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...

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...

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 --...

This book surveys big data tools used in macroeconomic forecasting and addresses related econometric issues, including how to capture dynamic relationships among variables; how to select parsimonious models; how to deal with model uncertainty, instability, non-stationarity, and mixed frequency...

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...

Chapter 1. An Introduction to the Econometrics of Program Evaluation -- Chapter 2. Methods Based on Selection on Observables -- Chapter 3. Methods Based on Selection on Unobservables -- Chapter 4. Local Average Treatment Effect and Regression-Discontinuity-Design -- Chapter 5....

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...