# **B. Comparative Country Analysis of Automotive Exports**

44. In this second part of the analysis, we carry out an analysis of South African automotive exports versus comparator countries that produce and export vehicles and components. As a first step, we compare South Africa with a sample of five African countries including Morocco, Tunisia, Egypt, Kenya and Zimbabwe. In a second step, we aim at expanding the sample size by considering as comparator countries other main global producers and exporters of vehicles and components. To design this latter sample of countries, we choose among world automotive producer and exporter countries which are classified, just as South Africa, by the World Bank as “middle-income economies”. This comprises two sub-set of countries: (i) a group classified as “lower-middle-income economies” (Ecuador, Egypt, Indonesia, Morocco, Philippines, Tunisia and Vietnam), with an annual GDP per capita in the range of $996-$3945; and (ii) an “upper-middle-income economies” group (Colombia, Malaysia, South Africa, Turkey and Venezuela), with an annual GDP per capita in the range of $3,946-$12,195.

45. We place a caveat on the selection of comparator countries. Ideally, we would like to find treatment (i.e. South Africa) and control groups (i.e. comparator countries) which are similar in every way except for receiving the treatment. Our group of comparators is not necessarily from a homogeneous geographic region, nor do they necessarily share comparable economic fundamentals or policy frameworks. We have however taken this into account by introducing additional control variables and by stress-testing the results obtained applying a number of robustness checks, including significant modifications in the composition of the sample countries.

46. A challenge in our study is that very few African nations produce and export autos, particularly in Sub-Saharan Africa. Outside the African continent, we have aimed at finding comparator based on three main considerations about the countries: (i) they are middle income economies producing and exporting autos; (ii) they are going (or have gone) through economic transformation away from agriculture and towards industry and services; and (iii) they have practiced some sort of industrial policy affecting the automotive sector.

47. As in the previous analysis, the D-in-D methodology also requires that the treatment and control group show similar trends prior to the treatment (i.e. the MIDP launch). This is true in both of the samples considered, as illustrated in Figures 5 and 6 in the previous section, where comparable trends in automotive exports before 1995 in all sample countries can be seen.

48. As noted, in a first step we proceed with a panel database of 6 African countries spanning 1993-2007. In a second step, we have increased the sample size by considering other middle income countries around the world that are automotive producers and exporters. Below, we describe in detail the methodology that has been applied in both analyses, as well as the results obtained.

49. The dependent variable is the natural logarithm of automotive exports (US$ real), obtained from UNComtrade. As in the section above, we start with a simple difference-in-difference (D-in D) approach where outcomes are observed for two groups (South Africa, as the treatment group, and all other countries that are automobile producers and exporters, as the control group) and two periods (before 19