NONSENSE REGRESSIONS BETWEEN INTEGRATED PROCESSES OF DIFFERENT ORDERS

Abstract Herein we develop an analytical study of the asymptotic distributions obtained when we run linear regressions in the levels of stochastically independent integrated time series when the orders of integration of the dependent and independent variables are different. These theoretical findings largely explain the Monte Carlo results recently reported in Banerjee et al. (1993).