Banking competition and economic growth: cross-country evidence

Abstract

The aim of this paper is to analyse the effect of banking competition on industry economic growth using both structural measures of competition and measures based on the new empirical industrial organisation perspective. The evidence obtained in the period 1993–2003 for a sample of 53 sectors in 21 countries indicates that financial development promotes economic growth. The results also show that bank monopoly power has an inverted-U-shaped effect on economic growth, suggesting that bank market power has its highest growth effect at intermediate values. The latter result is consistent with the literature on relationship lending, which argues that bank competition can have a negative effect on the availability of finance for companies that are informationally more opaque.

Keywords:

• economic growth
• banking competition
• financial development

JEL classification :

• D4
• G21
• L11

Acknowledgements

The authors acknowledge the useful comments of two anonymous referees and the financial support of the Spanish Savings Banks Foundation (Funcas), the Spanish Ministry of Education and Science-FEDER through the research program SEJ2007-60320/ECON and SEJ2010-1733/ECON, and the Valencian Government through the research program PROMETEO/2009/066.

Notes

The basis of the argument is that financial development can affect both the growth of a sector and the pattern of specialisation, so that it incentivises the less financially developed countries to specialise in sectors less dependent on external finance.

Baumol (1982) and Baumol, Panzar, and Willig (1982).

See, for example, Fernández de Guevara et al. (2005) for the analytical derivation of the Lerner index from a model of behaviour of banking firms.

In perfect competition, a proportional variation in the input prices induce a proportional change in revenue, since the output that minimises the average costs does not vary, while the price of the output varies in the same proportion. In a market with monopolistic competition, revenue grows less than proportionally to variations in the input prices because the demand faced by firms in the products market is inelastic. In the case of monopoly, a growth in the price of inputs increases the marginal costs, reduces the equilibrium level of production and consequently reduces the revenue.

The database is available at http://www.ggdc.net/dseries/60-industry.html.

Financial intermediation sectors (sectors 43–45) are excluded in the estimation of Equation (1). In Section 6, we check the robustness of the results estimating Equation (1) only for the manufacturing sectors.

See in Beck et al. (2003) a justification of the different proxies for financial development (see also Chinn and Ito 2006; Baltagi, Demetriades, and Law 2009).

http://unstats.un.org/unsd/class/default.htm.

Rajan and Zingales defined the external dependence as capital expenditures minus cash flows from operations divided by capital expenditures.

The approach to the measurement of the price of banking activity and to the estimation of marginal costs is similar to that used in Maudos and Fernández de Guevara (2004) and Fernández de Guevara et al. (2005, 2007).

The validity of the H-statistic rests on the assumption that sectors are in long-term equilibrium. To test this assumption, we re-estimate the revenue equation replacing the dependent variable by ROA (return on assets), so the long-term equilibrium is compatible with a value of the sum of the elasticities associated with the input prices equal to 0. Practically, in all cases, it is not possible to reject this hypothesis.

Table 3 summarises the variables and sources of information used, the descriptive statistics being shown in Table 4.

From the total of sectors hitherto analysed, we have eliminated the mining sector (sector 4), construction (sector 33) and all the services sectors (34–57). Results are available upon request.

The results are also robust if we include in the estimation the effect of variables specific to each country that are usually used in regressions to explain economic growth. Specifically, we include two explanatory variables: (a) human capital (proxied by the average of the years of schooling attained by the population over 25 years of age (source: Barro and Lee 2000) and (b) the initial GDP per capita, obtained from the OECD publication National Accounts. Results are available upon request to the authors.