Economic Research and Perspectives

Economic Research and Perspectives

The effects of Inflation and Unemployment on Multidimensional Inequality in the Iranian Provinces A Spatial Econometric Approach

Authors
esmaiel abounoori 1
anahita roozitalab 2
1 Professor of Econometrics and Social Statistics, Department of Economics, Semnan University, Semnan, Iran
2 Ph.D. in Econometrics, Department of Economics, Semnan University, Iran
10.48311/ecor.2025.13662
Abstract
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.
Keywords
Multidimensional Gini Coefficient
Inflation
Unemployment
Spatial Autoregression Model
Iran

Subjects

Abounoori, A.A., Muftah, S., Parhizi Geshti, H. (2009). Analysis of the effect of inflation on income distribution in Iran (comparative analysis of urban and rural areas of Iran), Financial Economy (Financial Economics and Development), 13(5), 77-96. (In Persian)
Abounoori, E., & Roozitalab, A. (2023). Estimation of Multidimension Gini Coefficient in Comparison with the Unidimensional in Iran. Journal of Economic Research (Tahghighat- E- Eghtesadi), 58(1), 1-23. doi: 10.22059/jte.2023.93458. (In Persian)
Abounoori, E., Khushkar, A. (2007). Analysis of factors affecting economic inequality in Iran using micro data, Islamic Economy, 8(30), 99-122. (In Persian)
Abounoori, Esmaiel and Fayazi Alireza (2019). Spatial econometrics from cross-sectional data to spatial panel, translation of Paul,. E. (2014), Semnan University, Semnan-Iran. (In Persian)
Alavirad, A., VakiliZarch, M., totonchi, J., & Dehghan Tafti, M. A. (2022). The effect of bank facilities and deposits on income inequality in Iranian provinces. The Journal of Economic Studies and Policies, 9(1), 194-219. doi: 10.22096/esp.2022.136462.1413. (In Persian)
Al‐Marhubi, F. A. (2000). Income inequality and inflation: the cross‐country evidence, Contemporary Economic Policy, 18(4), 428-439.
Anselin, L. (1988). Spatial econometrics: methods and models (Vol. 4). Springer Science & Business Media.
Armanmehr, M., farahmandmanesh, A. (2018). Investigating the Effect of Inflation on Income Inequality of Urban Households in Iran Using the Atkinson Approach, Journal Of Economics and Regional Development, 25(16), 127-152. doi: 10.22067/erd.v25i15.62836. (In Persian)
Atkinson, A. B., & Bourguignon, F. (1982). The comparison of multidimensioned distributions of economic status. Review of Economic Studies, 49, 183–201.
Azizi, A., Zare, H., Amini Fard, A., Khodaparast, J. (2022). Measuring the optimal inflation rate with the aim of minimizing economic inequality: a stochastic dynamic general equilibrium approach, Financial Economics, 16(60), 355-380. dio.10.30495/fed.2022.697619 (In Persian)
Babakhani M., Raghfar H. (2009). Relationship between Income inequality and health in Iran during 1976-2006. jha; 12 (37), 9-16. http://jha.iums.ac.ir/article-1-475-fa.html. (In Persian)
Banerjee, A.K. (2010). A multidimensional Gini index, Mathematical Social Sciences; 60(2), 87-93.
Blinder, A. S., &. Esaki, H. Y. (1978). Macroeconomic Activity and Income Distribution in the Postwar United States, Review of Economics and Statistics, 60, 604-9.
Bourguignon, F. (1999). Comment on ‘multidimensioned approaches to welfare analysis, in (E. Maasoumi and J. Silber, eds.), Handbook of Income Inequality Measurement, London: Kluwer Academic.
Brunori, P., Neidhöfer, G. (2021). The evolution of inequality of opportunity in Germany: A machine learning approach, Review of Income and Wealth, 67(4), 900-927.
Bui, T. K. T., & Erreygers, G. (2020). Multidimensional Inequality in Vietnam, 2002–2012. Economies, 8(2), 29-38.
Bukodi, E., Eibl, F., Buchholz, S., Marzadro, S., Minello, A., Wahler, S. , ... & Schizzerotto, A. (2018). Linking the macro to the micro: a multidimensional approach to educational inequalities in four European countries, European Societies, 20(1), 26-64.
Cardoso, E., & Urani, A. (1995). Inflation and unemployment as determinants of inequality in Brazil: the 1980s. In Reform, recovery, and growth: Latin America and the Middle East University of Chicago Press, 151-176.
Decancq, K. (2017). Measuring multidimensional inequality in the OECD member countries with a distribution-sensitive Better Life Index, Social Indicators Research, 131(3), 1057-1086.
Decanq, K., & Lugo, M. A. (2009). Measuring well being inequality with a multidimensional Gini index.
Domhari, M., & Hashemi, F. (2015). Analysis of regional inequality in Iran, International Conference of Management Elites, Tehran, June 2016, Shahid Beheshti University. (In Persian)
Feizi, M., Beirzanvand, M., & Malekosadati, S. (2021). Effect of Unemployment, Inflation and Minimum Wage on Income Inequality in Rural Areas of Iranian Provinces, Quarterly Journal of The Macro and Strategic Policies, 8(Special Issue), 30-45. Doi.10.30507/jmsp.2020.102779. (In Persian)
Golkhandan, A. (2016). Threshold Effect of Inflation on Income Inequality: Smooth Transition Regression (STR) Model, Journal of Iran's Economic Essays (JIEE), 13(25), 75-95. (In Persian)
Gorji, E., & Borhanipour, M. (2008). Globalization and Income Distribution in Iran. Iranian Journal of Economic Research, 10(34), 99-124. (In Persian)
Iranian Statistics Center (1402). Statistical data and information, development indicators, provincial indicators of economic status of provinces 2017-2021.(In Persian)
Khodaparast, M., & Davoodi, A. (2014). Public expenditures , poverty and inequality. Quarterly Journal of The Macro and Strategic Policies, 1(vol 1-no 4), 37-50. (In Persian)
Laidler, D. & M. Parkin. (1975). Inflation: A Survey, Economic Journal, 12(2), 741–809.
Lesage, J., & Pace, R. (2009). Introduction to Spatial Econometrics. Boca Raton: Taylor and Francis.
Li, Y., & Wei, Y. D. (2014). Multidimensional Inequalities in Health Care Distribution in Provincial C hina: A Case Study of H enan Province, Tijdschrift voor economische en sociale geografie, 105(1), 91-106.
Martincus, C. V. (2010). Spatial effects of trade policy: Evidence from Brazil, Journal of Regional Science, 50(2), 541-569.
Monnin, P. (2014). Inflation and income inequality in developed economies, CEP Working Paper Series.
Moradizadeh, M., Shirmehenji, M. B., & Nourahmadi, M. J. (2022). The Nonlinear Effect of Inflation on Income Inequality (Developing-Countries Study), Stable Economy Journal, 2(4), 29-54. doi: 10.22111/sedj.2022.40958.1170. (In Persian)
Nakamura, SH. & Avner, P. (2021). Spatial distributions of job accessibility, housing rents and poverty: The case of Nairobi, Journal of Housing Economics,51.
Nilsson, T. (2010). Health, wealth and wisdom: Exploring multidimensional inequality in a developing country, Social indicators research, 95(2), 299-323.
Parente, F. (2019). A multidimensional analysis of the EU regional inequalities, Social Indicators Research, 143(3), 1017-1044.
Pinar, M. (2019). multidimensional well-being and inequality across the European regions with alternative interactions between the well-being dimensions. Social Indicators Research, 144(1), 31-72.
Poppitz, P. (2019). multidimensional inequality and divergence: The Eurozone crisis in retrospect 420(2). Oldenburg Discussion Papers in Economics.
Raghfar H., Safarzadeh E., Aliakbari Salami F. (2018). The Measurement of the Multidimensional Inequality Index in Urban Areas of Iran, QJER,18 (1), 127-154. http://ecor.modares.ac.ir/article-18-21262-fa.html. (In Persian)
Rajan, R. G., & Zingales, L. (2003). The great reversals: the politics of financial development in the twentieth century. Journal of financial economics, 69(1), 5-50.
Ramsay, M. (1992). Human needs and the market. Aldershot: Avebury.
Rice, G. R., & Lozada, G. A. (1983). The effects of unemployment and inflation on the income distribution: A regional view, Atlantic Economic Journal, 11, 12-21.
Schultz, T. P. (1969). An economic model of family planning and fertility, Journal of Political Economy, 77(2), 153-180.
Seifeepour R, Rezaee M. (2011). An Analysis of the Effective Factors on Income Distribution in Iran with the Emphasis on Taxes. J Tax Res; 19(10), 121-142. http://taxjournal.ir/article-1-100-fa.html. (In Persian)
Sen, A. (1993). Capability and well-being73. The quality of life, 30, 270-293.
Sen, A. K. (1985). Commodities and capabilities. Amsterdam: North-Holland.
Stewart, F. (1985). Basic needs in developing countries. Baltimore, MD: Johns Hopkins University Press.
Yang, L., Lu, H., & Li, M. (2023). Multidimensional Inequality and Subjective Well-Being in China: A Generalized Ordered Logit Model Analysis. Social Indicators Research, 165(3), 1021-1052.
zaroki, S., Yousefi barfurushi, A., Mehri karnami, Y. (2020). The Effect of Black Market Premium and Asymmetric Inflation and Unemployment on Income Inequality in Iran. Quarterly Journal of Applied Theories of Economics, 7(1), 117-148. doi: 10.22034/ecoj.2020.9423. (In Persian)