Logarithm specification

Notes: * - 10%significance level,**-5% significance level,***-1%significance level

Finally we will estimate fixed/random effect model for log specification. With the use of Hausman test we determine that we should use fixed effect model (Table 9). The results of estimation are mentioned in Table 5 (Pooled regression (7)). Here as well we have to exclude corruption index so as to get rid of multicollinearity (Table 10).

In the final model with log specification all variables under consideration are significant (Table 5, Pooled regression (8)). Exchange rate increase positively influences dollarization, whereas rise in net foreign assets and deposit interest rate differential have negative impact. The whole model is significant as well and as R2-adjusted reports it explains almost 17% of the total variation.

Then we will give detailed interpretation of the effects.

a) If exchange rate rises by one unit, then deposit dollarization rises by 4,692 percent holding all other variables constant.

b) If net foreign assets rise by one unit, deposit dollarization falls by 2,2*10-9 percent holding all other variables constant.

c) If difference between deposit interest rates in national and foreign currency increases by one unit deposit dollarization declines by 7,166 percent holding all other variables constant.

What is more, though coefficient of corruption index is insignificant in fixed effect regression it has the right side as has been earlier found by Neanidis and Savva (2009). Also positive effect of exchange rate is persistent in all models. Inflation coefficient shows inadequate sign almost in all cases, but it is insignificant.

In accordance with the results mentioned earlier we can conclude that all three stated hypotheses have been confirmed. Thus, for Post-Soviet union countries we can say that rise of exchange rate has positive effect on deposit dollarization degree, whereas increase in both deposit interest rate differential and net foreign assets - negative.

Conclusions and limitations

Now we need to sum up the conclusions and discuss the results. Thus, research signifies that stronger currency, more attractive deposit interest rates in national currency and rising net foreign assets are important determinants of deposit de-dollarization for Post-Soviet Union countries. Such conclusions fully correspond to what authors have previously gained in their articles (see Theoretical Background). What is more, all of the hypotheses have been accepted. However, we need to take into account that some factors were not significant and we had to exclude several variables from regressions.

The present study approaches dollarization from deposit point of view. In future research it would be relevant to consider loan aspect of dollarization as well and use data of a higher frequency to increase number of observations.

It is also worth to expand the research by replacing some factors or including other factors which would allow making more accurate estimation. For example, in future it would be interesting to replace CPI-index with GDP deflator as an inflation factor and compare the results.

Next we need to mention that any research has certain limitations. This one does as well. First of all, since I take data only for a certain economic zone - Post-Soviet states - findings of the project can not be used for other economic zones. It is obvious that each country is placed into unique economic and political situation at any point in time and using the results for others is unacceptable.

Secondly, it is also necessary to focus attention on time constraints: time period used in the research considers 20 years. We do not consider the earlier data, due to constraints of data availability.

What is more, by the time this study is finished, new data for year 2015 (which can possibly have influence on the results) will become available. However, it will not be taken into account, since all the implications will be made by then.

In addition, not all countries were taken into consideration. Some of them did not provide available data of M2 and M2X aggregates, which mean that deposit dollarization figures could not be calculated via the utilized method.

Another limitation implies: due to the fact that data on dollarization degree was missing for some periods for different countries, the gained effects might be imprecise or may significantly differ from the genuine ones.

Methods used for computation of deposit interest rates in different countries are different as well. This fact limits their comparability. Thus, for instance, in Russia rates were calculated as average of deposits with period of one month, whereas in Azerbaijan International Monetary Fund computed average of twelve months deposit interest rates (IMF: Country Notes).

One more limitation concerns that exchange rate. Explanation is straightforward: if dollar appreciates against local currency then the whole value of dollars expressed in national currency would rise, which would result it increase of M2X and consequently in dollarization degree. In this case, dollarization degree changes without any economic transactions: if nobody sells or buys dollars it still changes. However, reality differs and a large number of economic transactions happens each day. That means the estimated exchange rate coefficient encompasses two effects: dollar appreciation (depreciation) and foreign exchange operations. However, it is very difficult to separate such effects, since it raises doubt whether we can precisely observe foreign exchange operations. One more trouble causes presence of operations with other currency (e.g. Euro, Yen, GBP etc.). Nevertheless, we can recommend using first differences of exchange rate in order to avoid foreign currency appreciation (depreciation) effect.

Finally, the research is exposed to the problem of endogeneity, which means that we can not include all the factors which affect deposit dollarization. There will always be some of them left without attention.

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Appendix 1

Table 6

Descriptive statistics

Picture 3 Q-Q plot graphs

Picture 4 Distribution Graphs

Picture 5 Box-Plot graphs

Appendix 2

Estimation results

Table 7