Dollarization of the economy in the Post-Soviet union countries

Factors, the causes and consequences of dollarization for Post-Soviet Union countries. Methods of calculation of deposit interest rates. The estimated exchange rate coefficient encompasses two effects: dollar appreciation and foreign exchange operations.

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23.09.2016

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Table of contents

  • Introduction
  • 1. Theoretical Background
  • 2. Posing research question
  • 3. Methodology
  • 4. Discussion of the results
  • Conclusions and limitations
  • References
  • Appendix 1
  • Appendix 2
  • Introduction
  • From the mid 20th century to our days the international financial system has undergone a plenty of changes. For example, there was the demise of Bretton-Woods system in 1973, which was used to recognize the gold standard as a fundamental framework for the financial system during previous thirty years. It was implemented to oblige each country to conduct monetary policy directed on maintenance of the exchange rate by linking its currency to gold as well as the ability of the International Monetary Fund (IMF) to fix temporary imbalances of payments. This in turn implied the system of fixed exchange rates. Abandonment from the gold standard made the U.S. dollar as the reserve currency for many states. By being a reserve currency, dollar was also a kind of an asset that manage to keep its value while many other currencies experienced inflation and devaluation. This happened during high inflation periods in countries other than the USA. Thus, for instance, phenomenon of hyperinflation occurred on emerging markets of Russia (1992-1994, 1998), Brazil, Peru etc. At that time domestic currencies depreciated several times. Obviously, it lowered the real value and purchasing power of the currencies. For that reason companies and households attempted to save the value of their savings by using dollar-denominated deposits. Dollar deposits did not lose their value and, for instance, served as a resort for savings. Thus, the phenomenon of dollarization took place.
  • Dollarization has certain consequences onto the country's economy. These aftermaths are both positive and negative. Thus, on the one hand, for example, dollar assets allow hedging against inflation. But, on the other - reduces effectiveness of monetary mechanisms, reduces seigniorage and so forth. These aspects will be thoroughly addressed later.
  • Nevertheless, while being affected by dollarization, governments lose the right to influence its own monetary policy by adjusting the money supply. Loss of monetary policy control leads to uncertainty in what is likely to happen with the country's monetary system.
  • In addition, highly dollarized economies suffer from high pass-through of exchange rate changes into import prices, which leads to increase in the general price level. What is more, pass-through literature gives evidence that exchange rate changes are reflected in imports in a more rapid way if market is a developing country. (Frankel, 2010) Countries which will be considered in the research are developing economies. Hence, they are exposed to high pass-through as well.
  • In this sense governments would benefit if they know what the main determinants of dollarization process are, which factors favor its decrease and which do not.
  • Today we still can find some countries and groups of countries with high dollarization degree of economy. Some of the states have managed to overcome dollarization (Angola, Peru, Turkey etc.) to a certain extent, while others could not (Belarus, Moldova, Serbia etc.). Each country had specific economic conditions while passing through dollarization period, which could foster or otherwise slower de-dollarization processes. However, this research will be focused on a range of countries which are geographically placed closely to each other and have been historically linked to one another by means of economy, politics etc. - Post-Soviet union countries.
  • But before we dive into their description, it is worth to mention, that there are some close countries with similar dollarization trouble. For instance, Caucasus and Central Asia countries.
  • Financial dollarization in these countries is rather high in comparison with other developing and emerging economies. Despite reliable and strong growth of economy during past two decades after the dissolution of the Soviet Union, achievements in macroeconomic stabilization, dollarization still remains persistent in Caucasus and Central Asia economies. Although degree of dollarization in this economic region has dropped since 2000, the trend reversed for a certain time after the global financial crisis. Deposit dollarization grew sharply, but loan dollarization increased moderately. Recently, foreign currency denominated deposits and loans have risen because of the valuation effects caused by currency depreciation in several countries. Deposit dollarization remained at 46 percent on average in the last quarter of 2013, whereas loan dollarization was a bit lower - 40 percent. (Naceur et al., 2015). Some of these countries considered in the previous study are taken into account in the present research as well.
  • One more example is Sub-Saharan Africa (SSA). In SSA countries dollarization is present, prominently, it also remains persistent and significant at more than 30 percent for bank loans and deposits. (Mecagni et al., 2015). The aforementioned facts confirm that problem persists and studying of de-dollarization drivers in Post-Soviet union countries is relevant.
  • Now we will focus attention on Post-Soviet union countries. Nowadays many Post-Soviet union countries can be characterized by rather high dollarization level - approximately from 15% to nearly 70% (Data from Central Bank of each country).
  • For example, financial dollarization in Armenian economy has been high throughout a long period of time, but it has experienced high fluctuations. Thus, in the third quarter of 2014, nearly 60 percent of all deposits and loans were denominated in dollars (Picture 1), which was slightly below the average of 65 percent. Fluctuations in dollarization rates were rather wide: it peaked at more than 80 percent in the 2000s, before falling below 40 percent in 2007 and 2008, until the global financial crisis stimulated dollarization increase again. (Rodriguez et al., 2014).
  • From all the aforementioned facts we can conclude that foreign currency was and still remains popular in transaction economies of many countries. From the historical perspective it can be fairly noticed that current international economic conditions can be characterized by high degree of co-integration because of globalization processes, which means that economic cooperation within countries under consideration has expanded as well: volumes of energy transit have increased, countries are collaborating in the sphere of agriculture, railroad transit and so forth.

Picture 1 Dollarization in Armenia, 1995 - 2014

dollarization economy deposit

By analyzing historical data on dollarization degree of the aforementioned economies, present project is aimed on finding the answer to the following research question: What are the key de-dollarization factors in Post-Soviet union countries?

In order to achieve the aforementioned aim we had a plenty of problems to solve. Thus, in chapter Introduction we discussed the roots of dollarization phenomenon and pointed out the importance of the topic under consideration. Next in Theoretical Background chapter we described theoretical aspects of dollarization, its causes and mention positive and negative consequences. In the same part we made a description of the most relevant studies in this area and depicted the main results. Chapter Posing research question includes explanation of methods and factors used in the research, main data sources and stated hypotheses. In Chapter Methodology we explain in details the principles of research methods and data collection process. Chapter Discussion of the results encompasses data description, building and running of regressions with latter interpretation of the effects. In the final chapter Conclusion and limitations we cover the main findings of the whole research, limitations and give recommendations for future research.

Findings of the research can provide information concerning the crucial determinants of dollarization in Post-Soviet union countries, which could be useful for policymakers as they would better understand main factors of this phenomenon, plan monetary adjustments in a more correct way, avoid policy shortcomings of the past as well as for the future researchers of the adjacent area.

Some authors have already analyzed factors and measures that promoted lowering of dollarization level in particular countries. Thus, previous studies by Galindo and Leiderman (2005), Herrera and Valdes (2004), Goujon (2006), Leiderman et al. (2006) pointed out several measures based on de-dollarization factors for solving the problem used by governments in Israel, Chile, Vietnam and Peru. Among them: deepening the local market for government bonds denominated in local currency, introduction of indexed instruments, floating exchange regime and restrictive monetary policy. In addition, research by Ponomarenko and Solovyeva (2011) found out that weak home currency exchange rate was the most important factor that promoted dollarization in Russia before 2011.

However, for the purpose of the research it is also necessary to pay attention at papers which were focused on groups of countries. Thus, Rennhack and Nozaki (2006) studied deposit dollarization factors in Latin American countries and determined that higher flexibility of exchange rate can foster de-dollarization. Garca-Escribano (2010) presents evidence that number of dollarized deposits and credits in Latin America countries have been reduced by means of macroeconomic stability, flexibility of exchange rate, the implementation of prudential regulations that can better represent currency risks.

Methods implemented in the paper include Ordinary Least Squares, normalization. Special attention is given to fixed and random effect models.

The paper is organised as follows: the introduction provides the importance of the problem. Section 2 gives theoretical background about the phenomenon of dollarization, its pros and cons as well as literature review. Then, Section 3 introduces the research design which describes the framework of the study. Section 4 describes the methodology of the research. In Section 5 I present the discussion of results gained after the investigation. Section 6 encompasses comments on the research results and limitations. Finally the volume of the research makes up thirty six pages without appendix and literature sources.

1. Theoretical Background

Definitely, the crucial concept in the research is dollarization. Accordingly, it is worth giving a notion. Authors have similar approaches to dollarization definition. Thus, they define dollarization as a situation when residents hold a significant portion of their assets in the form of foreign currency-denominated assets (Balino, 1999). Or, more generally - as a situation when residents officially or unofficially prefer to use foreign currency as a form of legal tender for carrying out transactions. In case of unofficial dollarization agents tend to use foreign currency for transactions. However, it might not be the legal tender. Official dollarization in turn considers foreign currency to become the tender within the country, but the national currency is also accepted.

The primary reason for dollarization is to replace a less stable currency by a more stable one. Dollarization mainly involves the US dollar (however, other currencies can also be taken into account, e.g. euro). This phenomenon is peculiar to developing countries which represent high inflation levels retrospectively - Bolivia, Bulgaria, Cambodia, Israel, Peru, Poland, Russia etc. (Alvarez-Plata and Garca-Herrero, 2008).

Generally, process of dollarization can be characterized from several dimensions. One of them - currency substitution - has been mentioned earlier. In this case foreign currency serves as a medium of exchange instead of domestic currency. Next aspect refers to such notion as unit of account. By being a unit of account foreign currency is used in the pricing and accounting processes. Another feature is asset substitution, which implies that foreign currency is utilized as a store of value. This in turn means deposit and loan dollarization (also called capital flight). It is common to single out several factors which favor capital flight:

a) Hedging against volatility driven by risk of return

b) Hedging against inflation and national currency-denominated assets depreciation

c) Market imperfections and poor financial intermediation (e.g. underdeveloped debt markets)

d) Institutional aspects: lack of credibility to foreign exchange rate peg, limited foreign exchange availability

Finally, de facto dollarization has certain advantages and disadvantages. Thus, theory points out three aspects of positive effects: hedging, policy anchor and financial deepening. The former allows hedging against inflation and supports portfolio diversification. The second one promotes macro discipline by using foreign exchange rate as an anchor for monetary policy. The later implies using instrument for domestic investment to form an alternative to capital flight, fostering financial deepening.

In addition, Lin and Ye (2013) point out another feature of dollarized economies which can be referred to positive ones. In the study they evaluate the average treatment effect of dollarization on bilateral US trade with six dollarized countries and on bilateral trade of the dollarized countries while carefully controlling for on-random selection of policy adoption. They found strong and robust evidence that dollarization not only significantly increases bilateral US trade with dollarized countries, but promotes trade among dollar-zone countries as well. Their results also suggest that the trade-enhancing effects of dollarization are substantial.

Negative sides are represented by next aspects: monetary policy, fiscal, balance sheet risks and lender-of-last-resort limitations. The first one causes reduction in effectiveness of monetary transmission mechanism. Fiscal aspect means seigniorage decrease. Balance sheet risks represent liquidity and solvency risks caused by exposure of public and private sectors to foreign exchange rate volatility when assets and liabilities are mismatched. The last aspect implies the reduction of lender-of-last-resort ability to stabilize bank system.

It is also worth to mention that all considered economies are transition. They differ from developed countries in a range of ways. Thus, they have high trade volatility, low credibility in terms of risk default and price stability and other imperfections. In additions, they are considered as price-takers of the world prices, which mean they perceive price as given with little power to influence it. Many of the consumed goods are imported from outside. That means goods are nominated in foreign currency. But, since residents pay in local currency exchange rate can significantly change price in national currency. This phenomenon is called pass-through effect. Highly dollarized economies suffer from rapid and high pass-through of exchange rate changes into import prices, which leads to increase in the general price level and can cause rise in inflation level. Pass-through literature gives evidence that exchange rate changes are reflected in imports in a more rapid way if market is a developing country. (Frankel, 2010)

One more point peculiar to transition economy is balance sheet effect. Balance sheet effect has become the most important effect among the various contractionary effects of devaluation process. Banks and firms in emerging markets often borrow funds denominated in foreign currency, even in spite of the fact that primary part of their revenues is in local currency. The situation is named currency mismatch. In case when currency mismatch happens accompanied a major devaluation, solvent firms meet trouble while servicing their debts. Sometimes they may have to close plants and lay off workers, or even go bankrupt.

Negative dollarization consequences overweight positive ones as high degree of dollarization is a signal of a weak economy (Alvarez-Plata and Garca-Herrero, 2008). That means finding a way to lower the dollarization level is an important problem. However, in order to find the solution for successful de-dollarization it is necessary to understand what determines its decrease.

Researchers point out the fact that though topic of dollarization consequences has been given a plenty of attention recently, there is yet a lack of attention towards the empirical aspect of the de-dollarization process (Garca-Escribano, 2010). Actually this is a part of the void the project is aimed to fill.

Anyway we need to review literature devoted to the topic under consideration. In accordance with the stated aim it is necessary to consider papers which have already figured out key determinants of dollarization for different countries or groups of states.

Thus, Neanidis and Savva (2009) in their paper study the factors of financial dollarization in economies in transition from a short-term perspective. With the use of aggregate data of both deposit and loan dollarization with periodicity of one month they study the determinants of short-run fluctuations in dollarization degree. The results give evidence that:

a) Positive (negative) short-term depreciation (monetary expansion) effects on dollarization of deposit are exacerbated in countries with high dollarization;

b) Short-term loan dollarization is basically driven by banks which are trying to match domestic loans and deposits, match currency of liabilities and assets, international financial integration and quality of institutions

c) Both types of short-term dollarization are influenced by differentials of interest rate as well as deviations from the desired dollarization level.

Some researchers have addressed the problem of dollarization in particular countries in transition. Thus, for example, Ponomarenko and Solovyeva (2011) measured the effects of various factors and provide the analysis of the short-term dollarization dynamics. They pointed out next key determinants: exchange rate factor, foreign liabilities to total liabilities ratio, net of deposits, changes in loan and deposit dollarization level, the differential between interest rate in rubles and the weighted average interest rates in euro and USD on loans and deposits. They conclude that exchange rate factor has the largest effect on de-dollarization process.

In his paper Honig (2009) analyses the impact of exchange rate regime on dollarization. He supposes that the dollarization of the domestic banking system represents a source of vulnerability for emerging market countries. He argues that the regime is far less important than the literature has previously claimed. Using annual data on deposit and credit dollarization for 1988-2000, author estimates the regression which includes exchange rate regime, government quality, macro and regulatory controls. Unofficial dollarization stems from a lack of belief in the national currency, which finally results from the faith that the local government will not conduct economic policy that would foster long-term stability of currency. Empirical findings indicate that improved quality of government decreases unofficial dollarization, whereas the exchange rate regime has no significant effect on promoting dollarization.

Hausmann and Panizza (2003) found out that the dollarization of foreign debt is another important aspect of financial dollarization. The reasons for the country being unable to borrow abroad in its own currency include the low level of institutional development, low credibility of monetary policy and questionable fiscal solvency.

Arteta (2002) and Barajas and Morales (2003) evaluate the effects of exchange rate policy on financial dollarization. Using a large sample of emerging market and transition economies, Arteta (2002) provides evidence that a flexible exchange rate regime may amplify bank currency mismatches by decreasing credit dollarization and increasing deposit dollarization. Author analyzes the practice of dollar lending by constructing an optimal portfolio allocation model and testing it using aggregate data for transition economies. Arteta assumes that banks' credit supply determines credit dollarization; thus, he does not include firms' hedging incentives as a factor in his model. Barajas and Morales (2003) provide evidence that, at least in the short run, greater exchange rate volatility reduces credit dollarization in a sample of Latin American economies. Their results also indicate that both bank asset and firm liability allocation decisions are important determinants of dollarization.

De Nicolo and Honohan (2005) analyzed the dollarization of bank deposits. Authors provide empirical evidence on the factors of deposit dollarization, the role they play in fostering financial development, and on if dollarization is related to financial instability. They found that:

a) Macroeconomic policy credibility and the institutional quality are both key drivers of cross-country variations in dollarization level;

b) Dollarization can possibly promote financial deepening only in countries with high inflation levels;

c) Financial instability is likely to be higher in economies with high dollarization degree.

For Latin America countries Vetlov (2001) found that specific factors may lead to dollarization--high devaluation expectations, inflation rate, significant interest spread between domestic and foreign currency deposits, current account deficits, and inadequate levels of international reserves.

Ize and Levy Yeyati (1998) provided analysis of exchange rate which showed that the share of dollars in the variance-minimizing portfolio depends on the stability of the real exchange rate and of the domestic price level and their correlation.

Some authors have the same conclusions as Barajas and Morales (2003) on exchange rate volatility. Thus, next several studies argued that higher exchange rate volatility, by itself, encourages de-dollarization.

Kokenyne and others (2010) and Garcia-Escribano (2010) show that this happens if two-way movements in the exchange rate are allowed. For example, after observing events in the real world we can conclude that a move toward higher exchange rate flexibility has further contributed to de-dollarization efforts. Such phenomenon happened in Lao P.D.R. (1995), Poland (1995-2000), and Turkey (2001). The evidence also shows that a trend toward local currency appreciation has significantly contributed to deposit de-dollarization in Bolivia, Peru, Paraguay, and Uruguay (2001-10), and that an increase in exchange rate volatility also encourages de-dollarization. The rationale is that the possibility that the local currency may appreciate increases the risk of holding balances in foreign currencies, which may lose value in local currency terms. Other studies, however, purport that the causal relationship between exchange rate volatility and de-dollarization is generally not strong (Berkmen and Cavallo 2010).

In general, most the studies made in the literature have had a primary goal to examine the determinants of long-term dollarization by basically focusing on deposit denominated in foreign currency. In a late survey of the literature, De Nicol et al. (2005) and Levy-Yeyati (2006) sum up the main determinants of deposit dollarization. They included the past rate of inflation in accordance with the currency substitution view (Savastano, 1996 and Sahay and Vegh, 1996), the minimum variance portfolio (mvp) of dollarization share in accordance with the portfolio view (Ize and Levy-Yeyati, 1998), the institutional quality and the exchange rate pegs in accordance with the institutional view (De Nicol et al., 2005 and Rennhack and Nozaki, 2006).

Further we will consider the factors of deposit and loan dollarization discovered earlier for economic regions. Prior analysis by Kokenyne et al. (2010) point out the significant role of macroeconomic stabilization and exchange rate volatility in explaining foreign currency loans for twenty one countries and foreign currency deposits for thirty two countries from Emerging Europe, Latin America and Africa.

Particularly, paper by Naceur et al. (2015) represents the first comprehensive paper which managed to explain the determinants of both foreign currency loans and deposits with a focus on economies of Caucasus and Central Asia. Addressing to this article is relevant since it includes some countries which will be considered in the present research.

As authors show problem of the dollarization in Latin American economies and Emerging European markets is much more thoroughly studied than that in the Caucasus and Central Asia (CCA) countries. In the literature among some relevant studies devoted to the CCA economies, De Nicolo et. al (2005) cover a plenty of countries in addition to the CCA economies and pay attention only at the consequences and causes of dollarized deposits. Honohan (2007) studies short-run deposit dollarization variations as well as the effects of changes in exchange rate using a sample that covers several CCA economies.

Luca and Petrova (2008) concentrate on the factors of loan dollarization only in the sample of twenty one transition economy, which covers five CCA countries. Neanidis and Savva (2009) examined short-run variations in both deposit and credit dollarization taking into account a number of countries with transition economy: Georgia, Armenia, Kyrgyz Republic.

Garca-Escriban and Sosa (2011) studied the loan and deposit de-dollarization experience. They focused on a group of Latin American economies: Bolivia, Peru, Paraguay, Uruguay. Authors found that appreciation of exchange rate was a key driver explaining de-dollarization of deposits, whilst the prudential measures implementation which create incentives for internalization of dollarization risks, the growth of a local currency capital market as well as successful deposit de-dollarization have all made contribution to a decrease in loan dollarization in these economies.

Another economic region that has been analyzed earlier is Sub-Saharan Africa. Mecagni et al (2015) show that efforts devoted to dollarization reduction in SSA economies during the previous ten years had mixed results.

Firstly, dollarization degree has been much higher and more persistent in SSA countries than in the other countries. Secondly, there have been not so many successful episodes of dollarization reduction. On the one hand, a downward trend could be seen in Angola. However, on the other hand, countries like the Democratic Republic of the Congo, So Tom, Liberia and Prncipe still have the same dollarization levels as in 2000s. In addition, the study supports the point of view that depreciation of nominal exchange rate and inflation are main factors of dollarization, favoring the currency substitution aspect that foreign currency is used for hedging against risk of inflation. Instability in politics, dependence on export of primary commodities, limited development of financial market also play a significant role in explanation the SSA dollarization levels.

Authors also give a kind of summary for dollarization problem and ways to solve it. Thus, they conclude that the SSA experience proves the point that successful de-dollarization needs time, coordinated and persistent efforts to introduce an appropriate range of sound macroeconomic policies, microprudential measures, market-based incentives. Direct control and mandatory measures seem to be effective in case when they are used as a supplement to a market-based strategy. Countries in SSA and all around the world that finally managed to cause a significant decrease in the use of foreign currency were successful in introducing sustained processes of stabilization and disinflation, which, in the end, helped to increase the attractiveness of local currency usage.

2. Posing research question

The main goal of the present research is to find out what are the key determinants of dollarization in Post-Soviet union countries. Achieving of the aim requires several measures to be made.

First of all, it is necessary to decide what factors and variables to chose. In order to answer this question I searched for indicators which have already been taken in previous researches. Thus, if to sum up the factors different authors used in their papers, we will find out most commonly used variables which would reflect dollarization process.

However, we need to mention that dollarization is a phenomenon. We are to find a way to measure it. Several approaches to measuring dollarization level exist. As it has already been said, some researchers point out two types of dollarization: deposit and loan dollarization. In this case scholars focus on analysis of financial dollarization. However, it considers only deposits and loans as the approach shows. It does not take into account cash held by residents. It can make up a significant value as it is presented on example of Russia by Timofeev (2015). Unfortunately, inclusion of cash may distort the results because this value is very hard to measure accurately and existent measurements are not solid and quite imprecise.

We will model dollarization degree as difference between M2X to GDP ratio and M2 to GDP ratio in national definition. It is obvious that by subtracting the latter figure from the former we will get the figure of dollarization level in percentage value. Indicators which are considered to explain dollarization degree are next: past inflation rate, exchange rate, differential between deposit interest rate in national currency and deposit interest rate in foreign currency, corruption and banks' net foreign asset.

Then it is worth to explain in brief why these factors may have impact on dollarization degree. Firstly, we will address to inflation indicator. Inflation represents increase or decrease in the country price level. If it goes up the whole price level rises as well. In this case, having the same amount of money as before increase, residents are able to buy less economic goods. Inflation fosters depreciation of savings and cash in national currency. That means if inflation rises economic agents may tend to switch from keeping their cash and deposits in national currency to holding them in foreign currency. Thus, they can make dollarization level grow.

Now it is necessary to focus attention on exchange rate. In the present research this figure depicts how much foreign currency costs in terms of national currency. Thus, economic agent may possess certain assets in foreign currency (for example, dollar). If dollar exchange rate increases then value of the assets will increase in terms of national currency and vice versa. Due to temporary fluctuations of exchange rate some economic agents may desire to increase their wealth by speculation, which can also cause the increase of dollarization degree.

Next we will pay attention to deposit interest rates. Economic agents who wish to place their savings in banks or elsewhere may do it in national or foreign currency. Primary reason of placing money in bank is to get premium in form of deposit percent for allowing bank to use the funds. However, it also serves as a way of saving money purchasing power by preventing its depreciation due to inflation increase. Thus, economic agent compares deposit interest rates in national and foreign currency and chooses the one with the best outcome. By observing difference between deposit interests rate in local and foreign currency we assume that greater difference causes decrease of dollarization, since local currency deposits become more attractive. In addition, if agent supposes exchange rate (for example, dollar) to rise in future (that is national currency will depreciate to dollar) he may prefer to make deposit in foreign currency.

Institutional factor is represented by corruption index. The main assumption here is that a higher figure of the corruption index represents a lower corruption degree. Thus, as the index rises, the institutional dollarization view should prescribe a lower dollarization degree. However, as Neandis and Savva (2009) argue the statistically corruption effect may be diverse and this can happen due to the restricted dataset.

Last variable under consideration is banks' net foreign assets. It is referred to the currency mismatch situation. We include the banks' net foreign assets because banks can match the level of overall liabilities and assets by currency. This fact implies that banks can substitute loans in foreign currency with foreign assets to borrowers in domestic country. That means for a certain level of deposits in foreign currency a short term increase of net foreign assets is likely to decline dollarization degree.

Then the task is to make up database for quantitative analysis. Data will be taken from the official web sites of central banks in each country in Statistics section, World Bank Report World Development Index (WDI), International Monetary Fund statistics and Corruption Perception Index. Thus, we will gain a dataset of 13 countries: Azerbaijan, Armenia, Belarus, Estonia, Georgia, Kazakhstan, Kyrgyz Republic, Latvia, Lithuania, Moldova, Russia, Tajikistan and Ukraine. Unfortunately Central Banks of Uzbekistan and Turkmenistan didn't provide free data for deposit and loan structure by national and foreign currency as well as for the aforementioned ratios of M2. Time interval was defined by the availability of data and covers period from 1995 to 2014.

Next we should also state the hypotheses of the research. Thus, in accordance with the theoretical aspect of each factor effect and with what has been summarized by De Nicol et al. (2005), Levy-Yeyati (2006) and Neanidis and Savva (2009) we can point out several hypotheses related to the impact of each factor. Briefly we can describe them as follows:

a) The first hypothesis is H0: increase in deposit interest rate differential causes decrease of dollarization degree. Against H1: increase in deposit interest rate causes increase of dollarization degree

b) The second hypothesis is H0: exchange rate decrease (appreciation of national currency) fosters decline in dollarization level. Against H1: exchange rate decrease (appreciation of national currency) causes increase in dollarization level.

c) And finally the third one is H0: increase of the net foreign assets decreases dollarization level. Against H1: increase of the net foreign assets causes increase in dollarization level.

Methods that I plan to use encompass Ordinary Least Squares, as proposed by De Nicol et al. (2005) and Levy-Yeyati (2006). In addition, these authors utilized average values over determined period of sample or a concrete year as well as lagged figures as explanatory variables. However, I will use the data on the end of the period chosen to take into account the value of flow, not stock value, since economic agents behavior is determined mainly by end-year figures in some economic variables, not by average values. But I will also use method of lagged variables as mentioned not only by these authors but also by Ponomarenko and Solovyeva (2011) and Neanidis and Savva (2009).

Researchers also recommend running pooled regression as well as fixed and random effect models (Neanidis and Savva, 2009). Estimation by pooling all observations together and running the regression model neglects the cross section and time series nature of data. The major trouble with such model is that is does not distinguish between the various countries in the sample. In other words, combining countries by pooling the heterogeneity or individuality that may exist among companies is denied.

The fixed effect model allows for heterogeneity or individuality among countries by allowing having its own intercept value. The term fixed effect is used due to the fact that although the intercept may differ across countries, intercept does not vary across time - it is time invariant.

In case of random effect model countries have a common mean value for the intercept. The model presumes that individual effects have occasional nature. (Wooldridge, 2013)

However, fixed and random effect models are suitable for usage in certain circumstances due to difference in their nature. Thus, before running fixed or random regression we need to choose an appropriate one. Hausman test will be used in order to decide on which one to choose.

After running regressions we will get estimated influence of each chosen factor. Once we get it we will be able to make a conclusion about positive or negative influence and compare the findings of this paper with previous ones.

Finally, in accordance with the theory and previous studies, we assume exchange rate to have positive sign, whereas deposit interest rate differential and net foreign assets - negative.

3. Methodology

This part of the proposal explains the methods used in carrying out the study. Various authors addressed the estimation of dollarization in different ways. Earlier researches by De Nicol et al. (2005), Levy-Yeyati (2006) are based on cross-sectional ordinary least squares (OLS) regression. They utilized average values over determined period of sample or a concrete year as well as lagged figures as explanatory variables. Such approaches describe the long-term determinants rather than reflecting short-term variations and outwit the problem of some regressors endogeneity to the dollarization level by using lags.

More recently, Neanidis and Savva (2009) have used pooled OLS with robust standard errors adjusted for heteroskedasticity. They next consider the unobserved country-specific effects with the use of the fixed effects estimator on data with period of one year.

While estimating dollarization in Russia Ponomarenko and Solovyeva (2011) based the estimation approach and variables choice on the aforementioned research of Neanidis and Savva (2009) that is considered to be a common draft of a comprehensive review of financial dollarization modeling in emerging markets.

After defining econometric approach it is worth to address the data aspect. This research utilizes yearly data on the supposed key dollarization factors (as exchange rate, inflation etc.) collected from 1995 to 2014 inclusively. Information will be taken from official sources like the Central Banks, World Bank Report World Development Index, International Monetary Fund statistics and Transparency International: Corruption Perception Index. Necessary data is represented by historical observations and has panel data structure: information on several indicators during last several years for a range of countries.

Next the description of the variables will be presented. As has been mentioned earlier the analysis includes six variables: dollarization degree of deposits, inflation, corruption index, exchange rate to dollar, deposit interest rate differential and net foreign assets. After computing all the descriptive statistics the results were formed in two tables and now they are placed in appendix (Table 1, Table 6). Then it is necessary to explain the results.

Table 1

Descriptive statistics

Dollarization degree

Corruption

Deposit interest rate differential

Exchange rate

Net Foreign Assets

Inflation

 Mean

0,098

3,106

3,174

335,182

1,14*1012

14,451

 Median

0,063

2,600

2,225

11,257

2,60*109

7,610

 Maximum

0,624

6,700

22,27

10224,10

3,48*1013

411,750

 Minimum

0,001

1,500

-6,326

0,480

-3,94*1013

-8,525

 Std. Dev.

0,115

1,332

4,692

1268,467

5,57*1012

38,396

Variance Coefficient

116,62 %

42,89 %

147,83 %

378,44 %

488,77 %

265,69 %

 Observations

193

148

93

193

203

193

First of all, after having a glance on mean and median in case of deposit dollarization determinants we can see that only dollarization degree variable has distribution close to normal, since these two figures are relatively close to be equal.

In continuation of the table analysis it is worth to consider skewness and kurtosis values. Skewness is a measure of asymmetry of the series distribution around their mean. Kurtosis measures peakedness or flatness of the distribution of the series.

We can observe that all variables are positively skewed. Thus, since figure of skewness is positive for all variables we might imply that distributions have some outliers. In addition, it means that on average figures of most observations exceed the value of the mode and that sample includes observations with relatively high values - countries with relatively high dollarization, weak local currency, high inflation etc.

In the considered sample kurtosis value is greater than three in all cases, which means all variables are leptokurtic and many values are far away from the mean. More variance is caused by the infrequent extreme deviations. We can make similar conclusion about the variables' values: some countries have relatively high dollarization, weak local currency, high inflation etc.

Jarque-Bera criterion represents a test statistic for testing whether the series is normally distributed. Its p-value for the sample is 0,00000 in all cases. That is another confirmation of no close to normal distribution of these variables. One more argument in favor of aforementioned results is Q-Q plot (Picture 3). We can hardly state that any of the presented quantiles are close to the line of normal distribution. And, in conclusion, the distributions itself is situated in appendix (Picture 4).

Coefficient of variation also reports that none of the samples can be called homogeneous, since none of the values is 33% or less (Table 1). That means data for each indicator varies significantly - from low to high values.

It is also worth to include correlation matrix in order to find out what presumable connection is there between independent and dependent variables. However, we will take into consideration two correlation matrixes. The reason is that deposit interest rate differential covers almost two times fewer observations, than other variables, which can be noticed from Table 1. Thus, we will run two separate regression models with and without this variable as well.

First, we will consider correlation matrix without deposit interest rate differential (Table 2). Matrix shows that dollarization degree and corruption index, exchange rate, net foreign assets are positively and significantly correlated; whereas connection between inflation and dollarization is positive, but not significant.

We can also observe that net foreign assets have positive significant dependence with corruption index and exchange rate. Inflation and exchange rate are positively connected as well. Though the highest correlation value between regressors is close to 0.5, which is moderate, it may cause multicollinearity further. However, to say it for sure, it is necessary to run the regression and then to arrange Variance Inflation Factor test.

Table 2

Correlation Table without Deposit Interest Rate Differentials

Observations: 148

Dollarization degree

Corruption Index

Exchange rate

Inflation

Net Foreign Assets

Dollarization degree

1,000000

x

x

x

x

x

Corruption Index

0,502242

0,0000

1,000000

x

x

x

x

Exchange rate

0,351323

0,0000

-0,078473

0,3431

1,000000

x

x

x

Inflation

0,062620

0,4496

-0,010210

0,9020

0,142266

0,0846

1,000000

x

x

Net Foreign Assets

0,157003

0,0567

-0,157939

0,0552

0,493604

0,0000

0,067187

0,4172

1,000000

x

Second correlation table (Table 3) includes deposit interest rate differential. Here we can notice that deposit interest rate differential and dollarization degree are negatively correlated, however, the connection is not significant. In addition, all other indicators but net foreign assets now have the same signs but connection is insignificant in each case.

In order to identify outliers Box-plot graph will be used. Plotted graphs are presented in Appendix (Picture 5). Graphs show that there are some outliers in each case but corruption index. But taking into consideration economic sense and box plot results we will exclude only some observations. Thus, we have 147 observations left in case without deposit interest rate differential factor and 74 - in case of inclusion.

The final point will be determination of the key drivers. After running the regression we will find out the impact of each considered factor.

To carry out the research it is necessary to define the suitable method that can be used to run the regression model. In this paper method of Ordinary Least Squares will be implemented. Using of OLS is adequate since it has already been proposed by earlier researchers.

Table 3

Correlation Table with Deposit Interest Rate Differentials

Observations: 74

Dollarization degree

Corruption Index

Deposit interest rate differential

Exchange rate

Inflation

Net Foreign Assets

Dollarization degree

1,000000

x

x

x

x

x

x

Corruption Index

0,021621

0,8549

1,000000

x

x

x

x

x

Deposit interest rate differential

-0,135461

0,2498

0,061243

0,6042

1,000000

x

x

x

x

Exchange rate

0,051989

0,6600

-0,189914

0,1051

0,298511

0,0098

1,000000

x

x

x

Inflation

-0,190782

0,1035

-0,191870

0,1015

0,517061

0,0000

0,140409

0,2328

1,000000

x

x

Net Foreign Assets

-0,129541

0,2713

-0,148120

0,2079

-0,007435

0,9499

0,495716

0,0000

0,004139

0,9721

1,000000

x

Also such method as normalization will be used. The reason for its implementation is that different countries due to different size have very distinctive economic figures, which distort the model. In order to provide an accurate computation we need to take into consideration the size of certain country's economy.

Due to the presence of multicollinearity in the model, functional form of some variables might be changed to log form. But all models run will be linear in both variables and parameters. Models will be run using White standard errors in order to avoid heteroscedasticity and get robust estimates.

Also in order to take into consideration the heterogeneity and some individual features of companies we will implement fixed/random effect models. To decide on what model to choose Hausman test will be applied. All calculations will be performed in the program Econometric views ver. 8.0.

Next we need to address the methods of computation for each variable. As it has already been mentioned in previous section we use variables that reflect aspects of dollarization process such as currency substitution, portfolio modeling and institutional. We should also point out one more time the variables which are necessary for the research. Thus, in theory maximum figure of variables that we can consider is constrained by the square root of observation number: = 16,12 (13 countries and 20 years) which does not exceed the number we have chosen.

Taking into account the limitations of data availability, we will use next variables that have been proposed earlier in two basic articles (Neanidis and Savva(2009), Mecagni et. al (2015)): exchange rate to dollar, deposit interest rate differential, net foreign assets, inflation rate and corruption index. As authors have proposed earlier, we will use inflation rate and corruption index as control variables as well.

However, it is also obligatory to give information about the dependent variable. Authors propose different approaches to measuring the phenomenon of dollarization. Thus, some (Neanidis and Savva (2009) estimate separately dollarization degree of deposits and loans on the end of considered period. It is computed and determined as ratio of deposits (loans) denominated in foreign currency to the total value of deposits (loans) of residents (individuals and legal entities) of the country under consideration. Authors implemented first differences of dependent variable and take into consideration its variation across time. This method accurately considers both sides of financial dollarization. However, it has certain flaws. Thus, it takes into account only deposits and loans and neglects cash held by residence which can make up a significant value and may influence estimation. However, inclusion of cash may distort the results because this value is very hard to measure accurately and existent measurements are not solid and quite imprecise.

We will utilize other approach, which, however, considers only deposit side of dollarization. Another reason for using this approach is raising number of observations. It allows to expand database more than two times and include countries that otherwise would not be considered at all. Nature of the approach is easy to demonstrate on an example. Thus, we will address to Russia.

On the 1st of march 2016 money aggregate M2 in national (e.g. ruble) definition made up 31 trln rubbles, whereas indicator of broad money - M2X on the same date equaled 51,4 trln rubbles. The indicator includes M2 and value of deposits in Russian banks in foreign currency. That means a significant portion (17 trln exactly in accordance with the exchange rate) held by Russian individuals and entities was kept in national banks but in form of foreign currency deposits. (Timofeev, 2015)

But it is also necessary to add cash in foreign currency. Its volume reached 47,5 mlrd dollars by the end of 2015 (7,1 mlrd in banks' cash departments and 40,3 mlrd dollars on hands in private sector) that gives another 3,1 trln rubbles with the exchange rate correction.

Picture 2 Money aggregate M2X Data: Central Bank of Russia

In conclusion, total value of money assets in Russia reaches around 55 trln rubbles. The example clearly illustrates the estimated components of money currently circulating in the economy and makes it simple to understand the idea. Next steps in computation of dollarization degree are focused on extracting foreign money portion.

We took data on M2 and Gross Domestic Product (GDP) from International Monetary Fund statistics in section Monetary data based on standardized report forms, Monetary data based on non-standardized report forms and National accounts. Standardized and non-standardized section differs in the countries included. Some report statistics based on certain forms while others do not. Both values were presented in millions that is why in order to get M2 to GDP ratio in national definition we merely divide M2 by GDP.




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