Hawk or dove: Switching regression model for the monetary policy reaction function in China

2016 ◽  
Vol 36 ◽  
pp. 94-111 ◽  
Author(s):  
Chung-Hua Shen ◽  
Kun-Li Lin ◽  
Na Guo
2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Irfan Ahmad Shah ◽  
Srikanta Kundu

Abstract This paper analyzes the reaction function of monetary authority in India from 1997Q 1 to 2019Q 4 using nonlinear Taylor rule. It has been found that monetary policy reaction function (MPRF) in India is asymmetric and is influenced by the state of the economy, determined by the lagged interest rate. To capture such asymmetry, we have used a set of nonlinear models including smooth transition regression (STR) model, threshold regression (TR) model and Markov-switching regression (MSR) model along with the instrumental variable estimation technique. The analysis discloses that the behaviour of the Reserve Bank of India (RBI) is asymmetric, reacts aggressively to output gap in general and particularly during periods of high interest rate. Furthermore, the RBI reacts more to inflation and output gap during low volatile regimes in MSR models compared to high volatile regimes. We also found that there is a high degree of inertia in the policy rates of the RBI. The study concludes that nonlinear models may not only help in understanding the behaviour of the RBI but also prevent from making incorrect and misleading conclusions in Indian context.


1991 ◽  
Vol 30 (4II) ◽  
pp. 931-941
Author(s):  
M. Aynul Hasan ◽  
Qazi Masood Ahmed

Monetary policy, in general, refers to those steps taken by the Central Bank to achieve such broader objectives of the economy as growth, employment, external balance and price stability through changes in the money supply, interest rates and credit policies. The money supply thus created by the Central Bank should be in response to the changes in key macroeconomic target variables such as GNP, balance of payments, inflation, internal debt and unemployment. Indeed, a properly estimated monetary policy reaction function can provide useful information regarding such matters as to whether the Central Bank, in fact, has been systematically accommodating to the changes in the target variables. The reaction function can also provide insight into the question as to what should be the relevant indicators of the monetary policy. In addition, as argued by Havrilesky (1967), it may also play a crucial role in the formulation of long-term monetary policy strategy. The other important consideration in the development of a monetary policy reaction function pertains to the endogeneity of the monetary policy. As pointed out by Goldfeld and Blinder (1972), if a policy variable responds to the lagged (or expected) target values, then considering such a policy variable as exogenous would not only introduce the problem of misspecification but will also produce serious biases in the parameters estimated from those models. In particular, if the monetary policy variable happens to be strongly influenced by target variables, then the standard result of the relative effectiveness of the monetary policy vis-a-vis fiscal policy can be questionable on the grounds of reverse causation problem.


2019 ◽  
pp. 1-30
Author(s):  
SAMIA NASREEN ◽  
SOFIA ANWAR

This study empirically investigates a monetary policy reaction function for South Asian economies by incorporating financial stability as an additional policy objective in the central bank’s loss function. Empirical results are estimated by applying auto-regressive distributed lag (ARDL) approach to cointegration and vector autoregressive (VAR) approach using time-series data of five South Asian countries, namely, Pakistan, India, Bangladesh, Nepal and Sri Lanka. Estimated results indicate that monetary policy significantly reacts to the level of financial stability in all countries. The result further suggests that central banks would tighten monetary policy if output gap widens and exchange rate depreciate. In addition, central banks of Pakistan and India do not respond significantly to inflation gap.


2011 ◽  
Vol 7 (9) ◽  
Author(s):  
Muhammad Saim Hashmi ◽  
Changsheng Xu ◽  
Muhammad Mahroof Khan ◽  
Mohsin Bashir ◽  
Faheem Ghazanfar

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