A New Keynesian Dynamic Stochastic General Equilibrium (DSGE) model with habit persistence used to examine the US slowdown is also used to analyze the contribution of basic demand and supply shocks to the Indian slowdown. Kalman filter-based maximum likelihood estimation is undertaken with Indian output, inflation and interest rate data. First, our model based output gap tracks the statistical Hodrick–Prescott filter-based output gap well. Second, comparison of estimated parameters, impulse responses and forecast error variance decomposition between India and the US brings out the differences in policy responses, the structure of the two economies and their inflationary processes. There is a higher impact of interest rate shocks on output and inflation, and lower impact of technology shocks on output but higher on inflation in comparison to US. The former indicates monetary policy over-reaction and the latter validates a supply curve that technology shocks shift and inadequate adjustment of actual to potential output. Habit persistence is higher, markup and interest rate shocks are more volatile in India. Markup shocks play a much larger role in determination of Indian inflation again pointing to the importance of supply side factors. Third, smoothed states obtained from the Kalman filter to create counterfactual paths of output and inflation (during 2009:Q4 to 2013:Q2) in the presence of a given shock, show monetary shocks imposed significant output cost. The output gap was negative post the 2011 slowdown and in 2016.