We incorporate our very own the brand new method to 21 countries with differing account off economic and you may monetary creativity. Which not only increases the external validity regarding earlier performance and allows us to exploit between-country (also inside-country) version both in brand new incidence off dating lending in addition to power of 2008–2009 recession. Additionally, that with business-height questionnaire analysis, we can identify anywhere between economically unconstrained businesses, firms that were both refused or disappointed from obtaining a good feabie loan, and you may firms without borrowing demand. Degree playing with borrowing from the bank registry study face the possibility limitation one non-applicant providers maybe do not need borrowing from the bank, otherwise needed borrowing from the bank but are frustrated out-of implementing. In the end, by the taking a look at the part off dating credit on the top and trough of the borrowing from the bank course, we could demonstrate that, as the predicted from the principle, dating financing is more very important while in the a good downturn. In spite of which very different empirical method, our very own efficiency line-up well, hence harden, before findings towards character of relationship credit while in the downturns.
Around three methodological points have earned comment. But not, by using analysis both for credit and you may low-borrowing organizations we could gauge the local general equilibrium effect of banks’ financing processes, and this we possibly may miss if the focusing only towards the borrowing providers. Second, we trust questionnaire studies for both enterprises and banking companies. If you’re enterprise-height survey research was popular on recent literature (age.g., Campello et al., 2010, Popov and you can Udell, 2012, Ongena et al., 2013), inquiries could occur regarding dimension error into the firms’ solutions to help you issues regarding as to why they do not apply for a loan, otherwise that getting rejected could merely mirror the deficiency of resource ventures which have positive websites expose worthy of. To help you decrease this type of concerns, you can expect several robustness evaluation with different meanings out-of firms’ borrowing restrictions, and tips predicated on equilibrium sheet research.
Third, our very own empirical method hinges on the location from finance companies and you will businesses being separate of each and every other. Following Berger, Miller, Petersen, Ra), we believe that the new financial surroundings near providers imposes an enthusiastic exogenous geographic maximum with the financial institutions one businesses get access to. We offer substantial evidence that’s in line with it assumption. I together with attempt to own heterogeneous negative effects of your neighborhood presence out-of finance companies you to take a look at by themselves while the relationship lenders around the different varieties of firms. It next contact the fresh new you’ll be able to endogenous complimentary of agencies and you may financial institutions.
The brand new papers proceeds as follows. Section 2 identifies the knowledge present we merge, and you will Point step 3 gift suggestions all of our empirical method. I talk about the standard show and you can robustness evaluating in the Sections cuatro and 5, respectively. Area 6 after that considers genuine outcomes, and you can Point seven finishes.
Area snippets
Our very own empirical data sleeps towards the joining three very important bits of suggestions: data into the firms’ credit constraints from the different occuring times, the newest geo-coordinates of the lender twigs related these businesses, and you may study on the credit process of those banks. I talk about the analysis on the firms’ genuine abilities for the Point six.
Methodology
To estimate the link between the share of relationship banks near a firm and the probability that the firm is credit-constrained, we use the following model for both the 2005 and 2008–2009 cross section. We hypothesize that relationship banks were particularly helpful once the cycle had turned in 2008. Consider the model Y i j k l = ? 1 X i j k l + ? 2 L j k + ? 3 S h a r e r e l a t i o n s h i p b a n k s j k + ? 4 C k + ? 5 I l + ? i j k l , where Yijkl is a dummy variable equal to one if firm i in locality j of country k in industry l is