We develop a nonparametric estimator for the volatility structure of the zero coupon yield curve in the Heath-Jarrow-Morton framework. The estimator incorporates cross-sectional restrictions along the maturity dimension, and also allows for measurement errors, which arise from the estimation of...

This paper studies the functional estimation of the drift and diffusion functions for recurrent scalar diffusion processes from equally spaced observations using the local polynomial kernel approach. Almost sure convergence and a CLT for the estimators are established as the sampling frequency...

We propose information theoretic tests for serial independence and linearity in time series. The test statisticsare based on the conditional mutual information, a general measure of dependence between lagged variables. In caseof rejecting the null hypothesis, this readily provides insights into...

The entropy principle yields, for a given set moments, a density that involves the smallest amount of prior information. We first show how entropy densities may be constructed in a numerically efficient way as the minimization of a potential. Next, for the case where the first four moments are...

This paper examines the empirical interplay between economic growth and greenhouse gas emissions using panel data. Relying on nonparametric methods, we find evidence supporting specifications which assume the constancy of the relationship between CO2 emissions and GDP per capita during the...

This paper investigates original issuers of high yield bonds in Chapter 11 bankruptcy to determine which factors affect the length of time spent in Chapter 11. In order to do this analysis we propose a flexible new duration model, the censored partial regression model. This model allows us to...

Recent studies in marketing show decompositions of sales promotion effects based on household-level scanner data. Typically, the total elasticity is decomposed into choice, timing, and quantity elasticities. We propose a model that estimates standard, enhanced, and flexible decompositions based...

We propose a functional estimation procedure for homogeneous stochastic differential equations based on a discrete sample of observations and with minimal requirements on the data generating process. We show how to identify the drift and diffusion function in situations where one or the other...