Fixed effects (FE) in panel data models overlap each other and prohibit the identification of the impact of "constant" regressors. Think of regressors that are constant across countries in a country-time panel with time FE. The traditional approach is to drop some FE and constant regressors by normalizing their impact to zero. We introduce "untangling normalization", meaning that we orthogonalize the FE and, if present, the constant regressors. The untangled FE are much easier to interpret. Moreover, the impact of constant regressors can now be estimated, and the untangled FE indicate to what extent the estimates reflect the true value. Our untangled estimates are a linear transformation of the traditional, zero-normalized estimates; no new estimation is needed. We apply the approach to a gravity model for OECD countries' exports to the US. The constant regressors US GDP, world GDP and the US effective exchange rate explain 90% of the time FE, making the latter redundant, so the estimated impacts indeed reflect the true value.

I develop an index for economic integration accounting for its gradual and bilateral nature: the Gradual And Bilateral Integration (GABI) index. The graduality captures differences in the depth and path of five stages in economic integration and is an improvement over the use of binary dummy variables. Its bilateral nature allows for country-pair differences, which is not possible with the multilateral indexes in existing literature. I apply the GABI index to a gravity model for 18 OECD countries and estimate the impact of the five stages on export. The estimates for these five stages allow me to investigate four different Brexit scenarios in a general equilibrium analysis, ranging from soft to very hard Brexit. I find that in the latter scenario real export of the UK decreases by a significant 32% in the long run. Other EU countries also experience a decrease in real export, while non-EU countries experience an increase due to trade diversion effects. Similarly, I also investigate potential future free trade agreements like TTIP.

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Fixed effects (FE) in panel data models overlap each other and prohibit the identification of the impact of "constant" regressors. Think of regressors that are constant across countries in a country-time panel with time FE. The traditional approach is to drop some FE and constant regressors by normalizing their impact to zero. We introduce "untangling normalization", meaning that we orthogonalize the FE and, if present, the constant regressors. The untangled FE are much easier to interpret. Moreover, the impact of constant regressors can now be estimated, and the untangled FE indicate to what extent the estimates reflect the true value. Our untangled estimates are a linear transformation of the traditional, zero-normalized estimates; no new estimation is needed. We apply the approach to a gravity model for OECD countries' exports to the US. The constant regressors US GDP, world GDP and the US effective exchange rate explain 90% of the time FE, making the latter redundant, so the estimated impacts indeed reflect the true value.