This paper is concerned with estimating the additive components of a nonparametric additive quantile regression model. We develop an estimator that is asymptotically normally distributed with a rate of convergence in probability of $n^{-r/(2r+1)}$ when the additive components are $r$-times...

Quantile regression (QR) methods fit a linear model for conditional quantiles, just as ordinary least squares (OLS) regression estimates a linear model for conditional means. An attractive feature of the OLS estimator is that it gives a minimum mean square error approximation to the conditional...

There is conflicting evidence regarding the recent evolution of unemployment duration in the U.S. In this study we rely on censored quantile regression methods to analyze the changes in the US unemployment duration distribution. We employed the decomposition method proposed by Machado and Mata...

One of the lessons of the treatment effects literature is the lack of consensus about the ability of statistical and econometric methods to replicate experimental estimates. In this paper, we provide new evidence using an unusual unemployment insurance experiment that allows the identification...

In this paper, local relationship between per capita health expenditure and GDP is investigated with local quantile regressions. The advantage of using local quantile regressions is the assumption of homogeneity on per capita health care expenditure could be relaxed so that number of countries...

This paper presents calculations of semiparametric efficiency bounds for quantile treatment effects parameters when selection to treatment is based on observable characteristics. The paper also presents three estimation procedures for these parameters, all of which have two steps: a...

We consider a semiparametric log periodogram regression estimation of memory parameter $d$ for non-stationary fractional time series using wavelet transformation. We propose wavelet-based log periodogram regression estimator, and obtain the asymptotic mean squared error, consistency and...

We consider semiparametric log periodogram regression estimation of memory parameter for the latent process in long memory stochastic volatility models. It is known that though widely used among researchers, the Geweke and Porter-Hudak (1983; GPH) LP estimator violates the Gaussian or Martingale...

This paper provides conditions for identification and estimation of the conditional or unconditional average effect of a binary treatment or policy on a scalar outcome in models where treatment may be misclassified. Misclassification probabilities and the true probability of treatment are also...

Finite-sample inference methods are developed for quantile regression models. The methods are conservative in that (i) they apply to arbitrary sample sizes without the liberal assumption that sample sizes approach infinity, (ii) they apply when the quantiles are partially or set identified,...