Search Results
Showing results 1 to 8 of approximately 8.
(refine search)
Working Paper
Choosing information variables for transition probabilities in a time-varying transition probability Markov switching model
This paper discusses a practical estimation issue for time-varying transition probability (TVTP) Markov switching models. Time-varying transition probabilities allow researchers to capture important economic behavior that may be missed using constant (or fixed) transition probabilities. Despite its use, Hamilton?s (1989) filtering method for estimating fixed transition probability Markov switching models may not apply to TVTP models. This paper provides a set of sufficient conditions to justify the use of Hamilton?s method for TVTP models. In general, the information variables that govern ...
Working Paper
Common drifting volatility in large Bayesian VARs
The estimation of large vector autoregressions with stochastic volatility using standard methods is computationally very demanding. In this paper we propose to model conditional volatilities as driven by a single common unobserved factor.> This is justified by the observation that the pattern of estimated volatilities in empirical analyses is often very similar across variables. Using a combination of a standard natural conjugate prior for the VAR coefficients and an independent prior on a common stochastic volatility factor, we derive the posterior densities for the parameters of the ...
Working Paper
Approximating high-dimensional dynamic models: sieve value function iteration
Many dynamic problems in economics are characterized by large state spaces, which make both computing and estimating the model infeasible. We introduce a method for approximating the value function of high-dimensional dynamic models based on sieves and establish results for the: (a) consistency, (b) rates of convergence, and (c) bounds on the error of approximation. We embed this method for approximating the solution to the dynamic problem within an estimation routine and prove that it provides consistent estimates of the model's parameters. We provide Monte Carlo evidence that our method can ...
Report
Nonparametric pricing of multivariate contingent claims
In this paper, I derive and implement a nonparametric, arbitrage-free technique for multivariate contingent claim (MVCC) pricing. Using results from the method of copulas, I show that the multivariate risk-neutral density can be written as a product of marginal risk-neutral densities and a risk-neutral dependence function. I then develop a pricing technique using nonparametrically estimated marginal risk-neutral densities (based on options data) and a nonparametric dependence function (based on historical return data). By using nonparametric estimation, I avoid the pricing biases that result ...
Journal Article
Ask the market
Working Paper
Estimating a dynamic equilibrium model of firm location choices in an urban economy
We develop a new dynamic general equilibrium model to explain firm entry, exit, and relocation decisions in an urban economy with multiple locations and agglomeration externalities. We characterize the stationary distribution of firms that arises in equilibrium. We estimate the parameters of the model using a method of moments estimator. Using unique panel data collected by Dun and Bradstreet, we find that our model fits the moments used in estimation as well as a set of moments that we use for model validation. Agglomeration externalities increase the productivity of firms by about 8 ...
Working Paper
General nonlinear estimation