Abstract
The paper tests the hypothesis that small member states of the European Union (EU) experience economies of scale constraints. This study adopts a production function approach, utilising data from the 27 differently sized EU member countries. The results confirm the hypothesis and indicate that larger EU member countries incur lower costs per unit of output produced when compared to the smaller ones. This finding has important implications for small EU member states, including that smaller countries have to overcome their economies of scale constraint in order to attain and maintain international competitiveness. This disadvantage is particularly relevant for small states, because these states tend to be highly dependent on international trade, in which case international competitiveness is a major issue.
Acknowledgement
The opinions expressed in this paper are those of the authors only.
Disclosure statement
No potential conflict of interest was reported by the authors.
Notes
1. See e.g. Briguglio (Citation1995), Atkins et al. (Citation2000), and Guillaumont (Citation2010).
2. Some find that the level of economic development is independent of country size (e.g. Rose, Citation2006).
3. Technology measures shifts in production function which cannot be explained through labour or capital changes. In this sense, erc captures any systematic factor other than labour and capital. erc reflects total factor productivity (TFP).
4. When time-series data are used, the efficiency term of the production function is often interpreted as capturing Hicks-neutral technological change. Alternatively, one can allow for a non-neutral type of technological change (David and Van de Klundert, Citation1965) in the sense that the factor augmenting efficiency changes are not assumed to be the same for labour and capital. Although the technical change parameter is usually applied to time-series data, we shall use the concept of efficiency in our cross-section analysis to allow for shifts in the production function due to differing factor enhancing endowments across countries.
5. Private sector is defined as total activities less public administration, defence, and compulsory social security.
6. The correlation coefficient between population size and the size of the private sector in the sample of countries was 0.96.
7. An alternative approach was to include a dummy variable for Luxembourg, (LU) to allow for this special characteristic of the country, where LU takes the value of 1 for Luxembourg and the value of zero for the other countries. The results were very similar to the estimated equation that leaves Luxembourg out, as shown in the following equation: ln Lit = 2.934 − 0.769lnWit + 0.968lnYit −-0.132Cit − -0.772LU
8. On the basis of the computed t value (4.29), we reject the null hypothesis that α2 is equal to 1.
9. The data on NAIRU was obtained from the annual macroeconomic database (AMECO) of the European Commission's Directorate General for Economic and Financial Affairs (DG ECFIN)
10. The countries with excess labour demand are Germany, Poland, Cyprus, and Slovakia.
11. On the basis of the computed t value (4.04), we reject the null hypothesis that α2 is equal to 1.
12. From the correlation coefficients, it can be concluded that exogenous variables are not highly collinear. This means that multicollinearity is inconsequential.
13. The agglomeration of economic production could also be factored in by augmenting Equation (Equation7(7) ) with the share of industrial activities in total GVA, sourced from Eurostat. This tests the hypothesis that the higher the share of industrial activities relative to total GVA the more able a country is to reap the benefits of the agglomeration given that geographical economies of scale do matter more for industrial activities as for services. The results of estimation gave practically the same results as those obtained by regressing Equation (Equation7(7) ), meaning that the coefficient on Y remains significantly less than unity, indicating increasing returns to scale.