2015
DOI: 10.1108/ijoem-09-2013-0145
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Inflation, its volatility and the inflation-growth tradeoff in India

Abstract: This paper amends the New Keynesian Phillips curve model to include inflation volatility. It provides results on the determinants of inflation volatility and expected inflation volatility for OLS and ARDL (1,1) models and for change in inflation volatility and change in expected inflation volatility using ECM models. Output gap affects change in expected inflation volatility alone (in the ECM model) and not in the other models. Major determinants of inflation volatility and expected inflation volatility are id… Show more

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Cited by 7 publications
(7 citation statements)
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“…This makes the error correction modeling approach a more suitable method for this study. This is because there may be delays in the relationship between the explanatory variables and the dependent variable for which reason the system may take some time to adjust ( Jha and Kulkarni, 2015). This study employs the Johansen (1991Johansen ( , 1995 cointegration procedure in the estimation of the symmetric and asymmetric models in order to produce both short-and long-run parameters as well as the speed of adjustment to equilibrium.…”
Section: Empirical Model Specification and Analytical Frameworkmentioning
confidence: 99%
See 1 more Smart Citation
“…This makes the error correction modeling approach a more suitable method for this study. This is because there may be delays in the relationship between the explanatory variables and the dependent variable for which reason the system may take some time to adjust ( Jha and Kulkarni, 2015). This study employs the Johansen (1991Johansen ( , 1995 cointegration procedure in the estimation of the symmetric and asymmetric models in order to produce both short-and long-run parameters as well as the speed of adjustment to equilibrium.…”
Section: Empirical Model Specification and Analytical Frameworkmentioning
confidence: 99%
“…The time series properties of the variables are first examined. Accordingly, unit root tests are performed to determine stationarity of series because non-stationary series can lead to spurious regression results ( Jha and Kulkarni, 2015). This is accomplished using the test proposed by Elliot et al (1996) (DF-GLS) and the Ng and Perron (2001) (the M-test) (hereafter NP) as well as the break point unit root test because they possess superior power against persistent alternatives.…”
Section: Empirical Model Specification and Analytical Frameworkmentioning
confidence: 99%
“…It could be estimated precisely by the ordinary least square (OLS) procedure provided all the variables are integrated of same order d and the residuals expressed as linear combination of all the variables are integrated of order less than d (Engle and Granger, 1987). However, if the variables included have unit roots and show co-movements, applying the OLS procedure would result in a spurious regression (Jha and Kulkarni, 2015). It is to be noted that transmission of exchange rate changes into the price level of an economy involves both the short-run (immediate) and long-run (accumulated) dynamics and that other variables too may show some lagged relationship with the dependent variable (Jha and Kulkarni, 2015).…”
Section: Analytical Framework Data and Econometric Methodologymentioning
confidence: 99%
“…However, if the variables included have unit roots and show co-movements, applying the OLS procedure would result in a spurious regression (Jha and Kulkarni, 2015). It is to be noted that transmission of exchange rate changes into the price level of an economy involves both the short-run (immediate) and long-run (accumulated) dynamics and that other variables too may show some lagged relationship with the dependent variable (Jha and Kulkarni, 2015). Therefore, some adjustment time may be consumed and it would rather be appropriate to consider an econometric methodology that is accommodative to both the immediate and accumulated responses.…”
Section: Analytical Framework Data and Econometric Methodologymentioning
confidence: 99%
“…To examine aspects of volatility, Kumar (2012) examined the statistical properties of the volatility index of India to predict market volatility. To investigate the behaviour of inflation volatility, Jha and Kulkarni (2015) tested the significance of inflation volatility for India using the amended New Keynesian Phillips Curve (NKPC) model. Investor sentiment is believed to play an important role in market volatility; Sayim and Rahman (2015) found that positive investor sentiments increase Istanbul Stock Exchange returns.…”
Section: Cluster 2: Financial Marketsmentioning
confidence: 99%