Session-specific features of a laboratory experiment, if those exist, do not disappear by clustering standard errors at the session level. Randomly ordering sessions, which is crucial to deal with sampling issues, cannot justify clustering the standard errors at the session level. The...

Session-specific features of a laboratory experiment, if those exist, do not disappear by clustering standard errors at the session level. Randomly ordering sessions, which is crucial to deal with sampling issues, cannot justify clustering the standard errors at the session level. The...

This paper develops asymptotic theory for estimated parameters in differentiated product demand systems with a fixed number of products, as the number of markets T increases, taking into account that the market shares are approximated by Monte Carlo integration. It is shown that the estimated...

This paper develops asymptotic theory for estimated parameters in differentiated product demand systems with a fixed number of products, as the number of markets T increases, taking into account that the market shares are approximated by Monte Carlo integration. It is shown that the estimated...

This paper develops asymptotic theory for differentiated product demand models with a large number of markets T. It takes into account that the predicted market shares are approximated by Monte Carlo integration with R draws and that the observed market shares are approximated from a sample of N...