Abstract
This paper examines the role of credit and the macroeconomy in small and medium enterprise (SME) distress during a prolonged economic downturn. Specifically, we estimate the determinants of SME distress in Ireland during the severe financial and economic crisis which began in 2007/2008. We use a measure of distress, insolvencies, which captures both bank and non-bank forms of credit. We conduct a survival analysis of insolvent liquidations and find that, controlling for firm location and economic activity, both variables capturing a build-up of stress in the macroeconomy and those capturing bank credit standards and availability throughout the cycle are determinants of firm survival.
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Notes
The vast majority of Irish companies are SMEs; the Central Statistics Office of Ireland’s Business in Ireland Survey 2009 reports that 99.8 % of enterprises were SMEs.
It is possible that the registered address is that of the firms solicitor rather than the company itself. Where this is obviously the case, the company is removed from the sample.
The eight sectors used are agriculture (including forestry, fishing and mining), retail and wholesale, manufacturing, transport and communications, construction and real estate, financials, hotels and restaurants and other business activities which incorporates utilities.
The NUTS 3 regions for Ireland are Dublin, Southeast, Southwest, West, Mideast, Border, Midlands and Midwest. In the NUTS 3 division, Tipperary is split between the Midwest and Southeast. In our analysis, we include Tipperary in the Southeast.
Unemployment rates are available from the Central Statistics Office (www.cso.ie) at the NUTS 3 regional classification.
This is a modified correlation measure using a Bayesian approach allowing for the relaxation of the bivariate normality assumption of the Pearson measure and the use of priors to inform the means standard deviation and heaviness of the tails. Barnard et al. (2000) outline in detail, but the net effect is correlation estimates robust to outliers.
The darker and lighter blue areas show the 50 and 95 % density regions, respectively. Half of all new data points are predicted to fall within the darker blue area.
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The views expressed in this paper are solely our own. We are grateful to Patrick Honohan, Gerard O’Reilly and Stefan Gerlach for comments.
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Kelly, R., Brien, E.O. & Stuart, R. A long-run survival analysis of corporate liquidations in Ireland. Small Bus Econ 44, 671–683 (2015). https://doi.org/10.1007/s11187-014-9605-1
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DOI: https://doi.org/10.1007/s11187-014-9605-1