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Accounting for Crises

Accounting for Crises. September 2008 Venky Nagar Gwen Yu. Causes of Crises. Fundamentals or self-fulfilling beliefs ? This paper tests a key comparative static of recent analytical papers: High precision public signals allows for better coordination …. of higher order beliefs

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Accounting for Crises

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  1. Accounting for Crises • September 2008 • Venky Nagar • Gwen Yu

  2. Causes of Crises Fundamentals or self-fulfilling beliefs? This paper tests a key comparative static of recent analytical papers: High precision public signals allows for better coordination …. of higher order beliefs And thus promotes self-fulfilling crises

  3. Causes of Crises Fundamentals or self-fulfilling beliefs This paper tests a key comparative static of recent analytical papers: High precision public signals allows for better coordination …. of higher order beliefs And thus promotes self-fulfilling crises

  4. Standard Models Fundamentals Value

  5. Recent Comparative Statics Models Coordinated Action Ex post cash flows Fundamentals Value

  6. Recent Comparative Statics Models Coordinated Action Ex post cash flows Fundamentals Value Higher order beliefs

  7. Example • % speculators needed to tank an asset (this information common knowledge) • 0% • 110% • 60%, 30%, 43% • Everyone believes nobody will attack • Everyone believes everyone will attack • Econ 101’s weird cousin • Coordinating role of public signals

  8. Recent Comparative Statics Models Institutional Features Financial Markets Technical Features Externalities (no speculator is too big) Role of Public Information Models Angeletos & co., Atkenson, Rey, Morris & Shin,

  9. Angeletos and Werning 2006 Multiplicity on x-axis

  10. Robustness • Endogenizing Payoffs • Endogenizing Policies • Endogenizing Information Signals • Externalities are the key

  11. Angeletos and Werning

  12. Why Accounting Data • Key information input into financial markets • Has precision metric satisfying Harvard Prof. Michael Kremer’s rule • Source of variation • Legal institutions • Excess volatility of other signals • Variance of noise vs. fundamentals • Statistical power • Unexplored to our knowledge

  13. Main Prediction • Fundamentals are more likely to predict crises in countries with low precision public information • Statistical Approach • In-sample prediction • Control for country fixed effects and cross-sectional correlation • Extensive set of controls

  14. Overall Background (1) (2) where (3)

  15. Table 1: Crisis onset years, 1976-2005 (Continued)

  16. Table 1: Crisis onset years, 1976-2005 (Continued)

  17. Table 2: Crisis onset years and number of public firms,1976-2005

  18. Table 2: Crisis onset years and number of public firms,1976-2005 (Continued) (Continued)

  19. Table 2: Crisis onset years and number of public firms,1976-2005 (Continued)

  20. Table 2: Crisis onset years and number of public firms,1976-2005 (Continued)

  21. Table 2: Crisis onset years and number of public firms,1976-2005 (Continued) (Continued)

  22. Table 2: Crisis onset years and number of public firms,1976-2005 (Continued)

  23. Key notion of Accounting Quality • Rational Investors want information on unrealized gains and losses (Accruals) • Writeoffs • Credit sales • Misreporting (scienter) • Causes of misreporting • Difficulty • Legal Regime • Variation in Accounting Quality (or Precision)

  24. Table 3: Measures of accounting information quality [c = country, f = firm, t = year]

  25. Table 3: Measures of accounting information quality(Continued) [c = country, f = firm, t = year]

  26. Empirical Approach • Construct a composite precision score • Bifurcate the sample

  27. Table 4: Countries’ average accounting information quality, 1981-2005 Panel A: Countries with high quality accounting information

  28. Table 4: Countries’ average accounting information quality, 1981-2005 (Continued) Panel B: Countries with low quality accounting information

  29. Table 5: Stability of accounting information across different legal institutions and over time Panel A: Country ranking of quality of legal institutions by accounting information quality

  30. Table 5: Stability of accounting information across different legal institutions and over time Panel A: Country ranking of quality of legal institutions by accounting information quality

  31. Table 5: Stability of accounting information across different legal institutions and over time (Continued) Panel B: Correlation of accounting information quality and legal institutions Panel C: AR(1) coefficients between the values of each accounting quality measures over non-over lapping consecutive periods

  32. Table 6: Definitions of leading indicators Panel A: Definition of leading indicators (Continued)

  33. Table 6: Definitions of leading indicators (Continued) (Continued)

  34. Table 6: Definitions of leading indicators (Continued)

  35. Table 6: Descriptive statistics of leading indicators Panel B: Descriptive statistics of leading indicators

  36. Table 6: Descriptive statistics of leading indicators (Continued) Panel B: Descriptive statistics of leading indicators

  37. Table 7: Descriptive statistics of country characteristics Panel A: Countries with high quality accounting information

  38. Table 7: Descriptive statistics of country characteristics(Continued) Panel B: Countries with low quality accounting information

  39. Table 8: Definitions of realizedaccounting signals Panel A: Definitions of realized accounting signals

  40. Table 8: Descriptive statistics of realizedaccounting signals Panel B: Descriptive statistics of realized accounting signals

  41. Figure 1: Realized accounting signals before and after 39 crises Panel A Accrualsc,t Crisis years - Countries with low information quality Crisis years - Countries with high information quality Tranquil years - All countries Panel B Profitabilityc,t Crisis years - Countries with low information quality Crisis years - Countries with high information quality Tranquil years - All countries

  42. Figure 1: Realized accounting signals before and after 39 crises Panel C Volatility c,t Crisis years - Countries with low information quality Crisis years - Countries with high information quality Tranquil years - All countries

  43. Takeaway • Accounting data behave as predicted

  44. Table 9: Correlation matrix of crises predictors Panel B: Time series correlation of accounting signals (Spearman \ Pearson)

  45. Table 10: Multivariate analysis of crises prediction Model: (Continued)

  46. Table 10: Multivariate analysis of crises prediction(Continued) (Continued)

  47. Table 10: Multivariate analysis of crises prediction (Continued)

  48. Table 11: Crisis prediction of accounting signals for high vs. low accounting quality Model : : if country has high quality accounting information , 0 otherwise. : if country has low quality accounting information , 0 otherwise. (Continued)

  49. Table 11: Crisis prediction of accounting signals for high vs. low accounting quality (Continued) (Continued)

  50. Table 11: Crisis prediction of accounting signals for high vs. low accounting quality (Continued)

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