Abstract
Occupations and sectors are the two fundamental dimensions of structural change. From the evolution of the high/low-skill employment levels and wage premium, we can study which sectors have been undertaking a process of technical change. We use Eu-Silc database to investigate the technological patterns followed before and after the 2008 crisis by four “Southern Europe” countries (Italy, Spain, Greece, Portugal) and three “Eastern Europe” countries (Poland, Hungary, Bulgaria) in comparison with the UK. Our empirical analysis shows that these two groups of countries follow heterogeneous patterns. Eastern Countries are not suffering from de-industrialization and are more oriented toward SBTC, as they are likely to perform better than Southern Countries. In particular, Poland stands out among the Eastern countries and Portugal among the Southern Countries, because they are closest to the UK in terms of technology ratio (level and dynamics after the crisis) and in terms of SBTC tendency.
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Notes
“A noteworthy implication of this framework is that technical change favoring one type of worker can reduce the real wages of another group. Therefore, the richer substitution possibilities between skill groups afforded by the endogenous allocation of skills to tasks highlights that, distinct from canonical model, technical change need not raise the wages of all workers. As importantly, this framework enables us to model the introduction of new technologies that directly substitute for tasks previously performed by workers of various skill levels. In particular, we can readily model how new machinery (for example, software that corrects spelling and identifies grammatical errors) can directly substitute for job tasks performed by various skill groups. This type of technical change provides a richer perspective for interpreting the impact of new technologies on labor market outcomes” (Acemoglu and Autor, 2011, pp.79-80).
The opposite result (σ < 1) was found in an estimate dealing with the United States (Lawrence 2015).
The Cambridge critique to the neoclassical production function maintains that the value of the capital stock is not independent from prices and distribution.
In Eu-Silc we use the variables pl050 (ISCO-88, 2-digit) and pl051 (ISCO-08, 2-digit). The change from ISCO-88 to ISCO-08 occurred in 2009. The differences between ISCO-88 and ISCO-08 in principle could affect the results, but empirically it is quite unlikely as we actually use the 1-digit classification and, hence, the differences between the two codifications are minimal. http://www.ilo.org/public/english/bureau/stat/isco/isco08/index.htm
The variable in Eu-Silc is py200g. This variable has many missing values (eg, it is not available for Germany), but it is the only variable about “earnings” or “income” that is time coherent with the variable about ISCO classification. In the dataset, the main variable about income refers to the previous year, while ISCO classification refers to the current year.
Summing up, we keep only the cases with valide responses about wages (Eu-Silc: py200g), ISCO classification (pl050/pl051), sector of activity (pl110/pl111), and employment (pl040). When data processing deserve weights, we use the personal cross-sectional weight provided by Eu-Silc (pb040).
Michaels et al. (2014), for example, focus on the role of computerization and contend that SBTC models do not adequately account for rising wage inequality over the last three decades. It is worth highlighting that here we are using the SBTC strategy as a shortcut for a context with growing HR and SP.
It might be worth recalling that, although wages usually represent the lion’s share of personal income, wage inequality more strictly relates to the labor market rules, while income inequality usually looks at disposable equivalent income and refers to the whole population.
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Angelini, E.C., Farina, F. & Valentini, E. Wage and employment by skill levels in technological evolution of South and East Europe. J Evol Econ 30, 1497–1514 (2020). https://doi.org/10.1007/s00191-020-00682-8
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DOI: https://doi.org/10.1007/s00191-020-00682-8