نوع مقاله : مقاله پژوهشی
نویسندگان
گروه اقتصاد دانشگاه سمنان
چکیده
کلیدواژهها
موضوعات
عنوان مقاله [English]
نویسندگان [English]
This research aims to examine the impact of inflationary mindset, which refers to the public's focus on rising prices of goods, especially assets, on inflationary expectations (or mental inflation) and its effect on inflation in the Iranian economy. The data used includes some indicators of mental inflation reflected in social media, specifically Google Trends, and a set of economic variables from March 2013 to March 2024. This is an applied study that uses descriptive-analytical methods and correlation analysis to investigate factors affecting inflation rates and predict them using machine learning algorithms in Python software. The results show that in the univariate analysis, a doubling of mental inflation without applying a time lag led to a 0.9-unit increase in the inflation rate. Additionally, with a three-month lag, this variable caused a 4-unit increase in the inflation rate. These findings suggest that the impact of mental inflation is not only immediate but also strengthens over time. In the multivariate analysis, the effect of inflationary mindset, compared to other variables, was reduced but still remained significant. This indicates that inflationary mindset, along with other key economic variables such as gold price, dollar exchange rate, and GDP, is a powerful tool for analyzing and predicting inflation. Among advanced machine learning algorithms, the decision tree algorithm performed best in forecasting inflation rates. The findings of this study can be useful for economic policymakers in managing inflation expectations and predicting future inflation trends.
کلیدواژهها [English]
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