Introduction
Financial development can unleash new growth sources by helping countries reap the benefits of globalization and make the transition to higher incomes. A recent focus has been on ensuring that gains from financial development can spread across the population. Central America, Panama, and the Dominican Republic have made significant strides in financial inclusion and development, with several countries having surpassed other non–Asian and Latin American emerging market and developing economies in boosting the enabling environment for financial inclusion.
While Figure 12.1 shows a simple correlation between incomes and growth, an extensive literature has documented the mostly positive impact from countries’ financial development. Efficient financial systems help channel funds to productive uses, provide insurance against shocks, reduce information asymmetries, and can alleviate poverty and inequality (Beck, Demirgüç-Kunt, and Levine 2004). Sound financial systems can foster innovation and entrepreneurship through risk diversification (King and Levine 1993).

Financial Development and PPP GDP per capita
Sources: World Development Indicators, Heng and others (2016), and IMF staff calculations.
Financial Development and PPP GDP per capita
Sources: World Development Indicators, Heng and others (2016), and IMF staff calculations.Financial Development and PPP GDP per capita
Sources: World Development Indicators, Heng and others (2016), and IMF staff calculations.Developments in financial services highlight the promise of financial inclusion in boosting growth while reducing poverty and inequality (Beck, Demirgüç-Kunt, and Levine 2007, Clarke, Xu, and Zou 2006). Financial inclusion helps mobilize savings and provides households and firms with greater access to the resources needed to finance consumption and investment, and so helps guard against income shocks. Financial inclusion also fosters labor and firm formalization— that is, it helps reduce informality—and has been positively linked with job creation, growth, and innovation (Beck, Demirgüç-Kunt, and Maksimovic 2005; Aiyagari, Demirgüç-Kunt, and Maksimovic, 2007). These, in turn, boost government revenues and strengthen social safety nets.
Advances in financial development and inclusion have not been broad-based in most CAPDR countries. While some countries stand out in certain areas (for example, Panama in financial development and Costa Rica for household inclusion), severe constraints remain in other areas (low household inclusion in Panama and high spreads and collateral requirements in Costa Rica). Thus, CAPDR has no clear champion for performing well on all aspects.
Given the region’s challenges with poverty and structural impediments to growth (such as crime and gender inequality discussed in Chapters 3 and 6), a careful deepening of financial systems and expansion of financial inclusion could help generate sustained and inclusive growth (Holden and Howell 2009; Aghion and others 2005). Such deepening could also bring insurance benefits by helping the countries (at the aggregate level) and households (at the micro level) cope with income shocks (Bhattacharya and Patnaik 2015). Deeper financial systems promote diversification and growth and have been found to be linked to financial stability (Sahay and others 2015; Heng and others 2016).
This chapter examines the current state of financial deepening and inclusion in CAPDR from several perspectives:
Use of the financial development index developed in Heng and others (2016) to examine financial market and institution development in the region compared with the rest of Latin America and Caribbean (LAC). This new approach uses a broad-based index that improves on narrower measures of financial deepening such as the private-credit-to-GDP ratio, the ratio of liquid liabilities of the financial system to GDP, stock market capitalization as a share of GDP, and the market turnover ratio (Levine 1997, 2005).
An examination of financial inclusion for households and small and medium enterprises (SMEs) in the region, including through a multidimensional financial inclusion index for households, SMEs, and access to financial services.
Trade-offs are then examined between inequality and growth when constraints to financial inclusion are loosened for enterprises using a quantitative model based on Dabla-Norris and others (2015), calibrated for CAPDR countries.
Finally, as a case study two CAPDR countries, Guatemala and Honduras, are examined in depth to illustrate potential policy considerations in countries where several financial constraints are significantly binding.
Stylized Facts on Financial Development
Using the broad-based index developed in Heng and others (2016), the analysis examines financial development of the CAPDR countries through two main pillars: financial institutions and financial markets. Each component is broken down into access, depth, and efficiency subcomponents (Figure 12.2). These subcomponents, in turn, are constructed based on several underlying variables that track development in each area.


The overall financial development index shows that all CAPDR countries improved in absolute terms between 1995 and 2013 (Figure 12.3). Their relative positions changed somewhat, with Guatemala going from second place in CAPDR to fourth place (behind El Salvador and Costa Rica) and significant gains from the Dominican Republic (which was in last place in 1995 at a much lower level than Nicaragua). Panama’s development levels reflect its role as a financial hub, and although the offshore sector is not directly measured in this index, the spillovers of technology and human capital have likely supported domestic development. El Salvador’s strong performance in the index is largely explained by strong market development, supported by debt markets, including for government debt. While Nicaragua appears as the least-developed LAC country for financial development, it is worth noting that two large regional banking groups are of Nicaraguan capital (Proamerica and Lafise).

Financial Development Index, 2013 versus 1995
Source: Based on index developed in IMF WP/16/81.Note: ARG = Argentina; BHS = The Bahamas; BOL = Bolivia; BRA = Brazil; BRB = Barbados; CHL = Chile; COL = Colombia; CRI = Costa Rica; DOM = Dominican Republic; ECU = Ecuador; GTM = Guatemala; HND = Honduras; JAM = Jamaica; MEX = Mexico; NIC = Nicaragua; PAN = Panama; PRY = Paraguay; PER = Peru; SLV = El Salvador; TTO = Trinidad and Tobago; URY = Uruguay; VEN = Venezuela. LAC = Latin America and the Caribbean.
Financial Development Index, 2013 versus 1995
Source: Based on index developed in IMF WP/16/81.Note: ARG = Argentina; BHS = The Bahamas; BOL = Bolivia; BRA = Brazil; BRB = Barbados; CHL = Chile; COL = Colombia; CRI = Costa Rica; DOM = Dominican Republic; ECU = Ecuador; GTM = Guatemala; HND = Honduras; JAM = Jamaica; MEX = Mexico; NIC = Nicaragua; PAN = Panama; PRY = Paraguay; PER = Peru; SLV = El Salvador; TTO = Trinidad and Tobago; URY = Uruguay; VEN = Venezuela. LAC = Latin America and the Caribbean.Financial Development Index, 2013 versus 1995
Source: Based on index developed in IMF WP/16/81.Note: ARG = Argentina; BHS = The Bahamas; BOL = Bolivia; BRA = Brazil; BRB = Barbados; CHL = Chile; COL = Colombia; CRI = Costa Rica; DOM = Dominican Republic; ECU = Ecuador; GTM = Guatemala; HND = Honduras; JAM = Jamaica; MEX = Mexico; NIC = Nicaragua; PAN = Panama; PRY = Paraguay; PER = Peru; SLV = El Salvador; TTO = Trinidad and Tobago; URY = Uruguay; VEN = Venezuela. LAC = Latin America and the Caribbean.Zooming in on the components of the index, CAPDR countries are broadly divided into three: (1) Panama, which leads the group, (2) Costa Rica, Guatemala, El Salvador, and Honduras in the middle, and (3) Nicaragua and the Dominican Republic, which lag (Figure 12.4). Each of these groups lags the previous one in nearly all categories, except for the Dominican Republic and Nicaragua in financial markets access, which are in line with the rest of CAPDR.

Financial Development Index: Ranking across Components
Sources: Heng and others (2016) and IMF staff calculations.Note: CAPDR = Central America, Panama, and the Dominican Republic; PAN = Panama; DOM = Dominican Republic; NIC = Nicaragua.
Financial Development Index: Ranking across Components
Sources: Heng and others (2016) and IMF staff calculations.Note: CAPDR = Central America, Panama, and the Dominican Republic; PAN = Panama; DOM = Dominican Republic; NIC = Nicaragua.Financial Development Index: Ranking across Components
Sources: Heng and others (2016) and IMF staff calculations.Note: CAPDR = Central America, Panama, and the Dominican Republic; PAN = Panama; DOM = Dominican Republic; NIC = Nicaragua.The region’s strong performance in institutions is partly explained by the prevalence of:
Large and successful conglomerates—with Guatemala, Honduras, and Nicaragua having home-grown conglomerates
ATMs and other access points, especially for Costa Rica (which has strong state banks) and Guatemala (with its strong presence of Banrural, a rural development bank)
Robust growth in credit to GDP and insurance markets (such as in Costa Rica).
Nevertheless, the region’s performance in financial institution efficiency could be improved, especially the high administration costs than have widened spreads. Past bank failures have also contributed to market consolidation, with different outcomes in Honduras and Guatemala. In Honduras, less efficient banks disappeared, leaving the market more competitive, while in Guatemala market concentration generated efficiency losses.
The region exhibits similar patterns in financial markets as in institutions. Panama again is the clear leader in CAPDR and the second-ranked LAC country for market depth, supported by financial, corporate, and public debt. El Salvador also ranks quite high due to its large public debt. When it comes to market access, the entire region (including Panama) ranks quite low, due to few issuers and small market capitalization for firms not ranked among the 10 biggest.
In general, financial markets in CAPDR appear somewhat underdeveloped compared to similar countries where financial institutions have reached comparable levels of development. For instance, for countries that score between 0.29–0.41 in the Financial Institutions subindex (which lists CAPDR countries except Nicaragua and the Dominican Republic), the average Financial Markets subindex is 0.17, compared to only 0.04 in CAPDR. This is partly because the productive sector remains relatively small in CAPDR when compared to banks (which are large regional entities) and because large corporations in some countries are family owned, which hinders public listings. Debt and insurance markets remain nascent throughout the region, and in some countries (for example, Guatemala) the government can only place as much debt as needed to finance the budget, restricting its ability to maintain market presence.
Zooming-in: Households and SMEs
Using the multidimensional indexes of Dabla-Norris and others (2015), the chapter next examines financial inclusion from three angles: (1) usage of financial services by households (Findex), (2) usage of financial services by SMEs (Enterprise Survey), and (3) access to financial institutions (Financial Access Survey). Figure 12.5 illustrates the indicators included in each of the indexes.

Financial Inclusion Indices
Source: Dabla-Norris and others (2015).Note: FAS = Financial Access Survey; SME = small and medium enterprise; WDI = World Development Indicators.
Financial Inclusion Indices
Source: Dabla-Norris and others (2015).Note: FAS = Financial Access Survey; SME = small and medium enterprise; WDI = World Development Indicators.Financial Inclusion Indices
Source: Dabla-Norris and others (2015).Note: FAS = Financial Access Survey; SME = small and medium enterprise; WDI = World Development Indicators.Despite notable improvements between 2011 and 2014, most of CAPDR continues to lag emerging markets on financial inclusion of households (Figure 12.6). The notable exception to this is Costa Rica, which in both 2011 and 2014 had surpassed the levels seen in other emerging markets. This large financial inclusion reflects, in part (1) the country’s higher levels of income per capita and education and much lower crime rates, which foster the use of ATMs and financial services, and (2) a long history of considering banking services a public good, supported by strong state banks that focus on access rather than profits.

Financial Inclusion of Households and SMEs
Source: Indices constructed in Dabla-Norris and others (2015).Note: ARG = Argentina; BLZ = Belize; BOL = Bolivia; BRA = Brazil; CHL = Chile; COL = Colombia; CRI = Costa Rica; DOM = Dominican Republic; ECU = Ecuador; GTM = Guatemala; HTI = Haiti; HND = Honduras; JAM = Jamaica; MEX = Mexico; NIC = Nicaragua; PAN = Panama; PER = Peru; PRY = Paraguay; SLV = El Salvador; TTO = Trinidad and Tobago; URY = Uruguay; VEN = Venezuela. EM = emerging market economies; LAC = Latin America and the Caribbean; SME = small and medium enterprises.
Financial Inclusion of Households and SMEs
Source: Indices constructed in Dabla-Norris and others (2015).Note: ARG = Argentina; BLZ = Belize; BOL = Bolivia; BRA = Brazil; CHL = Chile; COL = Colombia; CRI = Costa Rica; DOM = Dominican Republic; ECU = Ecuador; GTM = Guatemala; HTI = Haiti; HND = Honduras; JAM = Jamaica; MEX = Mexico; NIC = Nicaragua; PAN = Panama; PER = Peru; PRY = Paraguay; SLV = El Salvador; TTO = Trinidad and Tobago; URY = Uruguay; VEN = Venezuela. EM = emerging market economies; LAC = Latin America and the Caribbean; SME = small and medium enterprises.Financial Inclusion of Households and SMEs
Source: Indices constructed in Dabla-Norris and others (2015).Note: ARG = Argentina; BLZ = Belize; BOL = Bolivia; BRA = Brazil; CHL = Chile; COL = Colombia; CRI = Costa Rica; DOM = Dominican Republic; ECU = Ecuador; GTM = Guatemala; HTI = Haiti; HND = Honduras; JAM = Jamaica; MEX = Mexico; NIC = Nicaragua; PAN = Panama; PER = Peru; PRY = Paraguay; SLV = El Salvador; TTO = Trinidad and Tobago; URY = Uruguay; VEN = Venezuela. EM = emerging market economies; LAC = Latin America and the Caribbean; SME = small and medium enterprises.On average, CAPDR lags non-Asia/LAC EM in all subcategories of the index except for having a loan at a financial institution and saved at a financial institution. Particularly, only 41 percent in CAPDR report having an account at a formal institution versus 55 percent in non-Asia/LAC EM, with only 24 percent having a debit card (versus 40 percent). A key exception to this is, once again Costa Rica, where 65 percent of people have an account and 54 percent of them have a debit card. The reasons for gaps in other CAPDR countries could reflect a combination of factors, including lower levels of income and/or education. Indeed, surveys conducted in other LAC countries have found that the main reason cited for not having a bank account is often low income and the lack of need. Physical access is seldom cited as a constraint, as can be seen from Guatemala and Nicaragua having good access to financial infrastructure while scoring quite low in overall household use.
Reliance on nontraditional financing sources is quite high in CAPDR. In 2014, between 20 percent and nearly 45 percent of the population reported borrowing from informal channels, including family and friends. The banking correspondent model, however, has been making strides at “formalizing” financial services for many. This approach is helping to bridge the gap by allowing accessible retailers (food stores, gas stations, pharmacies) to act as an intermediary for basic financial transactions (deposits, withdrawal, and bill payments)1.
CAPDR on average performs much better in terms of financial inclusion of SMEs. Nearly 43 percent of firms have a loan or a credit line from banks (compared to 37 percent for non-Asia/LAC emerging market economies) and only 25 percent of firms report that financial access is a major constraint (contrast with 29 percent for non-Asia/LAC emerging market economies). However, only 20 percent of firms use banks to finance investments (versus 28 percent) and collateral amounts to 223 percent of the loan, in striking contrast with non-Asia/ LAC emerging market economies, where the corresponding number is only 135 percent. Reflecting their strong positions on the overall index, both El Salvador and the Dominican Republic have higher than non-Asia/LAC emerging market rates of firms using banks to finance investments and working capital, and more than half of firms report they have a bank loan or credit line.
Growth-Inequality Trade-offs
A micro-founded structural model borrowed from Dabla-Norris and others (2015) is used to examine the implications of relaxing various constraints to firms’ financial inclusion on growth and inequality. This model features agents born with different wealth and abilities who make choices between being workers or entrepreneurs. Agents can save without extra cost, but borrowing entails a fixed “participation cost” (see below). Once that cost is paid, the total amount that the agent can borrow will depend on the collateral posted. The “price” of borrowing will be determined by the economy’s spread between deposit and loan interest rates.2
The model is calibrated for each of the CAPDR countries. In the model, constraints to firms’ financial inclusion are grouped into three:
Participation costs, typically reflecting high documentation requirements by banks that impede access to finance (for example, for opening, maintaining, and closing accounts, and for loan applications). Other barriers can also be captured such as red tape and the need for guarantors. These are modelled as fixed costs, capturing that documentation requirements, while somewhat more onerous for very large scale projects, do not directly grow with loan or firm size.
Borrowing constraints are proxied by collateral requirements which regulate the leverage of firms in the credit system. These depend on factors such as creditors’ rights, information disclosure requirements, and contract enforcement procedures.
Intermediation costs (for example, high interest rates and fees) can reflect information asymmetries between banks and borrowers and limited competition in the banking system.
Key parameters are calibrated to match the moments of firm distribution, such as the percent of firms with credit and the firm employment distribution, as well as the economy-wide nonperforming loan ratio, and interest rate spread. As seen from Figure 12.7, when compared with advanced economies (which serve as proxies for the frontier), all countries in CAPDR lag in these indicators. For example, the percent of firms with access to credit in CAPDR is only 58 percent on average, about half of the 95 percent average in advanced economies. There are also significant differences across countries.
Constraints are most severe in Nicaragua, with the lowest proportion of firms with credit, the second highest interest spreads in the region, and the third highest level of collateral.
Two notable cases are those of the Dominican Republic and Guatemala, with the two lowest collateral requirements in the region. Interestingly, while interest rate spreads are relatively similar across the countries, the proportion of firms with credit is 64 percent in Dominican Republic versus 50 percent in Guatemala. As can be seen in the Guatemala case study, the low rates of access could be one of the drivers of the country’s low collateral and intermediation costs.
By contrast, Costa Rica has very high collateral and high interest rate spreads but relatively high levels rates of access with 60 percent of firms having credit.

Country-Specific Financial Constraints
Sources: World Bank Enterprise Surveys and author’s calculations.Note: AE = United Arab Emirates; ARG = Argentina; BLZ = Belize; BOL = Bolivia; BRA = Brazil; CHL = Chile; COL = Colombia; CRI = Costa Rica; DOM = Dominican Republic; ECU = Ecuador; GTM = Guatemala; HTI = Haiti; HND = Honduras; JAM = Jamaica; MEX = Mexico; NIC = Nicaragua; PAN = Panama; PRY = Paraguay; PER = Peru; SLV = El Salvador; TTO = Trinidad and Tobago; URY = Uruguay; VEN = Venezuela.
Country-Specific Financial Constraints
Sources: World Bank Enterprise Surveys and author’s calculations.Note: AE = United Arab Emirates; ARG = Argentina; BLZ = Belize; BOL = Bolivia; BRA = Brazil; CHL = Chile; COL = Colombia; CRI = Costa Rica; DOM = Dominican Republic; ECU = Ecuador; GTM = Guatemala; HTI = Haiti; HND = Honduras; JAM = Jamaica; MEX = Mexico; NIC = Nicaragua; PAN = Panama; PRY = Paraguay; PER = Peru; SLV = El Salvador; TTO = Trinidad and Tobago; URY = Uruguay; VEN = Venezuela.Country-Specific Financial Constraints
Sources: World Bank Enterprise Surveys and author’s calculations.Note: AE = United Arab Emirates; ARG = Argentina; BLZ = Belize; BOL = Bolivia; BRA = Brazil; CHL = Chile; COL = Colombia; CRI = Costa Rica; DOM = Dominican Republic; ECU = Ecuador; GTM = Guatemala; HTI = Haiti; HND = Honduras; JAM = Jamaica; MEX = Mexico; NIC = Nicaragua; PAN = Panama; PRY = Paraguay; PER = Peru; SLV = El Salvador; TTO = Trinidad and Tobago; URY = Uruguay; VEN = Venezuela.What are the effects to GDP and inequality from “removing” each of these constraints? To answer this question, three policy experiments are conducted:
1. relaxing collateral requirements to the world minimum,
2. reducing the participation cost to zero, and
3. reducing interest rate spreads to zero.
These policy changes are, of course, quite significant and would take time to phase-in.3 For ease of comparison, each of the economies is modeled before and after the full transition—that is, “steady states” are examined. The numbers presented below should therefore be interpreted as cumulative changes to GDP and Gini across several years, driven by the implementation of each of these policies alone. Across all CAPDR countries, the loosening of any of the three constraints increases GDP (Figure 12.8), while the loosening of participation costs reduces inequality for all but the lowering of collateral constraints generates mixed results. Each of these aspects is now discussed in detail.

Effects on GDP and Gini from Relaxing Constraints
Source: IMF staff calculations.Note: CRI = Costa Rica; DOM = Dominican Republic; GTM = Guatemala; HND = Honduras; NIC = Nicaragua; PAN = Panama; SLV = El Salvador.
Effects on GDP and Gini from Relaxing Constraints
Source: IMF staff calculations.Note: CRI = Costa Rica; DOM = Dominican Republic; GTM = Guatemala; HND = Honduras; NIC = Nicaragua; PAN = Panama; SLV = El Salvador.Effects on GDP and Gini from Relaxing Constraints
Source: IMF staff calculations.Note: CRI = Costa Rica; DOM = Dominican Republic; GTM = Guatemala; HND = Honduras; NIC = Nicaragua; PAN = Panama; SLV = El Salvador.Relaxing Borrowing Constraints
The largest GDP gains accrue from lowering collateral requirements. The model predicts that the total cumulative expansion of the CAPDR countries’ GDP could range between 13 and 22 percent if all collateral requirements were lowered to 50 percent, which is the lowest average collateral across countries in the World Enterprise Surveys. However, the size of GDP gains across countries depends on the other constraints. For instance, Honduras and El Salvador post significant gains driven by a combination of currently relatively large collateral and medium-sized constraints in other areas. When collateral constraints are loosened, firms can take full advantage since the other constraints are relatively benign.
Lowering collateral constraints will exacerbate inequality for some countries. While everybody benefits from borrowing more against the same level of collateral, productive firms in the economy benefit more because they have the most to gain from expanding the scale of their operations. Higher leverage leads to more investment for larger firms, which generates higher scale of production therefore boosting growth. These gains, however, accrue more to the top of the distribution (larger, wealthier firms), therefore worsening inequality. The countries for which lower levels of collateral lead to an improved level of inequality are the ones where collateral levels are already low—the larger (and more productive firms) are already near optimal levels so the expansion benefits smaller firms.
Lowering Participation Costs
Reducing participation costs to zero has smaller positive effects on GDP, ranging from about 2 to 6 percent. These gains tend to be higher for countries where small enterprises account for a larger portion of the economy. For example, in the Dominican Republic, El Salvador, and Panama, which gain more than 5 percent, the top 20 percent of largest firms account only for 69 percent of employment versus the case in Guatemala and Honduras (which gain about 3 percent), where the top 20 percent of firms account for 82 percent of employment. Moreover, these gains are also supported by relatively low spreads and collateral requirements which allows the smaller firms to fully take advantage of the credit market once they enter.
The participation cost, which is a fixed cost reflecting regulatory requirements, documentation, and red tape, is a more binding constraint for smaller firms (Krešić and others 2017) and therefore unambiguously improves inequality when lowered. In a sense, this is the most binding constraint on an extensive margin, as it largely determines how many firms have credit access but not directly how much credit. The size of the impact on inequality, once again, depends on how country-specific factors interact with financial sector characteristics. Once again, the large impact on inequality reduction for the Dominican Republic and Panama is partly driven by the dominance of small firms.
Lowering Intermediation Costs
Both growth and inequality in CAPDR are the least responsive to lowering the interest rate spread. Just as for collateral requirements, loosening this constraint mostly benefits those firms that already have access to credit, generating a positive impact on growth but a worsening in inequality. Contrary to collateral requirements, however, lower spreads make credit cheaper without directly expanding leverage; the impact is strongest among medium-sized firms for which these credit costs represent a larger proportion of their overall costs. A loosening of this constraint does little to help small firms excluded from credit markets for other reasons (for example, participation constraints), and it does not significantly hurt the most productive firms, which were already bearing the higher spreads in their borrowing. Hence, reducing interest rates has a smaller impact on growth and may actually widen inequality.
Combined Effect of all Constraints
The analysis above, based on relaxing individual constraints, shows that the benefits come with trade-offs. While the model suggests that the relaxation of the collateral requirement will generate the highest increase in growth, it could also exacerbate inequality; lowering participation costs will also boost growth but by a little less and will reduce inequality.
So what happens when all three constraints are loosened concurrently? There are interactions between the various constraints; therefore, the joint effect on GDP is more than the additive effect of loosening each constraint in isolation. With regard to inequality, it also declines on net for all CAPDR countries. Note however that in this case the nonlinear effect may worsen inequality, especially for countries where loosening collateral constraints and spreads both worsened inequality (their joint effect is stronger than the sum of their isolated effects).
Last, and while not directly included in the model, stability factors should inform the decision on which constraints to loosen. Policies such as reducing collateral constraints and lowering participation costs, while beneficial for growth and inequality, could also expose the economy to instability. For example, high leverage levels and the entry of lower-productivity/higher-risk firms into the credit market could increase nonperforming loans, which are already high in some countries. A strong regulatory environment will be paramount to ensure continued financial stability as inclusion policies move along.
Case Studies
As the model demonstrated, there is no “one-size-fits-all” solution to improving financial inclusion; the most binding constraints and drivers vary by country. This subsection examines the situation in two CAPDR countries to help shed light on the different constraints to financial inclusion and potential policies.
Guatemala
Guatemala’s income distribution is one of the most unequal in the world, with a Gini coefficient of 52 in 2011. One-tenth of the population receives about half of total income while nearly one-third of the population lives on less than $2 a day. Literacy rates are low (at 70 percent) and there is a strong urban-rural divide, both partly reflecting low infrastructure and social and education spending. Although GDP growth since the global financial crisis of 2008 has been robust, PPP GDP per capita remains low, at about $7,500.
As in many other countries in LAC, gross national savings are low, at about 12 percent of GDP on average. Banking penetration is shallow, with only 40 percent of the population having an account at a financial institution in 2014. In a country where labor informality exceeds 70 percent, the use of savings clubs reached 12 percent in 2014, and while one-fifth of the population reports borrowing from family and friends, just 12 percent borrow from financial institutions.
Among SMEs, access is relatively low, with 60 percent of firms reporting having a checking/saving account (compared to a LAC average of 92 percent) and 45 percent having lines of credit with a bank (LAC average of 46 percent). However, this low access does not appear to be driven by high costs or large collateral; deposit-lending spreads are about 8 percentage points, and collateral averages 117 percent of the loan (versus 201 percent in the wider region). Relatively low collateral and spreads reflect the high concentration of credit among a small number of large clients. Since a large part of banks’ business is with a small group of clients who are well known to them, risks remain low and informational asymmetries are greatly reduced.
According to the comparative statics results of the model, the loosening of any of the three constraints will generate an improvement in growth but the lowering of spreads and collateral requirements would worsen inequality. Intuitively, this is because, due to their already relatively low levels, the loosening of these two constraints generates much larger marginal benefits for those at the top of the talent and wealth piles than those at the bottom. In this situation, very talented or very wealthy entrepreneurs can significantly increase their leverage and their production.
Given large income inequality in Guatemala, policies that focus on loosening participation constraints should be a key first step. Increasing social spending, especially on education, and implementing a national plan for financial inclusion aimed at fostering financial literacy, would help bridge entry barriers for those who remain outside of the financial system. As demand-side barriers are addressed, regulators should also examine financial institutions’ lending practices and credit concentration limits. While basic regulation is in place, there are instances where the ultimate beneficiary of loans is not clear since firms are registered under several names. Finally, as participation barriers are relaxed and previously unbanked businesses enter the financial system, credit bureau implementation should be improved to lower information costs (and collateral requirements), especially for new clients. At the same time, increased competition in the banking sector should be promoted to improve efficiency and maintain low spreads.
El Salvador
In recent years, El Salvador has made significant strides in reducing inequality as evidenced by the decline in its Gini index from 53 in 2000 to 42 in 2012. However, economic growth has been anemic, averaging under 2 percent for the past decade. The country is also plagued by emigration to the United States, as the young seek better economic opportunities and an escape from violence—in 2014, there were 68.6 homicides per 100,000 people, making it one of the most violent countries in the world (see Chapter 6).
Gross national savings at only 9.5 percent are even lower than in Guatemala. Despite a history of lending through large national banks with a regional presence, banking penetration is low, with only 35 percent of the population having a bank account at a financial institution in 2014. The proportion of people who save either at a financial institution or a savings club is also lower than in Guatemala (only 7 percent used the latter in 2014). Nevertheless, the proportion of those who borrow from banks is much higher in El Salvador (17 percent versus 12 percent in Guatemala).
Financial inclusion of enterprises appears well developed, with both low cost of funds, low collateral requirements, and significant usage. Loan-deposit spreads are among the lowest in the region (at under 5 percentage points) and collateral requirements are at about 120 percent, below the LAC average of 138 percent. Over 90 percent of firms report having a bank account and about half of them have a line of credit. Contrary to Guatemala, low collateral and spreads in El Salvador likely reflect a banking sector that has had a history of large domestic banks with regional presence, which were bought first by global banks and then by Colombian conglomerates, which own nearly two-thirds of the current banking system assets. The credit bureau system is relatively well developed in El Salvador, covering over 80 percent of the adult population. Furthermore, the microfinance sector is quite well developed, with a significant presence of savings and loan societies and cooperative banks, although they remain mostly unregulated.
Comparative statics results from the model point to a significant positive effect on growth from lowering collateral levels, which is coupled with a worsening of inequality. In the case of Guatemala, this is because the marginal benefits of such a move benefit the wealthy and those who have higher productivity. In a country whose main goal would be to raise growth, policymakers need to evaluate to what extent the trade-off with worsening inequality in the short term would be worthwhile. In the case of El Salvador, where a focus on improving growth is warranted, relaxing collateral requirements and lowering spreads could have significant positive effects for firms at the top of the productivity distribution—the marginal gains for these firms are larger. However, a relaxation of already-low collateral constraints could have significant effects on financial system stability.4 For this reason, it would be important to couple reforms to promote growth through lower collateral requirements with measures to strengthen regulation and supervision (Sahay and others 2015). Given that El Salvador is a fully dollarized economy without a lender of last resort, a strong crisis management and resolution framework should also be implemented.
Conclusion and Policy Implications
Wide variation across CAPDR countries exists for financial systems development and inclusion. While Panama leads in financial development, financial inclusion of households and SMEs lags that of other countries in the region. In contrast, the Dominican Republic performs quite well both in inclusion of households and SMEs but lags in overall development.
Financial development could be improved. The financial development CAPDR countries (except for Panama) remains in the lower range of LAC. There is scope for improvement, but care should be taken to safeguard financial stability. Policies that may be pertinent for these countries include strengthening institutional and legal frameworks related to property rights and collateral registries, and improving the credibility of financial systems and deposit insurance, enhancing capital and liquidity buffers, and addressing balance sheet mismatches.
Policies to support SMEs are warranted. Key support measures include understanding the determinants of bank fees and charges, examining the existence of and eliminating predatory practices, and reviewing the adequacy of banking sector competition (including the framework for entry). As financial inclusion improves and more users enter the market, measures to reduce information costs (strong credit bureaus), efforts to reduce operational costs (using mobile networks and correspondent banking), and measures to improve the efficiency of courts and collateral recovery systems are necessary.
There is no silver bullet for easing financial constraints. There are trade-offs between growth, inequality, and financial stability; all should be considered when policies are designed. For example, even though policies aimed at lowering collateral requirements (such as strengthening the legal framework for managing and seizing collateral, reducing the size of collateral requirements, and creating modern collateral registries) are mostly beneficial for growth, they may also lead to higher inequality as marginal benefits accrue to the top of the distribution. In contrast, policies aimed at reducing participation costs (for example, lowering documentation requirements and reducing red tape and the need for informal guarantors to access finance) could help reduce inequality but may not yield comparable growth benefits.
There are synergies from a multipronged approach. The joint loosening of multiple constraints is likely to yield larger returns (higher growth and lower inequality) than the sum of loosening several constraints sequentially. However, the transition to that final state may also entail temporary increases in inequality. Tailored policies require a clear understanding of country-specific constraints, priorities, and timelines. Last, significant care should be taken to ensure that a strong framework for financial regulation and consumer protection is in place to safeguard the benefits of expanded financial inclusion without jeopardizing financial stability.
References
Aghion, P., Bloom, N., Blundell, R., Griffith, R. and Howitt, P., 2005. Competition and Innovation: An Inverted-U Relationship. The Quarterly Journal of Economics, 120(2), pp.701–728.
Aiyagari, M., A. Demirgüç-Kunt, and V. Maksimovic, 2007, “Firm Innovation in Emerging Markets,” World Bank Policy Research Working Paper 4157.
Beck, T., A. Demirgüç-Kunt and R. Levine. 2004. “Finance, Inequality and Poverty: Cross Country Evidence.” NBER Working Paper, No. 10979.
Beck, T., Demirgüç-Kunt, A. and Levine, R., 2007. Finance, inequality and the poor. Journal of economic growth, 12(1), pp. 27–49.
Beck, T., Demirgüç-Kunt, A.S.L.I. and Maksimovic, V., 2005. Financial and legal constraints to growth: Does firm size matter?. The Journal of Finance, 60(1), pp. 137–177.
Bhattacharya, R., I. Patnaik, 2015. Financial Inclusion, Productivity Shocks, and Consumption Volatility in Emerging Economies. The World Bank Economic Review 30(1), pp. 171–201.
Clarke, G. R., Xu, L.C. and Zou, H. F., 2006. Finance and income inequality: what do the data tell us? Southern economic Journal, pp.578–596.
Dabla-Norris, M. E., Ji, Y., Townsend, R. and Unsal, D. F., 2015. Identifying constraints to financial inclusion and their impact on GDP and inequality: A structural framework for policy (No. 15–22). International Monetary Fund.
Heng, Dyna, Anna Ivanova, Rodrigo Mariscal, Uma Ramakrishnan, and Joyce Wong. 2016. Advancing Financial Development in Latin America and the Caribbean. No. 16/81. International Monetary Fund.
King, R. G., and R. Levine. 1993. “Finance, Entrepreneurship and Growth.” Journal of Monetary Economics, Vol. 32, No. 3, pp. 513–542.
Krešić, A., J. Milatović, and P. Sanfey. 2017. “Firm Performance and Obstacles to Doing Business in the Western Balkans.” EBRD Working Paper 200, European Bank for Reconstruction and Development, London.
Levine, R., 1997. Financial development and economic growth: views and agenda. Journal of economic literature, 35(2), pp.688–726.
Levine, R., 2005. Finance and growth: theory and evidence. Handbook of economic growth, 1, pp.865–934.
Sahay, R., M. Cihak, P. N’Diaye, A. Barajas, D. Ayala Pena, R. Bi, Y. Gao, A. Kyobe, L. Nguyen, C. Saborowski, K. Svirydzenka, and R. Yousefi. 2015. “Rethinking Financial Deepening: Stability and Growth in Emerging Markets”, IMF Staff Discussion Notes No. 15–8.
Banking correspondents refer to nonfinancial commercial establishments that ofer basic financial services under the name of a financial services provider, becoming access points to the formal financial system. This difers from correspondent banks, which are financial institutions that provide services on behalf of other banks, mostly located in a diferent country.
For more details, please see Dabla-Norris and others 2015.
The lowering of spreads and participation costs to zero should be interpreted as an idealized frontier for ease of comparison. In reality, it is not likely that all barriers to credit are eliminated nor that there would be a zero margin to financial intermediation services.
Given the model’s assumption of a closed economy, interest rate spreads automatically adjust when nonperforming loans begin rising and thus function as a stabilizer. Tus, bad debt does not rise excessively in model simulations.