Job Losses from the Credit Crunch During the Great Recession

By Samuel Bentolila, Marcel Jansen Feb 4, 2014, 8:21 AM 

The evidence about the effect of declined lending during the Great Recession on the employment is quite limited. This column presents new research on the problem focusing on the case of Spain. A large part of credit to non-financial firms before the crisis came from weak banks, which solvency was strongly eroded during the crisis. As a result, firms that relied heavily on loans from such weak banks displayed significantly higher employment reduction in comparison to similar, less exposed firms. The bulk of employment destruction was driven by firm closures, which carries higher economic costs than downsizing, and could potentially make the recession more protracted.

Policymakers in both Europe and the US are concerned about the economic implications of the current shortage of credit. As the International Monetary Fund put it recently, “policymakers want to support markets because the decline in lending is seen to be a primary factor in the slow recovery” (IMF 2013).

Access to credit is currently especially difficult for small and medium-sized enterprises. For example, a survey undertaken by the European Central Bank (2013), referred to April-September 2013, shows that “access to finance” is the second-most frequent concern of the Eurozone’s small and medium-size enterprises (16%), after “finding customers” (24%).

Lending and employment during the recession: The case of Spain

The available evidence regarding the effect of the decline in lending during the Great Recession on employment is, however, still quite limited. For some of the most affected countries, including the US, there is a lack of comprehensive high-quality data on bank credit to firms and this poses a problem for identification.

  • The main challenge is to disentangle the shocks to credit supply from the endogenous fall in the credit demand of firms during recessions. In a recent study (Bentolila, Jansen, Jiménez, and Ruano 2013) we offer new data for Spain, another one of the crisis-ridden countries, which is ideally suited for this task.

Using data from the official credit register of the Bank of Spain, we are able to reconstruct the complete banking relationships of a sample of over 217,000 non-financial firms. This loan level data is linked to the balance sheets of all the banks and the balance sheets and income statements of the firms in our sample. Furthermore, we also have information on firms’ loan applications at non-current banks and we observe whether these applications are granted or not. Together these data sources constitute, to the best of our knowledge, the largest matched firm-loan-bank dataset ever assembled to study the real effects of credit supply shocks.

The extraordinary quality of the data is, however, not the only reason why it is interesting to study the Spanish experience during the Great Recession.

  • In comparison with other countries, Spanish firms – which are overwhelmingly small and medium-sized – rely heavily on bank credit and their high leverage ratios at the onset of the crisis made them vulnerable to the substantial contraction in bank lending that took place during the crisis.
  • Between 2007 and 2010, the flow of new credit to non-financial firms by deposit institutions, corrected for inflation, was falling at a stunning annual rate of 38%, after reaching record levels in the pre-crisis period. This fall in credit supply was briefly interrupted in 2011, but since that time it accelerated again, placing many firms in acute financial distress due to a lack of alternative funding sources.
  • Last but not least, since the credit supply shock originated in a boom-bust cycle in domestic housing prices, there are interesting parallels with countries like Ireland or the US, which also suffered a collapse of their housing markets followed by a strong and persistent rise in unemployment.

The role of weak banks

Following recent work by Chodorow-Reich (2014) and Greenstone and Mas (2013), our identification strategy exploits the marked differences in lender health at the onset of the crisis.

The debacle of the Spanish banking system was concentrated in a set of financial institutions that consisted almost exclusively of savings banks. In 2006, these weak banks, accounted for approximately one-third of total credit to non-financial firms, but almost two-thirds of their loans went to firms in the real estate industry (i.e. construction companies and real estate developers), compared with ‘only’ one-third at healthier banks. As the crisis unfolded, the solvency of these weak banks was strongly eroded and, eventually, they were either bought out by other banks, or bailed out by the State and nationalised.

Not surprisingly, the fall in credit supply during the crisis was particularly strong at these weak banks. To identify the real effects of this credit supply shock, we compute the difference in the change in employment during the crisis, from 2006 to 2010, between companies that relied heavily on credit from weak banks before the crisis (the treatment group) and firms that did not (the control group), and then attribute this difference to credit constraints.

The validity of our estimation strategy relies on the assumption that private firms could not predict the solvency problems of the banks when they established their banking relationships. Similarly, the firms that suffered unexpected reductions in credit from their current banks must not have been able to readily obtain credit at other banks. We provide evidence to corroborate both claims. Nevertheless, inspection of the data reveals significant differences between the two sets of firms at the onset of the crisis, with the firms in the treatment group featuring both lower average profitability and worse financial health than the firms in the control group. All our empirical specifications, therefore, include an exhaustive set of firm variables to ensure that we are really comparing similar companies. Furthermore, to rule out problems of reverse causality, we exclude all firms associated with real estate activities from our sample, and we experiment with a large number of different specifications to guarantee the robustness of our results.

  • In the baseline we estimate a standard difference-in-difference specification that compares the change in employment levels at the two sets of firms, but we also use matching techniques and we experiment with different definitions of our treatment variable. For example, in one of the experiments we use banks’ pre-crisis exposure to the real estate sector to identify the most vulnerable banks.
  • Alternatively, to prove that the differential access to credit is driving the results, we estimate instrumental variable specifications in which weak bank exposure is used as an instrument for changes in firms’ total credit during the crisis.
  • Finally, in our most ambitious exercise, we exploit a legal change in 1988 that liberalised the location decisions of savings banks to obtain exogenous variation in the degree of weak bank exposure at the municipal level in 2006.

Large job losses from the credit drought

Regardless of the specific estimation method, we obtain the same clear-cut result – firms that were heavily reliant on weak-bank credit suffer significantly higher employment reductions than similar, less exposed firms. The effect ranges from 3 to 13.5 percentage points, i.e. 8% to 36% of aggregate job losses in our sample of firms between 2006 and 2010. We also find significant heterogeneity according to the ex-ante financial vulnerability of firms. For example, the impact for firms that defaulted on a loan in the period between 2002 and 2006 is almost five times larger.

There is only one exception. For firms that rely on a single bank we do not find any significant differences. These firms are better treated by their banks than firms with several banking relations, and if anything, this effect is stronger for the firms that rely on a weak bank.

Lastly, we find that the bulk of the differences in employment destruction are driven by firm closures. This finding has potentially important welfare implications, since job losses via firm destruction carry a larger economic cost than downsizing by surviving firms, and they probably make the recession more protracted.

Concluding remarks

Admittedly, our estimation procedure does not yield estimates for the size of the aggregate employment loss. Nonetheless, assuming that our approach is valid, the assignment of firms to weak banks is as good as random. In other words, these firms could have been granted as much credit by healthy, as by weak banks. In this sense, while the total job losses suffered by firms attached to weak banks may or may not have been efficient, the estimated employment effects of the credit constraints we identify, once selection has been taken into account, reflect inefficient job losses.


•Bentolila, S, M Jansen, G Jiménez, and S Ruano (2013), “When Credit Dries Up: Job Losses in the Great Recession“, CEPR Discussion Paper 9776.
•Chodorow-Reich, G (2014), “The Employment Effects of Credit Market Disruptions: Firm-level Evidence from the 2008-09 Financial Crisis”, Quarterly Journal of Economics 129 (forthcoming).
•European Central Bank (2013), Monthly Bulletin, Frankfurt, November, Box 4.
•Greenstone, M and A Mas (2012), “Do Credit Market Shocks Affect the Real Economy? Quasi-Experimental Evidence from the Great Recession and ‘Normal’ Economic Times”, MIT Department of Economics Working Paper no. 12-27.
•International Monetary Fund (2013), Global Financial Stability Report: Transition Challenges to Stability, Washington, DC, October, chapter 2.

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