Estimating Production Gap and NAIRU in Iran's Economy by Using State-Space Model

Q4 Economics, Econometrics and Finance
Masoud Kiumarthi, M. Salimifar, H. Abrishami, M. Shadmehri
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Abstract

T he purpose of this paper is to estimate the output gap and NAIRU for Iran's economy, both of which are among the most important variables in determining the economic status. Since these variables are unobservable, to estimate them, one needs modern econometric techniques rather than conventional tools. For this reason, this paper uses the Kalman filter tool in the form of a state-space model. Since there are several different specifications for a state-space structure, seven different models are tested by using seasonal data from 1989 to 2014. Results show that only two specifications have suitable estimation results. The first one is a structural model consisting of output and unemployment rate decomposition, plus the relationship between the inflation rate and the output gap in the form of the Phillips curve, and the second is a system that only includes unemployment rate decomposition. The early model can show the periods of inflationary recession between 1992 and 1995, and a severe economic recession during the period of 2010–2013 due to economic sanctions imposed on Iran. The latter model can depict NAIRU gap fluctuations following the inflation fluctuations. In addition to the compatibility of these results with what is observed in reality, the parameters are also statistically significant.
利用国家空间模型估算伊朗经济中的生产差距和NAIRU
本文的目的是估计伊朗经济的产出差距和NAIRU,这两个变量都是决定经济状况的最重要变量之一。由于这些变量是不可观测的,因此要估计它们,需要现代计量技术而不是传统工具。出于这个原因,本文使用卡尔曼滤波器工具的状态空间模型的形式。由于状态空间结构有几种不同的规范,因此使用1989年至2014年的季节性数据对七种不同的模型进行了测试。结果表明,只有两个规范具有合适的估计结果。第一个是由产出和失业率分解组成的结构模型,加上菲利普斯曲线形式的通货膨胀率和产出差距之间的关系,第二个是只包括失业率分解的系统。早期模型可以显示1992年至1995年期间的通货膨胀衰退期,以及2010年至2013年期间由于对伊朗实施经济制裁而出现的严重经济衰退期。后一个模型可以描述通货膨胀波动之后的NAIRU缺口波动。除了这些结果与现实中观察到的结果相一致之外,这些参数也具有统计学意义。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Iranian Economic Review
Iranian Economic Review Economics, Econometrics and Finance-Economics, Econometrics and Finance (all)
CiteScore
0.70
自引率
0.00%
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