This paper considers transformations of nonlinear semiparametric mean functions that yield moment conditions for estimation. Such transformations are said to be information equivalent if they yield the same asymptotic efficiency bound. I derive a unified theory of algebraic equivalence for...

This article proposes a new nonparametric test to detect financial contagion by using a Kendall's tau-based asymmetric measure of comovements between two time series. Simulation studies demonstrate the reasonable size performance and good power in finite sample of our test. An empirical...

I propose a novel nonparametric method to empirically identify the degree of heterogeneity in individual preferences. Using preference information revealed by the observed behaviour, the method estimates interpersonal preference heterogeneity as the Kemeny distance between individual rankings...

In many applications of discrete choice modeling, there exist unobserved factors (UFs) driving the consumer demand that are not included in the model. Ignoring such UFs when fitting the choice model can produce biased parameter estimates and ultimately lead to incorrect policy decisions. At the...

We propose a novel theory-based approach to the reinforcement learning problem of maximizing profits when faced with an unknown demand curve. Our method is based on multi-armed bandits, which are a collection of minimal assumption non-parametric models that balance exploration and exploitation...

This article develops a novel nonparametric time-varying auto-regressive distributed-lag model to estimate and test the persistence of inflation. To characterize the temporal instability of persistence in the inflation process, our proposed model allows for time-varying coefficients with...