Fixed Effects Models -- When and How Much Do Fixed Effects Matter?- Random Effects Models -- Estimation of Sparse Variance-Covariance Matrix -- Models with Endogenous Regressors -- Dynamic Models and Reciprocity -- Random Coefficients Models -- Nonparametric Models with Random Effects --...

Chapter 1. Introduction -- Chapter 2. Robust Dynamic Space–time Panel Data Models Using εε-contamination: An Application to Crop Yields and Climate Change -- Chapter 3. Unbiased Estimation of the OLS Covariance Matrix When the Errors are Clustered -- Chapter 4. Refined GMM Estimators for...

This book introduces modern series methods with a focus on applications in econometrics and statistics. It explores how new orthogonal series techniques can address challenges in model building and estimation, particularly for variables with unbounded support, nonparametric nonstationary data,...

Analysis of Business Survey Data The Mannheim Years -- Predicting World Population with Endogenous Fertility and Uncertain Climate Change Reflections on Marc Nerlove s Parable of Firewood -- Re estimating Supply Elasticities of Selected Agricultural Commodities -- Discrete GamesA Historical...

Introduction: Sources and Types of Big Data for Macroeconomic Forecasting -- Capturing Dynamic Relationships: Dynamic Factor Models -- Factor Augmented Vector Autoregressions, Panel VARs, and Global VARs -- Large Bayesian Vector Autoregressions -- Volatility Forecasting in a Data Rich...

The purpose of this book is to establish a connection between the traditional field of empirical economic research and the emerging area of empirical financial research, and to build a bridge between theoretical developments in these areas and their application in practice. Accordingly, it...

This book presents the econometric foundations and applications of multi-dimensional panels, including modern methods of big data analysis. The last two decades or so, the use of panel data has become a standard in many areas of economic analysis. The available models formulations became more...

This book treats the notion of morphisms in spatial analysis, paralleling these concepts in spatial statistics (Part I) and spatial econometrics (Part II). The principal concept is morphism (e.g., isomorphisms, homomorphisms, and allomorphisms), which is defined as a structure preserving the...

Linear Econometric Models with Machine Learning -- Nonlinear Econometric Models with Machine Learning -- The Use of Machine Learning in Treatment Effect Estimation.-Forecasting with Machine Learning Methods.-Causal Estimation of Treatment Effects From Observational Health Care Data Using Machine...

This volume is in honour of the remarkable career of the Father of Spatial Econometrics, Professor Jean Paelinck, presently of the Tinbergen Institute, Rotterdam. Jean Paelinck, arguably, is the founder of modern spatial econometrics. The impact on the profession through his work in spatial...