Estimating the LQAC model with I(2) variables

✍ Scribed by Tom Engsted; Niels Haldrup

• Publisher: John Wiley and Sons
• Year: 1999
• Tongue: English
• Weight: 171 KB
• Volume: 14
• Category: Article
• ISSN: 0883-7252
• DOI: 10.1002/(sici)1099-1255(199903/04)14:2<155::aid-jae497>3.0.co;2-#

✦ Synopsis

This paper derives a method for estimating and testing the Linear Quadratic Adjustment Cost (LQAC) model when the target variable and some of the forcing variables follow I(2) processes. Based on a forwardlooking error-correction formulation of the model it is shown how to obtain strongly consistent estimates of the structural parameters from both a linear and a non-linear cointegrating regression where ®rst-dierences of the I(2) variables are included as regressors (multicointegration). Further, based on the estimated parameter values, it is shown how to test and evaluate the LQAC model using a VAR approach. A simple easy interpretable metric for measuring the model ®t is suggested. In an empirical application using UK money demand data, the non-linear multicointegrating regression delivers an economically plausible estimate of the adjustment cost parameter. However, the restrictions implied by the exact LQAC model under rational expectations are strongly rejected and the metric for model ®t indicates a substantial noise component in the model.