The impact of economic growth on the financial sector of the economy of Latvia

Theoretical background

The connection between the operation of the financial system and economic growth has been one of the most heavily researched topics in development economics. A lot of scholarly papers have been written with the aim to verify how the development and structure of an economy’s financial sector affect domestic savings, capital accumulation, technological innovation, and income growth, or vice versa.

There is an evidence of a statistical relation between finance and growth, which indicates causal link running from finance to growth. However, the relationship where high economic growth creates demand for more financial services and thus stimulates the development of the financial sector is equally possible. For instance, Demirgüc-Kunt and Levine [2] demonstrate that banks, other financial intermediaries and stock markets are larger, more active and more efficient in high income countries. As far as the link between finance and growth is concerned, for a long time, it was common to say that finance affects growth. Moreover, Levine [3] argues that the growth-maximizing mixture of financial markets and intermediaries may depend on economic development and also on legal, regulatory, political, and/or other factors.

Data and model

According to the literature, the generalised equation describing the impact of economic growth on the size of the financial sector may be as follows:

(1) Y = a0 + a1 GDP + a2CPI + a3Inf + a4Int + a5HTe + a6Inv + e

Table 1. Description of the equation

According to the coefficient of determination, the regression model is described by correct variables, as R2 is more than 70%. Moreover, F-test shows, that F is more than Fcrit (Fcrit is approximately 2,85). It means that R2 is significant in the model. Thus, the model is described by its variables by 70%.

As for testing the significance of coefficients, standard errors of the coefficients of the regression model should be less than their value. This rule is not fulfilled for the following variables: GDP, Inf , Inv.

This result ruins the main hypothesis that financial market development depends mainly on the growth of the GDP. Furthermore, inflation and net investment in nonfinancial assets are also insignificant in the model.

So we found out that the more correct equation will be as follows:

(2) {

Y = a0 + a2CPI + a4Int + a5HTe + e R2 = 0,88 F = 43,3

Variables describe 88% of the model and each variable is significant.

The fitted model is as follows:

• (3)    Y fitted = - 7,02 + 1,23 CPI - 2,46 Int - 4,43 HTe

  Y predicted (1996) = 2,192. Confidence intervals of predictive values are as follows: -16,64 < Y 1996 < 21,02. So, Y real(1996) appears to be inside the interval. Thus, the model can be called adequate.

In order to check the model for homoscedasticity the Goldfeld–Quandt test was used. GQ = 0,45, GQ(-1) = 2,18 what is less than Fcrit = 3,16. It means that there no heteroscedasticity in the model. With the aim to check autocorrelation Durbin–Watson test was used. Calculated d for the model is in the interval with uncertainty level, so other variables may exist that describe the model.

Conclusion

As far as correlation between financial market development and economic growth is concerned, the analyses showed that the first can be described by the second but with several limitations. The financial market development was represented as a domestic credit provided by financial sector. The choice was predetermined by the specific characteristic of Latvian financial market (inclusiveness into European financial market). Such indicator can be described by such economic variables as consumer price index, high-technology and export real interest rate while GDP per capita growth, inflation, and investments in nonfinancial assets have not significant role. Such dependence may be explained as follows: financial market participants actively use these two variables when deciding whether to invest in financial instruments. So, the rise of consumer price index by 1% leads to the change in domestic credit provided by financial sector by 1,23% of GDP. As for real interest rate – when it rises by 1%, domestic credit provided by financial sector declines by 2,46% of GDP. The model is adequate and appropriate for predicting the domestic credit provided by financial sector, however, there can be other variables that have also significant impact. However, such factors may be immeasurable, for example legal, regulatory, political, and other factors.