The full-text may be used and/or reproduced, and given to third parties in any format or medium, without prior permission or charge, for personal research or study, educational, or not-for-pro t purposes provided that:• a full bibliographic reference is made to the original source • a link is made to the metadata record in DRO • the full-text is not changed in any way The full-text must not be sold in any format or medium without the formal permission of the copyright holders.Please consult the full DRO policy for further details. AbstractIn this paper, we develop a small open economy New Keynesian DSGE model to understand the relative importance of two key technology shocks, Hicks neutral total factor productivity (TFP) shock and investment specific technology (IST) shock for an emerging market economy like India. In addition to these two shocks, our model includes three demand side shocks such as fiscal spending, home interest rate, and foreign interest rate. Using a Bayesian approach, we estimate our DSGE model with Indian annual data for key macroeconomic variables over the period of 1971-2010, and for sub-samples of pre-liberalization (1971-1990) and post-liberalization (1991-2010) periods. Our study reveals three main results. First, output correlates positively with TFP, but negatively with IST. Second, TFP and IST shocks are the first and the second most important contributors to aggregate fluctuations in India. In contrast, the demand side disturbances play a limited role. Third, although TFP plays a major role in determining aggregate fluctuations, its importance vis-à-vis IST has declined during the post liberalization era. We find that structural shifts of nominal friction and relative home bias for consumption to investment in the post-liberalization period can account for the rising importance of the IST shocks in India.

A New Keynesian monetary business cycle model is constructed to study why monetary transmission in India is weak. Our models feature banking and financial sector frictions as well as an informal sector. The predominant channel of monetary transmission is a credit channel. Our main finding is that base money shocks have a larger and more persistent effect on output than an interest rate shock, as in the data. The presence of an informal sector hinders monetary transmission. Contrary to the consensus view, financial repression in the form of a statutory liquidity ratio and administered interest rates, does not weaken monetary transmission. .in 2. Both Mishra, Montiel, and Sengupta (2016) and Mohanty and Rishabh (2016) provide recent surveys of monetary transmission in India and emerging market and developing economies (EMDEs), respectively. See also Das (2015).

How does volatility of inflation differ across the economies? Addressing this research question, the article undertakes an empirical exercise on monthly consumer price inflation over the sample period of M01, 1958 to M02, 2016 for 41 countries using the generalized autoregressive conditional heteroscedasticity (GARCH) (1, 1) model. The country-level analysis shows a modest difference of conditional volatility of inflation between the advanced and developing economies. However, this difference increases after controlling the country-specific traits by fixed effect panel estimation using generalized methods of moments on the estimated GARCH series. It is observed that, in the long run, the conditional variability of inflation is nearly three and half times greater in developing countries compared to advanced countries. JEL Classification: E10, E30, E31

The widespread impacts of global financial crisis (2008-09) reinstate the need for better assessment of the macro-financial linkages for forecasting and policy evaluation. Our paper contributes to the relevant literature with evidence from the Indian financial sector. Following Castelnuovo (2013), a New Keynesian model with macro-financial linkages is estimated by the Bayesian technique for the sample period 2004: Q3 to 2019: Q1. We find that, in an Emerging Market Economy like India, business cycle leads financial cycle through the channel of expectations. Further, our results show that the linkages are heterogeneous in size depending on the financial market segment and market-specific shocks. JEL Codes: C11, E44, G10

Do the different types of financial friction have differential implications for monetary transmission in emerging economies? We investigate this question using India as the country for analysis. We adopt a New Keynesian business cycle model with bank intermediation, extend it by the Indian economy-specific features and validate with the data. The baseline model explains the co-movements of interest rates, incomplete pass-through and sluggish adjustment mechanism of the macro-financial variables for a policy interest rate shock. It identifies the collateral-constrained, financially excluded households and low proportion of savers as the primary sources of frictions causing weak monetary transmission.