Econometrics

This book is an update of the 1993 publication of The Measurement of Productive Efficiency: Techniques and Applications. The same editors have here compiled over ten years of the most recent research in this changing field, and expanded on those seminal chapters and written this new edition. The book guides from the basic models to the latest, cutting-edge extensions, and is reinforced by references to classic and current theoretical and applied research. The book focuses on measuring and explaining producer performance. It views performance as a function of the state of technology and economic efficiency. It shows that insights can be gained by allowing for the possibility of a divergence between the economic objective and actual performance, and by associating this inefficiency with causal variables subject to managerial or policy influence.

David F. Hendry is a seminal figure in modern econometrics. He has pioneered the LSE approach to econometrics, and his influence is extensive. This book is a collection of original research in time-series econometrics, both theoretical and applied, and reflects David's interests in econometric methodology. Many internationally renowned econometricians who have collaborated with Hendry or have been influenced by his research have contributed to this book, which provides a reflection on the recent advances in econometrics and considers the future progress for the methodology of econometrics. The book is broadly divided into five sections, including model selection, correlations, forecasting, methodology, and empirical applications, although the boundaries are certainly opaque. Central themes of the book include dynamic modelling and the properties of time series data, model selection and model evaluation, forecasting, policy analysis, exogeneity and causality, and encompassing. The contributions cover the full breadth of time series econometrics but all with the overarching theme of congruent econometric modelling using the coherent and comprehensive methodology that David has pioneered. The book assimilates scholarly work at the frontier of academic research, encapsulating the current thinking in modern day econometrics and reflecting the intellectual impact that David has had, and will continue to have, on the profession.

This book brings to the fore recent advances in econometrics for treatment effect analysis. It aims to put together various economic treatment effect models in a coherent fashion, determine those that can be parameters of interest, and show how these can be identified and estimated under weak assumptions. The emphasis throughout the book is on semi- and non-parametric estimation methods, but traditional parametric approaches are also discussed. This book is ideally suited to researchers and graduate students with a basic knowledge of econometrics.

This book contains a up-to-date overview of nonlinear time series models and their application to modelling economic relationships. It considers nonlinear models in stationary and nonstationary frameworks, and both parametric and nonparametric models are discussed. The book contains examples of nonlinear models in economic theory and presents the most common nonlinear time series models. Importantly, it shows these models can be applied in practice. For this purpose, the building of various nonlinear models with its three stages of model building: specification, estimation, and evaluation, is discussed in detail and is illustrated by several examples involving both economic and non-economic data. Since estimation of nonlinear time series models is carried out using numerical algorithms, the book contains a chapter on estimating parametric nonlinear models and another on estimating nonparametric ones. Forecasting is a major reason for building time series models, linear or nonlinear. The book contains a discussion on forecasting with nonlinear models, both parametric and nonparametric, and considers numerical techniques necessary for computing multi-period forecasts from them. The main focus of the book is on models of the conditional mean, but models of the conditional variance, mainly those of autoregressive conditional heteroskedasticity, receive attention as well. A separate chapter is devoted to state space models.

This book reviews some of the main topics in panel data econometrics. It analyses econometric models with non-exogenous explanatory variables, and the problem of distinguishing between dynamic responses and unobserved heterogeneity in panel data models. The book is divided into three parts. Part I deals with static models. Part II discusses pure time series models. Part III considers dynamic conditional models.

This book considers periodic time series models for seasonal data, characterized by parameters that differ across the seasons, and focuses on their usefulness for out-of-sample forecasting. Providing an up-to-date survey of the recent developments in periodic time series, the book presents a large number of empirical results. The first part of the book deals with model selection, diagnostic checking, and forecasting of univariate periodic autoregressive models. It discusses tests for periodic integration, and provides an extensive discussion of the role of deterministic regressors in testing for periodic integration and in forecasting. The second part discusses multivariate periodic autoregressive models. It provides an overview of periodic cointegration models, including single-equation type tests and a full-system approach based on generalized method of moments. All methods are illustrated with extensive examples, and the book will be invaluable to advanced graduate students and researchers in econometrics and to practitioners looking for an understanding of how to approach seasonal data.

Theoretical research undertaken over the last decades showed that the nature of nominal rigidities plays a key role in determining the effects of different shocks on the economy. This research has made clear that a thorough understanding of the extent and causes of the sluggish adjustment of nominal prices is crucial to the design and conduct of monetary policy. This book presents the main results of a research program undertaken by the Eurosystem central banks on price setting decisions by firms in the euro area. Its objective is to deepen our understanding of the behavioral mechanisms driving agents' pricing decisions, adopting a methodological approach—asking firms directly about how they set the price of their output (their pricing strategies) and why (the rationale of these strategies)—that is particularly well suited for the purpose at hand. The book also compares results for the euro area to similar analyses for other countries and summarizes the main findings of studies based on individual quantitative micro data on consumer and producer prices carried out for most euro area countries. Finally, the book explores the monetary policy implications of the main findings.