Charles F. Manski

Bio: Charles F. Manski is an academic researcher from Northwestern University. The author has contributed to research in topics: Population & Empirical research. The author has an hindex of 82, co-authored 367 publications receiving 34951 citations. Previous affiliations of Charles F. Manski include Hebrew University of Jerusalem & Cambridge Systematics.

Identification of Endogenous Social Effects: The Reflection Problem

Abstract: This paper examines the reflection problem that arises when a researcher observing the distribution of behaviour in a population tries to infer whether the average behaviour in some group influences the behaviour of the individuals that comprise the group. It is found that inference is not possible unless the researcher has prior information specifying the compisition of reference groups. If this information is available, the prospects for inference depend critically on the population relationship between the variables defining reference groups and those directly affecting outcomes. Inference is difficult to implossible if these variables are functionally dependent or are statistically independent. The prospects are better if the variables defining reference groups and those directly affecting outcomes are moderately related in the population.

Economic Analysis of Social Interactions

Abstract: Economics is broadening its scope from analysis of markets to study of general social interactions. Developments in game theory, the economics of the family, and endogenous growth theory have led the way. Economists have also performed new empirical research using observational data on social interactions, but with much less to show. The fundamental problem is that observable outcomes may be generated by many different interaction processes, so empirical findings are open to a wide variety of interpretations. To make sustained progress, empirical research will need richer data, including experiments in controlled environments and subjective data on preferences and expectations.

The structure of random utility models

Abstract: I am grateful to Joseph B. Kadane for numerous constructive suggestions offered during discussions of this research. The financial sponsorship of the U.S. Department of Transportation through grant DOT-OS-4006 is also acknowledged. The opinions and conclusions expressed herein are solely those of the author.

The Estimation of Choice Probabilities from Choice Based Samples

Abstract: Ti-H CONCERN of this paper is the estimation of the parameters of a probabilistic choice model when choices rather than decision makers are sampled. Existing estimation methods presuppose an exogeneous sampling process, that is one in which a sequence of decision makers are drawn and their choice behaviors observed. In contrast, in choice based sampling processes, a sequence of chosen alternatives are drawn and the characteristics of the decision makers selecting those alternatives are observed. The problem of estimating a choice model from a choice based sample has suibstantive interest because data collection costs for such processes are often considerably smaller than for exogeneous sampling. Particular instances of this differential occur in the analysis of transportation behavior. For example, in studying choice of mode for work trips, it is often less expensive to survey transit users at the station and auto users at the parking lot than to interview commuters at their homes. Similarly, in examining choice of destination for shopping trips, surveys conducted at various shopping centers offer significant cost savings relative to home interviews.2 While interest in transportation applications provided the original motivation for our work, it has become apparent that choice based sampling processes can be cost effective in the analysis of numerous decision problems. In particular, wherever decision makers are physically clustered according to the alternatives they select, choice based sampling processes can achieve economies of scale not available with exogeneous sampling. Some non-transportation decision problems in which decision makers do cluster as described include the schooling decisions of students, the job decisions of workers, the medical care decisions of patients and the residential location decisions of households. Realization of the sampling cost benefits of choice based samples presupposes of course that the parameters of the underlying choice model can logically be inferred from such samples and that a tractable estimator with desirable statistical properties can be found. We shall, in this paper, confirm the logical supposition, develop a suitable estimator, and characterize the behavior of existing, exogeneous sampling, estimators in the context of choice based samples. An outline of the presentation and summary of major results follows.

Econometric Analysis of Cross Section and Panel Data

Abstract: The second edition of this acclaimed graduate text provides a unified treatment of two methods used in contemporary econometric research, cross section and data panel methods. By focusing on assumptions that can be given behavioral content, the book maintains an appropriate level of rigor while emphasizing intuitive thinking. The analysis covers both linear and nonlinear models, including models with dynamics and/or individual heterogeneity. In addition to general estimation frameworks (particular methods of moments and maximum likelihood), specific linear and nonlinear methods are covered in detail, including probit and logit models and their multivariate, Tobit models, models for count data, censored and missing data schemes, causal (or treatment) effects, and duration analysis. Econometric Analysis of Cross Section and Panel Data was the first graduate econometrics text to focus on microeconomic data structures, allowing assumptions to be separated into population and sampling assumptions. This second edition has been substantially updated and revised. Improvements include a broader class of models for missing data problems; more detailed treatment of cluster problems, an important topic for empirical researchers; expanded discussion of "generalized instrumental variables" (GIV) estimation; new coverage (based on the author's own recent research) of inverse probability weighting; a more complete framework for estimating treatment effects with panel data, and a firmly established link between econometric approaches to nonlinear panel data and the "generalized estimating equation" literature popular in statistics and other fields. New attention is given to explaining when particular econometric methods can be applied; the goal is not only to tell readers what does work, but why certain "obvious" procedures do not. The numerous included exercises, both theoretical and computer-based, allow the reader to extend methods covered in the text and discover new insights.

Discrete Choice Methods with Simulation

Abstract: This book describes the new generation of discrete choice methods, focusing on the many advances that are made possible by simulation. Researchers use these statistical methods to examine the choices that consumers, households, firms, and other agents make. Each of the major models is covered: logit, generalized extreme value, or GEV (including nested and cross-nested logits), probit, and mixed logit, plus a variety of specifications that build on these basics. Simulation-assisted estimation procedures are investigated and compared, including maximum simulated likelihood, method of simulated moments, and method of simulated scores. Procedures for drawing from densities are described, including variance reduction techniques such as anithetics and Halton draws. Recent advances in Bayesian procedures are explored, including the use of the Metropolis-Hastings algorithm and its variant Gibbs sampling. No other book incorporates all these fields, which have arisen in the past 20 years. The procedures are applicable in many fields, including energy, transportation, environmental studies, health, labor, and marketing.

Matching As An Econometric Evaluation Estimator: Evidence from Evaluating a Job Training Programme

Abstract: This paper considers whether it is possible to devise a nonexperimental procedure for evaluating a prototypical job training programme. Using rich nonexperimental data, we examine the performance of a two-stage evaluation methodology that (a) estimates the probability that a person participates in a programme and (b) uses the estimated probability in extensions of the classical method of matching. We decompose the conventional measure of programme evaluation bias into several components and find that bias due to selection on unobservables, commonly called selection bias in econometrics, is empirically less important than other components, although it is still a sizeable fraction of the estimated programme impact. Matching methods applied to comparison groups located in the same labour markets as participants and administered the same questionnaire eliminate much of the bias as conventionally measured, but the remaining bias is a considerable fraction of experimentally-determined programme impact estimates. We test and reject the identifying assumptions that justify the classical method of matching. We present a nonparametric conditional difference-in-differences extension of the method of matching that is consistent with the classical index-sufficient sample selection model and is not rejected by our tests of identifying assumptions. This estimator is effective in eliminating bias, especially when it is due to temporally-invariant omitted variables.

A Treatise on the Family

Abstract: 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. …

Automobile prices in market equilibrium

Abstract: This paper develops techniques for empirically analyzing demand and supply in differentiated products markets and then applies these techniques to analyze equilibrium in the U.S. automobile industry. Our primary goal is to present a framework which enables one to obtain estimates of demand and cost parameters for a class of oligopolistic differentiated products markets. These estimates can be obtained using only widely available product-level and aggregate consumer-level data, and they are consistent with a structural model of equilibrium in an oligopolistic industry. When we apply the tech- niques developed here to the U.S. automobile market, we obtain cost and demand parameters for (essentially) all models marketed over a twenty year period.