The 'Advances in Econometrics' series aims to publish annual original scholarly econometrics papers on designated topics with the intention of expanding the use of developed and emerging econometric techniques by disseminating ideas on the theory and practice of econometrics throughout the empirical economic, business and social science literature.

This volume of Advances in Econometrics contains articles that examine key topics in the modeling and estimation of dynamic stochastic general equilibrium (DSGE) models. Because DSGE models combine micro- and macroeconomic theory with formal econometric modeling and inference, over the past decade they have become an established framework for analyzing a variety of issues in empirical macroeconomics. The research articles make contributions in several key areas in DSGE modeling and estimation. In particular, papers cover the modeling and role of expectations, the study of optimal monetary policy in two-country models, and the problem of non-invertibility. Other interesting areas of inquiry include the analysis of parameter identification in new open economy macroeconomic models and the modeling of trend inflation shocks. The second part of the volume is devoted to articles that offer innovations in econometric methodology. These papers advance new techniques for addressing major inferential problems and include discussion and applications of Laplace-type, frequency domain, empirical likelihood and method of moments estimators.

The 30th Volume of Advances in Econometrics is in honor of the two individuals whose hard work has helped ensure thirty successful years of the series, Thomas Fomby and R. Carter Hill. This volume began with a history of the Advances series by Asli Ogunc and Randall Campbell summarizing the prior volumes. Tom Fomby and Carter Hill both provide discussions of the role of Advances over the years. The remaining articles include contributions by a number of authors who have played key roles in the series over the years and in the careers of Fomby and Hill. Overall, this leads to a more diverse mix of papers than a typical volume of Advances in Econometrics.

This volume is a collection of methodological developments and applications of simulation-based methods that were presented at a workshop at Louisiana State University in November, 2009. The first two papers are extensions of the GHK simulator: one reconsiders the computation of the probabilities in a discrete choice model while another example uses an adaptive version of sparse-grids integration (SGI) instead of simulation. Two studies are focused specifically on the methodology: the first compares the performance of the maximum-simulated likelihood (MSL) approach with a proposed composite marginal likelihood (CML) approach in multivariate ordered-response situations, while the second examines methods of testing for the presence of heterogeneity in the heterogeneity model. Further topics examined include: education savings accounts, parent contributions and education attainment; estimating the effect of exchange rate flexibility on financial account openness; estimating a fractional response model with a count endogenous regressor; and modelling and forecasting volatility in a bayesian approach.

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.