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Mendel University, Brno
- 1. The 18th conference of doctoral students PEFnet Mendel University in Brno Antonia FICOVAa, Juraj SIPKOb The Impact of Debt Crisis on Performance of Firms in Slovakia A PhD Candidate at Faculty of Economics and Business, Pan European University, Bratislava, Slovakia, 85105 B Assoc. Prof at Faculty of Economics and Business, Pan European University, Bratislava, Slovakia, 85105 20.11.2014
- 2. OUTLINE o Research Methodology, o Introduction, o Literature Review, o Hypotheses I., II., o Conclusions. Antonia Ficova, Juraj Sipko, Department of International Business, Pan European University, Bratislava, 2014
- 3. RESEARCH METHODOLOGY o official websites of firms on Slovak market, Statistical Office of the Slovak Republic, FinStat, o qualitative and quantitative analysis, oOrdinary Least Squares (OLS), ocorrelation matrix, o normality test, oThe ‘Student’ t-test distribution with (N−1) degrees of freedom, o the two-sample t-test for mean value o Eviews, MS Excel. Antonia Ficova, Juraj Sipko, Department of International Business, Pan European University, Bratislava, 2014
- 4. INTRODUCTION o Slovak economy has become strongly dependent on foreign demand, oSlovakia has performed a successful restructuring strategy: GDP Growth Rate 0.6% in Q1 2014 o Foreign investments in the automotive and electronic sectors = expansion= export o Machinery and transport equipment, manufactured goods, fuels and chemicals = import oa trade surplus of 233 EUR mln in Aug of 2014 Antonia Ficova, Juraj Sipko, Department of International Business, Pan European University, Bratislava, 2014
- 5. INTRODUCTION o indebted countries are expected their cost of debt financing increasing, o this has a negative impact and developing countries because - it could raise on debt valuation of emerging their cost of indebtedness, o better and careful monitoring over the internal financial system of the firm – Prevention - Corporate sector indicators Antonia Ficova, Juraj Sipko, Department of International Business, Pan European University, Bratislava, 2014
- 6. LITERATURE REVIEW o Trebesch, Ch. (2009) identified channels by which sovereign debt distress can affect private sector: 1. demand effects, default periods often coincide with output losses and lower domestic demand 2. the drop in corporate external credit may be attributable to supply effects. Antonia Ficova, Juraj Sipko, Department of International Business, Pan European University, Bratislava, 2014
- 7. Testing Hypothesis I. Antonia Ficova, Juraj Sipko, Department of International Business, Pan European University, Bratislava, 2014 o profit (€), working capital (million €), revenue (€), return on equity (%), return on assets (%), net debt/ebitda, investment, cash (€), capital expenditure (€), assets (%) debt ratio o data of 12 slovak firms with 3000-3999 employees during period from 2010 till 2013, o N=42 at 95 percent of probability
- 8. Testing Hypothesis I. Antonia Ficova, Juraj Sipko, Department of International Business, Pan European University, Bratislava, 2014 oChemicals & Plastics (Slovnaft, a.s.); Automotive industry (Kia Motors Slovakia s.r.o., Yazaki Wiring Technologies Slovakia s.r.o.); Telecommunications (Slovak Telekom, a.s.); Metal production and metallurgy (Železiarne Podbrezová a.s.); Retail sale (Lidl Slovenská republika, v.o.s.); Engineering (INA Kysuce, spol. s r.o.); Law, Consulting, Accounting (IBM International Services Centre s.r.o.), Mining (Hornonitrianske bane Prievidza, a.s.); Financial sector (Všeobecná úverová banka, a.s.; VÚB, a.s., Tatra banka, a.s., Slovenská sporiteľňa, a.s. SLSP, a.s.).
- 9. Antonia Ficova, Juraj Sipko, Department of International Business, Pan European University, Bratislava, 2014 Testing Hypothesis I.Dependent Variable: DEBT RATIO Method: Least Squares Sample: 1 42 Included observations: 42, k=10 Variable Coefficient Std. Error t-Statistic Prob. PROFIT 0.039 0.046 0.842 0.406 WORKING CAPITAL -0.022 0.004 -5.231 0.000 REVENUE 0.000 0.002 0.195 0.846 RETURN ON EQUITY 0.690 0.113 6.096 0.000 RETURN ON ASSETS -2.122 0.713 -2.972 0.005 NET DEBT EBITDA 1.886 3.065 0.615 0.542 INVESTMENT -0.002 0.004 -0.654 0.517 CASH 0.010 0.005 1.978 0.056 CAPITAL EXPENDITURE 13.477 6.157 2.188 0.036 ASSETS 0.005 0.000 6.661 0.000 C 41.348 4.090 10.1086 0.000 R-squared 0.913 Mean dependent var 57.085 Adjusted R-squared 0.884 S.D. dependent var 25.323 S.E. of regression 8.609 Akaike info criterion 7.363 Sum squared resid 2297.627 Schwarz criterion 7.818 Log likelihood -143.636 Hannan-Quinn criter. 7.530 F-statistic 32.375 Durbin-Watson stat 1.595 Prob(F-statistic) 0.000 Source: Author´s estimation by using Eviews. Debt ratio = 41.349 + 0.039*profit - 0.022*working capital + 0.000*revenue + 0.690*return on equity – 2.122*return on assets + 1.886* net deb/ebitda – 0.002* investment + 0.010*cash+ 13.477*capital expenditure + 0.005* assets
- 10. Source: Author´s estimation by using Eviews. TESTING HYPOTHESIS I. Antonia Ficova, Juraj Sipko, Department of International Business, Pan European University, Bratislava, 2014 10 20 30 40 50 60 70 80 90 100 -40 0 40 80 120 160 200 240 PROFIT Debtratio 10 20 30 40 50 60 70 80 90 100 0 400 800 1,200 1,600 2,000 Working Capital Debtratio 10 20 30 40 50 60 70 80 90 100 -20 0 20 40 60 80 100 Return on equity Debtratio 10 20 30 40 50 60 70 80 90 100 -4 0 4 8 12 16 20 24 Return on assets Debtratio 10 20 30 40 50 60 70 80 90 100 0 200 400 600 800 1,000 1,400 CASH Debtratio 10 20 30 40 50 60 70 80 90 100 -0.4 0.0 0.4 0.8 1.2 1.6 2.0 2.4 Capital expenditure Debtratio
- 11. Testing Hypothesis II. Antonia Ficova, Juraj Sipko, Department of International Business, Pan European University, Bratislava, 2014 oIs means of performance of the firms in 2010 are the same as means of performance of the firms in 2013 after debt crisis? owe use Normal Quantile Plot - Test for Non-Normality, oparametric test, method The ‘Student’ t-test distribution with (N−1) degrees of freedom, mean test of correlation with a known constant by using the two-sample t-test for mean value.
- 12. Antonia Ficova, Juraj Sipko, Department of International Business, Pan European University, Bratislava, 2014 Testing Hypothesis II. Source: Author´s estimation by using Eviews.
- 13. CONCLUSION FROM TESTING HYPOTHESIS I. o coefficient of determination is 0.913 indicates that 91.27%, o significance of F is 0.000000<0.01; o cash flow, extend payment terms (Purchasing), reduce collection terms (credit), identification and disposal of obsolete inventories (Controllership), reduce borrowing cost (Treasury), reduce finance administrative expense (Finance Leadership). Antonia Ficova, Juraj Sipko, Department of International Business, Pan European University, Bratislava, 2014
- 14. CONCLUSION FROM TESTING HYPOTHESIS II. o we explored performance of firms during period 2010 and 2013=could by caused by different strategy of each firm, o we found that firm´s return on equity, return on assets, total assets, profit is attached with debt portion of company positively, o if company debt ratio increases, there is negative correlation on the growth of the company, more to the point on working capital, investment, capital expenditure, revenue. Antonia Ficova, Juraj Sipko, Department of International Business, Pan European University, Bratislava, 2014
- 15. REFERENCES 1. Berger, A. N., Bouwman, H.S. Ch., 2009: Bank Capital, Survival, and Performance around Financial Crises, Wharton Financial Institutions Center, and Center – Tilburg University, Wharton Financial Institutions Center 2. Brown, M. - Lane, P. R., 2011: Debt Overhang in Emerging Europe? World Bank Policy Research Working Paper Series, Vol. , pp. -, 2011 3. Corsetti, G., - Pesenti, P. - Roubini, N., 1998: What Causes the Asian Currency and Financial Crises? A Macroeconomic Overview, New York University 4. Davis, E. P. - Mark, S., 2004: Corporate Financial Structure and Financial Stability. IMF Working Paper, Vol. , pp. 1-49 5. Duchin, R. - Ozbas, O. - Sensoy, B. A., 2009: Costly External Finance, Corporate Investment, and the Subprime Mortgage Credit Crisis, Journal of Financial Economics (JFE), Forthcoming; Marshall School of Business Working Paper No. MKT 01-09; Ross School of Business Paper No. 1121 6. Ernst and Young, 2013: Remaking financial services: risk management five years after the crisis, A survey of major financial institutions, EYG No. EK0162, 1303-1045437 BOS, ED 0714 7. FinStat, available at: <http://www.finstat.sk˃ 8. Flannery, M. J. – Hankins, K. W., 2013: Estimating dynamic panel models in corporate finance, Journal of Corporate Finance 19 (2013) 1–19 9. Gertler, M., - Gilchrist, S. - Natalucci, F. M., 2000: External Constraints on Monetary Policy and the Financial Accelerator, NBER Working Paper No. 10128 (Cambridge, Massachusetts: National Bureau of Economic Research). 10. IGBAL, A. - HAMEED, I. - RAMZAN, N., 2012: The Impact of Debt Capacity on Firm’s Growth, American Journal of Scientific Research, ISSN 1450-223X, Issue 59, pp. 109-115 11. IMF, 2012: Slovak Republic: 2012 Article IV Consultation—Staff Report 12. João, P., Coutinho dos Santos, João, M., 2014: Corporate Financing Choices after the 2007-2008 Financial Crisis 13. Krugman, P., 1999: Balance Sheets, the Transfer Problem, and Financial Crises, MIT 14. Mulder, Ch. - Perrelli, R. - Rocha, M., 2001: The Role of Corporate, Legal, and Macro Balance Sheet Indicators in Crisis Detection and Prevention 15. Nenova, T. - Claessens, S. - Simeon D., 2000: Corporate Risk around the World World, Bank Policy Research Working Paper No. 2271 16. Nerlove, M., 1967: Experimental evidence on the estimation of dynamic economic relations from a time series of cross sections, Econ. Stud. Quart. 18, 42–74. 17. Nickell, S., 1981: Biases in dynamic models with fixed effects, Econometrica 49, 1417–1426. 18. Statistical Office of the Slovak Republic, available at <http://slovak.statistics.sk˃ 19. Trebesch, Ch., 2009: The Cost of Aggressive Sovereign Debt Policies: How Much is the Private Sector Affected? IMF Working Papers, Vol., pp. 1-35 Antonia Ficova, Juraj Sipko, Department of International Business, Pan European University, Bratislava, 2014
- 16. Antonia FICOVA antoniaficova@zoho.com Juraj SIPKO juraj.sipko@gmail.com Antonia Ficova, Juraj Sipko, Department of International Business, Pan European University, Bratislava, 2014
Editor's Notes
- Slovak economy has become strongly dependent on foreign demand, especially from Germany and the euro area. In other words, business cycles in the industries concerned are often more pronounced than in other industries, especially services. During the past decade, Slovakia has performed a successful restructuring strategy. GDP Growth Rate in Slovakia averaged 0.93% from 1997 until 2014, reaching an all time high of 9% in the fourth quarter of 1998 and a record low of -7.60% in the first quarter of 2009 to 0.6% in Q1 2014 reported by the Statistical Office of the Slovak Republic. Moreoever, export industries have received special attention. Foreign investments in the automotive and electronic sectors have been the main source of the recent expansion. Main export partners are Euro Area members with German, Czech Republic, France and Poland being the most important. However, the biggest share of Slovakian imports are machinery and transport equipment, intermediate manufactured goods, fuels and chemicals and main import partners are Germany, Czech Republic, Russia and Hungary.
- However, more indebted countries are expected to see their cost of debt financing increasing, since the financial system of countries hit by the crisis is rebalancing its portfolio of assets into positions that are less risky. In this light, this has a negative impact and developing countries because it could raise on debt valuation of emerging their cost of indebtedness. In sum, better and careful monitoring over the internal financial system of the firm, even if the system seems healthy and not affected by contagion. Prevention, rather than curing, is the right policy in these times. Corporate sector indicators are useful for assessing the potential impact of exchange rate and interest rate changes on corporate sector balance sheets. The monitoring through the two indicators of exposure could be complemented by indicators related to corporate leverage, profitability, cash flow and financial structure.
- Viewed in this light, there are at least two causal channels according to the Trebesch, Ch. (2009) by which sovereign debt distress can affect private sector external borrowing in emerging market countries. First, demand effects, default periods often coincide with output losses and lower domestic demand, this can lead to a drop in production, investment and profits, which may be further reinforced by banking sector stress. As a result, firms may demand less credit. Second, the drop in corporate external credit may be attributable to supply effects. In sum, sovereign defaults might worsen country risk perceptions as a whole, increase risk premia on all new loans to domestic agents and thereby reduce private sector external debt issuance.
- According to the results of OLS at 95% confidence level, which are presented in Table 1 above show, that coefficient of determination R2 = 0.913 indicates that 91.27% of the variance of the endogenous variable (debt ratio) is being explained by changes in the variables x, that shows changes in profit, working capital, investments, revenue, etc., in short that means positive linear relationship. On the other hand, 8.74% of changes in the debt ratio of the firms are affected by other variables that are not included in this model, for example rate of economic growth of the country, inflation, government restrictions (higher taxe rate, exchange rate, interest rate), etc. The significance of the model, prob (F-statistic) is 0.000000<0.01; what is high statistically significant (++). The parameter β is high statistically significant because the P-value is 0.0000<0.01; (++). The parameter x2, x4, x5, x8, x9, x10 are high statistically significant because of the P-value. For N = 42, k = 10, and significant level = 5%, the significant Durbin-Watson statistic dL is 0.749, dU is 1.956. Since the Durbin-Watson d statistic, 4-1.595=2.405, a value near 2 indicates non-autocorrelation in this model. concluded that when company increase their debt level there should be positive impact on growth of the firm. As this paper found that company return on equity, return on assets, total assets, profit is attached with debt portion of company positively, so those companies having high leveraged company should decrease their debt portion for increasing their assets to maintain the growth in market.
- However, at this point we present illustrations of significant variables below. Moreover, the data are displayed as a collection of points, each having the value of one variable determining the position on the horizontal axis and the value of the other variable determining the position on the vertical axis. If the pattern of dots slopes from lower left to upper right, it suggests a positive correlation between the variables being studied, e. g. debt ratio and return on equity, debt ratio and return on assets, debt ratio and assets. If the pattern of dots slopes from upper left to lower right, it suggests a negative correlation, e.g . debt ratio and working capital, debt ratio and cash, see below.
- According to the results of OLS at 95% confidence level, which are presented in Table 1 above show, that coefficient of determination R2 = 0.913 indicates that 91.27% of the variance of the endogenous variable (debt ratio) is being explained by changes in the variables x, that shows changes in profit, working capital, investments, revenue, etc., in short that means positive linear relationship. On the other hand, 8.74% of changes in the debt ratio of the firms are affected by other variables that are not included in this model, for example rate of economic growth of the country, inflation, government restrictions (higher taxe rate, exchange rate, interest rate), etc. The significance of the model, prob (F-statistic) is 0.000000<0.01; what is high statistically significant (++). The parameter β is high statistically significant because the P-value is 0.0000<0.01; (++). The parameter x2, x4, x5, x8, x9, x10 are high statistically significant because of the P-value. For N = 42, k = 10, and significant level = 5%, the significant Durbin-Watson statistic dL is 0.749, dU is 1.956. Since the Durbin-Watson d statistic, 4-1.595=2.405, a value near 2 indicates non-autocorrelation in this model. concluded that when company increase their debt level there should be positive impact on growth of the firm. As this paper found that company return on equity, return on assets, total assets, profit is attached with debt portion of company positively, so those companies having high leveraged company should decrease their debt portion for increasing their assets to maintain the growth in market.
- In short, debt crisis may lead to a generalized systemic crisis through worsened conditions for local credits and through a decline of the demand in the world real economy. We suggest that, if a firm want to increase their financial performance, it is necessary to make changes as follows: if we look at cash flow, extend payment terms (Purchasing), reduce collection terms (credit), support customers with credit facilities (i.e. factoring) granting an affordable prompt payment discount, outlining strategies for identifying / selling idle / non-core assets (Finance Leadership), identification and disposal of obsolete inventories (Controllership), operating results, reduce borrowing cost (Treasury), reduce finance administrative expense (Finance Leadership), permanet review of gross margins (financial planning), cost containment programs (tracking system). In other words, good planning and production helps toward maximization of achieving ends with available resources. A costing team helps firm to analyze costs, volumes, plan profits through fixation of selling prices which are beneficial to both the buyer and the seller. A accounting team ensures that nothing goes unaccounted and that things are accounted correctly. It also ensures that statutory norms are maintained as required.