计量经济分析 = Econometric analysis

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

A review is presented of the book “Heuristics and Biases: The Psychology of Intuitive Judgment,” edited by Thomas Gilovich, Dale Griffin, and Daniel Kahneman.

Heuristics and Biases: The Psychology of Intuitive Judgment

Much research in the last two decades has demon- strated that human responses deviate from the performance deemed normative according to various models of decision mak- ing and rational judgment (e.g., the basic axioms of utility theory). This gap between the normative and the descriptive can be inter- preted as indicating systematic irrationalities in human cognition. However, four alternative interpretations preserve the assumption that human behavior and cognition is largely rational. These posit that the gap is due to (1) performance errors, (2) computational limitations, (3) the wrong norm being applied by the experi- menter, and (4) a different construal of the task by the subject. In the debates about the viability of these alternative explanations, attention has been focused too narrowly on the modal response. In a series of experiments involving most of the classic tasks in the heuristics and biases literature, we have examined the implica- tions of individual differences in performance for each of the four explanations of the normative/descriptive gap. Performance er- rors are a minor factor in the gap; computational limitations un- derlie non-normative responding on several tasks, particularly those that involve some type of cognitive decontextualization. Un- expected patterns of covariance can suggest when the wrong norm is being applied to a task or when an alternative construal of the task should be considered appropriate.

https://www.cambridge.org/core/services/aop-cambridge-core/content/view/S0140525X00003435

Individual differences in reasoning: Implications for the rationality debate?

The program of research now known as the heuristics and biases approach began with a survey of 84 participants at the 1969 meetings of the Mathematical Psychology Society and the American Psychological Association (Tversky & Kahneman, 1971). The respondents, including several authors of statistics texts, were asked realistic questions about the robustness of statistical estimates and the replicability of research results. The article commented tongue-in-heek on the prevalence of a belief that the law of large numbers applies to small numbers as well: Respondents placed too much confidence in the results of small samples, and their statistical judgments showed little sensitivity to sample size. The mathematical psychologists who participated in the survey not only should have known better – they did know better. Although their intuitive guesses were off the mark, most of them could have computed the correct answers on the back of an envelope. These sophisticated individuals apparently had access to two distinct approaches for answering statistical questions: one that is spontaneous, intuitive, effortless, and fast; and another that is deliberate, rule-governed, effortful, and slow. The persistence of large biases in the guesses of experts raised doubts about the educability of statistical intuitions. Moreover, it was known that the same biases affect choices in the real world, where researchers commonly select sample sizes that are too small to provide a fair test of their hypotheses (Cohen, 1969, 1992).

Representativeness revisited: Attribute substitution in intuitive judgment.

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The Winner-Take-All Society

Much of the economic education literature suggests that the principles of economics class size does not significantly affect student performance. However, study methods have varied in terms of the aggregation level (student or class), the measure of performance (TUCE or course letter grade), and the class size measure (e.g., students who completed both the TUCE pretest and posttest). The authors perform an experiment with principles students using total exam points as the dependent variable in a model to explain student performance. By using the same instructor for all sections, the authors control variation in instruction, lecture material, and topic coverage; they also account for variation in student abilities. In contrast to many other studies, the authors find statistically significant evidence that small class size has a positive impact on student performance.

/pdf/additional-evidence-on-the-relationship-between-class-size-3t4vq9jtvc.pdf

Additional Evidence on the Relationship between Class Size and Student Performance

Casino gambling and economic growth.- Misconceptions about casinos and growth.- Evidence on the growth effects of gambling.- Relationships among U.S. gambling industries.- The social costs of gambling.- Miscellaneous social cost issues.- Problems in gambling research.- Conclusion.

The Economics of Casino Gambling

Much of the opposition to legalized gambling is based on analyses of the social costs that occur as a result of pathological gambling. It is our contention that many, if not most, authors who have contributed to this literature are either unclear or misguided in what they define as social costs. Instead of starting with a clear definition of what constitutes a social cost, these authors have adopted an ad hoc approach—using “common sense” to determine what constitutes losses to society and then attempting to quantify the impact of those activities. We believe this is not, as some suggest, simply a matter of semantics. Rather, it is a serious problem in the gambling literature. How do we differentiate between a consequence of pathological gambling that is a “social cost” and one that is not? Which of the consequences of addictive behaviors that are associated with gambling arise when gambling is legal, and which will be manifest in some form whether or not gambling is legal? In this article we explain the economic perspective on social costs. An understanding of this paradigm removes the subjectivity in the classification of pathological gambling's social costs. The paper has three major components. First, we introduce the economic notion of social costs. Using this paradigm, we differentiate between the “true” social costs related to pathological gambling, and other negative consequences that cannot legitimately be classified as social costs. Second, we evaluate a recent social cost study using the economics social cost paradigm. Third, we discuss two types of social costs that have been largely overlooked in the gambling literature. One is caused by gambling prohibition. The other occurs as a result of “rent seeking” that is related to the political process surrounding the legalization of gambling.

/pdf/the-social-costs-of-gambling-an-economic-perspective-4hape45aj6.pdf

The Social Costs of Gambling: An Economic Perspective.

The adoption of lotteries by state governments has received significant attention in the economics literature, but the issue of casino adoption has been neglected by researchers. Casino gambling is a relatively new industry in the United States, outside Nevada and New Jersey. As of 2007, 11 states had established commercial casinos; several more states are considering legalization. We analyze the factors that determine a state’s decision to legalize commercial casinos, using data from 1985 to 2000, a period which covers the majority of states that have adopted commercial casinos. We use a tobit model to examine states’ fiscal conditions, political alignments, intrastate and interstate competitive environments, and demographic characteristics, which yields information on the probability and timing of adoptions. The results suggest a public choice explanation that casino legalization is due to state fiscal stress, to efforts to keep gambling revenues (and the concomitant gambling taxes) within the state, and to attract tourism or “export taxes.”

https://www.jstor.org/stable/pdfplus/40541949.pdf

Douglas M. Walker

Papers

The Winner-Take-All Society

Additional Evidence on the Relationship between Class Size and Student Performance

The Economics of Casino Gambling

The Social Costs of Gambling: An Economic Perspective.

Determinants of the probability and timing of commercial casino legalization in the United States