Testing for Structural Change: Evaluation of the Current Methodologies, a Misspecification Testing Perspective and Applications
Abstract
The unit root revolution in time series modeling has created substantial interest in non-
stationarity and its implications for empirical modeling. Beyond the original interest in trend vs.
di¤erence non-stationarity, there has been renewed interest in testing and modeling structural
breaks. The focus of my dissertation is on testing for departures from stationarity in a broader
framework where unit root, mean trends and structural break non-stationarity constitute only
a small subset of the possible forms of non-stationarity. In the â ¦rst chapter the most popular
testing procedures for the assumption, in view of the fact that general forms of non-stationarity
render each observation unique, I develop a testing procedure using a resampling scheme which
is based on a Maximum Entropy replication algorithm. The proposed misspeciâ ¦cation testing
procedure relies on resampling techniques to enhance the informational content of the observed
data in an attempt to capture heterogeneity â locallyâ using rolling window estimators of the
primary moments of the stochastic process. This provides an e¤ective way to enhance the
sample information in order to assess the presence of departures from stationarity. Depending
on the sample size, the method utilizes overlapping or non-overlapping window estimates. The
e¤ectiveness of the testing procedure is assessed using extensive Monte Carlo simulations. The
use of rolling non-overlapping windows improves the method by improving both the size and
power of the test. In particular, the new test has empirical size very close to the nominal and
very high power for a variety of departures from stationarity. The proposed procedure is then
applied on seven macroeconomic series in the fourth chapter. Finally, the optimal choice of
orthogonal polynomials, for hypothesis testing, is investigated in the last chapter.
Collections
- Doctoral Dissertations [13032]