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

https://www.thelancet.com/pdfs/journals/lancet/PIIS0140-6736(07)61692-4.pdf

Maternal and child undernutrition: consequences for adult health and human capital.

25. Multiple Imputation for Nonresponse in Surveys. By D. B. Rubin. ISBN 0 471 08705 X. Wiley, Chichester, 1987. 258 pp. £30.25.

Multiple Imputation for Nonresponse in Surveys

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

http://www1.worldbank.org/publicsector/pe/PEAMMarch2005/CMHReport.pdf

Macroeconomics and health: investing in health for economic development

The relationship between health and economic development is explored focusing on nutrition-based health indicators. The spotlight is placed on the inter-related feedbacks between the influence of health on productivity on one hand and the influence of income on health status on the other. Disentangling causality in these relationships has preoccupied much of the literature; we evaluate different empirical strategies that have been adopted and assess the results. There is now a body of evidence based on careful empirical studies that demonstrates a causal relationship between health and labor productivity; there is also evidence that at least among the very poor additional income is spent on improved nutrition. There are two issues that have received little attention although we argue they are likely to be very important. First measurement of health is discussed in detail. Evidence is presented on how taking into account differences in the extent of measurement error is critical for interpreting the impact of health on wages. The same theme emerges in studies of the effect of income on health (specifically calorie intake). The key role of non-linearities in these relationships is highlighted and we demonstrate that a good deal of the variation in estimates of income elasticities of demand for calories can be ascribed to the role of measurement and functional form. (authors)

Health nutrition and economic development.

The China Health and Retirement Longitudinal Study (CHARLS) is a nationally representative longitudinal survey of persons in China 45 years of age or older and their spouses, including assessments of social, economic, and health circumstances of community-residents. CHARLS examines health and economic adjustments to rapid ageing of the population in China. The national baseline survey for the study was conducted between June 2011 and March 2012 and involved 17 708 respondents. CHARLS respondents are followed every 2 years, using a face-to-face computer-assisted personal interview (CAPI). Physical measurements are made at every 2-year follow-up, and blood sample collection is done once in every two follow-up periods. A pilot survey for CHARLS was conducted in two provinces of China in 2008, on 2685 individuals, who were resurveyed in 2012. To ensure the adoption of best practices and international comparability of results, CHARLS was harmonized with leading international research studies in the Health and Retirement Study (HRS) model. Requests for collaborations should be directed to Dr Yaohui Zhao (nc.ude.dsn@oahzhy). All data in CHARLS are maintained at the National School of Development of Peking University and will be accessible to researchers around the world at the study website. The 2008 pilot data for CHARLS are available at: http://charls.ccer.edu.cn/charls/. National baseline data for the study are expected to be released in January 2013.

Cohort Profile: The China Health and Retirement Longitudinal Study (CHARLS)

This literature review focuses on education and health in its examination of the role that households and families play in choosing how to invest the human capital of their members. The introductory section describes the history of the development of economic models of the household and reviews how theoretical developments have become linked with data collection. The second section of the report looks at the effects of income on nutritional status and the reverse influence of nutrition (health) on labor productivity (income). Despite the controversies existing in the literature and the difficulties in choosing among the array of solutions to defined problems there is little doubt that investments in education and health enhance productivity fertility child health and child educational attainment. In an attempt to shed light on the underlying mechanisms in these relationships Section 3 focuses on the estimation of reduced form demands for human capital and considers the measurement of human capital; the effects of determinants such as education household resources and community resources; endogenous program placement and selective migration; and the possible estimation bias imposed by fertility and mortality selection. Section 4 continues this investigation by considering the process underlying the production of human capital in terms of the empirical issues involved in estimation of static and dynamic production functions as well as applications to child health and applications to educational attainment. Section 5 relates labor productivity to education and considers data issues the functional form of studies ability family background and school quality. Recent developments in modeling household behavior in a dynamic setting are reviewed in Section 6 and Section 7 describes links among individuals households and families. The concluding section notes that continued integration of survey data collection with theoretical frameworks will lead to a substantial improvement in our understanding of the magnitude of the significance of the effects predicted by the theory.

Human resources: empirical modeling of household and family decisions.

Many studies have demonstrated that parental education has a significant positive impact on child health This paper attempts to identify the mechanisms through which maternal education affects one indicator of child health-height conditional on age and sex Using data from the 1986 Brazilian Demographic and Health Survey, it is shown that almost all the impact of maternal education can be explained by indicators of access to information-reading papers, watching television, and listening to the radio In urban areas, whether the mother is semi-literate accounts for some of the education effect There are also significant interactions between maternal education and the availability of community services indicating that education and health services are substitutes but education and the availability of sewerage services are complements Very little of the maternal education effect is transmitted through income

https://www.jstor.org/stable/pdfplus/145920.pdf

John Strauss

Papers

Health nutrition and economic development.

Cohort Profile: The China Health and Retirement Longitudinal Study (CHARLS)

Human resources: empirical modeling of household and family decisions.

How does mother's education affect child height ?

Health and wages: evidence on men and women in urban Brazil.