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Nonparametric likelihood ratio model selection tests between parametric likelihood and moment condition models
Testing the Markov property with high frequency data
Estimation of possibly misspecified semiparametric conditional moment restriction models with different conditioning variables
Asymptotic and bootstrap inference for inequality and poverty measures
Semiparametric identification and estimation in multi-object, English auctions
Root-N consistent semiparametric estimators of a dynamic panel-sample-selection model
Nonparametric frontier estimation via local linear regression
Consistent estimator for basis selection based on a proxy of the Kullback–Leibler distance
The quantilogram: With an application to evaluating directional predictability
Semiparametric methods in econometrics
Nonparametric efficiency analysis: A multivariate conditional quantile approach
The second-order bias and mean squared error of estimators in time-series models
Estimating dynamic panel data discrete choice models with fixed effects
固定效应动态面板离散选择模型的估计
In this paper, I consider the estimation of dynamic binary choice panel data models with fixed effects. I use a Modified Maximum Likelihood Estimator (MMLE) that reduces the order of the bias in the Maximum Likelihood Estimator from O(T^(-1)) to O(T^(-2)), without increasing the asymptotic variance. I evaluate its performance in finite samples where T is not large, using Monte Carlo simulations. In Probit and Logit models containing lags of the endogenous variable and…
Testing constancy of the error covariance matrix in vector models
Testing for unit roots in time series models with non-stationary volatility
Efficient estimation of general dynamic models with a continuum of moment conditions
A structural analysis of the correlated random coefficient wage regression model
Testing joint hypotheses when one of the alternatives is one-sided
Modeling and calculating the effect of treatment at baseline from panel outcomes
Properties of optimal forecasts under asymmetric loss and nonlinearity
非对称损失与非线性下最优预测的性质
Evaluation of forecast optimality in economics and finance has almost exclusively been conducted under the assumption of mean squared error loss. Under this loss function optimal forecasts should be unbiased and forecast errors serially uncorrelated at the single period horizon with increasing variance as the forecast horizon grows. Using analytical results we show in this paper that all the standard properties of optimal forecasts can be invalid under asymmetric loss and…