5 Dollarization, Financial Deepening and Financial Inclusion – Understanding Dollarization

5Dollarization, Financial Deepening and Financial Inclusion

5.1Introduction

Financial deepening refers to the availability of funds provided by financial intermediaries to final users (individuals, governments and firms). Additionally, financial inclusion refers to the availability of financial products (deposits, savings, loans, etc.), and how easily or widely these products are accessed by most economic agents in an economy.

Literature has shown that over the long run, financial deepening is an important catalyst for economic growth in emerging markets (see Darrat, Elkhal and McCallum, 2006 among others). Countries with deep credit markets enable entrepreneurs to tap into much needed capital for growth. In return, growth provides jobs and economic stability.

Figure 5.1 shows the average growth rates in 119 developing countries plotted against the average credit to GDP ratios for the 2000–2014 period. We can observe that there is a positive relationship between financial depth and the country’s growth rate. The Slope coefficient of the best fit line presented in the figure is positive (0.01) but not statistically significant at 5%. The correlation is +0.12.

Figure 5.2 shows the same relationship but this time, only using data from developing countries with shallow financial systems (where credit to GDP ratio is 50% or less). The positive correlation we observed in Figure 5.1 is less clear in countries with shallow financial systems.

Figures 5.3 and 5.4, show the evolution of financial deepening in two important regions, Latin America and Transition economies.

Figures 5.5 and 5.6 show the relationship between financial deepening and growth in these two regions. While Latin American countries show a direct relationship between the two variables, for transition economies, we observe an inverse relationship between financial depth and GDP growth.

The following sections of the chapter are as follows. Section 5.2 reviews some of the existing literature on financial depth and dollarization and analyzes the empirical evidence regarding this relationship; Section 5.3 discusses an economic development issue known as financial inclusion and its relationship with dollarization, and Section 5.4 examines the role of Bitcoin as a new form of dollarization.

5.2What We Know about Financial Depth and Dollarization: A Review

The relationship between dollarization and financial depth influences the macroeconomic stability of countries, as measured through growth rates and the volatility ofinflation rates. We know from empirical research that a low inflation rate is closely linked with the strengthening of financial systems, and inflation remains low as a financial system becomes increasingly deep and sophisticated. In general, in an inflationary environment, banks lend and allocate less capital, stock markets become smaller and less liquid, and savers save less, preferring physical assets to financial securities.

Figure 5.1: Financial depth vs growth rates (all countries).

Figure 5.1 shows the average growth rates for 119 developing countries between 2000 and 2014 plotted against average credit to GDP ratios for the same period. The equation for the best fitted linear trendline is: Average Growth Rate = 0.0097 * Average Credit to GDP Ratio + 2.98.

Source: World Bank.

Figure 5.2: Financial depth vs growth rates (shallow financial systems).

Figure 5.2 shows the average growth rates for 100 developing countries with shallow financial systems (where credit to GDP ratio is 50% or lower) between 2000 and 2014 plotted against average credit to GDP ratios for the same period. The equation for the best fitted linear trendline is: Average Growth Rate = 0.0006 * Average Credit to GDP Ratio + 3.22.

Source: World Bank.

Figure 5.3. Development of financial depth in Latin American economies (2000–2014).

Figure 5.3 shows the evolution of financial depth (measured as the ratio of domestic private credit to GDP in percentages) in selected Latin American economies between 2000 and 2014. Source: World Bank Databank.

Figure 5.4: Financial deepening in selected transition economies (2000–2014).

Figure 5.4 shows the evolution of financial depth (measured as the ratio of domestic private credit to GDP in percentages) in selected transition economies between 2000 and 2014.

Source: World Bank Databank.

As we discussed in earlier chapters, one of the main reasons for the appearance of dollarization in an economy is the erosion of money’s function as a store of value (the Currency Substitution hypothesis). High and chronic inflation rates eventually lead to high dollarization ratios. It is important to remember that under this scenario, dollarization gives consumers a shelter from domestic inflation and enables savers to retain the value of their savings. To reiterate, dollarization does not only serve as a hedging instrument but also provides an incentive for saving which is very much needed in developing financial systems. As Feige (2003) points out, by offering an alternative investment mechanism, dollarization helps prevent capital flight from those economies and, by contributing to keep savings in the local economy, may also positively contribute to financial depth despite high inflation.

Figure 5.5: Financial deepening and economic growth (Latin American economies, 2000–2014).

Figure 5.5 shows the average growth rates for 18 Latin American and Caribbean countries between 2000 and 2014 plotted against average credit to GDP ratios for the same period. The equation for the best fitted linear trendline is: Average Growth Rate = 0.0143 * Average Credit to GDP Ratio + 1.97.

Source: World Bank.

Figure 5.6: Financial deepening and economic growth (Latin American economies) (2000–2014).

Figure 5.6 shows the average growth rates for 22 transition economies between 2000 and 2014 plotted against average credit to GDP ratios for the same period. The equation for the best fitted linear trendline is: Average Growth Rate = –0.044 * Average Credit to GDP Ratio + 5.82.

Source: World Bank.

Even though there have been studies on the effects of full dollarization on real economic variables such as growth and employment, there has been limited research performed to analyze the effects of partial dollarization on the development of financial systems. De Nicolo, Honohan and Ize (2005) are the first to empirically assess the effect of dollarization of bank deposits on the financial deepening of a country.

As indicated by these economists, any econometric investigation of financial deepening and dollarization is prone to endogeneity problems since “. . . many of the factors influential for monetary depth are also among the determinants of dollarization” (p. 1705). The authors note that the coexistence of the two phenomena could be a result of other factors, rather than having a causal relationship.

In order to deal with this endogeneity problem, the authors used an instrumental variable method which included instruments that are the causes of dollarization in their analysis. Their findings suggest that for high inflation economies, financial depth and inflation seem to be positively related. They use an interaction term between the two variables (dollarization and the logarithm of inflation) and find a significant and positive coefficient.41 The authors test if this relationship is present in high inflation countries and their findings suggest that for higher inflation economies, dollarization does indeed strengthen the financial system through the moderating effect of dollarization on the adverse effects of inflation upon monetary depth. The authors were not able to find the same result for low inflation economies.

Based on the previous findings, they contend that “[. . .] dollarization may have little impact on monetary depth where risk factors summarized by inflation are low [. . .]” (De Nicolo, Honohan and Ize, 2005, pp. 1712). Furthermore, they recognize that the more the dollarized the system, the riskier it becomes. The authors explain that this is mainly because “. . . dollarized financial systems are exposed to both solvency and liquidity risk. As regards [to] solvency, the main risk results from currency mismatches in the event of large depreciations.” Liquidity risk arises when depositors fear that local banks will not be able to honor the claims on their deposits. Such fears may be the result of an increase in risk premiums on foreign currency deposits in local banks. This risk premium is a direct result of the fact that local banks may hold large claims against the government in these economies, and as a result of the fact that local banks may “end up on-lending domestically a large share of their dollar deposits, effectively transferring the currency risk to their unhedged clients and retaining the resulting credit risk.” (pp. 1712–1713)

Court, Ozsoz and Rengifo (2012) performed a further empirical study that explored the links between dollarization and financial deepening. The authors estimated the impact of dollarization on financial deepening by using different models and specifications while controlling for creditor rights and consumer credit information.

Using a sample of 44 developing countries with high dollar denominated deposits and different levels of inflation over the 1996–2002 period, the authors studied the effect of deposit dollarization (measured as the ratio dollar deposits to total bank deposits42,43) on the extent of financial deepening experienced by these countries (measured as the ratio of domestic credit extended by the banking system to the private sector to the GDP which is available from IMF’s International Financial Statistics (IFS) database). The authors use a battery of models and estimation techniques in their analysis including Ordinary Least Squares (OLS) and Two-Stages-Least Squares to control for possible endogeneity issues as addressed by DeNicolo, Honohan and Ize (2005). The two equations estimated by the authors are:

Where CREDITit is the domestic credit for country i in year t, GDPit represents the nominal GDP in country i in year t and CRI is the creditor rights index which ranges from 0 (low protection) to 4 (high protection). This index shows the relative ease of seizing collateral by creditors if debt obligations are not fulfilled. The variable PB equals 1 if a private credit bureau operates in the country, 0 if otherwise. A private bureau is defined as a private commercial firm or non-profit organization that maintains a database on the standing of borrowers in the financial system, charged with the primary role of facilitating the exchange of information amongst banks and financial institutions. The variable INST is an equally-weighted average of the six institutional quality variables compiled by Kaufmann et al. (2009): Government Efficiency, Political Stability, Regulatory Quality, Rule of Law, Voice, and Corruption. The six governance indicators are measured in units ranging from –2.5 to 2.5, with higher values corresponding to better governance outcomes. Finally, logCGDPit is the logarithm of per capita income in country i in year t, and DDOLLit is the ratio of the dollar deposits in country i in year t to the overall deposits in the banking system. Dit is a dummy variable that takes the value of 1 if the inflation rate in country i in year t is over 20% and 0 if otherwise; DDOLLit * INFit represents the interaction between dollarization and inflation; INF represents the natural logarithm of the inflation and ε is the error term.

The authors also use institutional quality variables as instruments in their estimations. The Creditor Rights Index (CRI) and Private Credit Bureau Availability Dummy (PB) are obtained from World Bank’s Doing Business website.

Tables 5.15.3 show the authors’ estimation results for the two models they used. Their results show that in countries with moderate inflationary processes, deposit dollarization consistently and significantly exerts a negative impact on financial deepening. This means that dollarization has a moderating effect on the adverse effects of inflation upon financial depth in high inflation economies.

In their paper, the authors also used the Minimum Variance Portfolio coefficient introduced by Ize and Levy-Yeyati (2003) and the Minimum Variance Portfolio coefficient calculated according to Neanidis and Savva (2009) (MVP2)44 as analytical instruments. Tables 5.2 and 5.3 present these results.

From the Tables 5.2 and 5.3 the reader can extrapolate that, under different specifications, the authors verify that deposit dollarization does indeed have a negative impact on financial deepening in low inflation environments. This is consistent with the findings of De Nicolo, Honohan and Ize (2005), which show that dollarization moderates the negative effects of inflation on financial deepening under high inflation, but has pernicious effects on low-inflation economies. The coefficient of the dollarization variable ranges from –0.412 to –0.936 suggesting that a 10% increase in the deposit dollarization ratio can reduce the credit-to-GDP ratio by almost 4–9% in the countries studied. The value of the dollarization coefficient (DDOLL) is also much higher (in absolute value terms) in specifications where the Minimum Variance Portfolio variable defined according to Neanidis and Savva (2009) is used. (See Table 5.3).

In economies with controlled inflation, it appears that the dollarization of deposits in a banking system slows financial development by limiting domestic credit. These restrictions could be attributed to the currency mismatch and loan default risks that banking systems face in dollarized environments. Kutan, Ozsoz and Rengifo (2012) showed that dollarization exerts a negative impact on bank profitability and simultaneously contributes to the shallowness of the financial system.

Table 5.1: Determinants of domestic private credit—all countries.

Table 5.1 shows the estimation results of the first model (Eq. 5.1). CREDIT represents domestic credit, CGDP is the real per capita GDP in US Dollars, CRI is the creditor rights index which ranges from 0 (low protection) to 10 (high protection), INST stands for institutional quality and is an equally weighted average of the 6 institutional quality variables published by Kaufmann et al. (2009). It ranges from –2.5 to 2.5, with higher values corresponding to better governance outcomes. PB is a dummy variable that takes the value of 1 if there is a private credit bureau in the country, DDOLL is the ratio of the dollar deposits to the overall deposits in the banking system and D is the high-inflation dummy that takes the value of 1 if the inflation rate in country i in year t is over 20% and 0 otherwise. This table does not include the results for Africa and Middle East countries because the authors did not have a representative sample *Significant at 10%; **significant at 5%; ***significant at 1%

The more foreign currency depositors want to keep in their bank accounts, the higher the risk banks face in terms of currency mismatches or loan defaults. In an effort to minimize their exposure to such risks, banks may find it in their best interests to be more careful in selecting their loan portfolios. As Court, Ozsoz and Rengifo (2012) put it, “Banks may scrutinize their credit applications more vigorously to make sure their borrowers have the ability to repay their loans independent of fluctuations in the value of the local currency and sometimes will not be willing to provide capital to good projects based on this exchange rate exposition” (p. 49).

However, when a country begins to experience the effects of high inflation,, dollarization plays a moderating effect on the adverse effects of inflation on financialdepth of an economy, as indicated by the sign of the interaction term (DDOLL * INF) in Tables 5.1 through 5.3. This finding is also consistent with the findings of De Nicolo, Honohan and Ize (2005). This result could be linked to previously discussed role of dollarization as an alternative hedging mechanism for savings.

Table 5.2: Results of Model 2 using MVP.

Table 5.2 presents the results of the model developed by De Nicolo, Honohan and Ize (Eq. 5.2). DDOLL is the ratio of the dollar deposits to the overall deposits in the banking system, INF is the natural logarithm of the inflation, logCGDP is the logarithm of per capita GDP. Instrument list A: INST, MVP, RESTRIC Instrument List B: A + logCGDP. Where INST stands for institutional quality, MVP the Minimum Variance Portfolio coefficient, RESTRIC the index of restrictions on the holdings of foreign currency deposits. The null for the Sargan test: The error term is uncorrelated with the instruments. The critical values for chi2(2) and chi2(3) are 5.991 and 7.815 at 5% critical value. *Significant at 10%; **significant at 5%; ***significant at 1%

Table 5.3: Results of Model 2 using MVP2.

Table 5.3 presents the results of the model developed by De Nicolo, Honohan and Ize (2005) according to their Equation (5.2). DDOLL is the ratio of the dollar deposits to the overall deposits in the banking system, INF is the natural logarithm of the inflation, logCGDP is the logarithm of per capita GDP. Instrument list A: INST, MVP, RESTRIC Instrument List B: A + logCGDP. Where INST stands for institutional quality, MVP2 the Minimum Variance Portfolio coefficient calculated according to Neanidis and Savva (2009), RESTRIC the index of restrictions on the holdings of foreign currency deposits. The null for the Sargan test: Over identification restrictions are not valid. The critical values for chi^2 (2) and chi^2 (3) are 5.991 and 7.815 at 5% critical value.

*Significant at 10%; **significant at 5%; ***significant at 1%.

Court, Ozsoz and Rengifo (2012) found that inflation (INF) by itself has a negative and significant coefficient on financial deepening. This is an expected result. High inflation restricts the availability of credit in an economy. The coefficient of the inflation variable (INF) varies between –0.03 and –0.16, meaning that a 1% increase in the inflation rate lowers the credit-to-GDP ratio in the countries studied between 0.03 and 0.16%. Additionally, the variable that accounts for institutional quality (INST) has a positive and significant coefficient around 0.15, suggesting that a one-step increase in the value of this variable increases credit-to-GDP ratio by 15%. The results gathered at the regional level also support this view; the authors explain that “this result is not surprising given that previous literature (such as Graff (2003) among others) has demonstrated that institutional quality and culture are important in the financial development of transition and emerging market economies” (p. 50). A graphical illustration of these findings can be found in Figures 5.5 and 5.6.

Figure 5.7 shows dollarization (measured as the ratio of dollar deposits to M2 money supply) and financial depth ratios (measured as the ratio of domestic credit to GDP) for selected dollarized economies.

For highly dollarized economies, the trend line that shows the relationship between dollarization and financial deepening is steeper as opposed to the overall sample. The slope coefficient equals 0.426 and is statistically significant at the 5% level.

Figure 5.8 presents a scatter diagram charting the relationship between financial depth and deposit dollarization rates for 9 heavily dollarized economies in this sample. We define a heavy dollarized economy as an economy where the ratio of foreign currency deposits to M2 is more than 30%.

5.3Financial Inclusion

The topic of financial inclusion studies the relationship between the financial deepening of an economy and growth rates, and refers to the availability of financial products (deposits, savings, loans, etc.) and the ease of access to these products by most economic agents in an economy. Dollarization and financial inclusion bear some relation; in economies where foreign currency accounts are available, more individuals can enjoy access to credit lines in foreign currencies in addition to the local currency. As a corollary, dollarization may have a positive impact on financial inclusion,45 and one would expect financial markets that exhibit some of the characteristics of dollarization to be more inclusive.

Figure 5.7: Financial depth vs dollarization in selected dollarized economies.

The figure shows financial depth (measured as the ratio of domestic credit to GDP) of several economies versus its deposit dollarization (measured as the ratio dollar deposits to M2). The equation for the fitted line is Credit-to-GDP=0.426*Dollarization+0.33.

Source: IMF-IFS, Court, Ozsoz and Rengifo (2012).

In this section we highlight the possible relationships that one can deduce from examining common economic-financial data. Table 5.4 shows the dollarization and bank account ownership ratios for the ten countries that have the highest bank account ownership percentages among low, middle and upper middle income countries, as ranked by the World Bank. According to the table, except for Thailand, Mauritius and Sri Lanka all of the countries in the list can be considered heavily dollarized, since their respective dollarization ratio is above 20%.

The financial instruments that we refer to in this section are the possibility of opening banking accounts (savings) and the availability of access to different loan or credit products (investment loans, consumption credit, mortgages, among others) in both local and foreign denominated currencies.

Economic agents in several developing economies (especially agents in frontier markets46) do not have access to the full array of financial instruments available elsewhere. This limitation hinders the societal benefits that can be achieved through a more inclusive financial sector.

Figure 5.8: Financial depth vs dollarization in selected dollarized economies (heavily dollarized economies).

The figure shows the financial depth of an economy (measured as the ratio of domestic credit to GDP) versus its deposit dollarization (measured as the ratio dollar deposits to total bank deposits) in heavily dollarized economies (where the ratio of foreign currency deposits to the M2 is more than 30%). The equation for the fitted line is Credit-to-GDP=1.45*Dollarization+0.18. Source: IMF-IFS, Court, Ozsoz and Rengifo (2012).

Table 5.4: Financial inclusion and dollarization.

Table 5.4 shows the dollarization ratios and bank account ownership for the countries that rank within the top ten among World Bank’s list of low, middle and upper middle income countries in terms of financial inclusion. The dollarization metrics used are: *Liability Dollarization, **Foreign Currency Deposit to M2, ***Foreign Currency deposits to Total Deposits, ± Loan Dollarization (Ratio of Foreign Currency Loans to total Loans. Source: World Bank Financial Inclusion Database (Findex), IMF—Financial Soundness Indicators (FSI), IMF—International Financial Statistics, Yeyati (2006) and Kutan, Ozsoz and Rengifo (2012).

As economic theory has shown, individuals display a preference for consumption smoothness, i.e. consumers try to avoid period of abundance followed by periods of scarcity. One way to avoid those situations is by saving economic resources during good times in order to use them during bad times.

Individuals who cannot access savings accounts face many problematic challenges. Firstly, the inability to access savings products and related services makes preparing for the future a very hard task. Under these circumstances, individuals try to keep their moneys “under the mattress” (a strategy with obvious drawbacks) or alternatively invest in real assets that are not always liquid.47,48 Secondly, without a safe place to store their savings, many people fail to develop any sort of saving strategy at all.49 Thirdly, individuals who are unable to save or access other financial services such as lending are unable to take advantage of investment opportunities that may come along.

Cash economies suffer from several other problems.50 As mentioned before, keeping cash for savings purposes exposes people to robberies and increases transactional costs. For example, performing cash transactions that involve large amounts or are executed between parties located far away from one another presents additional security risks and coordination problems. Overall, it is clear that economic agents in developing countries could benefit greatly from broad, low-cost access to financial services provided by the banking systems.

As a way to show access to the financial services commonly available in developed economies, Figure 5.9 shows ten countries within World Bank’s low, middle and upper middle income group (a total of 112 countries) that have the highest credit card ownership ratios for individuals above the age of 15 years old.

As can be seen even in the countries with the highest penetration ratios (Uruguay and Turkey) this number does not go above 40%. In the meantime, in the US this ratio is over 60% and in Canada (which has the highest number of ATMs per capita as of 2014), this ratio reaches 77%. (Source: Findex Database, World Bank).

Figure 5.9: Top ten low, middle and upper middle income countries in terms of ATMs per 100,000 (2014). Source: World Bank, Findex Database.

Other metrics used to examine financial inclusion are presented in Figures 5.10 (top ten developing countries with the highest percentage of adults that have borrowed from a financial institution in 2014) and 5.11 (Bottom ten developing countries with the lowest percentage of adults that have borrowed from a financial institution) as well as in Table 5.5 (credit depth index). These two metrics are used to show often economic agents access lines of credit (Figure 5.12).

Figure 5.10: Top ten low, middle and upper-middle income countries in terms of the percentage of adults that have borrowed from a financial institution in 2014.

Source: World Bank, Findex Database.

Figure 5.11: Bottom ten low, middle and upper middle income countries in terms of percentage of adults that have borrowed from a financial institution in 2014.

Source: World Bank, Findex Database.

According to the World Bank financial inclusion data,51 there are two billion people who do not have an account at a formal financial institution. This problem is more pronounced in non-metropolitan areas, where banking services cannot be provided for several reasons. For banks, it is not profitable to serve these clients (due to high monitoring costs), thus it does not make economic sense for banks to set up branches in such places. For individual clients, banking charges may be prohibitive, and access to their local bank branch may be too difficult (they may need to travel significant distances to access one branch, which might also involve suffering transportation costs).

Lately, alternative solutions have been appearing that may ameliorate these issues. One of these possible solutions uses cell phone technology to serve local communities that are geographically far away from major cities. According to the Economist (September 20, 2014) “Kenya leads the world in mobile money, with more active accounts than adults in its population. The total value of transactions made by mobile phone in 2013 was around $24 billion, more than half the country’s GDP. The leading mobile payment system in Kenya, M-PESA, was launched in 2007. A year later it expanded to Tanzania. While uptake there has not been as strong, the totaltransaction value is close to that of Kenya. As mobile phones have become more widely available, mobile payment transfers have helped reach the ‘unbanked’. In at least eight countries, including Congo and Zimbabwe, more people have registered mobile-money accounts than traditional bank accounts” (Figure 5.13).

Table 5.5: Low, middle and upper-middle income countries with the highest ranking of credit depth information index (as of 2014).

Country name Depth of credit information index (0=low to 8=high)
Benchmarks
USA 8
Germany 8
China 6
Euro Area 5.68
Developing countries with highest scores
Argentina 8
Armenia 8
Dominican Republic 8
Ecuador 8
Egypt, Arab Rep. 8
Georgia 8
Honduras 8
Lithuania 8
Mexico 8
Nicaragua 8
Panama 8
Paraguay 8
Peru 8
Uruguay 8
Middle-ranking countries
Bulgaria 5
Cambodia 5
Kyrgyz Republic 5
Latvia 5
Lebanon 5
Philippines 5
Tunisia 5
Countries with the lowest scores
Afghanistan 0
Algeria 0
Angola 0
Bangladesh 0
Belize 0
Burkina Faso 0
Burundi 0
Central African Republic 0
Chad 0
Comoros 0
Congo, Dem. Rep. 0
Cote d’Ivoire 0
Djibouti 0
Ethiopia 0
Guinea 0
Haiti 0
Iraq 0
Jordan 0
Kenya 0
Lao PDR 0
Lesotho 0
Liberia 0
Madagascar 0
Malawi 0
Mali 0
Mauritania 0
Myanmar 0
Nepal 0
Niger 0
Senegal 0
Sierra Leone 0
Sudan 0
Tanzania 0
Togo 0
Uganda 0
Yemen, Rep. 0

Source: World Bank Findex Database.

Figure 5.12: Credit card ownership: top ten countries among low, middle and upper-middle income group.

Figure 5.12 shows the ten countries within World Bank’s low, middle and upper middle income group (a total of 112 countries) that have the highest credit card ownership ratios for individuals above 15 years of age.

Source: Findex Database, World Bank.

A pioneer service called M-Pesa (Kenya) allows customers to use simple cell phone technology (SMS messaging) to make payments through mobile phones. M-Pesa has also become a popular method of sending remittances from urban to rural areas.

Similarly to M-Pesa, there are several companies in different countries that have been experimenting with these technologies to make banking services available to many people in different geographic regions. Amongst these we have bKash in Bangladesh, GCash and SMART Money in the Philippines.

Recently, cell phones have been exploiting internet-technologies (smart phones); thanks to economies of scale, falling commodity prices and burgeoning expertise, the costs to manufacture smart phones are falling, and supporting these technological advances, internet service payments are also being reduced significantly. This is allowing more and more people access to smart phones, enabling service providers to extend their reach and further invest in infrastructure to service this growing demand.

The increasing availability of smart phones at lower prices and with cheaper connectivity fees can greatly facilitate financial transactions and improve the ease of access to financial products in developing countries.52

Figure 5.13: Mobile money in developing countries (top ten in terms of account ownership, 2014).

Figure 5.13 shows the ten countries with the highest mobile account holder ratios as a percentage of adult population (aged 25 and older) among the low, middle and upper middle income group countries.

Source: Findex Database, World Bank.

5.4Bitcoin: The New Future Form of Dollarization?

First appearing in 2008, Bitcoin is one of the first digital or crypto-currencies. Bitcoin is the world’s first fully decentralized, peer-to-peer system for electronic transactions.

Bitcoin facilitates the transfer of value between two unknown parties without relying on a third party to validate the transaction. Bitcoin has eliminated the need for a centralized clearing house (i.e. credit card company, bank, government, or escrow agent) allowing monetary transfers that are approved through a mechanism that involves the entire network but does not rely on any single individual or institution. In this environment, banks and governments have no power to create bitcoins, and nobody can freeze or seize funds that do not belong to them.

Paying for a good or service can be done almost instantly, anywhere in the world via an internet connection. Bitcoin has the potential to alter the world’s economic landscape, and its related technologies could potentially offer solutions to unbanked and under-banked individuals and improve the stuttering economies in which they live. Argentina is a clear example of a country where Bitcoin has become increasingly popular due to structural economic problems and capital controls.

Argentina was rated by Bloomberg as one of the worst economies in the world in 2015 (Bloomberg News); the government’s strategies to solve the country’s economic problems have proved extremely inefficient in reducing unemployment and controlling inflation. In this environment, out-of-the-box solutions are appearing, and among them we can find digital currencies like bitcoins, which are out of the reach of forced currency conversions (which many depositors suffered as part of Argentina’s slew of capital controls).

Argentina faced a serious financial crisis in 2001 when the peso, at the time pegged to the US dollar, collapsed. Again in 2014, the country faced an economic crisis and government responses failed once more. The government has refused to acknowledge the extremely high levels of inflation by publishing false statistics that contradict studies conducted by independent organizations. Argentina’s official inflation figures had been massaged and misreported to such an extent that at the end of 2013, the International Monetary Fund officially reprimanded the country. Figure 5.14 shows the official inflation estimations as compared to those of independent organizations estimated by JP Morgan):

Facing this crisis, Argentinian confidence in the peso is very low. Most of Argentina’s citizens prefer US dollars to protect their purchasing power. However, citizens can only convert portion of their income to USD due to government regulations. Also, as mentioned previously, dollar purchases are taxed up to 20%.

The Argentinian government has also imposed capital controls in an attempt to reduce the capital outflows from the country. This, together with citizens’ restrictions to buy dollars, has created a growing black market for foreign currencies, especially US dollars. As shown in Chapter 1, the spread between the unofficial (black market) and official rates is large. Furthermore, all black market transactions are done in cash, which leaves Argentinians vulnerable to theft or fraud.

Figure 5.14: Inflation in Argentina official vs unofficial figures.

Source: JP Morgan/FT.

When citizens no longer believe in the credibility of the government and financial institutions, individuals desire a method to circumvent traditionally sanctioned institutions and avoid government interference. Consequently, many people in Argentina are currently using Bitcoin as a way to circumvent the traditional financial system.

Online retailer “Avalancha” introduced the option to pay with Bitcoin. The company is able to offer a 10% discount to customers who pay with Bitcoin, as the cost efficiency of Bitcoin allows them to earn more on these transactions than they would on credit card transactions processed through the banking system.

Moreover, during the summer of 2014, Argentina-based Bitcoin company Bit-Pagos launched its “Ripio” service that enables users to buy bitcoins at more than 8,000 mobile phone kiosks and allowing customers to buy small amounts of bitcoin at convenience stores within the kiosks. This makes it much easier for Argentinians to purchase Bitcoins, as the country’s regulations prohibit individuals from purchasing bitcoins through online exchanges.

More importantly, customers can use this service without having a bank account. If a customer has access to a kiosk, the transaction can be executed using just a mobile phone. This allows potential customers to utilize digital currencies while circumventing existing financial institutions entirely. Moreover, as accessing bitcoins becomes more convenient than frequenting the black market, Bitcoin will emerge as the primary currency representing dollarization in the economy.

It is obvious that Argentina is suffering from failed government policies and a severe lack of confidence in the national currencies. Here, digital currencies like Bitcoin infrastructure appear to be providing a needed service that allows its users to use alternative measures to maintain their purchasing power under a heavily regulated economy.