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Analyzing Credit Supply and Firm Lending During the Crisis: Croatian Micro-level Insights

This research examines credit supply to Croatian enterprises during the crisis, detecting possible credit misallocation and exploring lending patterns. It discusses the impact of bank capitalization and loan restructuring on the economy.

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Analyzing Credit Supply and Firm Lending During the Crisis: Croatian Micro-level Insights

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  1. Lending activity and credit supply to firms during the crisisEvidence from the Croatian micro level data * Tomislav Ridzak, Financial Stability Department Croatian National Bank *The views expressed in this article are those of theauthor and do not necessarily represent the views of, andshould not be attributed to the CNB

  2. Motivation • Crisis brought the need to rebalance the Croatian economy • Cutting the losses and transferring resources to more productive uses (depends on capitalization, legal framework, own interest of bank management). • Anecdotal evidence point to a lot of inertia in loan dynamics: • Loan prolongation / restructuring instead of cutting the losses.

  3. Introduction • This research aims to analyse the credit supply to individual enterprises in Croatia during the crisis and to detect possible credit misallocation • Steps: • get an overview on dynamics of the credit activity in Croatia using credit creation and destruction; • explore differences in lending patterns before and during the crisis and find possible evidence of loan misplacement (evergreening, zombie lending) using firm level data.

  4. International evidence on loan reallocation • 1st approach: reducing exposures to enterprises in distress and turning to new and promising projects: • US in each recession from 1979 to 2008 (Contessi and Francis, 2009). • 2nd approach: extending time limits for loan repayments (evergreening, zombie lending): • Mostly associated with the case of Japan - Peek and Rosengreen (2003) find that the banks increased loans to severely impaired firms in Japan because of corporate affiliations and government pressure. • Recent financial crisis exposed all the vulnerabilities of the banking systems in the US and Europe - Albetrazzi and Marchetti (2010) find evidence of evergreening in Italy.

  5. Credit creation and destruction

  6. Credit creation and destruction • The creation was calculated as the sum of all increases in total loan amounts to individual clients (relative to the balance at the end of the previous period) • The destruction was calculated as the sum of all decreases in total loan amounts to individual clients (relative to the balance at the end of the previous period) • The excess credit growth which measures the reallocation in excess of net credit change is defined as follows

  7. Credit creation and destruction (median of all banks)

  8. Credit reallocation: Excess credit growth

  9. Summary: crisis and pre-crisis

  10. Lending patterns

  11. Data • Bank × company panel dataset in two periods: • CRISIS: begins 30.9.2008, ends 31.12.2009 • PRE-CRISIS: begins 30.6.2007, ends 30.9.2008 • Dependent variable, corporate lending from bank b to company i, is introduced in a regression as the change in the loans deflated by firm’s average assets • Explanatory variables are: • banks’ performance and financial strength • firms’ financial indicators and other characteristics • interaction terms

  12. Explanatory variables • Bank variables: • Liquidity, profitability, capitalization and share of bad loans to firms in total loans • Bank size dummy • Biggest creditor dummy • Firm variables: • Z-Score dummy for companies riskier than median • Dummy for low productive companies (TFP below the median for the sector) • Small firm dummy • Interactions between bank and firm variables

  13. Estimation strategy, Lending patterns and evergreening • I use multiple lending and fixed effects to single out the effect of bank variables, i.e. credit supply on change in loans • Fixed effects will pick-up the unobservable part of the error term (ui) that does not vary among banks • As a result the obtained coefficients on the bank specific variables can be interpreted as drivers of supply

  14. Estimation results: credit supply • Two bank specific variables are significant determinant of credit supply to firms in the crisis period: • Capitalization • Non-performing loan ratio • Can this be interpreted as evidence of capitalization related credit crunch? • Yes, as only about 8 per cent of the decrease in loans from low capitalized banks is substituted by loans from high capitalized banks (5 per cent in the pre-crisis period) • Results are robust across specifications

  15. Estimation results: evergreening

  16. Conclusion • Bank capitalization was significant factor of loan supply in the crisis period • Less capitalized banks extended the loans to problematic enterprises (evergreening) • Small and medium sized banks are forced to deal with the clients that are financially less stable, because of the competition from the big banks • Bank-firm relationship in Croatia seems to be strong

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