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VIEWS: 4 PAGES: 7

									Comments on
“Credit Contagion and the
Amplification of the Crisis of 2007-
2009”

            Hsien-hsing Liao
            Department of Finance
            National Taiwan University


                                         1
Contents
 Summary
 Comments
 Suggestions




               2
Summaries of This Paper-1
 Major Objective:
 This study examines credit contagion through
 supplier-customer relationship using American
 bankruptcy firms data during period of 2005 to
 2009.



                                            3
Summaries of This Paper-2
 Major preliminary findings:
    Suppliers are more prone to customer default,
     especially in crisis period.
    Balance contagion is more pronounced for
     industrial firms.




                                                     4
General Comments
 The research topic of this study is very interesting.
 Credit contagion issues have been very hot after the
 recent financial tsunami. Unveiling the exact
 mechanisms of the contagion phenomenon is
 important for both academic literature and
 regulatory policy makings.
 The preliminary findings show the potentials of this
 paper.


                                                    5
Suggestions-1
 When doing panel regressions, controlling for firm
 (or industry) and time fixed effects is necessary.
 When doing regressions, collinearity checks should
 be done. Variables from financial statements are
 usually highly correlated.




                                                      6
Suggestions-1I
 Considering the possibility of heteroskedasticity in
 estimating panel regressions, suggesting using
 methods of White’s (1984) robust standard errors
 or Peterson’s (2009) robust standard errors
 clustered at industry and time level simultaneously.
     White, H., 1984, “A Heteroskedasticity-Consistent
      Covariance Matrix Estimator and a Direct Test for
      Heteroskedasticity, Econometrica 48, 817-838.
     Petersen, M. 2009, “Estimating Standard Errors in Finance
      Panel Data Sets: Comparing Approaches.” Review of
      Financial Studies, 22, 435-480.
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