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.

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Econometric Analysis of Cross Section and Panel Data

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

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.

Evolution and Rationality Some Recent Game-Theoretic Results. Identification and Estimation of Local Average Treatment Effects

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)

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Regression discontinuity designs in economics

The Rise of the Creative Class

Bartik reviews evidence on whether state and local policies affect job growth. He then presents empirical data supporting the intentions of such programs, showing that job growth may lead to a number of positive long-term effects including: lower unemployment, higher labor force participation, higher real estate values, and better occupational opportunities. He also shows that the earnings gains to disadvantaged groups outweigh the resulting increased real estate values for property owners, and concludes by saying that regional competition for jobs may actually be a benefit for the nation as a whole.

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Who Benefits from State and Local Economic Development Policies

This article examines how corporate decisions about the location for a new manufacturing plant in the U.S. are influenced by unionization, taxes, and other characteristics of states. The conditional logit model is used with some modifications to make the model more applicable to the business location decision. The most important finding is that the union sympathies of states have a major effect on business location. The results also indicate that state taxes affect business location, contradicting the conventional wisdom in the economic literature, although the tax effect is of modest magnitude.

https://www.jstor.org/stable/pdfplus/1391685.pdf

Business Location Decisions in the United States: Estimates of the Effects of Unionization, Taxes, and Other Characteristics of States

This paper shows that the econometric problem of estimating hedonic demand parameters is not a standard identification problem caused by demand-supply interaction, as has been often assumed. Estimation procedures based on this assumption lead to biased results. The hedonic estimation problem is instead caused by the endogeneity of both prices and quantities when households face a nonlinear budget constraint. An instrumental variables solution to this problem is suggested using instruments that exogenously shift the budget constraint.

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The Estimation of Demand Parameters in Hedonic Price Models

This paper estimates how the characteristics of American states affect small business start-ups. The paper is of interest for three reasons: two methodological contributions; and, the paper's empirical findings. First, unlike most of the business location literature, the paper relies on micro data. The availability of micro data allows a focus on one specific type of business location decision, the small business start decision. Most previous business location research has used an aggregate business activity measure as the dependent variable.' Examining one type of business location decision allows the use of a micro model of profitmaximization. Aggregate measures of local economic activity reflect small business start-ups, new branch plants, plant expansions and contractions, and plant closings. These decisions probably are made in very different ways. These differences make it difficult to devise an aggregate model of business location.

Small Business Start-ups in the United States: Estimates of the Effects of Characteristics of States

This article empirically examines whether variations in state environmental regulations have affected the location of manufacturing branch plants by the Fortune 500 companies. Using several measures of environmental regulation, no statistically significant effects of environmental regulation on business location are found. For most manufacturing industries, the estimates are precise enough to rule out the possibility of large effects of environmental regulation on business location. For highly polluting industries, however, the variance in the estimates is quite large. We cannot rule out the possibility of effects of environmental regulation on the location of highly polluting industries that are large enough to be important to policymakers.

Timothy J. Bartik

Papers

Who Benefits from State and Local Economic Development Policies

Business Location Decisions in the United States: Estimates of the Effects of Unionization, Taxes, and Other Characteristics of States

The Estimation of Demand Parameters in Hedonic Price Models

Small Business Start-ups in the United States: Estimates of the Effects of Characteristics of States

The Effects of Environmental Regulation on Business Location in the United States