rates as well as the exchange rate

rates as well as the exchange rate and the relevant monetary stock contemporaneously, but not real
output and the price level. Thus the monetary policy rate R is taken to be contemporaneously
unaffected by Y and P. As in Sims and Zha (1998), the exchange rate is potentially contemporaneously
affected by all the other variables.
2.3. Exploring channels of transmission
Finally, though our ultimate concern is with the effectiveness of monetary transmission in
developing countries, as indicated in the last section our priors on this issue are based on the view that
several conventional transmission channels are likely to be inoperative in such countries, and that
there are reasons to suspect that the channel that is most likely to be operative – the bank lending
channel – may be weak and/or unstable. Several of the papers that we will review in the next five
sections explicitly investigate the strength of particular transmission channels. Before moving to the
evidence, therefore, it is worth pausing to consider how this is done.
There are essentially two approaches, both of which require the inclusion in the VAR of a variable
(or variables) intended to serve as an indicator of a specific channel of transmission. Consider, for
example, the bank lending channel. To assess the role of this channel, the stock of bank credit and/or
the bank lending rate would be included among the endogenous variables in the VAR. Assuming that
monetary policy shocks are found to have significant effects on aggregate demand (as revealed by
statistically significant values of the IRFs for real output and/or the price level), the contribution of the
bank lending channel to this outcome can be assessed as follows:
i. The first approach determines whether the monetary policy shock has a statistically significant
effect (as reflected in the IRF) on the lending rate or the stock of bank credit in the direction
predicted by theory (i.e., a monetary contraction should produce a contraction in bank credit and/or
an increase in the lending rate). An affirmative answer suggests a statistically well-defined role for
the bank lending channel, but does not indicate the quantitative strength of that channel.
ii. To assess the latter, Ramey (1993) suggested a simulation approach, based on a comparison of
impulse response functions of the aggregate demand indicator (output or prices) to a monetary
policy shock when the bank lending variable is permitted to respond endogenously to the shock and
when it is treated as an exogenous variable. The difference between the two IRFs provides a
measure of the quantitative strength of the bank lending channel.
2.4. Benchmark results in non-LIC economies
What should we expect in the application of the VAR methodology to low-income countries? One
way to answer this question is by using results from advanced and emerging economies as a
benchmark. Conclusions about monetary policy effects in such economies drawn from VARs have
primarily been based on the signs, magnitudes, and statistical significance of impulse response
functions. The relevant literature has at times produced counterintuitive results (e.g., the early
‘‘liquidity puzzle’’ and the occasional finding of a ‘‘price puzzle’’).10 However, the key point is that,
even under a variety of identification schemes, this literature has tended to yield IRFs that are in
accordance with theoretical predictions and that have been estimated with sufficient precision for a
broad consensus to emerge about the dynamic effects of monetary policy shocks on a large set of
macroeconomic variables.
As an illustration, Kim (1999) examines monetary policy effects in the G-7 countries individually,
using a common structural identification scheme. He concludes:
In response to money supply shocks, initially, the interest rates rise significantly and monetary
aggregates fall significantly. The price levels decline smoothly and significantly at least at some