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SWITCHING COSTS IN LOCAL CREDIT MARKETS

SWITCHING COSTS IN LOCAL CREDIT MARKETS. Guglielmo Barone (with Roberto Felici and Marcello Pagnini) Bank of Italy, Economic Research Unit, Bologna Branch. Ancona, 23/09/2006. Switching costs (SC) defined.

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SWITCHING COSTS IN LOCAL CREDIT MARKETS

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  1. SWITCHING COSTS IN LOCAL CREDIT MARKETS Guglielmo Barone (with Roberto Felici and Marcello Pagnini) Bank of Italy, Economic Research Unit, Bologna Branch Ancona, 23/09/2006

  2. Switching costs (SC) defined • Any cost incurred by a customer when she breaks current relationship with a supplier and initiates a new relationship with a different seller • They arise when a sunk investment specific to the current seller must be duplicated for a new seller

  3. Motivations • Relevance within credit markets • High transaction costs • Complexity of contractual rules • Search and evaluation • Asymmetries of information • Relational investment • Implication of switching costs in general • market power over existing clientele • barriers to entry • …

  4. Our contribution • Assessing existence and magnitude of SC within loan markets • detecting pricing strategies consistent with the presence of SC • testing SC existence through state dependence in firm-bank relationships controlling for matching • comparing SC for different borrower categories

  5. Related literature • Theory • IO: pricing with SC and customer recognition (Chen, JEMS 1997) and Taylor, RJE 2003) • Banking: Adverse selection and informational asymmetries (Sharpe, JoF 1990 and von Thadden, FRL 2004) • Gering and Stenbacka (2005) and Vesala (2005) try to unify these literatures • Empirics • Deposit markets (Sharpe, RIO 1997 and Shy, IJIO 2002) • Credit card markets (Ausbel, AER 1991, Calem and Mester, AER 1995, Stango, JIE 2002) • Kim et al (JoFI, 2003) specifically targeted at measuring SC in business loan markets

  6. Hypotheses to be tested • Pricing: poaching strategies (H1) banks offer teasing prices to new borrowers (or they pay customers to switch) • State dependence (H2) From the demand side, the borrower’s choice of her bank depends on her previous choices

  7. Data • Sources: mainly Survey on lending rates and Bank of Italy supervisory reports • Data refer to single firm-bank (i, j) pair: • a flag if i borrows from j • matched, revocable and term loans and interest rate • firm characteristics (legal form, size, sector of economic activity, share of matched and term loans) • bank characteristics (size, location, …) • Distance between lender and borrower • Two periods: march 2004 (t – 1) and march 2005 (t) • The province is the geographic relevant market (4 provinces: Turin, Bologna, Rome, Naples) • Main 15 banks per province are considered • About 50,000 firms and 79,000 bank-firm relationships

  8. (P1) Pricing: interest rate equation • Pooled data • INTRATEijt: interest rate charged by bank j to firm i in march 2005 • DNEWijt: 1 if j was not i’s main lender in t - 1; 0 otherwise • bp < 0 => banks poach rivals’ customers (and => that poaching incentives are greater than those induced by adverse selection)

  9. (P1) Pricing: econometric evidence Interest rate regression (standard errors in brackets) • Banks do offer teasing prices • Robust to different definition of DNEW • Robust to selectivity: Heckman correction with physical distance as matching factor

  10. (P2) State dependence: choosing main bank • By provinces • Pijt: net indirect benefit firm i obtains from choosing bank j in t as its mail bank • Wijt: 0 if i chose bank j in the previous period; -1 otherwise • ln (d)  N (dmean; dstd. dev.) • If d > 0 => switching main banks generates disutility • Parameters are estimated in a mixed logit framework (Train, 2003) matching factors

  11. (P2) State dependence: econometric evidence Mixed logit model – ML estimates (standard errors in brackets) • INTRATE and DIST reduce indirect benefit • SC mean > 0 controlling for unobserved heterogeneity

  12. Other findings • If d is normally distributed then only a small fraction of firm population has a negative value for d • SC are greater of single-bank firms, controlling for size • Among firms resorting to multiple lending, changing the main bank partner generates SC even when moving to an already known bank => the main bank has a special role

  13. Summing up • Bank will offer a discount to the new customers, consistently with the tenets of SC models with customer recognition • In Italian local credit markets relationship influence firms iterate the choice of their bank partner through time and this reflects a genuine causal link between past and current choices • Exclusive bank relationships are an obstacle to firm mobility across banks • Multiple lenders will pay SC even when switching to an already known bank

  14. Thank you for your attention

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