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Generalized Moments Estimation for Panel Data

Druska, Viliam - 2003

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/10012469113

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/10012458043

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/10012458292

Maximum Likelihood Estimation of Stochastic Volatility Models

Ait-Sahalia, Yacine - 2004

We develop and implement a new method for maximum likelihood estimation in closed-form of stochastic volatility models. Using Monte Carlo simulations, we compare a full likelihood procedure, where an option price is inverted into the unobservable volatility state, to an approximate likelihood...

Persistent link: https://www.econbiz.de/10012468114

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

Creal, Drew D. - 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/10012458545

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/10012458978

A Maximum Likelihood Method for the Incidental Parameter Problem

Moreira, Marcelo - 2008

instrumental variable (IV) model; and (iv) a dynamic panel data model with fixed effects. In the first two examples, there exist … change with the sample size. In a dynamic panel data model with N individuals and T time periods, MILE is consistent as long …

Persistent link: https://www.econbiz.de/10012464860

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

Brandt, Michael W. - 2001

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/10012470313

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

Christiano, Lawrence J. - 1999

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/10012471773

Maximum Likelihood Estimation of Generalized Ito Processes with Discretely Sampled Data

Lo, Andrew W. - 1986

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/10012477081