فصلنامه تحقیقات اقتصادی
پیاپی 148 (پاییز 1403)

The COVID-19 pandemic has emerged as a profound global crisis with extensive impacts on social and economic structures worldwide. This study examines the shifts in income mobility within Iranian households, focusing particularly on those with employed women prior to the onset of the pandemic. Utilizing household income and expenditure data from 2017 to 2019, this research employs advanced econometric models such as the regression discontinuity design and transition matrix analysis to explore the economic repercussions of the pandemic. The findings reveal a significant disparity in income mobility between households with employed women and those with only employed men. Households with employed women experienced greater financial instability and a higher likelihood of descending into lower income brackets compared to their male counterparts. The pandemic disproportionately affected sectors with high female employment rates, such as the service industry, exacerbating the economic vulnerability of these households. In-depth analysis indicates that the closure of schools and childcare facilities, coupled with the downturn in service sector demand, are pivotal factors that intensified the economic decline for women in the workforce. These sectors traditionally employ a higher percentage of women, and the sudden reduction in demand has led to a notable increase in female unemployment rates, further impacting household income stability. In conclusion, The insights provided in this study not only contribute to a deeper understanding of the pandemic's impacts but also inform future policy-making aimed at fostering economic resilience and equality.

Crude oil's pivotal role in the global economy has heightened concerns among economists about the impact of oil price shocks. While considerable research has delved into developed and oil-importing economies, there remains a gap in understanding these phenomena in oil-exporting countries. This paper addresses this gap by employing the Quantile Vector Autoregression (QVAR) method to estimate systemic risk and examine the spillover effects of volatilities between the oil and stock markets of OPEC and OPEC Plus member countries. Analyzing daily data spanning from March 1, 2014, to March 1, 2023, the findings reveal a systemic risk of 42%, with a notable increase exceeding 50% in the last three years. OPEC and Brent oil prices emerge as permanent transmitters of fluctuations within the network. Notably, 75% of Iranian stock market return volatilities are attributed to idiosyncratic risks, with systemic risks accounting for only 25%. Furthermore, Iran's stock market is significantly influenced by shocks from OPEC and Brent oil prices. These insights hold implications for regulators and investors, providing a nuanced understanding of the intricate dynamics between systemic risks and volatilities of oil and stock markets.

High and volatile inflation has had numerous adverse effects on the Iranian economy. Effective inflation-targeting policies require a thorough understanding of the key drivers of inflation. This study aims to identify the most important determinants of inflation in the Iranian economy from 2008 to 2022. In this study, tree-based ensemble methods, which are a class of intelligent machine-learning techniques, have been utilized. Furthermore, Shapley Additive Explanations (SHAP) are utilized to interpret model predictions and determine feature importance. Model performance is evaluated using three error metrics: Mean Absolute Error (MAE), Mean Absolute Percentage Error (MAPE), and Root Mean Squared Error (RMSE). Results indicate that Gradient Boosting (GB), Random Forest (RF), and Extreme Gradient Boosting (XGB) exhibit the lowest error rates across all three metrics. The findings reveal that broad money growth is the most significant determinant of inflation, contributing an average of 72% across all models. The exchange rate, while a contributing factor, plays a less substantial role compared to broad money, accounting for approximately 17% of the inflationary pressures.

Consumption decisions, in addition to directly affecting the well-being of households, are signals to other members of society. This problem is introduced in the economic literature as conspicuous consumption, where the cultural and social aspects of consumption are explored. Based on Heffetz's (2011) study, the present study tests conspicuous consumption among Iranian households. The main question of the research is to examine the relationship between income elasticities and the degree of observability of household consumption items. The relationship between observability (conspicuous consumption) and income elasticity of 36 consumption groups has been investigated. The observability index was calculated from the responses of 250 urban households to the designed questionnaire, and the income elasticities were calculated based on the household budget data of 2015 of the Iran Statistics Center and through non-parametric estimation. Despite showing the alignment of elasticity and observability in many consumer items, the results of the study do not confirm the significant relationship between the two mentioned indicators for the urban society of Iran.

This article utilizes the continuous wavelet transform and its associated tools to provide novel evidence regarding fundamental questions about the Phillips curve in the Iranian economy: slope stability, the role of expectations, and the long-run trade-off. The results indicate that the output gap's impact coefficient on inflation is not constant. Specifically, a positive effect was observed in the short run (2008-2010), while a negative effect was observed in the medium run (2000-2004) and the long run (1995-2004). Inflation expectations positively and significantly influence inflation in both the short and medium runs (2004-2013), but this effect becomes insignificant in the long run. Consequently, the slope of the Phillips curve is deemed unstable: it is negative only in the long run (1995-2004). Therefore, expectations cannot be considered a determining factor for inflation in the long run.

Floods are among the natural disasters that have occurred in recent years for various reasons, especially due to severe climate changes with different intensities and fluctuations around the world. They have caused changes in the housing market. Iran is also one of the countries that has always been exposed to various natural disasters due to its geographical location and can face challenges in the housing market as a result of these disasters. One of the most severe of these disasters was the 2019 flood in Golestan province, which caused significant economic damage to 14 cities and 437 villages in Golestan province. However, its economic impact, especially on the housing market, has been less studied due to reasons such as lack of data. Thus, the present study aims to explore the effect of the Golestan flood on probability of homeownership between 2018 and 2019. Therefore, initially, 381 household from Golestan and 418 household from Kurdistan and Kermanshah provinces were selected. Then, by defining a Dummy variable for flood, the effect of floods on probability of homeownership was estimated using Panel Probit method. The main results of this study indicate that the flood significantly reduces probability of homeownership by 0.028 units.