Nonparametric inference on structural breaks

By Miguel A. Delgado, J. Hidalgo. 2000

75 citations recorded by the source corpus.

This paper proposes estimators of location and size of structural breaks in a, possibly dynamic, nonparametric regression model. The structural breaks can be located at given periods of time and/or they can be explained by the values taken by some regressor, as in threshold models. No previous knowledge of the underlying regression function is required. The paper also studies the case in which several regressors explain the breaks. We derive the rate of convergence and provide Central Limit Theorems for the estimators of the location(s) and size(s). A Monte Carlo experiment illustrates the performance of our estimators in small samples.

Subfields: Economics and Econometrics, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/b9f857abe361999c039157330e9ec07570212ac9

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Citations in the corpus

Adaptive Estimation of Autoregressive Models with Time-Varying Variances (2008, methodology): “The inconsistency of the error variance function estimator at points of discontinuities has a diminishing effect on the behavior of adaptive estimators of the autoregressive coefficients when the sample size is large, as is clear from (15).”
Robust inference for threshold regression models (2017, background): “Feder (1975), Chan and Tsay (1998), and Hansen (2017) considered the estimation of the model (11) along with an auxiliary condition of 30 6= 0 to ensure the identification of the change-point 0.”
A Smoothed Least Squares Estimator for Threshold Regression Models (2007, background): “The paper of Delgado and Hidalgo (2000) work with the more general case of multiple unknown threshold points in a nonparametric regression and obtain a full set of results for estimation and inference.”
Threshold Regression with Endogeneity (2017, unknown): “The threshold effect does not depend on x and x|q is uniformly distributed, and so the DKE of Delgado and Hidalgo (2000) can be applied.”
Nonparametric estimation of structural change points in volatility models for time series (2005, background): “2 Very recently, Perron (2001) extends Delgado and Hidalgo (2000)’s nonparametric procedure to detect discontinuities in conditional variance function and proposed an estimator of jumps in the volatility of 1nancial returns.”
Regression discontinuity designs with unknown discontinuity points: Testing and estimation (2015, methodology): “When k(0) = 0 (and k0(0) > 0), the convergence rate is p nh=h = n= p nh slower than n; see Müller (1992), Wu and Chu (1993), and Delgado and Hidalgo (2000) for the details.29 Loader (1996) puts forward a similar estimator as ours but he only considers the case with xed design and the error term…”
On the functional estimation of jump-diffusion models (2003, methodology): “…the existing theoretical treatments on the estimation of structural breaks in discretetime (c.f. Yin (1998), Müller (1992), Chu and Wu (1993), Delgado and Hidalgo (2000) and Perron (1999), inter alia) definition) for the consistency and weak convergence results in this paper to be valid.”
Testing for Threshold Effects in Regression Models (2010, background): “KEY WORDS: Davies problem; Empirical process; Maximum rank correlation estimation; Maximum score estimation; U-process.”