Advances in Econometrics is a research annual whose editorial policy is to publish original research articles that contain enough details so that economists and econometricians who are not experts in the topics will find them accessible and useful in their research. Volume 37 exemplifies this focus by highlighting key research from new developments in econometrics.
PART I: INTRODUCTIONProgress In Spatial Modeling Of Discrete And Continuous Dependent VariablesPART II: DISCRETE DEPENDENT VARIABLES MAXIMUM LIKELIHOODFast Simulated Maximum Likelihood Estimation Of The Spatial Probit Model Capable Of Handling Large Samples - R. Kelley Pace and James P. LeSageLikelihood Evaluation Of High-Dimensional Spatial Latent Gaussian Models With Non-Gaussian Response Variables - Roman Liesenfeld, Jean-François Richard and Jan VoglerPART III: DISCRETE DEPENDENT VARIABLES BAYESIANThe Impact Of Storms On Firm Survival: A Bayesian Spatial Econometric Model For Firm Survival - Mihaela Craioveanu and Dek TerrellvBayesian Spatial Bivariate Panel Probit Estimation - Badi H. Baltagi, Peter H. Egger and Michaela KesinaEstimating Binary Spatial Autoregressive Models For Rare Events - Raffaella Calabrese and Johan A. ElkinkA Multivariate Spatial Analysis For Anticipating New Firm Counts - Yiyi Wang, Kara M. Kockelman and Paul DamienA Multivariate Spatial-Time Of Day Analysis Of Truck Crash Frequency Across Neighborhoods In New York City - Wei Zou, Xiaokun Wang and Yiyi WangPART IV: CONTINUOUS DEPENDENT VARIABLES MAXIMUM LIKELIHOODGroup Interaction In Research And The Use Of General Nesting Spatial Models - Peter Burridge, J. Paul Elhorst and Katarina ZigovaHow To Measure Spillover Effects Of Public Capital Stock: A Spatial Autoregressive Stochastic Frontier Model - Jaepil Han, Deockhyun Ryu and Robin SicklesPART V: CONTINUOUS DEPENDENT VARIABLES BAYESIANLocal Marginal Analysis Of Spatial Data: A Gaussian Process Regression Approach With Bayesian Model And Kernel Averaging - Jacob Dearmon and Tony E. SmithCity And Industry Network Impacts On Innovation By Chinese Manufacturing Firms: A Hierarchical Spatial- Interindustry Model - Yuxue Sheng and James P. LeSage
Badi H. Baltagi, Syracuse University, Syracuse, NY, USAJames P. Lesage, Texas State University, San Marcos, TX, USAR. Kelley Pace, Louisiana State University, Baton Rouge, LA, USA