Philippine Rural Banks and Economic Development 1

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2 Philippine Rural Banks and Economic Development 1 Céline CROUZILLE a, Jessica LOS BANOS b, Emmanuelle NYS a, Alain SAUVIAT a a LAPE, Université de Limoges, 5 rue Félix Eboué, BP 3127, Limoges Cedex, France b CBA, University of the Philippines, Diliman, Quezon City 1101, Philippines Abstract: This paper examines the link between financial and economic development at the regional level in the Philippines and focuses on the role played by rural banks in regional economic activity. We apply cointegration panel data analysis on regional banking and economic data for the period 1993 to We ranked the sixteen regions in three different groups based on their average economic development. The wealthier the region, the more important the financial depth is. However the Asian crisis prevents us to find a positive long term relationship from the cointegration analysis between finance and growth when studying all regions together. When investigating the less developed regions, our results show some support for a long-run relationship between financial development and economic growth. In that case, the findings also bear out a threshold effect of rural bank presence on economic activity encouraging government policy to strengthen rural finance. JEL Classification: G21, O16 1 This paper was prepared for the ASIA-LINK human resource development project: Euro-Philippines Network on Banking and Finance, Safety and Soundness of the Financial System, coordinated by the University of Limoges ( ASIA-LINK is a programme of the European Commission that seeks to promote regional and multilateral networking among higher education institutions in Europe and developing economies in Asia. 2

3 Section 1. Introduction The link between financial development and economic growth has been the subject of extensive research in recent years, often anchored on the seminal works of McKinnon (1973) and Shaw (1973). McKinnon and Shaw posit that removing restrictions on interest rates increases interest levels and amplifies the volume of money for lending, eventually leading to greater capital formation and productivity, and consequently economic growth. Their influential work on financial liberalization laid the groundwork for the renewed interest in the role of financial intermediation in the economic growth process, which this present study investigates in the case of the Philippine regions. Existing literature on the function of financial markets in economic growth include, among others King and Levine (1993a, 1993b), Bencivenga and Smith (1991), and Beck et al. (2000). A number of research themes are prominent in the growth literature (see Levine 1997, for a comprehensive review). Some studies concentrate on exploring the channels through which financial development stimulates economic growth (see Calderón and Liu 2003) such as capital formation and productivity. Others focus on the impact of savings and lending on growth (Demetriades and Luintel 1997 and Bandiera et al. 2000). A number examine the resulting resource allocation efficiency (Bencivenga and Smith 1991) of intermediaries ensuing from financial liberalization. This allocative efficiency is argued to aid in risk management by savers and investors (Angbazo 1997), to lead to better identification of long-term investments that are more productive than short-term ventures (Bencivenga and Smith 1991), to improve investment decisions (Greenwood and Jovanovic 1990), and to facilitate information collection and evaluation of investment projects (King and Levine 1993b and Boyd and Prescott 1986). The more contentious area of research investigates the causality of the relationship between growth and financial intermediation (King and Levine 1994, Demetriades and Hussein 1996, and Wachtel and Rousseau 1995). The positive link between financial development and output growth is argued to be complicated by the direction of the relationship (Christopoulos and Tsionas 2004). Some researchers assert that it is financial development that follows growth (See King and Levine, 1993a,b, and Demetriades and Hussein 1996) while others find otherwise, that it is growth that fuels financial development (Christopoulos and Tsionas 2004) since improvements in productivity and economic output would require increased investment and funding. Other studies claim that this causality is 3

4 actually bi-directional (Demetriades and Hussein 1996) while a few do not find any link between financial development and economic growth at all (Lucas, 1988, Chandavarkar, 1992). Existing empirical studies mainly focus on the influence of the financial development on economic growth across countries, and therefore they need to control for institutional, social and political disparities. In this paper, we only study the case of the Philippines which enables us to assume that macroeconomic conditions and political governance (monetary and exchange rate policy, banking regulation, education and health policy, industrial policy ) are relatively homogeneous across the regions of this country. Therefore we can focus on structural differences in the banking industry among the regions in order to provide deeper insights into the finance and growth nexus. In the case of the Philippines, this question is of particular interest. The formal banking system is composed of three categories of banks: universal and commercial banks (UKB), thrift and private development banks (TB) and regional rural and cooperatives banks (RB). Although the formal banking system is dominated by commercial banks, rural banks in the Philippines were primarily established to promote and expand the rural economy. They generally cater to small borrowers including farmers, entrepreneurs, market vendors, business owners, wage earners, teachers and cooperatives. From the 1960s to the 1980s, rural banks served as conduits of subsidized loan funds from the government and international donors and were plagued by high default rates, insolvent lending programs, and high operating costs to name a few (Agabin and Daly 1996). In response, regulations were passed in the 1990s covering minimum capitalization requirements, limitations and restrictions to single borrowers and shareholders, and increase in capital adequacy ratio for all banks at 10% of risk-weighted assets. Interest rate restrictions were also removed and the liberalization of new bank openings and branching was pursued. Using regional banking and economic data for the period 1993 to 2005, we test whether the presence of rural banks positively affects regional economic activity. Our estimation model is designed to address the heterogeneity of economic development and banking coverage of the regions in the Philippines and to enable us to efficiently utilize the limited regional data available presently. We apply the model on three sub-samples of regions in the Philippines (all regions, intermediate developed regions and less developed regions). Regions are classified as less-economically-developed, intermediate-developed, and developed using macroeconomic data from the Philippine National Statistics Office, National 4

5 Statistical Coordination Board and the Bangko Sentral ng Pilipinas. We build on the work of Apergis et al. (2007) and Christopoulos and Tsionas (2004) for our cointegration panel data analysis which aims to assess the special role of rural banks on regional economic activity in the Philippines. Our estimation results find support for a long-run relationship between financial development and economic growth in the Philippines. Our findings bear out a threshold effect of rural banking financial depth for the less developed regions in the Philippines. The paper is organized as follows. Section 2 follows the introduction and provides a brief survey on regional economic development. Section 3 presents the role of rural banks and banking coverage in the Philippine regions. Section 4 presents the econometric methodology and discusses the results and Section 5 concludes the paper. Section 2. Disparities of Regional Economic Development in the Philippines The Philippines is divided into seventeen (17) geographic regions, with seven regions in Luzon, including the National Capital Region (NCR), three in the Visayas and seven regions in Mindanao. For this study however, we refer to only 16 regions, having integrated Region 4-A, Calabarzon and Region 4-B, Mimaropa (Region 4 was divided into two separate jurisdictions only in 2002). Stages of economic development of the regions in the Philippines are distinct and divergent. The heterogeneity of their economic performance is obviously due to differences in the impact of political, economic, social, environmental and other factors affecting economic growth. The per capita real gross regional domestic product (PC_RGRDP) rankings of the regions have remained relatively constant over the period covered by this study. Table 1 presents the real per capita gross regional product of the regions. NCR continues to be the most economically developed and the ARMM, the worst performer among the regions in the country. Those regions whose economic performance has deteriorated have period growth rates that are significantly lower than those whose positions have significantly improved and those who have retained their PC_RGRDP rankings. 5

6 Table 1 Per Capita Real Gross Regional Domestic Product Developed regions Rank Rank Period Growth NCR % CAR % Northern Mindanao % Intermediate developed regions Davao % Central Visayas % South Luzon % Western Visayas % Socksargen % Central Luzon % Less developed regions Zamboanga Peninsula % Ilocos % Cagayan Valley % CARAGA* % Eastern Visayas % Bicol % ARMM % Source: National Statistical Coordination Board. *CARAGA figure corresponds to In view of the heterogeneity of the stages of economic development and in line with our estimation model, we classify the regions into three groups: less-economically developed, intermediate developed and developed regions. Based on simple statistical analysis of the above data, we identify the less-economically developed regions to be the following: Ilocos, Cagayan Valley and Bicol in Luzon, the Eastern Visayas region in the Visayas and Zamboanga Peninsula, the Autonomous Region in Muslim Mindanao (ARMM) and the CARAGA in Mindanao. These regions are basically agriculture intensive with lower levels of industrialization. Their regional contribution to the Philippine GDP as of 2005 is below 2% whereas their inhabitants account for 26% of the Philippine population. Except for Bicol which has one economic zone and a single locator, there is no economic zone presence in the regions. The human 6

7 development indices, poverty incidence of families, and education spending for this group are among the worst in the country. The developed regions, NCR, CAR and Northern Mindanao are those with a strong service sector coupled with a vibrant industrial sector. There is also a robust presence of economic zones and a large number of business establishments in these regions. Their per capita gross regional domestic products are among the highest in the country. CAR is classified as developed in view of the presence of the province of Benguet in the region, which is highly developed and which greatly improves the ranking of the region despite the significantly poorer economic performance of the other provinces in the region. Central Visayas (with Cebu province) and Davao (with Davao del Sur province) regions, despite being more highly urbanized than Northern Mindanao and the CAR, were not classified in this group in view of the lower ranking of their per capita GDRP levels as of The intermediate economically-developed regions are comprised of those regions that were not classified as developed and include Central Luzon and Southern Luzon regions in Luzon, the Western Visayas and Central Visayas regions in the Visayas, and Davao and Socsargen in Mindanao. Section 3. Banking system and role of rural banks in the Philippines The formal financial sector 2 is dominated by banks, which as of 2005, are comprised of the universal and commercial banks (UKBs) which number 40 and with 56% of the total bank offices in the Philippines, 83 thrift and private development banks (TBs) with 17% of bank office share and 861 regional rural and cooperative banks (RCBs) with the remaining 27% of the total banking offices operating in the country (BSP 2007). To date, the RCBs remain the major source of agricultural credit with the bulk of their average net loan portfolio allocated to the agriculture, forestry and fishery (AFF) sectors. 3 The net loan portfolio (NLP) share of the RCBs for the AFF, industry and service sectors over the period are provided in Table A1. 2 In this paper, we do not aim to study the semi-formal and informal financial sectors. For a presentation of the financial system in the Philippines, see Dauner Gardiol, Helms and Deshpande (2005). For a detailed study of rural finance, see Llanto (2005). 3 This figure was derived from data on rural bank net loan portfolio for the period provided by the BSP. 7

8 As with regional economic development, banking structure and coverage of the regions is also heterogeneous, with UKBs accounting for a significant share of the financial intermediation taking place in the regions. Those regions that are classified as less-economically developed are served by less than 1/5 of the total banking offices in the country. Of these, almost one-half of the offices are rural banks. The intermediate developed regions in turn share almost 1/2 of the total bank offices, with the remaining 1/3 located in the developed regions, and with UKBs accounting for 3/4 of the total regional offices. With large number of offices, bank density of the RCBs in the less developed regions, while peaking during the financial crisis period have not returned to 1993 levels except for the CARAGA region. All banks located in the less developed regions operate with only 2% of the total banking assets, among which 144% are held by RCBs. The majority of total banking assets, around 87%, are located in the most developed regions and the remaining 10% in the intermediate developed regions. In terms of deposit taking, the same trend can be observed across the three groups with a majority of deposits being placed in UKBs by depositors in the most developed regions of the country. Savings in the less developed regions account for less than 1/10 of the total deposits in the regions, implying that UKBs and TBs are still preferred over RCBs as depositories. Individuals and firms in the more developed regions are also found to be saving significantly more. As regards borrowing, UKBs are the preferred banks to obtain financing from. However UKBs have not yet recovered the level of net loan portfolio they have reached before the Asian crisis. On the other hand, despite the initial decrease of loans they granted just after 1997, RCBs have been able to increase in most regions their loan market share, and to exceed the 1997 peak. Individuals and firms in the less developed regions engaged in significantly fewer economic activities borrowing less than 3% of the total national loan portfolio as of 2005 consistent with their economic weight. However, creditors from the less-developed regions increasingly borrow from RCBs with 32% of their financing requirements obtained from the RCBs in 2005 even if a significant portion of the market share for loans still goes to UKBs. 8

9 As a consequence the intermediation rate, derived by dividing net loan portfolio by deposit liabilities has decreased after the 1997 financial crisis in the less developed and the intermediate developed regions. Moreover financial depth of the regions, measured by the ratio of the net loan portfolio over gross regional domestic product, has significantly declined in all regions. Section 4. Empirical framework and estimation results 4 Rank-order correlation tests To begin our investigation on the relationship between economic growth and financial intermediation in the Philippines regions and on the possible role of rural banks, we initially test for correlation between selected banking and economic development indicators. The current financial system in the Philippines is considered to be bank-based because of the dominance of banks in the country as evidenced by the limited presence of equity markets in the regions, and the fact that only the largest corporations are listed in the country s stock exchanges. Hence funding for the majority of businesses in the country is expected to be sourced primarily from banks and not through financial markets. The use of bank-based financial proxies is thus appropriate. Our study over the period relies heavily on data obtained from Bangko Sentral ng Pilipinas, the National Statistics Office and the National Statistical Coordination Board. Two measures of the regional economic structure are used: the per capita real gross regional domestic product (PC_RGRDP) and the per capita real gross added value in the agricultural and fishery sector (PC_RAgri). To measure financial depth and local intermediation, four different measures are used: the share of total net loans over nominal gross regional domestic product (Credit), the share of total deposits over gross regional domestic product (Deposit), the number of banking offices per capita (Banking office density) and the total net loans over total deposits (Intermediation). To detect an additional effect of rural banks, two measures for rural banks presence are computed: the share of net loans granted by rural banks per region over total net loans granted per region (RB Credit share), and the share of total resources of rural banks per region over total resources for all banks per region (RB 4 Except for the CARAGA region which was created in

10 resources share). We perform these tests for four samples (all regions, economically developed regions, intermediate developed regions, and less economically developed regions). Table 2 presents the results of our correlation analysis for the different groups of series for the four samples of regions in the Philippines using Spearman rank-order tests. The null hypothesis is the absence of rank-order correlation between two series for a sample of regions. Table 2. Correlation Analysis: Spearman rank-order with PC_RGRDP as referent variable All regions Developed Intermediate Less developed regions regions developed regions - PC_RAgri *** *** Financial depth - Credit 033*** 041*** Deposit 044*** 084*** 047** 046** - Banking office density 052*** 048*** 014*** 058*** Local intermediation - Intermediation 081*** 085*** -097*** 010 Rural banks market share - RB Credit share -061*** -089*** 097*** 084*** - RB Resources share -080*** -053*** *** Boldface values denote a presence of a rank-order correlation. (***), (**) and (*) signify rejection of the null hypothesis of absence of rank-order correlation at the 1%, 5% and 10% levels respectively. Three main results are obtained from the rank order tests. First, for the four different samples, a positive and significant correlation between economic growth and financial depth at the regional level is obtained when financial depth is measured by banking office density and deposit. This result is consistent with the existing empirical literature on the finance growth nexus. The correlation obtained is stronger for the economically developed regions than for the intermediate and less economically developed regions. When credit is used as indicators of financial depth, the correlation is also significant for the economically developed regions but not for the intermediate and less economically developed regions. Results are the same as the latter for correlation between intermediation and PC_RGDRP. 10

11 Second, when considering the relationship between regional economic growth and the agricultural share a significant negative correlation is obtained between PC_RGDRP and PC_RAgri for the economically developed regions whereas the correlation is positive and significant for the less economically developed regions. In other words, as expected, the agricultural sector is of main importance to favor the growth of poor regions whereas the growth of the wealthy regions comes from the industrial and service sectors. Third, the most interesting result with regard to our issue is related to the role of rural banks on regional economic activity. A negative and significant correlation is obtained between growth and rural banks presence (whatever the indicators were used) on the sample all regions as well as for the economically developed regions. And for this last group, the effect is stronger. On the contrary, a positive and significant correlation is obtained between the variables PC_RGDRP and the market share of rural banks. For the less economically developed regions, we find that the higher the market share of rural banks, the higher is the economic growth. 4 Panel data tests The lack of agreement on the role, in terms of existence, the level or the direction of financial development in the process of economic growth is argued to arise primarily from the estimation techniques that should be properly applied to the available data set (Apergis et al. 2007). According to Apergis et al (2007), a problem with cross-sectional estimation is a possible omission to discuss the integration and cointegration properties of the data, leading to a failure to examine the direction of causality between financial development and economic growth. In estimating panel data, Apergis et al. (2007) point out that using instrumental variables and GMM dynamic panel estimators alone to account for potential biases induced by simultaneity of regressors, omitted variables and unobserved countryspecific effects on the finance-growth nexus may be insufficient and that the integration properties of the data should still be considered. In order to explore the long-run equilibrium relationship between finance and growth and to detect an additional positive effect of rural banks, we first conduct panel unit root tests. We used Im, Pesaran and Shin t-test 5. Results are presented in Table 3. 5 The IPS test is based on individual ADF regressions and assumes separate unit roots between the cross-sections units. 11

12 Table 3. Im, Pesaran and Shin (IPS) panel unit root tests Variable in level IPS Variable in first difference IPS PC_RGDRP 27-36*** Financial depth - Credit 05-25*** - Deposit -15** - Banking office density ** Local intermediation - Intermediation 01-27*** Rural banks market share - RB Credit share 67-24*** - RB Resources share 13-29*** (***), (**) and (*) signify rejection of the null hypothesis of absence of unit root at the 1%, 5% and 10% levels respectively. Panel unit root tests support the hypothesis of a unit root for most variables in level. For Deposit, we reject the null hypothesis at the 5% level with the IPS test and at the 10% level with ADF test. In first difference, unit root tests show that all variables are stationary. As a second step, we conduct panel cointegration tests. To test for the presence of a long run relationship between financial and economic development, we used the methodology proposed by Pedroni ((1999);(2004)). This procedure is based on Engle-Granger (1987) two-step cointegration tests. Pedroni proposed eleven statistics that allow for heterogeneous intercepts and trend coefficients across cross sections. Two alternatives hypothesis are tested: homogeneous alternative (within dimension tests) and heterogeneous alternative (group statistics tests). Cointegration tests are performed using alternatively as explanatory variables (i) one of the two I(1) measures for financial depth (Credit or Banking office density) 6 or the local intermediation variable and (ii) one of the two I(1) measures for rural banks market share (RB Credit share or RB Resources share). 6 The deposit variable is I(0). 12

13 We then test the null hypothesis of no cointegration relation for these different groups of variables over four samples. These samples have been chosen in light of the Spearman rank-order test. We focus our analysis mainly on the intermediate and less developed regions in order to identify the role played by rural banks. Table 4 reports the results of the panel cointegration tests. On the sample all regions, we find some evidence of cointegration relationship between financial and economic development. For three pairs of explanatory variables, seven of the eleven Pedroni statistics are significant, and for the three other pairs of explanatory variables, six statistics are significant. We therefore reject the null hypothesis of the absence of a long term relationship between finance and growth. When we restrict the sample to the less and intermediate economically developed regions, we obtain stronger evidence of a cointegration relationship for all pairs of explanatory variables (we can even reject the null hypothesis in nine cases for one pair (Credit; RB Credit share). Finally, we perform the panel cointegration tests over the less economically-developed regions sample. In most cases, the null hypothesis is rejected by four of the eleven Pedroni statistics. However stronger results are obtained when we add a restriction on the level of rural banks market share (based on the amount of loans granted). 13

14 Table 4. Pedroni panel cointegration tests: Number of significant statistics tests (over 11 statistics) Dependent variable: PC_RGDRP Rural bank market share Financial depth/local intermediation RB Credit share RB Resources share All regions (N 1 = 204 ; N 2 = 16) Credit 7 2 (***); 3 (**); 2(*) Banking office density 6 5 (***) ; 1 (**) Intermediation 7 3 (***) ; 4 (**) Intermediate developed regions (N 1 = 78 ; N 2 = 6) Credit Banking office density Intermediation Less developed regions (N 1 = 87 ; N 2 = 7) Credit Banking office density Intermediation 7 5 (***); 1 (**) 1 (*) 6 6 (***) 5 3 (***); 1 (**); 1 (*) 4 4 (**) 4 3 (***) ; 1 (*) 4 3 (***) ; 1 (*) 6 1 (***); 4 (**); 1(*) 6 1 (***) ; 2 (**) ; 3(*) 7 3 (***) ; 2 (**) ; 2(*) 1 1 (*) 4 3 (**); 1 (*) 3 1 (**); 2 (*) 4 3 (***) ; 1 (**) 3 1 (***); 1 (**); 1 (*) 4 3 (***); 1 (**) Less developed regions for which RB Credit share > 25% (N 1 = 48 ; N 2 = 4) 9 7 Credit 6 (***) ; 1 (**) ; 2 (*) 4 (***) ; 1 (**) ; 2(*) 7 4 Banking office density 3 (***) ; 3 (**) ; 1 (*) 2 (**); 2 (*) 7 7 Intermediation 6 (***) ; 1 (**) 4 (***); 1 (**); 2(*) The total number of significant calculated statistics is in bold. (***), (**) and (*) signify rejection of the null hypothesis of absence of a long run relationship at the 1%, 5% and 10% levels respectively. N 1 and N 2 are respectively the number of observations and the number of cross-section units. Table 5 displays the vector error correction estimates of the cointegration relationships, however only the long run estimations, and not for all pairs of variables, are shown, consistent with our research issue. We present the results only for the variable RB credit share because signs the coefficients are the 14

15 same as for RB resources share and their Pedroni statistics are better. Moreover with regard to the RB credit share variable, we do not display results with the local intermediation variable because the quality of the estimations is weak and does not allow a meaningful economic interpretation. The sample all regions, where the weight of the richest regions is obviously predominant, shows a counter-intuitive result that is a negative impact of financial depth on economic growth. This result might be explained by a strong decrease in the level of loans granted by commercial banks following the Asian crisis, whereas the economic activity recovered more rapidly. Indeed the role of commercial banks is of main importance for the country because of their strong presence especially in the wealthy regions. And therefore our results cannot establish any role for rural banks at the national level. When we study the sample of the intermediate economically developed regions, we find the same results as for the nationwide economy that we can interpret identically. On the contrary, when we analyze the seven less developed regions, our results show a positive impact of financial depth on economic growth. This effect is more substantial when financial depth is measured as the ratio of credit to gross regional domestic product than by banking office density. To favor the economic activity in these regions, it seems more important to facilitate the access to the credit market rather than to develop the number of offices. Moreover for this sample, we observe that rural bank presence impact positively on economic development as we could expect from the Spearman rank-order tests. These less developed regions, where the GRDP is mainly driven by the agricultural and fishery sector, fully benefit from the specificity of the rural finance well-fit to the primary sector. Finally, these results for the less developed regions are strengthened when we restrict this sample to the four regions (Ilocos, Cagayan Valley, Bicol, and CARAGA) for which the credit market share of the rural banks represents at least 25% of loans granted at the end of the studied period. Our results suggest that a threshold might exist, under which it is easiest to underline the link between financial and economic development. Above this threshold regional economic activity is mainly driven by real factors such as innovation, education, entrepreneurship, among others. 15

16 Table 5. Cointegration relationship: long run estimation between financial and economic development Dependent variable: PC_RGDRP Financial depth Credit Banking office density All regions (N 1 = 204 (Included observations = 156) ; N 2 = 16) Financial depth -14 (30) Rural bank credit market share -05 (-07) Intermediate developed regions (N 1 = 78 (Included observations = 60) ; N 2 = 6) Financial depth -28 (-30) Rural bank credit market share -07 (-02) Less developed regions (N 1 = 87 (Included observations = 66) ; N 2 = 7) Financial depth 733 (054) Rural bank credit market share 58 (14) -25 (-14) -07 (-02) -24 (-25) 05 (17) 09 (08) 18 (12) Less developed regions for which RB Credit share > 25% (N 1 = 48 (Included observations = 36) ; N 2 = 4) Financial depth 20 (53) 18 (40) Rural bank credit market share 04 (34) 01 (10) N 1 and N 2 are respectively the number of observations and the number of cross-section units. Section 5. Conclusion This paper aims to identify the role played by rural banks, as part of the Philippine financial nexus, on the economic development using macroeconomic data. The period studied on the one hand is relatively short because of data availability, and on the other hand, includes the Asian crisis which makes more difficult the identification of a long term relationship between financial and economic development. 16

17 As expected, our results cannot show an impact of rural banks at the national level because rural finance represents only a small proportion of the banking activity. However, in the case of the less developed regions, and when rural bank presence is relatively significant, an increase in the credit market share of rural banks strengthens the economic development of the region. Our research may encourage continuing government efforts aimed at developing the Philippine rural banking sector and in increasing the volume of investments in the regions. Policy implications may include the need to enhance confidence in the Philippine rural banking system, to encourage savings in regional rural banks, and to ensure efficient transfer of resources from savers to investors. 17

18 References Agabin, M., and J.L. Daly. (1996) An Alternative Approach to Rural Financial Intermediation: The Philippine Experience. Washington, D.C.: Chemonics International. Angbazo, L. (1997) Commercial bank net interest margins, default risk, interest-rate risk, and offbalance sheet banking, Journal of Banking and Finance, 21: Apergis, N., Filippidis, I. and Economidou, C. (2007) Financial Deepening and Economic Growth Linkages: A Panel Data Analysis, Review of World Economics, 143(1) Aziz, J. & Duenwald, C. (2002) Growth-Financial Intermediation Nexus in China, IMF Working Paper, WP/02/194. Bangko Sentral ng Pilipinas (2007), Manual of Regulations for Banks. Available: (Accessed 2007 June 28). Bandiera, O., Caprio, G., Honohan, P., and Schiantarelli, F (2000) Does financial reform raise or reduce private savings?, Review of Economics and Statistics, 82(2): Beck T., Levine, R. and Loayza, N. (2000) Finance and the sources of growth, Journal of Financial Economics, 58: Bencivenga, V. R. and Smith, B. D. (1991) Financial intermediation and endogenous growth, Review of Economic Studies, 58: Bencivenga, V. R. and Smith, B. D. (1998) Economic development and financial depth in a model with costly financial intermediation, Research in Economics, 52: Boyd, J. H. and E. C. Prescott (1986) Financial Intermediary Coalitions, Journal of Economic Theory, 38: Burgess, R. and Pande, R. (2005) Do Rural Banks Matter? Evidence from the Indian Social Banking Experiment, American Economic Review, 95(3): Calderón, C. and Liu, L. (2003) The direction of causality between financial development and economic growth, Journal of Development Economics, 72: Christopoulos, D. and Tsionas, G. (2004) Financial development and economic growth: evidence from panel unit root and cointegration tests, Journal of Development Economics 73: Dauner Gardiol, I., Helms, B., and Deshpande, R. (2005) Philippines. Country-Level Savings Assessment, CGAP Savings Initiative 18

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21 Table A1. Comparative Net Loan Portfolio of RCBs per Economic Sector (2005, ) Agriculture, Fisheries and Forestry (AFF) Industry (IND) Services (SERV) Region 2005 Average 2005 Average 2005 Average NCR 145% 177% 33% 104% 822% 729% CAR 416% 174% 93% 250% 481% 565% Northern Mindanao 397% 291% 01% 163% 602% 536% Davao 452% 445% 18% 26% 529% 529% Central Visayas 349% 222% 105% 296% 545% 482% South Luzon 439% 459% 94% 92% 467% 459% Western Visayas 590% 491% 22% 90% 388% 419% Socksargen 479% 319% 23% 123% 508% 558% Central Luzon 440% 450% 87% 85% 472% 455% Zamboanga Peninsula 367% 321% 11% 97% 613% 582% Ilocos 489% 263% 70% 238% 431% 499% Cagayan Valley 544% 505% 16% 156% 440% 339% CARAGA* 274% 303% 21% 38% 695% 669% Eastern Visayas 668% 508% 16% 165% 326% 337% Bicol 507% 514% 183% 154% 310% 332% ARMM 398% 139% 00% 143% 602% 728% Average 432% 344% 59% 138% 519% 517% 21

22 Figure A1. Regional Market Share in Offices of Banks ( ) Ilocos Northern Mindanao Davao Socsargen CAR ARMM CARAGA NCR Cagayan Valley Central Luzon South Luzon Bicol Western Visayas Central Visayas Eastern Visayas Zamboang a 22

23 Figure A2. Regional Market Share in Total Assets of Banks ( ) Ilocos Northern Mindanao Davao Socsargen CAR ARMM CARAGA NCR Cagayan Valley Central Luzon South Luzon Bicol Western Visayas Central Visayas Eastern Visayas Zamboanga

24 Figure A3. Regional Market Share in Deposit Liabilities of Banks ( ) Ilocos Northern Mindanao Davao Socsargen CAR 1 ARMM 1 CARAGA 1 NCR Cagayan Valley Central Luzon South Luzon Bicol Western Visayas Central Visayas Eastern Visayas Zamboanga

25 Figure A4. Regional Market Share in Net Loan Portfolio of Banks ( ) Ilocos Northern Mindanao Davao Socsargen CAR ARMM CARAGA NCR Cagayan Valley Central Luzon South Luzon Bicol Western Visayas Central Visayas Eastern Visayas Zamboanga

26 Figure A5. Average Intermedition Rates for the Period % 500% 400% 300% 200% 100% 0% Ilocos Cagayan Valley Central Luzon SouthLuzon Bicol Western Visayas Central Visayas Eastern Visayas Zamboanga Peninsula Northern Mindanao Davao Socksargen CAR ARMM CARAGA* NCR UKB TB RCB 26