9 citations · 20 across the 9 of their papers we have counts for
10 papers
Identification in (Endogenously) Nonlinear SVARs Is Easier Than You Think
James A. Duffy, Sophocles Mavroeidis
We study identification in structural vector autoregressions (SVARs) in which the endogenous variables enter nonlinearly on the left-hand side of the model, a feature we term endog…
Stationarity with Occasionally Binding Constraints
James A. Duffy, Sophocles Mavroeidis, Sam Wycherley
This paper studies a class of multivariate threshold autoregressive models, known as censored and kinked structural vector autoregressions (CKSVAR), which are notably able to accom…
Cointegration with Occasionally Binding Constraints
James A. Duffy, Sophocles Mavroeidis, Sam Wycherley
In the literature on nonlinear cointegration, a long-standing open problem relates to how a (nonlinear) vector autoregression, which provides a unified description of the short- an…
The Local to Unity Dynamic Tobit Model
Anna Bykhovskaya, James A. Duffy
This paper considers highly persistent time series that are subject to nonlinearities in the form of censoring or an occasionally binding constraint, such as are regularly encounte…
Cointegration without Unit Roots
James A. Duffy, Jerome R. Simons
It has been known since Elliott (1998) that standard methods of inference on cointegrating relationships break down entirely when autoregressive roots are near but not exactly equa…
Estimation and Inference in the Presence of Fractional d=1/2 and Weakly Nonstationary Processes
James A. Duffy, Ioannis Kasparis
We provide new limit theory for functionals of a general class of processes lying at the boundary between stationarity and nonstationarity -- what we term weakly nonstationary proc…
Asymptotic Theory for Kernel Estimators under Moderate Deviations from a Unit Root, with an Application to the Asymptotic Size of Nonparametric Tests
James A. Duffy
We provide new asymptotic theory for kernel density estimators, when these are applied to autoregressive processes exhibiting moderate deviations from a unit root. This fills a gap…
Generalized Indirect Inference for Discrete Choice Models
Marianne Bruins, James A. Duffy, Michael P. Keane +1
This paper develops and implements a practical simulation-based method for estimating dynamic discrete choice models. The method, which can accommodate lagged dependent variables,…
Uniform convergence rates over maximal domains in structural nonparametric cointegrating regression
James A. Duffy
This paper presents uniform convergence rates for kernel regression estimators, in the setting of a structural nonlinear cointegrating regression model. We generalise the existing…
A uniform law for convergence to the local times of linear fractional stable motions
James A. Duffy
We provide a uniform law for the weak convergence of additive functionals of partial sum processes to the local times of linear fractional stable motions, in a setting sufficiently…