According to the credit channel theory of the monetary transmission mechanism, frictions in credit markets that generate a wedge between the costs of raising funds externally and internally, the external finance premium, help explain the effect of monetary policy on real variables. For example, the cost of monitoring in credit markets suggests poorly-collateralized borrowers will pay a higher premium for external funds than larger, more-collateralized borrowers. The credit channel of monetary policy is the mechanism through which monetary policy impacts the real economy by altering the external finance premium. In particular, by affecting this wedge countercyclically, monetary policy has an additional impact on real variables beyond its standard effect through the cost of capital. Thus, the credit channel is an enhancement mechanism that amplifies conventional channels of monetary transmission (Bernanke and Gertler, 1995).
Credit channel effects have been widely incorporated into general equilibrium models through costly state verification to enhance the empirical relevance of these models (Bernanke et al., 1999). A key result from these models is that the strength of monetary transmission increases with the level of financial frictions. In particular, in financial systems where financial frictions such as the cost of monitoring (state verification cost) are more pronounced, monetary policy has a larger impact on output. Cross country empirical tests of this result, however, are scarce.
In this paper, we investigate the cross-country relationship between financial market frictions and the strength of monetary policy transmission (hereafter MTS). Using cross-country data is preferable to comparing MTS within a specific country at different time periods. The reason is that financial frictions are relatively stable over time, especially compared to monetary policy. One potential issue, however, is that it is difficult to identify monetary policy shocks using the same model specification for countries that are at different stages of development. Nevertheless, we find similar results using various methodologies.
In our baseline model, we use bankruptcy recovery rates, the proportion of a firm’s value creditors can recover from a defaulting firm, as an indicator of financial frictions. This variable provides a close match to the source of financial frictions in costly state verification models. Our paper therefore represents, to the best of our knowledge, a first attempt at using comprehensive cross-country data (including both developing and developed countries) to test the empirical relevance of these models.
We then generate proxies for MTS in each country by obtaining the maximum amplitude of output responses to a one standard deviation monetary policy shock. Impulse responses are obtained from a structural vector autoregressive (SVAR) model, and monetary policy shocks are identified using the strategies of Kim (1999) and Hoffman (2007) for G-8 and non-G-8 countries, respectively. For most of the countries, the impulse responses do not show any evidence of the price and liquidity puzzles (the increase in prices and money aggregates following an increase in interest rates), providing some validation for our approach.
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Financial Frictions and Monetary Transmission Strength: A Cross-Country Analysis
