Methods

We set up an econometric model of persuasion and study identification of key parameters under various scenarios of data availability.

Collective models identifying resource shares are promising tools to analyze intra-household welfare and poverty. However, their empirical application has proven difficult in practice as authors contend with large standard errors and unstable estimates. This paper uses a prominent framework to show how a common feature of the structure of these models makes the task so difficult and proposes an empirical strategy to stabilize the estimates.

Economic data are often generated by stochastic processes that take place in continuous time, though observations may occur only at discrete times.

Since 1995, police forces in England and Wales have obtained the right to raise revenues locally to supplement central government grants in order to fund their activities.

We derive necessary and sufficient conditions for a finite data set of price and demand observations to be consistent with an additively separable preference.

It is almost self-evident that social interactions can determine economic behavior and outcomes. Yet, information on social ties does not exist in most publicly available and widely used datasets. We present methods to recover information on the entire structure of social networks from observational panel data that contains no information on social ties between individuals.

We extend conformal inference to general settings that allow for time series data.

We provide adaptive inference methods for linear functionals of L1-regularized linear approximations to the conditional expectation function.

We develop an approach to valuing non-market goods using nonparametric revealed preference analysis. We show how nonparametric methods can also be used to bound the welfare effects of changes in the provision of a non-market good.

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.

This paper studies dynamic discrete choices by relaxing the assumption of rational expectations.

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

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.

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

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.

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.