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.

/pdf/how-much-should-we-trust-differences-in-differences-407p70a9b4.pdf

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

The American university was shaped in a formative period from 1890 to 1940 long before the rise of federal funding, the G.I. Bill, and mass higher education. Both the scale and scope of institutions of higher education were greatly increased, the research university blossomed, states vastly increased their funding of higher education, and the public sector greatly expanded relative to the private sector. Independent professional institutions declined, as did theological institutes and denominational colleges in general. Increases in the scale and scope of institutions of higher education were generated by exogenous changes in the that affected the professions generally and that of the clergy in particular. The increase in the share of students in the public sector may also have been prompted by these exogenous changes for they gave advantages to institutions, such as those in the public sector, that had research facilities, reputation, and a long purse. The high school movement, which swept parts of the country from 1910 to 1940, brought students from less privileged backgrounds to college and thus also buoyed enrollments in the public sector. States differed widely in their funding of higher education per capita and we find that greater generosity in 1929 was positively associated with later statehood, lower private college enrollments in 1900, greater shares of employment in mining and manufacturing, higher income, and a proxy for greater and more equally distributed wealth.

The Shaping of Higher Education: The Formative Years in the United States, 1890 to 1940

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. However, deferred payment schemes can solve some efficiency wage problems without requiring job rationing. A wide variety of evidence on interindustry wage differences is analyzed. Efficiency wage models appear useful in explaining the observed pattern of wage differentials. The models also provide several mechanisms for cyclical fluctuations in response to aggregate demand shocks.

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Efficiency wage theories: a partial evaluation

The Moving to Opportunity (MTO) demonstration assigned housing vouchers via random lottery to public housing residents in five cities. We use the exogenous variation in residential locations generated by MTO to estimate neighborhood effects on youth crime and delinquency. The offer to relocate to lower-poverty areas reduces arrests among female youth for violent and property crimes, relative to a control group. For males the offer to relocate reduces arrests for violent crime, at least in the short run, but increases problem behaviors and property crime arrests. The gender difference in treatment effects seems to reflect differences in how male and female youths from disadvantaged backgrounds adapt and respond to similar new neighborhood environments.

https://papers.ssrn.com/sol3/Delivery.cfm/nber_w10777.pdf?abstractid=593451

Neighborhood Effects on Crime for Female and Male Youth: Evidence from a Randomized Housing Voucher Experiment

In the most popular type of efficiency wage model of unemployment, firms pay wages in excess of market clearing to give workers an incentive not to shirk.1 Such payments in excess of market clearing and the resultant equilibrium unemployment act as a worker discipline device. This chapter concerns what is usually considered the most important theoretical criticism of such models: the so-called bonding argument.

Do Deferred Wages Eliminate the Need for Involuntary Unemployment as a Worker Discipline Device

This paper analyzes a marked change in the evolution of the U.S. wage structure over the past fifteen years: divergent trends in upper-tail (90/50) and lower-tail (50/10) wage inequality. We document that wage inequality in the top half of distribution has displayed an unchecked and rather smooth secular rise for the last 25 years (since 1980). Wage inequality in the bottom half of the distribution also grew rapidly from 1979 to 1987, but it has ceased growing (and for some measures actually narrowed) since the late 1980s. Furthermore we find that occupational employment growth shifted from monotonically increasing in wages (education) in the 1980s to a pattern of more rapid growth in jobs at the top and bottom relative to the middles of the wage (education) distribution in the 1990s. We characterize these patterns as the %u201Cpolarization%u201D of the U.S. labor market, with employment polarizing into high-wage and low-wage jobs at the expense of middle-wage work. We show how a model of computerization in which computers most strongly complement the non-routine (abstract) cognitive tasks of high-wage jobs, directly substitute for the routine tasks found in many traditional middle-wage jobs, and may have little direct impact on non-routine manual tasks in relatively low-wage jobs can help explain the observed polarization of the U.S. labor market.

Lawrence F. Katz

Papers

The Shaping of Higher Education: The Formative Years in the United States, 1890 to 1940

Efficiency wage theories: a partial evaluation

Neighborhood Effects on Crime for Female and Male Youth: Evidence from a Randomized Housing Voucher Experiment

Do Deferred Wages Eliminate the Need for Involuntary Unemployment as a Worker Discipline Device

The Polarization of the U.S. Labor Market