عوامل تاثیرگذار بر سرعت همگرایی شاخص فلاکت در استان‌های ایران طی دوره 1399-1385

در این مطالعه، به بررسی تاثیر رشد اقتصادی، فناوری اطلاعات و ارتباطات (فاوا)، سرمایه انسانی و  بی انضباطی پولی بانک ها بر همگرایی شاخص فلاکت در استان‌ها در دوره زمانی 1399-1385 با استفاده از اقتصادسنجی فضایی پرداخته ‌شده است. نتایج حاصل از برآورد مدل‌ها، نشان داد که رشد اقتصادی و سرمایه انسانی، تاثیر منفی و معنی دار، فاوا و بی انضباطی پولی بانک ها، تاثیر مثبت و معنی دار بر همگرایی شاخص فلاکت در استان‌ها دارند. سرعت همگرایی بتای شرطی برآورد شده با حضور رشد اقتصادی، فناوری اطلاعات و ارتباطات (فاوا)، سرمایه انسانی و بی انضباطی پولی بانک ها، بیشتر از حالت همگرایی مطلق می‌باشد. با توجه به سرعت همگرایی، درحالت همگرایی مطلق، سالانه حدود 9/10درصد و در حالت  همگرایی شرطی، سالانه حدود 6/12 درصد از اختلاف میان نرخ رشد فعلی شاخص فلاکت استان ها و شاخص فلاکت تعادلی بلندمدت استان ها بر طرف می شود. ضریب وقفه فضایی متغیر وابسته نیز نشان داد که شاخص فلاکت هر استان، می‌تواند تحت تاثیر تغییرات شاخص فلاکت استان های مجاور قرار گیرد.

factors affecting the convergence speed of misery index in the provinces of iran over the period 2006-2020

aim and introductiontoday, planners and decision makers of countries need timely and accurate evaluation of their decisions and policies. the issue of time and precision is so important that it provides the possibility of implementing possible changes and modifications of patterns and plans, and prevents wasting resources and opportunities. fortunately, various indicators have provided such a possibility to evaluate these policies and decisions. misery index is one of the most important measures of social welfare. this index is obtained from the linear combination of inflation and unemployment. this index was introduced by aokan (1999) and expanded by barro (1996). an increase in the misery index is associated with many social and economic costs, such as an increase in crime, poverty, divorce, a decrease in social security, damage to mental health, the collapse of families, a decrease in health expenses, and a decrease in life expectancy. inflation causes the imposition of welfare costs by reducing the value of people’s financial assets, and on the other hand, it harms production by creating uncertainty in the decisions of institutions for investment and creating other costs. inflation leads to sub - optimal allocation of resources, economic inefficiency and social, cultural and political disorder of the society. unemployment like inflation is the cause of chaos in the economic conditions of the society. unemployment has caused people to suffer from social problems such as crimes, addiction and moral corruption. unemployment causes people to be caught in social problems such as crime, addiction and moral corruption.methodologyknowledge and awareness of the state of misery index in the regions of the country in certain time horizons are very important for the planners of the region and economic policy makers of the country. considering the importance of the misery index, this question is raised: which factors affect the convergence of the misery index in the provinces? in this regard, several studies have been conducted in the field of misery index. however, none of the studies have investigated the influence of the factors affecting the convergence of the misery index in the provinces using spatial econometrics. in economic literature, there are several methods for investigating the convergence. absolute beta convergence and conditional beta convergence have been used in this study. absolute beta convergence is formed independently of initial conditions and other characteristics of an economy.for this purpose, using theoretical foundations and empirical studies, the variables of economic growth, monetary indiscipline, human capital, and information and communications technology (ict) were added to the convergence model as explanatory variables. absolute beta convergence and conditional beta convergence models have been estimated using the spatial econometric method over the period 2006-2020.in this study, after defining the spatial weight matrix, the unit root test is used to examine the stationary of the variables. moran test and lagrange multiplier test are used to detect spatial autocorrelation and examine the presence of spatial effects, respectively. chow’s test is used to determine whether the data is a panel, and hausman’s spatial test is used to use the fixed or random effect method. finally, the model is estimated, and effects of space spillovers are analyzed with spatial econometrics method by accounting for direct and indirect effects in stata software.