اثرات تورم و بیکاری بر نابرابری چندبعدی در استان های ایران: رویکرد اقتصادسنجی فضایی (مقاله علمی وزارت علوم)
درجه علمی: نشریه علمی (وزارت علوم)
آرشیو
چکیده
نابرابری پدیده ای چندبعدی است. با توجه به شرایط و ویژگی های جغرافیایی هر منطقه، نابرابری ها در میان استان ها] مناطق [متفاوت هستند. هدف اساسی از این مطالعه، بررسی اثرات تورم و بیکاری به همراه متغیرهای سرانه مخارج واقعی دولت و سرانه واقعی تسهیلات پرداختی به عنوان شاخصی از توسعه مالی بر نابرابری چندبعدی در استان های ایران طی دوره زمانی 1400-1379 است. بدین منظور، با استفاده از ریزداده های طرح هزینه (درآمد) خانوار، ابتدا ضریب جینی چندبعدی در 9 گروه عمده کالایی: خوراک، پوشاک و کفش، مسکن، ارتباطات و حمل و نقل، آموزش، تفریحات و سرگرمی، بهداشت، اثاثیه و خدمات و سایر به تفکیک استان های کشور برآورد شده، سپس براساس جدیدترین اطلاعات بین استانی موجود، تورم، بیکاری، سرانه مخارج واقعی دولت و سرانه واقعی تسهیلات پرداختی ، الگوی عامل های مؤثر بر نابرابری چندبعدی براساس مفهوم اقتصادسنجی فضایی برآورد شده، و نتایج نشان می دهد که تورم، بیکاری، سرانه مخارج واقعی دولت و سرانه واقعی تسهیلات پرداختی، دارای اثرات مثبت و معنادار بر نابرابری چندبعدی در استان های ایران بوده است. همچنین براساس نتایج به دست آمده، افزایش هر یک از متغیرهای فوق، سبب بدتر شدن وضعیت توزیع درآمد در استان های همجوار می شودThe effects of Inflation and Unemployment on Multidimensional Inequality in the Iranian Provinces A Spatial Econometric Approach
Inequality is a multidimensional phenomenon. Given the geographical conditions and characteristics of each region, inequalities vary across different provinces. The primary objective of this study is to examine the effects of inflation and unemployment, along with the variables of real per capita government expenditures and real per capita paid facilities as an indicator
of financial development, on multidimensional inequality in Iran's provinces during the period
2000-2021. To this end, using microdata from the Household Expenditure (Income) Survey, we first estimate the multidimensional Gini coefficient across nine major commodity groups: food, clothing and
footwear, housing, communications and transportation, education, recreation and entertainment, health, furniture and services, and others— disaggregated by province. Subsequently, based on the latest available interprovincial data, we estimate a model of the
factors influencing multidimensional inequality using
the concept of spatial econometrics, incorporating inflation, unemployment, real per capita government expenditures, and real per capita paid facilities. The results indicate that inflation, unemployment, real per capita government expenditures, and real per capita paid facilities have significant positive effects on multidimensional inequality in Iran's provinces. Additionally, the findings reveal that an increase in any of these variables worsens income distribution in neighboring provinces.
Aim and Introduction
Inequality is a multidimensional phenomenon that affects various aspects of households' lives. The economic well-being of individuals depends not only on their income but also on other factors such as access to healthcare, education, transportation, etc. Therefore, one-dimensional methods (income-focused) are insufficient for measuring inequality. The multidimensional approach to inequality considers different aspects of individual welfare, unlike the one-dimensional approach. The concentration of population and activities in some provinces of Iran, along with macroeconomic indicators (inflation and unemployment), exacerbates inequality. These inequalities affect various dimensions of people's lives and endanger their economic welfare. The primary aim of this study is to examine the effects of inflation and unemployment on multidimensional inequality in the provinces of Iran and their reciprocal effects on each other, using a multidimensional Gini coefficient estimated from the household budget microdata of the Statistical Center of Iran for the years 2000-2021.
Methodology
In this study, the multidimensional Gini coefficient by Kumar Banerjee (2010) has been estimated for 9 dimensions of welfare. Then, the effects of inflation and unemployment, along with variables such as per capita real government expenditure and per capita real financial facilities as indicators of financial development, will be analyzed using a spatial econometric model. The mathematical form of the multidimensional Gini coefficient (MGI) is as follows:
Here, the mathematical formula would be inserted) In this equation: represents the non-increasing rank of the unit under study in the individual's overall welfare vector, and represents the sample size. The range of this index fluctuates between zero (completely equal distribution) and one (completely unequal distribution). For measuring multidimensional inequality in this study, the multidimensional Gini coefficient by Kumar Banerjee (2010) has been used which is based on the microdata from the household expenditure (income) survey of the Statistical Center of Iran and involves data mining processes such as aggregating groups of beverages and tobacco, ready meals with food expenditure groups, and communications with transportation, and extracting data related to each household code in each province using R Studio 2020 software. The model is based on the spatial econometric method with spatial panel data, defined using a proximity method in which provinces sharing a border have an element of one and otherwise zero. The adjacency matrix (spatial weight) is normalized, where neighboring provinces carry the most weight, and distant provinces carry the least.
Findings
The results of estimating the multidimensional Gini coefficient for the provinces during 2000-2021 show that most provinces have experienced a high rate of inequality. Provinces such as Bushehr, Khuzestan, Kermanshah, Kurdistan, Markazi, Qazvin, Qom, Semnan, Sistan and Baluchestan, West Azerbaijan, Zanjan, and Yazd are in an unfavorable condition compared to the country, and most of these provinces are border regions. Over these 22 years, Sistan and Baluchestan with 77.66% have the highest rate of multidimensional inequality, while Isfahan with 60.85% has the lowest among the provinces. Additionally, the findings indicate that inflation, unemployment, per capita real government expenditure, and per capita real disbursed financial facilities have a significant positive effect on multidimensional inequality in the provinces of Iran. The proximity of provinces has also worsened the inequality conditions in the neighboring provinces.
Discussion and Conclusion
Four variables including unemployment, inflation, per capita real government expenditure, and per capita real disbursed financial facilities have a significant positive effect on the multidimensional Gini coefficient, worsening income distribution. The most significant impact is seen with per capita real government expenditure, which is not allocated effectively to enhance welfare and improve economic conditions, thus not improving income distribution and reducing inequality. The effects of the other variables are in the following order: per capita real disbursed financial facilities, unemployment, and inflation. It is recommended to consider all welfare dimensions in the household consumption basket, create equal conditions for access to bank facilities, allocate a specific quota of facilities to lessdeveloped provinces, allocate government expenditures to expand public services and infrastructure in deprived provinces, consider the interactive effects between provinces in policymaking, and implement effective policies to improve welfare conditions and balanced income distribution across all provinces.
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