Large scope to boost productivity through a better allocation of talent

By Müge Adalet McGowan and Dan Andrews.

Raising productivity growth is highly dependent on a country’s ability to innovate and adopt technologies, which requires an effective supply of human capital. While increases in the stock of highly educated workers have significantly boosted labour productivity over the past 50 years, the rate of increase in the stock of human capital is projected to slow (Braconier et al., 2014). In this context, the ability of economies to efficiently deploy their existing stock of human capital will become increasingly important. However, some countries are more effective at channelling skills to productive uses than others, and these differences can be partly explained by public policies.

Skill mismatch and labour productivity

The efficiency of human capital allocation in OECD countries can be proxied by indicators of skill mismatch, which combine information on self-reported skill mismatch and quantitative information on skill proficiency from the 2012 Survey of Adult Skills (PIAAC) (Quintini, 2014). While the effect of mismatch on individual labour market outcomes is well understood, the potential gains to aggregate productivity from improving the efficiency of human capital allocation is unclear. A recent OECD study uses mismatch indicators and firm-level data to better understand the sources of cross-country differences in living standards by directly linking mismatch with labour productivity. A key finding to emerge is that high rates of skill mismatch – particularly over-skilling – tends to lower aggregate productivity by constraining the growth of innovative firms.

On average across countries, roughly one-quarter of workers report a mismatch between their existing skills and those required for their job – i.e. they are either over or under-skilled – but this figure is closer to one-third in Italy, Spain and the Czech Republic (Figure 1). Over-skilling is generally more common than under-skilling, with the average likelihood of being over-skilled roughly two and a half times greater than that of being under-skilled.

Blog13.1Link: Adalet McGowan, M and D. Andrews (2015), “Labour market mismatch and labour productivity: Evidence from PIAAC data”, OECD Economics Department Working Paper, No. 1209.

Using an industry-level analysis, Adalet McGowan and Andrews (2015) shows that higher skill mismatch is associated with lower labour productivity performance, with over-skilling being particularly costly. The negative association between over-skilling and labour productivity is driven through the channel of a less efficient resource allocation. From the perspective of any given firm, hiring an over-skilled worker may be beneficial for productivity, assuming there are no adverse effects on job satisfaction and the higher wages do not more than offset any associated productivity gains. From the perspective of the economy as a whole, however, the impacts may be very different. Assuming that wages do not adjust to these frictions in the short-run, mismatch could have reallocation effects, if skilled labour is clogged up in low productivity firms. In this case, the more productive firms remain smaller than otherwise, lowering aggregate productivity relative to a situation where workers are reallocated to achieve a more efficient match.

Indeed, the OECD study finds that in industries with a higher share of over-skilled workers, the more productive firms find it more difficult to attract suitable labour, in order to expand their operations. At the same time, skill mismatch has the potential to explain a non-trivial share of cross-country labour productivity gaps. For example, Italy – a country with high skill mismatch and low allocative efficiency – could boost its level of labour productivity by around 10% and potentially close one-fifth of its gap in allocative efficiency with the United States if it were to reduce its level of mismatch within each industry to that corresponding to the OECD best practice (Figure 1).

The role of public policy

While education policies clearly matter, these links between mismatch and productivity through the reallocation channel suggest that a wider range of policies could affect mismatch. An accompanying paper using micro-data from the 2012 Survey of Adult Skills (PIAAC) shows that differences in skill mismatch across countries are related to differences in public policies. Well-designed product and labour markets and bankruptcy laws that do not overly penalise business failure are associated with lower skill mismatch (Figure 2). For example, reducing the cost of closing a business (a measure of the stringency of bankruptcy law) from its most restrictive level to the median level is associated with a 3.6 percentage point implied gain to labour productivity. Skill mismatch is also lower in countries with housing policies that do not impede residential mobility (e.g. transaction costs on buying property and stringent planning regulations). Greater flexibility in wage negotiations and higher participation in lifelong learning as well higher managerial quality are also associated with a better matching of skills to jobs.

Blog13.2Link: Adalet McGowan, M and D. Andrews (2015), “Skill mismatch and public policy in OECD countries”, OECD Economics Department Working Paper, No. 1210.

This analysis adds further weight to the idea that policymakers should not only be concerned with increasing the stock of human capital, but also with allocating the existing stock of human capital more efficiently. Reducing mismatch may be beneficial to growth in the short-to-medium term to the extent that the benefits of human capital-augmenting policies take a long time to be realised, while it may also enhance the ‘bang-for-the-buck’ – i.e. the productivity impacts – of such policies in the longer run.

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