Inflation and Inflation Uncertainty in Iran (original) (raw)
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Inflation, Growth and their Uncertainties: A Bivariate GARCH Evidence for Iran
Iranian Economic Review, 2010
sing a bivariate GARCH model, we investigate the causal relationships between inflation, growth, inflation uncertainty (nominal uncertainty) and output uncertainty (real uncertainty) for seasonally adjusted quarterly data in Iran. Our results indicate that increased inflation is associated with higher nominal uncertainty. Further, we found that higher output uncertainty increases both inflation and growth. Increased growth, in turn, is associated with higher real uncertainty. We found no strong evidence in favor of other causal relationships which we have tested. These results support the argument of a price stability objective for the monetary authority. To mitigate the harmful effects of real uncertainty, Iran should take policy measures to withstand adverse domestic and external shocks and lessen their exposure to the volatility.
2015
There are many harmful impacts of inflation and inflation volatility in any economy, which includes increasing the risk premium, costs of hedging, and consequently leads to redistribution of national income between strata of society unfairly. Therefore, this study came to test the relationship between inflation and inflation uncertainty for Jordan from 1976 to 2013. For that purpose we employing two different methodologies generalized autoregressive conditional heteroscedasticity (GARCH) process, and the granger causality technique. The results of the GARCH model support the hypothesis of Friedman and Ball through Indicating strong support for the presence of a positive relationship between the inflation rate and its uncertainty. The Granger causality results report supporting hypothesis of Cukierman and Meltzer in 1986, and also Granger causality test running in the both ways.
Journal of Business Economics and Management, 2013
This paper investigates the relationship between inflation, economic growth and their respective uncertainties in Iran for the period of 1988–2008 by using quarterly data. We employ a Bivariate Generalized Autoregressive Conditional Heteroskedasticity-in-Mean (BGARCH-M) model to examine in a unified empirical framework all the possible interactions between inflation uncertainty and growth in Iran. The model is simultaneously estimated by using the maximum log-likelihood method with the BEKK approach. The main findings of the present study are: (1) Inflation causes inflation uncertainty, supporting the Friedman-Ball hypothesis. (2) Inflation uncertainty affects the level of economic growth, supporting the Friedman (1977) hypothesis. (3) Growth uncertainty does not affect the level of economic growth, supporting the Friedman (1968) hypothesis. (4) And finally our empirical evidence shows that growth uncertainty affects the level of inflation, supporting the Deveraux (1989) hypothesis.
Inflation and Inflation Uncertainty Nexus: Empirical Evidence from Pakistan
2012
This study examines relationship between Inflation and Inflation uncertainty for Pakistan using monthly data over 1957:1-2007:12. ARMA-GARCH model is applied to estimate conditional volatility of inflation. Findings of the study support Friedman-Ball hypothesis for Pakistan as Granger-causality test reveals that inflation affects inflation uncertainty positively. We find no evidence for inflation uncertainty affecting inflation rates as suggested by Cukierman & Meltzer (1986) and only unidirectional relation is evident with causality running from inflation to inflation uncertainty. High volatility persistence for inflation is also confirmed. Results of the study may be useful for policymakers at central bank to devise more efficient monetary policy.
International Journal of Business and Development Studies, 2010
This paper investigates the relationship between inflation and inflation uncertainty for the period of 1990-2009 by using monthly data in the Iranian economy. The results of a two-step procedure such as Granger causality test which uses generated variables from the first stage as regressors in the second stage, suggests a positive relation between the mean and the variance of inflation. However, Pagan (1984) criticizes this two-step procedure for its misspecifications due to the use of generated variables from the first stage as regressors in the second stage. This paper uses the Full Information Maximum Likelihood (FIML) method to address this issue. The estimates we gathered with the new set of specifications suggest that inflation causes inflation uncertainty, supporting the Friedman-Ball hypothesis.
International Journal of Business and Development Studies, 2011
This paper investigates the relationship between inflation and growth uncertainty in Iran for the period of 1988-2008 by using quarterly data. We employ Generalized Autoregressive Conditional Heteroscedasticity in Mean (GARCH-M) model to estimate timevarying conditional residual variance of growth, as a standard measures of growth uncertainty. The empirical evidence shows that growth uncertainty affects the level of inflation. This result is in line with Feizi Yengjeh (2010), supporting Deveraux (1989) hypothesis.