Econometrics in Theory and Practice

Analysis of Cross Section, Time Series and Panel Data with Stata 15.1

Inbunden, Engelska, 2019

2 739 kr

Beställningsvara. Skickas inom 10-15 vardagar

Fri frakt för medlemmar vid köp för minst 249 kr.

This book introduces econometric analysis of cross section, time series and panel data with the application of statistical software.

Produktinformation

Utgivningsdatum2019-09-19
Mått155 x 235 x 38 mm
Vikt1 051 g
FormatInbunden
SpråkEngelska
Antal sidor565
FörlagSpringer Verlag, Singapore
ISBN9789813290181

Tillhör följande kategorier

Matematisk statistik inom Naturvetenskap och teknik
Optimering inom Naturvetenskap och teknik
Affärsapplikationer inom Data och it
Mikroekonomi inom Ekonomi och ledarskap

Panchanan Das is a Professor of Economics, currently teaching Time Series and Panel Data Econometrics at the Department of Economics, University of Calcutta. His main research areas are Development Economics, Indian Economics, and Applied Macroeconomics. He has published several articles and book chapters on growth, inequality and poverty, and is a principal author of Economics I and Economics II, graduate-level textbooks published by Oxford University Press, New Delhi. He was also a major contributor to the West Bengal Development Report – 2008, published by the Academic Foundation, New Delhi, in collaboration with the Planning Commission, Government of India.

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.