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Illiquidity, Financial Development and the Growth-Volatility Relationship By Enisse Kharroubi

Illiquidity, Financial Development and the Growth-Volatility Relationship By Enisse Kharroubi. Comments by: Arturo Galindo Universidad de los Andes. The Growth and Welfare Effects of Macroeconomic Volatility Barcelona - March 17-18, 2006. General Comment.

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Illiquidity, Financial Development and the Growth-Volatility Relationship By Enisse Kharroubi

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  1. Illiquidity, Financial Development and the Growth-Volatility RelationshipBy Enisse Kharroubi Comments by: Arturo Galindo Universidad de los Andes The Growth and Welfare Effects of Macroeconomic Volatility Barcelona - March 17-18, 2006

  2. General Comment • This is a nice paper that analyzes both from a theoretical and empirical perspective the link between volatility, growth and financial development • The paper concludes that the negative relationship between growth and volatility is stronger in countries with lower financial development. • …and more likely to be positive in countries with deeper credit markets.

  3. Two Sets of Comments • Clarifying questions on the theoretical part of the paper • Comments on the empirical tests

  4. Summary of the Model • The model assumes that lenders choose the allocation of short term and long term loans, and that there is interim moral hazard (the possibility of the borrower deviating long term fund from their original use) • To reduce this type of moral hazard lenders discipline borrowers by issuing short term debts • This solves a micro problem but generates a coordination problem and can lead to multiple equilibria • One in which s.t. loans are rolled over • Inefficient run eq.

  5. Summary of the Model • There is a level of short term payments that increases the desire of the entrepreneur from not deviating form his L.T. technology. This allows for an incentive compatible solution in which the lender supplies incentives to the entrepreneur to continue in the L.T. technology, and can be reached as long as the L.T. technology is not too illiquid (safe financing strategy). • There is also a risky lending strategy when the production technology is sufficiently illiquid. Entrepreneurs make decisions based on expected rollover probability. If this probability is low the entrepreneur finances his investment with less S.T: debt. This is risky in the sense that it depends on the rollover risk.

  6. Clarifying questions about the model • What is the economic interpretation of h? There is none in the paper. • Should it be interpreted as a liquidity shock? • Is it known in t=0? • Is there any uncertainty on h? • Is uncertainty about h relevant in the moral hazard story?

  7. Clarifying questions about the model • Is there uncertainty about R or r? Is it always the case that R>r2? • Why would the entrepreneur who at t=0 chooses the L.T: technology want to move to the S.T. technology? • Intuitively, why is there a difference between t and t’? In particular why is t > t’? • In a two period world (that is in a non repeated game set up), why is it more costly to default on a l.t. debt than on a s.t. debt if defaulting on the s.t. debt implies reducing the roll over probability? • If t’ is sufficiently large would that rule out interim moral hazard?

  8. Clarifying questions about the model • How is the interest rate structure determined? • In f.n.8: interest rates are exogenous and such that investors are indifferent between lending s.t. and l.t. • Is the fact that s.t. loans are perfectly enforceable and l.t. loans are not, the possibility that there is interim MH, and h, incorporated in the interest rate structure? • Why is rs independent of a and b? Does the competitive structure of lenders matter? If lenders are competitive one would expect that they break even, in such a case wouldn’t a and b and other parameters affect r?

  9. Summary of the Model • In the mixed strategy eq, expected growth decreases with d and growth volatility increases with d • In the pure strategy eq. expected growth increases with dif and only d<m2 +z1 • In the pure strategy eq. growth volatility increases with dif and only d<m2 +z2

  10. Summary of the Model • When d is low the mixed strategy equilibrium prevails and there is a negative correlation between growth and growth volatility • When d is high the pure strategy equilibrium prevails and there is a positive correlation between growth and volatility

  11. Summary of the Model • However, despite the fact that there is a negative correlation, the impact of d – financial development - on growth and growth volatility, seem to be counter intuitive for countries with low d! • Moreover according to the model there is always a negative relationship between d and growth! • Several research pieces suggest that there is a positive correlation between d and growth for developing countries (Levine 2004). The model suggests that this correlation should be negative! • Moreover research also has suggested that there is a negative correlation between d and the volatility of growth for developing countries. (Bekaert, Harvey, Lundblad 2004, Easterly, Islam, Stiglitz, 2000)

  12. Comments on Empirics • The paper estimates the following regression: • Where dis a measure of financial development, g is the growth rate of GDP per capita and x is the log of GDP. • The crucial empirical findings are that • The author claims that this finding supports the theory, but one should look at the results carefully.

  13. According to the data: • In very little cases there is a positive correlation between g and volatility • According to the estimates of table 2, there is a positive correlation when ll>0.95 • This occurs in only 3% of the observations

  14. According to the data: • According to the estimates of table 3, there is a positive correlation when fia>1.7 • This occurs in only 3.6% of the observations

  15. Comments on Empirics • The author does not claim any causal effects in the estimations. In fact endogeneity appears to be a source of concern. • Not only in g, but also in d • But even if you are looking only at the correlations you should be cautious with: • High collinearity between d and g, induces high variance in your estimates so it is difficult to make any inferences • Omitted variables that affect the precision of the estimates: previous studies have also included developing country dummies, (M+X)/GDP, volatility of money growth, volatility of real wages, level and volatility of capital flows, among others.

  16. The model provides an explanation of how s.t. and l.t loans are chosen • From the perspective of development countries I have doubts that the setting is completely relevant. • “Original sin” view, seems to be more important (at least in LAC). • IDB 2005 explores determinants of loan composition in LAC and find that regulatory barriers and lack of matching funding are the main determinants of the composition of lenders portfolio. • In the case of L.T. vs S.T. loans the driving force for low share of L.T. loans is lack of L.T. liabilities and restrictions on maturity mismatches. • Macro instability, prob of S.S., etc. seems to be a more plausible story for the determination of the debt structure of firms in LAC

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