We study entrepreneurs' start-up financing from banks and local financiers. An informal network, whose membership cannot be observed by outsiders, conveys the good signals it gets about the hidden types of network entrepreneurs to local financiers, which are then reflected in different loan...

A measurement error model is a regression model with (substantial) measurement errors in the variables. Disregarding these measurement errors in estimating the regression parameters results in asymptotically biased estimators. Several methods have been proposed to eliminate, or at least to...

This paper develops a two-sector general equilibrium model in which firms in the primary economy have to create workplaces prior to production and product market competition. For this, we introduce the endogenous sunk cost approach with two-stage decisions of firms from IO in the macro-labor...

This paper proposes a dichotomous choice model that is based on a transformed beta (or "z") distribution. This model, called betit, nests both logit and probit and allows for various skewed and peaked disturbance densities. Because the shape of this density affects the estimated relation between...

This paper introduces a new and simple decomposition method for a binary choice model that is equivalent to the Blinder-Oaxaca decomposition analysis for wage differentials. The decomposition method is first developed for a single probit model and later generalized to a simultaneous equations...

This paper develops a simulation estimation algorithm that is particularly useful for estimating dynamic panel data models with unobserved endogenous state variables. The new approach can easily deal with the commonly encountered and widely discussed "initial conditions problem," as well as the...

A common approach to dealing with missing data is to estimate the model on the common subset of data, by necessity throwing away potentially useful data. We derive a new probit type estimator for models with missing covariate data where the dependent variable is binary. For the benchmark case of...

The Wooldridge method is based on a simple and novel strategy to deal with the initial values problem in the nonlinear dynamic random-effects panel data models. This characteristic of the method makes it very attractive in empirical applications. However, its finite sample performance is not...

In this paper we use a dynamic structural life-cycle model to analyze the employment, fiscal and welfare effects induced by unemployment insurance. The model features a detailed specification of the tax and transfer system, including unemployment insurance benefits which depend on an...

The pregibit discrete choice model is built on a distribution that allows symmetry or asymmetry and thick tails, thin tails or no tails. Thus the model is much richer than the traditional models that are typically used to study behavior that generates discrete choice outcomes. Pregibit nests...