The origins of cross-country differences in living standards have captured the attention of economists for years. Most researchers agree that at the centre of the variation in output per worker across countries are differences in productivity. Why do countries have different levels of productivity? Recent research suggests that differences in managerial practices play an important role in productivity differences across countries (Bloom and Van Reenen 2011, Bloom et al. 2015). In particular Bloom et al. (2015) find that about a quarter of cross-country differences in productivity can be attributed to differences in management practices, or ‘managerial quality’ for short. It is, however, an open question how to interpret differences in managerial quality across countries.
In a recent paper (Guner et al. 2015), we attempt to understand why managerial quality differs across countries in the first place. Understanding factors that determine managerial quality at the national level is of central importance for public policy, since quality of management is likely to be sensitive to government policies in regulation, taxation, and more broadly, in education.
Our starting point in understanding the sources of differences in managerial quality is to analyse lifetime earnings profiles of workers holding managerial and non-managerial occupations using large individual-level datasets for twenty developed countries. We compare the lifetime growth of managers’ earnings to the growth of non-managers’ earnings during prime working ages (between ages 25-29 to 50-54). The age-earnings profiles of managers relative to non-managers differ non-trivially across countries. In the US, the earnings of managers grow by about 75%, while the earnings growth for non-managers is about 40%. This gap is weaker in other countries in our sample. In Belgium, for instance, earnings growth of managers in prime working years is about 65%, whereas earnings growth of non-managers is similar to the US. At the other extreme, we find that in Spain the earnings of non-managers grow more than those of managers over the life-cycle. We then uncover a strong, positive relation between the relative steepness of age-earnings profiles and GDP per worker: managerial earnings grow faster than non-managerial earnings in countries with higher GDP per worker (Figure 1).
Figure 1. Cross-country relationship between output per worker and lifetime growth of managers’ earnings relative to non-managers
Managers differ across countries in their incentives to invest in skills
Why do managers in richer countries experience faster lifetime growth of earnings compared to non-managers? We argue in our paper that incentives to invest in skills play a crucial role. However, if the empirical relationship in Figure 1 points at cross-country differences in incentives, we could expect that a similar picture would hold for workers of non-managerial occupations in which investments in skills are equally important. There is no systematic relation, however, between GDP per worker and the relative earnings growth of professionals (lawyers, engineers, doctors etc.) versus workers, self-employed versus workers, or college-educated versus non-college educated. These results point to the central role of incentives faced by managers in explaining the empirical relationship in Figure 1.
In order to understand and draw implications from our empirical findings, we study a span-of-control model with a life-cycle structure. Every period, a large number of finitely lived agents are born. These agents are heterogeneous in terms of their initial endowment of managerial skills. The objective of each agent is to maximise the lifetime utility from consumption. In the first period of their lives, agents make an irreversible decision to be either workers or managers. In the model economy, differences in managerial quality emerge from differences in selection into management work, along the lines of Lucas (1978), and differences in skill investments, as we allow for managerial abilities to change over time as managers invest in their skills. Hence, we place incentives of managers to invest in their skills and the resulting endogenous skill distribution of managers at the centre of income and productivity differences across countries.
In the model economy, skill investment decisions reflect the costs (resources that have to be invested rather than being consumed) and the benefits (the future rewards associated with being endowed with better managerial skills). Since consumption goods are an input for skill investments, a lower level of aggregate productivity results in lower incentives for managers to invest in their skills. Furthermore, managers face potential size-dependent distortions as in the literature on misallocation in economic development. We model size-dependent distortions as progressive taxes on the output of a plant, and do so via a simple parametric function that was proposed originally by Benabou (2002).
Size-dependent distortions have two effects in our setup.
- First, a standard reallocation effect, as the introduction of distortions implies that capital and labour services flow from distorted (large) to undistorted (small) production units;
- Second, a skill accumulation effect, as distortions affect the incentives for skill accumulation and thus, the overall distribution of managerial skills – which manifests itself in the distribution of plant level productivity.
Overall, under higher exogenous productivity and smaller distortions, managers invest more in their skills in equilibrium and operate larger and more productive plants. As a result, both output per worker and the gap between the earnings of managers to non-managers become larger, in line with the cross-country evidence presented in Figure 1.
Cross-country income differences and the earnings growth of managers relative to non-managers
We use our model to assess the combined effects of distortions and exogenous variation in economy-wide productivity. For these purposes, we force the model economy to reproduce jointly the level of output per worker in each country and the earnings growth of managers relative to non-managers. We do so by choosing economy-wide productivity levels and the level of size dependency of distortions in each country to hit these two observations. We find that distortions are critical in generating relative earnings growth across countries. As a result, observations on relative earnings growth provide us with natural targets to discipline the extent of distortions.
Once we are able to reproduce both the level of GDP per worker and the relative earnings growth of managers within our model, we can assess the contribution of economy-wide productivity and distortions to cross-country differences in output per worker. To this end, we first allow economy-wide productivity to differ across countries and shut down the distortion channel, and then do the reverse (i.e. we allow distortions to vary and shut down differences in economy-wide productivity). The level of distortions that reproduce the relative earnings growth of managers in Italy, for example, where the relative earnings growth of managers is about half of what we observe in the US, are able to generate about 40% of the observed output gap with the US. Looking at all the countries in our sample, we find that distortions alone account for about 42% of variation in GDP per worker gap with the US across countries, while the rest of the variation is accounted for by differences in exogenous economy-wide productivity and interaction effects.
As a by-product of our model, we can also quantify the importance of the novel channel emphasised in the paper – managerial skill investments – for a host of variables of interest in response to the introduction of size-dependent distortions. We ask: How large is the amplification role of such investments? We find that managerial skill formation accounts for about one-quarter of changes in output when size-dependent distortions are introduced. Our model also predicts that managerial investments account for all changes in relative earnings growth over the life cycle associated to size-dependent distortions. Overall, this is key finding, for investments in skill formation are relatively small (less than 1% of output) in the benchmark economy.
To conclude, we contend that in order to understand why countries like Italy and others lag behind the US in terms of output per worker, we should take into account that in the US, the incentives to invest in managerial skills are not as distorted. A young person who contemplates a managerial career takes into account distortions (regulations and other factors that act as implicit size-dependent taxes) that he or she will face when earning a higher compensation as a manager. In economies with larger distortions, individuals will either invest less in their managerial skills or choose a non-managerial career. In equilibrium, these reactions lead to lower managerial quality and output per worker, and to lower earnings growth of managers relative to non-managers, as the data indicates.
Benabou, R (2002), “Tax and Education Policy in a Heterogeneous-Agent Economy: What Levels of Redistribution Maximize Growth and Efficiency?”, Econometrica 70(2): 481-517.
Bloom, N and J V Reenen (2011), “Human Resource Management and Productivity” in D Card and O Ashenfelter (eds.), Handbook of Labor Economics, Amsterdam: Elsevier.
Bloom, N, R Sadun and J V Reenen (2015), “Management as a Technology”, Working Paper.
Guner, N, A Parkhomenko and G Ventura (2015), “Managers and Productivity Differences”, CEPR Discussion Paper 11012.
Lucas, Jr., R E (1978), “On the Size Distribution of Business Firms”, Bell Journal of Economics 9(2): 508-523.