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Econometrics in theory and practice ...

Das, Panchanan.

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Econometrics in theory and practice = analysis of cross section, time series and panel data with Stata 15.1 /

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Econometrics in theory and practice/ by Panchanan Das.
其他題名:	analysis of cross section, time series and panel data with Stata 15.1 /
作者:	Das, Panchanan.
出版者:	Singapore :Springer Singapore : : 2019.,
面頁冊數:	xxvii, 565 p. :ill., digital ;24 cm.
內容註:	Introduction to Econometrics and Statistical Software -- Linear Regression Model: Properties and Estimation -- Linear Regression Model: Goodness of Fit and Testing of Hypothesis -- Linear Regression Model: Relaxing the Classical Assumptions -- Analysis of Collinear Data: Multicollinearity -- Linear Regression Model: Qualitative Variables as Predictors -- Limited Dependent Variable Model -- Multivariate Analysis -- Time Series: Data Generating Process -- Stationary Time Series -- Nonstationarity, Unit Root and Structural Break -- Cointegration, Error Correction and Vector Autoregression -- Cointegration, Error Correction and Vector Autoregression -- Time Series Forecasting.
Contained By:	Springer Nature eBook
標題:	Econometrics. -
電子資源:	https://doi.org/10.1007/978-981-32-9019-8
ISBN:	9789813290198

Econometrics in theory and practice = analysis of cross section, time series and panel data with Stata 15.1 /
Das, Panchanan.

Econometrics in theory and practiceanalysis of cross section, time series and panel data with Stata 15.1 /[electronic resource] :by Panchanan Das. - Singapore :Springer Singapore :2019. - xxvii, 565 p. :ill., digital ;24 cm.

Introduction to Econometrics and Statistical Software -- Linear Regression Model: Properties and Estimation -- Linear Regression Model: Goodness of Fit and Testing of Hypothesis -- Linear Regression Model: Relaxing the Classical Assumptions -- Analysis of Collinear Data: Multicollinearity -- Linear Regression Model: Qualitative Variables as Predictors -- Limited Dependent Variable Model -- Multivariate Analysis -- Time Series: Data Generating Process -- Stationary Time Series -- Nonstationarity, Unit Root and Structural Break -- Cointegration, Error Correction and Vector Autoregression -- Cointegration, Error Correction and Vector Autoregression -- Time Series Forecasting.

This book introduces econometric analysis of cross section, time series and panel data with the application of statistical software. It serves as a basic text for those who wish to learn and apply econometric analysis in empirical research. The level of presentation is as simple as possible to make it useful for undergraduates as well as graduate students. It contains several examples with real data and Stata programmes and interpretation of the results. While discussing the statistical tools needed to understand empirical economic research, the book attempts to provide a balance between theory and applied research. Various concepts and techniques of econometric analysis are supported by carefully developed examples with the use of statistical software package, Stata 15.1, and assumes that the reader is somewhat familiar with the Strata software. The topics covered in this book are divided into four parts. Part I discusses introductory econometric methods for data analysis that economists and other social scientists use to estimate the economic and social relationships, and to test hypotheses about them, using real-world data. There are five chapters in this part covering the data management issues, details of linear regression models, the related problems due to violation of the classical assumptions. Part II discusses some advanced topics used frequently in empirical research with cross section data. In its three chapters, this part includes some specific problems of regression analysis. Part III deals with time series econometric analysis. It covers intensively both the univariate and multivariate time series econometric models and their applications with software programming in six chapters. Part IV takes care of panel data analysis in four chapters. Different aspects of fixed effects and random effects are discussed here. Panel data analysis has been extended by taking dynamic panel data models which are most suitable for macroeconomic research. The book is invaluable for students and researchers of social sciences, business, management, operations research, engineering, and applied mathematics.

ISBN: 9789813290198

Standard No.: 10.1007/978-981-32-9019-8doiSubjects--Topical Terms:

542934
Econometrics.

LC Class. No.: HB139 / .D37 2019

Dewey Class. No.: 330.015195

Econometrics in theory and practice = analysis of cross section, time series and panel data with Stata 15.1 /
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520 $a This book introduces econometric analysis of cross section, time series and panel data with the application of statistical software. It serves as a basic text for those who wish to learn and apply econometric analysis in empirical research. The level of presentation is as simple as possible to make it useful for undergraduates as well as graduate students. It contains several examples with real data and Stata programmes and interpretation of the results. While discussing the statistical tools needed to understand empirical economic research, the book attempts to provide a balance between theory and applied research. Various concepts and techniques of econometric analysis are supported by carefully developed examples with the use of statistical software package, Stata 15.1, and assumes that the reader is somewhat familiar with the Strata software. The topics covered in this book are divided into four parts. Part I discusses introductory econometric methods for data analysis that economists and other social scientists use to estimate the economic and social relationships, and to test hypotheses about them, using real-world data. There are five chapters in this part covering the data management issues, details of linear regression models, the related problems due to violation of the classical assumptions. Part II discusses some advanced topics used frequently in empirical research with cross section data. In its three chapters, this part includes some specific problems of regression analysis. Part III deals with time series econometric analysis. It covers intensively both the univariate and multivariate time series econometric models and their applications with software programming in six chapters. Part IV takes care of panel data analysis in four chapters. Different aspects of fixed effects and random effects are discussed here. Panel data analysis has been extended by taking dynamic panel data models which are most suitable for macroeconomic research. The book is invaluable for students and researchers of social sciences, business, management, operations research, engineering, and applied mathematics.
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