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...

Most empirical work in the social sciences is based on observational data that are often both incomplete, and therefore unrepresentative of the population of interest, and affected by measurement errors. These problems are very well known in the literature and ad hoc procedures for parametric...

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...

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...