We consider the problem of estimating and testing for multiple breaks in a single equation framework with regressors that are endogenous, i.e., correlated with the errors. We show that even in the presence of endogenous regressors, it is still preferable, in most cases, to simply estimate the break dates and test for structural change using the usual ordinary least-squares (OLS) framework. Except for some knife-edge cases, it delivers estimates of the break dates with higher precision and tests with higher power compared to those obtained using an IV method. Also, the OLS method avoids potential weak identi…cation problems caused by weak instruments. To illustrate the relevance of our theoretical results, we consider the stability of the New Keynesian hybrid Phillips curve. IV-based methods only provide weak evidence of instability. On the other hand, OLS-based ones strongly indicate a change in 1991:1 and that after this date the model loses all explanatory power. JEL Classi…cation Number: C22.

We investigate intra-safe haven currency behavior during the recent global financial crisis. The currencies we consider are the USD, the JPY, the CHF, the EUR, the GBP, the SEK, and the CAD. We first assess which safe haven currency appreciates the most as market uncertainty increases, i.e. we assess which safe haven currency is the "safest". We then use non-temporal threshold analysis to investigate whether intra-safe haven currency behavior changes, e.g. accelerates or decelerates, as market uncertainty increases. We find that the JPY is the "safest" of safe haven currencies and that only the JPY appreciates as market uncertainty increases regardless of the prevailing level of uncertainty. For all other currencies under study we find significant market uncertainty threshold effects. We extend our analysis to also consider intra-safe haven currency behavior before and after the global financial crisis. JEL codes: F31, G15

This paper proposes a new test for factor loading structural change in dynamic factor models. The proposed test is robust to the nonmonotonic power problem that occurs if the factor loadings exhibit structural changes at common dates over crosssections. To illustrate the usefulness of our test, we rst show that the leading test proposed by Breitung and Eickmeier (2011) exhibits nonmonotonic power, essentially because the breaks are considered as spurious factors with stable factor loadings. We use both local and non-local asymptotic frameworks to investigate the power of their test. The new test eliminates the e ects of the spurious factors by maximizing the test statistic over possible numbers of the original factors. This approach is e ective because the original factors are not identi ed under the alternative hypothesis. Monte Carlo simulations and an empirical example using U.S. Treasury yield curve data clearly illustrate the validity of the asymptotic power analysis and usefulness of the proposed test.JEL Classi cation Number: C12, C38

We provide a comprehensive treatment for the problem of testing jointly for structural changes in both the regression coefficients and the variance of the errors in a single equation system involving stationary regressors. Our framework is quite general in that we allow for general mixing‐type regressors and the assumptions on the errors are quite mild. Their distribution can be nonnormal and conditional heteroskedasticity is permitted. Extensions to the case with serially correlated errors are also treated. We provide the required tools to address the following testing problems, among others: (a) testing for given numbers of changes in regression coefficients and variance of the errors; (b) testing for some unknown number of changes within some prespecified maximum; (c) testing for changes in variance (regression coefficients) allowing for a given number of changes in the regression coefficients (variance); (d) a sequential procedure to estimate the number of changes present. These testing problems are important for practical applications as witnessed by interests in macroeconomics and finance where documenting structural changes in the variability of shocks to simple autoregressions or vector autoregressive models have been a concern.

This note provides a simple proof for the problem of estimating and testing for multiple breaks in a single equation framework with regressors that are endogenous. We show based on standard assumptions about the regressors, instruments and errors that the second stage regression of the instrumental variable (IV) procedure involves regressors and errors that satisfy all the assumptions in Perron and Qu (2006) so that the results about consistency, rate of convergence and limit distributions of the estimates of the break dates, as well as the limit distributions of the tests, are obtained as simple consequences. The results are obtained within a uni…ed framework for various cases about the nature of the reduced form: stable, no structural changes but time variations in the parameters, structural changes at dates that are common to those of the structural form, and structural changes occurring at arbitrary dates. JEL Classi…cation Number: C22.