developed economies; iv) capital inflows are subject to dramatic ”sudden stops” (see Agenor
et al. (2000), Aguiar and Gopinath (2007) and Neumeyer and Perri (2005), for example).
By sharing some of these characteristics, India provides a particularly interesting chal-
lenge for macroeconomic modelling. From the early 90s, high growth rates were accom-
panied by a significant wave of trade and financial liberalization, with high-growth and
highly-skilled services and exports sectors co-existing with a sizeable informal, low-skilled
labour intensive sector. Given the stage of development of India’s financial sector, frictions
of this nature, affecting both firms and households, may be greatly exacerbated in adverse
conditions. Such a scenario implies that policymakers, in their quest for price and financial
stability, face extra significant trade-offs when setting monetary conditions in response to
shocks. This, in turn, requires careful investigation of the mechanisms that contribute to
the propagation and amplification of economic and financial shocks hitting the economy.
This study aims to integrate some of these distinct features within a framework that
provides a convenient way of taking the models to the data. First, we introduce a standard
DSGE model with typical New Keynesian frictions, in the form of imperfect competition,
sticky prices and investment adjustment costs. We show how to augment the baseline
model with additional frictions in order to reflect the characteristics of the Indian econ-
omy. In particular, we explore the presence of financial frictions in the form of a financial
accelerator mechanism as in Bernanke et al. (1999) and liquidity constrained consumers.
Moreover, we further develop the model by allowing for the existence of a formal and a
less capital-intensive informal sector, producing distinct goods with different technologies
sold at different prices. This phenomenon is particularly important in emerging economies,
given their high degrees of informal labour and financial services and the implications these
have for the effectiveness of macroeconomic policy (see Batini et al. (2010b) for a recent
survey).
Then, using data on four key macroeconomic variables (output, investment, inflation
and interest rates), we first explore the differences in business cycle dynamics between
a developed economy (the US) and India, as captured by the baseline New Keynesian
DSGE model. We subsequently investigate the empirical success of the competing models
in explaining the main stylized facts of the Indian business cycle. We do so by employing
Bayesian system estimation techniques, in the vein of Smets and Wouters (2003), Smets
and Wouters (2007) and Fernandez-Villaverde and Rubio-Ramirez (2004) (for a survey, see
Fernandez-Villaverde, 2009). To our knowledge, this is the first study that estimates a
model with a formal-informal sectors distinction.
We take a Bayesian approach for several reasons. First, these procedures, unlike full
information maximum likelihood, for example, allow us to use prior information to iden-
tify key structural parameters. In addition, the Bayesian methods employed here utilize
all the cross-equation restrictions implied by the general equilibrium set-up, which makes
estimation more efficient when compared to the partial equilibrium approaches. More-
over, Bayesian estimation and model comparison are consistent even when the models are