8 papers
Identification and Estimation in Panel Data Models with Nonparametric Two-Way Fixed Effects
Hugo Freeman, Dennis Kristensen
We study identification and estimation of panel data models that are characterised by a common, potentially, infinite-dimensional parameter, and an unknown transformation $g(α_…
Inference on Linear Regressions with Two-Way Unobserved Heterogeneity
Hugo Freeman, Dennis Kristensen
We develop a general estimation and inference procedure for the common parameters in linear panel data regression models with nonparametric two-way specification of unobserved hete…
Closed-form approximations of moments and densities of continuous-time Markov models
Dennis Kristensen, Young Jun Lee, Antonio Mele
This paper develops power series expansions of a general class of moment functions, including transition densities and option prices, of continuous-time Markov processes, including…
Diffusion Copulas: Identification and Estimation
Ruijun Bu, Kaddour Hadri, Dennis Kristensen
We propose a new semiparametric approach for modelling nonlinear univariate diffusions, where the observed process is a nonparametric transformation of an underlying parametric dif…
Identification of a class of index models: A topological approach
Mogens Fosgerau, Dennis Kristensen
We establish nonparametric identification in a class of so-called index models using a novel approach that relies on general topological results. Our proof strategy requires substa…
Solving Dynamic Discrete Choice Models Using Smoothing and Sieve Methods
Dennis Kristensen, Patrick K. Mogensen, Jong Myun Moon +1
We propose to combine smoothing, simulations and sieve approximations to solve for either the integrated or expected value function in a general class of dynamic discrete choice (D…
Local Polynomial Estimation of Time-Varying Parameters in Nonlinear Models
Dennis Kristensen, Young Jun Lee
We develop a novel asymptotic theory for local polynomial extremum estimators of time-varying parameters in a broad class of nonlinear time series models. We show the proposed esti…
Bayesian Indirect Inference and the ABC of GMM
Michael Creel, Jiti Gao, Han Hong +1
In this paper we propose and study local linear and polynomial based estimators for implementing Approximate Bayesian Computation (ABC) style indirect inference and GMM estimators.…