Nasrin Rezaee-Moghaddam; Mahdi Mostafavi; Ali Cheshmi
Abstract
Sustaining long-term price stability, even when the central bank does not adopt an explicit inflation targeting policy, is known as the primary objective of monetary policy. Moreover, due to the lags of monetary policy, choosing appropriate measure of inflation is very important. Thus, in many countries, ...
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Sustaining long-term price stability, even when the central bank does not adopt an explicit inflation targeting policy, is known as the primary objective of monetary policy. Moreover, due to the lags of monetary policy, choosing appropriate measure of inflation is very important. Thus, in many countries, core inflation is widely calculated as an indicator that clarifies long-term trend of inflation and it is used to predict inflation and also to have an inflation target. The concept of core inflation and its efficiency in identifying long-term inflation trend can help policy-makers to have a better understanding of inflation components. Inflation in Iran has been influenced by many internal and external shocks. In this study, core inflation in Iran is estimated by using the Kalman filter in the context of structural time series during the period of 1974-2011. Based on the result, core inflation is affected by long-run effects of variables such as monetary base and liquidity and it has fluctuations like the measured inflation and the value of core inflation on average in the period under study is 15 percent.
Hamid Amadeh; Nader Mehregan; Mahmood Haghani; Meisam Hadad
Volume 13, Issue 51 , January 2014, , Pages 53-80
Abstract
The correct estimation of gas oil demand function in agriculture industry and calculation of price and income elasticities is important to adopt the price and income policies. Therefore, in the present study the price and income elasticity of gas oil demand were estimated applying non-observable ...
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The correct estimation of gas oil demand function in agriculture industry and calculation of price and income elasticities is important to adopt the price and income policies. Therefore, in the present study the price and income elasticity of gas oil demand were estimated applying non-observable component to the process and creation of a state-space pattern and using maximum likelihood method and the Kalman Filter algorithm. In order to compare the obtained coefficients, ARDL, ECM and FMOLS methods were used. In addition, the data used in this research are collected for the period between 1974 and 2010. The results indicate that the estimated process is random and nonlinear, and its modality is Local Level Model. According to the estimated demand function, the estimated price elasticity of gas oil demand in the short and long term are -0.09 and -0.13, respectively. Also, in the short and long term, the income elasticity is 0.4 and 0.57, respectively. In addition, the coefficient of tractor number in each acre of the area under cultivation, which shows the sensitivity of gas oil demand to equipment and agricultural machines changes, is obtained to be 0.34.
