## 1. Loan Interest Rates in the Baltics and the Euro-Area, 2015–22 ## Source details **Canonical URL:** [1. Loan Interest Rates in the Baltics and the Euro-Area, 2015–22](https://www.imf.org/-/media/files/publications/cr/2022/english/1lvaea2022002.pdf) ## Other formats - [Markdown version](/-/media/files/publications/cr/2022/english/1lvaea2022002.pdf.md) - [Structured JSON version](/-/media/files/publications/cr/2022/english/1lvaea2022002.pdf.json) --- ### Executive summary and main findings - Loan interest rates in the Baltic countries, and especially Latvia, have been relatively high and (recently) rising despite euro-area membership. - Key empirical findings documented in the chapter: - There is segmentation in bank lending interest rates between the Baltic states and the euro-area during 2015–22. - Interest rates in Latvia are higher than in its Baltic peers, with the gaps being yet wider at longer maturities and, within those, for smaller-sized loans. - There is some relationship between Latvia’s weak corporate credit and high interest rates. - Policy implication stated: The findings call for broad-based actions to alleviate both supply and demand-side factors that affect Latvia’s interest rates and bottlenecks to its credit provision. ### Context and motivation - Problem framed: - High lending rates in the Baltics persist despite euro-area membership and raise concerns about monetary transmission and access to finance. - Latvia experienced a protracted credit-less recovery: while Lithuania and Estonia started credit recoveries by 2013–14, Latvia’s credit continued to contract for the entire decade following the global financial crisis (GFC) of 2008–09. - Latvia’s household credit turned positive in 2021, but corporate lending growth remained in negative territory. - Comparative focus: the three Baltic countries versus the euro-area average, with emphasis on the period 2015–22 (12-month averages used to smooth monthly volatility in some segments). ### Stylized facts on interest rates (data source: ECB Statistical Data Warehouse and IMF staff estimates) - Aggregate dynamics: - Weighted average interest rates in all Baltic countries slightly increased over the past six years, with Latvia remaining the highest. - Euro-area average weighted interest rates fell perceptibly during the same period. - Unweighted average interest rates show a decline in Latvia almost by the same margin as that of the euro-area, albeit from much higher levels—implying pronounced differences concentrated in segments with relatively small volumes. - By borrower type: - Broad alignment of interest rates within the Baltics and de-coupling of the Baltics from the euro-area average (weighted averages). - Latvia’s rates remain the highest within the Baltics and changed relatively little over the past six years despite easing of euro-area monetary policy. - By maturity: - Short-term borrowing costs: within-Baltics alignment and de-coupling from the euro-area. - Long-term borrowing costs (over one year): Latvia’s long-term borrowing costs have increased perceptibly from already high levels and have diverged from both the euro-area and the Baltics. - By loan purpose and segment: - Consumption loans: convergence of the Baltics toward the euro-area, but very high disparity in levels; rates are in double digits for Latvia across all maturities. - Mortgage loans: Latvia’s interest rates declined broadly by the same margin as the euro-area at the short end, but stayed constant at high levels on the long end, diverging from the euro-area. - Small corporate loans: Latvia’s interest rates declined by a smaller margin than the euro-area on the short end while increasing (and diverging) sharply on the long end. - Note: two bottom figures use 24-month averages instead of 12-month averages due to data availability issues. - By loan size (corporates): - Smaller corporate loans (below EUR 1 million) tend to have an interest rate premium over large loans; in Latvia this premium has been the largest. - For short-maturity small loans the premium declined perceptibly over the past six years; for longer-maturity small loans the premium has appreciably increased in Latvia (and to a smaller extent in Estonia). - The size of loans acted as an “amplifier” of dynamics when interacting with maturity. ### Quantified differentials and patterns - Pairwise and aggregate differentials (2021–22 comparisons and change 2015–16 to 2021–22): - Latvia’s loan interest rate “premium” over Estonia: about 2 percentage points as an unweighted average. - Latvia’s premium rises to 4–6½ percent for household house purchase loans with maturity of above one year. - Baltics interest rate premium over euro-area: around 4 percentage points as an unweighted average and up to 9 percentage points for some types of loans to households. - Differential tends to be higher for household loans and higher maturities; relationship may be non-linear for some segments (e.g., housing loans where long-term contracts can be more standardized and carry lower rates than shorter maturities). - Convergence/divergence patterns: - Scatter plots of changes in interest rate differentials versus initial (2015–16) levels show both convergence and divergence. - Divergence is more frequent in comparisons of Latvia/Baltics and the euro-area; within the Baltics, convergence is more frequent. - Convergence instances concentrate where initial differentials were high; where differentials were narrower, divergence tends to dominate. - Overall, there is a clear lack of convergence in most segments. ### Cost of deposits and funding - Overall cost of deposits is low for all types of deposits. - Unweighted average: Estonia’s deposit cost is perceptibly higher than other Baltics, largely explained by the high cost of Estonia’s NFC deposits of over two years whose volume is relatively low. - Weighted average: cost of deposits is uniformly negligible at below 0.1 percent for all Baltic countries; Estonia’s deposits remain relatively more costly but only marginally so. - Euro-area banks’ two small advantages versus Baltics: - Greater reliance on longer-term deposits (long-term deposits carry a higher cost relative to short-term funding but mitigate maturity-mismatch risk). Euro-area banks attract long-term deposits in a higher proportion and at a smaller cost than the Baltic countries. - Lower cost of enterprise deposits: euro-area banks carried enterprise deposits at negative nominal rates (unlike Baltic countries, which have those at positive nominal rates). Difference is relatively small at 0.1–0.3 percentage point relative to the Baltic countries. - Deposit-rate differentials explain only a small share of lending-rate differentials: between 1 percent (for Lithuania) and 5 percent (for Latvia) of the loan rate differential. - Central bank financing (including TLTRO) can smooth differences in funding costs across euro-area banks. ### Risks of non-bank borrowers and term premia - Latvia’s total bank lending term premium is 4 percentage points, the highest among the Baltic countries and well above the euro-area average; it has increased substantially relative to peers in recent years. - Term-premium increases are also observed in subsectors: small loans to NFCs and loans for house purchase. - Some segments (large corporate loans, consumption, “other” household loans) have volatile and scant data; in some of these Latvia’s term premia are lower than Estonia’s. - Caution: aggregate term premia as proxies for borrower risks may be affected by shifts in bank/borrower composition, few transactions, and non-standardized transaction terms. ### Non-performing loans (NPLs), collateral, equity gap, and firm-size effects - NPLs and sectoral vulnerabilities: - Latvia’s NPL ratio has been higher and more volatile than other Baltic countries, reflecting large effects from the GFC and other factors. - NPL ratio experienced a temporary uptick in 2016–17 but has shown a sustained reduction overall, particularly since 2018. - NPL reduction continued during the COVID-19 shock except in pandemic-hit services such as food and accommodation. - Remaining sectoral vulnerabilities: NPL ratios have remained relatively high in some sectors, suggesting vulnerabilities among some corporate borrowers. - Note: NPLs are backward-looking indicators and imperfect proxies for current borrower risk. - Collateral and firm-size effects: - The collateral “discount” (difference between interest rates on collateralized and total corporate loans) has been relatively small and declining over time. - OLS regression results indicate the level of the discount over the past decade is negatively associated with the time trend term in small, medium, and large NFC loan segments. - Interpretation caveats: aggregated data, absence of granular controls, possible compositional shifts (credit toward larger borrowers who typically require less collateral). - Latvia’s corporate equity gap (Ebeke et al. (2021)): - Estimated at some 5 percent of GDP based on pre-COVID-19 firm-level data. - Projected at 9 percent of GDP post-pandemic. - These levels were the highest among the 15 euro-area countries in that study’s sample. - Firm-size and financing constraints: - Latvia’s share of SMEs relative to large enterprises: 99.9 percent (sample statistic reported). - Proportion of insolvent firms in the sample: around 50 percent. - EIB (2021) comparison: overall finance-constrained firms — Estonia 7 percent, Latvia 8 percent; for small and micro firms — Estonia 12 percent, Latvia 22 percent. - Implication: small firms face greater financing constraints and barriers to investing and productivity growth; an analysis of quantity and composition of bank credit by firm size is needed. ### Role of banks and bank-related factors - Bank-related supply-side factors that can elevate interest rates: low competition, conservative lending policies, lower risk appetite, higher bank costs. - Empirical studies (Benkovskis et al. (2021); Bank of Latvia (2021)) using bank-level data argue bank-related supply-side factors, including conservative lending policies, are likely major contributors to high interest rates in Latvia. - However, these studies left substantial unexplained residuals and required judgmental elements for policy conclusions. - Data on extent of bank competition in Latvia are not extensive or granular enough for full modeling. - Baltic banks’ profitability: - Bank profitability in the Baltic countries is among the highest in the euro area, suggesting higher interest rates translate into higher profits. - Latvian banks’ capitalization and profitability are among the highest in the euro-area, which should incentivize risk-taking and market-share expansion; yet Latvia’s corporate credit remains weak, indicating additional factors at play. - Need to assess determinants of credit growth to distinguish demand-side from supply-side and macro-financial influences on banks and borrowers. ### Analysis of corporate credit growth and regression findings - Latvia’s credit growth weaker than peers for both corporates and households: - Latvia’s credit to households: broadly flat over the past six years. - Latvia’s corporate credit: contracted by 20 percent in nominal terms, in contrast to significantly positive growth in peers. - The contraction is more pronounced relative to GDP. - Time-series analysis (following Cihak and Tamirisa (2006)): - Aggregate bank credit growth regressed on proxies for loan demand (industrial production growth, wage growth, and unemployment), loan supply (bank soundness measured as NPLs/total loans), and real policy interest rates. - Model estimated on monthly and quarterly data for 2013–21 (monthly regressions for Latvia cover 2015–21 due to data availability). - Parsimonious specifications obtained via general-to-specific modeling with lag selection (12 lags for monthly, four lags for quarterly), and robustness diagnostics applied. - Regression findings: - Commonality: negative association between corporate credit growth and lagged industrial production in both Latvia and Estonia (interpreted as strong retained earnings enabling internal financing). - Asset quality (NPLs), policy rate, and change in unemployment generally came out statistically insignificant in these regressions. - Key difference: wage growth term sign differs — in Estonia higher wage growth positively associated with corporate loan growth; in Latvia higher wage growth negatively associated with corporate loan growth. - Interpretation: Estonia’s positive wage-growth association may reflect resilient credit demand driven by strong productivity performance; Latvia’s negative sign aligns with expectations where higher wages can dampen corporate credit growth. - Identification caveats: - Demand-side factors are more easily identified; supply-side channels are harder to pin down given limited data (NPLs are backward-looking and not available monthly for Latvia except via interpolation). - Availability of forward-looking measures (e.g., probabilities of default) would aid identification. ### Residuals from credit growth regressions and lending interest rates - Residuals from the credit growth regressions for both Latvia and Estonia are negatively correlated with their respective lending interest rates, suggesting a relationship between unexplained credit growth variation and lending rates. - The text notes that credit growth is likely endogenous with lending interest rates, and therefore (non-policy) interest rates should not be included in OLS regressions of credit growth because of reverse causality concerns. - Examination of residuals is used to provide insights on potentially missing correlates given endogeneity concerns and limited instruments. - Further investigation over the sample period is impeded by: - the relative shortness of the time sample; and - a limited menu of variables that could be candidates for instrumenting for reverse causality. ### Policy recommendations — supply- and demand-side measures - Broad diagnostic: Recent research suggests both supply- and demand-side explanations for weak credit and high interest rates; three broad dimensions shape interest rates and credit: (i) macroeconomic relationships; (ii) bank-level factors; and (iii) borrower-related conditions. - Structural reforms to support firms’ productivity and resilience: - Enhance productivity and competitiveness to support demand for credit. - Address barriers faced by small and micro enterprises, including balance sheet weaknesses, constrained access to finance, problematic business environment, and limited access to productivity-enhancing services such as digital and transport infrastructure. - EIB (2021) evidence: "some 57 percent of small and micro firms in Latvia report digital infrastructure as a barrier to long-term investment versus 29 percent in Estonia." - Latvia’s share of the shadow economy: "26 percent in 2021," the highest among the Baltics; reducing the shadow economy would catalyze productivity and demand for credit. - Address the corporate equity gap and solvency support: - Latvia’s corporate equity gap appears comparatively high; further work is needed to assess its current (post-COVID-19) level, composition, and economic effects. - IMF (2021) and IMF (2022) provide guidance on recapitalization and solvency support options. - Latvia has used the EU state-aid framework for larger enterprises; scope exists to assess support for SMEs and micro firms. - Norway’s grant-based support scheme is noted as a key option for micro enterprises, subject to fiscal space and tailored cost-benefit analysis. - Improve enforcement and insolvency procedures: - Upgrading quality of enforcement procedures can improve insolvency recovery rates and productivity (Wu (2019)). - Substantial reforms have improved the framework, but legislative implementation and translation to transactions “on the ground” need further work. - Faster implementation of the EU restructuring directive will simplify debt restructuring through out-of-court and hybrid procedures. - Restructure banks formerly servicing foreign clients (BSFCs): - Well-tailored restructuring can expand credit provision by helping BSFCs find viable domestic niches and increase competition in lending. - Stepped-up supervision is critical as BSFCs become more exposed to domestic competitive pressures and funding-market shocks and regulatory changes. - Monitor banking competitiveness and non-bank credit provision: - Regular reviews of competitiveness (e.g., Herfindahl-Hirschman index across loan segments) could identify bottlenecks and policy opportunities. - Assess trends in credit provision by non-banks to understand banks’ comparative advantages. - Analyze Latvia-specific access to finance by enterprise type, using comparative surveys such as the ECB’s SAFE and the EIB investment survey. - Advance AML/CFT agenda: - AML/CFT shocks and costs have likely limited credit provision and increased bank costs and interest rates, affecting (i) all banks via higher costs and reduced risk appetite; (ii) BSFCs via client-relationship impacts; and (iii) many non-bank clients subject to enhanced due diligence. - With a risk-based AML/CFT approach and modernization of oversight, opportunities exist to reduce risks and costs; after fixed pre-qualification compliance costs are incurred, ongoing compliance costs should be lower. - Improve statistics and public analytical reporting: - Further data improvements are recommended, including availability of monthly data on non-performing loans and high-frequency lending interest rate data broken down by economic sector. - Such data are publicly available in Estonia and would aid comparison and understanding of Latvia’s corporate sector risks. - Periodic comprehensive reports (similar to Bank of Estonia’s “Financing the Economy”) could assess cost and availability of financing across sectors, promote analytical debate, and mobilize public and private action. ### Conclusions - Key diagnostic conclusions: - Latvia’s relatively high interest rates and still-weak credit are interrelated problems. - Stylized facts point to segmentation in lending interest rates between the Baltics and the euro-area, and to a lesser extent within the Baltics. - This segmentation is unlikely to derive from the cost of bank deposits (which does not experience significant segmentation) or the health of the banking system (which is well-capitalized and profitable in Latvia and the other Baltics). - The segmentation appears rooted in the nexus between borrower-side risks and related banks’ policies. - Empirical analysis: - Links between interest rates and loan growth are assessed and bottlenecks to credit provision are identified, but pervasive endogeneity in risk perceptions and data gaps limit clear-cut results. - Estonia as a policy comparator: - Estonia’s advances in productivity and credit provision while supporting a dynamic SME sector can inform Latvia’s reform agenda. - Consolidated reform priorities (verbatim list of key areas): - (i) implementing steps to enhance productivity and non-price competitiveness and further reduce the shadow economy - (ii) assessing and tackling Latvia’s corporate equity gap with a particular focus on SMEs and micro-enterprises - (iii) improving the implementation of the insolvency procedures on the ground - (iv) completing the overhaul and re-orientation of BSFCs - (v) further proactively addressing AML/CFT challenges - (vi) assessing and fostering a competitive landscape of the banking system - (vii) improving the granularity of statistics and publicly available analysis and reporting on bank interest rates and credit growth *Source: IMF staff estimates; content as provided in the supplied chapter.* ### 1. Loan Interest Rates in the Baltics and the Euro-Area, 2015–22 __________________________ 5 ### 1. Loan Interest Rates in the Baltics and the Euro-Area, 2015–22 ### Executive summary and main findings - Loan interest rates in the Baltic countries, and especially Latvia, have been relatively high and (recently) rising despite euro-area membership. - Key empirical findings documented in the chapter: - There is segmentation in bank lending interest rates between the Baltic states and the euro-area during 2015–22. - Interest rates in Latvia are higher than in its Baltic peers, with the gaps being yet wider at longer maturities and, within those, for smaller-sized loans. - There is some relationship between Latvia’s weak corporate credit and high interest rates. - Policy implication stated: The findings call for broad-based actions to alleviate both supply and demand-side factors that affect Latvia’s interest rates and bottlenecks to its credit provision. ### Context and motivation - Problem framed: - High lending rates in the Baltics persist despite euro-area membership and raise concerns about monetary transmission and access to finance. - Latvia experienced a protracted credit-less recovery: while Lithuania and Estonia started credit recoveries by 2013–14, Latvia’s credit continued to contract for the entire decade following the global financial crisis (GFC) of 2008–09. - Latvia’s household credit turned positive in 2021, but corporate lending growth remained in negative territory. - Comparative focus: the three Baltic countries versus the euro-area average, with emphasis on the period 2015–22 (12-month averages used to smooth monthly volatility in some segments). ### Stylized facts on interest rates (data source: ECB Statistical Data Warehouse and IMF staff estimates) - Aggregate dynamics: - Weighted average interest rates in all Baltic countries slightly increased over the past six years, with Latvia remaining the highest. - Euro-area average weighted interest rates fell perceptibly during the same period. - Unweighted average interest rates show a decline in Latvia almost by the same margin as that of the euro-area, albeit from much higher levels—implying pronounced differences concentrated in segments with relatively small volumes. - By borrower type: - Broad alignment of interest rates within the Baltics and de-coupling of the Baltics from the euro-area average (weighted averages). - Latvia’s rates remain the highest within the Baltics and changed relatively little over the past six years despite easing of euro-area monetary policy. - By maturity: - Short-term borrowing costs: within-Baltics alignment and de-coupling from the euro-area. - Long-term borrowing costs (over one year): Latvia’s long-term borrowing costs have increased perceptibly from already high levels and have diverged from both the euro-area and the Baltics. - By loan purpose and segment: - Consumption loans: convergence of the Baltics toward the euro-area, but very high disparity in levels; rates are in double digits for Latvia across all maturities. - Mortgage loans: Latvia’s interest rates declined broadly by the same margin as the euro-area at the short end, but stayed constant at high levels on the long end, diverging from the euro-area. - Small corporate loans: Latvia’s interest rates declined by a smaller margin than the euro-area on the short end while increasing (and diverging) sharply on the long end. - Note: two bottom figures use 24-month averages instead of 12-month averages due to data availability issues. - By loan size (corporates): - Smaller corporate loans (below EUR 1 million) tend to have an interest rate premium over large loans; in Latvia this premium has been the largest. - For short-maturity small loans the premium declined perceptibly over the past six years; for longer-maturity small loans the premium has appreciably increased in Latvia (and to a smaller extent in Estonia). - The size of loans acted as an “amplifier” of dynamics when interacting with maturity. ### Quantified differentials and patterns - Pairwise and aggregate differentials (2021–22 comparisons and change 2015–16 to 2021–22): - Latvia’s loan interest rate “premium” over Estonia: about 2 percentage points as an unweighted average. - Latvia’s premium rises to 4–6½ percent for household house purchase loans with maturity of above one year. - Baltics interest rate premium over euro-area: around 4 percentage points as an unweighted average and up to 9 percentage points for some types of loans to households. - Differential tends to be higher for household loans and higher maturities; relationship may be non-linear for some segments (e.g., housing loans where long-term contracts can be more standardized and carry lower rates than shorter maturities). - Convergence/divergence patterns: - Scatter plots of changes in interest rate differentials versus initial (2015–16) levels show both convergence and divergence. - Divergence is more frequent in comparisons of Latvia/Baltics and the euro-area; within the Baltics, convergence is more frequent. - Convergence instances concentrate where initial differentials were high; where differentials were narrower, divergence tends to dominate. - Overall, there is a clear lack of convergence in most segments. ### Hypotheses explored for drivers of differentials - Candidate explanations outlined for high and diverging lending rate differentials: - Differences in banks’ cost of funding, notably the cost of attracting bank deposits. - Differences in risks associated with non-bank borrowers. - Different characteristics of banks, including health, extent of bank competition, and differences in lending policies. - Further investigation of these hypotheses proceeds via cross-country and country-specific stylized facts (deposit rates and other sections follow in the chapter). ### Empirical and policy implications (as framed in the chapter) - Empirical linkage: the chapter’s analysis links Latvia’s weak corporate credit to high lending rates through stylized facts and regression analysis (detailed empirical tables and regressions are presented later in the chapter). - Policy recommendation (stated): Calls for broad-based actions to alleviate both supply and demand-side factors that affect Latvia’s interest rates and bottlenecks to its credit provision. *Source: 1lvaea2022002 - 1. Loan Interest Rates in the Baltics and the Euro-Area, 2015–22 (ECB Statistical Data Warehouse and IMF staff estimates).* ### 12. The ECB database contains information that permits to gauge cross-country ### 12. The ECB database contains information that permits to gauge cross-country differences in the cost of deposits. ### Cost of deposits - Overall cost of deposits is low for all types of deposits. - Unweighted average: Estonia’s deposit cost is perceptibly higher than other Baltics, largely explained by the high cost of Estonia’s NFC deposits of over two years whose volume is relatively low. - Weighted average: cost of deposits is uniformly negligible at below 0.1 percent for all Baltic countries; Estonia’s deposits remain relatively more costly but only marginally so. - Euro-area banks’ two small advantages versus Baltics: - Greater reliance on longer-term deposits (long-term deposits carry a higher cost relative to short-term funding but mitigate maturity-mismatch risk). Euro-area banks attract long-term deposits in a higher proportion and at a smaller cost than the Baltic countries. - Lower cost of enterprise deposits: euro-area banks carried enterprise deposits at negative nominal rates (unlike Baltic countries, which have those at positive nominal rates). Difference is relatively small at 0.1–0.3 percentage point relative to the Baltic countries. - Deposit-rate differentials explain only a small share of lending-rate differentials: between 1 percent (for Lithuania) and 5 percent (for Latvia) of the loan rate differential. - Central bank financing (including TLTRO) can smooth differences in funding costs across euro-area banks. ### Risks of non-bank borrowers and term premia - Latvia’s total bank lending term premium is 4 percentage points, the highest among the Baltic countries and well above the euro-area average; it has increased substantially relative to peers in recent years. - Term-premium increases are also observed in subsectors: small loans to NFCs and loans for house purchase. - Some segments (large corporate loans, consumption, “other” household loans) have volatile and scant data; in some of these Latvia’s term premia are lower than Estonia’s. - Caution: aggregate term premia as proxies for borrower risks may be affected by shifts in bank/borrower composition, few transactions, and non-standardized transaction terms. ### Non-performing loans (NPLs) and sectoral vulnerabilities - Latvia’s NPL ratio has been higher and more volatile than other Baltic countries, reflecting large effects from the GFC and other factors. - NPL ratio experienced a temporary uptick in 2016–17 but has shown a sustained reduction overall, particularly since 2018. - NPL reduction continued during the COVID-19 shock except in pandemic-hit services such as food and accommodation. - Remaining sectoral vulnerabilities: NPL ratios have remained relatively high in some sectors, suggesting vulnerabilities among some corporate borrowers. - Note: NPLs are backward-looking indicators and imperfect proxies for current borrower risk. ### Collateral, corporate equity gap, and firm-size effects - Analysis of interest rates for NFCs: the collateral “discount” (difference between interest rates on collateralized and total corporate loans) has been relatively small and declining over time. - OLS regression results (Table 1) indicate the level of the discount over the past decade is negatively associated with the time trend term in small, medium, and large NFC loan segments. - Interpretation caveats: aggregated data, absence of granular controls, possible compositional shifts (credit toward larger borrowers who typically require less collateral). - Latvia’s corporate equity gap (Ebeke et al. (2021)): - Estimated at some 5 percent of GDP based on pre-COVID-19 firm-level data. - Projected at 9 percent of GDP post-pandemic. - These levels were the highest among the 15 euro-area countries in that study’s sample. - Firm-size and financing constraints: - Latvia’s share of SMEs relative to large enterprises: 99.9 percent (sample statistic reported). - Proportion of insolvent firms in the sample: around 50 percent. - EIB (2021) comparison: overall finance-constrained firms — Estonia 7 percent, Latvia 8 percent; for small and micro firms — Estonia 12 percent, Latvia 22 percent. - Implication: small firms face greater financing constraints and barriers to investing and productivity growth; an analysis of quantity and composition of bank credit by firm size is needed. ### Role of banks and bank-related factors - Bank-related supply-side factors that can elevate interest rates: low competition, conservative lending policies, lower risk appetite, higher bank costs. - Empirical studies (Benkovskis et al. (2021); Bank of Latvia (2021)) using bank-level data argue bank-related supply-side factors, including conservative lending policies, are likely major contributors to high interest rates in Latvia. - However, these studies left substantial unexplained residuals and required judgmental elements for policy conclusions. - Data on extent of bank competition in Latvia are not extensive or granular enough for full modeling. - Baltic banks’ profitability: - Bank profitability in the Baltic countries is among the highest in the euro area, suggesting higher interest rates translate into higher profits. - Latvian banks’ capitalization and profitability are among the highest in the euro-area, which should incentivize risk-taking and market-share expansion; yet Latvia’s corporate credit remains weak, indicating additional factors at play. - Need to assess determinants of credit growth to distinguish demand-side from supply-side and macro-financial influences on banks and borrowers. ### Analysis of corporate credit growth - Latvia’s credit growth weaker than peers for both corporates and households (Figure 17): - Latvia’s credit to households: broadly flat over the past six years. - Latvia’s corporate credit: contracted by 20 percent in nominal terms, in contrast to significantly positive growth in peers. - The contraction is more pronounced relative to GDP. - Time-series analysis (following Cihak and Tamirisa (2006)): - Aggregate bank credit growth regressed on proxies for loan demand (industrial production growth, wage growth, and unemployment), loan supply (bank soundness measured as NPLs/total loans), and real policy interest rates. - Model estimated on monthly and quarterly data for 2013–21 (monthly regressions for Latvia cover 2015–21 due to data availability). - Parsimonious specifications obtained via general-to-specific modeling with lag selection (12 lags for monthly, four lags for quarterly), and robustness diagnostics applied. - Regression findings (Tables 2,3): - Commonality: negative association between corporate credit growth and lagged industrial production in both Latvia and Estonia (interpreted in literature as strong retained earnings enabling internal financing). - Asset quality (NPLs), policy rate, and change in unemployment generally came out statistically insignificant in these regressions. - Key difference: wage growth term sign differs — in Estonia higher wage growth positively associated with corporate loan growth; in Latvia higher wage growth negatively associated with corporate loan growth. - Interpretation: Estonia’s positive wage-growth association may reflect resilient credit demand driven by strong productivity performance; Latvia’s negative sign aligns with expectations where higher wages can dampen corporate credit growth. - Identification caveats: - Demand-side factors are more easily identified; supply-side channels are harder to pin down given limited data (NPLs are backward-looking and not available monthly for Latvia except via interpolation). - Availability of forward-looking measures (e.g., probabilities of default) would aid identification. _italic Source: IMF staff estimates and ECB Statistical Data Warehouse as presented in the provided content._ ### 25. The residuals from the credit growth regression are negatively correlated with lending ### 25. The residuals from the credit growth regression are negatively correlated with lending ### Residuals and lending interest rates — empirical finding - Residuals from the credit growth regressions for both Latvia and Estonia are negatively correlated with their respective lending interest rates, suggesting a relationship between unexplained credit growth variation and lending rates (Figure 18). - The text notes that credit growth is likely endogenous with lending interest rates, and therefore (non-policy) interest rates should not be included in OLS regressions of credit growth because of reverse causality concerns. - Examination of residuals is used to provide insights on potentially missing correlates given endogeneity concerns and limited instruments. - Further investigation over the sample period is impeded by: - the relative shortness of the time sample; and - a limited menu of variables that could be candidates for instrumenting for reverse causality. ### Policy recommendations — supply- and demand-side measures (E.) - Broad diagnostic: Recent research suggests both supply- and demand-side explanations for weak credit and high interest rates; three broad dimensions shape interest rates and credit: (i) macroeconomic relationships; (ii) bank-level factors; and (iii) borrower-related conditions. - Structural reforms to support firms’ productivity and resilience: - Enhance productivity and competitiveness to support demand for credit. - Address barriers faced by small and micro enterprises, including balance sheet weaknesses, constrained access to finance, problematic business environment, and limited access to productivity-enhancing services such as digital and transport infrastructure. - EIB (2021) evidence: "some 57 percent of small and micro firms in Latvia report digital infrastructure as a barrier to long-term investment versus 29 percent in Estonia." - Latvia’s share of the shadow economy: "26 percent in 2021," the highest among the Baltics; reducing the shadow economy would catalyze productivity and demand for credit. - Address the corporate equity gap and solvency support: - Latvia’s corporate equity gap appears comparatively high; further work is needed to assess its current (post-COVID-19) level, composition, and economic effects. - IMF (2021) and IMF (2022) provide guidance on recapitalization and solvency support options. - Latvia has used the EU state-aid framework for larger enterprises; scope exists to assess support for SMEs and micro firms. - Norway’s grant-based support scheme is noted as a key option for micro enterprises, subject to fiscal space and tailored cost-benefit analysis. - Improve enforcement and insolvency procedures: - Upgrading quality of enforcement procedures can improve insolvency recovery rates and productivity (Wu (2019)). - Substantial reforms have improved the framework, but legislative implementation and translation to transactions “on the ground” need further work. - Faster implementation of the EU restructuring directive will simplify debt restructuring through out-of-court and hybrid procedures. - Restructure banks formerly servicing foreign clients (BSFCs): - Well-tailored restructuring can expand credit provision by helping BSFCs find viable domestic niches and increase competition in lending. - Stepped-up supervision is critical as BSFCs become more exposed to domestic competitive pressures and funding-market shocks and regulatory changes. - Monitor banking competitiveness and non-bank credit provision: - Regular reviews of competitiveness (e.g., Herfindahl-Hirschman index across loan segments) could identify bottlenecks and policy opportunities. - Assess trends in credit provision by non-banks to understand banks’ comparative advantages. - Analyze Latvia-specific access to finance by enterprise type, using comparative surveys such as the ECB’s SAFE and the EIB investment survey. - Advance AML/CFT agenda: - AML/CFT shocks and costs have likely limited credit provision and increased bank costs and interest rates, affecting (i) all banks via higher costs and reduced risk appetite; (ii) BSFCs via client-relationship impacts; and (iii) many non-bank clients subject to enhanced due diligence. - With a risk-based AML/CFT approach and modernization of oversight, opportunities exist to reduce risks and costs; after fixed pre-qualification compliance costs are incurred, ongoing compliance costs should be lower. - Improve statistics and public analytical reporting: - Further data improvements are recommended, including availability of monthly data on non-performing loans and high-frequency lending interest rate data broken down by economic sector. - Such data are publicly available in Estonia and would aid comparison and understanding of Latvia’s corporate sector risks. - Periodic comprehensive reports (similar to Bank of Estonia’s “Financing the Economy”) could assess cost and availability of financing across sectors, promote analytical debate, and mobilize public and private action. ### Conclusions (F.) - Key diagnostic conclusions: - Latvia’s relatively high interest rates and still-weak credit are interrelated problems. - Stylized facts point to segmentation in lending interest rates between the Baltics and the euro-area, and to a lesser extent within the Baltics. - This segmentation is unlikely to derive from the cost of bank deposits (which does not experience significant segmentation) or the health of the banking system (which is well-capitalized and profitable in Latvia and the other Baltics). - The segmentation appears rooted in the nexus between borrower-side risks and related banks’ policies. - Empirical analysis: - Links between interest rates and loan growth are assessed and bottlenecks to credit provision are identified, but pervasive endogeneity in risk perceptions and data gaps limit clear-cut results. - Estonia as a policy comparator: - Estonia’s advances in productivity and credit provision while supporting a dynamic SME sector can inform Latvia’s reform agenda. - Consolidated reform priorities (verbatim list of key areas): - (i) implementing steps to enhance productivity and non-price competitiveness and further reduce the shadow economy - (ii) assessing and tackling Latvia’s corporate equity gap with a particular focus on SMEs and micro-enterprises - (iii) improving the implementation of the insolvency procedures on the ground - (iv) completing the overhaul and re-orientation of BSFCs - (v) further proactively addressing AML/CFT challenges - (vi) assessing and fostering a competitive landscape of the banking system - (vii) improving the granularity of statistics and publicly available analysis and reporting on bank interest rates and credit growth *Source: IMF staff estimates; content as provided in the supplied chapter.* --- _Source: https://www.imf.org/-/media/files/publications/cr/2022/english/1lvaea2022002.pdf_