A New Quadratic Asymmetric Error Correction Model: Does Size Matter?

Abstract

We introduce a new quadratic error correction model that comprehensively accounts for both sign and size asymmetries. We also propose a test protocol that allows to rigorously identify the different sources of long-run nonlinearity, namely, quadratic nonlinearity, size asymmetry and sign asymmetry. We use a non-parametric residual recursive bootstrap technique to report p-values for the long-run tests. Although, our estimation of the Okun’s Law for the U.S confirms previous findings on the direction of the sign asymmetry, its reveals that the magnitude of the impact of economic downturns on unemployment decreases faster than the impact of upturns. Forecasting results show that our new QAECM performs better than NARDL.