Econometric Methods

6 Key excerpts on "Econometric Methods"

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  eBook - PDF

  Introductory Econometrics

  A Modern Approach

  • Jeffrey Wooldridge, Jeffrey Wooldridge, , , (Authors)
  • 2019(Publication Date)
  • Cengage Learning EMEA

    (Publisher)

  The task of answering such questions may seem daunting at first. At this point, you may only have a vague idea of the kind of data you would need to collect. By the end of this introductory econometrics course, you should know how to use Econometric Methods to formally evaluate a job training program or to test a simple economic theory. The Nature of Econometrics and Economic Data C H A P T E R 1 CHAPTER 1 The Nature of Econometrics and Economic Data 2 Econometrics is based upon the development of statistical methods for estimating economic relationships, testing economic theories, and evaluating and implementing government and business policy. A common application of econometrics is the forecasting of such important macroeconomic variables as interest rates, inflation rates, and gross domestic product (GDP). Whereas forecasts of economic indicators are highly visible and often widely published, Econometric Methods can be used in economic areas that have nothing to do with macroeconomic forecasting. For example, we will study the effects of political campaign expenditures on voting outcomes. We will consider the effect of school spending on student performance in the field of education. In addition, we will learn how to use Econometric Methods for forecasting economic time series. Econometrics has evolved as a separate discipline from mathematical statistics because the for-mer focuses on the problems inherent in collecting and analyzing nonexperimental economic data. Nonexperimental data are not accumulated through controlled experiments on individuals, firms, or segments of the economy. (Nonexperimental data are sometimes called observational data , or retrospective data , to emphasize the fact that the researcher is a passive collector of the data.) Experimental data are often collected in laboratory environments in the natural sciences, but they are more difficult to obtain in the social sciences.

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  Modernism and the Social Sciences

  Anglo-American Exchanges, c.1918–1980

  • Mark Bevir(Author)
  • 2017(Publication Date)
  • Cambridge University Press

    (Publisher)

  3 Econometrics Thomas A. Stapleford Econometrics has a loose meaning, generally encompassing the use of mathematics and statistical data in economic analysis. In its most com- mon form today, econometrics involves constructing a mathematical model (often based in part on economic theory), estimating parameters of that model using empirical data, and then testing the reliability of the results. The process has a threefold connection to statistics: the data themselves are statistical, the parameters are typically calculated using regression techniques, and the reliability of the parameterized model is judged using standard statistical tests. 1 In 1900, neither the term econometrics nor its research practices existed, and even the organizing meeting for the Econometric Society in 1930 attracted a paltry sixteen scholars, two of whom (sociologist William Ogburn and mathematician Norbert Wiener) dropped out of the society shortly thereafter. 2 Yet within three decades, econometrics had become ubiquitous. As Robert Strotz declared in a 1968 survey article, “econo- metrics is ... becoming now nearly coterminous with the entire field of economics.” 3 Today, econometrics is a core component of undergraduate and postgraduate training in economics, and it is the bread and butter of most economists’ daily work. The breadth and rapidity of that triumph lends it an aura of inevitability. Yet the spread of econometric analysis was neither straightforward nor universally celebrated. Throughout the twentieth century, econometrics has drawn barbs from leading economists, and even more sympathetic researchers have looked askance at its implementation in practice.

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  eBook - ePub

  The Art and Science of Econometrics

  • Ping Zong(Author)
  • 2022(Publication Date)
  • Routledge

    (Publisher)

  However, this definition never means that a single one of these aspects can be taken by itself for econometrics. Econometrics is by no means the same as economic statistics. Nor is it identical with what is generally called economic theory, although a considerable portion of this theory has a definitively quantitative character. Nor should econometrics be taken as synonymous with the application of mathematics to economics. Experience has shown that each of these three viewpoints, that of statistics, mathematics, and economics, is a necessary, but not by itself a sufficient condition for real understanding of the quantitative relations in modern economic life. It is the unification of all three powerful components. It is this unification that constitutes econometrics.

  Today, econometrics has been a unified study of economic theory, mathematical statistics, and economic data. Within the field of econometrics, there are sub-divisions and specialisations: theoretical econometrics and applied econometrics. The econometric theory concerns the development of econometrics and the study of the properties of Econometric Methods, while applied econometrics is a term describing the development of quantitative economic models and the application of Econometric Methods to economic problems using economic data.

  Both these econometric sub-divisions use statistical methods as an econometric foundation; i.e., the statistics foundation (metrics) was applied to economics, therefore, it is called ‘econometrics’. Indeed, the statistics foundation (metrics) can be applied to many different disciplines such as psychometrics, sociometric, chemometrics, technometrics, morphometrics, environmetrics, and even cliometrics (history).

  Econometrics is an application of statistics and is exclusively focused on using statistical methods for economic problems. There are many overlapping areas of interest between econometrics and statistics such as linear models, hypothesis testing, graphical models for causal or non-causal inference, multiple testing, re-sampling, and time series analysis. Despite this, there are still some differences between econometrics and statistics from sociological as well as scientific views of points. For instance, econometrics is highly focused on discovering the causal relationships based on the economic theory; however, there are often unique statistical problems in statistical models. Some economic causality arose in specific applications that statisticians may be unaware of, or may not be of interest. The ‘Two-Step Estimators’ to analyse the economic problem in econometrics may be one of the examples. Econometricians are typically interested in capturing causal effects from observed data, and the models they used usually need to be justified by some economic theory more than by goodness of fit only.

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  Mathematical Statistics for Applied Econometrics

  • Charles B Moss(Author)
  • 2014(Publication Date)
  • Chapman and Hall/CRC

    (Publisher)

  My point is that despite the desire of economists to be classified as a scientists, economists are frequently reticent to put theory to an empirical test in the same way as a biologist or physicist. Because of this failure, economics largely deserves the suspicion of these white coated practitioners of more basic sciences. 1.1 Mathematical Statistics and Econometrics The study of mathematical statistics by economists typically falls under a broad sub-discipline called econometrics. Econometrics is typically defined as the use of statistics and mathematics along with economic theory to describe economic relationships (see the boxes titled Tinbergen on Econometrics and Klein on Econometrics ). The real issue is what do we mean by de-scribe? There are two dominant ideas in econometrics. The first involves the scientific concept of using statistical techniques (or more precisely, statistical inference) to test implications of economic theory. Hence, in a traditional sci-entific paradigm, we expose what we think we know to experience (see the box 4 Mathematical Statistics for Applied Econometrics titled Popper on Scientific Discovery ). The second use of econometrics in-volves the estimation of parameters to be used in policy analysis. For example, economists working with a state legislature may be interested in estimating the effect of a sales tax holiday for school supplies on the government’s sales tax revenue. As a result, they may be more interested in imposing economi-cally justified restrictions that add additional information to their data rather than testing these hypotheses. The two uses of econometrics could then be summarized as scientific uses versus the uses of planners. Tinbergen on Econometrics Econometrics is the name for a field of science in which mathematical-economic and mathematical-statistical research are applied in combination.

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  Palgrave Handbook of Econometrics

  Volume 2: Applied Econometrics

  • Terence C. Mills, Kerry Patterson, Terence C. Mills, Kerry Patterson, T. Mills, K. Patterson(Authors)
  • 2009(Publication Date)
  • Palgrave Macmillan

    (Publisher)

  1.2 What is “Applied Econometrics”? “When I use a word,” Humpty Dumpty said in rather a scornful tone, “it means just what I choose it to mean – neither more nor less.” (Lewis Carroll, 1899) At the superficial level, “Applied Econometrics” is “any application of economet- rics,” as distinct from theoretical econometrics. If it were not for the imperialist tendencies of econometricians, that would suffice, but econometrics has been applied in space science, climatology, political science, sociology, epidemiology, marketing, inter alia, not to mention the claim in How the Laws of Physics Lie (see Cartwright, 1983) that econometrics is the key methodology for all of science . . . Sorry to disappoint the eager reader, but I will not be covering even a wide range of the economic applications, never mind that plethora of outside studies. Some applied econometricians would include any applications involving anal- yses of “real economic data” by Econometric Methods, making “Applied Econo- metrics” synonymous with empirical econometrics. However, such a view leads to demarcation difficulties from applied economics on the one hand and applied statistics on the other. Defining “econometrics,” as in Frisch (1933), to comprise only studies involving the unification of economic theory, economic statistics (data), and mathematics (statistical methods) helps in demarcation, but limits its scope and inadvertently excludes (say) developing econometric theory itself, or just improving data measurement and collection. Outsiders might have thought that “Applied Econometrics” was just the appli- cation of econometrics to data, but that is definitely not so; virtually no journal editor would publish such a piece. Rather, the notion of mutual penetration domi- nates – but as a one-way street.

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  Statistics for the 21st Century

  Methodologies for Applications of the Future

  • Gabor Szekely(Author)
  • 2000(Publication Date)
  • CRC Press

    (Publisher)

  (See Christ, 1983). Econometrics (unlike biometrics and psychometrics) was not defined as the application of statistical methods to economics. Ragnar Frisch defined it as the application of statistical and mathematical methods in economics. He reiterated this definition in Frisch (1936). As a consequence mathematical economics also comes un-der the umbrella of econometrics. This has produced strange results. In recent years the issues of Econometrica have had only a couple of papers on econometrics (statistical methods in economics) and the rest are all on game theory and mathematical economics. If you look at the list of fellows of the Econometric Society, you find one or two econometricians and the rest are game theorists and mathematical economists. Econome-tricians have lost control of both the econometric society and the journal Econometnca. When Frisch defined econometrics as including mathemat-ical economics, it was appropriate to do so, because there was no other avenue for mathematical economists. But now there are journals in math-ematical economics and game theory: there is Economic Theory, Journal of Mathematical Economics and journals in game theory. It is not fair that Econometrica and the Econometric Society are dominated by these groups. In the 21st century, econometricians should work to regain control of Econometnca, or split it into two sections (as was done with the Annals of Mathematical Statistics), Annals of Econometrics and Annals of Mathe-mat2cal Economics. Something has to be done to at least put a quota-that the number of econometricians elected as fellows of the Econometric Soci-ety should be 50% of the total number elected. Currently each year of the 20 who are elected, about 2 or 3 are econometricians: this is crazy. 3. Frisch's Early Work Ragnar Frisch worked on errors in variables (EIV) models, (See Frisch 1934). So did Koopmans, (See 1937). Subsequently, the emphasis in econo-metrics shifted to the errors in equations models.

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