An Estimated DSGE Model of the Indian Economy.

corresponding four observables for the Indian economy, covering the period from the first
quarter of 1996 and the last quarter of 2008 and taken from the IFS and RBI database.
The inflation rate is calculated on the Wholesale Price Index (WPI), which includes food,
fuel and manufacturing indices. The interest rate is measured by the 91-day Treasury Bill
rate, in order to capture the combined effect of the RBI policy rates and liquidity changes
brought about by the Bank sterilization interventions (see Bhattacharya et al. (2010)). A
time series for investment is only available at the annual frequency. Thus, we use the inter-
polation techniques suggested by Litterman (1983) to obtain quarterly data based on the
Index of Industrial Production (IIP) for capital goods.⁷ For GDP, data is available from
1996:4 onwards, so we interpolate the first few initial periods from annual data, using the
IIP.

Since the variables in the model are measured as deviations from a constant steady
state, the US GDP and investment are simply de-trended against a linear trend in order to
obtain approximately stationary data. In the case of India, however, a quadratic trend is
required to ensure stationarity.⁸ Real variables are measured in logarithmic deviations from
the respective trends, in percentage points, while inflation and the nominal interest rate
are demeaned and expressed as quarterly rates. The corresponding measurement equation
for the US data and model is (for the remaining models, the structure is similar):

In order to implement Bayesian estimation, it is first necessary to define prior distri-
butions for the parameters. A few structural parameters are kept fixed in the estimation
procedure, in accordance with the usual practice in the literature (see Table 1). This is
done so that the calibrated parameters reflect steady state values of the observed variables.
For the US, we follow Smets and Wouters (2007) in defining the priors for the estimated
parameters and calibrated parameters.⁹ In the case of India, for instance, β is set at 0.9823,
corresponding to an interest rate of 7% (matching its sample mean), while δ = 0.025 is a
common choice for the depreciation rate. In turn, the investment adjustment cost parameter
φX is set at 2.

The choice of priors for the estimated parameters is usually determined by the theoretical

⁷The Bayesian system estimation techniques used in our study can easily handle variables measured with
imprecision, by introducing stochastic measurement errors. Exploratory analysis revealed that measurement
errors are a negligible source of uncertainty in our estimated models and we therefore focus on estimation
results without measurement errors.

⁸ Removing a quadratic trend from the US data or employing the Hodrick-Prescott filter for both countries
delivers time series with similar behaviour and estimation results are qualitatively, and quantitatively, very
close

⁹The prior means for the standard deviation of government spending and markup shocks are re-scaled
based on the differences in model setups.

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