Propensity score matching (PSM) has become a popular approach to estimate causal treatment effects. It is widely applied when evaluating labour market policies, but empirical examples can be found in very diverse fields of study. Once the researcher has decided to use PSM, he is confronted with a lot of questions regarding its implementation. To begin with, a first decision has to be made concerning the estimation of the propensity score. Following that one has to decide which matching algorithm to choose and determine the region of common support. Subsequently, the matching quality has to be assessed and treatment effects and their standard errors have to be estimated. Furthermore, questions like 'what to do if there is choice-based sampling?' or 'when to measure effects?' can be important in empirical studies. Finally, one might also want to test the sensitivity of estimated treatment effects with respect to unobserved heterogeneity or failure of the common support condition. Each implementation step involves a lot of decisions and different approaches can be thought of. The aim of this paper is to discuss these implementation issues and give some guidance to researchers who want to use PSM for evaluation purposes.

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Some practical guidance for the implementation of propensity score matching

1. Introduction and Overview. 2. Detecting Influential Observations and Outliers. 3. Detecting and Assessing Collinearity. 4. Applications and Remedies. 5. Research Issues and Directions for Extensions. Bibliography. Author Index. Subject Index.

Regression Diagnostics: Identifying Influential Data and Sources of Collinearity

A Treatise on the Family. G. S. Becker. Cambridge, MA: Harvard University Press. 1981. Gary Becker is one of the most famous and influential economists of the second half of the 20th century, a fervent contributor to and expounder of the University of Chicago free-market philosophy, and winner of the 1992 Nobel Prize in economics. Although any book with the word "treatise" in its title is clearly intended to have an impact, one coming from someone as brilliant and controversial as Becker certainly had such a lofty goal. It has received many article-length reviews in several disciplines (Ben-Porath, 1982; Bergmann, 1995; Foster, 1993; Hannan, 1982), which is one measure of its scholarly importance, and yet its impact is, I think, less than it may have initially appeared, especially for scholars with substantive interests in the family. This book is, its title notwithstanding, more about economics and the economic approach to behavior than about the family. In the first sentence of the preface, Becker writes "In this book, I develop an economic or rational choice approach to the family." Lest anyone accuse him of focusing on traditional (i.e., material) economics topics, such as family income, poverty, and labor supply, he immediately emphasizes that those topics are not his focus. "My intent is more ambitious: to analyze marriage, births, divorce, division of labor in households, prestige, and other non-material behavior with the tools and framework developed for material behavior." Indeed, the book includes chapters on many of these issues. One chapter examines the principles of the efficient division of labor in households, three analyze marriage and divorce, three analyze various child-related issues (fertility and intergenerational mobility), and others focus on broader family issues, such as intrafamily resource allocation. His analysis is not, he believes, constrained by time or place. His intention is "to present a comprehensive analysis that is applicable, at least in part, to families in the past as well as the present, in primitive as well as modern societies, and in Eastern as well as Western cultures." His tone is profoundly conservative and utterly skeptical of any constructive role for government programs. There is a clear sense of how much better things were in the old days of a genderbased division of labor and low market-work rates for married women. Indeed, Becker is ready and able to show in Chapter 2 that such a state of affairs was efficient and induced not by market or societal discrimination (although he allows that it might exist) but by small underlying household productivity differences that arise primarily from what he refers to as "complementarities" between caring for young children while carrying another to term. Most family scholars would probably find that an unconvincingly simple explanation for a profound and complex phenomenon. What, then, is the salient contribution of Treatise on the Family? It is not literally the idea that economics could be applied to the nonmarket sector and to family life because Becker had already established that with considerable success and influence. At its core, microeconomics is simple, characterized by a belief in the importance of prices and markets, the role of self-interested or rational behavior, and, somewhat less centrally, the stability of preferences. It was Becker's singular and invaluable contribution to appreciate that the behaviors potentially amenable to the economic approach were not limited to phenomenon with explicit monetary prices and formal markets. Indeed, during the late 1950s and throughout the 1960s, he did undeniably important and pioneering work extending the domain of economics to such topics as labor market discrimination, fertility, crime, human capital, household production, and the allocation of time. Nor is Becker's contribution the detailed analyses themselves. Many of them are, frankly, odd, idiosyncratic, and off-putting. …

A Treatise on the Family

Offering a unifying theoretical perspective not readily available in any other text, this innovative guide to econometrics uses simple geometrical arguments to develop students' intuitive understanding of basic and advanced topics, emphasizing throughout the practical applications of modern theory and nonlinear techniques of estimation. One theme of the text is the use of artificial regressions for estimation, reference, and specification testing of nonlinear models, including diagnostic tests for parameter constancy, serial correlation, heteroscedasticity, and other types of mis-specification. Explaining how estimates can be obtained and tests can be carried out, the authors go beyond a mere algebraic description to one that can be easily translated into the commands of a standard econometric software package. Covering an unprecedented range of problems with a consistent emphasis on those that arise in applied work, this accessible and coherent guide to the most vital topics in econometrics today is indispensable for advanced students of econometrics and students of statistics interested in regression and related topics. It will also suit practising econometricians who want to update their skills. Flexibly designed to accommodate a variety of course levels, it offers both complete coverage of the basic material and separate chapters on areas of specialized interest.

Estimation and Inference in Econometrics

This paper considers causal inference and sample selection bias in nonexperimental settings in which (i) few units in the nonexperimental comparison group are comparable to the treatment units, and (ii) selecting a subset of comparison units similar to the treatment units is difficult because units must be compared across a high-dimensional set of pre-treatment characteristics. We discuss the use of propensity score-matching methods, and implement them using data from the National Supported Work experiment. Following LaLonde (1986), we pair the experimental treated units with nonexperimental comparison units from the CPS and PSID, and compare the estimates of the treatment effect obtained using our methods to the benchmark results from the experiment. For both comparison groups, we show that the methods succeed in focusing attention on the small subset of the comparison units comparable to the treated units and, hence, in alleviating the bias due to systematic differences between the treated and compariso...

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Propensity score-matching methods for nonexperimental causal studies

http://faculty.smu.edu/millimet/classes/eco7377/papers/black%20smith.pdf

How robust is the evidence on the effects of college quality? Evidence from matching

This work provides an overview of standard social science data sources that now allow some systematic study of the gay and lesbian population in the United States. For each data source, we consider how sexual orientation can be defined, and we note the potential sample sizes. We give special attention to the important problem of measurement error, especially the extent to which individuals recorded as gay and lesbian are indeed recorded correctly. Our concern is that because gays and lesbians constitute a relatively small fraction of the population, modest measurement problems could lead to serious errors in inference. In examining gays and lesbians in multiple data sets we also achieve a second objective: We provide a set of statistics about this population that is relevant to several current policy debates.

https://surface.syr.edu/cgi/viewcontent.cgi?article=1167&context=cpr

Demographics of the Gay and Lesbian Population in the United States: Evidence From Available Systematic Data Sources

Existing studies of the effects of college quality on wages typically rely on a single proxy variable for college quality. This study questions the wisdom of using a single proxy given that it likely contains substantial measurement error. We consider four econometric approaches to the problem that involve the use of multiple proxies for college quality: factor analysis, instruments variables, a method recently proposed by Lubotsky and Wittenberg, and a GMM estimator. Our estimates suggest that the existing literature understates the wage effects of college quality and illustrate the value of using multiple proxies in this and other similar contexts.

https://www.jstor.org/stable/10.1086/505067

Estimating the Returns to College Quality with Multiple Proxies for Quality

We examine the effect of the Worker Profiling and Reemployment Services system. This program "profiles" Unemployment Insurance (UI) claimants to determine their probability of benefit exhaustion and then provides mandatory employment and training services to claimants with high predicted probabilities. Using a unique experimental design, we estimate that the program reduces mean weeks of UI benefit receipt by about 2.2 weeks, reduces mean UI benefits received by about $143, ana increases subsequent earnings by over $1,050. Most of the effect results from a sharp increase in early UI exits in the treatment group relative to the control group. (JEL J650)

Is the Threat of Reemployment Services More Effective than the Services Themselves? Evidence from Random Assignment in the UI System *

Conventional analysis predicts that workers pay part of their on-the-job training costs by accepting a lower starting wage and subsequently realize a return to this investment in the form of greater wage growth. Missing from the conventional treatment of on-the-job training is a discussion of the process by which heterogeneous workers are matched to jobs requiring varying amounts of training. This matching process constitutes a key feature of the on-the-job training model presented in this article and tested with a unique data set containing extensive information concerning on-the-job training, employer search, wages, and wage and productivity growth.

https://www.jstor.org/stable/pdfplus/2534987.pdf

Dan A. Black

Papers

How robust is the evidence on the effects of college quality? Evidence from matching

Demographics of the Gay and Lesbian Population in the United States: Evidence From Available Systematic Data Sources

Estimating the Returns to College Quality with Multiple Proxies for Quality

Is the Threat of Reemployment Services More Effective than the Services Themselves? Evidence from Random Assignment in the UI System *

Job Matching and On-the-Job Training