Financial Development and Economic Growth in Bangladesh

1. Financial Development and Economic Growth in Bangladesh 2 April 2019 Jatiya Kabi Kazi Nazrul Islam University Trishal, Mymensingh Qamarullah Bin Tariq Islam, PhD (Glasgow, UK) Associate Professor Department of Economics, University of Rajshahi

2. Outline • Motivation for the Study • Practical Experience • Why Bank-level Study Important? • Features from Earlier Studies & Some Key Variables of Interest • Methodology, Data & Results • Conclusion

3. Motivation for the Study Background • Many studies have already done on the relationship between financial development and economic growth. • This includes: • Country specific study • Cross-country study in a particular region • Cross-country study across regions • To make an original contribution to the literature, it was decided to work on one of the transmission mechanism between these two.

4. Motivation for the Study (contd.) Background (contd.) • Allocation of short- and long-term credit has also been mentioned as one of the channels between financial development and economic growth (Yucel 2009, Das and Guha-Khasnobis 2008). • If these channels work, then it should mean that banks would now be able to lend more. • This would also imply that financial liberalisation (FL) should substantially reduce excess liquidity (EL).

5. Motivation for the Study (contd.) How FL can reduce or remove the EL problem? • One of the main aims of the FL was the increase in the banking sector competition. • To attain this, it was suggested that countries will: • deregulate interest rates, • Privatise and liberalise bank licensing, • lower reserve requirements, • dismantle any credit allocation schemes. • As a result, judicious bankers will allocate funds to the most productive users. • Banks’ ability to give more credit would imply that there should be substantially less EL • In short, the FL should substantially reduce the EL problem.

6. Why FL may fail to reduce EL and increase it? FL includes many policies. All these policies may make the economy less stable and banks may feel uncertain to lend. Before FL, the banks were more confident as the government would have come to rescue the banks in any trouble. After FL, the chance is less which makes the environment risky. If banks are not good at risk management, then they may not lend enough. For a similar reason, banks may also keep/invest their money on government bills and bonds as in most cases the rates are quite high and also they are risk-free. Motivation for the Study (contd.)

7. Why FL may fail to reduce EL and increase it? (contd.) Because of FL, there will be no ceiling on the interest rate and this may increase the interest rate. “higher interest rates induce firms to undertake projects with lower probabilities of success but higher payoffs when successful.” (Stiglitz and Weiss, 1981). On the other side, as interest rate rises, safer borrowers are less able to apply for loans. “[only] high-risk investors are willing to pay more for a loan.” (Blanchard and Fischer, 1989). Motivation for the Study (contd.)

8. Practical Experience Situation of EL in Bangladesh • EL has been a major issue for the economy of Bangladesh. • Various measures taken but still a problem. • “Banks are sitting on piles of excess liquidity” (Bhuyan, 2009). • “Though the BB says there is no liquidity crisis, as a borrower I face it” (Hussain, 2011) • The graph in the next slide shows the EL situation for the period of 1987-2011 in Bangladesh • It reached all-time high in 2009.

9. Practical Experience (contd.)

10. Practical Experience (contd.) Situation of EL in other countries • Economies around the world shows that there is excess liquidity around the world. • EL is present in the African countries (see Saxegaard 2006, Fielding and Shortland 2005, Khemraj 2006). • Also present in China (see Chen 2008, Yang 2010, Zhang 2009). • Similarly in Asian countries. For example, Thailand (Agenor et al. 2004), India (Mohan 2006), Japan (Eggertsson 2005) and Bangladesh (Majumder 2007, Bhattacharya and Khan 2009).

11. Motivation for the Study (contd.) Definition and measurement of EL • EL has been measured differently. The most appropriate definition is liquidity minus requirements. • If data is not available, it can be approximated by liquidity. • In this bank-level study, two possible measures discussed: • the ratio of liquid assets to deposit and short term funds • the above mentioned ratio minus the cash required reserve (CRR).

12. Motivation for the Study (contd.) Definition and measurement of EL (contd.) • The second definition of EL is used here for three reasons: • This is more in line with the appropriate definition. • CRR is that this part of the required reserve must be kept in cash while the other part can also be kept in government bills and bonds. • the explanatory variables includes a measure of the treasury bill rate, so that part of required reserve is not used here.

13. Banks in Bangladesh are normally classified broadly into 4 groups: State-owned commercial banks (SCBs), Depository financial institutions (DFIs), Private commercial banks (PCBs) and Foreign commercial banks (FCBs). Banks can also be classified as: Public or private (1 if public, 0 otherwise) Conventional or Islamic (1 if conventional, 0 otherwise) New or old (1 if new, 0 otherwise) Large or small (1 if large, 0 otherwise) These different types of banks may perform differently or can have different impact when FL happens. Why Bank-level Study Important?

14. Private banks are more efficient than the public banks Private banks are more efficient than the nationalised commercial banks when FL takes place (Abbas and Malik, 2010) Generally new banks perform better than the old It is believed that new banks will perform better in times of FL. However, the empirical results do not always support this view (Kraft and Tirtiroglu, 1998). The possible effect of FL on the Islamic banking is ambiguous On one hand, there is perception that Islamic banks could not take full advantage of the FL as they were comparatively small and narrow in focus. But it is also believed that the Islamic banks were able to cope with the vulnerability and the fragility caused by the FL. (Bashir, 2007). Why Bank-level Study? (contd.)

15. The effect of bank size is also unclear While some argue that large banks perform better in times of FL (Andries and Capraru, 2013; Yildirim, 2002; Berger and Humphrey, 1997), possibly due to the larger market power and their ability to diversify credit risk in an uncertain macroeconomic environment. Some others have observed that the smaller banks are more efficient than the larger ones (Leong and Dollery, 2002; Ataullah, Cockerill and Le, 2004) mainly due to their higher flexibility and adaptability to changes in the banking industry brought about by the FL. Why Bank-level Study? (contd.)

16. Features from Earlier Studies (contd.) Type of study • Most of the studies on the EL problem are done on a specific country at an aggregate level (e.g. Agenor et al. 2004, Aikaeli 2011, Chen 2008, Fielding and Shortland 2005, Khemraj 2008). • Probable reason: Unavailability of EL data or rate of required reserve for each country in any international database. For one country, these were obtained from their central bank. • Only a few studies (Saxegaard 2006, Khemraj 2010) are on cross-country level. All these are on Africa. • Probable explanation: Either used the database created by them or used the data source which have data for most African countries.

17. Features from Earlier Studies: Standard Control Variables • In the earlier studies of EL (e.g. Agenor et al. 2004, Aikaeli 2011, Chen 2008, Fielding and Shortland 2005, Khemraj 2008, Nyagetera 1997, Chirwa and Michila 2004, Jiao and Ma 2007), the determinants that were discussed and used to explain this problem include: • lag of EL (positive), • deposit volatility (positive), • the lending rate (positive), • the rate of required reserve (negative).

18. Some Key Variables of Interest • Supply of credit or loan can be assumed to be very much related with the EL since an increase in the supply of credit from the banking sector should mean that there will be less EL. • Thus EL can be taken as the other side of the coin of credit supply. • So the factors that may affect the supply of credit can also be the factors of EL. • Therefore, loan default can increase excess liquidity situation if banks become more careful in lending. • This is examined with a variable named ‘impaired loan’.

19. Some Key Variables of Interest (contd.) • Another possible factor regarding the liquidity problem can be the treasury bill rate. • Out of the total required reserve for each bank, some part is needed to be kept as cash. This is called the CRR. • The rest can be put in cash or in government bills or bonds. • Since these bills or bonds are from government, they are risk free. Also the rates are quite high in most cases. • So, there is a tendency from the banks to put part of their reserves in the government bills and bonds.

20. Some Key Variables of Interest (contd.) • Finally, the variable that is also of interest to us is the financial liberalisation (FL). • FL has been represented by different variables or measures in different works. • Using dummy variable for FL is also a very common practice. • Since FL is a continuous process, it is very difficult to capture the FL process with only one particular variable. Moreover, it involves many processes together and also the process is an on-going one.

21. Some Key Variables of Interest (contd.) • To overcome these problems, there has been a recent trend to build index of FL • Abiad, Detragiache and Tressel (2008) formed an index of FL where they distinguished seven different dimensions of FL. • These are: credit controls and excessively high reserve requirements, interest rate controls, entry barriers, state ownership in the banking sector, capital account restrictions, prudential regulations & supervision of the banking sector, and securities market policy.

22. Equation of excess liquidity to be estimated in this study can be simply written as: ELit = α0 + β1ELi,t-1 + β2DVit + β3DRit + β4TBRit + β5ILit + β6FLt + β7(FLt*Btit) + εit Some possible methods There are various methods of estimation for the panel data. These include: random effects (RE) estimation fixed effects (FE) estimation, GMM (Generalised Method of Moments) system GMM. Among the first two models of FE and RE, the Hausman test can tell which one is more appropriate. Methodology

23. Advantages of system GMM If the lagged dependent variable is used then it can give rise to the problem of autocorrelation. This possible problem is resolved by GMM as the first-differenced lagged dependent variable is also instrumented with its past level. If lagged dependent variable is used as one of the explanatory variables, the results obtained from the estimates of FE and OLS are both biased (OLS is biased upwards while FE is biased downwards). System GMM gives unbiased result. Thus the estimated coefficient will be higher than FE and lower than OLS. Finally, it has also been observed that this estimator is also efficient for small-T and large-N panels. Methodology

24. Bankscope database was mainly used. Some of the data have also been taken from other sources. These include: Bangladesh Economic Review, paper of Ahmed and Islam (2004), paper of Abiad, Detragiache and Tressel (2008), etc. Dataset is for 1997-2011. Although most banks have 15 years of data but for some, 15 years data are not available. In some cases, there is also some missing years inside the series. Out of 38 banks (excluding the FCBs), data are available for 37 banks. According to categories, data are available for all 4 SCBs, all 30 PCBs, and 3 DFIs (out of 4). Data

25. 37 banks included in the study, represent the banking sector in Bangladesh very well. They account for more than 99 per cent of bank branches of total bank branches. Moreover, they had a share of more than 90 per cent of assets of total assets. Moreover, they had a share of more than 90 per cent of deposits of total deposits. (Source: Bangladesh Bank Annual Report, 2013). Data (contd.)

26. Scatter plot of bank-level EL for the period 1997-2011 Data (contd.)

27. Data (contd.) Correlation matrix of EL and the control variables

28. Results (system GMM) Robust standard errors in the parentheses for coefficients and probability values for others. *, **, *** respectively show significant at 10%, 5% and 1% level.

29. The Hansen test showed that there was no identification problem. The Arellano-Bond (1991) test of autocorrelations showed, with the values of AR(2) test, that there was no problem of autocorrelation. The Wald test, which was equivalent to the F-test, showed that the overall results were significant for all cases. For private banks, 1 per cent increase in financial liberalisation led to an increase of 1.170 while it was even higher for public banks. Results (contd.)

30. Public banks having higher excess liquidity could be due to large number of staffs and lack of technological approach usually less efficient than private ones and hence were less able to cope with financial liberalisation Similarly, small, conventional and old banks also experienced significant increase of 1.278, 1.147 and 1.157 respectively for a 1 per cent rise in financial liberalisation. Results (contd.)

31. New banks differed significantly from old banks and had lower percentage change (1.272) in excess liquidity. This could be due to: coped better with the risky environment better and thereby had less excess liquidity. higher efficiency due to their modern approach applying latest technologies of banking. All new banks had unique goal of profit maximisation while some of the old banks were public and had various social objectives to fulfil. Large and Islamic banks did not experience significant difference. Results (contd.)

32. Results (contd.)

33. Possible explanations Prudent lending: lower NPL (as a ratio of total lending) experienced some increase at the beginning of this study period for a couple of years but then decreased continuously from 1999. Govt. bill & bond: banks might opt towards keeping more reserves in government bills as a second best option in terms of return but a more secured one, without the fear of default. Variations in interest rate: according to different bank-specific characteristics can play a significant role in difference in excess liquidity. Conclusion

34. Possible explanations (contd.) Incomplete financial liberalisation: The financial liberalisation index constructed and applied in this study showed that although liberalisation started in Bangladesh in the early 1990s, it was still far from reaching its completion stage. For example, in slide, it was mentioned that: deregulate interest rates, Privatise and liberalise bank licensing, lower reserve requirements, dismantle any credit allocation schemes. Conclusion

35. Some policy suggestions General policies are not enough and tailor-made policies for different bank haracteristics based on the above findings can be very helpful in terms of effectiveness. Therefore, a multidimensional approach should be taken to get the maximum benefit. Special attention needs to be given for variation in interest rates according to bank-specific characteristics. Conclusion (contd.)

36. Some policy suggestions (contd.) As the financial liberalisation in was still far from reaching its completion stage, hence it is very important that the remaining process is incorporated and accomplished with urgency so that maximum benefit from it can be achieved. Sequencing of liberalisation can also play a crucial role in achieving the benefit from this process. For countries where the process started long back (like in Bangladesh, strengthening the institutional factors is crucial for the success of financial liberalisation (Caprio et al., 2006). Conclusion (contd.)

37. Initial title: Financial Development and Economic Growth in Bangladesh. Final title: Relationship between Financial Liberalisation and Excess Liquidity at Bank-level in Bangladesh. Conclusion (contd.)

38. Thank you