Failure prediction of government funded start-up firms
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DOIhttp://dx.doi.org/10.21511/imfi.14(2-2).2017.01
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Article InfoVolume 14 2017, Issue #2 (cont. 2), pp. 296-306
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This study aims to create a prediction model that would forecast the bankruptcy of government funded start-up firms (GFSUs). Also, the financial development patterns of GFSUs are outlined. The dataset consists of 417 Estonian GFSUs, of which 75 have bankrupted before becoming five years old and 312 have survived for five years. Six financial ratios have been calculated for one (t+1) and two (t+2) years after firms have become active. Weighted logistic regression analysis is applied to create the bankruptcy prediction models and consecutive factor and cluster analyses are applied to outline the financial patterns. Bankruptcy prediction models obtain average classification accuracies, namely 63.8% for t+1 and 67.8% for t+2. The bankrupt firms are distinguished with a higher accuracy than the survived firms, with liquidity and equity ratios being the useful predictors of bankruptcy. Five financial patterns are detected for GFSUs, but bankrupt GFSUs do not follow any distinct patterns that would be characteristic only to them.
- Keywords
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JEL Classification (Paper profile tab)G33, H81, M13, M21
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References47
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Tables8
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Figures0
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- Table 1. Formulae of financial ratios applied in the analysis
- Table 2. Descriptive statistics of financial ratios for the whole sample and two types of firms, %
- Table 3. Results of weighted logistic regression (LR) analysis for periods t+1 and t+2
- Table 4. Classification accuracies of logistic regression models for periods t+1 and t+2
- Table 5. Median values of financial ratios through five detected patterns, %
- Table 6. Contingency between detected patterns and firm statuses
- Table 7. Results of hypotheses testing
- Table 8. Rotated factor matrix
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- Aldrich, H. E., & Auster, E. R. (1986). Even dwarfs started small: Liabilities of age and size and their strategic implications. Research in Organizational Behavior, 8, 165-198.
- Altman, E. I., Iwanicz-Drozdowska, M., Laitinen, E. K., & Suvas, A. (2017). Financial distress prediction in an international context: A review and empirical analysis of Altman’s Z-Score model. Journal of International Financial Management & Accounting, 28(2), 131-171.
- Altman, E. I. (1968). Financial ratios, discriminant analysis and the prediction of corporate bankruptcy. Journal of Finance, 23(4), 589-609.
- Argenti, J. (1976). Corporate collapse: the causes and symptoms. McGraw-Hill, New York, NY.
- Balcaen, S., & Ooghe, H. (2006). 35 years of studies on business failure: an overview of classic statistical methodologies and their related problems. British Accounting Review, 38(1), 63- 93.
- Bates, T. (2005). Analysis of young, small firms that have closed: delineating successful from unsuccessful closures. Journal of Business Venturing 20(3), 343-358.
- Beaver, W. H. (1966). Financial ratios as predictors of failure. Journal of Accounting Research, 4, 71-111.
- Bellovary, J. L., Giacomino, D. E., & Akers, M. D. (2007). A review of bankruptcy prediction studies: 1930 to present. Journal of Financial Education, 33(4), 3-41.
- Boyer, T., & Blazy, R. (2014). Born to be alive? The survival of innovative and non-innovative French micro start-ups. Small Business Economics, 42(4), 669-683.
- Brüderl, J., Preisendörfer, P., & Ziegler, R. (1992). Survival chances of newly founded business organizations. American Sociological Review, 57(2), 227-242.
- Cannon, M. D., & Edmondson, A. C. (2005). Failing to learn and learning to fail (intelligently): How great organizations put failure to work to innovate and improve. Long Range Planning, 38(3), 299-319.
- Chrisman, J. J., & McMullan, W. E. (2004). Outsider assistance as a knowledge resource for new venture survival. Journal of Small Business Management, 42(3), 229-244.
- Coad, A., Frankish, J., Roberts, R. G., & Storey, D. J. (2013). Growths paths and survival chances: An application of Gambler’s Ruin theory. Journal of Business Venturing, 28(5), 615-632.
- Cochran, A. B. (1981). Small business mortality rates: a review of the literature. Journal of Small Business Management, 19(4), 50-59.
- Cooper, A. C., Gimeno-Gascon, J. F., & Woo, C. Y. (1994). Initial human and financial capital as predictors of new venture performance. Journal of Business Venturing, 9(5), 371-395.
- Del Monte, A., & Scalera, D. (2001). The life duration of small firms born within a start-up programme: Evidence from Italy. Regional Studies, 35(1), 11-21.
- Dimitras, A. I., Zanakis, S. H., & Zopounidis, C. (1996). A survey of business failures with an emphasis on prediction methods and industrial applications. European Journal of Operational Research, 90(6), 487-513.
- du Jardin. (2015). Bankruptcy prediction using terminal failure processes. European Journal of Operational Research, 242(1), 286-303.
- du Jardin. (2017). Dynamics of firm financial evolution and bankruptcy prediction. Expert Systems with Applications, 75(1), 25-43.
- Girma, S., Görg, H., & Strobl, E. (2007). The effects of government grants on plant survival: A micro-econometric analysis. International Journal of Industrial Organization, 25(4), 701-720.
- Henderson, A. D. (1999). Firm strategy and age dependence: A contingent view of the liability of newness, adolescence and obsolescence. Administrative Science Quarterly, 44(2), 281-314.
- Huyghebaert, N., Gaeremynck, A., Roodhooft, F., & van de Gucht, L. M. (2000). New firm survival: The effects of start-up characteristics. Journal of Business Finance & Accounting, 27(5-6), 627-651.
- Laitinen, E. K. (1991). Financial ratios and different failure processes. Journal of Business Finance & Accounting, 18(5), 649-673.
- Laitinen, E. K. (1992). Prediction of failure of a newly founded firm. Journal of Business Venturing, 7(4), 323-340.
- Laitinen, E. K. (2016). Financial failure of a startup: a simulation approach. International Journal of Management and Enterprise Development, 15(4), 282-307.
- Liao, J., & Gartner, W. B. (2006). The effects of pre-venture plan timing and perceived environmental uncertainty on the persistence of emerging firms. Small Business Economics, 27(1), 23-40.
- Lukason, O., & Laitinen, E. K. (2016). Failure processes of old manufacturing firms in different European countries. Investment Management and Financial Innovations, 13(2), 310-321.
- Lukason, O., Laitinen, E. K., Suvas, A. (2016). Failure processes of young manufacturing micro firms in Europe. Management Decision, 54(8), 1966-1985.
- Lukason, O., & Masso, J. (2010). Performance of selected Estonian firms financed with start-up grant: Ability to follow plans and grant usage efficiency. Discussions on Estonian Economic Policy, 18, 253-265.
- Lussier, R. N. (1995). A nonfinancial business success versus failure prediction model for young firms. Journal of Small Business Management, 33(1), 8-20.
- Mata, J., & Portugal, P. (1994). Life duration of new firms. Journal of Industrial Economics, 42(3), 227-245.
- Miettinen, M. R., & Littunen, H. (2013). Factors contributing to the success of start-up firms using two-point or multiple-point scale models. Entrepreneurship Research Journal, 3(4), 449-481.
- Ooghe, H., & de Prijcker, S. (2008). Failure processes and causes of company bankruptcy: a typology. Management Decision, 46(2), 223-242.
- Pellegrini, G., & Muccigrosso, T. (2016). Do subsidized new firms survive longer? Evidence from a counterfactual approach. Regional Studies (early view article).
- Pergelova, A., & Angulo- Ruiz, F. (2014). The impact of government financial support on the performance of new firms: the role of competitive advantage as an intermediate outcome. Entrepreneurship and Regional Development, 26(9-10), 663-705.
- Perry, S. C. (2001). The relationship between written business plans and the failure of small businesses in the U.S. Journal of Small Business Management, 39(3), 201-208.
- Pinches, G. E., Mingo, K. A., & Caruthers, J. K. (1973). The stability of financial patterns in industrial organizations. Journal of Finance, 28(2), 389-396.
- Pretorius, M. (2009). Defining business decline, failure and turnaround: a content analysis. Southern African Journal of Entrepreneurship and Small Business Management, 2(1), 1-16.
- Ravi Kumar, P., & Ravi, V. (2007). Bankruptcy prediction in banks and firms via statistical and intelligent techniques – a review. European Journal of Operational Research, 180(1), 1-28.
- Stam, E., Audretsch, D., & Meijaard, J. (2008). Renascent entrepreneurship. Journal of Evolutionary Economics, 18(3), 493-507.
- Sun, J., Li, H., Huang, Q.-H., & He, K.-Y. (2014). Predicting financial distress and corporate failure: A review from state-of-art definitions, modelling, sampling, and featuring approaches. Knowledge-Based Systems, 57, 41-56.
- Wiklund, J., Baker, T., & Shepherd, D. (2010). The age-effect of financial indicators as buffers against the liability of newness. Journal of Business Venturing, 25(4), 423-437.