Bøger i Foundations and Trends (R) in Econometrics serien

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.

Summarizes the structural econometric analysis of observational data from auctions. First developing the necessary economic theory, then mapping this to the data-generating processes, and finally investigating the various estimation strategies. Throughout the review, the authors illustrate the methods using a variety of examples.

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.

Takes a straightforward approach to illustrating the value of the CML method for the estimation of discrete and mixed dependent variable models in Econometrics. This book provides an overview of developments and applications, and explains why the approach can be effective for the analysis of high-dimensional heterogeneous data.

Offers a partial review of the vast literature in econometrics and statistics on calculating semiparametric efficiency bounds for a large class of models used in applied economics research. This book will help researchers learn more about efficiency bounds, their calculation, and their usefulness in semiparametric estimation.

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.

Spatial panel models have panel data structures to capture spatial interactions across spatial units and over time. There are static as well as dynamic models. Estimation of Spatial Panels provides some recent developments on the specification and estimation of such models.

Provides a survey of the Bayesian methods used in modern empirical macroeconomics. The book reviews and extends the Bayesian literature on VARs, TVP-VARs and TVP-FAVARs with a focus on the practitioner. The authors go beyond simply defining each model, but specify how to use them in practice.

Presents a unified econometric framework for dealing with the issues of endogeneity in Markov-switching models and time-varying parameter models. This book focuses on the LIML (limited information maximum likelihood) estimation of a single equation of interest out of a simultaneous equations model.

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.

Presents the fundamentals of Monte Carlo simulation, pointing to opportunities not often utilized in current practice, especially with regards to designing their general setup, controlling their accuracy, recognising their shortcomings, and presenting their results in a coherent way.

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.

Provides a survey of the main theoretical results for large dimensional factor models, emphasizing results that have implications for empirical work. The authors focus on the development of the static factor models and on the use of estimated factors in subsequent estimation and inference.