Similar Search Results

Generalized Moments Estimation for Panel Data

Druska, Viliam; Horrace, William C. - 2021

This paper considers estimation of a panel data model with disturbances that are autocorrelated across cross … estimate spatial dependence parameters. For the case where the time dimension is small (the usual panel data case), we develop … Kelejian and Prucha. We apply this approach in a stochastic frontier framework to a panel of Indonesian rice farms where …

Persistent link: https://www.econbiz.de/10013232767

Estimation of Dynamic Discrete Choice Models by Maximum Likelihood and the Simulated Method of Moments

Eisenhauer, Phillipp - 2014

We compare the performance of maximum likelihood (ML) and simulated method of moments (SMM) estimation for dynamic discrete choice models. We construct and estimate a simplified dynamic structural model of education that captures some basic features of educational choices in the United States in...

Persistent link: https://www.econbiz.de/10013044978

Spatial Errors in Count Data Regressions

Bertanha, Marinho - 2014

of health and unemployment. Along with negative binomial, Poisson panel regressions are a preferred method of analysis …, this result also applies to the commonly used Logit model of panel data with fixed effects. We develop a test for time …

Persistent link: https://www.econbiz.de/10013049006

Solution and Maximum Likelihood Estimation of Dynamic Nonlinear Rationalexpectations Models

Fair, Ray C.; Taylor, John B. - 2021

A solution method and an estimation method for nonlinear rational expectations models are presented in this paper. The solution method can be used in forecasting and policy applications and can handle models with serial correlation and multiple viewpoint dates. When applied to linear models, the...

Persistent link: https://www.econbiz.de/10013220429

Simulated Likelihood Estimation of Diffusions with an Application to Exchange Rate Dynamics in Incomplete Markets

Santa-Clara, Pedro; Brandt, Michael W. - 2021

We present an econometric method for estimating the parameters of a diffusion model from discretely sampled data. The estimator is transparent, adaptive, and inherits the asymptotic properties of the generally unattainable maximum likelihood estimator. We use this method to estimate a new...

Persistent link: https://www.econbiz.de/10013235636

Maximum Likelihood in the Frequency Domain : a Time to Build Example

Christiano, Lawrence J.; Vigfusson, Robert J. - 2021

A well known result is that the Gaussian log-likelihood can be expressed as the sum over different frequency components. This implies that the likelihood ratio statistic has a similar linear decomposition. We exploit these observations to devise diagnostic methods that are useful for...

Persistent link: https://www.econbiz.de/10013240316

Maximum Likelihood Estimation of Generalized Ito Processes with Discretely Sampled Data

Lo, Andrew W. - 2021

In this paper, we consider the parametric estimation problem for continuous time stochastic processes described by general first-order nonlinear stochastic differential equations of the Ito type. We characterize the likelihood function of a discretely-sampled set of observations as the solution...

Persistent link: https://www.econbiz.de/10013244771

Maximum Likelihood Estimation of the Equity Premium

Avdis, Efstathios - 2013

The equity premium, namely the expected return on the aggregate stock market less the government bill rate, is of central importance to the portfolio allocation of individuals, to the investment decisions of firms, and to model calibration and testing. This quantity is usually estimated from the...

Persistent link: https://www.econbiz.de/10013072344

Estimation of Affine Term Structure Models with Spanned or Unspanned Stochastic Volatility

Creal, Drew - 2014

We develop new procedures for maximum likelihood estimation of affine term structure models with spanned or unspanned stochastic volatility. Our approach uses linear regression to reduce the dimension of the numerical optimization problem yet it produces the same estimator as maximizing the...

Persistent link: https://www.econbiz.de/10013053780

Online Estimation of DSGE Models

Cai, Michael D.; Del Negro, Marco; Herbst, Edward P.; … - 2022

This paper illustrates the usefulness of sequential Monte Carlo (SMC) methods in approximating DSGE model posterior distributions. We show how the tempering schedule can be chosen adaptively, document the accuracy and runtime benefits of generalized data tempering for “online” estimation...

Persistent link: https://www.econbiz.de/10013323879