تجزیه و تحلیل اثرات متغیرهای اقتصادی بر قیمت سیمان و پیش‌بینی روند قیمتی آن

نوع مقاله : مقاله پژوهشی

نویسندگان

1 استادیار موسسه مطالعات و پژوهش‌های بازرگانی

2 دکتری اقتصاد و پژوهشگر موسسه مطالعات و پژوهش های بازرگانی

3 دانشیار موسسه مطالعات و پژوهش‌های بازرگانی

چکیده

هدف مطالعه حاضر، شناسایی متغیرهای اثرگذار بر قیمت سیمان و ارائه پیش‌بینی­های درون و برون­ نمونه ­ای با استفاده از داده ­های ماهانه 1401:12-1398:1 و مدل خودرگرسیون برداری (VAR) است. در همین راستا، طبق نتایج آزمون هم ­انباشتگی یوهانسون- جوسیلیوس، وجود رابطه بلندمدت بین متغیرها تأیید شد. سپس روابط بلندمدت و کوتاه­مدت (VECM) برآورد و ضریب جمله تصحیح خطا برابر 0858/0- تخمین زده شد. در مرحله بعدی، بر اساس نتایج توابع واکنش آنی، شوک­های نرخ ارز و شاخص قیمت نهاده­ های ساختمانی (به­ترتیب با تأثیر مثبت 8 و 8/6 درصدی به شکل استاندارد)، بیش از سایر متغیرها بر نوسانات قیمت سیمان مؤثر بوده­اند. نتایج تجزیه واریانس نیز نشان داد که متغیرهای شاخص قیمت نهاده ­های ساختمانی، هزینه انرژی و نرخ ارز، در توضیح قیمت سیمان مؤثر هستند. در نهایت، دو پیش­بینی درون و برون نمونه­ای برآورد شد که مطابق نتایج معیارهای ارزیابی پیش­بینی، مدل تحقیق توانسته پیش‌بینی‌هایی خوبی را از روند قیمتی سیمان ارائه دهد.

کلیدواژه‌ها

عنوان مقاله [English]

Analysis of the Effects of Economic Variables on the Price of Cement and Forecasting its Price Trend

نویسندگان [English]

  • Seyed Saleh Akbar Mousavi 1
  • Tayyebeh Rahnemoon Piruj 2
  • Mansour Asgari 3
1 Assistant Professor at Institute for Trade Studies and Research
2 PhD in Economics and researcher at Institute for Trade Studies and Research
3 Associate Professor at Institute for Trade Studies and Research
چکیده [English]

The present study aims to identify the variables affecting the price of cement and provide in- and out-of-sample forecasts using monthly data from 2019:03 to 2023:02 and a vector autoregression (VAR) model. In this regard, according to the results of the Johansen-Juselius cointegration test, the long-term relationship between the variables was confirmed. Then, the long-term and short-term models were estimated, and the error correction coefficient was -0.0858. In the next stage, based on the results of impulse response functions, exchange rate and construction input price index shocks (respectively with a positive effect of 8 and 6.8 percent in the standard form) have been more effective than other model variables on the fluctuations of cement price. The results of variance decomposition also showed that the construction input price index, energy cost, and exchange rate are important in explaining the price of cement. Finally, we estimated in-sample and out-of-sample forecasts. Based on the forecast evaluation criteria, our founding research model can accurately predict the price trend of cement.

کلیدواژه‌ها [English]

  • Price Forecasting
  • Cement
  • VAR Model

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