Forecasting Inflation: A Combination Approach

IF 2.5 3区 经济学 Q2 ECONOMICS Inzinerine Ekonomika-Engineering Economics Pub Date : 2020-04-30 DOI:10.5755/j01.ee.31.2.24609
Martin M. Bojaj, Gordana Djurovic
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引用次数: 4

Abstract

The objective of this paper is to investigate and forecast the determinants of Montenegrin inflation empirically, using forecast combination methods, from January 2006 to December 2016, and out-of-sample 12-month horizon forecasting from January 2017 to December 2017. The main research problem is that given the struggle policymakers have had to define proper criteria to diagnose the onset of inflation indicators, we felt compelled to identify an approach and methodology that the government of Montenegro can use in the threshold to accessing the European Union. We examine three individual-predictor SVAR models to forecast inflation.  Model 1 examines the internal determinants of inflation. Model 2 relates to demand-pull and cost-push variables. Model 3 examines external determinants. Combining the above three forecasts, we disclose two more RMSEs: equal and inverse MSE weights. Model 1 predicts inflation at 1.3%, the inverse MSE at 1.5%, and the weighted average at 1.4%. They show forecasting performances that are sustainable and average inflation not more than 1.5% above the rate of the three best performing Member states: Cyprus (0.2%), Ireland (0.3%), and Finland (0.8%) over the 12 months covering April 2017-March 2018. Our findings allow the policymakers to understand the factors involved in identifying the onset of inflation dynamics and inflation expectations in Montenegro better and develop more effective government regulations that can be employed nationally. In so doing, this research advances and recommends the toolset needed, combining forecasts, to combat the concerns of many macroprudential policymakers in Montenegro, especially the Central Bank of Montenegro.
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预测通货膨胀:一种综合方法
本文的目的是利用预测组合方法,从2006年1月至2016年12月,以及2017年1月至2017年12月的样本外12个月水平预测,对黑山通货膨胀的决定因素进行实证研究和预测。主要的研究问题是,考虑到政策制定者不得不定义适当的标准来诊断通货膨胀指标的开始,我们感到有必要确定黑山政府可以在进入欧盟门槛时使用的方法和方法。我们检验了三个个体预测变量SVAR模型来预测通货膨胀。模型1考察了通货膨胀的内部决定因素。模型2涉及需求拉动和成本推动变量。模型3检验外部决定因素。结合上述三种预测,我们揭示了另外两种均方根误差:相等和相反的均方根误差权重。模型1预测通货膨胀率为1.3%,逆MSE为1.5%,加权平均值为1.4%。在2017年4月至2018年3月的12个月里,它们的预测表现是可持续的,平均通货膨胀率不超过三个表现最好的成员国的1.5%:塞浦路斯(0.2%)、爱尔兰(0.3%)和芬兰(0.8%)。我们的研究结果使政策制定者能够更好地了解确定黑山通胀动态和通胀预期开始的因素,并制定可在全国范围内采用的更有效的政府法规。在此过程中,本研究推进并建议了所需的工具集,结合预测,以解决黑山许多宏观审慎政策制定者,特别是黑山中央银行的担忧。
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
CiteScore
5.20
自引率
3.60%
发文量
32
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