It can also be seen in Tables 6 and 7 that the contributions of the selected shocks
to the forecast error variance of the endogenous variables are broadly similar across the
three models (especially between the models characterizing financial frictions). Perhaps one
noteworthy discrepancy is exhibited by the contributions of the price mark-up shock to the
variations in output implied by the NK model with financial frictions. The estimated model
suggests that this shock has a noticeable effect on output, dominating the productivity
shock.
Overall, the results show that the supply-side shocks account for some of the long-run
variance which is in line with the business cycle literature and identified VAR studies in both
industrialized and developing economies. The disturbances from government expenditures
and the risk premium shock are very important at explaining the dynamics of macro-
variables in the Indian economy. Finally the technological disturbances and price mark-up
shock from the informal sector in India are more noticeable than these shocks affecting the
formal sector. The findings in this analysis are consistent with our estimation results of
2-sector model reported in Table 3. In particular, the properties of all our estimation results
clearly indicate a significant presence of informality in the observed data. In this section
we show that the disturbances in the informal sector have a much greater impact on the
dynamics of the economy, further highlighting the important role of informal sector over
the Indian economy. Moreover, Table 8 shows that the exogenous government spending
shock contributes noticeable fractions of forecast variances of output, interest rate and
investment and the estimated model suggests that a great deal more volatility is being
transmitted persistently by the fiscal side of the Indian economy.
5.5 Posterior Impulse Response Analysis
We now compare the impulse response functions (IRFs) implied by the estimated models, in
order to investigate the importance of each of the shocks to the dynamics of the endogenous
variables. Figures 4 to 8 plot the deterministic mean responses corresponding to a positive
one standard deviation of each shock’s innovation. The IRFs show the quarterly percentage
changes to the relevant variables about the their steady-state values. In the 2-sector model,
we confine the analysis to shocks to productivity, the price mark-up and the risk premium
in the formal sector and output, investment, hours worked, marginal costs refer to that
sector. Inflation refers to CPI inflation. Given our specification of real wage determination
in the formal sector, percentage changes to the real wage are the same in the two sectors.
Before we compare the IRFs in the simple NK model I, the one-sector model II and
two-sector model III both with financial frictions, the differences between the estimated
Taylor rules should be noted. There is a similar degree of interest rate smoothing and
degrees of forward-looking and backward-looking behaviour across all models, but the rules
are far more aggressive in their response to CPI inflation in models II and III. This means
that in comparing the IRFs, we are not making a simple comparison between models with
or without financial frictions and informality.
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