ارزیابی عملکرد شاخص شرایط مالی در پیش‌بینی متغیرهای کلان اقتصادی ایران؛ رهیافت الگوهای پارامتر متغیر زمانی

نوع مقاله : علمی

نویسندگان

1 دانشجوی دکتری، گروه اقتصاد، دانشگاه آزاد اسلامی، واحد اصفهان (خوراسگان)، اصفهان، ایران،

2 دانشیار، گروه اقتصاد، دانشگاه آزاد اسلامی، واحد اصفهان (خوراسگان)، اصفهان، ایران

3 استادیار، گروه اقتصاد، دانشگاه آزاد اسلامی، واحد اصفهان (خوراسگان)، اصفهان، ایران

چکیده

امروزه در بسیاری از کشورهای جهان، شاخص شرایط مالی به عنوان ابزاری برای پیش­بینی متغیرهای کلان اقتصادی معرفی شده است. به همین منظور در مطالعه حاضر، ابتدا به ساخت شاخص شرایط مالی در الگوهای مختلف پارامترهای متغیر زمانی پرداخته و سپس عملکرد شاخص شرایط مالی در پیش­بینی متغیرهای کلان اقتصادی با استفاده از رویکرد میانگین مربعات خطای پیش‌بینی (MSFE) و رویکرد مجموع تجمعی لگاریتم احتمالات پیش­بینی مورد تجزیه و تحلیل قرار می­گیرد.
نتایج حاصله بیانگر آن است که شاخص شرایط مالی ساخته شده توانایی انطباق با حالت­های مختلف اقتصاد ایران را دارد و نوسانات آن در طول زمان افزایش می­یابد. براساس نتایج بدست آمده از رویکرد میانگین مربعات خطای پیش­بینی، الگوی خود­توضیح‌برداری عامل افزوده ‌شده با پارامترهای متغیر زمانی (TVP-FAVAR) در مقایسه با الگوی خود­توضیح برداری عامل افزوده‌شده (FAVAR) و نیز الگوی خودتوضیح برداری پارامتر متغیر زمانی عامل افزوده‌شده (FA-TVP-VAR) خطای پیش­بینی کمتری را در برخی از متغیرهای کلان اقتصادی نشان می­دهد و نیز استفاده از الگوهای ترکیبی خودتوضیح برداری عامل افزوده شده با پارامترهای متغیر زمانی که در آن ضرایب و مجموعه متغیرهای منتخب شاخص شرایط مالی بسته به شرایط اقتصادی تغییر می­کنند، باعث بهبود عملکرد شاخص شرایط مالی در پیش­بینی متغیرهای کلان اقتصادی می­شود. نتایج مجموع تجمعی لگاریتم احتمالات پیش­بینی نشان می­دهد که به کارگیری الگوهای پارامتر متغیر اثر زیادی در کاهش خطای پیش­بینی برخی از متغیرهای کلان ندارد.

کلیدواژه‌ها

موضوعات


عنوان مقاله [English]

Evaluating the Performance of the Financial Condition Index in Forecasting Iran's Macroeconomic Variables: Time-varying Parameter Patterns Approach

نویسندگان [English]

  • Atefe Alahverdi 1
  • saeed Daei-Karimzadeh 2
  • Sara Ghobadi 3
1 Ph.D. Student, Department of Economics, Isfahan (Khorasgan) Branch, Islamic Azad University, Isfahan, Iran
2 Associate Professor, Department of Economics, Isfahan (Khorasgan) Branch, Islamic Azad University, Isfahan, Iran,
3 Assistant Professor, Department of Economics, Isfahan (Khorasgan) Branch, Islamic Azad University, Isfahan, Iran
چکیده [English]

Today, the financial condition index is introduced as a tool for forecasting macroeconomic variables in many countries of the world. The aims of the present study are, first, to construct the financial condition index in different patterns of time-varying parameters and then, to analyze the performance of the financial conditions index in order to forecast the macroeconomic variables using the mean squared forecasting error approach (MSFE) and the cumulative sum of log-predictive likelihoods.
The results show that the constructed financial conditions index can adapt to different states of Iran's economy and its fluctuations increase over time. Based on the obtained results, the time-varying parameter factor-augmented vector autoregressive model (TVP-FAVAR) shows less forecast error in some macroeconomic variables compared to the factor-augmented vector autoregressive model (FAVAR) and also the vector autoregressive time-varying parameter factor-augmented model (FA-TVP-VAR). The use of combined time-varying parameter factor-augmented vector autoregressive models when the coefficients and selected variables of the financial conditions index change depending on the economic condition, improve the performance of the financial conditions index in forecasting macroeconomic variables. The cumulative sum of log-predictive likelihoods shows that using variable parameter patterns does not have a great effect in reducing the forecast error of some macro variables.

کلیدواژه‌ها [English]

  • Financial condition index
  • forecasting
  • macroeconomic variables
  • mean squared forecasting error
  • the cumulative sum of log-predictive likelihoods
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