for liability dollarization and liquidity-constrained households, which further amplify the
effects of financial stress. In Batini et al. (2010a) they then focus on monetary policy
analysis, calibrating (but not estimating as in this paper) the model using data for India
and the US economy.
Many emerging economies conduct their monetary and fiscal policy according to the
‘three pillars macroeconomic policy framework’: a combination of a freely floating exchange
rate, an explicit target for inflation over the medium run, and a mechanism that ensures a
stable government debt-GDP ratio around a specified long run, but may allow for counter-
cyclical adjustments of the fiscal deficit over the business cycle. By contrast, the currency
monetary policy stance of the Indian Reserve Bank intervenes in the foreign exchange
market to prevent what it regards as excessive volatility of the exchange rate. On the
fiscal side, Central Government has a rigid fiscal deficit target of 3% of GDP irrespective
of whether the economy is in boom or recession, see Shah (2008). The framework adopted
in the papers cited allow one to contrast these implied policy prescriptions for interest rate
rules.
There is now a growing literature that compares alternative monetary policy regimes in
their ability to stabilize emerging economies when faced with shocks and financial frictions.
Some papers close to ours include Gertler et al. (2003), Cespedes et al. (2004), Cook (2004),
Devereux et al. (2006) and Curdia (2008). All these papers confirm the result in Batini et al.
(2010a) and in their other cited papers that flexible exchange rate regimes outperform a
peg. Only Curdia (2008) compares these regimes with the optimal policy, but circumscribed
to a deterministic exercise in which optimal policy is designed following a sudden stop. By
contrast the rules examined in the Batini et al papers are optimal or, the case of simple
rules optimized within the category or rule in anticipation of a range of future stochastic
shocks. An important feature of their work is the introduction of a zero lower bound into
the construction of policy rules.
Finally, future modelling developments will combine these open economy features with
the introduction of a large informal sector as in this paper. We will then estimate the
model by Bayesian-Maximum-Likelihood methods.15 In doing so we will confront the data
limitations associated especially with the informal and partly hidden economy by adopting
a consistent partial information assumption for the econometrician and private sector alike,
as in Justiniano et al. (2008).
References
Adolfson, M., Laseen, S., Linde, J., and Villani, M. (2008). Evaluating an estimated new
Keynesian small open economy model. Journal of Economic Dynamics and Control,
15Anand et al. (2010) estimate and open economy model with many of the features in Batini et al. (2010a),
but with no informal economy. Their results suggest support for the existence of a financial accelerator and
liability dollarization.
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