The faculty of regional development

The first universities were established in the medieval age, connected to the Catholic church and educating only a small handful. A millennium later, and universities have expanded in number, scope and scale: tens of thousands of institutions of higher education exist around the world, with hundreds of millions of students studying fields ranging from the classical (theology, law) to modern sciences and technology.

Despite the explosion in higher education since World War II, the contribution of universities to economic development remains somewhat unclear. Yes, education matters for growth, and university graduates typically have greater earnings potential than non-graduates. But universities as a specific motor for economic growth is, to a large extent, more posited than proven. Valero and Van Reenen attempt to close this gap using data on almost 15,000 universities across 78 countries.

Looking for effects. Source: US National Archives / Wikimedia Commons.

The focus of Valero and Van Reenen’s analysis is on regional effects: what a university means for development in the area around it. The reader may wonder what constitutes a ‘region’; the paper considers regions in line with work by Gennaioli et al. (2014). Given the differences in the organisational structure of countries, regions take the form of states and provinces, or statistical units such as the Nomenclature of Territorial Units for Statistics (NUTS) applied by Eurostat.

A positive association

Valero and Van Reenen’s headline finding is that there is indeed a relationship between universities and regional growth. Their ordinary least squares (OLS) results show a positive correlation between new universities and growth rates after five years. The effect of the number of universities also holds when controlling for population size and population growth rates (noting that one would expect areas with larger populations to have more educational institutions). Additional robustness checks, including tests for the quality of universities, reinforce the overall story.

The effect of universities on regional growth (1960–2010)

Dependent variable:
Regional growth of GDP per capita
(1)(2)(3)(4)(5)(6)(7)(8)(9)
Lagged growth in number of universities0.047⁎⁎⁎
(0.010)
0.036⁎⁎⁎
(0.010)
0.040⁎⁎⁎
(0.011)
0.046⁎⁎⁎
(0.011)
0.044⁎⁎⁎
(0.010)
0.045⁎⁎⁎
(0.011)
0.047⁎⁎⁎
(0.011)
0.047⁎⁎⁎
(0.016)
0.023⁎⁎
(0.010)
Lagged level of regional GDP per capita−0.015⁎⁎⁎
(0.001)
−0.013⁎⁎⁎
(0.001)
−0.058⁎⁎⁎
(0.003)
−0.078⁎⁎⁎
(0.005)
−0.078⁎⁎⁎
(0.007)
−0.077⁎⁎⁎
(0.005)
Lagged level of country GDP per capita−0.021⁎⁎⁎
(0.004)
0.038⁎⁎⁎
(0.006)
0.038⁎⁎
(0.018)
Lagged level of population /1000.178⁎⁎⁎
(0.032)
−0.030
(0.035)
−0.076
(0.040)
−0.086⁎⁎
(0.039)
−1.095⁎⁎⁎
(0.333)
−0.850⁎⁎
(0.352)
−0.850
(0.720)
−1.724⁎⁎⁎
(0.476)
Lagged growth in population−0.099⁎⁎
(0.038)
−0.113⁎⁎⁎
(0.039)
−0.209⁎⁎⁎
(0.045)
−0.183⁎⁎⁎
(0.045)
−0.183⁎⁎⁎
(0.068)
−0.182⁎⁎⁎
(0.050)
Dummy for capital in region0.012⁎⁎⁎
(0.002)
0.011⁎⁎⁎
(0.002)
Observations812881288128812881288128812881288128
Number of clusters1498149814981498149814981498781498
Clustering byRegionRegionRegionRegionRegionRegionRegionCountryRegion
Year dummiesNoNoYesYesYesYesYesYesYes
Country dummiesNoNoYesYesYesYesYesYesYes
Region controlsNoNoNoYesYesYesYesYesYes
Region trendsNoNoNoNoNoYesYesYesYes
Country by year dummiesNoNoNoNoNoNoNoNoYes
Notes. ⁎⁎⁎ indicates significance at the 1% level, ⁎⁎ at the 5% level and * at the 10% level. OLS estimates, 78 countries. Column (1) is a simple correlation between regional GDP per capita growth and the lagged growth in university numbers. Column (2) controls for the lagged log of population. Column (3) includes country and year dummies. Column (4) controls for lagged regional GDP per capita, the lagged growth in population, the lagged log population level, a dummy for whether the region contains a capital city, together with latitude, inverse distance to ocean, malaria ecology, log(oil and gas production) 1950–2010 (not reported here). Column (5) adds lagged country GDP per capita. Column (6) includes regional fixed effects, and the time varying controls of column (4). Column (7) adds lagged country GDP per capita. Standard errors are clustered at the regional level except in column (8) where they are clustered at the country level. Levels of GDP per capita and population are in natural logs.
Source: Table 3, Valero and Van Reenen 2019.

In broad terms, Valero and Van Reenen find that a 10 per cent increase in the number of universities in a given region is on average associated with 0.4 per cent higher GDP per capita. However, this likely underestimates the true effect, as universities have benefits beyond their home regions. The authors provide additional results testing neighbouring-region effects, which are suggestive of spillovers that are spatially correlated — that is, the closer you are to a university, the greater its effect.

The results above are correlations only, and thus cannot say anything specifically about the effect caused by universities. One could, for example, imagine that regions with greater future growth prospects are likely to attract new universities. The lagged effects partly address this problem, and the authors discuss the effect of different lags. However, they discount the explanatory power from tests of longer periods, given that with longer windows of time, there are simply a greater number of other factors which can enter the picture and influence the measured growth outcome.

Different drivers

Establishing a causal effect of universities on growth is complicated. A central challenge is that there are multiple channels by which one might expect higher education to influence development — what effect one finds (or not) depends on what one is looking for.

The most direct effect — and arguably the principal reason for investing in universities today — relates to increasing workforce skills. This human capital effect implies an increase in output for a given quantity of labour. A related but more indirect effect is that higher education fosters innovation by increasing the capacity to generate new ideas and knowledge, giving rise to technical advances that boost output for a given level of inputs.

Education also matters for society as a whole. As such, the role of universities as supporting architecture for institutions and democracy may also have measurable consequences. To the extent higher education facilitates better economic and political institutions (as well as confidence in those institutions), this should in turn enhance growth potential.

Lastly, universities may act as a magnet for local economic activity, by drawing in a population of workers and students, which in turn increase aggregate demand in the immediate area. In this story, universities — on par with other large institutions or major employers — are associated with increased consumption of goods and services.

Four mechanisms

Human capital

Increased investment in skills

Higher labour productivity (output per worker)

Innovation

Increased capacity for new ideas and knowledge

New products, techniques and markets

Institutions and democracy

Improved state capacity and trust

Greater stability and economic confidence

Demand

More people and resources flow to region

Increased demand for goods and services

Valero and Van Reenen examine the first two of these channels using different additions to their baseline specifications. For human capital, the authors consider changes in graduates’ share of the regional population. For innovation, the authors use data on growth in the total number of patents granted. In both cases, however, the authors rely on an OLS specification — and while both human capital and innovation as measured are associated with higher growth, the results do not measure the causal effect of universities through each of these channels.

The authors’ discussion of the remaining two channels is somewhat more qualitative. With respect to institutions and democracy, Valero and Van Reenen show that regions with universities exhibit higher approval for democracy in surveys. However, this of itself does not provide evidence of an effect on growth: the authors suggest any such effect is likely to accrue over the very long term — likely with spillovers to neighbouring regions.

Finally, while the authors cannot exclude a demand effect (the fourth channel), they regard it as unlikely that this alone explains the positive association between universities and growth. One reason for this is that in many cases, universities are primarily funded within the regions that establish them — thus, the universities would not represent a demand shock, but merely a reallocation of regional resources. However, to the extent that external resources are drawn to the region in connection with a new university, the principal effect of this should be observed at the time the university is established (for example, through construction activity or the migration of staff and the initial student pool to the area). That is, it would point to a contemporaneous boost to growth rather than any lagged effect. The authors’ results do not support this story.

Ready to contribute to regional growth. Source: This is Edinburgh / Wikimedia Commons.

Critical thinking

Valero and Van Reenen acknowledge the limitations of their data and their analysis, and specifically note that their results should not be interpreted as causal. Nevertheless, they conclude that their results are consistent with a positive effect of universities on growth. The authors’ discussion of the possible causal channels is in any event interesting, and provides a useful framework for future research.

The analysis considers universities in their contemporary (post-war) context — a component of the wider mass education system, at least in the developed world. In a historical context, any causal effects from universities might look quite different. For example, research by Cantoni and Yuchtman (2014) on medieval universities highlights the role played by the institutions channel, with higher education facilitating well-functioning markets and the rule of law.

Furthermore, differences in the content of university education might result in different patterns of economic activity. It was first in the nineteenth century that the natural sciences began to take hold in academia, leading to engineering programmes at polytechnic institutes and universities. This in turn provided a suite of relevant skills during industrialisation. Those universities with a greater focus on the classical fields of law and theology might not have had the same effect on economic development as those with a strong grounding in science.

Valero and Van Reenen offer a welcome ‘big picture’ view of the effects of higher education. And their focus on regional effects is well-placed, with decentralisation of educational institutes a live political issue in many countries. In that context, the authors’ call for further research on the contribution of universities to development should be heeded. Quantification of the causal effects, while challenging, would provide a more credible evidence base for policymakers and better inform public debates around the role of universities in a modern society.

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