This book is a collection of 20 chapters on chosen topics from cross-section and panel data econometrics. It explores both theoretical and practical aspects of selected cutting-edge techniques which are gaining popularity among applied econometricians, while following the motto of “keeping things simple”. Each chapter gives a basic introduction to one such method, directs readers to supplementary references, and shows an application. The book takes into account that—A: The field of econometrics is evolving very fast and leading textbooks are trying to cover some of the recent developments in revised editions. This book offers basic introduction to state-of-the-art techniques and recent advances in econometric models with detailed applications from various developing and developed countries. B: An applied researcher or practitioner may prefer reference books with a simple introduction to an advanced econometric method or model with no theorems but with a longer discussion on empirical application. Thus, an applied econometrics textbook covering these cutting-edge methods is highly warranted; a void this book attempts to fills.
The book does not aim at providing a comprehensive coverage of econometric methods. The 20 chapters in this book represent only a sample of the important topics in modern econometrics, with special focus on econometrics of cross-section and panel data, while also recognizing that it is not possible to accommodate all types of models and methods even in these two categories. The book is unique as authors have also provided the theoretical background (if any) and brief literature review behind the empirical applications. It is a must-have resource for students and practitioners of modern econometrics.
Mục lục
Count Data Regression: Modelling Diversification in Sports Participation in Spain.- Modeling and Analysis of Discrete Response Data: Applications to Public Opinion on Marijuana Legalization in the United States.- Random Logit Model: An application to demand estimation for differentiated product.- Tobit Regression Analysis of Farmer Adoption Behavior: A Case from El Salvador.- Multiple Hurdle Tobit: Modelling Consumer Behaviour in the US.- Quantile Regression and Decomposition Techniques to Analyse Nutritional Demand in India.- Mixture Models to Infer Income Class Membership in India.- A Primer on Spatial Regression Models: Applications to Poverty and Inequality of Indian Districts.- Nonparametric and Semiparametric Regressions: An Empirical Investigation of Engel’s Law in the context of Brazil.- Copula-based dependence modelling with application in finance.
Giới thiệu về tác giả
Deep Mukherjee is Associate Professor at the Department of Economic Sciences of Indian Institute of Technology (IIT) Kanpur. He obtained Ph.D. in Agricultural & Resource Economics from the University of Connecticut and M.S. in Quantitative Economics from the Indian Statistical Institute (ISI). His research and teaching interests lie in applied microeconomics and quantitative policy analysis. He has conducted significant fieldwork as part of research in the form of extension visits, focus group discussions, and household surveys in various parts of India. Prior to joining Ph D program, he worked for GE Capital International Services (now, Genpact) as Business Analyst.