The general financial stress confronting Chinese local governments requires public spending to become more efficient. While previous work has attempted to study what determines the efficiency, the focus was put on various factors that were not under direct control by policymakers. This paper...

We use a dynamic panel Tobit model with heteroskedasticity to generate point, set, and density forecasts for a large cross-section of short time series of censored observations. Our fully Bayesian approach allows us to flexibly estimate the cross-sectional distribution of heterogeneous...

This paper reviews some key contributions to econometric analysis of human fertility in the last 20 years, with special focus on discussion of prevailing econometric modeling strategies. We focus on the literature that highlights the role of the key drivers of the birth outcomes, including age...

A new over-dispersed discrete probability model is introduced, by compounding the Poisson distribution with the weighted Ishita distribution. The statistical properties of the newly introduced distribution have been derived and discussed. Parameter estimation has been done with the application...

This paper reviews some key contributions to econometric analysis of human fertility in the last 20 years, with special focus on discussion of prevailing econometric modeling strategies. We focus on the literature that highlights the role of the key drivers of the birth outcomes, including age...

We develop a model for museum visits and estimate it on a large sample of holders of a museum card that provides free access to all museums. Our model distinguishes two stages, referring to the determination of the number of trips and destination choice and can deal with an effect of income on...

The purpose of this paper is to apply count data models to predict the number of times a credit applicant will not pay the amount awarded to repay the credit. Poisson models and negative binomial distribution models, taking into account the observed heterogeneity, are generally used in...

We propose a new finite sample corrected variance estimator for the linear generalized method of moments (GMM) including the one-step, two-step, and iterated estimators. Our formula additionally corrects for the over-identification bias in variance estimation on top of the commonly used finite...

We use a dynamic panel Tobit model with heteroskedasticity to generate point, set, and density forecasts for a large cross-section of short time series of censored observations. Our fully Bayesian approach allows us to flexibly estimate the cross-sectional distribution of heterogeneous...