Volume 27 of "Advances in Econometrics", entitled "Missing Data Methods", contains 16 chapters authored by specialists in the field, covering topics such as: Missing-Data Imputation in Nonstationary Panel Data Models; Markov Switching Models in Empirical Finance; Bayesian Analysis of Multivariate Sample Selection Models Using Gaussian Copulas; Consistent Estimation and Orthogonality; and Likelihood-Based Estimators for Endogenous or Truncated Samples in Standard Stratified Sampling.

Volume 27 of "Advances in Econometrics", entitled "Missing Data Methods", contains 16 chapters authored by specialists in the field, covering topics such as: Missing-Data Imputation in Nonstationary Panel Data Models; Markov Switching Models in Empirical Finance; Bayesian Analysis of Multivariate Sample Selection Models Using Gaussian Copulas; Consistent Estimation and Orthogonality; and Likelihood-Based Estimators for Endogenous or Truncated Samples in Standard Stratified Sampling.

This Book Set consists of: *9781780525242 - Missing Data Methods: Cross-sectional Methods and Applications (Part A) *9781780525266 - Missing Data Methods: Time-series Methods and Applications (Part B) The papers in this volume cover topics in the econometric approach to missing data problems. Data can be missing because an individual failed to answer a question or because the laws of nature imply that an individual can only follow one of several possible paths. We refer to the first case as one of missing observations and to the second case as one of unobserved outcomes. This volume reflects the fact that econometricians have been very active in the development and use of methods for unobserved outcomes. The huge interest in these methods caused the volume to be split into parts A and B. The 12 chapters in Part A discuss cross-sectional methods. All the papers either derive, survey, or evaluate new methods for handling missing-data problems. Per the current interest in econometrics, 11 of the 12 papers address unobserved-outcome problems. The 4 chapters in Part B discuss time-series methods. Two chapters comprehensively survey the use of Markov switching models in finance. The third chapter surveys discrete-time and continuous-time models for volatility. The fourth chapter derives a new imputation method for nonstationary panel-data models and compares it to existing methods.