NONSENSE REGRESSIONS BETWEEN INTEGRATED PROCESSES OF DIFFERENT ORDERS
- 1 August 1996
- journal article
- Published by Wiley in Oxford Bulletin of Economics and Statistics
- Vol. 58 (3) , 525-536
- https://doi.org/10.1111/j.1468-0084.1996.mp58003006.x
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).Keywords
This publication has 12 references indexed in Scilit:
- Understanding spurious regressions in econometricsPublished by Elsevier ,2002
- Correlation theory of spuriously related higher order integrated processesEconomics Letters, 1996
- SPURIOUS REGRESSIONS BETWEEN I(d) PROCESSESJournal of Time Series Analysis, 1995
- The asymptotics of single-equation cointegration regressions with I(1) and I(2) variablesJournal of Econometrics, 1994
- Limiting Distributions of Least Squares Estimates of Unstable Autoregressive ProcessesThe Annals of Statistics, 1988
- Do we reject too often?: Small sample properties of tests of rational expectations modelsEconomics Letters, 1986
- Do We Reject Too Often? Small Sample Properties of Tests of Rational Expectations ModelsPublished by National Bureau of Economic Research ,1985
- Trends, random walks, and tests of the permanent income hypothesisJournal of Monetary Economics, 1985
- Trends and random walks in macroeconmic time seriesJournal of Monetary Economics, 1982
- Spurious regressions in econometricsJournal of Econometrics, 1974