Within this literature has there been any shift in the models that are used as a result of the proliferation of "big data". For example many of the variables in the model are aggregate measurements such as aggregate consumption/investment/capital stock etc, however it might be possible to measure and compute these models at a smaller level of detail (for example at the state, city, or household). Do you think an added level of granularity would increase the explanatory power of the model?
Within this literature has there been any shift in the models that are used as a result of the proliferation of "big data". For example many of the variables in the model are aggregate measurements such as aggregate consumption/investment/capital stock etc, however it might be possible to measure and compute these models at a smaller level of detail (for example at the state, city, or household). Do you think an added level of granularity would increase the explanatory power of the model?