Books in the Foundations and Trends (R) in Econometrics series

Provides an overview of Efficiency and Productivity Analysis, a very important field of research and practice, spanning over and engaging with many disciplines, most prominently Economics (theoretical and applied), Statistics (and therefore Econometrics), Operations Research and Management Science.

Presents the body of econometric techniques that are customized to experimental applications. This monograph is aimed at two types of reader -- the experimental economist who is interested in expanding their skill set in econometric techniques and the econometrician interested in the econometric techniques currently being used by experimentalists.

Provides a review of the research in this new and growing field. The book describes econometric methods for empirical climate modelling that can account for wide-sense non-stationarity; considers hazards confronting empirical modelling of nonstationary time-series data; and provides a brief excursion into climate science.

Provides the reader with stated preference data collection methods, discrete choice models, and statistical analysis tools that can be used to forecast demand and assess welfare impacts for new or modified products or services in real markets, and summarise the conditions under which the reliability of these methods has been demonstrated.

Takes a broad view of spatial econometrics and introduces some of the basic concepts. After an introduction, the book introduces methods for the spatial econometric analysis of regional data, explores the new emerging field of microeconometrics, and applies the general SARAR paradigm to the case of spatial interaction models.

Details the important econometric area of efficiency estimation, both past approaches as well as new methodology. There are two main camps in efficiency analysis: Data Envelopment Analysis and Stochastic Frontier Analysis (SFA). This volume focuses exclusively on SFA.

Provides a thorough examination of this topic for students and researchers alike. While nonparametric estimators are widely used to estimate the productive efficiency of firms and other organizations, it is often done without any attempt to make statistical inference.

Shows why failing to consider the alternative hypothesis often leads to incorrect conclusions. The book shows that for most standard econometric estimators, it is not difficult to compute the proper probabilities using Bayes theorem. Simple formulas that require only readily available information in standard estimation reports are provided.

Explores the copula approach for econometrics modeling of joint parametric distributions and demonstrates that practical implementation and estimation is relatively straightforward despite the complexity of its theoretical foundations.