Abstract
In this thesis, the economic effects of Covid-19 and the policy responses in Norway and Sweden are researched. Because Norway and Sweden chose quite different policy responses to prevent the spread of the pandemic, it is of interest to compare estimates of covid effects on the two countries’ GDP. Using a well-documented machine learning algorithm, I constructed multiple-equation aggregate models as well as final form equations for Mainland-Norway GDP and for Sweden. The models were simulated to define hypothetical counterfactual no-covid scenarios. The results indicate a statistically significant medium- to long-run covid effect on Mainland-Norway GDP. On the other hand, the results show no indication of a long-term effect on GDP in Sweden. Compared to pre-existing studies for Norway, the main impression is that the results are similar, but of slightly stronger magnitude. Both sample differences and differences in methodology can explain the differences. For Sweden, there have been surprisingly few studies of the numerical consequences of the pandemic (and the responses to it) on GDP. I found a stronger economic effect on GDP in Sweden than in the limitedly available comparable studies.