1 1 Macroeconomic fluctuations and corporate financial fragility C. Bruneau (1), O. de Bandt (2) & W. El Amri (3) (1) ECONOMIX, University of Paris X (1,2,3) Bank of France (CEF, July 2009, Sydney)

2 2 Main purposes Model the interactions between business cycle and corporate defaults by integrating individual data on non financial companies ( Dynamic system ) Improve forecasting of Business cycle ( here the GAP (expected default as leading indicator of GAP), as Lindé et al. (2003,2007); Koopman&Lucas (2005) Assess the impact of macro shocks on defaults («Stress testing ») With the aim at taking into account the second round effects of defaults on the macroeconomy.

Plan of the presentation I. Modelling choices  The dynamic system of the panel analysis  The duration model underlying one equation of the system  The specification retained for the duration model (in the lines of Shumway, 2000) so as to estimate the parameters of interest by implementing a standard LOGIT estimation procedure II. (Successive and separate) empirical investigations of:  The impact of macroeconomic conditions on the financial fragility of corporate firms, from a duration model ( at a firm level)  The impact of bankruptcies on the business cycle investigated with panel data (at a sector level) III. Stress tests  Effects of macroeconomic shocks on the distribution of default frequencies (and losses), at the firm level ( standard)  Effects of macroeconomic shocks on the fragility of firms and feedback effects of shocks affecting the default probability on the business cycle, with impulse–response analysis as deduced from a VAR- X type system of equations, estimated at a sector level (more originally)

I. Modelling choices I.1 Dynamic system at sectoral level j

66 I.2 Modelling financial fragility of corporate firms in France from a duration model a / Basic duration Model, without explanatory variable : Introduce a random variable D i which is the number of years between the start of operations and the year at which default of company i occurs ; one realisation of D i is : The density of D i is f and F is the cumulative distribution function. S is the survival function, S=1-F The Hazard function :

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8 8 b/ Duration Model, with explanatory variable (model is conditional on explanatory variables) One introduces the (individual) explanatory variables in the specification of the hazard function - in the standard way, as: - or according to Shumway (2000):

9 9 c/Extensions One can add macroeconomic variables X t, next to the micro/financial variables Z it, provided that their number is less than T. The introduction of these variables helps supporting the assumption of independence across individuals, when taken conditionally on those variables :

10 d/ Likelihood function When the duration variable is taken as a discrete variable, one can rewrite the likelihood as : Such a the likelihood function is formally identical to the one of a multiperiod LOGIT model, with individuals becoming « firm-years » (i,t) and with a cumulated distribution function specified as :

11 The latter property allows to estimate directly the parameters of the hazard function, by using codes available to estimate a standard LOGIT model, but implemented on units which correspond to firm-year observations. Provided that the (usual) number of degrees of freedom in such a procedure is modified to take into account of «non-independency» of the individuals that are firm-years

12 II. Data sources and (successive) empirical investigations of both types of impacts: II.1 Impact of macroeconomic conditions on the fragility of firms, measured from the duration model, at the firm level II. 2 Impact of fragility of firms on the business cycle (measured at a sector level, from panel data)

13 II.1. Impact of macroeconomic conditions on the fragility of firms, measured from the duration model, at the firm level) Data base FIBEN FIBEN is the acronym of FIchier Bancaire des Entreprises, run by Banque de France. Access to FIBEN is, since 1982, reserved to public and credit institutions Around balance sheets collected every year FIBEN is made of companies with annual turnover > euros (Medium sized and large companies) Covers companies accounting for 90% of bank loans

14 Sample period: Initial database: firms among them failed firms ( Obs.) Sample: Dynamic Model (H3): firms. Among them failed firms ( obs.; firms-dates) Variables : Financial Ratios (Micro) + Dummy variables + Macro variables * Financial Ratios (individual)  Profit = Profit / Total assets  Leverage = Total Borrowing / Total Liabilities  Liquidity = Liquid assets / Financial Debt  Business credit (in day of purchase)=360 * business Credit / Purchases (VAT)  Int = Interest paid / (Interest paid+Profit) * Dummy variables  IP = Payment incidents (1 if incident ; 0 otherwise)  Det.Etat = Debt vis-à-vis the government (URSAF&FISC) ; (1 si Det.Etat ; 0 sinon) * Macro variables  GAP = Output Gap  INF = Inflation rate  IRL = Nominal long term interest rate  Ex.Rate = Nominal euro/dollar exchange rate

15 For the microeconomic explanatory variables, we take into account the whole information available before default if the company defaults and the whole available information, otherwise Here we chose to introduce macroeconomic variables with lags 2 and 3 and the financial ratios with a lag equal to 3, because they are more reliable for scoring purposes

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Tree-year Horizon 17

Two-year Horizon 18

19 We take into account the individual and cyclical dynamics (both micro and macro) Default probability is closely related to the (opposite) GAP ( - GAP)

II. 2. Impact of fragility of firms on the business cycle (measured at a sector level, from panel data)

22 III. Stress Testing exercises III. 1 Standard stress test exercise : effects of macroeconomic shocks on the distribution of default frequencies (and losses), at the firm level III. 2 Effects of macroeconomic shocks on the fragility of firms and feedback effects of shocks affecting the default probality on the business cycle, through an impulse– response analysis as deduced from a VAR- X type system of equations estimated at a sector level 22

23 III.1.Implementing (standard) Stress Test I

Scenario2: GAP in 2002 – 2 S. dev. 24

25 Scenario2: GAP in 2002 – 2 S. dev. 25

26 III.2.Implementing Stress Test II Putting the 2 equations together : Study the joint dynamics of default and GAP

27 III.2.Implementing Stress Test II (+ 1 s.d on the GAP variable)

28 The building blocks (Stress Testing)

29 Impulse responses from the VAR shock=1.s.d. on each variable 29

Impulse responses from Panel-VAR with macroeconomics variables réactions 30

Conclusion Thanks to a rich individual data base (Bank of France) (large individual dimension and significant time dimension ( 15 years) We have measured : 1/ the impact of macroeconomic conditions on the fragility of corporate firms 2/ the influence of the financial fragility of firms on the business cycle first, separately, 1/ at the individual level (from a duration model) and 2/ at the sector level (panel analysis) then, jointly, in stress test exercices implemented - in a standard way, at the firm level, - more originally, by taking into account second round effects, at the sector level

Conclusion Possible Improvements:  Investigating other specifications of the duration model, to investigate for exemple the influence of the life duration on the default  Checking the exogeneity assumption for financial ratios in the model  Implementing a real stress test exercice with the second round effects in the case of the portfolio of a particular bank, in order to measure the impact of the dynamics on the risk level of the bank (through VaR or CVaR measures)