Journal Issue

Costa Rica: Selected Issues and Analytical Notes

International Monetary Fund. Western Hemisphere Dept.
Published Date:
May 2016
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Financial Inclusion in Costa Rica1

This note examines the current status of financial inclusion in Costa Rica, identifies the remaining gaps, and analyzes the impact on growth and inequality of removing impediments to financial inclusion. Costa Rica has excelled on household inclusion but lags behind on enterprise inclusion, compared to both other emerging markets and the country’s own fundamentals. Financial physical infrastructure could also be improved. Financial inclusion policies in Costa Rica should focus on modernizing the collateral framework and strengthening regulatory environment in the first instance. Improving efficiency of financial intermediation by ensuring the level playing field for private banks could also help improve inclusion and raise economic growth but inequality might also rise in tandem.

A. Introduction

1. The benefits of financial inclusion could be notable in Costa Rica. Financial inclusion holds the promise of boosting economic growth and reducing poverty and inequality, notably by mobilizing savings and providing households and firms with greater access to resources needed to finance consumption and investment and to insure against shocks. In addition, financial inclusion can foster labor and firm formalization, helping, in turn, to boost government revenues and strengthen social safety nets. Given modest potential growth, rising inequality as well as low savings and investment in Costa Rica, the benefits from further financial inclusion could be pronounced.

2. The note takes two separate approaches for examining different facets of financial inclusion and its impediments in Costa Rica.2 First, an empirical approach focuses on measuring financial inclusion, identifying financial inclusion gaps, their underlying drivers, and policy actions that could help narrow them. It is based on a composite measure of household and firm financial inclusion as well as access to financial infrastructure using the recently updated FINDEX dataset (World Bank), the Enterprise Survey (World Bank), and the Financial Access Survey (IMF). These measures allow placing Costa Rica in a temporal and cross-country perspective. Second, a novel theoretical framework is employed to identify the most binding financial sector frictions that impede financial inclusion in Costa Rica on enterprise side. This framework allows examining the implications of alleviating financial frictions on both inequality and growth.

B. Empirical Approach

B1. Where Does Costa Rica Stand on Financial Inclusion Compared to Peers?

3. Costa Rica has excelled on financial inclusion of households but lags behind peers on inclusion of enterprises and access to financial infrastructure (Figure 1). Costa Rica has made important strides on household inclusion over the past few years, with the largest improvements in account holdings, usage of ATMs, and debit cards. The country now stands as one of the champions on financial inclusion of households among LAC countries. It also compares favorably on this dimension to other emerging markets. In fact, it outperforms its peers on all of the subcomponents of the household financial inclusion index. However, the country is lagging behind its peers on the inclusion of enterprises. This reflects, in particular, high collateral requirements compared to other emerging markets. Access to and cost of finance is also seen as a major constraint by a large share of SMEs in Costa Rica. This, in part, may reflect relatively weak access to financial institutions as measured by the number of bank branches and ATMs in relation to population and area. Some countries have been successful at filling this last void using mobile phones and correspondents banking but in Costa Rica’s case, these measures also compare poorly to peers.

Figure 1.Financial Inclusion in Costa Rica and Emerging Markets

Access to Financial Services: Mobile versus Infrastructure

4. Costa Rica also lags behind on creating an enabling environment for financial inclusion. It scores below the average of other emerging markets on the Global Microscope index, which assesses the regulatory environment for financial inclusion across 12 indicators and 55 countries. This is in contrast to many LAC countries which score well on this index, with Peru being the world champion. Costa Rica performs well on prudential regulation and is ahead of other LAC countries on credit reporting systems, but it underperforms on all other indicators, namely, regulation and supervision of deposit-taking activities, regulation and supervision of branches and agents, regulation and supervision of credit portfolios, grievance redress and operation of dispute resolution mechanisms, market conduct rules, requirements for non-regulated lenders, regulatory and supervisory capacity for financial inclusion, regulation of electronic payments, regulation of insurance for low-income populations, and government support for financial inclusion. High financial inclusion of households and weak regulatory environment may seem contradictory but as shown below we find that the Microscope score is more relevant for explaining the inclusion of enterprises.

B2. Where Does Costa Rica Stand on Financial Inclusion Compared to Macroeconomic Fundamentals?

5. Financial inclusion gaps help account for the differences in the underlying macroeconomic conditions. We compute financial inclusion gaps with respect to own fundamentals as deviations of financial inclusion indices from the values predicted by the exogenous domestic factors such as income per capita, education, size of the shadow economy, the rule of law, the share of foreign-owned firms, and importance of fuel exports. The calculated negative gaps may capture possible distortions or market frictions while positive gaps may reflect financial excesses.3 We find that financial inclusion is higher in countries with the following characteristics (Table 1 and Dabla -Norris et al, 2015): higher income per capita (for households and firms), higher education (for households), stronger rule of law (for households), lower degree of informality (for households), lower prevalence of foreign-owned firms (for firms and access to financial institutions), lower fuel exports (for firms and access to financial institutions). In the longer run, as domestic fundamentals continue to improve, there may be scope for further gains in financial inclusion. To identify such possibilities, we have constructed gaps with respect to an Asian benchmark—a recognized success story on financial inclusion in countries with relatively strong fundamentals.

Table 1.Costa Rica: Financial Inclusion and Fundamentals
Access to Financial
Institutions (Physical
VARIABLESHH 2011HH 2011 &2014HH 2014FirmInfrustructure)
Mean years of schooling (of adults) (years)0.0173**0.0160***0.0162**0.00927−0.0189
Shadow Economies Index−0.00118−0.00188*−0.00268*−0.0008720.00149
Fuel exports (% of merchandise exports)−0.000506−0.000389−0.000285−0.00235**−0.00200*
Prevalence of foreign ownership, 1-7 (best)−0.0281−0.01590.00585−0.107***−0.0634**
Rule of Law (-2.5(weak) to 2.5(strong))0.0733***0.0657***0.0502**0.06700.0330
Robust standard errors in parentheses*** p<0.01, ** p<0.05, * p<0.1
Robust standard errors in parentheses*** p<0.01, ** p<0.05, * p<0.1

6. Costa Rica has a positive financial inclusion gap for households but a negative financial inclusion gap for enterprises. It is broadly in line with fundamentals on account holding while the positive gaps on ATM and debit card usage outweigh negative gaps on savings and borrowing from a financial institution and the usage of credit cards resulting in an overall positive household inclusion gap. In contrast to many other LAC countries, Costa Rica has positive financial inclusion gap also with respect to an Asian benchmark and there are no obvious indications that the positive household gap reflects excesses or inefficiencies. Hence, Costa Rica appears to be at the frontier on household inclusion. On the firm side, however, the overall gap with respect to own fundamentals is negative. The negative gap reflects high value of collateral, high share of firms identifying access to/cost of finance as a constraint, and low usage of banks by SMEs to finance investment and working capital, which outweigh the positive gaps on savings and checking account holdings as well as high share of SMEs having a loan or credit line from the bank. The large negative gap on collateral required for a loan can be linked to the weak legal collateral framework. The high cost of financing is, in part, due to the substantial presence of public banks, which lack incentives to improve efficiency. The gap with respect to an Asian benchmark on the firm side is also negative suggesting potential gains in firm inclusion over the longer run as fundamentals continue to improve.

7. An econometric examination of the factors behind financial inclusion gaps reveals the importance of strengthening the regulatory environment in Costa Rica. The results of a simple regression analysis (Table 2 and Dabla-Norris et al) suggest that higher (more positive/less negative) financial inclusion gaps with respect to domestic fundamentals are associated with lower non-interest income (for household and firms), lower bank safety buffers (for households), lower bank efficiency, as measured by the overhead costs (for firms) and stronger regulatory environment, as measured by the Global Microscope score (for firms). However, the direction of causality is not clear, in particular in the case of bank safety buffers and efficiency, which could be the result of increased inclusion rather than themselves being the driver of inclusion. In the case of Costa Rica, one obvious recommendation that results from this analysis is that strengthening the regulatory environment for financial inclusion (as measured by the Global Microscope) could help improve inclusion of firms. In particular, putting in place regulatory incentives to formalize micro-lenders/savers (which are currently constituted as non-regulated NGOs) and explicit regulations related to banking agents, e-money and micro-insurance would help bring many of these activities, which currently exist, into the light. However, this analysis is only partial and other factors, as indicated above, are likely at play.

Table 2.Costa Rica: Determinants of the Financial Inclusion Gaps
HH FI GapFirm FI GapAccess Gap
Non-Interest Income / Total income (%)−0.00428**−0.00515*0.00272
Bank net interest margin (%)−0.0144−0.02020.0399
3 Bank Asset Concentration (%)0.0009870.0008950.000984
Overhead Costs / Total Assets (%)0.01830.0320*−0.0216
Microscope-Overall Score (0-100, 100 best)0.0004300.00314*0.000585
Distance to default−0.00261**−0.00243−0.000316
Robust standard errors in parentheses*** p<0.01, ** p<0.05, * p<0.1
Robust standard errors in parentheses*** p<0.01, ** p<0.05, * p<0.1

C. Theoretical Approach

8. We apply a micro-founded structural model to shed light on the implications of relaxation of various constraints to financial inclusion for fostering growth and reducing inequality. (See Appendix and Dabla-Norris et al. (2015) for model description).

We group financial constraints into three broad dimensions:

  • Participation costs. These typically reflect high documentation requirements by banks for opening, maintaining, and closing accounts, and for loan applications that impede access to finance. These can also reflect various forms of barriers, including red tape and the need for informal guarantors as connections to access finance.

  • Borrowing constraints. The amount firms can borrow (the depth of credit) once they have access to banking systems is generally determined by collateral requirements, which depend on the state of creditors’ rights, information disclosure requirements, and contract enforcement procedures, among others.

  • Intermediation costs. High intermediation costs resulting from information asymmetries between banks and borrowers and limited competition in the banking system can lead to smaller and less capitalized borrowers being charged higher interest rates and fees.

The model’s key parameters are calibrated to match the moments of firm distribution, such as the percent of firms with credit and firm employment distribution, as well as the economy-wide nonperforming loan ratio and interest rate spread (Figure 4). We conduct policy experiments to identify the most binding constraints to financial inclusion and examine the macroeconomic effects of removing these constraints (Figure 5). Three illustrative simulations include: (i) reducing the financial participation cost to 0, (ii) relaxing borrowing constraints in the form of collateral requirements to the world minimum (iii) increasing intermediation efficiency (i.e., reducing monitoring costs to 0 by equalizing spreads to the proportion of non-performing loans).4

Figure 2.Enabling Environment for Financial Inclusion

Figure 3.Financial Inclusion Gaps

Source: Authors’ calculations.

Figure 4.Country-Specific Financial Constraints

Source: World Bank Enterprise Surveys.

Figure 5.Impact of Reducing Financial Constraints on GDP and Inequality

Source: Authors’ calculations.

9. The results suggest that there can be policy tradeoffs between achieving growth and equity objectives. A decline in financial constraints pushes up GDP through several channels. A lower participation cost enables more firms to have access to the formal banking system, leading to more capital invested in production. Moreover, lower financial frictions result in a more efficient allocation of funds and higher productivity as the best firms increase their scale of production. Finally, fewer funds are wasted in unproductive contract negotiation, freeing up more capital for investment. The impact on GDP, however, varies across countries, depending on country-specific characteristics and the underlying constraint being alleviated. The model findings suggest that the highest growth dividends accrue from a relaxation of collateral requirements, but this policy may drive up inequality since the main benefits of this policy accrue to those entrepreneurs which are most productive, already have access to credit, and thus already have higher incomes. This increase in inequality, however, could be alleviated if the relaxation of the collateral constraint also benefits previously constrained entrepreneurs. Similar trade-offs occur with the reduction in intermediation costs but not with participation costs (which tend to bind those outside the financial system more). In general, entrepreneurs who are already included in the financial system benefit more from the reduction in collateral requirements and less so from a reduction in the participation cost which is a fixed cost and a relatively lower share of their income. Lower participation costs, however, benefit new entrepreneurs more, thereby decreasing inequality.5 Nevertheless, the “poor” may still be better off overall under the lower borrowing constraints scenario, albeit with smaller gains than the “rich.”

10. Costa Rica faces substantial borrowing and intermediation costs. The share of firms with access to credit in Costa Rica is close to 60 percent, which places it at the average of the Central American countries. While the number of firms that have access to finance is relatively good, at least compared to Central American countries, Costa Rica has the highest collateral-to-loan ratio in the region. Collateral needed for loans by firms in Costa Rica is 1.5 times higher in Guatemala, for example. Similarly, Costa Rica tops the list of Central American countries on the interest rate spreads (the difference between lending and deposit rates), which are 2.5 times higher in Costa Rica than in Panama and El Salvador.

11. Costa Rica could raise growth by relaxing collateral constraints and lowering intermediation costs but only the former will provide the added benefit of lowering inequality. Collateral levels are so high in Costa Rica that a significant number of firms remain constrained in the amount of borrowing they can access (even those which have a positive level of credit). Because of this, the benefits of lower collateral accrue not only to those firms at the top of the distribution, but also a large mass of medium-sized firms, some of which expand significantly, driving up workers’ wages and lower inequality. In contrast, a reduction in monitoring costs, while providing high growth benefits, may lead to a moderate increase in inequality as the marginal benefit of their reduction accrues much more to those firms which already have credit access and thus also tend to be higher-income entrepreneurs. The reason why the relaxation of these two constraints has differing effects on inequality is explained by their different effects on the extensive and intensive margins of credit access. While the lowering of collateral constraints (which are unusually high) will both help bring new entrepreneurs into the credit net and relieve constraints for some which already have credit, the change in the intermediation costs affects mainly the intensive margin, thus mostly benefitting those entrepreneurs which already have credit and are unconstrained.

D. Conclusions and Policy Recommendations

  • Costa Rica has excelled in financial inclusion of households, but lags behind other emerging markets on the inclusion of enterprises and access to financial physical infrastructure. The country has made important strides in household inclusion over the past few years, with the largest improvements in account holdings, usage of ATMs, and debit cards.

    • Costa Rica also lags behind peers on creating enabling environment for financial inclusion. While the country performs well on prudential regulation and is ahead of other LAC countries on credit reporting systems, the fact that large portions of the financial system remain outside of the regulatory perimeter hinders further inclusion.

  • Even after accounting for differences in macroeconomic fundamentals, Costa Rica has a positive financial inclusion gap for households but a negative gap for enterprises. The negative gap on firm inclusion reflects high value of collateral required for a loan, which can be linked to the weak legal collateral framework, and high cost of financing, which can be related to the dominance of public banks that lack incentives to improve efficiency, an uneven playing ground for private banks that stifles competition, and weak regulatory environment for financial inclusion.

  • Costa Rica could raise growth by relaxing collateral constraints and intermediation costs, but only the former will provide the added benefit of lowering inequality. More generally, the results of the micro-founded general equilibrium model suggest that there may be a trade-off between the objectives of growth and inequality reduction.

  • Financial inclusion policies in Costa Rica should focus on further modernizing the collateral framework and strengthening regulatory environment in the first instance. Ensuring the level playing field for private banks compared to public banks, which can help lower intermediation costs, could provide additional growth benefits but policymakers should be aware of the potential for inequality in this case.

Appendix I. Financial Inclusion Indices

This Appendix explains the construction of Indices of Financial Inclusion and its components and provides an overview of the data and its processing for the construction of indices.

Measuring Financial Inclusion

  • Since there is no commonly accepted definition of financial inclusion we used a practical definition for the purpose of this note, namely, access and effective usage of financial services by households and firms. We employ multi-dimensional indices to capture different faucets of financial inclusion. In particular, we construct three multi-dimensional indices capturing different angles of financial inclusion: (i) usage of financial services by households (Findex); (ii) usage of financial services by SMEs (Enterprise Survey); and (iii) access to financial institutions (Financial Access Survey). The diagram below illustrates indicators included in each of the indices. We chose indicators that cover the most important aspects of financial inclusion emphasized in the literature, while taking into account data constraints. For example, the household inclusion index encompasses information on the use of bank accounts, savings, borrowing, and payment methods but omits information on insurance due to data constraints. We also chose not to combine the three indices into a single index, notably because cross-country data coverage across households and firms varies substantially. Instead, we compare Costa Rica and other LAC countries to other regions and for households across time,1 separately on each dimension.2

Data Sources and Processing

Table below shows the main data sources. The data from Global Findex covers the period for 2011 and 2014 only. The data point from enterprise survey is the latest observation available.

  • From the components to the composite index

  • All variables were normalized using the following formula: Ix,it

  • Where Ix,it is the normalized variable x of country i on year t, min(xit) is the lowest value of variable xit over all it; and max(xit) is the highest value of xit. For those variables that capture a lack of financial inclusion, such as Value of collateral needed for a loan and percent of firms identifying access or cost of finance as major constraint, the reverse formula was used:

  • Several methods were used to estimate the weights: principal component analysis with the variables in levels and in differences, factor analysis with the variables in levels and in differences, as well as equal weights within a subcomponent of the index. For most of the methods the weights were not very different from equal weights and econometric results were robust to the method of aggregation. Thus, for simplicity of exposition the paper presents an index with equal weights.

Use of Financial ServicesHouseholdsAccount at a formal financial institution (% age 15+)Global Findex
ATM is main mode of withdrawal (% with an account, age 15+)Global Findex
Debit card (% age 15+)Global Findex
Loan from a financial institution in the past year (% age 15+)Global Findex
Saved at a financial institution in the past year (% age 15+)Global Findex
Firms/SMEs (Enterprise Survey, <100 employees)% of SMEs Firms With a Checking or Savings AccountEnterprise Survey
% of SME Firms With Bank Loans/line of CreditEnterprise Survey
% of SME Firms Using Banks to Finance InvestmentsEnterprise Survey
Working Capital Bank Financing (%)Enterprise Survey
Value of Collateral Needed for a Loan (% of the Loan Amount)Enterprise Survey
% of SME Firms not needing a loanEnterprise Survey
% of SME Firms Identifying Access/cost of Finance as a Major ConstraintEnterprise Survey
Access to financial infrastructureNumber of ATMs per 1,000 sq kmIMF, Financial Access Survey
Number of branches of ODCs per 1,000 sq kmIMF, Financial Access Survey
Number of branches per 100,000 adultsIMF, Financial Access Survey
Number of ATMs per 100,000 adultsIMF, Financial Access Survey

Household Inclusion Index

East Asia and Pacific99
Europe and Central Asia2929
Latin America2020
Middle East and North Africa99
South Asia66
Sub-Sahara Africa3131

Firm Inclusion Index

RegionM.R.A. 1/
East Asia and Pacific9
Europe and Central Asia2
Latin America31
Middle East and North Africa5
South Asia4
Sub-Sahara Africa28

Access Index

RegionM.R.A. 1/
East Asia and Pacific24
Europe and Central Asia46
Latin America32
Middle East and North Africa15
North America2
South Asia7
Sub-Sahara Africa35

Most recent year available.

Most recent year available.

Appendix II. Model Characteristics

The model features an economy where agents differ in their talent and wealth. Each person has to decide whether to become a worker (earn wages) or an entrepreneur (earn profits) and whether to pay a fixed participation cost to be able to borrow from the banking system. Entrepreneurs then decide on how much of their wealth to invest in their business, whether and how much to borrow at the going interest rate, and how many workers to employ at the going wage rate. The output from business projects depends on the amount of capital invested, the amount of labor hired, as well as on the entrepreneur’s talent. In the model, the magnitude of the participation cost represents the cost of financial contracting. The higher is this cost, the more agents remain in credit autarky. Moreover, it tends to disproportionately exclude poor but talented individuals as the fixed cost amounts to a larger fraction of their wealth.

Once in the banking system, the amount of credit available is constrained by other financial frictions. If an entrepreneur has paid the participation cost, he or she can borrow from the banking system at the going interest rate. The model assumes that a business can fail for external reasons (“bad luck”), with some probability. Given imperfect enforceability of contracts, entrepreneurs have to post personal wealth as collateral for the loan. Since banks runs the risk that entrepreneurs can defraud them, this constrains the amount that can be borrowed. Therefore, weak contract enforceability leads to lower leverage, imposing borrowing constraints on entrepreneurs. A second friction is modeled as arising from asymmetric information between the bank and the borrower. The underlying intuition is that if the entrepreneur does not pay back the loan, the bank cannot be sure whether the business actually failed. Banks have to pay an audit or monitoring cost to find out. Otherwise, entrepreneurs could benefit from claiming failure and keep the profits. These costs—measure of the degree of intermediation costs in the economy—are recuperated by banks through interest rates and high overhead fees.1

In the baseline, the model is calibrated to data for 12 LAC countries. Firm-level data for 2005 from the World Bank Enterprise Survey are used, in addition to standard macroeconomic and financial variables (savings rate, non-performing loans (NPLs), and interest rate spreads) for 2010 or the latest year available. While lack of financial inclusion is an even more acute problem for firms in the informal sector, the model focuses primarily on formal sector firms. The model’s key parameters are jointly chosen to match the simulated moments, such as the percent of firms with credit and the firm employment distribution, with the actual data for each country (see Dabla-Norris et al., 2015, for details).

Prepared by Anna Ivanova, Yixi Deng, and Joyce Wong.

The notes follows closely the IMF working paper “Financial Inclusion: Zooming in on Latin America” by Era Dabla-Norris, Yixi Deng, Anna Ivanova, Izabela Karpowicz, Filiz Unsal, Eva VanLeemput, and Joyce Wong.

The regressions explain a large portion of the variation in financial inclusion, with R-squares close to 0.7 in the regressions for households and firms. Nonetheless, the lack of a solid theory on the factors driving financial inclusion implies that the correct model specification is subject to uncertainty. Hence, the gaps should be interpreted with due caution, in particular, with respect to causality. Nevertheless, they could be useful in indicating a possible area where financial inclusion is lacking. The explanatory power for access to financial institutions regression is low and we omit the discussion of the results of this regression for Costa Rica.

Specifically, we focus on changes in the steady state of the economy when these constraints changes. These examples are illustrative, however, as the calibration for the financial inclusion process is chosen arbitrarily. Moreover, in practice, as many reforms are implemented on various fronts contemporaneously they are likely to reduce the frictions in unison with additive effects.

This is because “rich” entrepreneurs (possibly also more talented and more productive) can borrow much more when collateral constraints are relaxed increasing their profits, thus becoming richer. The optimal production scale of new entrants is lower and, even if they can borrow, they are not likely to achieve the same profits.

Findex data is available for two years: 2011 and 2014.

We explore different aggregation methods, namely, weights derived from the principle component analysis (Camara, N., and D. Tuesta, 2014), factor analysis (Amidžić et al., 2014) and equal weights. The results are similar when using alternative measures (see Appendix 1). For simplicity of exposition we present the results for indices constructed using equal weights.

In the model, the bank’s optimal verification strategy follows Townsend (1979), whereby verification only occurs if the entrepreneur cannot pay the face value of the loan. This happens when the entrepreneur is highly leveraged and also faces a production failure. As a result, banks only monitor if a production failure is reported and the loan contract is highly-leveraged. A low-leveraged loan implies that entrepreneurs are not borrowing much from the bank and therefore the required repayment is small.

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