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,...

This paper investigates how conditional quantiles of a given distribution relate to each other. Given two conditional quantiles estimated nonparametrically, we investigate their relation by linking them through a parametric transformation. Asymptotic normality of the associated parameter vector...

We study participation and relative earnings in the formal, informal, and self-employed sectors in Bolivia. We estimate quantile earnings equations corrected for self-selectivity to address potential biases in the estimates of relative earnings gaps due to the endogeneity of sector...

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...

This paper considers a linear triangular simultaneous equations model with conditional quantile restrictions. The paper adjusts for endogeneity by adopting a control function approach and presents a simple two-step estimator that exploits the partially linear structure of the model. The first...

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...

Strong seasonality in demand, a short product life cycle, and the absence of any price competition make the release date of first-run movies one of the main strategic decisions taken by movies' distributors. Movies are typically released on a Friday within a short release season, thus making the...

In this paper we extend the setting analysed in Hahn and Hausman (2002a) by allowing for conditionally heteroscedastic disturbances. We start by considering the type of conditional variance-covariance matrices proposed by Engle and Kroner (1995) and we show that, when we impose a GARCH...

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...