By D. Thomakos
I was searching for data on globalization, to possibly connect them with inequality and government trust which we presented in this last post. Then I though, how about economic freedom and globalization? Is there a relationship between the two and if yes, what would this relationship look like? In this post I present some preliminary and interesting findings merging two datasets from completely different sources – and the results are mighty interesting. You can look at some of the possibly related literature in Google Scholar. Read on!
I gather data for a globalization index from the ETH Zurich KOF website and data for economic freedom from the Heritage Foundation. The data files I used and the associated Python file are, of course, available for your experimentations at my github repository. What I am after is the “causal” impact of either globalization or economic freedom into the other variable; a priori one would expect a very high temporal cross-correlation between these series but what is more interesting is to see which of the components of these two indices are mostly significant and mostly affected by one another. I will focus on the general globalization index and some of the components of the economic freedom index, but you can very easily run the Python file to see any combination of variables that you like.
The following two tables present the cross-country, cross-time, correlations for some components of the economic freedom index (Overall Score, Property Rights, Government Integrity, Government Spending, Tax Burden, Business Freedom and Financial Freedom) and the KOF General Index (KOFGI). In Table 1 we have these cross-correlations between the 2020 scores of KOFGI and 2000 and 2010 scores of the components of economic freedom (you can easily experiment with different years with the Python file!); in Table 2 we have the cross-correlations between the 2020 scores of the components of economic freedom and the 2000 and 2010 scores of KOFGI. This way we can see whether there are some changes in the “causal” patterns among the variables and understand which are significant drivers in their joint evolution.
| Economic Freedom Component |  KOFGI 2020, component 2000 | KOFGI 2020, component 2010 |
| Overall Score | 63% | 72% |
| Property Rights | 70% | 74% |
| Government Integrity | 71% | 75% |
| Government Spending | -51% | -30% |
| Tax Burden | -21% | -22% |
| Business Freedom | 61% | 65% |
| Financial Freedom | 55% | 70% |
| Economic Freedom Component | KOFGI 2000, component 2020 | KOFGI 2010, component 2020 |
| Overall Score | 69% | 74% |
| Property Rights | 75% | 79% |
| Government Integrity | 83% | 82% |
| Government Spending | -47% | -45% |
| Tax Burden | -43% | -33% |
| Business Freedom | 63% | 67% |
| Financial Freedom | 71% | 74% |
The results are very suggestive and conform to many stylized facts. Globalization is very highly correlated with economic freedom and that correlation has increased over the years – their correlation has considerable feedback as we can see from the overall score entries. When we look, at Table 1, on the causal impact of past economic freedom on globalization, we see that property rights and government integrity are the variables with the highest cross-time correlations, followed by the very considerable impact of financial freedom on globalization (not surprising this one, globalization was/is mostly about financial freedom!). The impact of government spending and taxation is negative on globalization, with the former having a much stronger effect than the latter.
Turning to Table 2, on the causal impact of past globalization on economic freedom, we see three significant differences: first, past globalization is very highly associated with government integrity with correlation of over 80%; second, past globalization has a higher negative impact on the tax burden and higher negative impact on government spending – compared the past impact of these variables on globalization. That is, as globalization increased it “pushed” for higher government integrity but also for lower government spending and lower taxation.
The above are only but a quick run through the data but the results are informative and with policy implications. Furthermore, one can easily associate these results with inequality and government trust from the previous post and look more carefully into the cross-section of countries involved in my computations. Well, get your hands on the data and the code and maybe you can find out more by additional analysis!
PROGNOSTIKON 