Wavelet analysis is a new mathematical tool developed as a unified field of science over the last decade. As spatially adaptive analytic tools, wavelets are useful for capturing serial correlation where the spectrum has peaks or kinks, as can arise from persistent/strong dependence, seasonality...

This paper studies the asymptotic properties of standard panel data estimators in a simple panel regression model with error component disturbances. Both the regressor and the remainder disturbance term are assumed to be autoregressive and possibly non-stationary. Asymptotic distributions are...

In this paper, we propose an estimation and testing framework for parameter instability in cointegrated panel regressions with common and idiosyncratic trends. We develop tests for structural change for the slope parameters under the null hypothesis of no structural break against the alternative...

This paper establishes that regressors in the models with censored dependent variables need not be bounded for the standard asymptotic results to apply. Thus regressors which grow monotonically with the observation index may be acceptable. It also purports to provide an upper bound on the rate...

This paper proposes a test for sphericity in a fixed effects panel data model. It uses the Random Matrix Theory based approach of Ledoit and Wolf (2002) to test for sphericity of the error terms in a fixed effects panel model with a large number of cross-sectional units and time series...