VoxEU Column Financial Markets

Home bias and the credit crunch: Evidence from Italy

Understanding credit crunches is a major concern for policymakers. This column suggests that the severity of a credit crunch in a specific area depends on the hierarchical structure of the banks operating in that credit market. It explores the Italian case and shows that, in the months following the collapse of Lehman Brothers, banks retracted disproportionally from markets that are more distant from their headquarters.

The management of the Eurozone sovereign debt crisis will have significant effects on the stability of national banking systems, as argued in some recent Vox columns (Acharya et al 2011, Wyplosz 2011). The interaction between the debt crisis and banking risk will likely affect bank capital positions and might also affect bank liquidity and the fragility of the interbank markets. This raises the prospect of another intense credit crunch similar to the one that followed Lehman’s bankruptcy in September 2008 (Doménech 2011).

The credit crunch in Europe

This crisis, like most before it, has been associated with both credit-supply and credit-demand effects. Disentangling these two effects (ie disentangling the contraction of credit supply from the parallel reduction of credit demand) makes the identification of a credit crunch during a global crisis a major concern for policymakers. It is also one of the biggest challenges facing empirical work in this area. Similarly difficult is the assessment of the factors that may drive differences in the severity of the crunch across firms and markets.

A number of studies of the effect of the global financial crisis on European small and medium enterprises confirm the presence of a credit crunch in Europe after Lehman’s collapse (Albertazzi and Marchetti 2010, Iyer et al 2010, Jimenez et al forthcoming, Puri et al 2011). The evidence also suggests that younger firms, smaller firms, and more opaque firms may have been more severely affected (Artola and Genre 2011, Popov and Udell forthcoming).

The severity of the credit crunch in a specific area could also depend on the hierarchical structure of the banks operating in that credit market. As pointed out by de Haas and van Horen (2011a) in a recent Vox column, “banks with head offices farther away from their customers are less reliable funding sources during a crisis”. Distant banks are less able to provide relationship lending to small and medium enterprises because of difficulties associated with producing and transmitting soft information. This implies that as the ‘functional distance’ between loan officers and the headquarters where final lending decisions are made increases, banks are less able to make relationship-based loans and access to credit to local firms becomes tighter (Alessandrini et al 2009).

This column presents the results of a recent paper (Presbitero et al 2012) in which we explore the Italian case during the crisis. Italy, like many European countries, is characterised by a large number of small firms that are highly dependent on bank credit, and by a banking system in which small local banks compete in local markets with a few large multi-market banks, whose branches are widely spread out at a great distance, on average, from their respective bank’s headquarters. Thus, Italy offers a representative case study on the relevance of ‘home bias’ in shaping credit supply during this current credit crunch.

Distance and the credit crunch

The availability of detailed survey data on loan applications and their outcomes by a large sample of manufacturing firms allows us to separate demand and supply effects. Matching firm-level data on access to bank credit with a measure of the functional distance of the banking system at the provincial level, we show that, in the months following the collapse of Lehman Brothers, banks retracted disproportionally from markets which are more distant from their headquarters. In addition, our evidence on the credit crunch does not support the hypothesis that the credit retrenchment has been significantly more severe for small and medium enterprises than larger firms.

Figure 1 clarifies the role of functional distance on the intensity of the credit crunch. Two main patterns emerge from the diagrams. The first concerns timing and shows that while the demand for credit remained quite stable before and after Lehman's collapse, the restraining response of the banking system to the reduction in global liquidity was evident and immediately transmitted to the real sector.1

Figure 1. Demand and supply of bank credit in Italy

Notes: Elaborations based on the sample of 3,631 firms (24,651 observations). Source: ISAE/ISTAT Survey on Manufacturing Firms. The shares of firms which applied for bank credit (panel a), and which have been credit-rationed (panel b) have been calculated separately for firms located in provinces where the banking system is functionally close (the indicator of functional distance is below the 75° percentile of its distribution) and functionally distant (the indicator is above the 75° percentile of its distribution). Functional distance is measured at the province level as the ratio of the number of branches in the province weighted by the logarithm of 1 plus the kilometric distance between the province of the branch and the province where the parent bank is headquartered, over total branches in the province.

The second – and the more interesting – pattern is related to the geographical differences in the access to bank credit. On average, over the sample period, firms located in provinces densely populated by functionally distant banks are less likely to seek credit. The opposite trend is observable with the share of rationed firms. Just before the onset of the crisis, the share of credit-rationed firms was 11.6%, irrespective of the functional distance of local banking systems. In the first quarter after the Lehman collapse, the tightening of credit conditions is common everywhere, but the increase in credit rationing is statistically higher in provinces dominated by distantly managed banks.2

Home bias or flight to quality?

Recent studies have considered the existence of a home bias in banks' lending reactions to adverse shocks to their financial condition during this global crisis by looking at the behaviour of international banks in the syndicated loan market (de Haas and van Horen 2011b, Giannetti and Laeven forthcoming) and by looking a cross-border small and medium enterprises lending (Popov and Udell forthcoming). We also investigate whether the withdrawal of distant banks from local markets has been the result of a flight to quality or whether it signals the presence of a home bias by multi-market banks.

To establish which of the two effects prevails, we test whether smaller and riskier enterprises in more functionally distant banking systems are more (flight to quality) or less (home bias) likely to suffer from a contraction of credit after Lehman's collapse. Our results show that the credit tightening in functionally distant credit markets has not been focused on riskier, less productive, and more opaque firms. Functionally distant banks shy away from lending in provinces which are at a distance from their headquarters irrespective of borrowers’ characteristics. As result, distantly managed banks hurt all of their borrowers, including safe and transparent firms, who comprise the bulk of their customer base.

This evidence is inconsistent with the common idea that the credit crunch has partially been the result of a flight to quality by nationwide, distantly managed banks, while supporting the hypothesis of a home bias effect by multi-market banks.


Acharya, V, D Schoenmaker, and S Steffen (2011), “How much capital do European banks need? Some estimates”, VoxEU.org, 22 November.

Albertazzi, U and DJ Marchetti (2010), “Credit supply, flight to quality and evergreening: an analysis of bank-firm relationships after Lehman”, Working Paper n° 756, Bank of Italy.

Alessandrini P, AF Presbitero and A Zazzaro (2009), “Banks, distances and firms' financing constraints”, Review of Finance 13(2): 261–307.

Artola, C and V Genre (2011), “Eurozone SMEs Under Financial Constraints: Belief or Reality?”, Working Paper Series 3650, CESifo.

de Haas, R and N van Horen (2011a), “Running for the exit: International banks and crisis transmission”, VoxEU.org, 13 February.

de Haas, R and N van Horen (2011b), “Running for the exit: International banks and crisis transmission”, DNB Working Papers 279, Netherlands Central Bank.

Domenéch, R (2011) “The Eurozone debt crisis: Slipping into a double-dip recession?”, VoxEU.org, 1 December.

Giannetti, M and L Laeven (forthcoming), “The flight home effect: Evidence from syndicated loan market during financial crises”, Journal of Financial Economics.

Iyer, R, S Lopes, J Peydro, and A Schoar (2010), “Interbank liquidity crunch and the firm credit crunch: Evidence from the 2007–2009 crisis” Working Paper, MIT.

Jimenez, G, S Ongena, J Peydro, and J Saurina (forthcoming), “Credit supply and monetary policy: identifying the bank-balance sheet channel with loan applications”, American Economic Review.

Popov, A and GF Udell (forthcoming), “Cross-border banking, credit access, and the financial crisis”, Journal of International Economics.

Presbitero, AF, GF Udell, and A Zazzaro (2012), “The home bias and the credit crunch: A regional perspective”, paper presented at the MoFiR workshop on banking

Puri, M, J Rocholl, and S Steffen (2011), “Global retail lending in the aftermath of the US financial crisis: Distinguishing between supply and demand effects”, Journal of Financial Economics 100(3): 556-578.

Wyplosz, C (2011) “Do Eurozone leaders finally ‘get it’? Not quite yet”, VoxEU.org, 5 December.


1 The share of rationed firms increased from 11.6% in the third quarter of 2008 to 21.6% in the last quarter of the year and further to 25.5% and 27.5% respectively in the first and third quarters of 2009.

2 The share of rationed firms is 26.4% (20.9%) in provinces where functional distance is above (below) the 75° percentile of its provincial distribution, and this difference is statistically significant.


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