Title: Estimating long run effects in models with cross sectional dependence
Authors: Jan Ditzen - Heriot-Watt University (United Kingdom) [presenting]
Abstract: It is shown how to estimate long run coefficients in a dynamic panel with heterogeneous coefficients and common factors and a large number of observations over cross-sectional units and time periods. The common factors cause cross-sectional dependence which is approximated by cross-sectional averages. Heterogeneity of the coefficients is accounted by taking the unweighted averages of the unit specific estimates. Three different models to estimate long run coefficients are considered, a simple dynamic model, an error correction model and an ARDL model. It is explained how to estimate all three models and estimation results are compared by simulation. Further emphasis is put on estimating the standard errors of the long run coefficients. Estimated standard errors obtained by the delta method and bootstrapped standard errors are compared.