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Typically, a Poisson model is assumed for count data. In many cases, there are many zeros in the dependent variable, thus the mean is not equal to the variance value of the dependent variable. Therefore, Poisson model is not suitable anymore for this kind of data because of too many zeros. Thus, we suggest using a hurdle‐generalized Poisson regression model. Furthermore, the response variable in such cases is censored for some values because of some big values. A censored hurdle‐generalized Poisson regression model is introduced on count data with many zeros in this paper. The estimation of regression parameters using the maximum likelihood method is discussed and the goodness‐of‐fit for the regression model is examined. An example and a simulation will be used to illustrate the effects of right censoring on the parameter estimation and their standard errors.

Cover; Half-title; Title; Copyright; Contents; Figures; Tables; Preface; 1 In the beginning; 2 Basic notions of statistics; 3 Choosing; 4 Paradigms of choice data; 5 Processes in setting up stated choice experiments; 6 Choices in data collection; 7 NLOGIT for applied choice analysis: a primer; 8 Handling choice data; 9 Case study: mode-choice data; 10 Getting started modeling: the basic MNL model; 11 Getting more from your model; 12 Practical issues in the application of choice models; 13 Allowing for similarity of alternatives; 14 Nested logit estimation; 15 The mixed logit model.

This collection of methodological developments and applications of simulation-based methods were presented at a workshop at Louisiana State University in November, 2009. Topics include: extensions of the GHK simulator; maximum-simulated likelihood; composite marginal likelihood; and modelling and forecasting volatility in a bayesian approach.

Regression analysis using panel data for 42 colleges and universities over 14 years suggests that the economics faculty size of universities offering a Ph.D. in economics is determined primarily by the long-run average number of Ph.D. degrees awarded annually; the number of full-time faculty increases at almost a one-for-one pace as the average number of Ph.D.s grows. Faculty size at Ph.D. granting universities is largely unresponsive to changes in the contemporaneous number of undergraduate economics degrees awarded at those institutions. Similarly, faculty size at colleges where a bachelor's is the highest degree awarded is responsive to the long and short term average number of economics degrees awarded but not the annual changes in BS and BA degrees awarded in economics.