Research methods

We consider a situation where a distribution is being estimated by the empirical distribution of noisy measurements.

We study the asymptotic properties of a class of estimators of the structural parameters in dynamic discrete choice games.

The interaction of economic agents is one of the most important elements in economic analyses.

We consider identification and estimation of nonseparable sample selection models with censored selection rules.

This paper proposes a simple and efficient estimation procedure for the model with non-ignorable missing data studied by Morikawa and Kim (2016).

We propose an estimation methodology for a semiparametric quantile factor panel model.

Moment restriction semiparametric models, where both the dimension of parameter and the number of restrictions are divergent and an unknown function is involved, are studied using the generalized method of moments (GMM) and sieve method dealing with the nonparametric parameter.

High frequency trading (HFT) has grown substantially in recent years, due to fast-paced technological developments and their rapid uptake, particularly in equity markets.

This paper studies a model with both a parametric global trend and a nonparametric local trend.

In this paper, we propose three new predictive models: the multi-step nonparametric predictive regression model and the multi-step additive predictive regression model, in which the predictive variables are locally stationary time series; and the multi-step time-varying coefficient predictive regression model, in which the predictive variables are stochastically nonstationary.

We study a longitudinal data model with nonparametric regression functions that may vary across the observed subjects.

This paper develops the identification and estimation of nonlinear semi-parametric panel data models with mismeasured variables and their corresponding average partial effects using only three periods of data.

We study the behaviour of the Betfair betting market and the sterling/dollar exchange rate (futures price) during 24 June 2016, the night of the EU referendum.

Understanding whether and how connections between agents (networks) such as declared friendships in classrooms, transactions between firms, and extended family connections, influence their socio-economic outcomes has been a growing area of research within economics.

A large literature has shown evidence that people are influenced by others, especially in group interactions.

The R package Counterfactual implements the estimation and inference methods of Chernozhukov et al. (2013) for counterfactual analysis.

Extremal quantile regression, i.e. quantile regression applied to the tails of the conditional distribution, counts with an increasing number of economic and financial applications such as value-at-risk, production frontiers, determinants of low infant birth weights, and auction models.

We propose strategies to estimate and make inference on key features of heterogeneous effects in randomized experiments.

New nonparametric methods that identify and estimate counterfactuals for individuals, when each is characterized by a vector of unobserved characteristics, are developed and applied to estimate systems of individual consumer demand and welfare measures.

This paper introduces new inference methods for counterfactual and synthetic control methods for evaluating policy effects.