نوع مقاله : مقالات پژوهشی

نویسندگان

• صمد حکمتی فرید
• فهمیده فتاحی

دانشگاه ارومیه

چکیده

هدف از این مطالعه، بررسی اثر شاخص‌های فناوری بر فقر و شدت آن با استفاده از داده‌های هزینه درآمد خانوارهای شهری و روستایی در سال 1393 است؛ ازاین‌رو ابتدا خط فقر نسبی خانوارهای شهری و روستایی برآورد شده و در ادامه تأثیرپذیری شدت فقر و احتمال وقوع فقر از فناوری اطلاعات و ارتباطات و ویژگی‌های خانوارها مورد بررسی قرار گرفته است. برای این منظور از مدل هکمن دو مرحله‌ای استفاده می‌شود که در آن ابتدا از طریق مدل پروبیت تأثیر متغیرها بر فقر خانوارها بررسی شده و احتمال وقوع فقر خانوارها محاسبه می‌شود. در ادامه با برآورد شدت فقر خانوارهای فقیر، تأثیر متغیرهای تحقیق بر شدت فقر خانوارها مورد بررسی قرار می‌گیرد. نتایج برآورد مدل نشان می‌دهد گسترش شاخص‌های فناوری اطلاعات و ارتباطات تأثیر مثبت و معنی‌داری بر کاهش احتمال وقوع فقر و شدت فقر خانوارهای شهری و روستایی دارد، بطوریکه با افزایش درصد خانوارهای دارای تلفن همراه غیر شغلی، رایانه و اینترنت احتمال وقوع فقر در بین خانوارهای شهری به ترتیب 42/21، 92/11 و 8/10 درصد و در بین خانوارهای روستایی به ترتیب 73/22، 44/15 و 70/10 درصد کاهش یافته و شدت فقر در بین خانوارهای شهری به ترتیب 84/35، 98/31 و 87/31 درصد و در بین خانوارهای روستایی به ترتیب 17/26، 56/34 و 03/17 درصد کاهش یافته است. افزایش شاخص‌ سرمایه انسانی و همسرداربودن سرپرست خانوار هم تأثیر مثبت و معنی‌داری بر کاهش احتمال وقوع فقر و شدت فقر خانوارهای شهری و روستایی دارد. همچنین نتایج حاکی از آنست که با افزایش سن سرپرست خانوار ابتدا احتمال وقوع فقر و شدت فقر خانوارهای شهری و روستایی کاهش و پس از رسیدن به سن خاصی افزایش می‌یابد. علاوه بر این بعد خانوار، شاغل بودن سرپرست خانوار و نسبت افراد دارای درآمد در خانوار در کاهش احتمال وقوع فقر و شدت فقر خانوارها مؤثر می‌باشند.

کلیدواژه‌ها

• خط فقر نسبی
• فناوری ارتباطات و اطلاعات
• ICT
• هکمن دو مرحله ای
• شدت فقر

عنوان مقاله [English]

The impact of Information and Communication Technology Indices on Poverty Probability and Poverty Intensity in Iran

نویسندگان [English]

• Samad Hekmati Farid
• fahmideh fattahi

Urmia University

چکیده [English]

The aim of this study is estimating the effect of technology indices on poverty probability and poverty intensity by using rural and urban Household data from Statistics Center of Iran in 2014. For this purpose, first, we estimated the relative poverty line then the impact of ICT indices and household characteristics on poverty probability and poverty intensity were analyzed by two-step Heckman Method. In this method, the first step estimates the probit model to investigate the effect of variables on poverty. Moreover, in this step we calculate poverty probability. In the second step, we regress explanatory variables on poverty intensity variable after calculating poverty intensity.
The results indicate that an increase in ICT indices has a negative and significant impact on the probability of being poor and poverty intensity. Therefore, if the percentage of urban households with mobile phones, computers and internet, increases, the probability of being poor decreases respectively to 21.42, 11.92, 10.8 percent for urban households and 22.73, 15.44 and 10.7 percent for rural households. Furthermore, an increase in the percentage of urban households with mobile phones, computers and internet, decreases poverty intensity respectively 35.84, 31.98, 31.87 percent for urban households and 26.17, 34.56, 17.03 percent for rural households.
Moreover, the results show that an increase in the education level and marriage of heads of households have a positive and significant impact on poverty reduction probability and poverty intensity. In addition, the results indicate that the relationship between age and poverty may not be linear, Therefore, Increasing the age before the aging stage reduces poverty probability but after this stage, Increasing the age lead to increasing poverty probability. In addition, increasing household size and employment of the head of household have a negative and significant impact on the probability of being poor and poverty intensity.

Extended Abstract
Poverty is wide-spread and it is a global phenomenon that cuts across all countries of the world. No nation, not even the most technically and economically advanced economy, could boastfully assert the absence of at least a single dimension of poverty within her economy. However, poverty seems to be predominantly a fundamental trait among developing and the less developed countries alike. (Anigbogu, Onwuteaka, Anyanwu, & Okoli, 2014). There are many factors that can affect poverty alleviation. Information and communication technology (ICT) is one of the most important factors that affects poverty. Throughout history technology has been a powerful instrument for economic and social development. Technology played a critical role in reducing poverty in vast areas of the world in the past and can play a crucial role in the battle against poverty today. It can be employed in a variety of fields, from increasing agricultural productivity to the generation of cheap energy, from providing clean water to improving health. In particular, information and communication technology (ICT) can address the problem of poverty by increasing people’s access to education, health, and financial services. ‌‌‌Strikingly, even simple technologies might make a difference in poverty reduction. The case of cellular phones in Africa is a well-known example. Likewise, small businesses and social enterprises creating access to primary goods are greatly helped by new technologies (Popoli, 2015). Given the importance of this issue the aim of this study is surveying the effect of ICT indices on poverty in Iran.

Methodology
In this paper, we have used rural and urban household data from Statistics Center of Iran in 2014 that contain information about 18885 urban households and 19390 rural households. For surveying the effect of ICT indices on poverty, we investigate the impact of information and communication technology indices on poverty probability and poverty intensity. For this purpose, first, we estimate relative poverty line as half of the average household expenditure in Iran. It is an indicator of inequality at the bottom of the income distribution, which acts as a cause of social exclusion and undermines equality of opportunity.
After determining relative poverty line we can identify poor households and then the impact of ICT indices and household characteristics on poverty probability and poverty intensity by two-step Heckman Method. In this Method, the first step is estimates probit model to investigate the impact of variables on poverty. Also in this step we calculate poverty probability. In second step, calculating poverty intensity, we regress explanatory variables on poverty intensity variable. In the first step the estimated coefficients are used to estimate the inverse Mills ratio for each individual. In Step 2, the estimated Mills ratio is used as an instrument or regressor in the logit model.

Results and Discussion
The results show that relative poverty line for urban and rural households in 2014 was 94023127 and 104338980 Rials respectively which implies that households by lower expenditure than this line are poor households. The estimation of the first step of Heckman model showed that all of the coefficients are significant. Marginal effects after probit coefficients indicate that an increase in ICT indices have a negative and significant impact on the probability of being poor and poverty intensity. Therefore, an increase in the percentage of urban households with mobile phone, computer and internet, decreases the probability of being poor 21.42, 11.92, and 10.8 percent for urban households respectively and 22.73, 15.44 and 10.7 percent for rural households. It should be noted that lack of infrastructure, especially in developing countries, results in the poor being deprived of the information and knowledge that would help them to live healthier lives, improve their educational standards, and gain employment and business opportunities. ICTs have the potential to process and disseminate vast amounts of information and can therefore have a far greater impact on the lives of the poor than informal information networks. ICTs enable households, that works in firms, to improve productivity and income generation by allowing them to access the market information faster and cheaper. This may strengthen forward linkages to the market (Mbuyisa & Leonard, 2015)
In addition, the results indicate that the relationship between age and poverty may not be linear, So that Increasing the age before the aging stage reduces poverty probability but after this stage, Increasing the age lead to increasing poverty probability. Furthermore, an increase in human capital index (education level) and marriage of heads of households has a positive and significant impact on poverty reduction probability. In addition, employment of the head of the household has a significant and negative impact on the probability of being poor.
To estimate the second step of the Heckman method first we calculated poverty intensity. Therefore, purpose, we should square the poverty gap, which measures the extent to which households fall below the poverty line, for each household. This index puts more emphasis on observations that fall far short of the poverty line rather than those that are closer.
Poverty intensity will be a dependent variable in the second step of Heckman method and its value for non-poor households will be zero. Estimating poverty intensity equation in the second step of Heckman show that an increase in the percentage of urban households with mobile phone, computer and internet, decreases poverty intensity for 35.84, 31.98, and 31.87 percent for urban households respectively and 26.17, 34.56, and 17.03 percent for rural households that indicate that ICT has an important role in decreasing poverty intensity.
Moreover, the results show that an increase in education level and household size, together with being married and of the employment of the head of household have a negative and significant impact on poverty intensity.
Conclusion
The results of this paper show that improvement in ICT indices can reduce probability of being poor and poverty intensity and provides evidence for benefits of ICT and the role that it plays in poverty alleviation. As ICT contributes to poverty reduction, there are good reasons for governments to promote the use of ICTs in the business sector and households for poverty alleviation.
Furthermore, results indicate that household characteristics such as education level, household size, being married, age and employment of the head of the household have a significant impact on poverty. Hence, governments should pay attention to this characteristic in poverty alleviation programs.

کلیدواژه‌ها [English]

• relative poverty
• Information and Communication TechnologyHeckman
• ICT
• two-step method
• poverty intensity