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.

/pdf/econometric-analysis-of-cross-section-and-panel-data-3jzr8emmtf.pdf

Econometric Analysis of Cross Section and Panel Data

Considerable controversy surrounds the impact of schools and teachers on the achievement of students. This paper disentangles the separate factors influencing achievement with special attention given to the role of teacher differences and other aspects of schools. Unique matched panel data from the Harvard/UTD Texas Schools Project permit distinguishing between total effects and the impact of specific, measured components of teachers and schools. While schools are seen to have powerful effects on achievement differences, these effects appear to derive most importantly from variations in teacher quality. A lower bound suggests that variations in teacher quality account for at least 7« percent of the total variation in student achievement, and there are reasons to believe that the true percentage is considerably larger. The subsequent analysis estimates educational production functions based on models of achievement growth with individual fixed effects. It identifies a few systematic factors a negative impact of initial years of teaching and a positive effect of smaller class sizes for low income children in earlier grades but these effects are very small relative to the effects of overall teacher quality differences.

Teachers, Schools, and Academic Achievement

This paper is the latest in a short series on the origins, processes and effects of performativity in the public sector. Performativity, it is argued, is a new mode of state regulation which makes it possible to govern in an ‘advanced liberal’ way. It requires individual practitioners to organize themselves as a response to targets, indicators and evaluations. To set aside personal beliefs and commitments and live an existence of calculation. The new performative worker is a promiscuous self, an enterprising self, with a passion for excellence. For some, this is an opportunity to make a success of themselves, for others it portends inner conflicts, inauthenticity and resistance. It is also suggested that performativity produces opacity rather than transparency as individuals and organizations take ever greater care in the construction and maintenance of fabrications.

The teacher's soul and the terrors of performativity

The author suggests that we apply recent research knowledge to improve our conceptualization, measures, and methodology for studying the effects of teachers’ professional development on teachers and students. She makes the case that there is a research consensus to support the use of a set of core features and a common conceptual framework in professional development impact studies. She urges us to move away from automatic biases either for or against observation, interviews, or surveys in such studies. She argues that the use of a common conceptual framework would elevate the quality of professional development studies and subsequently the general understanding of how best to shape and implement teacher learning opportunities for the maximum benefit of both teachers and students.

/pdf/improving-impact-studies-of-teachers-professional-3pzi4k3euo.pdf

Improving Impact Studies of Teachers’ Professional Development: Toward Better Conceptualizations and Measures

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.

Regression Discontinuity Designs in Economics

The twelfth century rabbinic scholar Maimonides proposed a maximum class size of 40. This same maximum induces a nonlinear and nonmonotonic relationship between grade enrollment and class size in Israeli public schools today. Maimonides’ rule of 40 is used here to construct instrumental variables estimates of effects of class size on test scores. The resulting identiecation strategy can be viewed as an application of Donald Campbell’s regression-discontinuity design to the class-size question. The estimates show that reducing class size induces a signiecant and substantial increase in test scores for fourth and efth graders, although not for third graders. When asked about their views on class size in surveys, parents and teachers generally report that they prefer smaller classes. This may be because those involved with teaching believe that smaller classes promote student learning, or simply because smaller classes offer a more pleasant environment for the pupils and teachers who are in them [Mueller, Chase, and Walden 1988]. Social scientists and school administrators also have a longstanding interest in the class-size question. Class size is often thought to be easier to manipulate than other school inputs, and it is a variable at the heart of policy debates on school quality and the allocation of school resources in many countries (see, e.g., Robinson [1990] for the United States; OFSTED [1995] for the United Kingdom; and Moshel-Ravid [1995] for Israel). This broad interest in the consequences of changing class size

/pdf/using-maimonides-rule-to-estimate-the-effect-of-class-size-4o9dcifnmx.pdf

Using Maimonides' Rule to Estimate the Effect of Class Size on Scholastic Achievement

The effect of class size on student achievement has long been of concern to educators, parents, and scholars. In Israeli public schools today, class size is partly determined using a rule proposed by Maimonides in the 12th century. This rule induces a nonlinear and non-monotonic relationship between enroll- ment size and class size. We use this relationship to construct instrumental variables estimates of the effect of class size on the test scores of Israeli 4th and 5th graders in 1991 and 3rd graders in 1992. Because the up-and-down pattern in class size induced by Maimonides' rule matches a similar pattern in test scores, the rule provides a credible source of exogenous variation for investigation of the causal effect of class size on student achievement. Our use of Maimonides' rule can be viewed as an application of Campbell's (1969) regression-discontinuity design to the class size question. The results of this application show that reductions in class size induce a significant increase in reading and math scores for 5th graders and a smaller increase in reading scores for 4th graders. In contrast, there is little evidence of any association between class size and the test scores of 3rd graders, although this finding may result from problems with the 1992 wave of the testing program. The estimates also suggest that the gains from small classes are largest for students from disadvantaged backgrounds. Besides being of metho- dological interest and providing new evidence on the class size question, these findings are of immediate policy interest in Israel where legislation to reduce the maximum class size is pending.

Using Maimonides' Rule to Estimate the Effect of Class Size on Student Achievement

This article presents evidence on the child-quantity/child-quality trade-off using quasi-experimental variation due to twin births and preferences for a mixed sibling sex composition, as well as ethnic differences in the effects of these variables. Our sample includes groups with very high fertility. An innovation in our econometric approach is the juxtaposition of results from multiple instrumental variables strategies, capturing the effects of fertility over different ranges for different sorts of people. To increase precision, we develop an estimator that combines different instrument sets across partially overlapping parity-specific subsamples. Our results are remarkably consistent in showing no evidence of a quantity-quality trade-off.

/pdf/multiple-experiments-for-the-causal-link-between-the-3s053wfsbu.pdf

Multiple Experiments for the Causal Link between the Quantity and Quality of Children

Better child health is widely thought to improve school performance, and therefore post-school productivity. But most of the literature ignores that child health as well as child schooling reflects behavioral choices. Therefore the estimated impact of child health on child schooling in these studies may be biased, perhaps substantially. This study employs longitudinal data to investigate the impact of child health (as indicated by nutritional status) on school enrollments in rural Pakistan using an explicit dynamic model for the preferred estimates. These estimates use price shocks when children were of preschool age to control for behavior determining the child health stock measure. They indicate that child health (nutrition) is three times as important for enrollment than suggested by "naive estimates" that assume that child health is predetermined rather than determined by household choices in the presence of unobserved factors such as preferences and health endowments. These results, therefore, reinforce strongly the importance of using estimation methods that are consistent with the economic theory of households to explore the impact of some choice variables on others using socioeconomic behavioral data.

https://www.jstor.org/stable/pdfplus/3069675

Victor Lavy

Papers

Using Maimonides' Rule to Estimate the Effect of Class Size on Scholastic Achievement

Using Maimonides' Rule to Estimate the Effect of Class Size on Student Achievement

Using Maimonides' Rule to Estimate the Effect of Class Size on Student Achievement

Multiple Experiments for the Causal Link between the Quantity and Quality of Children

Child Health and School Enrollment: A Longitudinal Analysis