This article was first published on VoxEU.org.
Developed countries differ markedly in a number of social and economic indicators. Wage inequality, labour productivity, school attainment, and employment rates are all higher in the US than in southern Europe (OECD 2013). The population of active firms differs too, with a larger number of small and less productive firms in the latter group (Bartelsman et al. 2009). While understanding these differences is important both from a positive and a normative standpoint, their origin remains largely an open question.
A multiple equilibria story
In a recent paper, we show that large differences in socioeconomic and labour market outcomes can emerge as alternative equilibria sustained by different – yet rational – beliefs on the role played by ability and effort in determining individual economic success (Bonfiglioli and Gancia 2014).
Our theory hinges on two key assumptions:
- Firms gain more from screening workers when ability is more dispersed.
- If workers put effort into improving ability, both its average and its dispersion in the population increase.
This introduces a complementarity between firms’ and workers’ strategies that can give rise to two equilibria. In the high-effort equilibrium, heterogeneity in ability is sufficiently large to induce firms to select the best workers. In turn, this confirms the initial belief that effort is important for finding good jobs. In the low-effort equilibrium, instead, ability is not sufficiently dispersed to justify screening, so the probability of finding jobs depends more on luck than on merit, thereby confirming the initial belief on the low value of effort.
Nested into the framework of Helpman et al. (2010) – where heterogeneous firms and workers interact in a labour market with matching frictions and imperfectly observable ability – this mechanism delivers interesting implications for labour market and firm-level outcomes. In particular, in the equilibrium with higher effort and screening, ability is higher and more dispersed, and firms are more productive and subject to more selection. Moreover, a stronger sorting pattern between firms and workers generates more inequality, both across firms (in terms of size) and workers (in terms of skill premium and residual wage inequality).
A preliminary look at the data suggests that our theory is consistent with several salient differences observed between countries such as the US and the largest southern European countries, Italy and Spain.
The divide in labour market and firm-level outcomes
Differences in terms of wage inequality are remarkable. In particular, the college premium relative to the earnings of workers with secondary education is around 1.8 in the US, compared to 1.5 in Italy and 1.4 in Spain (OECD 2013). Broader measures of wage inequality display similar patterns: as reported in Krueger et al. (2010), for instance, the total variance of the logarithm of U.S. wages is above 0.4 and around 0.2 in the other two countries.
Turning to firms, available data suggest US firms are on average bigger and more productive, and their size distribution is more dispersed than their European counterparts, with a 30% higher variance of log revenues. Interestingly, US markets are more selective, with a survival rate for new firms 10% lower than in Italy (Bartelsman et al. 2009). Finally, there is also evidence that American firms attach a higher value to selecting talent. An index capturing the importance of attracting and keeping talented people to the company, built by Bloom and Van Reenen (2010), ranks the US first out of 17 countries, and Italy last.
The cultural divide
Existing evidence suggests that Americans believe in individual merit, work ethic and competition more than Southern Europeans. For instance, according to the 1981-2000 World Values Survey, 26.4% of Americans strongly agree with the statement that “hard work brings success”, against a share of 14.6% in Italy and 12.2% in Spain. Those who instead strongly believe that success “is a matter of luck and connections” represent 2.3%, 8.9%, and 7.8% of respondents in the three countries respectively.
The human capital divide
The divide in beliefs comes together with significant differences in investment in education. For instance, in 2010 the working-age population with tertiary schooling was 42% in the US versus 15% in Italy and 32% in Spain (OECD 2013). Moreover, total expenditure on tertiary education as a percentage of GDP is 2.8%, 1% and 1.3% in the three countries, respectively. Regarding outcomes, US students outperform those from Italy and Spain in all major international comparisons, but also exhibit more dispersion in the results (see Brown et al. 2007).
To have a sense of the quantitative importance of the proposed mechanism, we take our model in the no-screening equilibrium and calibrate it so as to broadly match some key observations in Spain and Italy. We then ask how much of the gap relative to the US can be explained by a switch to the screening equilibrium. The answer is that equilibrium multiplicity alone can account for 15-20% of the differences in salient variables, such as the dispersion of wages and revenues and the unemployment rate. We view this as a remarkable result. Although differences in preferences, technology and institutions probably remain of paramount importance, the qualitative success and quantitative significance of the model’s predictions make us more confident that our theory may be capturing real world phenomena.
In addition to these positive implications, our model yields useful policy insights. It suggests that governments in countries like Italy and Spain could play an important role in transitioning the economy towards the high-effort equilibrium. To this end, it may be useful to adopt measures aimed at improving the process of acquisition and selection of human capital, but also to strengthen the social perception of the value of effort and meritocracy in such a way to coordinate workers and firms to the desirable equilibrium.
Bartelsman, E, J Haltiwanger, and S Scarpetta (2009), “Measuring and Analyzing Cross Country Differences in Firm Dynamics,” in Dunne, Jensen and Roberts (eds), Producer Dynamics: New Evidence from Micro Data, NBER/University of Chicago Press.
Bloom, N and J Van Reenen (2010), “Why Do Management Practices Differ across Firms and Countries?”, Journal of Economic Perspectives 24(1), 203-24.
Bonfiglioli, A and G Gancia (2014), “Heterogeneity, Selection and Labor Market Disparities,” CEPR Discussion Paper No. 9981.
Brown, G, J Micklewright, S V Schnepf, and R Waldmann (2007), “International surveys of educational achievement: how robust are the findings?”, Journal of the Royal Statistical Society Series A, 170(3), 623-646.
Helpman, E, O Itskhoki, and S J Redding (2010), “Inequality and Unemployment in a Global Economy,” Econometrica, 78(4), 1239-1283.
Krueger, D, F Perri, L Pistaferri, and G L Violante (2010), “Cross-sectional facts for macroeconomists,” Review of Economic Dynamics, 13, 1-14.
OECD (2010a), PISA 2009 at a Glance, OECD Publishing,
OECD (2013), Education at a Glance 2013: OECD Indicators, OECD Publishing,