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The methodology of econometrics is the study of the range of differing approaches to undertaking econometric analysis.〔Jennifer Castle and Neil Shephard (Eds) (2009) ''The Methodology and Practice of Econometrics - A Festschrift in Honour of David F. Hendry'' ISBN 978-0-19-923719-7〕 Commonly distinguished differing approaches that have been identified and studied include: * the Cowles Commission approach〔Christ, Carl F. 1994. “The Cowles Commission Contributions to Econometrics at Chicago: 1939-1955” ''Journal of Economic Literature''. Vol. 32.〕 * the Vector autoregression approach〔Sims, Christopher (1980) Macroeconomics and Reality, ''Econometrica'', January, pp. 1-48.〕 * the LSE approach to econometrics - originated with Denis Sargan now associated with David Hendry (and his general-to-specific modeling). Also associated this approach is the work on integrated and cointegrated systems originating on the work of Engle and Granger and Johansen and Juselius(Juselius 1999) * the use of calibration - Finn Kydland and Edward Prescott〔Kydland, Finn E & Prescott, Edward C, 1991. " The Econometrics of the General Equilibrium Approach to Business Cycles," ''Scandinavian Journal of Economics'', Blackwell Publishing, 93 (2),161–178.〕 * the ''experimentalist'' or difference in differences approach - Joshua Angrist and Jörn-Steffen Pischke.〔Angrist, J. D., & Pischke, J.-S. (2009). ''Mostly harmless econometrics: An empiricist's companion''. Princeton: Princeton University Press.〕 In addition to these more clearly defined approaches, Hoover〔Hoover, Kevin D. (2006). Chapter 2, "The Methodology of Econometrics." in T. C. Mills and K. Patterson, ed., ''Palgrave Handbook of Econometrics'', v. 1, ''Econometric Theory'', pp. 61-87.〕 identifies a range of ''heterogeneous'' or ''textbook approaches'' that those less, or even un-, concerned with methodology, tend to follow. ==Methods== Econometrics may use standard statistical models to study economic questions, but most often they are with observational data, rather than in controlled experiments. In this, the design of observational studies in econometrics is similar to the design of studies in other observational disciplines, such as astronomy, epidemiology, sociology and political science. Analysis of data from an observational study is guided by the study protocol, although exploratory data analysis may by useful for generating new hypotheses.〔Herman O. Wold (1969). "Econometrics as Pioneering in Nonexperimental Model Building," ''Econometrica'', 37(3), pp. (369 )-381.〕 Economics often analyzes systems of equations and inequalities, such as supply and demand hypothesized to be in equilibrium. Consequently, the field of econometrics has developed methods for identification and estimation of simultaneous-equation models. These methods are analogous to methods used in other areas of science, such as the field of system identification in systems analysis and control theory. Such methods may allow researchers to estimate models and investigate their empirical consequences, without directly manipulating the system. One of the fundamental statistical methods used by econometricians is regression analysis.〔For an overview of a linear implementation of this framework, see linear regression.〕 Regression methods are important in econometrics because economists typically cannot use controlled experiments. Econometricians often seek illuminating natural experiments in the absence of evidence from controlled experiments. Observational data may be subject to omitted-variable bias and a list of other problems that must be addressed using causal analysis of simultaneous-equation models.〔Edward E. Leamer (2008). "specification problems in econometrics," ''The New Palgrave Dictionary of Economics''. (Abstract. )〕 抄文引用元・出典: フリー百科事典『 ウィキペディア（Wikipedia）』 ■ウィキペディアで「Methodology of econometrics」の詳細全文を読む スポンサード リンク
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