A general class of non-stationary time series is considered in this paper. We estimate the time-varying coefficients by using local linear M-estimation. For these estimators, weak Bahadur representations are obtained and used to construct simultaneous confidence bands. practical implementation, we propose a bootstrap based method circumvent slow logarithmic convergence theoretical Our results s...

Abstract Invariance under time translation (or stationarity) is probably one of the most important assumptions made when investigating electromagnetic phenomena. Breaking this assumption expected to open up novel possibilities and result in exceeding conventional limitations. However, explore field time-varying structures, we primarily need contemplate fundamental principles concepts from a non...

Abstract I propose to identify an SVAR, up shock ordering, using the autocovariance structure of squared innovations implied by arbitrary stochastic process for variances. These higher moments are available without parametric assumptions on variance process. In contrast, previous approaches exploiting heteroskedasticity rely path innovation covariances, which can only be recovered from data und...