Abstract
Has the Portuguese economy benefited from tertiarization in terms of aggregate productivity performance? Did human capital availability play a role in this expansion of the services sector? To answer these two research questions, we investigate the existence of causality among services sector expansion, human capital, and aggregate productivity for the period 1970–2006 in the Portuguese economy based on the estimation of VAR models and impulse response analysis. We distinguish between the contributions of five different services sub-sectors that can be broadly classified as either traditional personal services or modern progressive services. The evidence suggests bi-directional causality between services sub-sectors employment shares and aggregate productivity. Across services sub-sectors, community social and personal services, that include health care and education activities, seem to be the most influential sector, followed by finance, insurance, real estate and business services, making both a positive and lasting contribution to aggregate productivity. Although only indicative, this evidence points to the relatively low weight of modern progressive services sectors in Portugal, together with a relatively less important role for some traditional personal services sub-sectors that can be sources of human capital, as candidate explanations for the slowdown in aggregate productivity growth over the period under analysis. The causality analysis did not allow us to confirm the role of human capital in driving the expansion of services subsectors, although the impulse response analysis points to a positive impact on aggregate productivity and the expansion of finance, insurance, real estate and business services and community social and personal services.
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Notes
Deindustrialization has occurred in both high and low income countries, as documented by Ghani and O'Connell (2014) for a sample of 100 countries over the period 1990–2012. According to the authors, manufacturing industry has been losing its relative importance in terms of its contribution to GDP in all the countries in the sample. The only exception is China, where the relative importance of manufacturing increased.
In a recent study, Franck and Galor (2017) even suggest that intensive industrialization can have an adverse effect on income per capita levels when it is associated with underinvestment in human capital and lower employment in skilled-intensive activities. According to the authors, it was not the adoption of more productive technology in manufacturing that was the main source of prosperity in todays advanced countries but its association with higher human capital levels. They provide evidence on the effect of industrialization on the process of development supporting this argument based on the diffusion and adoption of steam engines across France.
Several authors also highlight the possibility that tertiarization is a consequence not a cause of economic growth due to higher demand as income grows or more investment in R&D and education as a country develops, see e.g. (Foellmi and Zweimüller 2008); (Bonatti and Felice 2008); (Peneder 2003), so reverse causation can also occur.
For some earlier empirical analyses see (Dutt and Lee 1993) and (Ansari 1992). Both the cross-country study of Dutt and Lee (1993) and the time series studies of Ansari (1992) point to a negative growth impact of increased specialisation towards the services sector. None of these studies differentiates across services sub-sectors and do not consider more recent periods when information and communication technologies became more important for productivity growth, especially in the services sector.
Average number of years of primary, tertiary and total education of the working age population were also considered as proxies for human capital in the VAR models. The average number of years of secondary education of the working age population was the proxy selected because it produces better results in terms of rejection of nullity of its coefficients in the VAR models and also in terms of the information criteria (BIC).
We also applied the KPSS stationarity test (Kwiatkowski et al. (1992)). The results from the KPSS test give a somewhat different picture. For the variables syr and sh_h_emp_c the null of stationary around a trend is not rejected at the 10% level of significance. These results are available from the authors upon request.
The results of all the tests described in this paragraph are available from the authors.
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We would like to thank participants at the 15th INFER Annual Conference, EcoMod2013, and three anonymous referees for valuable comments and suggestions. The usual disclaimer applies.
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Appendix
Appendix
Impulse response shocks, Model 1: wholesale and retail trade – T
Impulse response shocks, Model 2: hotels and restaurants – R
Impulse response shocks, Model 3: transport and storage and communications – C
Impulse response shocks, Model 4: finance, insurance, real estate and business services – F
Impulse response shocks, Model 5: community social and personal services - P
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Simões, M.C.N., Duarte, A. & Andrade, J.S. Human capital and productivity growth in a services economy: Some insights from the Portuguese case. Int Econ Econ Policy 16, 511–534 (2019). https://doi.org/10.1007/s10368-019-00439-0
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DOI: https://doi.org/10.1007/s10368-019-00439-0