Relationship between Financial Liberalization and Bank Spread

Relationship between Financial Liberalization and Bank Spread

Financial monetary and financial fields have attracted attention of researchers across the world. One of the contemporary challenges in the financial sector is financial liberalization and contemporary capitalism. Some of this challenges have led to enormous benefits. At the same time, the process can pose serious obstacles to economic prosperity and development.  This research will analyze the impact of liberalization on bank spread. The necessity of the study will be to increase knowledge of the process involved in bank liberalization and effects it has on bank spread.
The paper first gives a brief outline on economic liberalization and the composition of financial liberalization. It then outlines the perceived benefits of financial liberalization to the financial sector on a theoretical standpoint. The research will assess whether or not financial liberalization affects bank spread. However, financial liberalization subject cannot be exhausted in this paper. Result of the comparative study will be summarized in the literature review.

1.      Introduction

1.1.            Background

There has been a lot of attention from financial scholars on financial liberalization and effects it has on the economy, financial markets and interest rates. The macro and micro effects of financial liberalization is an important factor not only in the financial sector but also on a government level. Moyo & Roux (2020), links financial liberalization with the great financial crisis of 2008 – 2009. The crisisis brought the issue of financial reforms, in particular, the issue of financial spread was put into the spotlight. According to Bartmann (2017), the main cause of the great recession was as a result of interest rates falling bellow equilibrium that resulted to malinvestment. Under this situation, producers and consumers activities were not coordinated. On the other hand, Jickling (2010) argued that the financial crisis was caused by a drop in savings glut.
Sawyer & Arestis (2016) comprehensively defines financial liberalization as the act of freeing the market and allowing demand and supply forces to determine the market prices, credit and grants. Moyo & Roux (2020) explores that policy process in a wider perspective. In the research, financial liberalization was viewed as a set of operation reforms and policy measures that are designed to transform and deregulate the financial system towards having a liberalized market system. Thus, financial liberalization can be termed as measures directed at dismantling and diluting the control over instruments and activity agents in various financial sectors. These reforms can either be internal or external.
While liberalization is a term used across board, financial liberalization encompass the following concepts: removal or reduction of trade barriers, removal of restrictions in free exchange of goods and services withing a financial sectors. Financial liberalization may also include removal or reduction of tariffs, non-tariff obstacles, license rules, surcharges, duties, quotas and other requirements. The eradication and easing of financial restrictions is also known as ‘free trade’. Interest rate deregulation involve movement towards privatizing interest rate, making it more free-market dictated rather than being regulated by the government. Liberalization may likely lead to discouraging marginal investment, increasing interest rates, improving effectiveness of intermediation, enhancing access to under-serviced sectors and improving monitory transmission. Financial liberalization improve bank spread since it is dictated by the market demand. Thus, financial liberalization may encourage savings in the situation where the investor will get returns. On the other hand, where interest rates will lead to higher cost of capital, the situation will lead to inflation in the economy. Financial institutions will be able to change interest rates to balance the situation.

1.2.            Financial Liberalization

According to Akyüz (2019), financial liberalization consists of deregulation of domestic capital sector, foreign sector capital account and the stock market. The decentralization separates them from domestic sectors. Financial systems play an important role in the economy in a number of functions. Basically, it takes care of mobilizing financial resources, allocate resources to the most important projects, providing a payment system that makes trade among economic participants,  facilitate risk management and monitoring financial resources in exerting corporate governance.
Financial liberalization was intended to improve performance of banks. It is an important ingredient in the generation of high saving investment and savings rates. Additionally, financial liberalization provides a necessary incentives that allow domestic investors to save or borrow. Various researchers have linked liberalization of financial policies to enabling accumulation of equity thereby lowering the cost of borrowing. Similarly, financial liberalization is a necessary financial markets to operate efficiently as well as providing new opportunities for providing financial markets with capital. Dahir & Islam (2010)  defined financial liberalization as the act of eliminating series of impediments in the financial sector to bring it to line of development of the economy. The researcher introduced three types of financial liberalizations: first, financial liberalization may be used to describe domestic financial sector reforms such as increasing credit extensions to the private sector and complete privatization. Secondly, financial liberalization may refer to stock market liberalization aimed at opening up the stock markets to foreign investors as well as allowing domestic companies to access the financial market. Lastly, the financial liberalization may refer to capital market liberalization. According to Sedik & Sun (2012), special exchange rates in the capital account are related. It facilitates domestic companies to borrow money from abroad where reserve requirements are favorable.

1.3.            Bank Spread and Savings

Bank spread, also referred to as interest rates is an important issue in financial policy. It is known to affect savings and borrowing behavior.  It is with no doubt that the interest a short term or a temporary swing. It is known to affect private savings behavior since it is largely governed by plans and expectations of the current or future incomes and expenses. Interest rates alter with the level of savings mainly by affecting levels of income and investments. However, when there is an increase in interest rate that is expected to be permanent, probably as a result of implementation of a policy, consumer behavior is likely to remain the same.  Sedik & Sun (2012) urges that by removing financial repression will have a positive effect on levels of savings. Typically, empirical studies have not been able to distinguish between permanent and temporally changes in interest rates.
Evidence obtained by Sedik & Sun (2012) on savings behavior on a number of developing countries that have changed their interest rate policies show no specific relationship between private savings and interest rates. However, even though that is the case, it should be considered that even according to the conventional theory, the income depends on relative forces of economic forces pushing on the opposite directions mainly the substitution effects and income. Additionally, the income relatively falls to a risen interest rate, the expected future income can be associated with other factors such as fall in savings. This situation may happen when interest deregulation occurs during rapid inflation  or when combined with a sharp decline in employment and income due to microeconomics tightening.
Secondly, interest rate swing may lead to consumption of wealth, especially when the swing is enormous. The process of financial liberalization is expected to increase asset prices and volatility of interest leading to increase in competition in the financial sector. This paper will seek to show the relationship between financial liberalization and bank spreads. It will review the dynamic behavior interest rate before and after introduction of liberalization process. bank rates and bill rates shifted rents from the public sector which in turn favored borrowers. On the other hand, quoted bank spreads in developed countries during the 1990s contracted, while developing countries remained very high. presumably, reflecting the higher risk and market power of lending in the developing countries.
Section 1 and 2 of this research comprise of a review of literature of the global pattern of long term and short-term changes in the interest rate levels and its spread. Section 3 consists of methods used to collect, analyze data and limitations in data collection of used methods. Empirical methods used to analyze the data was to find the dynamics of bank spreads with regard to financial liberalization policies.

1.4.            Research Questions

  • What is the effect of financial liberalization on bank spread?
  • What are the relationships between financial liberalization and bank interest rates

1.5.            Research Objectives

The research was developed to:

  • Examine the effect of financial liberalization on bank interest rates
  • Investigate the relationship between lending interest rates and financial liberalization

1.6.            Study Scope

To understand the real effect of financial liberalization on bank spread, a wide range of data was required for analysis. The study used data from developing countries and developed countries.  Data of 10 countries for periods between 1987 to 2019 was used. Hypothesis to be tested were developed for further analysis.

1.7.            Research Hypothesis

H01 : Financial liberalization has no significant effect on bank rates on developed countries.
H02 : There is no relationship between financial liberalization and bank spreads.

2.       Literature Review

A considerable body of literate has highlighted the importance of financial liberalization in developed and developing countries. It has been linked to economic growth. In a research conducted by Honohan (2000), financial repression is as a result of the government controlling interest rates. Financial systems play an important role in economic development. at the same time, banks and financial institutions play an important role in converting deposits to financial assets. They provide a platform for firms requiring financial assets to access them thereby facilitating formation of trade. Banks also play an important role of knowing who or which company is fit to get a loan through screening borrowers and monitoring their behavior through the bank systems. The process of thus require the banks to have an efficient information system to be able to implement a financial liberalization policy.
Lack of financial liberalization leads dominance, amelioration of growth prospects which may affect growth. On a conventional view, financial liberalization leads to higher growth as a result of increase in loan-able funds through increase in real interest rates. the process increase household savings to bank deposits, therefore increasing bank system efficiency. However, Bai (2016) argued that interest rates can reduce economic growth by reducing credit for business demand.
According to Bai (2016) banking efficiency of banking is characterized by its ability to intermediate spreads, which is difference between deposited taking and lending. Bank systems in developing countries mostly show a persistent and high spread. Similarly, policy makers in Latin America has failed to cover the banks spreads to international levels. The expectation is that the government should remove controls on interest rates and the barriers laid in the financial system. through financial liberalization, the country will increase competition and lower profit margins or interest spreads of banks and other financial institutions. Based on data analyzed by Xiangrong, Jiaming, & Xueliang (2016), the data showed nonlinear impact of financial liberalization and interest rates.
In a research done by Honohan (2016), there has been an increase in the real interest rate since 1960 internationally. Surprisingly, there seem to have a sharp strike feature in the real interest rates in the last 40 years, compared to that of 1980 to 1990s. The swing is evident in both deposit rates and money market. Theoretically, Bai (2016) argued that the variations over the period was due to unregulated, inflation rate and trends in productivity of capital markets and the perceptions of risks. The changes in degree of interest rates and administrative control is another factor that has led to change in interest rates.

2.1.            Impact of Financial Liberalization on Interest Rates of Commercial Banks

With the fast development of social economy and internet technology in financial sector, increase in pressure for competition, reasonable control of financial risks has become important. Currently, bank product and services have changed. Customers have increased innovation of asset business. In this context, financial institutions such as banks are required to increase the content of non-credit asset business. At the end of 2018, the scale of non-credit assets of China’s commercial bank’s non-credit assets grew by 21.2%. Investment business grew at the same time. However, the risk of interest marketization poses a significant threat, especially after implementation of asset structure optimization, implementation of new regulations and commercial bank adjusts.
Financial liberalizations have increased active liabilities of commercial banks. The continuous increase in interest rate liberalization has become inevitable. The impacts has been business debt of financial institutions.  A one year change in time deposited rate will increase deposit rate to increase, leading to increase in bank liabilities. Today, there has been an increase in financial market competition, financial disintermediation and shadow banking. To stay up to competition, commercial banks are expected to increase reasonable price controls, financial products and narrow gap in the basic amount of lending and deposit to meet bank’s development (Barrella, Karima, & Ventouri, 2017).

3.       Data and Methodology

This chapter discusses the empirical methods used to investigate impact of financial liberalization and bank spread. Bank interest rates is determined by many factors. The literature review modeled the framework in which interest rates have been impacted by financial liberalization. However, no single model perfectly describe the behavior through important role of portfolio theory. This chapter specifies models used to test and derive indices for financial liberalization in specific countries. It also consists of estimation techniques that will be used to test the hypothesis.
Data collection method used in the analysis was secondary data. According to Ajayi (2017), data collection plays an important role in statistical analysis. Secondary data collection method relates to data collection method from past. This research collected data from IMF and World Bank, international financial institutions. Literature review also included use of previously done surveys, journals articles, websites etc (Salkind, 2010). This research used both qualitative and quantitative methods. Data collected from IMF and World Bank was analyzed quantitatively to find relationships between variables. Analysis was conducted using Stata V15 and results discussed based on existing research.
Financial institutions seek to maximize profits defined by set of assets and liabilities based on interest rates set per unit cost of producing each component by the bank. This research therefore seeks to increase understanding of the phenomena through testing hypothesis. Empirical specifications were set in this section to understand the behavioral assumptions of the banking firm, behavior of volume of loans, deposit rates and interest rates on loans.

3.1.            Data

Before looking for data, it was important to understand the kind of data was required for analysis. First, the research required to understand measures used to establish financial liberation. According to Hauner & Prati (2008), financial liberalization is measured by simple indexes such as interest rate controls, entry barriers in banking sector such as limitations of foreign bank participation or licensing requirements. The financial liberalization index was collected from the IMF website (IMF, 2019). The database consisted of indices for 180 countries being studied. It comprised of summaries of financial institutions, financial markets, ability of a financial institution to provide sustainable services at a low cost, access to financial services. The dateset comprised of nine indices from 1980. The variables were defined as follows:
FD = Financial development
FI = Financial institution
FM = Financial markets
FID = Financial institutions depth
FIA = financial institutions access
FIE = financial institutions efficiency
FMA = financial markets access
FME = Financial markets efficiency
The financial development index was constructed using three-step approach. It was conducted by reducing multidimensional data summary index: normalization of variables, aggregating sub-indices into final index and aggregating normalized variables to functional dimensions of sub-indices. This research used nine indices to assess levels of abstraction of financial systems across the world. The indices include FID, FIA, FIE, FMA and FME.

3.2.            Model Estimation

3.2.1.      Preliminary Analysis

3.2.2.      Descriptive Analysis

The data was first analyzed using descriptive method. Main purpose of conducting descriptive analysis was to provide a summary and measures of variables being studied. Rozalia (2019) recognized descriptive analysis as a major component of quantitative data analysis. The analysis was intended to be used to come up with conclusion from analyzed data. Analyzed data shown in table 1 breaks down the big data into simple understandable data. The analysis was used to measure the central tendency and variability. Measure of central tendency methods used in this analysis was the mean, described as the sum of variables then divided by the number of values. Secondly, the measures of central dispersion or variation was conducted. the standard deviation, min and max values were calculated to show the spread from the data-set (Sharma, 2019).

3.2.3.      Variable Description

Financial development (FD) was an important financial liberalization index that will assist in establishing whether financial liberalization affected bank spreads. According to Moyo & Roux, (2020), financial reforms have a direct correlation with financial development. The research conducted showed that financial liberalization in undeveloped countries reduced the likelihood of financial crisis. Furthermore, the the policies are likely to strengthen the ruddictive effect of financial liberalization on financial crisis liberalization. The variable was important in our current study since it showed likelihood of increasing bank credit intake (Bai, 2016).
According to WorldBank (2016), financial depth is a measure of financial sector with respect to the economy. It is the size of financial institutions, banks, and financial markets of a country in total and compared to the economic output. It was an important variable in this study since it shows the level of growth of financial institutions. The variable is a good measure of financial liberalization since it does not include local currency GDP, government agencies and public enterprises. Additionally, it does not include credits offered by central banks.
Financial institutions access was used in this analysis. It is an index used to measure the level of financial liberalization. According to O’Toole (2014), there is close relationship between financial liberalization and access to financial institution. Financial liberalization ensures that interest rates are relative to the consumer demand in a specific period of time. It ensure appropriate mobilization of savings, development of projects, risk management and enforcing contracts.
Financial institution efficiency was an important financial liberalization index used to measure how well or badly financial systems are able to allocate necessary resources to economic projects. It is a good measure of financial liberalization. According to Harker & Starvos (2000), bank efficiency is instrumental to efficient functioning of a financial system. It is also important in fueling economies of the twenty first century. The financial institution efficiency was an important variable for measuring financial liberalization.
Financial market efficiency provides important information about current financial status. It is affected by many factors among them being government and financial regulations. An efficient market will be encouraged by proper information and regulations. Mishra (2011) emphasized on the importance of financial liberalization on an efficient financial market. The variable was used to estimate effect it has on bank spreads.
Bank spread was put into consideration as a variable in this research. Bank spreads is the difference between what the bank charges when an individual or firm borrows many and the interest rate a bank pays to the depositor. The bank is used to show how much a financial institution is expected to earn compared to what it give out as debts. The bank spread is affected by regulations in the financial sector and the government. Therefore, the variable will be used to estimate whether financial liberalization affects bank spreads.

3.2.4.      Multi-collinearity

Before the analysis was conducted, we first conducted multi-collinearity to estimate biases and test the hypothesis (Daoud, 2017). A multicollinearlity analysis was used since there were more than one independent variable in the regression model. Correlation between predictors is likely to be higher or otherwise. The data obtained is expected to be in two sets of data one set with low correlation among the predictors. The regression analysis is expected to yield regression information. Simple models were first predicted each at a time. Correlation coefficient of the predictors was very low (-0.038). results were shown in table 2.
The primary concern of this study was to assess the contribution of financial liberalization and bank spreads. Research regressed proxy for liberalization indexes with bank spread over the period. Bank spread consist of interest rates of banks over study period from 1870 to 2020. The liberalization indexes will likely have a potential influence to bank spread. Regression analysis equation was represented according to equation 1 and equation 2. Financial liberalization indexes were set as the dependent variables while bank spread was the dependent variables. Due to potential nonlinear relationships between the variables, all variables were set in a natural logarithm. However, to account for serial correlation error, an error term in the dynamic panel formula was included.
Equation 1: Static Panel Model
regression analysis formula- Relationship between Financial Liberalization and Bank Spread 
Equation 1 to 5 above represent regression analysis formula used to test the relationship between financial liberalization and bank spreads. Equation 1 represents the static panel model, where  is the dependent variable (bank spread) while independent variable. The assumption in the equation was that the liberalization index was normally distributed. Additionally, a multivariant ordered logistic regression (OLS) method was used to deepen the understanding of the nature of relationships among the variables. As a result, the variables were categorized to 5 using a nonparametric OLS model.

3.2.5.      Correlation Models

To further understand the relationships, correlation analysis was conducted. correlation matrix is an important quantitative analysis method. It uses the r2 as a standardized measure or accuracy of a model. Based on Waldmann (2019) research, correlation analysis method is used to monitor the similarity between two variables. Correlation matrix was used to find the show linear relationships between each variable. The correlation coefficient is calculated using the formula shown in equation 6. The x represents the values of independent variable in the independent variable (financial liberalization index) while y is the dependent variable (bank spread). The correlation coefficient obtained in the result will show the relationship from -1 to 1 where – 1 will indicate opposite relationship between variables while 1 means there is a strong relationship. 0 indicates that there is no relationship between the variables. Correlation formula is as follows:
………….. Eq 6
Where: r xy is the correlation coefficient of a linear relationship between the dependent and independent variable (X and Y), xi is the sample value of x variable, is the mean value of the dependent variable (x), yi is the sample value of y valuable (independent variable) and ȳ is the mean value of the independent variable.

4.     Results

This chapter examines results obtained from data analysis. The analyzed data was represented in tables for easy understanding. The descriptive analysis results (table 1) was used to explain data at a glance. Financial liberalization variables consisted of 7,416 observations. The mean of FME, FMA, FMD, FIE, FIA, and FID were 0.313, 0.165, 0.1615, 0.154, 0.5484, 0.2663 and 0.2026 respectively. Bank spread over the study period was 0.313, its min was 0, while the max bank spread was 1.42. Min and max for financial liberalization index variables were 0 and 1 respectively. FIE showed the highest standard deviation of 0.5484 while the lowest standard deviation was the FID variable with 0.222.

4.1.           Correlation Analysis Results

In a research conducted by Ajayi (2017) emphasizes the effectiveness of correlation model in finding the relationships between variables. Mooi & Sarstedt (2014) confirms the finding that financial liberalization impacts bank profits. Regression analysis will seek to establish whether there is a relationship financial liberalization indexes and bank spreads. The analysis confirms findings by Bai (2016) that there is low relationship between financial liberalization policies and bank interest rate. The results (table 3) shows the highest relationship to be between FMD and bank spread with a correlation result of 0.1814. The correlation was between FIA and bank spread obtained was 0.1591, 0.0759, 0.432, 0.1725 and 0.1814 for FIA, FMD, FIE, and FME respectively. The result shows fairly low relationship between financial liberalization indexes and bank spread.

4.2.            Regression Analysis Results

Further analysis was conducted on the data to establish the effect of each financial liberalization index with bank spreads. Results obtained will be used to establish whether we should accept or reject the hypothesis.
H01 : Financial liberalization has no significant effect on bank rates on developed countries.
was used to test the relationship between financial institute depth. The regression analysis results showed high statistical significance. The p-value obtained was <0.05 (p= 0.00). However, there was no close effect of FID to the interest rate spread as shown in r square of 0.0329 (3.29%) rate. The coefficient interval confirms the low relationship between the two variables. The relationship between financial institution access and bank spread showed statistical significance (p value = 0.000), confidence interval of 0.1577 and coefficient value of 0.2402. The r square was also significantly low (r2= 0.0253) indicating low influence of FIA on bank spread. Regression between FMD and bank spread showed statistical significance. The p value was 0.007, very low relationship of 0.0058 (0.5%) relationship shown by the r square. Coefficient value of the regression was 0.1059 and confidence interval of between 0.289 and 1.8299.
H02 : There is no relationship between financial liberalization and bank spreads.
Financial market access (FMA) was also used to test the influence it has on bank spread. The result confirms relationship. However, the influence is low, as shown by r squared result of 0.0298 and p value of 0.000. It indicates that that the FMA influence bank interests and revenue it gets. However, the effect is not significant. The coefficient intervals was between 0.08 and 0.24468 and a coefficient of 0.1859. Lastly, a regression analysis was conducted between FME and bank spread. Analysis conducted showed statistical significance of the two variables FME and bank spread. The P value was <0.05 (p value =0.00) coefficient interval was 0.0216 and 0.401. R squared shows low relationship between the variable of 0.0329. Results are shown in Appendix 1.
We can therefore confirm the null hypothesis (H0) that financial liberalization has no significant effect on bank spread. The analysis confirms with Larbi (2014) research that financial liberalization has no significant with bank spread. The H1 hypothesis that there is no relationship between financial liberalization and bank spread. All the variables showed relationships.

5.     Conclusion

Theoretically, financial liberalization is expected to allow financial institutions to adopt to new market demands. According to Dahir & Islam (2010), government regulation affects interest rates that in turn affect bank spread. Financial liberalization has been linked to financial progress. Banks have been part of financial growth for many economies since they provide financial capital for growth and development. This research is aimed at finding out whether financial liberalization would affect bank spread, which in turn affects interest rates. According to the descriptive analysis conducted in this research confirms the hypothesis. It however rejects the hypothesis that there is no relationship between financial liberalization and bank spreads.
Evidence obtained by Sedik & Sun (2012) on savings behavior on a number of developing countries that have changed their interest rate policies show no specific relationship between private savings and interest rates. However, even though that is the case, it should be considerd that even according to the conventional thery, the income depends on relative forces of economic forces pushing on the opposite directions mainly the substitution effects and income. Additionally, the income relatively falls to a risen interest rate, the expected future income can be associated with other factors such as fall in savings. The research conducted confirms with data analysis results obtained.

6.     References

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Variable Obs Mean Std. Dev Min Max
FD 7,416 0.2577225 0.2086203 0 1
FI 7,416 0.3446006 0.2215784 0 1
FM 7,416 0.1610685 0.2220575 0 1
FID 7,416 0.2025922 0.2301993 0 1
FIA 7,416 0.2663801 0.2670157 0 1
FIE 7,416 0.5484179 0.2253704 0 1
FMD 7,416 0.1540046 0.2290341 0 1
FMA 7,416 0.161553 0.2357638 0 1

Table 1: Descriptive Analysis results

Spread Coef. Std. Err t P>|t| [95% Conf. Interval]
FID -0.08331 0.042185 -1.97 0.049 -0.16607 -0.00055
FIA 0.066822 0.029346 2.28 0.023 0.00925 0.124394
FIE -0.02342 0.024089 -0.97 0.331 -0.07068 0.023835
FMD -0.34736 0.053304 -6.52 0 -0.45194 -0.24279
FMA 0.290977 0.050541 5.76 0 0.191822 0.390132
FME 0.233576 0.031638 7.38 0 0.171507 0.295645
_cons 0.306082 0.01289 23.75 0 0.280794 0.33137