This paper considers issues related to estimation, inference and computation with multiple structural changes occurring at unknown dates in a system of equations. Changes can occur in the regression coefficients and/or the covariance matrix of the errors. We also allow arbitrary restrictions on these parameters, which permits the analysis of partial structural change models, common breaks occur...

We provide an approach to forecasting the long-run (unconditional) distribution of equity returns making optimal use of historical data in the presence of structural breaks. Our focus is on learning about breaks in real time and assessing their impact on out-of-sample density forecasts. Forecasts use a probabilityweighted average of submodels, each of which is estimated over a different history...

Abstract This paper examines long-range dependence in the inflation rates of G7 countries by estimating their (fractional) order integration d over sample period January 1973—March 2020. The results indicate that series are very persistent, estimated value being equal to or higher than 1 all cases. Possible non-linearities form Chebyshev polynomials time ruled out. Endogenous break tests then c...

Recent evidence suggests that ignoring structural breaks in volatility financial asset returns can result overestimation of spillover among markets. This paper examines major US equity sectors (i.e. Financial, Technology, Energy, Health, Consumer and Industrial) with bivariate GARCH models utilizing daily data from April 2006 to March 2021 after adjusting for breaks. I find significantly less b...