Bank credit and regional economic growth of French regions
The goal of this research is in perfect synchronization with the study’s location via its distinctive administrative, banking and geographical build-up. Scholars prefer to analyse effects using a national GDP visible in economic-growth related studies. In a bid to be unique, especially in an evergreen area needing scholarly inputs, there is a need to comprehensively address regional dimensions on the topic as regards Metropolitan France and its overseas territories. The stance of Schumpeter (1912), where he advocated that the banking system remains the ultimate catalyst for economic growth and proper bank functioning, can aid adequate financing investible opportunities and quality advisory. However, empirical evidence provided by Hasan, Koetter & Wedow (2009) suggests that improved bank efficiency spurs regional growth to a greater extent than an increase in credit will. Foundational work by Berger & DeYoung (1997) posits that bank efficiency effectively captures the quality of bank lending and further declared bank efficiency a superior measure to balance-sheet based measures. Furthermore, Narayan & Narayan (2013), using a panel of 65 developing countries, concluded that bank credit has a significant negative effect on economic growth with the exception in Middle East Countries and Asia. Cucinelli (2015) reaffirms that credit risk hurts the lending behaviour of Italian banks.
The re-establishment of credit risk as an impediment to bank lending to needy sectors in a sovereign economy is in perfect consensus with a cross-country comparative study of France and Germany by Chaibi & Ftiti (2015). The analysis herein highlighted that credit risk in a market-based economy supersedes that of a bank-based economy because the higher risk is due to the susceptibility of France to bank-specific factors. The issue of credit risk suffices in the French scenario. In search of regional-based empirical evidence, Ghosh (2017) examined the consequences of commercial bank failure on the regional economy of 50 states, including the District of Columbia (United States of America). Results pronounce that the effect of bank failures on different measures of regional economic activity. Also, bank failures affect construction-sector employment and GDP growth rates. In line with Ghosh’s (2017) findings, Chaibi & Ftiti (2015) also posited that the increase in the unemployment rate also leads to an increase in French NPLs, slowdown in France affects NPLs ratio negatively in consensus with Moody’s Analytics recent forecast about French Banks. Also, a smaller non-interest income of French banks subjects them to adverse macroeconomic shocks.
Substantial empirical evidence with a geo-regional presence in France resides in the work of Sfar & Ouda (2016). They sought to study the contribution of French cooperative banks in regional economic growth. The empirical results by the system generalized method of moments method allow us to confirm that cooperative banks are positively associated with regional economic growth after controlling for various determinants.
There is a dearth of empirical studies on bank lending behaviour and regional economic activity in France. To be more elaborate in this research, emphasis on study-specifics regarding data coverage encompassing regions that makeup Metropolitan France vis-à-vis verified measures of regional economic activity. Also, bank lending behaviour across sectoral and firm-level lending and the total loan portfolio of French banks. Against the backdrop of the lacuna observed, the primary purpose of this study is to assess the effect of bank lending behaviour on regional economic activity in French regions from 2000-2020.
Specific objectives include;
- To examine the direction of causality between bank credit and regional economic growth in French regions.
- To find out if there is a long-run relationship between bank credit and regional economic growth of French regions.
- To assess the impact of bank efficiency on the regional economic growth of French regions.
- To examine the impact of macroeconomic fluctuations on non-performing loans of French banks.
1.3 RESEARCH BENEFITS/SIGNIFICANCE OF THE STUDY
This study’s inherent benefit is sacrosanct to upcoming researchers across undergraduate, postgraduate levels, research institutes and academia can build further considering the foundation this research lays. The uniqueness of the sample, as well as its data coverage, methodology and econometric tools used. Also, the research team of notable French banks can adopt findings to advise top management on regional business policies and banks’ business in the thirteen French regions. Banque de France can also adopt findings of this research to fine-tune apex bank policies on lending to the real sector both in urban and regional centres.
Practical benefits to core professionals and academic researchers on the mundane topic of regional economic activity is residing in an attempted modification cum copy-manufacture of foundational economic growth theories by Solow in 1956. The recent wavelength pioneered by Aghion & Howitt (1998) and Barro & Sala-i-Martin (1997) emphasizes firms’firms’ economic behaviour. In line with their thoughts, regional growth is not as a result of exogenous productivity-enhancing factors. However, more specific is a function of deliberate choices of individual actors comprises of firms and policymakers.
2.0:
DESIGN/PLAN OF STUDY
Sample Size and Sampling Techniques:
The sample size hovers thirteen administrative regions in Metropolitan France and consists of Systemically Important Banks and other tiers two banks in France. The projected sampling technique is the Purposive sampling technique.
Data Sources:
Financial information from French banks emanates from the BankScope database, and regional economic indicators emanate from the National Institute of Statistics and Economic Studies and the European Commission’sCommission’s Eurostat Database. The study period will span twenty-five years covering 1995-2020.
Econometric Technique: The peculiarity of this research influences the choice of a suitable econometric method to answer the research questions herein. As implied in the stated objectives above, long-run relationships and detection of causality using panel data necessitate the adoption of a panel co-integration and causality econometric methods. There is an extant need to decipher cross-sectional dependence before subjecting collected data to panel unit root testing. Empirical entries are provided by (Pesaran 2007 & Pesaran et al., 2008). Foundational papers on panel co-integration are provided by (Pedroni 1999 & Pedroni, 2004). A range of econometric software to be used includes; E-views, STATA, LIMDEP and SAS. Model Diagnostics must be presented to validate the estimated model in the study.