This paper proposes a nonparametric method for evaluating treatment effects in the presence of both treatment endogeneity and attrition/non-response bias, using two instrumental variables. Making use of a discrete instrument for the treatment and a continuous instrument for...

This paper develops a nonparametric methodology for treatment evaluation with multiple outcome periods under treatment endogeneity and missing outcomes. We use instrumental variables, pre-treatment characteristics, and short-term (or intermediate) outcomes to identify the average treatment...

Volatility-based filtering is proposed to pre-process historical daily return data of stock indexes before applying to price-based technical analysis trading rules. Any “nearly flat” days which have daily gains or losses less than a threshold about 20% of a daily volatility measure, is...

In a number of semiparametric models, smoothing seems necessary in order to obtain estimates of the parametric component which are asymptotically normal and converge at parametric rate. However, smoothing can inflate the error in the normal approximation, so that refined approximations are of...

This paper proposes a nonparametric method for evaluating treatment effects in the presence of both treatment endogeneity and attrition/non-response bias, using two instrumental variables. Making use of a discrete instrument for the treatment and a continuous instrument for...

Given functional data from a survival process with time-dependent covariates, we derive a smooth convex representation for its nonparametric log-likelihood functional and obtain its functional gradient. From this we devise a generic gradient boosting procedure for estimating the hazard function...

We consider identification and estimation of nonseparable sample selection models with censored selection rules. We employ a control function approach and discuss different objects of interest based on (1) local effects conditional on the control function, and (2) global effects obtained from...

We deal with two kinds of Cox regression models with varying coefficients. The coefficients vary with time in one model. In the other model, there is an important random variable called an index variable and the coefficients vary with the variable. In both models, we have p-dimensional...

This research examines regional government performance in Indonesia's provinces after the implementation of fiscal decentralization in 2001 using a two-stage approach. First, extensive input and output data are utilized to measure government productivity and efficiency indices using a Malmquist...

The taxable income elasticity is a key parameter for predicting the e?ect of tax reform or designing an income tax. Bunching at kinks and notches in a single budget set have been used to estimate the taxable income elasticity. We show that when the heterogeneity distribution is unrestricted the...