اقتصاد و الگو سازی

اقتصاد و الگو سازی

بررسی تأثیر اجزای نقدینگی بر تورم ایران: رویکرد روش‌های میانگین‌گیری و یادگیری ماشین

نوع مقاله : مقاله پژوهشی

نویسندگان
منصور حیدری 1
سامان حاتم راد 2
صادق رضایی 3
الهام نوبهار 4
حسین اصغرپور 5
1 دانشجوی دکتری گروه اقتصاد دانشکده اقتصاد و مدیریت دانشگاه تبریز، تبریز، ایران
2 استادیار اقتصاد گروه اقتصاد دانشکده‌ علوم انسانی دانشگاه زنجان، زنجان، ایران
3 استادیار گروه توسعه کارآفرینی دانشکده‌ کارآفرینی دانشگاه تهران، تهران، ایران
4 دانشیار گروه توسعه اقتصادی دانشکده‌ اقتصاد و مدیریت دانشگاه تبریز، تبریز، ایران
5 استاد گروه اقتصاد دانشکده اقتصاد و مدیریت دانشگاه تبریز، تبریز، ایران
10.48308/jem.2025.236260.1934
چکیده
سیاست‌های پولی و عوامل مربوط به خلق نقدینگی از مهمترین دلایل ایجاد تورم در اقتصاد است. در فرآیند خلق نقدینگی عوامل مهمی دخیل هستند که بررسی تأثیر هر کدام از اجزای نقدینگی می‌تواند در کنترل تورم و سیاستگذاری اقتصاد کلان بسیار مهم و حائز اهمیت باشد. مطالعه حاضر با استفاده از روش‌های میانگین‌گیری بیزی اثرات اجزای مختلف نقدینگی بر تورم ایران طی دوره 1400-1360 مورد بررسی قرار داده است. برای این منظور، با استفاده از سه روش میانگین‌گیری بیزی BACE، BAS و BMA عوامل مهم موثر بر تورم شناسایی شده و سپس با به کارگیری دو روش JMA، MALLOWS الگوی تورم تخمین زده شده است. بررسی استحکام نتایج با روش یادگیری ماشین موید یافته‌های دو روش JMA و MALLOWS است. نتایج نشان می‌دهد که از 6 عامل مهم دخیل در خلق نقدینگی، سه عامل بدهی بانک‌ها به بانک مرکزی، حجم پول و انتظارات تورمی مهمترین عوامل موثر در بروز تورم هستند. نتایج تمامی روش‌های مورد استفاده دلالت بر آن دارد که متغیر خالص بدهی دولت به بانک مرکزی اثرات تورمی بسیار کمتری نسبت به 3 عامل یاد شده دارد. همچنین رشد شبه پول به همراه متغیر دارایی‌های خارجی بانک مرکزی اثرات ضد تورمی دارند. 
کلیدواژه‌ها
تورم
یادگیری ماشین
میانگین‌گیری بیزی
JMA
موضوعات

عنوان مقاله English

Investigating the Impact of Liquidity Components on Inflation in Iran: Averaging and Machine Learning Approaches

نویسندگان English

Mansour Heydari 1
Saman Hatamerad 2
Sadeq Rezaie 3
Elham Nobahar 4
Hossein Asgharpur 5
1 PhD Candidate in Economics, Faculty of Economics and Management, University of Tabriz, Tabriz, Iran
2 Assistant Professor of Economics, Faculty of Humanities, University of Zanjan, Zanjan, Iran
3 Assistant Professor of Economics, Faculty of Entrepreneurship, University of Tehran, Tehran, Iran
4 Associate Professor of Economics, Faculty of Economics and Management, University of Tabriz, Tabriz, Iran
5 Professor of Economics, Faculty of Economics and Management, University of Tabriz, Tabriz, Iran
چکیده English

Monetary policies and factors influencing liquidity creation are among the key drivers of inflation in the economy. Various elements play a role in the process of liquidity creation and analyzing the impact of each can greatly aid in controlling inflation and shaping macroeconomic policies. This study investigates the effects of different components of liquidity on inflation in Iran during the period 1981-2021, employing Bayesian averaging methods. Using three Bayesian averaging techniques -BACE, BAS, and BMA- the study identifies the main factors influencing inflation. Subsequently, inflation models are estimated using JMA and MALLOWS methods. Robust checks, conducted via machine learning techniques, confirm the findings of JMA and MALLOWS. The results reveal that among the six key factors contributing to liquidity creation, the most significant drivers of inflation are commercial banks overdraft, the money supply, and inflation expectations. Across all methods employed, the findings indicate that the net debt of government to the central bank has a far smaller inflationary effect compared to the aforementioned three factors. Additionally, growth in quasi-money and the central bank's foreign assets exhibit anti-inflationary effects.

کلیدواژه‌ها English

Inflation
Machine learning
Bayesian Averaging Method
JMA
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