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Актуальные проблемы авиации и космонавтики - 2021. Том 3
УДК 331.56
ВЛИЯНИЕ ДИДЖИТАЛИЗАЦИИ НА УРОВЕНЬ БЕЗРАБОТИЦЫ В ИНДИИ
1 2 В. В. Иваницкая *, А. В. Цветцых
1 Будапештский университет имени Корвина Венгрия, 1093, г. Будапешт, ул. Fovam ter 8
2Сибирский государственный университет науки и технологий имени академика М. Ф. Решетнева
Российская Федерация, 660037, г. Красноярск, просп. им. газ. «Красноярский рабочий», 31
*E-mail: violetta.ivanitskaya@yandex.ru
В статье рассматривается влияние диджитализации на уровень безработицы на примере Индии.
Ключевые слова: Индия, диджитализация, уровень безработицы, рынок труда, экономический рост.
THE IMPACT OF DIGITALIZATION ON UNEMPLOYMENT RATE IN INDIA
V. V. Ivanitskaia1*, A. V. Tsvettsykh2
:Corvinus University of Budapest 8, Fovam ter, Budapest, 1093, Hungary 2Reshetnev Siberian State University of Science and Technology 31, Krasnoyarskii rabochii prospekt, Krasnoyarsk, 660037, Russian Federation *E-mail: violetta.ivanitskaya@yandex.ru
The article considers the impact of digitalization on the unemployment rate in the case of India.
Key words: India, digitalization, unemployment rate, labour market, economic growth.
Introduction
Nowadays the topic of digitalization has a high relevance in the literature, many researchers try to figure out the impact of digitalization on the unemployment rate in the short and long run. The process of digitalization leads to the structural changes in the labour market, but there is still no consensus in the literature regarding the impact of digitalization on unemployment. Some authors argue that the process of digitalization will create new jobs, whereas other authors claim that it increases unemployment. According to some authors, the investment in data and digital infrastructure is essential to support innovation, growth and jobs in the digital economy [1]. At the same time, according to Brynjolfsson, McAfee (2011), technologies are able to replace not only jobs with routine tasks, but also non-routine which require high skills [2]. Rifkin (2014) argues that the long run digital revolution will reduce employment. According to him, even a low-paid worker will be more expensive than the additional cost of using a machine. As a result, there will be a growth in jobs for innovative products and decline in jobs for standard products [3].
In this article, we are going to estimate the impact of digitalization on the unemployment rate in the case of India. E-governance initiatives in India took a broader dimension in the mid 1990s for wider sectoral applications with emphasis on citizen-centric services [4]. Starting from 2015, the Digital India programme (DI) was officially launched by the government. According to the official site of the programme, the main nine pillars of DI are: Broadband highways, Universal access to mobile connectivity, Public internet access programme, Reforming government through technology,
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Electronic delivery of services, Information for all, Electronics manufacturing, IT for jobs, Early harvest programmes. All the initiatives of the Digital India programme have definite completion time targets. Most part of the initiatives are planned to be realized within the three years. The initiatives such as "Early Harvest Programmes'' and citizen communication initiatives "Information for All" have already been completed [5].
As we can see, there is still no consensus in the literature regarding the impact of digitalization on unemployment rate and this topic requires further research. Moreover, the case of India provides a high interest for research in this field, because the development of digitalization in this country is a primary task for the government, and some of the results are already visible. In this article, we are going to estimate the impact of digitalization on unemployment in case of India with help of time-series ordinary least squares (OLS) regression in STATA. Based on data availability, the chosen period for regression is 2000-2017.
Description of data and empirical results
The descriptive statistics of the data is presented in Table 1. The dependent variable in the regression is unemployment rate, which measured in percentages of the total labour force. The explanatory variable is the variable which is the best approximation to variable of digitalization, in this case we have chosen the variable of information and communication technology service exports (ICT), which includes computer and communications services (telecommunications and postal and courier services) and information services (computer data and news-related service transactions). Data are in current U.S. dollars.
Table 1
Descriptive Statistics
Variable Obs Mean Std. Dev. Min Max
year 18 2008.5 5.339 2000 2017
unempl 18 5.575 .13 5.281 5.725
ICT 18 4.465e+10 2.712e+10 5.027e+09 7.852e+10
All the yearly values of dependent and independent variables were taken from The World Bank official site [6].
As the first step, we have generated the logarithm of dependent and independent variables to be able to receive the more precise results. As a result, we are going to estimate a log-log regression model. As the second step we have checked the normality assumption with the help of Jarque-Bera test for normality. According to the Jarque-Bera test we received a p-value of 0,15, which means that the distribution of the residuals is close to normal. To be able to see the trend existence in our time-series data we have run the regression with variable of trend for dependent variable of unemployment rate. The results are presented in Table 2.
Table 2
Time-series regression with trend
lunempl Coef. St.Err. t-value p-value [95% Conf Interval] Sig
1ICT -.029 .017 -1.67 .115 -.067 .008
t .003 .003 1.13 .277 -.003 .01
Constant 2.395 .398 6.02 0 1.547 3.243 * * *
Mean dependent var 1.718 SD dependent var 0.024
R-squared 0.231 Number of obs 18.000
F-test 2.251 Prob > F 0.140
Akaike crit. (AIC) -83.652 Bayesian crit. (BIC) -80.981
*** p<.01, ** p<.05, *p<.1
Актуальные проблемы авиации и космонавтики - 2021. Тома 3
According to Table 2, we can see that trend has no significance (p-value is 0, 277) for the regression. Because of that we do not need to detrend our variables and can run the time-series ordinary least squares regression. The results are shown in Table 3.
Table 3
Time-series regression without trend
lunempl Coef. St.Err. t-value p-value [95% Conf Interval] Sig
lICT -.011 .006 -1.78 .094 -.023 .002 *
Constant 1.977 .145 13.61 0 1.669 2.285 * * *
Mean dependent var 1.718 SD dependent var 0.024
R-squared 0.166 Number of obs 18.000
F-test 3.175 Prob > F 0.094
Akaike crit. (AIC) -84.186 Bayesian crit. (BIC) -82.406
*** p<.01, ** p<.05, *p<.1
According to Table 3, we can see that the variable of ICT has a little significance (at 10% level) which still can be taken into consideration, and negative association with unemployment. These results allow us to make a conclusion that the increase of the variable of ICT by 1% leads to decrease of unemployment rate by 0,011% in case of India. Conclusion
The empirical results show that nowadays the process of digitalization in India has little, but negative impact on the unemployment rate. Because the Digital India programme has been launched quite recently, in 2015th, it will be possible to measure the real effect of its initiatives some years later.
References
1. OECD, The Digital Economy: Innovation, Growth and Social Prosperity [Electronic resource]. URL: http://www.oecd.org/digital/ministerial/meeting/New-Markets-and-New-Jobs-discussion-paper.pdf (appeal date 09.03.2021).
2. Brynjolfsson E., McAfee A. Race against the machine: How the digital revolution is accelerating innovation, driving productivity, and irreversibly transforming employment and the economy: Lexington, MA, Digital Frontier Press. 2011.
3. Rifkin, J. The Zero Marginal Cost Society: The internet of things, the collaborative commons, and the eclipse of capitalism: Basingstoke, Palgrave Macmillan. 2014.
4. Digitalization in India: Several opportunities for growth and transformation [Electronic resource]. URL: https://www.proschoolonline.com/blog/digitization-in-india-several-opportunities-for-growth-transformation (appeal date: 10.03.2021).
5. How Digital India will be realized: Pillars of Digital India [Electronic resource]. URL: https://digitalindia.gov.in/content/programme-pillars (appeal date: 10.03.2021).
6. World Bank data [Electronic resource]. URL: https://data.worldbank.org/indicator/ (appeal date: 17.03.2021).
© Ivanitskaia V. V., Tsvettsykh A. V., 2021
