In this paper we propose a model which includes both a known (potentially) nonlinear parametric component and an unknown nonparametric component. This approach is feasible given that we estimate the finite sample parameter vector and the bandwidths simultaneously. We show that our objective

The 2nd International Conference on Econometrics and Statistics (EcoSta 2018) will take place at the City University of Hong Kong, Hong Kong 19-21 June 2018.

The 1st International Conference on Econometrics and Statistics, EcoSta 2017 has taken place at the Hong Kong University of Science and

Longitudinal functional data consist of functional data collected at multiple time points for which the observational times may vary by subject. They differ from traditional longitudinal data in that the observation at each time point is a function rather than a scalar. The aim is to extend the

Since the underlying economic structure is likely to be affected by changes in preferences, technologies, policies, crises, etc., data in the previous time period may be irrelevant to the present data-generation process. Thus, econometric forecasts are often based on rolling estimation. However, it

Choosing the number of mixture components remains a central but elusive challenge. Traditional model selection criteria can be either overly liberal or conservative when enforcing parsimony. They may also result in poorly separated components of limited practical use. Non-local priors (NLPs) are a

In this work we propose one of the first models of "product framing" and pricing. Product framing refers to the way in which consumer choice is influenced by how products are framed, or displayed. We introduce a model in which a set of products are organized into a set of virtual pages.

In this paper, we model an online platform for short-term rentals of housing assets and analyze how a change in the pricing strategy due to the growing influx of corporate players to the platform affects the performance and payoffs of stakeholders. Many short-term online house rental platforms like

We examine whether firm internal governance with respect to headquarter-plant monitoring affects workplace safety. We use travel time reductions due to new airline routes as exogenous shocks to the cost of monitoring, and find that workplace safety improves as a result of greater proximity between

Modern decision analytics frequently involves the optimization of an objective over a finite horizon where the functional form of the objective is unknown. The decision analyst observes covariates and tries to learn and optimize the objective by experimenting with the decision variables. We present

We synthesize the field of machine learning with the canonical problem of empirical asset pricing: measuring asset risk premia. In the familiar empirical setting of cross section and time series stock return prediction, we perform a comparative analysis of methods in the machine learning