal ArticleDOI
TL;DR: This article used regional variation in the relative level of the federal minimum wage to separately identify the impact of the minimum wage from nationwide growth in "latent" wage dispersion during the 1980s.
Abstract: The magnitude of growth in "underlying" wage inequality in the United States during the 1980s is obscured by a concurrent decline in the federal minimum wage, which itself could cause an increase in observed wage inequality. This study uses regional variation in the relative level of the federal minimum wage to separately identify the impact of the minimum wage from nationwide growth in "latent" wage dispersion during the 1980s. The analysis suggests that the minimum wage can account for much of the rise in dispersion in the lower tail of the wage distribution, particularly for women.

698 citations


Cited by
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TL;DR: In this article, the authors provide an introduction and user guide to regression discontinuity (RD) design for empirical researchers, including the basic theory behind RD design, details when RD is likely to be valid or invalid given economic incentives.
Abstract: This paper provides an introduction and "user guide" to Regression Discontinuity (RD) designs for empirical researchers. It presents the basic theory behind the research design, details when RD is likely to be valid or invalid given economic incentives, explains why it is considered a "quasi-experimental" design, and summarizes different ways (with their advantages and disadvantages) of estimating RD designs and the limitations of interpreting these estimates. Concepts are discussed using examples drawn from the growing body of empirical research using RD.

3,455 citations

Journal ArticleDOI
TL;DR: In the last two decades, much research has been done on the econometric and statistical analysis of such causal effects as discussed by the authors, which has reached a level of maturity that makes it an important tool in many areas of empirical research in economics, including labor economics, public finance, development economics, industrial organization, and other areas in empirical microeconomics.
Abstract: Many empirical questions in economics and other social sciences depend on causal effects of programs or policies. In the last two decades, much research has been done on the econometric and statistical analysis of such causal effects. This recent theoreti- cal literature has built on, and combined features of, earlier work in both the statistics and econometrics literatures. It has by now reached a level of maturity that makes it an important tool in many areas of empirical research in economics, including labor economics, public finance, development economics, industrial organization, and other areas of empirical microeconomics. In this review, we discuss some of the recent developments. We focus primarily on practical issues for empirical research- ers, as well as provide a historical overview of the area and give references to more technical research.

3,175 citations

Posted Content
TL;DR: In this paper, the authors investigated conditions sufficient for identification of average treatment effects using instrumental variables and showed that the existence of valid instruments is not sufficient to identify any meaningful average treatment effect.
Abstract: We investigate conditions sufficient for identification of average treatment effects using instrumental variables. First we show that the existence of valid instruments is not sufficient to identify any meaningful average treatment effect. We then establish that the combination of an instrument and a condition on the relation between the instrument and the participation status is sufficient for identification of a local average treatment effect for those who can be induced to change their participation status by changing the value of the instrument. Finally we derive the probability limit of the standard IV estimator under these conditions. It is seen to be a weighted average of local average treatment effects.

3,154 citations

ReportDOI
TL;DR: This paper found that computer capital substitutes for workers in performing cognitive and manual tasks that can be accomplished by following explicit rules, and complements workers in non-routine problem-solving and complex communications tasks.
Abstract: We apply an understanding of what computers do to study how computerization alters job skill demands. We argue that computer capital (1) substitutes for workers in performing cognitive and manual tasks that can be accomplished by following explicit rules; and (2) complements workers in performing nonroutine problem-solving and complex communications tasks. Provided these tasks are imperfect substitutes, our model implies measurable changes in the composition of job tasks, which we explore using representative data on task input for 1960 to 1998. We find that within industries, occupations and education groups, computerization is associated with reduced labor input of routine manual and routine cognitive tasks and increased labor input of nonroutine cognitive tasks. Translating task shifts into education demand, the model can explain sixty percent of the estimated relative demand shift favoring college labor during 1970 to 1998. Task changes within nominally identical occupations account for almost half of this impact.

2,843 citations

Journal ArticleDOI
TL;DR: In this paper, the authors provide an introduction and user guide to regression discontinuity (RD) designs for empirical researchers, and discuss the advantages and disadvantages of estimating RD designs and the limitations of interpreting these estimates.
Abstract: This paper provides an introduction and “user guide” to Regression Discontinuity (RD) designs for empirical researchers. It presents the basic theory behind the research design, details when RD is likely to be valid or invalid given economic incentives, explains why it is considered a “quasi-experimental” design, and summarizes different ways (with their advantages and disadvantages) of estimating RD designs and the limitations of interpreting these estimates. Concepts are discussed using examples drawn from the growing body of empirical research using RD. ( JEL C21, C31)

2,687 citations