"Regime Switching Monetary and Fiscal Policy Rules and Their Interaction: An Indian Case Study", Empirical Economics, July 2017
Link: http://rdcu.be/t0OO
Summary: The recession following the sub-prime crisis has rekindled international interest in the field of monetary and fiscal policy interaction. However, very little has been done to appropriately estimate these dynamic policies. This paper estimates regime switching monetary and fiscal policy rules and lays strong emphasis on mis-specification testing. We apply a Markov regime switching model to estimate monetary and fiscal policy rules for India to highlight the evolving stance of Indian macro-policy for the period 1951-2008; and investigate the behaviour of select macroeconomic variables under the estimated policy regimes. Our results suggest that, in India, fiscal policy was largely active for the entire period except for a few periods of restraint. Monetary policy, despite achieving greater autonomy post 1990s, has largely been accommodating fiscal policy. Whenever monetary policy became active, fiscal policy undermined monetary policy’s effectiveness by not accommodating accordingly. We argue for an aggressive monetary policy and a constrained fiscal policy in India.
"Monetary versus Fiscal Policy in India: An SVAR Analysis", Macroeconomics and Finance in Emerging Market Economies, March 2017
Link: http://www.tandfonline.com/doi/abs/10.1080/17520843.2017.1297325?journalCode=reme20
Summary: Conventionally, the policy makers relied on three policy alternatives to manage business cycles - debt financed government spending, debt financed tax rebate and interest rate. While the first two are fiscal policy instruments, the latter is a monetary policy instrument. This chapter aims to capture interactions among Indian monetary and fiscal policy actions, and the impact of such policy actions on select macro-economic variables for the period 1990Q1-2011Q4.The policy actions are identified using the sign restrictions approach combined with magnitude restrictions in an SVAR framework, and interpreted using impulse responses and variance decomposition.The results show that Indian monetary policy responds to tax rebate shocks and spending shocks differently. In the case of a tax rebate shock, Indian monetary policy responds by reducing interest rates thereby accommodating fiscal expansion. On the opposite, monetary policy seems not to accommodate expenditure shocks. Interestingly, the monetary policy shock is accompanied by a fiscal expansion that threatens the credibility of the central bank actions, thus indicating fiscal policy dominance. A comparison of the efficacy of the policies suggests that interest rate is more effective in stimulating output. Out of the two fiscal policy instruments analyzed, the tax rebate seems to be the better option for stimulating output considering the output-debt trade-off.
"Estimating the Indian Natural Interest Rate and Evaluating Policy" with Prof. Ashima Goyal, Economic Modelling, November 2016
Link: http://www.sciencedirect.com/science/article/pii/S0264999316301468
Summary: We estimate unobserved Indian time-varying natural interest rate (NIR), potential output, and trend growth using the Kalman filter. Semi-structural New Keynesian estimates of aggregate demand and supply with adaptive expectations provide inputs in the process. Sensitivity analysis confirms the Indian aggregate demand to be elastic and aggregate supply flat but subject to frequent shocks. The NIR is extracted from a model where optimization seeks to maintain subsistence consumption. Food price shocks reduce subsistence consumption and raise the willingness to work to protect it, reducing the NIR, but to the extent they raise inflation NIR rises. This dual role reflects transition in an economy that has a high growth potential if it can overcome structural bottlenecks. Since food price shocks are volatile, they raise the estimated volatility of all three unobserved variables, but improve precision of NIR estimation, better capture turning points that require a changed policy stance, and explain volatility of trend growth in emerging markets. Monetary policy was broadly contractionary and procyclical for the period under study. Using food inflation and its impact on NIR could improve policy decisions.
"Inferring India's Potential Growth and Policy Stance" with Prof. Ashima Goyal, Journal of Quantitative Economics, January-July 2013
Link: http://www.jqe.co.in/journals/jqe_v11_60-83_ashima_goyal.pdf
Summary: We propose an alternative method to infer potential growth, and use it to derive the Indian monetary policy stance based on estimated linear and Markov switching policy rules. We define growth to reach potential if a second round pass through of supply shocks to inflation occurs. Growth reached potential only in 2007-08 when growth exceeded 9 percent. Conventional measures of potential growth support the conclusions. Estimates with a two-variable Vector Auto Regression show multiple supply shocks, not second round effects, largely explain inflation. A one percent underestimate of potential output leads to a 25 basis point rise in policy rates.
"The Indian Exchange Rate and Central Bank Action: An EGARCH Analysis" with Prof. Ashima Goyal, Journal of Asian Economics, February 2012
Link: http://www.sciencedirect.com/science/article/pii/S1049007811000868
Summary: We analyze the impact of conventional monetary policy measures such as interest rates, intervention, and other quantitative measures, on exchange rate level and volatility, and compare these to the impact of Central Bank communication using dummy variables in the best of a family of GARCH models estimated with daily and monthly Indian data. Since India has a managed float, we also test if the measures affect the level of the exchange rate. We find variations in the Euro/Dollar rate strongly affect the Rupee/Dollar level and volatility. The interest rate differential has strong perverse effects, tending to increase variance and depreciate the Indian currency. News decreases volatility as it adds to scarce information. Domestic policy variables affect both level and volatility, and persist at the monthly frequency, but sometimes work at cross-purposes. Communication channels have potential but were not used effectively.