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Titlebook: Econometrics; Badi H. Baltagi Textbook 19981st edition Springer-Verlag Berlin Heidelberg 1998 cointegration.econometrics.integration.panel

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書目名稱Econometrics
編輯Badi H. Baltagi
視頻videohttp://file.papertrans.cn/302/301457/301457.mp4
概述Treats basic econometric methods as well as more advanced topics * New material is presented in a simple and accessible way *.Numerous empirical illustrations and exercises at the end of each chapter
圖書封面Titlebook: Econometrics;  Badi H. Baltagi Textbook 19981st edition Springer-Verlag Berlin Heidelberg 1998 cointegration.econometrics.integration.panel
描述This book is intended for a first year graduate course in econometrics. However, the first six chapters have no matrix algebra and can be used in an advanced undergraduate class. This can be supplemented by some of the material in later chapters that do not require matrix algebra, like the first part of Chapter lIon simultaneous equations and Chapter 14 on time-series analysis. This book teaches some of the basic econometric methods and the underlying assumptions behind them. Estimation, hypotheses testing and prediction are three recurrent themes in this book. Some uses of econometric methods include (i) empirical testing of economic theory, whether it is the permanent income consumption theory or purchasing power parity, (ii) forecasting, whether it is GNP or unemployment in the U.S. economy or future sales in the computer industry. (iii) Estimation of price elasticities of demand, or returns to scale in production. More importantly, econometric methods can be used to simulate the effect of policy changes like a tax increase on gasoline consumption, or a ban on advertising on cigarette consumption. It is left to the reader to choose among the available econometric software to use
出版日期Textbook 19981st edition
關(guān)鍵詞cointegration; econometrics; integration; panel data; regression; regression analysis; statistics; time ser
版次1
doihttps://doi.org/10.1007/978-3-662-00516-3
isbn_ebook978-3-662-00516-3
copyrightSpringer-Verlag Berlin Heidelberg 1998
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Simple Linear Regressionth observation on the dependent variable Y which could be consumption, investment or output, and X. denotes the i-th observation on the independent variable X which could be disposable income, the interest rate or an input. These observations could be collected on firms or households at a given poin
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The General Linear Model: The Basicsk. In this case, y is a column vector of dimension (nxl) and X is a matrix of dimension (nxk). Each column of X denotes a variable and each row of X denotes an observation on these variables. If y is consumption per capita in real terms, then the columns of X may contain a column of ones for the con
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Generalized Least Squaresre Ω is a positive definite matrix of dimension (nxn). First Ω is assumed known and the BLUE for β is derived. This estimator turns out to be different from ., and is denoted by ., the generalized least squares estimator of β. Therefore, we study the properties of . under this non-spherical form of
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