This paper describes a randomization-based inference procedure for the distribution or quantiles of potential outcomes for a binary treatment and instrument. The method imposes no parametric model for the treatment effect, and remains valid for small n, a weak instrument, or inference on tail...

We propose a method to identify bounds (i.e. set identification) on the sharing rule for a general collective household consumption model. Unlike the effects of distribution factors, it is well known that the level of the sharing rule cannot be uniquely identified without strong assumptions on...

We propose a method to identify bounds (i.e. set identification) on the sharing rule for a general collective household consumption model. Unlike the effects of distribution factors, it is well known that the level of the sharing rule cannot be uniquely identified without strong assumptions on...

This paper considers the treatment of endogenous explanatory variables in the work of the Cowles Commission and in Carl Christ's classic 1966 textbook, and certain problems that arise when this approach is followed in areas such as the study of female labor supply where a prior knowledge is...

This study analyses the effectiveness of targeted public support for R&D investment. In particular, we test whether the specific policy design aiming at incentivizing (international) collaboration and R&D in small and medium-sized firms achieves the desired objectives on input as well as output...

This study analyses the effectiveness of targeted public support for R&D investment. In particular, we test whether the specific policy design aiming at incentivizing (international) collaboration and R&D in small and medium sized firms achieves the desired objectives on input as well as output...

This paper analyzes the mortgage borrowing process from a Russian state-owned supplier of residential housing mortgages concentrating on the estimation of demand function with heterogeneous borrowers' preferences. Analysis takes into account the underwriting process and the choice of contract...

We consider median regression and, more generally, quantile regression in high-dimensional sparse models. In these models the overall number of regressors p is very large, possibly larger than the sample size n, but only s of these regressors have non-zero impact on the conditional quantile of...

We construct new features based on order book data and separate them into three groups, e.g., time-insensitive features, time-sensitive features and cointegration features. For time-insensitive features, we applied serval transformation on imbalance in different levels, and some other features...

In this paper, we clarify the relations between the existing sets of regularity conditions for convergence rates of nonparametric indirect regression (NPIR) and nonparametric instrumental variables (NPIV) regression models. We establish minimax risk lower bounds in mean integrated squared error...