Alternative Estimators of Cointegrating Parameters in Models With Non-Stationary Data: An Application to US Export Demand Export

@article{citeulike:6044844, abstract = {This paper presents Monte Carlo simulations which compare the empirical performance of two alternative single equation estimators of the equilibrium parameters in a dynamic relationship. The estimators considered are Stock and Watson's dynamic ordinary least squares (DOLS) estimator and Bewley's transformation of the general autoregressive distributed lag model. The results indicate that the Bewley transformation produces a lower mean-square error as well as superior serial correlation properties even with lower truncation lags for the lagged variables included in the estimation equation. An application is then provided which examines the nature of the equilibrium relationship between aggregate US exports, world trade and the US real exchange rate. This confirms that estimation of the equilibrium parameters of this relationship by the Bewley transformation produces results which are superior to estimation by DOLS.}, author = {Forest, James J. and Turner, Paul}, citeulike-article-id = {6044844}, citeulike-linkout-0 = {http://ssrn.com/abstract=1443102}, citeulike-linkout-1 = {http://papers.ssrn.com/sol3/Delivery.cfm/SSRN_ID1443102_code1304683.pdf?abstractid=1443102&mirid=1}, day = {08}, journal = {Social Science Research Network Working Paper Series}, keywords = {bewley, demand, dols, estimator, export, transformation, us}, month = {August}, posted-at = {2009-10-30 21:00:29}, priority = {0}, publisher = {SSRN}, title = {Alternative Estimators of Cointegrating Parameters in Models With Non-Stationary Data: An Application to US Export Demand}, url = {http://ssrn.com/abstract=1443102}, year = {2009} }

TY - JOUR ID - citeulike:6044844 L3 - citeulike-article-id:6044844 N2 - This paper presents Monte Carlo simulations which compare the empirical performance of two alternative single equation estimators of the equilibrium parameters in a dynamic relationship. The estimators considered are Stock and Watson’s dynamic ordinary least squares (DOLS) estimator and Bewley’s transformation of the general autoregressive distributed lag model. The results indicate that the Bewley transformation produces a lower mean-square error as well as superior serial correlation properties even with lower truncation lags for the lagged variables included in the estimation equation. An application is then provided which examines the nature of the equilibrium relationship between aggregate US exports, world trade and the US real exchange rate. This confirms that estimation of the equilibrium parameters of this relationship by the Bewley transformation produces results which are superior to estimation by DOLS. JF - Social Science Research Network Working Paper Series TI - Alternative Estimators of Cointegrating Parameters in Models With Non-Stationary Data: An Application to US Export Demand PB - SSRN KW - bewley KW - demand KW - dols KW - estimator KW - export KW - transformation KW - us AU - Forest, James AU - Turner, Paul PY - 2009/August/08/ UR - http://ssrn.com/abstract=1443102 ER -