CC BY
12FINANCE
NAREK KARAPETYAN
PhD Student of the Chair of Finance of Armenian State University of Economics, https://orad.org/0000-0003-4978-6107
IMPACT OF DOMESTIC PUBLIC DEBT ON THE BANKING SECTOR IN ARMENIA: IS "LAZY BANK" HYPOTHESIS CONFIRMED?
Only % of the RA Government debt is in the Armenian dram, which poses high FX risks for debt sustainability. Improving the share of local currency debt in the public debt is a big challenge for developing countries, as they often fall into the "lazy bank" trap when the government debt substitutes private sector lending (as a result of rational profitseeking behavior of the banks) and diminishes financial deepening. To test the viability of the "lazy bank" hypothesis for Armenia, a bank-level dataset was built, and fixed effect panel regression models were estimated, which capture the effects of investments in the RA Government bonds on bank profitability and lending. Results of the analysis confirm the hypothesis for only 3 of 17 banks in terms of better financial performance associated with investments in government bonds, and for all 17 banks in terms of distorting private sector lending. These results imply that further deepening of the domestic public debt market imposes significant risks of distorting financial development, which was one of the drivers of post-GFC economic growth in Armenia. The paper concludes that to mitigate risks for financial development, the government should prioritize further reforms aimed at financial integration and liberalization.
Keywords: financial development, "lazy banks", fixed-effects panel regression, multiplier
JEL: H63, G21
DOI: 10.52174/1829-0280_2021_6_7
Introduction.The RA Government has targeted developing the domestic public debt market and increasing its role for state budget deficit financing. In the last two decades, it achieved certain results: national currency (the Armenian Dram) denominated debt composed 24.4% of the Government debt at the end of 2020, when in 2000 it constituted only 8.3%. The Government Debt Management Strategies of recent years set a target to increase it further until a debt structure would be reached, which would mitigate risks of FX shocks.1
What effect of domestic public debt on financial development should policymakers expect for Armenia? Even though the issue is crucial for fiscal, public debt management, and financial sector policies, there is a literature gap studying it. Hence, the paper aims to reveal the impact of investments in government bond on bank efficiency and private sector lending in Armenia. The results of the research are expected to contribute to filling this gap with empirical analysis based on a new dataset, also contributing the literature with one more evidence for a developing country and new evidence for a post-soviet transition economy.
Literature review. There is growing literature analyzing twofold linkages between government debt and the financial sector. On one side of this interrelationship is the impact of financial development on domestic public debt. Following Caballero and Krishnamurthy (2004), lack of financial depth constraints the ability of countercyclical fiscal policy, as with shallow financial intermediation debt-financed fiscal expansion pushes the country risk premium up - resulting in further decline of financial intermediation. Meanwhile, as empirically proved by Kutivazdze (2011), the share of domestic debt in public debt depends on the degree of financial development. On the other side of this interrelationship is the impact of public debt on the financial sector, the nature of which is widely argued in academic and policy circles. The debate is comprehensively described by Hauner (2009), who discusses two alternatives -the "safe asset" and "lazy bank" views. Particularly, on the one hand, domestic public debt can play a positive role for financial intermediation providing "safe assets" in financial markets - highly liquid collateral, which is important for settlement systems and derivative market development and acts as a benchmark for corporate bonds pricing. On the other hand, as emphasized by Hauner, public debt can become a profitable alternative for private sector lending with directing money from the private sector to deficit financing and diminishing financial deepening over time, as it distorts decisions of financial institutions. The banks, which become overly reliant on government bonds, are labeled in policy circles as "lazy banks". Even though Hauner empirically revealed some proofs in favor of the "safe asset" view, he mainly favors the "lazy bank" view, as he empirically reveals that overdependence of banks from government bonds increases their profitability but reduces efficiency when it exceeds a certain threshold or coincides with financial repression. Kumhoff and Tanner (2005)
1 Following the public debt sustainability framework of the IMF, when domestic currency debt surpasses 40% of overall debt, debt portfolio risks are moderate, and when surpasses 80% - low (IMF, 2014).
bring evidence in favor of the "safe asset" view, but also discuss the negative consequences of domestic debt associated with situations of crises and defaults. They argue that government bonds are critical for establishing key infrastructure for the corporate market and act as a benchmark for the corporate yield curve. Meanwhile, when the banking system of a developing country is considerably reliant on government bonds, the debt default or debt devaluation would have a severe negative impact on financial development. Emran and Farazi (2009) revealed empirical evidence in favor of the "lazy bank" view. They have estimated the impact of government borrowing from financial markets on bank lending based on a sample of 60 developing countries spanning from 1975 to 2006, and found out that 1 dollar increase of public borrowing reduces private sector lending by 1.4 dollars. Ismihan and Ozkan (2010) also argue for the "lazy bank" view - basing the analysis on a theoretical model. They affirm that state borrowing from the banking sector reduces private sector lending and disturbs financial development. Moreover, the lower the financial deepness of the country is, the more the financial deepening will get disturbed. Janda and Kravtsov (2017) claim that although public debt can harm financial development in the long and medium run, it can impact positively on bank efficiency in the short run. They analyzed the impact of domestic public debt on financial development for Central Eastern Europe, the Balkan and Baltics region based on data spanning from 1995 to 2014, studying the impact focusing on liquidity and risk channels of transmission. Their empirical results showed that an increase in domestic public debt impacts negatively bank lending in the long and medium-term. Yet, domestic public debt can have a positive impact on the efficiency of the banks in the short run. Bui (2018) draws the link between financial freedom and integration to public debt's effect on financial development. Particularly, using a data panel of 22 Asia-Pacific countries he has estimated the effect of domestic public debt on financial development, and concluded that domestic public debt crowds out private sector lending in countries with low financial freedom and low integration to global financial markets. He claimed that the negative effect can be reduced with deeper financial integration and enhanced financial freedom. Gray, Karam and Turk (2014) analyzed the issue of low financial intermediation in the Middle East and North Africa and discussed how the public debt impacts the degree of financial deepness. They argue that the domestic public debt crowds out the private sector lending with two channels: increase of interest rates and maturity mismatch, limiting the appetite of banks for long-term private sector financing.
In conclusion, the literature review has demonstrated that there is no single view regarding the impact of domestic public debt on financial development. But it showed that the impact can be undesirable in the financial system with low openness and liberalization. Moreover, the linkage is most probable to have non-linearities, particularly it can be positive at some initial stages than become negative from a level which is related to characteristics of the economy. Hence, individual estimates are necessary to understand the linkage for the Armenian economy.
The method. For the analysis, a panel dataset based on bank interim financial reports from 2015 to 2020 is built, which cover 17 Armenian banks. Although the data span is relatively short, it includes domestic public debt market deepening of last five years, when domestic public debt increased from 6.4% in 2015 to 15.5% of GDP in 2020, the cycle of monetary policy loosening (which started in 2015 and ended in 2020), and two stresses for the banking sector - in 2015 and 2020. Overall, the dataset is sufficiently informative for carrying out the analysis.
Given that the Armenian banking system passed through several consolidations during that period, the initial data from bank reports is modified to make them consistent over time (Table 1).
Table 1
Banking system consolidation during 2015-2020
Before the merge/acquisition deal | After consolidation | Data of consolidation |
Ardshinbank CJSC Ardshinbank CJSC 2016Q4
Areximbank-Gazprombank Group CJSC
Araratbank OJSC Araratbank OJSC 2016Q4
Armenian Development Bank CJSC
Armeconombank OJSC Armeconombank OJSC 2016Q4
BTA Bank CJSC
InecoBank CJSC InecoBank CJSC 2015Q4
ProCredit Bank CJSC
The data panel includes 17 banks (21 before the consolidation) for 24 quarters - overall 408 observations for each variable. The analysis is built on indicators measuring financial aggregates of the banks (assets, loans, investments in the RA Government bonds measured in Armenian Drams), the efficiency of the banks (ROA and ROE), and indicators that capture the investment strategy of the banks (shares of RA Government bonds and private sector loans in assets).
Table 2
Statistical properties of the data panel
Private sector loans, bln AMD
Assets, bln AMD
Investment in the RA Government bonds, bln AMD
Return on assets, quarterly, %_
Return on equity, quarterly, %
Net interest income/assets, quarterly, %_
Investments in RA Government bonds/assets, %
Private sector loans/assets, %
In addition, Armenia's economic growth rate (quarterly, y/y)2 and the RA treasury bond GMI index by the RA Central Bank (which captures all coupon bonds with maturity larger than one month3) is also used as control variables, the first to represent macroeconomic environment of the banks, and the second to represent the trends of government bond prices. Overall, the selection of
Min. Mean Max. Standard deviation
5.6 27.0 0.8 -2.3 -16.3 0.2 0.5 11.7 172.6 269.1 OK Q 720.1 1090.6 OflQ A 145.0 201.2 OR 1
26.9 0.3 1 c; 209.4 2.1 11 25.1 0.5 O 7
1.5 io c II.3 2.3 RR Q 2.7 0.4 10 £
13.5 58.9 56.9 82.6 12.6 14.7
2 Source: RA Statistical Commite, https://www.armstat.am/en/?nid=202
3 Source: Central Bank of Armenia, https://www.cba.am/Storage/EN/fin/Index%20history.xlsx
variables follows both the literature review and statistical analysis carried out with a large spectrum of variables.
To analyze the impact of government bond investments on bank performance, fixed effect panel regression models are built, expressed as follows:4 Cti£ = B^+RzXt,E+^,¡ = 1,2, ...,17
where C denotes dependent variables (expressing bank financial aggregates or efficiency indicators), Bi is the intercept, B2 is the vector of slope coefficients, Xt is the vector of independent variables (expressing asset structure of banks or control variables), t is time index by quarters, and Et is the error term of the regression model.
Analysis and results. The investments in the RA Government bonds relative to banking sector assets slightly increased from 8.8% to 11.3% during 2005 to 2020 and maintained a relatively low level of pressure on the banking sector in international comparison.5 Figure 1 represents the asset structure of banks for 2015-2020, which shows that almost half of the banks have lower than 10% of their assets invested in the RA Government bonds, and 3 banks have their ratios in the 20-50% range. These banks have relatively low shares of their assets invested in private sector lending.
■ RA Government Bonds ■ Private sector loans Other assels
Figure 1. Asset structure of the RA banks, % in assets, average 2015-2020
To account for the heterogeneity of investment strategies of banks in terms of two investment alternatives (private sector loans and government bonds) in the empirical analysis, clustering is applied. Following the asset allocation strategy, banks are grouped into 2 clusters (subgroups). The banks that are included in Subgroup 1 allocate a bigger part of their assets (60-70%) in private sector loans and a little part (5-10%) in the RA Government bonds. The banks that are included in Subgroup 2 (3 banks only) on average allocate a larger part of their assets in the RA Government bonds than in private sector loans.6
4 In the fixed effects regression, the intercept will differ across the banks, but each banks' intercept will not vary over time.
5 Kumhof and Tanner (2005). View around 10% of bank asset invested in government bonds more typical for industrial countries, whereas in developing countries 20-40% ratios are more typical.
6 Possible different determinants of asset allocation strategies are not accounted in the paper, keeping it for further research.
80 70 SO
* Su bg rou p 1 * Subg rou p 2
■p '■V ^ v<3 Byblos Bank Armenia
S 50 CJSC ArmSwissBank CJSC
s ,5 I 40 30 # 0
■ii Vi 4 20 Mel 1st Bank CJSC •
10
£ n
0 5 tO 15 20 25 30 35 40 45 50
RA Government bonds/assetsr %
Figure 2. The grouping of RA banks following the asset allocation strategy7
First, the financial performance of two subgroups is studied, which did not show clear differences in efficiency between the two subgroups. Specifically, as Table 3 demonstrates, despite that the net interest income of banks relative to bank assets is slightly higher for Subgroup 1 banks, return on assets is almost two times higher for Subgroup 2 banks. The return on equity is higher in Subgroup 1, as the Subgroup 2 banks have a more than two times larger ratio of equity to assets (which can also imply that higher ROA can also be attributed to high capital adequacy).
Table 3
Performance of RA bank subgroups (if otherwise not stated, average 2015-2020)
Subgroup 1 Subgroup 2
The RA Government bonds in bank assets, % Private sector loans in bank assets, % u .t <J 1 . 1 64.5 32.8 17.4 37.5 4.3 4.0 1.1 2.0 6.3 4.9
Bank equity/assets ratio, % Net interest income in bank assets, % (annualized)
Return on assets, % (annualized) Return on equity, % (annualized)
Second, different fixed effects panel regression models are estimated to reveal the impact of investments in the RA Government bonds relative to banks' assets on the banks' financial performance. Table 4 describes the results of the regression model capturing effects on ROA (return on assets). Effects, as discussed, are estimated based on 3 samples: all banks, Subgroup 1, Subgroup 2. The estimates are controlled with economic growth rates (to capture macroeconomic developments), bank size (expressed by bank assets to capture the economy of scale effect), and bond price GMI index (to capture the effect of bond price changes on bank performance). The results indicate that investments in the RA Government bonds impact positively ROA based on analysis of all banks and Subgroup 2 (the effect is larger for the latter), but there is no statistically significant link for Subgroup 1 banks. The ROA of the latter is positively associated only with macroeconomic developments (economic growth rates), and in Subgroup 2 banks, in addition to investments in the RA
7 I applied K-means algorithm, which, as cited in Zhu and Liu (2021), is the most widely used clustering method so far, whose biggest advantage lies in its simplicity, speed and objectivity, being widely used in many research fields such as data processing, image recognition, market analysis, and risk evaluation.
Government bonds, the bond price index is a statistically significant determinant. The regression model based on Subgroup 2 banks has better goodness of fit than the model based on the whole sample and Subgroup 1.
Table 4
Fixed effect panel regression model estimation results for ROA8
Return on assets (ROA)
| All banks | Subgroup 1 | Subgroup 2
Log (the RA Government bonds / assets) 0.08 -0.02 0.81***
Log (Economic growth rate) 1.15*** n 1A 1.10*** n CO 0.76 n vc:**
Log (Assets) Log (GMI index) c 0.14 0.10 0.07 0.11 c 7c*** -0.7 5 1.01* 7 70*
C R-squared -0.40 0.34 -5.75 0.28 -7.72 0.56
The impact of investments in the RA Government bonds on ROE is significantly positive only for Subgroup 2, but for Subgroup 1 a negative impact (in 10% confidence level) can be accounted for. As was the case for the model for ROA, economic growth rates determine banks' ROA for the whole sample and Subgroup 1, whereas the bond price index is the only statistically significant determinant for the whole sample and Subgroup 2 banks. The impact of bank size is nonsignificant for the whole sample and Subgroup 1 banks and is significantly negative for Subgroup 2 banks. Like regressions with ROA, the model built on Subgroup 2 has better goodness of fit.
Table 5
Fixed effect panel regression model estimation results for ROE
Return on equity (ROE)
| All banks | Subgroup 1 | Subgroup 2
Log (the RA Government bonds / assets) 0.05 -0.52 0.10**
Log (Economic growth rate) 6.40*** 1 17* 6.19*** n RR 0.05 pi no**
Log (Assets) Log (GMI index) c 1.17 0.65 07 oc*** 0.55 0.97 OA r\C*** -0.02 0.02** Q A&*
C R-squared -37 .85 0.30 -34.06 0.29 -9.88 0.47
Third, the impact of investments in the RA Governments bonds on private sector lending is estimated - using the first differences of variables and controlling the estimates with bank size. Results indicate that for the whole sample 1 dram increase of bond investments reduces private sector loans by 0.4 drams. For Subgroup 1 banks the negative multiplier is roughly the same, but for Subgroup 2 it is small and is equal to 0.2.
Table 6
Fixed effect panel regression model estimation results for private sector loans
■■'■ Private sector loans
A Investments in the RA Government bonds All banks Subgroup 1 Subgroup 2
À Assets -u.ti -u.j;7 -yj. 1 u 0.53*** 0.54*** 0.23*** 1.34** 1.61** 0.79** 0.56 0.59 0.41
C R-squared
8 In the tables * denotes that the coefficient is significant in 90% confidence level, ** denotes 95% confidence level and *** denotes 99% confidence level.
But there is also strong heterogeneity in the results across banks. To demonstrate it, the cross-section effects9 of the model are shown in Figure 3. The analysis of cross-section effects shows that, in general, for larger banks the crowding-out effect is stronger, and it is the weakest for Subgroup 2 banks.
Figure 3. Cross-section effects of explaining private sector loans
Summary and discussion. Being a post-soviet small economy, Armenia is still in the process to establish a deep and liquid domestic debt market, which would provide a possibility to manage public debt minimizing the FX risk - critical for debt sustainability. But as domestic public debt market deepening has its advantages like having a low-risk debt portfolio and providing stimulus for corporate financial market development (known as "safe asset" view), it also has important drawbacks, such as the crowding-out effect. Hauner (2009) describes this with the "lazy bank" hypothesis, meaning that government bonds can become a profitable alternative to private sector loans, which diminishes financial development over time. Further literature acknowledges that domestic government borrowings in developing countries crowd out private sector loans, but the negative impact can be mitigated with financial integration and liberalization reforms.
To test the "lazy bank" hypothesis for Armenia a bank-level panel dataset has been built. Although the reliance of the banking system on government bonds is low and can be compared with developed countries, the analysis showed quite high heterogeneity in banks' asset allocation strategies, as some of the banks have a high reliance on investments in the RA Government bonds. Therefore, the sample was divided into two subgroups. Subgroup 1 involves banks with low reliance on the RA Government bonds and Subgroup 2, which involves only 3 banks with high reliance on the RA Government bonds (from 20% to 50% of assets allocated in RA Government bonds). The Subgroup 2 banks can also be considered as "lazy" banks - following the logic proposed by Hauner (2009). A comparative analysis of bank performance in the two subgroups yielded uncertain results, as Subgroup 2 banks have on average higher ROA, but lower ROE. The analysis was turned to fixed effects panel regression models, which indicate a statistically positive impact of the investment in the RA
9 Cross-section effect constitutes the deviations of individual intercepts from the model intercept.
Government bonds relative to assets to ROA and ROE. Meanwhile, statistically significant results were not detected in Subgroup 1, and it was revealed, that Subgroup 2 banks ("lazy banks") drive the overall results. The impact of investments in the RA Government bonds on private sector lending also was estimated, which indicated that for the whole sample 1 dram increase of bond investments (under other unchangeable conditions) reduces private sector lending by 0.4 drams. But these estimates are very different across the cross-section of the banks, as the crowding-out effect is stronger for larger banks and smaller in "lazy" banks, which can be explained by the high capital adequacy and liquidity of the latter.
In general, our results confirm the "lazy bank" hypothesis for a smaller part of Armenian banks in terms of positive impact on the profitability, and for all banks in terms of negative impact on private sector lending. For the banks the hypothesis is fully confirmed (confirmed both in terms of impact on profitability and lending), high reliance on government bonds is associated with better financial performance and diminishes financial deepening. Referring to the literature, a key reason for the negative impact on financial deepening can be attributed to low financial integration with international capital markets, specifically, the near absence of foreign investors in the domestic debt market10. The paper signals to debt management and financial sector policymakers the risks steaming from further deepening of the domestic public debt market for financial development, which can be mitigated with reforms aimed at financial integration and liberalization.
References
1. Aizenman, J., Jinjarak, Y., Park, D., & Zheng, H. (2020). Good-Bye Original Sin, Hello Risk On-Off, Financial Fragility, and Crises? (No. w27030). National Bureau of Economic Research.
2. Bui, D.T. (2018). How Financial Freedom and Integration Change Public Debt Impact on Financial Development in the Asia -Pacific: A Panel Smooth Transition Regression Approach. Australian Economic Review, 51(4), 486-501.
3. Caballero, R.J., & Krishnamurthy, A. (2004). Fiscal policy and financial depth (No. w10532). National Bureau of Economic Research.
4. Carstens, A., & Shin, H.S. (2019). Emerging markets aren't out of the woods yet. Foreign Affairs.
5. Eichengreen, B., & Hausmann, R. (1999). Exchange rates and financial fragility (No. w7418). National bureau of economic research.
6. Emran, M.S., & Farazi, S. (2009). Lazy banks? Government borrowing and private credit in developing countries. Government Borrowing and Private Credit in Developing Countries (June 11, 2009).
10 As of end-2020 only 0.3% of the Treasury bonds of the RA Governments are in the hands of non-residents.
7. Hauner, D. (2009). Public debt and financial development. Journal of development economics, 88(1), 171-183.
8. IMF Policy Paper (April 1, 2014). Revised Guidelines For Public Debt Management. prepared by IMF and World Bank staffs. https://www.imf.org/en/Publications/Policy-Papers/Issues/2016 /12/31/Revised-Guidelines-for-Public-Debt-Management-PP4855
9. Ismihan, M., & Ozkan, F. G. (2012). Public debt and financial development: A theoretical exploration. Economics Letters, 115(3), 348-351.
10. Janda, K., & Kravtsov, O. (2017). Time-varying Effects of Public Debt on the Financial and Banking Development in the Central and Eastern Europe.
11. Kumhof, M., & Tanner, E. (2005). Government debt: A key role in financial intermediation.
12. Kutivadze, N. (2011). Public debt and financial development. Universita degli Studi di Milano.
13. RA Government (2020). RA Government Debt Management Strategy of 2021-2023. https://minfin.am/website/images/files/73ea9cb9.doc
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001: 10.52174/1829-0280_2021_6_7
НАРЕК КАРАПЕТЯН
Аспирант кафедры финансов Армянского государственного
экономического университета
Влияние внутреннего государственного долга на банковский сектор Армении: подтверждается ли гипотеза о "ленивых банках"?- В настоящее время только четверть государственного долга Армении выражена в драмах, что создает большие валютные риски для устойчивости долга. Увеличение в государственном долге доли долга в национальной валюте является большим вызовом для развивающихся стран, поскольку они часто попадают в ловушку «лени-вости банков», когда государственный долг заменяет кредитование частного сектора (в результате рационального стремления к прибыли со стороны банка) и замедляет процесс финансового углубления. Чтобы проверить жизнеспособность гипотезы о "ленивых банках" для Армении, была разработана база данных на уровне банков и были оценены регрессионные модели панельных данных с фиксированным эффектом, которые отражают влияние инвестиций в государственные облигации РА на прибыльность и кредитование банков. Результаты анализа подтверждают гипотезу только для 3 из 17 банков с точки зрения лучших финансовых показателей, связанных с инвестициями в государственные облигации, и для всех 17 банков с точки зрения ухудшения кредитования частного сектора. Результаты предполагают, что дальнейшее расширение внутреннего рынка государственного долга создает значительные риски искажения финансового развития, что было одним из драйверов экономического роста в Армении после глобального финансового кризиса 2009 года. В статье делается вывод о том, что для снижения рисков с целью финансового развития правительство должно уделять
первостепенное внимание дальнейшим реформам, направленным на финансовую интеграцию и либерализацию финансового рынка.
Ключевые слова: финансовое развитие, «ленивые банки», регрессионные модели панельных данных с фиксированными эффектами, мультипликатор Н63, в21
001: 10.52174/1829-0280_2021_6_7
