proxied by an estimate of technical efficiency, based on stochastic frontier analysis (SFA). The structural reform indicators are selected and interpreted based on the 12-pillar classification developed for the Global Competitiveness Index (WEF 2018).

Institutions and better-functioning domestic product markets are a key structural determinant of growth. Perception of the quality of government services and policies significantly affects economic growth, mainly through the capital and productivity channels, probably through their impact on investment decisions and reduction of operating costs. Lower taxes and higher regulatory quality contribute to higher growth. The effect of such structural reforms would be transmitted through all three input channels, hence spurring the use of labor and capital and thus promoting productivity.

Better educational attainments, which contribute to higher quality of human capital, are associated with both higher employment and productivity, hence higher economic growth. The results show that an increase in the level of educational attainments affects both the use of labor and the efficiency channel, and the result is robust across alternative model specifications.

Growth is positively affected by how well-developed a country’s financial systems are and by its innovation capability. The higher the share of domestic credit to the private sector as a percent of GDP, the deeper and more efficient its use of capital. Availability of the latest technologies improves the use of both labor and capital inputs.

Changes in labor market regulation may have ambiguous effects. A reduction of the extent to which working time conditions are regulated seems to increase overall productivity, hence spurring growth. The result is weak for the other two input channels, most importantly for labor. The weakness of the result may however reflect also the inability of the model and/or indicators to properly capture the impact of labor market reforms.

Trade liberalization does not have a straightforward relationship with growth. Once institutions are controlled for, the net effect of greater trade openness, proxied by a decrease in tariffs, customs border procedures, or other nontariff trade barriers, depends on the relative strength of the impact that different degrees of protection have on both capital accumulation and productivity.

Other factors, including infrastructure and use of information and communications technology (ICT), also matter for growth. For example, the higher the number of Internet users, the higher the growth, although the effect is relatively small. The results are stronger when the sample is enlarged.

If Serbia were to close the gap with Germany, reforms would add significant contribution to Serbia’s potential growth. It is possible to quantify the likely effect of structural reforms on Serbia’s economic growth—assuming that, following the reforms, the country’s main structural variables would over a certain time horizon converge to the value for Germany. Keeping in mind the underlying linearity assumption of the model, more than at providing a precise estimate, the simulations aim at quantifying the relative importance of each reform. In particular, enhancing government effectiveness, regulatory quality, human capital and financial development may contribute the most to economic growth. EU accession would also add to economic growth, mainly by boosting capital deepening.

Pro-competition reforms may have less impact on real GDP growth if they occur during economic slowdowns. In assessing the impact of structural reforms, the potential endogeneity to the economic environment should be considered. This makes it possible to disentangle the effects of a reform carried out on the verge of a cyclical economic upswing (downswing) from those of the upswing (downswing) itself. The issue is important because often implementation gaps, perhaps because of bad timing, make 3