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

Most papers that employ Differences-in-Differences estimation (DD) use many years of data and focus on serially correlated outcomes but ignore that the resulting standard errors are inconsistent. To illustrate the severity of this issue, we randomly generate placebo laws in state-level data on female wages from the Current Population Survey. For each law, we use OLS to compute the DD estimate of its “effect” as well as the standard error of this estimate. These conventional DD standard errors severely understate the standard deviation of the estimators: we find an “effect” significant at the 5 percent level for up to 45 percent of the placebo interventions. We use Monte Carlo simulations to investigate how well existing methods help solve this problem. Econometric corrections that place a specific parametric form on the time-series process do not perform well. Bootstrap (taking into account the autocorrelation of the data) works well when the number of states is large enough. Two corrections based on asymptotic approximation of the variance-covariance matrix work well for moderate numbers of states and one correction that collapses the time series information into a “pre”- and “post”-period and explicitly takes into account the effective sample size works well even for small numbers of states.

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How Much Should We Trust Differences-In-Differences Estimates?

https://www.oxfordmartin.ox.ac.uk/downloads/academic/The_Future_of_Employment.pdf

The future of employment: How susceptible are jobs to computerisation?

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.

/pdf/identification-of-endogenous-social-effects-the-reflection-rurdh6yhqn.pdf

Identification of Endogenous Social Effects: The Reflection Problem

▪ Abstract This paper assesses and synthesizes the cumulative results of a new “neighborhood-effects” literature that examines social processes related to problem behaviors and health-related outcomes. Our review identified over 40 relevant studies published in peer-reviewed journals from the mid-1990s to 2001, the take-off point for an increasing level of interest in neighborhood effects. Moving beyond traditional characteristics such as concentrated poverty, we evaluate the salience of social-interactional and institutional mechanisms hypothesized to account for neighborhood-level variations in a variety of phenomena (e.g., delinquency, violence, depression, high-risk behavior), especially among adolescents. We highlight neighborhood ties, social control, mutual trust, institutional resources, disorder, and routine activity patterns. We also discuss a set of thorny methodological problems that plague the study of neighborhood effects, with special attention to selection bias. We conclude with promising ...

ASSESSING "NEIGHBORHOOD EFFECTS": Social Processes and New Directions in Research

This paper surveys recent developments in the literature on efficiency wage theories of unemployment. Efficiency wage models have in common the property that in equilibrium firms may find it profitable to pay wages in excess of market clearing. High wages can help reduce turnover, elicit worker effort, prevent worker collective action, and attract higher quality employees. Simple versions of efficiency wage models can explain normal involuntary unemployment,segmented labor markets, and wage differentials across firms and industries for workers with similar productive characteristics. Deferred payment schemes andother labor market bonding mechanisms appear to be able to solve some efficiency wage problems without resultant job rationing and involuntary unemployment. A wide variety of evidence on inter-industry wage differences is analyzed. Efficiency wage models appear useful in explaining the observed pattern of wage differentials.The models also provide several potential mechanisms for cyclical fluctuations in response to aggregate demand shocks.

Efficiency Wage Theories: a Partial Evaluation

This paper examines the evolution of the Mexican-born workforce in the United States using data drawn from the decennial U.S. Census throughout the entire 20th century. It is well known that there has been a rapid rise in Mexican immigration to the United States in recent years. Interestingly, the share of Mexican immigrants in the U.S. workforce declined steadily beginning in the 1920s before beginning to rise in the 1960s. It was not until 1980 that the relative number of Mexican immigrants in the U.S. workforce was at the 1920 level. The paper examines the trends in the relative skills and economic performance of Mexican immigrants, and contrasts this evolution with that experienced by other immigrants arriving in the United States during the period. The paper also examines the costs and benefits of this influx by examining how the Mexican influx has altered economic opportunities in the most affected labor markets and by discussing how the relative prices of goods and services produced by Mexican immigrants may have changed over time.

The Evolution of the Mexican-Born Workforce in the United States

This paper uses job applications data to investigate the relationship between job queues and wage differentials. The main finding is that openings for jobs that pay the minimum wage attract more job applicants than jobs that pay either slightly more or slightly less than the minimum wage. This spike in the job application rate distribution suggests that ex ante rents generated for employees by an above market-level minimum wage are not completely dissipated by reductions in nonwage benefits. In addition, we find that highly unionized firms, large firms, and firms in high-wage industries tend to receive relatively many job applicants for openings.

Job Queues and Wages

Industrial Wage and Employment Determination in an Open Economy

A simple supply and demand framework is used to analyze changes in the U.S. wage structure from 1963 to 1987. Rapid secular growth in the demand for more-educated workers, 'more-skilled' workers, and females appears to be the driving force behind observed changes in the wage structure. Measured changes in the allocation of labor between industries and occupations strongly favored college graduates and females throughout the period. Movements in the college wage premium over this period appear to be strongly related to fluctuations in the rate of growth of the supply of college graduates.

Lawrence F. Katz

Papers

Efficiency Wage Theories: a Partial Evaluation

The Evolution of the Mexican-Born Workforce in the United States

Job Queues and Wages

Industrial Wage and Employment Determination in an Open Economy

Changes in Relative Wages, 1963-1987: Supply and Demand Factors