Ruoyao Shi (史若瑶)

I am an assistant professor at Department of Economics, University of California, Riverside. My research areas are econometrics methods and applied microeconomics.

Here is my CV. Here is my Google Scholar page.

Working Papers

3. An Averaging Estimator for Two Step M Estimation in Semiparametric Models (February 2019, new draft coming soon)

Abstract: In this paper, we study the two step M estimation of a finite dimensional parameter which depends on a first step estimation of a potentially infinite dimensional nuisance parameter. We present an averaging estimator that combines a semiparametric estimator based on nonparametric first step and a parametric estimator which imposes parametric restrictions on the first step. The averaging weight is the sample analog of an infeasible optimal weight that minimizes quadratic risk functions. This averaging estimator strikes a balance between the robust semiparametric estimator and the efficient parametric estimator, as we show that the averaging estimator uniformly dominates the semiparametric estimator in terms of asymptotic quadratic risk regardless of whether the first step parametric restrictions hold or not. In particular, we prove that under certain sufficient conditions, the asymptotic lower bound of the truncated quadratic risk differences between the averaging estimator and the semiparametric estimator is strictly less than zero under a class of data generating processes that includes both correct specification and misspecification of the first step parametric restrictions, and the asymptotic upper bound is weakly less than zero. We illustrate our estimator in a variety of applications using simulations and real data.

2. What Time Use Surveys Can (And Cannot) Tell Us About Labor Supply (joint with Cheng Chou, July 2019, under review) [slides]

Abstract: Nonclassical measurement errors in conventional microeconomic surveys result in biased estimates regarding weekly labor supply. The American Time Use Survey (ATUS) accurately measures hours worked on a single day. We show that despite the impossibility to recover weekly hours, weekly labor supply parameters can be consistently and efficiently estimated using the ATUS. We propose impute estimator and carefully examine its properties. It is a simple modification of the 2SLS estimator, which imputes both dependent and independent variables using daily subsamples. We apply it to the ATUS and find substantially different elasticity estimates from the CPS, especially for married women.

1. Identification and Estimation of Nonparametric Hedonic Equilibrium Model with Unobserved Quality (May 2019, under review) [appendices] [slides]

Abstract: This paper studies a nonparametric hedonic equilibrium model in which certain product characteristics are unobserved by researchers. Unlike most previously studied hedonic models, the observed and unobserved agent heterogeneities both enter the structural functions nonparametrically. Prices are endogenously determined in the equilibrium. Using both within market and cross market price variations, I show the nonparametric identification of all the structural functions of the model up to normalization. In particular, the unobserved product quality function is identified if the relative prices of the agent characteristics differ in at least two markets. Following the constructive identification strategy, I provide easy-to-implement series minimum distance estimators of the structural functions and derive their uniform rates of convergence. To demonstrate the estimation procedure, I estimate the unobserved efficiency of American full-time workers as a function of age and unobserved ability.