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

The relationship between school resources and student achievement has been controversial, in large part because it calls into question a variety of traditional policy approaches. This article reviews the available educational production literature, updating previous summaries. The close to 400 studies of student achievement demonstrate that there is not a strong or consistent relationship between student performance and school resources, at least after variations in family inputs are taken into account. These results are also reconciled with meta-analytic approaches and with other investigations on how school resources affect labor market outcomes. Simple resource policies hold little hope for improving student outcomes.

https://www.jstor.org/stable/pdf/1164207.pdf

Assessing the Effects of School Resources on Student Performance: An Update

A universe of education production function studies was assembled in order to utilize meta-analytic methods to assess the direction and magnitude of the relations between a variety of school inputs and student achievement. The 60 primary research studies aggregated data at the level of school districts or smaller units and either controlled for socioeconomic characteristics or were longitudinal in design. The analysis found that a broad range of resources were positively related to student outcomes, with effect sizes large enough to suggest that moderate increases in spending may be associated with significant increases in achievement. The discussion relates the findings of this study with trends in student achievement from the National Assessment of Educational Progress and changes in social capital over the last two decades.

The Effect of School Resources on Student Achievement

PIP: This paper presents the effects of climate, topography, and natural ecology on public health, nutrition, demographics, technological diffusion, international trade and other determinants of economic development in Africa. The goal of this paper is to emphasize the need for intensified research on the issues at the intersection of ecology and human society. Geography was given emphasis because of three reasons: the minimal gain from another recitation of the damage caused by statism, protectionism and corruption to African economic performance; negligence of the role of natural forces in shaping economic performance; and tailoring of policies to geographical realities. The paper also discusses the general problems of tropical development and the focus of Africa's problems in worldwide tropical perspectives; demographic trends in Africa; use of standard cross-country growth equations with demographic and geographic variables, to account for the relative roles of geography; and the future growth strategies and the need for urban-based export growth in manufacturing and services. Lastly, the authors provide a summary of conclusions and discuss the agenda for future research.

/pdf/geography-demography-and-economic-growth-in-africa-21hd177zjf.pdf

Geography, demography, and economic growth in Africa.

The results of recent correlations showing a negative impact of population growth on economic development in cross-country data for the 1980s, versus "nonsignificant" correlations widely found for the 1960s and 1970s, are examined with contemporaneous and lagged components of demographic change, convergence-type economic modeling, and several statistical frameworks. The separate impacts of births and deaths are found to be notable but offsetting in the earlier periods. In contrast, the short-run costs (benefits) of births (mortality reduction) increase (decrease) significantly in the 1980s, and the favorable labor-force impacts of past births are not fully offsetting.

/pdf/aggregate-population-and-economic-growth-correlations-the-2luudet5jd.pdf

Aggregate population and economic growth correlations: the role of the components of demographic change

Who Maximizes What? A Study in Student Time Allocation

Aggregate Population and Economic Growth Correlations: The Role of the Components of Demographic Change

This paper develops a flexible framework for modeling population's role in economic growth by assessing and extending a rendering suggested by several Harvard economists. Our framework includes a ``productivity'' model explaining output-per-worker growth and a ``translation'' model translating that growth into per-capita terms. We specify a core economic model and several ``enriched'' demographic variants that include dependency, size, and density. Regressions using a cross-country panel spanning the period 1960-1995 reveal that combined impacts of demographic change have accounted for approximately 20% of per capita output growth impacts, with larger shares in Asia and Europe.

Evolution of Recent Economic-Demographic Modeling: A Synthesis

Numerous studies have investigated the impact of class size on student outcomes. This analysis contributes to this discussion by examining the impact of class size on student outcomes in higher education. Additionally, this paper investigates the importance of student load (total number of students taught across all courses) in educational outcomes. We find that both class size and student load negatively impact student assessments of courses and instructors. Large classes and heavy student loads appear to prompt faculty to alter their courses in ways deleterious to students.

The Impact of Class Size and Number of Students on Outcomes in Higher Education.

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