## Financial Development and Growth in the Caucasus and Central Asia — Working Paper No. WP/22/134

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### I. Introduction
- Objective:
  - Provide stylized facts on financial development in the Caucasus and Central Asia (CCA) and assess how financial development can boost growth in these countries.
- Theoretical and empirical background:
  - Financial development mobilizes savings, supports efficient allocation, raises potential output (King and Levine, 1993; Levine, 1997).
  - Sahay and others (2015) develop a multidimensional Financial Development Index (institutions and markets; depth, access, efficiency) showing a bell-shaped relationship between financial development and growth.
- Main approach:
  - Use Sahay and others (2015) Financial Development Index updated through 2019.
  - Present stylized facts, benchmark CCA against EM and LIC peers, and re-estimate standard growth regressions to quantify growth gains from financial development.

### II. Financial Development in the CCA: Stylized Facts
- Data and index construction:
  - Overall Financial Development Index (FD) = financial institutions index (FI) + financial markets index (FM); each with sub-indices depth, access, efficiency.
  - Indicators normalized between 0 and 1; data winsorized at 5th and 95th percentiles.
  - Sample: seven CCA countries—Armenia (EM), Azerbaijan (EM), Georgia (EM), Kazakhstan (EM), Kyrgyz Republic (LIC), Tajikistan (LIC), Uzbekistan (LIC). Turkmenistan excluded due to data limitations.
- Evolution 1993–2019 (key points):
  - Armenia and Georgia: FD more than doubled from around 0.1 in 2000 to around 0.2–0.25 in 2019.
  - Kazakhstan: FD rose from 0.15 in 2000 to 0.4 in 2008, then declined and converged to 0.3 in 2019.
  - Cross-country dispersion: early 2000s FD range ~0.08–0.15; in 2019 FD ranged from 0.1 (Kyrgyz Republic and Tajikistan) to 0.3 (Georgia and Kazakhstan).
  - Early 2000s: FD in five CCA countries was below average LIC; by 2019, FD exceeded average LIC in five CCA countries and two converged to average EM.
- Financial institutions versus markets:
  - FI > FM across all countries (bank-dominated system); banks represent almost 90 percent of total financial system assets in the CCA.
  - Kazakhstan is an exception where FM is relatively higher (FM data for Kazakhstan should be interpreted with caution).
  - FI improved in most CCA countries and exceeded LIC average in 2019; FM stagnated and remained below LIC average in most countries except Kazakhstan.
- Sub-indices of FI (1993–2019):
  - Financial Institutions Depth (FID):
    - Started around 0.02 in mid-1990s; in 2019 FID ranged from 0.03 (Tajikistan) to 0.15 (Georgia and Kazakhstan).
    - In 2019 only three CCA countries had FID above LIC average; all CCA countries' FID below EM average of 0.23.
    - Constraints: high lending-deposit spreads, low domestic savings, weak trust in deposit insurance, stringent regulatory frameworks prioritizing stability.
  - Financial Institutions Access (FIA):
    - Increased from <0.1 in mid-1990s to between 0.2 and 0.7 in 2019.
    - As of 2019, FIA in all CCA countries exceeded LIC average; FIA in three CCA countries exceeded EM average.
  - Financial Institutions Efficiency (FIE):
    - No clear directional trend over 1993–2019; stayed below LIC average in most countries.
    - Some improvement in FIE in four CCA countries in the last three years of the sample.
    - Factors weighing on FIE: macroeconomic and political risks, high markups reflecting ownership structure, market concentration, competition, and legal framework on creditor rights and insolvency.
- Stylized-fact summary:
  - Financial development improved post-independence but unevenly across countries.
  - Progress mainly from FI improvements and especially access; depth and efficiency show further scope for improvement.
  - Financial markets remain underdeveloped in most CCA countries.

### III. Financial Development and Growth: Empirical Analysis
- Empirical specification:
  - Dependent variable: Δln(yit) where y is per capita GDP at chained PPPs (in mln 2017 USD).
  - Regressors: ln(yit−1), FD (or subcomponent), FD^2, controls: secondary school enrollment, FDI/GDP, government consumption/GDP, CPI inflation, trade/GDP; country and time fixed effects.
  - Estimation sample: non-overlapping five-year intervals covering 134 LIC and EM countries for 1980–2019.
  - Estimator: system dynamic GMM; quadratic specification tests bell-shaped FD–growth relationship.
  - Expected signs for bell-shaped relationship: linear term positive, quadratic term negative; ln(yit−1) expected negative (convergence).

- Estimation results (selected, exact values reported):
  - Evidence of a bell-shaped relationship between financial development and growth: linear term positive and quadratic term negative and significant for FD and FI.
  - FI and sub-indices FID and FIA show significant positive linear and significant negative quadratic coefficients; FIE quadratic term insignificant.
  - Selected coefficient estimates (exact as reported in Table 1):
    - Lagged GDP per capita: -8.225*** (col 1), -5.829*** (col 2), -7.652*** (col 3), -6.488*** (col 4), -14.349*** (col 5).
    - Education (secondary enrollment): 0.042*** (col 1), 0.049*** (col 2), 0.108*** (col 3), 0.014 (col 4), -0.006 (col 5).
    - Foreign direct investment/GDP: 0.075 (col 1), 0.081** (col 2), 0.052* (col 3), 0.084*** (col 4), 0.120** (col 5).
    - CPI inflation: 0.004*** (col 1), -0.000 (col 2), -0.001 (col 3), -0.000*** (col 4), 0.004*** (col 5).
    - Trade/GDP: 0.032*** (col 1), 0.030*** (col 2), 0.050*** (col 3), 0.025*** (col 4), -0.000 (col 5).
    - FD: 29.084*** (linear term, col 1); FD^2: -31.470** (col 1).
    - FI: 69.474*** (linear term, col 2); FI^2: -62.133*** (col 2).
    - FID: 21.778*** (linear term, col 3); FID^2: -22.695*** (col 3).
    - FIA: 19.058*** (linear term, col 4); FIA^2: -21.497*** (col 4).
    - FIE: 7.892 (linear, col 5); FIE^2: -0.600 (col 5).
  - Model statistics (exact as reported):
    - Observations: 433 (col 1), 436 (col 2), 509 (col 3), 431 (col 4), 372 (col 5).
    - Number of countries: 114 (col 1), 114 (col 2), 115 (col 3), 113 (col 4), 104 (col 5).
    - AR2 p-value: 0.719 (col 1), 0.685 (col 2), 0.0277 (col 3), 0.601 (col 4), 0.395 (col 5).
    - Sargan p-value: 0.0800 (col 1), 0.1100 (col 2), 0.0949 (col 3), 0.344 (col 4), 0.225 (col 5).

- Implications for CCA (exact reported estimates of potential growth gains from convergence to frontier CCA FD):
  - All CCA countries lie on the left side of the bell-shaped FD–growth curve, well below the turning point, indicating scope to boost growth via further financial development.
  - Estimated additional contribution to growth from convergence to frontier CCA FD (Georgia and Kazakhstan):
    - Kyrgyz Republic and Tajikistan: around 2.5 percent.
    - Azerbaijan: 1.5 percent.
    - Armenia and Uzbekistan: 0.5 percent.
  - Caveats:
    - Point estimates subject to uncertainty.
    - Private-sector financing and institutional factors (governance, supervision, collateral and insolvency frameworks, property rights) matter.
    - Fintech not captured in FD index and requires further research.

### IV. Policy Recommendations (country-specific focus)
- Overarching guidance:
  - Scope to boost growth through further financial development; require country-specific approaches targeting lagging components (depth, access, efficiency).
- Selected priorities from CCA vs EM and LIC medians, 2019:
  - Private sector credit/GDP:
    - EM CCA laggards: Azerbaijan and Kazakhstan behind EM median (possible reasons: deteriorated loan quality and bank restructuring).
    - LIC CCA: scope to improve in Tajikistan.
  - Pension fund assets/GDP:
    - Data available for three CCA countries; only Kazakhstan exceeds EM median.
    - Scope to expand private pension schemes in Armenia and Georgia.
  - Life and non-life insurance premiums/GDP:
    - CCA levels well behind EM and LIC peers; scope to expand insurance sector.
  - Efficiency of financial intermediation (net interest margins, lending-deposit spreads, non-interest income/total income, overhead costs/total assets, ROA, ROE):
    - Efficiency could be improved by fostering competition (including reducing the role of state, promoting fintech), reducing risks, and strengthening banking supervision.
- Additional policy notes:
  - Greater financial inclusion via state expansion is unlikely to yield large growth dividends; emphasis should be on private-sector financing.
  - Sustainable fintech development requires enabling environment balancing innovation with risk management.

### V. Conclusions
- Main conclusions:
  - CCA countries improved financial development since early 1990s, but unevenly across countries and indicators.
  - Progress concentrated in financial institutions—primarily access—while depth and efficiency lag; financial markets remain underdeveloped (except Kazakhstan).
  - CCA countries are located on left side of the bell-shaped FD–growth relationship; achieving frontier CCA FD levels could raise annual growth by between 0.5–2.5 percent for lower-FD countries.
  - Achieving growth dividends requires country-specific policy measures addressing depth, access, and efficiency, and attention to institutional frameworks and fintech implications.

*Source: IMF Working Paper (wpiea2022134-print-pdf).*

### References .............................................................................................................

### wpiea2022134-print-pdf - References .............................................................................................................

### I. Introduction
- Objective: provide stylized facts on financial development in the Caucasus and Central Asia (CCA) and assess how financial development can boost growth in these countries.
- Key theoretical/empirical background:
  - Financial development mobilizes savings, supports efficient allocation, raises potential output (King and Levine, 1993; Levine, 1997).
  - Sahay and others (2015) develop a multidimensional Financial Development Index (institutions and markets; depth, access, efficiency) showing a bell-shaped relationship between financial development and growth.
- Main approach:
  - Use Sahay and others (2015) Financial Development Index updated through 2019.
  - Present stylized facts, benchmark CCA against EM and LIC peers, and re-estimate standard growth regressions to quantify growth gains from financial development.

### II. Financial Development in the CCA: Stylized Facts
- Data and index construction:
  - Overall Financial Development Index (FD) = financial institutions index (FI) + financial markets index (FM); each with sub-indices depth, access, efficiency.
  - Indicators normalized between 0 and 1; data winsorized at 5th and 95th percentiles.
  - Sample: seven CCA countries—Armenia (EM), Azerbaijan (EM), Georgia (EM), Kazakhstan (EM), Kyrgyz Republic (LIC), Tajikistan (LIC), Uzbekistan (LIC). Turkmenistan excluded due to data limitations.
- Evolution 1993–2019:
  - Most CCA countries improved FD; particularly Armenia and Georgia where FD more than doubled from around 0.1 in 2000 to around 0.2-0.25 in 2019.
  - Kazakhstan: FD rose from 0.15 in 2000 to 0.4 in 2008, then declined and converged to 0.3 in 2019.
  - Cross-country dispersion: early 2000s FD range ~0.08–0.15; in 2019 FD ranged from 0.1 (Kyrgyz Republic and Tajikistan) to 0.3 (Georgia and Kazakhstan).
  - In early 2000s, FD in five CCA countries was below average LIC; by 2019, FD exceeded average LIC in five CCA countries and two converged to average EM.
- Financial institutions versus markets:
  - FI > FM across all countries (bank-dominated system); banks represent almost 90 percent of total financial system assets in the CCA.
  - Kazakhstan is an exception where FM is relatively higher (FM data for Kazakhstan should be interpreted with caution).
  - FI improved in most CCA countries and exceeded LIC average in 2019; FM stagnated and remained below LIC average in most countries except Kazakhstan.
- Sub-indices of FI (1993–2019):
  - Financial Institutions Depth (FID):
    - Most started around 0.02 in mid-1990s; in 2019 FID ranged from 0.03 (Tajikistan) to 0.15 (Georgia and Kazakhstan).
    - In 2019 only three CCA countries had FID above LIC average; all CCA countries' FID below EM average of 0.23.
    - Constraints: high lending-deposit spreads, low domestic savings, weak trust in deposit insurance, stringent regulatory frameworks prioritizing stability.
  - Financial Institutions Access (FIA):
    - Increased from <0.1 in mid-1990s to between 0.2 and 0.7 in 2019.
    - As of 2019, FIA in all CCA countries exceeded LIC average; FIA in three CCA countries exceeded EM average.
  - Financial Institutions Efficiency (FIE):
    - No clear directional trend over 1993–2019; stayed below LIC average in most countries.
    - Some improvement in FIE in four CCA countries in the last three years of the sample.
    - Factors weighing on FIE: macroeconomic and political risks, high markups reflecting ownership structure, market concentration, competition, and legal framework on creditor rights and insolvency.
- Stylized-fact summary:
  - Financial development improved post-independence but unevenly across countries.
  - Progress mainly from FI improvements and especially access; depth and efficiency show further scope for improvement.
  - Financial markets remain underdeveloped in most CCA countries.

### III. Financial Development and Growth: Empirical Analysis
#### A. Empirical specification
- Growth regression:
  - Dependent variable: Δln(yit) where y is per capita GDP at chained PPPs (in mln 2017 USD).
  - Regressors include ln(yit−1), FD (or subcomponent), FD^2, controls: secondary school enrollment, FDI/GDP, government consumption/GDP, CPI inflation, trade/GDP; country and time fixed effects.
  - Estimation sample: non-overlapping five-year intervals covering 134 LIC and EM countries for 1980–2019.
  - Estimator: system dynamic GMM (to address endogeneity); quadratic specification tests bell-shaped FD–growth relationship.
- Expected signs:
  - For bell-shaped relationship: β2 > 0 and β3 < 0; β1 (lagged GDP per capita) expected negative (convergence).

#### B. Estimation results (Table 1 highlights)
- Main findings:
  - Evidence of a bell-shaped relationship between financial development and growth: linear term positive and quadratic term negative and significant for FD and FI.
  - FI and sub-indices FID and FIA show significant positive linear and significant negative quadratic coefficients, implying contribution to growth up to a turning point.
  - Coefficients on the quadratic term of FIE are insignificant.
- Selected coefficient values (exact as reported in Table 1):
  - Lagged GDP per capita: -8.225*** (col 1), -5.829*** (col 2), -7.652*** (col 3), -6.488*** (col 4), -14.349*** (col 5).
  - Education (secondary enrollment): 0.042*** (col 1), 0.049*** (col 2), 0.108*** (col 3), 0.014 (col 4), -0.006 (col 5).
  - Foreign direct investment/GDP: 0.075 (col 1), 0.081** (col 2), 0.052* (col 3), 0.084*** (col 4), 0.120** (col 5).
  - CPI inflation: 0.004*** (col 1), -0.000 (col 2), -0.001 (col 3), -0.000*** (col 4), 0.004*** (col 5).
  - Trade/GDP: 0.032*** (col 1), 0.030*** (col 2), 0.050*** (col 3), 0.025*** (col 4), -0.000 (col 5).
  - FD: 29.084*** (linear term, col 1); FD^2: -31.470** (col 1).
  - FI: 69.474*** (linear term, col 2); FI^2: -62.133*** (col 2).
  - FID: 21.778*** (linear term, col 3); FID^2: -22.695*** (col 3).
  - FIA: 19.058*** (linear term, col 4); FIA^2: -21.497*** (col 4).
  - FIE: 7.892 (linear, col 5); FIE^2: -0.600 (col 5).
- Model statistics (exact as reported):
  - Observations: 433 (col 1), 436 (col 2), 509 (col 3), 431 (col 4), 372 (col 5).
  - Number of countries: 114 (col 1), 114 (col 2), 115 (col 3), 113 (col 4), 104 (col 5).
  - AR2 p-value: 0.719 (col 1), 0.685 (col 2), 0.0277 (col 3), 0.601 (col 4), 0.395 (col 5).
  - Sargan p-value: 0.0800 (col 1), 0.1100 (col 2), 0.0949 (col 3), 0.344 (col 4), 0.225 (col 5).
- Implications for CCA:
  - All CCA countries lie on the left side of the bell-shaped FD–growth curve, well below the turning point, indicating scope to boost growth via further financial development.
  - Estimated additional contribution to growth from convergence to frontier CCA FD (Georgia and Kazakhstan):
    - Kyrgyz Republic and Tajikistan: around 2.5 percent.
    - Azerbaijan: 1.5 percent.
    - Armenia and Uzbekistan: 0.5 percent.
  - Caveats: point estimates subject to uncertainty; private-sector financing and institutional factors (governance, supervision, collateral and insolvency frameworks, property rights) matter; fintech not captured in FD index and requires further research.

#### C. Policy recommendations (country-specific focus)
- Overall: scope to boost growth through further financial development; require country-specific approaches targeting lagging components (depth, access, efficiency).
- Selected areas identified from Figure 6 comparisons (CCA vs EM and LIC medians, 2019):
  - Private sector credit/GDP:
    - EM CCA laggards: Azerbaijan and Kazakhstan behind EM median (possible reasons: deteriorated loan quality and bank restructuring).
    - LIC CCA: scope to improve in Tajikistan.
  - Pension fund assets/GDP:
    - Data available for three CCA countries; only Kazakhstan exceeds EM median.
    - Scope to expand private pension schemes in Armenia and Georgia.
  - Life and non-life insurance premiums/GDP:
    - Available data show CCA levels well behind EM and LIC peers; scope to expand insurance sector.
  - Efficiency of financial intermediation (net interest margins, lending-deposit spreads, non-interest income/total income, overhead costs/total assets, ROA, ROE):
    - Efficiency could be improved by fostering competition (including reducing the role of state, promoting fintech), reducing risks, and strengthening banking supervision.
- Additional policy notes:
  - Greater financial inclusion via state expansion is unlikely to yield large growth dividends; emphasis should be on private-sector financing.
  - Sustainable fintech development requires enabling environment balancing innovation with risk management.

### IV. Conclusions
- Main conclusions:
  - CCA countries improved financial development since early 1990s, but unevenly across countries and indicators.
  - Progress concentrated in financial institutions—primarily access—while depth and efficiency lag; financial markets remain underdeveloped (except Kazakhstan).
  - CCA countries are located on left side of the bell-shaped FD–growth relationship; achieving frontier CCA FD levels could raise annual growth by between 0.5–2.5 percent for lower-FD countries.
  - Achieving growth dividends requires country-specific policy measures addressing depth, access, and efficiency, and attention to institutional frameworks and fintech implications.

### Key figures and table inventory (as presented)
- Figures:
  - Figure 1. Financial Development Index
  - Figure 2. Financial Development Index in the CCA Countries
  - Figure 3. Financial Institutions and Financial Markets Indices in the CCA Countries
  - Figure 4. Sub-Indices of Financial Institutions Index in the CCA Countries
  - Figure 5. Bell-Shaped Relationship between Financial Development and Growth
  - Figure 6. Selected Financial Development Indicators: CCA versus EM and LIC peers, 2019
- Table:
  - Table 1. Estimation Results (system dynamic panel GMM; dependent variable: 5-year average real GDP per capita growth; FD indicators abbreviated: FD, FI, FID, FIA, FIE; significance: *** p <0.01, ** p <0.05, * p <0.1)

*Source: IMF Working Paper (content as provided: wpiea2022134-print-pdf - References .............................................................................................................)*

### References

### wpiea2022134-print-pdf - References

### Financial development, growth, and theory
- King, R., and R. Levine. 1993. “Finance and Growth: Schumpeter Might Be Right,” The Quarterly Journal of Economics, 108 (3): pp. 717–37
- Levine, R. 1997. “Financial Development and Economic Growth: Views and Agenda,” Journal of Economic Literature, 35(2): pp. 688-726.
- Philippon, T., and A. Reshef. 2012. “Wages and Human Capital in the U.S. Finance Industry: 1909–2006,” Quarterly Journal of Economics, 127 (4): pp. 1551–69
- Philippon, T., and A. Reshef. 2013. “An International Look at the Growth of Modern Finance,” Journal of Economic Perspectives, 27 (2): pp. 73-96
- Arcand, J.-L., E. Berkes, and U. Panizza. 2012. “Too Much Finance?” IMF Working Paper WP/12/161. International Monetary Fund, Washington, DC.

### Financial inclusion, fintech, and COVID-19 era implications
- Blancher, N., Appendino, M., Bibolov, A., Fouejieu, A., Li, J., Ndoye, A., Panagiotakopoulou, A., Shi, W., and T. Sydorenko. 2019. “Financial Inclusion of Small and Medium-Sized Enterprises in the Middle East and Central Asia,” IMF Departmental Paper 19/02. International Monetary Fund, Washington, DC.
- Barajas, A., T. Beck, M. Belhaj, and S. Ben Naceur. 2020. “Financial Inclusion: What Have We Learned So Far? What Do We Have to Learn?” IMF Working Paper WP/20/157. International Monetary Fund, Washington, DC.
- Lukonga, I. 2018. “Fintech, Inclusive Growth and Cyber Risks: A Focus on the MENAP and CCA Region,” IMF Working Paper WP/18/201. International Monetary Fund, Washington, DC.
- Sahay, R., U. von Allmen, A. Lahreche, P. Khera, S. Ogawa, M. Bazarbash, and K. Beaton. 2020. “The Promise of Fintech: Financial Inclusion in the Post COVID-19 Era,” IMF Departmental Paper No. 20/09. International Monetary Fund, Washington, DC.
- Sahay, R., M. Čihak, P. N’Diaye, A. Barajas, R. Bi, D. Ayala, Y. Gao, A. Kyobe, L. Nguyen, C. Saborowski, K. Svirydzenka, and S. R. Yousefi. 2015. “Rethinking Financial Deepening: Stability and Growth in Emerging Markets,” IMF Staff Discussion Note SDN/15/08. International Monetary Fund, Washington, DC.

### Regional focus: Caucasus and Central Asia; MENAP and CCA
- Gigineishvili, N., Teodoru, I., Karapetyan, N., and Y. Ustyugova. 2022. “Paving the Way to More Resilient, Inclusive and Greener Economies in Caucasus and Central Asia,” IMF Departmental Paper (forthcoming). International Monetary Fund, Washington, DC.
- Khandelwal, P., Cabezon, E., Mirzayev, S., and R. Al-Farah. 2022. “Macroprudential Policies to Enhance Financial Stability in the Caucasus and Central Asia,” IMF Departmental Paper 2022/006. International Monetary Fund, Washington, DC.
- Teodoru, I., and K. Akepanidtaworn. 2022. “Managing Financial Sector Risks from the COVID-19 Crisis in the Caucasus and Central Asia,” IMF Departmental Paper 2022/005. International Monetary Fund, Washington, DC.
- Vera Martin, M., Jardak, T., Tchaidze, R., Trevino, J. and H. W. Wagner. 2018. “Building Resilient Banking Sectors in the Caucasus and Central Asia,” IMF Departmental Paper 18/08. International Monetary Fund, Washington, DC.

### Contractual savings, pensions, insurance, and capital markets
- Catalán, M., Impavido, G., and A. Musalem. 2000. “Contractual Savings or Stock Market Development Which Leads?” Available at SSRN: https://ssrn.com/abstract=632492
- Impavido, G., Musalem, A., and T. Tressel. 2001. “Contractual Savings, Capital Markets, and Firms' Financing Choices,” Available at SSRN: https://ssrn.com/abstract=632681
- Impavido, G., Tressel, T., and A. Musalem. 2002. “Contractual Savings Institutions and Banks' Stability and Efficiency,” Available at SSRN: https://ssrn.com/abstract=634464
- Impavido, G. and I. Tower, I. 2009. “How the Financial Crisis Affects Pensions and Insurance and Why the Impacts Matter,” IMF Working Paper WP/09/151. International Monetary Fund, Washington, DC.

### Measurement, indices, and methodology
- Svirydzenka, K. 2016. “Introducing a New Broad-based Index of Financial Development,” IMF Working Paper WP/16/5. International Monetary Fund, Washington, DC.

### Country reports and sectoral contributions
- Belhocine, N. 2015. “Fostering Financial Sector Contribution to Growth,” IMF Country Report No. 15/212. International Monetary Fund, Washington, DC.

*Financial Development and Growth in the Caucasus and Central Asia — Working Paper No. WP/22/134*

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_Source: https://www.imf.org/-/media/files/publications/wp/2022/english/wpiea2022134-print-pdf.pdf_