International Trade Price Index: A Leading Indicator for Indonesia's Inflation?

W. Kurniawan, K. Kadir
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Abstract

As one of essential indicators in economy, inflation rate can be determined by several factors. One of these factors is price index other than CPI, representing price change, other at consumer level. Many studies have examined the effect of price indices such as Producer Price Index (PPI) and Wholesale Price Index (WPI) on inflation, including in Indonesia. However, in an open economy, the level of openness, which can be approximated by International Trade Price Index (IHPI), may also influence changes in inflation. In Indonesia, no studies still examine the nexus between ITPI and inflationThis study aims to examine the effect of price indices variables other than at consumer level, particularly ITPI, on inflation and whether we can use it as one of the leading indicators of inflation in Indonesia. The analysis results of the ARDL-ECM model show that all price indices variables simultaneously influence inflation. However, the effect of each variable partially on inflation in the short and long run varies. The speed of adjustment to return to equilibrium is 4.67% per month after the shock happened. Nevertheless, the effect of ITPI on inflation is insignificant, both in the short and long run. Thus, we can conclude that ITPI is not yet able to be a leading indicator of inflation in Indonesia. However, the result of this study must be carefully concluded since the use of time series analysis depends on the lag length and the number of observations included.
国际贸易价格指数:印尼通胀的领先指标?
通货膨胀率作为经济的重要指标之一,可以由几个因素决定。其中一个因素是CPI以外的价格指数,代表消费者层面的价格变化。许多研究考察了生产者价格指数(PPI)和批发价格指数(WPI)等价格指数对通货膨胀的影响,包括在印度尼西亚。然而,在开放的经济中,可以用国际贸易价格指数(IHPI)来近似的开放程度也可能影响通货膨胀的变化。在印度尼西亚,目前还没有研究ITPI和通货膨胀之间的关系。这项研究旨在研究消费者层面以外的价格指数变量,特别是ITPI对通货膨胀的影响,以及我们是否可以将其作为印度尼西亚通货膨胀的主要指标之一。ARDL-ECM模型的分析结果表明,所有价格指数变量都同时影响通货膨胀。然而,从短期和长期来看,每个变量对通货膨胀的影响各不相同。冲击发生后,恢复平衡的调整速度为每月4.67%。然而,从短期和长期来看,ITPI对通货膨胀的影响都是微不足道的。因此,我们可以得出结论,ITPI还不能成为印度尼西亚通货膨胀的主要指标。然而,必须仔细总结这项研究的结果,因为时间序列分析的使用取决于滞后长度和包括的观测值的数量。
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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24 weeks
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