Factors driving sectoral and occupational employment changes during the Spanish boom (1995–2005)

ABSTRACT

Spain's economy grew at a real annual average rate of over 3.5% between 1995 and 2005. Total employment increased by more than five million. This process altered the sectoral and occupational structure of employment. The dynamics of final demand, technology and labour requirements linked to technology and labour market institutions mostly drive shifts in the structure of employment. We analyse their effects and relative weights on private employment growth in an input–output framework, by means of structural decomposition. The analysis of the occupational structure is a novelty. Sectoral and occupational structures of employment are receiving a great deal of attention: the productivity growth and economic prospects of service economies and the debate between skilling and polarization are, respectively, the main issues. This paper provides useful insights on the dynamics of the structure of employment during a process of vigorous job growth.

KEYWORDS:

• Employment growth
• sectoral growth
• occupational change
• structural decomposition analysis

Acknowledgements

I thank the editor Michael Lahr for his advice and help. Several anonymous referees contributed with their feedbacks and suggestions. Milford Edge provided excellent proofreading. I am indebted to Joan Carles Martori and Ramon Oller, from DAM research group for fruitfully discussions.

Disclosure statement

No potential conflict of interest was reported by the authors.

ORCID

Rafa Madariaga http://orcid.org/0000-0002-2530-7813

Notes

1 Havik et al. (2014) explain the standard ‘production function’ methodology. Figure A1 in the Appendix shows empirical evidence. Many papers have tried to explain this poor development: Pilat (2005), Mas and Quesada (2006), Martinez et al. (2008) analyse the role played by Information and Communication Technologies. Alonso-Borrego (2010), Boldrin et al. (2010), González and Miles-Touya (2012) and Mora-Sanguinetti and Fuentes (2012) focus on the role of institutions. Jimeno (2007) and Andrés et al. (2010) focus on labour market regulations and reforms. Garcia Serrano (2011) focuses on sectoral employment growth but only with a four sectoral breakdown. Hospido and Moreno-Galbis (2015) talk about ‘productivity puzzle’. Researchers see the results as weak and unpromising for long-term growth. They share the view that institutional issues are the most important: tight labour market regulations, dual labour market, inefficient wage bargaining system and lack of competition. All of these works use production functions as a benchmark.

2 For a general review and some pieces of evidence that SBTC cannot explain, Card and DiNardo (2002).

3 It is necessary to bear in mind that the discussions on these changes in the occupational structure of employment require the definition of a rank-ordering method to appreciate the changes. Criteria based on median wage or median educational level have been generally used following pioneer work inspired by Stiglitz in the President's Council of Economic Advisors (Wright and Dwyer, 2003). As the purpose of our study is not exactly to discuss these questions but to describe the changes and to analyse driving factors, we do not go further in this issue. Anyway, the occupational categories used are ordered by average annual wage obtained from the Encuesta de Estructura Salarial (Wage Structure Survey) from 2002.

4 Availability of data have limited the scope of the paper to private sectors.

5 A general overview of SDA techniques and several examples can be found in Miller and Blair (2009). A critical review of SDA methods is offered by Rose and Casler (1996) and an analysis of the problems caused by the existence of multiple forms in Dietzenbacher and Los (1998).

6 The use of production functions presents methodological problems that are largely overlooked by most economists. The discussion of such methodological problems goes back to the ‘Cambridge controversies’ that developed from the mid-1950s to the mid-1970s. See Colacchio and Soci (2003), Cohen and Harcourt (2003), Garegnani (2012) and Felipe and McCombie (2014) for a sample of criticisms.

7 The employed figures include wage-earners and self-employed. There is no data on these two categories. On the other hand, LFS asks about employment status the previous week: it estimates total employment, but it is not accurate to measure the extent of temporary employment.

8 It also shows the abbreviations used throughout the paper.

9 In this sense, the employment data set is unique. Unfortunately it will not be possible to continue the study or to extend it for a longer period. Furthermore, it is not possible to further disaggregate occupations or sectors.

10 Elementary occupations in the ISCO are comprised of basic sales and service occupations, agricultural, fishery and related labourers; and labourers in mining, construction, manufacturing and transport.

11 The ERM report was carried out by The European Foundation for the Improvement of Living and Working Conditions (EuroFound) which is a tripartite European Union Agency that was established in 1975 to contribute to the planning and design of better living and working conditions. It develops its role in partnership with governments, employers, trade unions and the European Union institutions. (http://www.eurofound.europa.eu/)

12 It also shows the abbreviations used along the paper.

13 For more information, http://www.euklems.net/index.html (Last access, February 2018)

14 We construct an employment E matrix (8×14) with occupations across rows and sectors in columns. This is convention, but it implies that in Equation 3 we obtain a transposed version of h.

15 The elements of this matrix are also called ‘vertically integrated labour coefficients’.

16 We are indebted to an anonymous referee who suggested this strategy.

17 Eurostat data based on the EU Labour Force Survey.