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Annex 1. Panel Unit Root and Cointegration Tests
Annex 2. Summary Statistics and Correlation Matrices
Annex 3. Variable Definition and Sources
CIRPÉE (University of Québec in Montréal) and ERUDITE (University of Paris XII). The authors would like to thank Andy Berg, Sylviane Guillaumont, Patrick Imam, Vitaliy Kramarenko, Ross Levine, Prachi Mishra, Johannes Mueller, Norbert Toé, John Wakeman-Linn, Irene Yackovlev, and seminar participants at the 2009 African Economic Conference in Addis Ababa for many helpful comments and suggestions. Anne Grant provided useful editorial comments.
Because large firms are able to raise funds from abroad or self-finance their investment, small and medium enterprises (SME), which constitute the backbone of the productive sector, are hit hardest by the lack of long-term credit because they have fewer financial resources and the projects they undertake are innovative, hence riskier. Also, if a firm chooses to start up a long-term investment using credit with shorter maturity, this increases the risk that the project will be delayed or halted if the credit line is not renewed.
Benin, Burkina Faso, Côte d’Ivoire, Guinea-Bissau, Mali, Niger, Senegal, and Togo.
The Banque Centrale des Etats de l’Afrique de l’Ouest (BCEAO) and the Regional Banking Commission.
Average private credit to GDP stood at 12 percent for WAEMU countries over 1995–2006, compared with 15.6 percent for other SSA countries (excluding central African CFA countries).
With the Agrément Unique, a single banking license is sufficient to set up banking operations anywhere in the WAEMU.
Organisation pour l’Harmonisation en Afrique du Droit des Affaires.
“Negative information” refers to data on late payments and defaults; “positive information” refers to information on borrowers who have paid their obligations on time.
Periods of high inflation occurred during the devaluation of the CFA franc in 1994 and more recently following international food and fuel price hikes.
Statutory reserves are not remunerated in the WAEMU.
The quality of bank portfolios, however, varies by country: net NPLs are well above the regional average in Togo and Mali.
Net interest margin is defined as the average return on loans less the average cost of resources.
The recent boom in telecommunications has also helped increase long-term credit to the service sector. Long-term credit includes mortgages to households, but the share is low except in Côte d’Ivoire and Senegal.
It may be possible that limited domestic market and low regional integration hampered the competitiveness of the industry sector. Although the devaluation would raise the price of imported goods, local industries may not be competitive enough to increase their market share due to high production cost.
The large increase in long-term credit to agriculture in 2002 mostly reflects the financing of the cotton crop in Mali. With good rainfall cotton production more than doubled in 2002 stimulated by an increase in the producer price of 14 percent. Long-term credit to agriculture increased by nearly 500 percent in 2002, whereas short-term credit rose by 72 percent. Banks were aided by a surge in deposits as Malians living in Côte d’Ivoire repatriated savings, and activities were transferred from banks in Côte d’Ivoire to Malian banks during the Ivorian crisis.
Joseph, Rafinot, and Venet (1998) state that the contrasting results of the panel approach and the country-specific analysis could be attributable to wide variations (high volatility) in the level of financial development.
The results not presented in this paper are available upon request.
By including both short and long-term credit in the regression, we are controlling for the fact that more demand for long-term credit will also stimulate demand for short-term credit.
It is worth noting that the GMM System estimator might not be appropriate for our model because it is designed for panel data with large N (individuals/countries) and small T (time dimension). Also, the number of instruments quickly becomes large relatively to sample size; to avoid overfitting, we assume that initial GDP level is predetermined, financial development is endogenous, and other variables are exogenous. When all the explanatory variables are instrumented, the results are, however, similar except that the probability of the Hansen test is very close to 1.
Given that there are some concerns about the power of panel unit root tests, the results from the fixed effect and System GMM estimator may still be relevant.
For more details, see the panel unit root and cointegration tests in Annex 1. We are grateful to Peter Pedroni for sharing the code for the cointegration test.
In estimating the long-run relationship, the model is restricted to the financial development and control variables that are consistently significant in the previous regressions (initial GDP per capita and inflation). This also makes it possible to minimize loss of data due to missing observations. However, including trade openness, education attainment, and government expenditure in the model does not change the quality of the results.
This is likely driven by the banking regulation which requires that banks finance long-term credit with long-term resources.
This threshold has a standard deviation of 0.007, suggesting that the actual threshold lies between 2.8 percent and 5.6 percent at a 95 percent confidence interval.
When we use return on equity (ROE), the coefficient is positive but only marginally significant at 12 percent.