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Estimating Firms’ Vulnerability to Short-Term Financing Shocks: The Case of Foreign Exchange Companies in Pakistan

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  • Ijaz Hussain

    (Head of Department of Economics, Beaconhouse National University, Lahore, Pakistan.)

Abstract

Using firm-level balance sheet data for 20 of the 24 exchange companies in Pakistan for the period 2006–11, we explore the sources of firms’ vulnerability to short-term financing shocks. Based on the probability estimates of a maximum likelihood binary probit model, this paper shows that the incidence and degree of vulnerability of foreign exchange companies to short-term financing shocks has risen significantly over time. If not managed opportunely, these shocks can cumulate into long-term financing shocks and even lead to corporate failure in the long run. Our regression results show that the corporate managers of these companies cannot ignore macroeconomic factors such as global changes and the macroeconomic environment (inflation and GDP growth) in addition to firm-specific factors (growth opportunities, firm size, permanent earnings, earnings volatility, and working capital management) when managing their firms’ vulnerability to short-term financing shocks.

Suggested Citation

  • Ijaz Hussain, 2013. "Estimating Firms’ Vulnerability to Short-Term Financing Shocks: The Case of Foreign Exchange Companies in Pakistan," Lahore Journal of Economics, Department of Economics, The Lahore School of Economics, vol. 18(2), pages 147-163, July-Dec.
    • Handle: RePEc:lje:journl:v:18:y:2013:i:2:p:147-163
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    1. Patnaik, Ila & Shah, Ajay, 2010. "Does the currency regime shape unhedged currency exposure?," Journal of International Money and Finance, Elsevier, vol. 29(5), pages 760-769, September.
    2. Kevin Cowan & José De Gregorio & Alejandro Micco & Christopher Neilson, 2008. "Financial Diversification, Sudden Stops, and Sudden Starts," Central Banking, Analysis, and Economic Policies Book Series, in: Kevin Cowan & Sebastián Edwards & Rodrigo O. Valdés & Norman Loayza (Series Editor) & Klaus Schmidt- (ed.),Current Account and External Financing, edition 1, volume 12, chapter 5, pages 159-194, Central Bank of Chile.
    3. Sumit Sarkar & Deb Ghosh, 1998. "Partitioning the Attribute Set for a Probabilistic Reasoning System," INFORMS Journal on Computing, INFORMS, vol. 10(4), pages 399-416, November.
    4. Mr. Jorge A Chan-Lau & Mr. Toni Gravelle, 2005. "The END: A New Indicator of Financial and Nonfinancial Corporate Sector Vulnerability," IMF Working Papers 2005/231, International Monetary Fund.
    5. Gerald A. Hanweck, 1977. "Predicting bank failure," Research Papers in Banking and Financial Economics 19, Board of Governors of the Federal Reserve System (U.S.).
    6. Sunti Tirapat & Aekkachai Nittayagasetwat, 1999. "An Investigation of Thai Listed Firms' Financial Distress Using Macro and Micro Variables," Multinational Finance Journal, Multinational Finance Journal, vol. 3(2), pages 103-125, June.
    7. Edward I. Altman, 1968. "Financial Ratios, Discriminant Analysis And The Prediction Of Corporate Bankruptcy," Journal of Finance, American Finance Association, vol. 23(4), pages 589-609, September.
    8. Merton, Robert C, 1974. "On the Pricing of Corporate Debt: The Risk Structure of Interest Rates," Journal of Finance, American Finance Association, vol. 29(2), pages 449-470, May.
    9. Martin, Daniel, 1977. "Early warning of bank failure : A logit regression approach," Journal of Banking & Finance, Elsevier, vol. 1(3), pages 249-276, November.
    10. Edward I. Altman, 1968. "The Prediction Of Corporate Bankruptcy: A Discriminant Analysis," Journal of Finance, American Finance Association, vol. 23(1), pages 193-194, March.
    11. Ohlson, Ja, 1980. "Financial Ratios And The Probabilistic Prediction Of Bankruptcy," Journal of Accounting Research, Wiley Blackwell, vol. 18(1), pages 109-131.
    12. Pettway, Richard H & Sinkey, Joseph F, Jr, 1980. "Establishing On-Site Bank Examination Priorities: An Early-Warning System Using Accounting and Market Information," Journal of Finance, American Finance Association, vol. 35(1), pages 137-150, March.
    13. Gary Whalen, 1991. "A proportional hazards model of bank failure: an examination of its usefulness as an early warning tool," Economic Review, Federal Reserve Bank of Cleveland, vol. 27(Q I), pages 21-31.
    14. West, Robert Craig, 1985. "A factor-analytic approach to bank condition," Journal of Banking & Finance, Elsevier, vol. 9(2), pages 253-266, June.
    15. Beaver, Wh, 1966. "Financial Ratios As Predictors Of Failure," Journal of Accounting Research, Wiley Blackwell, vol. 4, pages 71-111.
    16. Coleen C. Pantalone & Marjorie B. Platt, 1987. "Predicting commercial bank failure since deregulation," New England Economic Review, Federal Reserve Bank of Boston, issue Jul, pages 37-47.
    17. Reynolds, Stephen & Fowles, Richard & Gander, James & Kunaporntham, Wannapat & Ratanakomut, Somchai, 2002. "Forecasting the Probability of Failure of Thailand's Financial Companies in the Asian Financial Crisis," Economic Development and Cultural Change, University of Chicago Press, vol. 51(1), pages 237-246, October.
    18. Gregory R. Gajewski, 1989. "Assessing the risk of bank failure," Proceedings 250, Federal Reserve Bank of Chicago.
    19. Herman Kamil, 2012. "How Do Exchange Rate Regimes Affect Firms' Incentives to Hedge Currency Risk? Micro Evidence for Latin America," IMF Working Papers 2012/069, International Monetary Fund.
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    More about this item

    Keywords

    Foreign exchange companies; vulnerability; financing shocks; Pakistan.;
    All these keywords.

    JEL classification:

    • G33 - Financial Economics - - Corporate Finance and Governance - - - Bankruptcy; Liquidation
    • G30 - Financial Economics - - Corporate Finance and Governance - - - General
    • L80 - Industrial Organization - - Industry Studies: Services - - - General
    • L89 - Industrial Organization - - Industry Studies: Services - - - Other

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