This study presents a structural estimation method for nonlinear stochastic dynamic models of heterogeneous firms. I perform a Monte Carlo experiment to evaluate the performance of the estimators for the AR(1) dynamic panel data subject to sample selection without exogenous regressors. The...

It is almost self-evident that social interactions can determine economic behavior and outcomes. Yet, information on social ties does not exist in most publicly available and widely used datasets. We present methods to recover information on the entire structure of social networks from...

This paper develops an unbiased Monte Carlo approximation to the transition density of a jump-diffusion process with state-dependent drift, volatility, jump intensity, and jump magnitude. The approximation is used to construct a likelihood estimator of the parameters of a jump-diffusion observed...

I show how simulated Geometric Brown Motion price paths can be used to value a real option - in this case a field of oil wells. The methodology shows how the long-term value of the oil well is largely unaffected when oil prices are below marginal cost today, a benefit over the standard cash-flow...

This paper assesses the economic implications of existing fiscal rules in Poland, Switzerland and Germany. In the analysis we establish economic relationships between output, government revenues and expenditures estimating a VAR model on US data for the years 1960–2015. Imposing fiscal...

Andrieu et al. (2010) prove that Markov chain Monte Carlo samplers still converge to the correct posterior distribution of the model parameters when the likelihood is estimated by the particle filter (with a finite number of particles) is used instead of the likelihood. A critical issue for...