Lobna bousl imi and basma majerbi

The Role of Non-bank Financial Institutions and Credit Unionsin Economic Growth

Lobna BOUSL IMI and Basma MAJERBI1

Introduction

The recent global financial crisis has renewed debate on the role of the financial systemin economic development and growth. In particular, the question of whether there existsan optimal structure for the financial system seems to attract, once again, the attentionof both academics and policy makers (see recent studies by Beck et al., 2011; Demirguc-Kunt et al., 2011). Indeed, the answer to this question has important policy implicationsand may contribute to shaping financial sector policies in favor of a particular type offinancial institution or market in an effort to promote more sustainable development.Moreover, the question of an optimal financial structure goes beyond the classic debatebetween the merits of bank-based versus market-based financial systems. While recenttheoretical and empirical evidence point towards the importance of both markets andinstitutions in the financial development process, we still do not have a clearunderstanding of the relative contribution to economic growth of various types ofinstitutions within the financial intermediaries segment.

This paper attempts to contribute to this ongoing debate by investigating the role of thenon-bank financial institutions in general, and the credit union sector in particular, alongwith their potential impact on economic growth.2 While banks still represent thedominant financial institutions in many countries, the importance of non-bank financialinstitutions has evolved over time and in some countries, represents a substantial portionof the overall financial system. For instance, from 1981 to 2005 in the U.S., private creditby non-bank financial institutions represented on average more than 80% of thecountry’s GDP, compared to a ratio of 51% for the credits to the private sector issuedby banking institutions.3 Furthermore, in many developing countries the non-bankfinancial sector – particularly credit unions and financial cooperatives – play an importantrole in alleviating issues of access to financial services and credit, therefore contributingto easing of financial constraints in the entrepreneurial and Small and Medium SizedEnterprises (SMEs) sector, a very important sector in these developing economies.

The Amazing Power of Cooperatives ...73...

05-Bouslimi_Mise en page 1 12-09-05 09:56 Page73

According to the World Council of Credit Unions (WOCCU), there were 53,000 creditunions operating in 100 countries around the world at the end of 2010. Collectively,they served 188 million members and managed USD 1.46 trillion in assets.

This motivates the need for closely studying the impact of the non-bank financialinstitutions and credit unions on economic growth across countries. Our study builds onprevious literature in the finance-growth nexus, which – since the seminal work ofGoldsmith (1969) – studies the link between financial development and long runeconomic growth. However, most of this research has focused mainly on the role of thebanking sector and, to a lesser extent, the stock market (e.g. King and Levine, 1993;Demirguc-Kunt and Levine, 1996; Levine and Zervos, 1998; Levine et al., 2000; Rousseauand Wachtel, 2000).4The empirical evidence from these studies shows that the selectedmeasures of financial development, such as the depth of the banking sector measuredby the ratio of private credit to GDP, or stock market turnover, are positively andsignificantly related to per capita GDP growth rates, with the causality going from financeto economic growth. More recently, Hassan et al. (2011) examine the relationshipbetween finance and growth in various geographic regions and find a positive associationbetween financial development and growth in developing countries.

However, other studies based on more recent data, such as Rousseau and Wachtel(2011), show that the significance of the commonly used variable of bank credit as anindicator of financial development is very sensitive to the sample period and becomesinsignificant in explaining cross-country variations in per capita GDP growth rates overmore recent time periods. Further, Arcand et al. (2011) find that the standard “financialdepth” measure seems to have a negative impact on output growth once the ratio ofprivate credit by banks to GDP exceeds a threshold of about 110%.

In this context, and in light of the recent evidence of evolving financial structures overtime – pointing to the fact that both markets and institutions become more complex ascountries progress in the development process – we investigate whether other types offinancial institutions have a positive impact on economic growth while still controllingfor the contribution of the banking sector.

Indeed, in most countries, there are several non-bank financial intermediaries such asinsurance companies, pension funds and mutual funds that play an important role bothin collecting savings and in supplying credit to the economy, for example throughpurchases of corporate and government debt securities.5 There are also other financialintermediaries that represent an important source of financing for firms and contributeto the overall growth of the financial system in several developed and developingcountries. These intermediaries include: credit unions, savings and credit cooperatives,mutual banks, leasing companies and other types of institutions that are not necessarily

...74... The Amazing Power of Cooperatives


included in the measures of financial development used in previous studies in thefinance-growth literature, which mainly focuses on the banking sector.6 Yet, there is onlya limited number of empirical studies (e.g. Ward and Zurbruegg, 2000; Han et al., 2010,for insurance; Davis and Wei Hu, 2005, for hedge funds) that have looked at the role ofnon-bank financial institutions in promoting economic growth despite the increasingimportance of these institutions in the financial systems of both emerging and developedeconomies.

Emmons and Schmid (2000) looked at how credit unions contribute to bankingcompetition in the United States. The authors examine how households respond toincreases in commercial-banking costs and find evidence that growth in credit unionsleads to growth in deposit markets. These results suggest that commercial banks andcredit unions are direct competitors in the local household deposit market. Another studyby Griffith et al. (2009) looked at the contribution of credit unions to the nationaldevelopment of Barbados, where credit union participation rates represent about 36%of the country’s labor force. The authors conclude that credit unions have a significantlypositive long-run effect on national development in Barbados. They also show that creditunions have a significantly positive short-run effect on real capital stock. Although it isa country-specific study, this evidence suggests that more attention must be paid to therole of credit unions in the overall financial development levels of countries.

In this paper, we look more closely at the credit union sectors in a large number ofcountries. We also study the impact of other types of non-bank financial institutions.We refer to these institutions as “OFI” (Other Financial Institutions) and examine theirrelation with economic growth, while controlling for bank credit. To this end, we firstconstruct new measures based on the size of assets and amounts of credit provided byOFIs at the aggregate level without distinguishing between specific types of OFI. Second,we consider the credit union sector more specifically as a component of the overall OFIsector.

From a theoretical point of view, the importance of other types of financial institutionsin the financial intermediaries sector can be motivated by the findings of recent researchin the field of new institutional economics. For instance, Smith and Stutzer (1990, 1995),and Hart and Moore (1998) show that it is possible to find equilibriums where marketfailure does not occur, but where more than one institutional form emerges. Theinstitutional design of the intermediary – often a mutual form – is essential. This suggeststhat the co-existence of various forms of financial institutions, such as a mutual and ajoint stock, is essential for the economy. Further, using principles of agency theory,Cummins et al. (2004) find that stock and mutual intermediaries are sorted into marketsegments where they have comparative advantages in agency and production costs.



Stein (2002) shows that it is difficult for large banks to transmit the soft informationassociated with relational and SME lending through the communication channels of alarge bank. Since non-bank depository institutions tend to be smaller and use differentlending technologies, they may be able to better use soft information, thus makingtransactions possible. These theoretical findings motivate the need for including bothbanks and non-bank institutions as separate but complementary constituents of thefinancial system when studying the impact of financial development on economicgrowth.

Our study contributes to the literature on at least three grounds. First, it contributes tothe renewed debate on financial structure and development by focusing on the role of“other financial institutions” as a separate component of the financial system, in additionto the standard banking sector. By considering both banks and non-bank financialinstitutions as separate constituents of the financial system structure, this analysisenhances our understanding of the impact of the financial system on economic growth,based on a more comprehensive coverage of the financial intermediaries sector assuggested by the theoretical models mentioned above. This allows us to evaluate therelative contribution to growth of OFIs compared to the banking sector, which mayprovide relevant insights to policy makers. Second, our study uses a panel dataset from1981 to 2005, thus allowing us to include the more recent time period over which theimpact of finance on growth became more controversial as shown by Rousseau andWatchel (2011) and Arcand et al. (2011). Finally, we provide new insights on the role ofcredit unions and financial cooperatives as a separate component of the financial sector.

Our empirical results show that “other financial institutions” have a positive andsignificant impact on long-run economic growth. Using both pure cross sectionalinstrumental variable estimators and dynamic panel techniques, we find that measuresbased on OFI assets and OFI credits to the private sector are significantly related to realper capita GDP growth even after controlling for bank credit and stock marketdevelopment. For credit unions, we also find that the ratio of loans from theseinstitutions to GDP is positively linked to economic growth. Consistent with previousstudies, we find that bank credit is positively related to growth; however the coefficientis not statically significant over our sample period. This result is consistent with thefinding of Rousseau and Wachtel (2011) that drew attention to the sensitivity of therelationship between financial development and economic growth across time. Theabove evidence suggests that non-bank financial institutions play a significant role inpromoting economic growth. Therefore, policy makers should pay more attention to thevarious types of financial institutions other than traditional banks for informing thedesign of new financial sector policies aimed toward achieving more sustainabledevelopment.



The remainder of the paper is organized as follows: In section 2 we describe the dataand present the empirical methodology used in this study. Section 3 presents the mainempirical results and Section 4 concludes the paper and suggests avenues for futureresearch.

Data and methodology

Data Description

Our study covers a sample of 76 countries over the period 1981-2005. Appendix 1provides the definitions and data sources of the variables used in the analysis. Our maindependent variable, economic growth, is measured by the real per capita GDP growthrate. The data about other financial institutions is obtained from the Financial StructureDatabase and International Financial Statistics (IFS).7 Data about Credit Unions assetsand loans are obtained from the World Council of Credit Unions (WOCCU). To accountfor banking sector development, we follow Levine and Zervos (1998) and other studiesand use Bank Credit or Private Credit, which is equal to deposit money, which banksclaim on the private sector as a percent of GDP.

For the variable OFI, we use two alternative measures based on assets and credits:

� OFI assets: Other Financial Institutions Assets divided by GDP;

� OFI credit: Private Credit by Other Financial Institutions divided by GDP.

For Credit Unions, we construct a measure based on loans issued by credit unions dividedby GDP, which represents CU loans. We also construct a measure based on credit unionsassets divided by GDP, which represents CU assets. Our control variables are derivedfrom the literature and include the logarithm of initial real per capita GDP (i.e. initialincome per capita) to capture the tendency of growth to converge. We use schoolenrollment ratios as an indicator of human capital stock in the economy. We also controlfor additional variables shown in the finance-growth literature to be correlated witheconomic growth (Barro, 1991; Easterly and Levine, 1997; Levine et al., 2000). Theseinclude the inflation rate and the ratio of government expenditure to GDP (i.e.government) as indicators of macroeconomic stability, and the sum of export and importsin percent of GDP to control for the degree of openness of an economy (i.e. openness totrade).

Looking at the data, we document that there is important variation of both the size,measured by assets, and the amount of credit provided to the private sector acrosscountries. For example, OFI assets represent less than 1% in Uruguay, El Salvador,Switzerland, Argentina and Peru, while the ratio is greater than 44% in Korea, Norway,Sweden, South Africa, Netherland and the United States. Similarly, OFI credit variesbetween 0.02% of GDP for Uruguay and more than 80% of GDP for the U.S.



The credit unions sector also shows important variation across countries. For example,the assets of credit unions in percent of GDP represent less than 0.10% in Brazil, Mexico,Venezuela, Japan, South Korea, Malaysia and Indonesia. However, the ratio is greaterthan 5% in Canada, Grenada, Barbados, and Trinidad and Tobago.

Overall, the data shows that although the banking sector remains the dominantcomponent of the financial system for some countries, as shown by the size of variablebank credit to GDP, other financial institutions also represent a relatively importantsegment of the financial system in many countries and across various income groups.

Model and Methodology

To examine the relation between other financial institutions and economic growth, weuse a standard growth regression where the real per capita GDP growth rate is regressedover our main financial development variable, plus a set of macroeconomic controlvariables. The model we estimate takes the following form:

Yit= β

0+ β

1 F

it + β

2 OFI

it + β

2 X

it +µ

i+λ

t+ε

it(1)

Where Yit is the growth rate of real per capita GDP for country i at time t, Fit is thestandard measure of financial sector development used in previous studies – bank creditto GDP – OFIit represents other financial institutions assets or credit, Xit refers to a set ofcontrol variables that have been shown by empirical literature to be significantdeterminants of economic growth, µi and λt represent unobserved country and time-specific effects respectively, and εit is the error term.

The model in equation (1) controls simultaneously for bank credit and OFI credit, orassets, to capture the marginal effects of other financial institutions beyond thoseattributed to private credit by deposit money banks which is the standard measure offinancial development used in the finance-growth literature.

We estimate equation (1) for the various measures of OFIs described above as well asfor the credit unions measures “CU assets” and “CU loans”. We use two econometricmethods: first, we employ a traditional cross sectional instrumental variable regression;second, we use a dynamic panel estimation technique to take advantage of both thecross-sectional and time series characteristics of the dataset and address theshortcomings associated with the pure cross-sectional analysis (the potential biasesinduced by simultaneity, omitted variables and including country specific effects).

Cross-country regressions with instrumental Variables:To control for the endogenous determination of the OFI measures with the sources ofgrowth, we perform a traditional cross-sectional instrumental variable estimation. Weuse the legal origin indicators as instruments for the financial development variables,



OFI and bank credit as suggested by La Porta et al. (1998). The legal origin is consideredas an appropriate instrument for financial development indicators for different reasons;on the one hand, legal origin is considered as exogenous to economic growth becausethe English, French and German legal systems were spread during colonization and onthe other hand, legal origin is correlated with financial development.8

For the cross-sectional analysis, the data is averaged for 76 countries over the period from1981 to 2005. We use standard generalized-method of moments (GMM) techniques thatgenerate efficient estimates of the coefficients as well as consistent estimates of thestandard errors. The Hansen test of over-identifying restrictions evaluates if theinstrumental variables are related with growth. The null hypothesis of the Hansen test isthat the instruments are not correlated with the error term.

Dynamic panel estimation:We also employ dynamic panel estimation techniques to address the econometricshortcomings associated with the pure cross-sectional study by taking into account thevariability of the time series dimension, thus gaining a higher degree of freedom and moreprecise estimates. We are also able to measure the country effects that are not detectablein purely cross-sectional and time series estimations. Since we are interested in the long-run relationship between finance and growth, we follow previous studies by averagingthe data over non-overlapping five-year periods yielding five observations per country.

To estimate equation (1) using the five-year averages panel dataset, we use the two stepGMM estimators developed for dynamic panel models by Arellano and Bover (1995) andBlundell and Bond (1998), combining the regression in differences and the regression inlevels. Windmeijer (2005) shows that corrected standard errors of the two-step systemGMM estimators are lower than the corresponding one-step errors, leading to moreaccurate inferences. Furthermore, in the two-step system GMM estimation procedure,the errors are robust to heteroskedasticity and use is made of arbitrary patterns ofautocorrelation within countries (Roodman, 2006). In addition, we employ the forwardorthogonal deviations transformation to our panel. This procedure, proposed by Arellanoand Bover (1995), minimizes data loss since during the first-difference transformation,the average of all future available observations of a variable are subtracted instead ofsubtracting the previous observation from the contemporaneous one.

Due to the small size of our sample, we employ the small-sample correction proposed byWindmeijer (2005) that early studies in the finance-growth literature did not consider.The hypothesis underlying the consistency of the “system GMM” estimator is that theinstruments are valid and the error terms are not serially correlated. To test bothhypotheses, we run two specification tests proposed by Hansen (1982) and Arellano andBond (1991) as shown below.



Empirical Results

Cross-sectional analysis:

As mentioned above, we first perform a cross-sectional instrumental variable estimationusing the various measures for OFIs and CU assets and loans. In all specifications, wecontrol for all the main conditioning information variables used in previous literature. Thecoefficients on other financial institutions are positive and statistically significant for OFIassets and OFI credits at 10% and 1% respectively. However, the coefficient on the creditunions variables is positive but not statistically significant in the cross-sectional regressions.

The coefficient for bank credit is positive but not always statistically significant over theperiod 1981 to 2005. This result contrasts with the early empirical evidence using datafrom the 1960s and showing a positive and significant relation between bank credit andeconomic growth (e.g. King and Levine 1993; Levine 1997; Beck and Levine 2000, amongothers). However, our result is consistent with the findings of the recent study by Rousseauand Wachtel (2011). The authors show that the robust relationship between bank creditand economic growth based on data covering 1960 to 1980 disappears when we use morerecent data starting from the 1990s.

Consistent with previous studies, the coefficient on government expenditure is negativeand significant. Also, the coefficient on log of initial real GDP is negative and significantwhich supports the notion of beta convergence. The coefficient on inflation is positive andnot significant which is consistent with the finding of Boyd et al. (2001) and Beck et al.(2000).

Dynamic panel estimation results

Table 1 presents the results obtained from the panel data regressions that we estimatewith the GMM-in-system procedure. We consider two specification tests proposed byArellano and Bond (1991) and Arellano and Bover (1995) to assess the validity of thehypotheses on which the GMM-in-system estimator is based. The first one is a Hansen(1982) J test of over-identifying restrictions which tests the validity of the instruments. Ourmodel specification is adequate if we cannot reject the null hypothesis of over-identifyingrestrictions. The second is a serial correlation test (m2) of the null hypothesis that the errorterms are not serially correlated (i.e. it specifically examines whether the difference errorterm has second-order serial autocorrelation).

The results in Table 1 suggest that, for all specifications, the Hansen J test and the serialcorrelation test cannot reject the null hypothesis, that our instruments are appropriate andthere is no second-order autocorrelation in the residuals.

The coefficients on OFI assets, OFI credits and CU loans are positive and statisticallysignificant at the 5% level even after controlling for bank credit. This finding suggests that



other financial institutions in general, and credit unions in particular, play a significant rolein achieving faster economic growth. The result for the OFIs sector is consistent with thestudy of Beck et al. (2011), which finds a positive impact for low-end financial institutionsand specialized lenders on access to finance. This is also consistent with the rapid expansionof other financial institutions in both emerging and developed countries.

The coefficient on bank credit is positive but not statistically significant in the threespecifications. The control variables also have the expected signs. The coefficient onschooling is positive and significant confirming previous evidence about the importance ofhuman capital in economic growth. The coefficient on government expenditure is negativeand significant which implies that large government size impedes or slows down economicgrowth. The coefficient on openness to trade is positive, but not statistically significant forthe time frame of this study.

Unlike the cross-sectional analysis, for credit unions the coefficient is positive andstatistically significant at 5%. This result suggests that there is a positive long-termassociation between economic growth and credit unions development. Countries wherecredit unions have a higher contribution to credit in the economy grow fasters thancountries with a smaller credit union sector, after controlling for other growth determinants,including the contribution to credit by the commercial banking sector.

Overall, these results suggest that the development of other financial institutions in general,and credit unions in particular, have a positive impact on economic growth. This may explainthe lack of significance of banking sector measures in recent studies due to a changingstructure of the overall financial systems in which other types of financial institutions,besides banks, are becoming increasingly important players in stimulating economic activity.For example, Nguyen et al. (2011) find a significant positive relationship between overallinsurance growth and economic growth, using a sample over 1980 to 2006.

Conclusion

Since the start of global financial crisis in 2007-08, the relationship between financialstructure and economic growth has attracted a renewed interest from academics and policymakers. This paper contributes to the current debate by investigating the role of non-bankfinancial institutions and credit unions in the relationship between finance and growth. Earlystudies in the finance-growth literature mainly focused on bank credit as an indicator offinancial development. Other studies have debated the merits of bank-based versus market-based financial systems in promoting growth. Little research has been dedicated toexamining the role of other types of financial institutions performing the intermediationfunction, for instance, insurance companies, pension funds, mutual funds, credit unions andfinancial cooperatives, etc.



Recent theoretical models in the new institutional economics field suggest that havingvarious institutional forms in the financial intermediaries sector is essential and beneficialto the economy. This result, in combination with the renewed debate on the link betweenfinancial structure and development, motivates the need to learn more about the growtheffects of other types of financial institutions beyond the banking sector. In this context,we use data on non-bank financial institutions (OFI) as a broad component of thefinancial system, as well as data on the credit unions and financial cooperatives sectoras a sub-component of OFIs. Based on a sample of 76 countries over the period 1981 to2005, we construct several financial development indicators based on OFI credits andassets in percent of GDP, in addition to size and credit indicators of the credit unionssector. Using both cross sectional instrumental variable estimations and dynamic paneltechniques (Arellano and Bond, 1991; Arellano and Bover, 1995), we document severalinteresting findings. First, we find that the OFI variables are positively and significantlyrelated to real per capita GDP growth. We also find that the measures of credit unionssector are positively related to economic growth. The positive association documentedbetween other financial institutions/credit unions and economic growth holds, evenwhen controlling for the impact of bank credit which is the most widely used indicatorof financial development in the finance-growth literature. In most specifications, we findthat bank credit is positive but not statistically significant. This result is consistent withthe recent study by Rousseau and Watchel (2011). Our results are robust to the use ofdifferent estimation procedures and various robustness checks that incorporate the latesteconometric techniques to correct for small sample size (Windmeijer, 2005) and limitsthe proliferation of instruments (Roodman, 2008). These findings suggest that non-bankfinancial institutions may significantly affect output growth either through their directcontribution to supplying credit to the entrepreneurial sector and/or indirectly throughpurchases of corporate and government debt securities. In summary, our analysisprovides new evidence that non-bank financial institutions have a significant positiveimpact on economic growth and should receive greater attention by policy makers topromote more sustainable development through a more diversified financial systemstructure. In particular, financial cooperatives and credit unions should receive moreattention from policy makers in their efforts to foster financial sector development andimprove access to finance especially in developing countries.




Appendix 1: Description of Variables and Data Sources

This table describes the variables used in this study and their respective sources. All data are for theperiod 1981-2005.



Table 1: Dynamic Panel Estimations: Two-step GMM Regressions

Dependent Variable: Real GDP per Capita Growth Rate; Period: 1980-2005.

***. **. * refer to the 1, 5 and 10% levels of significance respectively, P values are in parentheses.


Notes1 Bouslimi is at HEC Montréal, 3000, Côte Sainte Catherine Street, Montréal, Quebec, H3T 2A7,Canada. She can be reached at [email protected]. Majerbi is at the Gustavson School of Business,University of Victoria, PO Box 1700, STN CSC, Victoria, BC, V8W 2Y2, Canada. She can be reached [email protected] The term “credit unions” is used here to capture various types of financial and credit cooperativeswhich are referred to by different names in various regions of the world. For example, Savings andCredit Cooperatives (SACCOs) in East Africa; “Caisses populaires” or “Caisses d’épargne et de crédit”in West and Central Africa; “Cooperativas de ahorro y crédito” or “cajas de ahorro y crédito” in LatinAmerica; credit unions in the UK, USA and parts of Canada. These institutions collect deposits and dobusiness often solely with members.3 These averages are calculated using data from the World Bank’s “Financial Structure Database”.4 For a more detailed review of the finance-growth literature, see Levine (2005) and Ang (2008).5 As noted by Trichet (2009), insurance companies and pension funds are very important investors infinancial markets. Within the Eurozone, their investment amounted to ¤6 trillion at the end June 2009.In addition, insurance companies and pension funds in the Euro area hold about ¤435 billion of debtsecurities issued by euro area banks, which represents about 10% of the total amount outstandingof debt securities issued by banks in the euro zone.6 For instance, the World Council of Credit Unions reports that in 2007, credit unions in the UnitedStates served 43.4% of the working age population. According to Keldon et al. (2009), while U.S.credit unions account for only 10% of deposits, they boasted 86 million members in 2006 whichaccount of 29% of all Americans as owners/customers.7 The World Bank’s Financial Structure Database defines the category “Other Financial Institutions”or OFI to include: 1) Banklike Institutions such as savings banks, cooperative banks, mortgage banks,building societies and specialized finance companies that raise funds mainly through bond markets;2) Insurance Companies; 3) Private Pension and Provident Funds such as life insurance; 4) PooledInvestment Schemes which are financial institutions that invest on behalf of their shareholders in acertain type of asset, as real estate investment schemes or mutual funds; and 5) Development Banks.8 La Porta et al. (1998) showed that the laws governing shareholders and creditors rights, accountingstandard and contract enforcement are influenced by the legal origin.

Bibliography

ANG, J.-B. (2008). A survey of recent development in the literature of finance and growth, Working paper. ARCAND, J.-L., E. BERKES and U. PANIZZA (2011). Too much Finance?, IMF Working Paper.ARELLANO, M. and S. BOND (1991). “Some Tests of Specification for Panel Data: Monte Carlo Evidence and an

Application to Employment Equations”, Review of Economic Studies, Vol. 58, p. 277-297.ARELLANO, M. and O. BOVER (1995). “Another Look at the Instrumental Variable Estimation of Error Component

Models”, Journal of Econometrics, Vol. 68, p. 29-51. BARRO, R.-J. (1991). “Economic Growth in a Cross-section of Countries”, The Quarterly Journal of Economics,

Vol. 56, p. 407-443.BECK, T., A. DEMIRGUC-KUNT and R. LEVINE (1999). A new database on financial development and structure,

World Bank Policy, Research working paper, No WPS 2146.BECK, T. and R. LEVINE, (2002). "Industry Growth and Capital Allocation: Does Having a Market- or Bank-Based

System Matter"?, Journal of Financial Economics, Vol. 64, p.147-180.BECK, T., A. DEMIRGÜÇ-KUNT and V. MAKSIMOVIC (2008). “Financing patterns around the world: Are small firms

different?, Journal of Financial Economics, Vol. 89, No 3, p. 467-487.



BECK, T., A. DEMIRGÜÇ-KUNT and D. SINGER (2011). Is Small Beautiful? Financial structure, Size and Access toFinance, World Bank Policy Research Working Paper 5806.

BLUNDELL, R. and S. BOND (1998). "Initial Conditions and Moment Restrictions in Dynamic Panel Data Models",Journal of Econometrics, Vol. 87, p. 115-143.

BOYD, J.-H, R. LEVINE and B.-D. SMITH (2001). “The Impact of Inflation on Financial Sector Performance”, Journalof Monetary Economics, Vol. 47, No 2, p. 221-248.

CUMMINS, J.-D., M. RUBIO-MISA and H. ZI (2004). “The Effect of Organizational Structure on Efficiency: Evidencefrom the Spanish Insurance Industry”, Journal of Banking and Finance, Vol. 28, p. 3113-3150.

DAVIS, E.-P. and Y. WEI HU (2005). Is there a link between pension fund assets and economic growth? A crosscountry study, Working paper.

DEMIRGUC-KUNT, A., E. FEYEN and R. LEVINE (2011). Optimal Financial Structures and Development: The evolvingimportance of banks and markets, Working Paper.

DEMIRGÜÇ-KUNT, A. and R. LEVINE (1996). “Stock Market Development and Financial Intermediaries: StylizedFacts”, World Bank Economic Review, No 10, p. 291-322.

EASTERLY, W. and R. LEVINE (1997). “Africa’s Growth Tragedy: Policies and Ethnic Division”, Quarterly Journalof Economics, Vol.112, p. 1203-1250.

EMMONS, W. and F. SCHMID (2000). Bank competition and concentration: Do credit unions matter, FEDS,Working Paper.

GRIFFITH, R.-K., T. WAITHE and R. CRAIGWELL (2009). The contribution of credit unions to the national developmentof Barbados, Barbados Ministry of Economic Affairs.

HAN, L., D. MOSHIRIAN and Y. TIAN (2010). “Insurance development and economic growth”, The Geneva Paperson Risk and Insurance, No 35 (3), p. 183-199.

HANSEN, L.-P. (1982). “Large Sample Properties of Generalized Method of Moments Estimators”,Econometrica, No 50, p. 1029-1054.

HART, O. and J. MOORE (1998). Cooperative vs. Outside Ownership, National Bureau of Economic Research,Working Paper, No.6421.

HASSAN, M.-K., B. SANCHEZ and J.-S.YU (2011). “Financial development and economic growth: New evidencefrom panel data”, The Quarterly Review of economics and finance, Vol. 51, No 1, p. 88-104

KING, R.-G. and R. LEVINE (1993). “Finance and Growth: Schumpeter Might be Right”, Quarterly Journal ofEconomics, Vol. 108, p.717-737.

KELDON, J.-B., L.-M. LINDA and N. TAKESHI (2009). “The effects of mergers on credit unions performance”, Journalof banking and Finance, Vol. 33, No 12, p. 2267-2274

LA PORTA, R., F. LOPEZ-DE-SILANES, A. SHLEIFER and R.-W. VISHNY (1998). “Law and Finance», Journal of PoliticalEconomy, No 106, p. 1113-1155.

LEVINE, R. (2005). “Finance and Growth: Theory and Evidence", in P. Aghion and S. N. Durlauf (editor),NorthHolland, Amsterdam, Handbook of Economic Growth.

LEVINE, R. and S. ZERVOS (1998). “Stock Markets, Banks and Economic Growth”, American Economic Review,No 88, p. 537-558

LEVINE, R., N. LOAYZA and T. BECK (2000). “Financial Intermediation and Growth: Causality and Causes”, Journalof Monetary Economics, Vol. 46, p. 31-77.

LEVINE, R. (2002). “Bank-Based or Market-Based Financial Systems: Which Is Better?” Journal of FinancialIntermediation, Vol. 11, p. 398-428.

ROODMAN, D. (2006). How to Do xtabond2: An Introduction to “Difference” and “System” GMM in Stata,Center for Global Development, Working Paper, No 103

ROODMAN, D. (2008). "A note on the theme of too many instruments", Oxford Bulletin of Economics andStatistics, Vol. 71, No 1, p. 135–158.

ROUSSEAU, P.-L. and P. WACHTEL (2000). "Equity Markets and Growth: Cross-Country Evidence on Timing andOutcomes", Journal of Business and Finance, No 24, p. 1933-1957.

ROUSSEAU, P.L and P.WACHTEL (2011). “What is happening to the impact of financial deepening on economicgrowth?”, Economic Inquiry, Vol. 49, No 1, p. 276-288.

SMITH, B. -D. and M.-J. STUTZER (1990). “Adverse Selection, Aggregate Uncertainty, and the Role for MutualInsurance Contracts”, The Journal of Business, Vol. 63, p. 493-510.

SMITH, B.-D. and M.-J. STUTZER (1995). “A Theory of Mutual Formation and Moral Hazard with Evidence fromthe History of the Insurance Industry”, The Review of Financial Studies, Vol. 8, p. 545-577.



STEIN, J. (2002) “Information Production and Capital Allocation: Decentralized vs. Hierarchical Firms”, Journalof Finance, Vol. 57, p. 1891-1921.

TRICHET, J.-C. (2009). "Insurance companies, pension funds and the new EU supervisory architecture", BISReview 147/2009.

WARD, D. and R. ZURBRUEGG (2000). “Does insurance promotes economic grwoth? Evidence from OECDcountries”, The Journal of Risk and Insurance, Vol. 67, No 4, p. 489-506

WINDMEIJER, F. (2005). “A finite sample correction for the variance of linear efficient two-step GMMestimators”, Journal of Econometrics, Vol. 126, p. 25-51.



Summary

This paper investigates the role of non-bank financial institutions and credit unions in promotingeconomic growth based on a panel dataset of 76 countries over the period 1981-2005. We constructnew financial development measures based on the size of assets and loans provided by “otherfinancial institutions” (OFIs) and credit unions (CU) and estimate the impact of these measures oneconomic growth. Our empirical results show that these measures are positively and significantlyrelated to real per capita GDP growth rates across countries. In particular, we find that countries withhigher contributions to credit from the CU sector grew significantly faster over the sample period.These results have important policy implications and suggest that other types of financial institutions,in addition to banks, also play a significant role in promoting economic growth. In particular, financialcooperatives and credit unions should receive more attention from policy makers in their efforts topromote financial stability and economic growth.

Resumen

Este trabajo investiga el rol de las instituciones financieras no bancarias y de las uniones de créditoen la promoción del crecimiento económico basándose en un conjunto de datos de una muestraconformada por 76 países en el período de 1981-2005. Se desarrollan nuevas medidas de desarrollofinanciero en base a la cantidad de activos y préstamos otorgados por “otras instituciones financieras”(OFI, por sus siglas en inglés) y uniones de crédito (CU, por sus siglas en inglés) y se calcula el impactode estas medidas en el crecimiento económico. Los resultados empíricos demuestran que estasmedidas se relacionan de manera positiva y significativa con los índices de crecimiento del productointerno bruto per cápita en los distintos países. En particular, los resultados indican que los paísesdonde las cajas de ahorro y crédito más contribuyen al crédito, registraron un crecimiento más rápidodurante el período de muestra. Estos resultados tienen importantes implicaciones en términos depolíticas y sugieren que otros tipos de instituciones financieras, además de los bancos, tambiéndesempeñan un rol destacado en la promoción del crecimiento económico. En especial, lascooperativas financieras y las uniones de crédito deberían recibir más atención por parte de quienesestablecen las políticas con la intención de promover la estabilidad financiera y el crecimientoeconómico.

Résumé

Dans ce texte, nous examinons le rôle des institutions financières non bancaires et des caissesd’épargne ou de crédit dans la promotion de la croissance économique en nous basant sur unéchantillon de 76 pays couvrant la période de 1981-2005. Nous établissons de nouvelles mesures dedéveloppement financier en fonction de la taille des actifs et prêts accordés par les institutionsfinancières non bancaires et les caisses d’épargne ou de crédit et nous évaluons l’incidence de cesmesures sur la croissance économique. Les résultats empiriques révèlent qu’il existe une corrélationpositive et significative entre ces mesures et le taux de croissance du PIB réel par habitant. Nousconstatons surtout que les pays où les caisses d’épargne et de crédit contribuent le plus au crédit ontenregistré une croissance beaucoup plus rapide au cours de la période étudiée. Ces résultats ont desconséquences importantes sur les politiques et suggèrent qu’en plus des banques, les institutionsfinancières non bancaires jouent un rôle important dans la promotion de la croissance économique.En particulier, les coopératives et les caisses d’épargne et de crédit doivent recevoir plus d’attentionde la part des décideurs politiques dans leur effort pour assurer la stabilité du système financier etpromouvoir la croissance économique.



Lobna bousl imi and basma majerbi

Documents

Transcript of Lobna bousl imi and basma majerbi