1 Introduction
In this chapter, we study the business cycle dynamics of the Indian economy through the
lenses of the New Keynesian DGSE framework, both from a theoretical and an empirical
perspective. We develop a closed-economy DSGE model of the Indian economy and esti-
mate it by Bayesian Maximum Likelihood methods using Dynare. We build up in stages
to a model with a number of features important for emerging economies in general and the
Indian economy in particular: a large proportion of credit-constrained consumers, a finan-
cial accelerator facing domestic firms seeking to finance their investment and an informal
sector. The simulation properties of the estimated model are then examined under a gener-
alized inflation targeting Taylor-type interest rate rule with forward and backward-looking
components.
Understanding business cycle fluctuations is at the core of macroeconomics research.
The need for models that capture the main features of economic activity and help assessing
the role of economic policies has been recognized since the Keynesian tradition of the 50s
and 60s. Though the Lucas critique has exposed some of the early flaws of macroeconomic
modelling in the 70s, recent developments in the macro literature have led to a breed of
dynamic stochastic general equilibrium (DGSE) models that are micro-founded, display
consistent expectations-formation mechanisms, can be readily estimated and are therefore
appropriate to explain business cycle dynamics from a structural perspective.
The use of DSGE models to analyze business cycles was championed by Kydland and
Prescott (1982), who found that a real business cycle (RBC) model with exogenous tech-
nology shocks helps explaining a significant portion of the fluctuations in the US economy.
Much of the research in this area has, since then, attempted to uncover and understand
other potential sources of business cycle fluctuations. This led to several extensions to the
basic Kydland-Prescott RBC model, both in the form of additional, different shocks and
nominal frictions, the latter introducing a (new) Keynesian flavour to the RBC approach.1
Indeed, there is a substantial body of literature devoted to understanding business cycle
dynamics in developed economies, where DSGE models have been found to provide good
empirical fit and forecasting performance (see Christiano et al. (2005), Smets and Wouters
(2003) and Smets and Wouters (2007), among others). However, research focusing on
emerging economies is relatively sparser. Data limitations have often been identified as a
cause, but the real challenge is to provide sensible explanations for the markedly distinct
observed fluctuations in these economies.
In fact, some stylized facts may be pointed out: i) output growth tends to be subject
to larger swings in developing countries; ii) private consumption, relative to income, is
substantially more volatile; iii) terms of trade and output are strongly positively correlated,
while real interest rates and output/net exports display large countercyclicality relative to
1Thus Christiano and Eichenbaum (1992) add demand shocks to the standard RBC model, Carlstrom
and Fuerst (1997) and Bernanke et al. (1999) allow for financial frictions, while Christiano et al. (2005)
include nominal rigidities, just to name a few contributions.