A hierarchical analysis of structural change and labour productivity convergence across regions, countries and industries within the EU

ABSTRACT

This study explores the effect of structural change on the process of labour productivity convergence at different levels of data aggregations (regions, industries, countries), which is also known as hierarchical convergence analysis in the recent literature. Different forms of structural changes have occurred in the European Union, for instance, variations in the share of employment in different industries, variations in the demand pattern and variations in trade patterns and advancement in technology, which may have an influence on the nature of convergence. Earlier studies on convergence have neglected the effect of the structural change, which may have resulted in different conclusion about the convergence. Based on the results, the study found that the nature of convergence changes after considering the effect of the structural change.

KEYWORDS:

• Labour productivity
• convergence
• structural changes
• panel data
• panel unit root

Disclosure statement

No potential conflict of interest was reported by the authors.

Notes

1. See for example Abramovitz 1986; Baumol 1986; Dollar and Wolff 1988; Dollar et al. 1993; Barro and Sala-I-Martin 1992; Quah 1993; O’leary 1997.

2. For details, see Webber and Horswell 2009; Byrne et al. 2009; Enflo and Hjertstrand 2009.

3. Some studies discussed and find the evidence of heterogeneity across industries and countries. For details, see Bernard and Durlauf 1995; Artige and Nicolini 2006.

4. For details, see Kuznets and Murphy 1966; Gemmell 1982; Dowrick and Nguyen 1989; Dollar et al. 1993; VAN ARK 1996; Doyle and O’leary 1999.

5. For details, see Dollar and Wolff 1988; Dowrick and Nguyen 1989; Dollar et al. 1993; Bernard and Jones 1996; O’leary 1997; Curran and Sensier 2012; Sondermann 2014.

6. For details, see Solow 1956; Barro and Sala-I-Martin 1992.

7. The test is suggested by Fisher (1922) and defined by Maddala and Wu (1999).

8. Furthermore, they also proved that IPS test is better than LLC, because LLC test is based on the homogeneity of the autoregressive parameter, while IPS test is based on heterogeneity of the autoregressive parameter.

9. Naveed and Ahmad (2016) have used this methodology for measuring structural change.

10. Structural changes are usually measured as sectoral shares of employment. For details, see Kuznets and Murphy 1966; Gemmell 1982; Chenery et al. 1986; Dowrick and Nguyen 1989; Dollar et al. 1993; VAN ARK 1996; Doyle and O’leary 1999.

11. The results for other two panel unit root tests (LLC and IPS) are available on request from the authors.

12. Drift mean includes a constant in the specifications, while no-drift does not include constant. This is a standard procedure followed by empirical literature for robustness check.

13. Fisher test reports four different values of test statistics (provide same decision) but for the convenience, we only report modified inverse chi-squared and others are available on request.

14. Furthermore, they also proved that IPS test is better than LLC, because LLC test is based on the homogeneity of the autoregressive parameter, while IPS test is based on heterogeneity of the autoregressive parameter.

Additional information

Notes on contributors

Nisar Ahmad

Nisar Ahmad is currently working as an Assistant Professor at the Department of Economics and Finance Sultan Qaboos University (SQU). He also worked as Associate Professor at the Department of Border Region Studies, the University of Southern Denmark as an Assistant and Associate Professor. He is graduated (PhD Economics) from Aarhus University, Denmark. Currently, he is teaching Game Theory, Econometrics, Micro and Macroeconomics. His main areas of research are quantitative economics, labour economics, energy economics and  Systematic Literature reviews. Apart from teaching and research, he is a member of the international accreditation team of SQU.More information: https://www.squ.edu.om/ceps/Academic-Departments/Economics-and-Finance/Faculty-and-Staff/Nisar-Ahmad

Amjad Naveed

Amjad Naveed is an Assistant professor of Economics at the Department of Business Development and Technology (BTECH), Aarhus University, Denmark. He is graduated from the University of Southern Denmark (PhD Economics) and Aarhus University (MSc Economics). Currently, he is teaching Business Economics, Micro and Macroeconomics and Advanced Business Economics. His main areas of research are quantitative economics, economic development and growth, business economics, labour economics and productivity and growth at the industry, country and regional levels. More information: http://au.dk/[email protected]

Amber Naz

Amber Naz is a visiting faculty at the Department of Economics and Finance Sultan Qaboos University (SQU). She is graduated from the University of Southern Denmark (PhD Economics) and Aarhus University (MSc Economics). Currently, she is teaching Industrial Organization, Micro and Macroeconomics. Her main areas of research are quantitative economics, Economic Growth, Regional Economics, and Convergence.