|
on Information and Communication Technologies |
| By: | Thomas A. Fackler; Oliver Falck; Simon Krause; Thomas Fackler |
| Abstract: | Governments worldwide subsidize rural broadband expansion to address the urban-rural connectivity divide, but the economic benefits and costs remain unclear. This paper examines the causal effect of high-speed Internet on real estate prices and evaluates the fiscal effectiveness of rural broadband subsidies. Using a spatial regression discontinuity design and comprehensive micro-data, our identification strategy exploits variation at state borders from German states’ broadband expansion policies. We find that high-speed Internet availability (16 Mbit/s) increases rents by 3.8 percent (€17/month) and sale prices by 8 percent (€14, 700) compared to slower access at the discontinuity, with diminishing returns at higher speeds. The capitalization effects are demand-driven, as evidenced by increased broadband uptake, migration, and remote work adoption, while property supply remains unaffected. A cost-benefit analysis within the marginal-value-of-public-funds framework shows the economic surplus exceeds deployment costs for 90 percent of households, while property owners benefit from subsidies through higher property prices. |
| Keywords: | high-speed broadband internet, real estate prices, capitalization effect, policy evaluation, local public finance, spatial RDD, MVPF |
| JEL: | D60 H40 H70 L86 R20 |
| Date: | 2024 |
| URL: | https://d.repec.org/n?u=RePEc:ces:ceswps:_11595 |
| By: | Aomar Ibourk; Zakaria Elouaourti |
| Abstract: | This paper was originally published on erf.org.eg The digital divide in the financial sector has occurred through the development of financial technologies. These latest “FinTech” refers to technological innovations that have emerged in the financial system in recent years, which are the new channels for providing financial services. These innovations have disrupted traditional financing models by making financial transactions more secure and by reducing spatiotemporal constraints. The purpose of this paper is to investigate 1) the digital financial inclusion levels across the MENA countries? 2) which segments of the population are digitally financially excluded? 3) How the digital divide could preclude some segments from being financially included as a result of a lack of financial literacy (risks)? 4) and how FinTech could promote financial inclusion of segments excluded by the conventional financial system (women, elderly) and therefore the inclusive development of the MENA region (opportunities). To tackle these issues, we employed a mixed methodological approach (quantitative and qualitative) and by mobilizing micro-level data on 9, 053 individuals extracted from the World Bank's latest Global Findex 2021 database. First, our comparative analysis mobilizing the principal component analysis method to develop a Digital Financial Inclusion Index (DFII) highlighted that despite the various initiatives that have been undertaken in recent years, digital financial inclusion in the MENA region remains at a low level compared to other countries worldwide. Second, the results of the estimations on a Logit model pointed out that the educational level, labor force participation, information and communication technologies, and internet access are the main drivers of digital financial inclusion in the MENA region. Our work is original in that it provides grounded empirical evidence on the digital financial inclusion levels across MENA countries and investigates how to ensure that the digital divide in the financial sector "Financial Technologies" does not further exclude segments of the population (women, elderly...) financially excluded by the conventional financial system by increasing their digital financial literacy, promoting their participation in the labor market, and expanding access to mobile phones and the Internet. Considering the comprehensiveness of our sample, policy implications will be of great interest to financial sector regulators in MENA region to improve digital financial inclusion in the region, as these implications have been drawn from the micro-level experiences of individuals constituting our database. |
| Date: | 2023–07 |
| URL: | https://d.repec.org/n?u=RePEc:ocp:rpaeco:rpnn_74 |
| By: | Azizul Hakim Rafi; Abdullah Al Abrar Chowdhury; Adita Sultana; Abdulla All Noman |
| Abstract: | Given the fact that climate change has become one of the most pressing problems in many countries in recent years, specialized research on how to mitigate climate change has been adopted by many countries. Within this discussion, the influence of advanced technologies in achieving carbon neutrality has been discussed. While several studies investigated how AI and Digital innovations could be used to reduce the environmental footprint, the actual influence of AI in reducing CO2 emissions (a proxy measuring carbon footprint) has yet to be investigated. This paper studies the role of advanced technologies in general, and Artificial Intelligence (AI) and ICT use in particular, in advancing carbon neutrality in the United States, between 2021. Secondly, this paper examines how Stock Market Growth, ICT use, Gross Domestic Product (GDP), and Population affect CO2 emissions using the STIRPAT model. After examining stationarity among the variables using a variety of unit root tests, this study concluded that there are no unit root problems across all the variables, with a mixed order of integration. The ARDL bounds test for cointegration revealed that variables in this study have a long-run relationship. Moreover, the estimates revealed from the ARDL model in the short- and long-run indicated that economic growth, stock market capitalization, and population significantly contributed to the carbon emissions in both the short-run and long-run. Conversely, AI and ICT use significantly reduced carbon emissions over both periods. Furthermore, findings were confirmed to be robust using FMOLS, DOLS, and CCR estimations. Furthermore, diagnostic tests indicated the absence of serial correlation, heteroscedasticity, and specification errors and, thus, the model was robust. |
| Date: | 2024–12 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2412.16166 |
| By: | Jaelyn S. Liang; Rehaan S. Mundy; Shriya Jagwayan |
| Abstract: | E-commerce is rapidly transforming economies across Africa, offering immense opportunities for economic growth, market expansion, and digital inclusion. This study investigates the effects of e-commerce on select African regions. By utilizing readiness factors, including mobile money deployment, GDP per capita, internet penetration, and digital infrastructure, the preparedness of African countries for e-commerce adoption is quantified, highlighting significant disparities. Through case studies in urban and rural areas, including Lagos, Kano, Nairobi, and the Rift Valley, the study shows e-commerce's significant effects on small and medium-sized enterprises (SMEs), employment, and market efficiency. Urban centers demonstrated significant gains in productivity and profitability, whereas rural regions experienced slower growth due to limited internet access and infrastructural barriers. Despite these challenges, localized solutions such as mobile money systems and agricultural e-commerce platforms are bridging gaps. This study highlights the significant potential of e-commerce in Africa while emphasizing the need for targeted investments and strategies to address existing regional disparities. |
| Date: | 2024–12 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2412.03879 |
| By: | Aritri Chakravarty (Assistant Professor, Madras School of Economics, Chennai, Tamil Nadu, India, 600025) |
| Abstract: | The NSSO report (2015) shows that 41 percent of the rural households in India have accessed information and 34 percent households have used them. This paper explores the households’ use of information and understand their preference of information sources and their determinants. Households with better socio-economic conditions access information and from multiple sources. Media has the highest access while public sources have the lowest. Most of the households accessing information use it but the source-wise adoption rates show that, the source with the highest access, media, has the lowest use. This study tries to identify potential factors that lead to a systematic difference in using patterns across households and also across sources. Almost 80 percent of the households accessing information have used it and those not using information have cited lack of credit as a big hurdle to adoption among other reasons. Source-wise disaggregation of use shows that media has the lowest use at around 60 percent, even though it is the highest accessed resource. For all other sources, the share hovers around 80 to 90 percent. The analysis uses a Heckman Selection model to identify the potential factors that drive information use and also the differences between users and non-users of information from media. Overall, use of information is driven more by education and availability of credit than by other factors directly. Caste doesn’t appear to be a significant determinant of use directly, but obviously through the caste dynamics that shape different outcomes like education, access to information and access to credit. This analysis finds evidence to support the existing argument that development of human capital is crucial in processing information and using it for efficiency gains. |
| Keywords: | Agriculture, Information, Sample selection bias, human capital |
| JEL: | Q12 O13 D81 |
| Date: | 2024–12 |
| URL: | https://d.repec.org/n?u=RePEc:mad:wpaper:2024-273 |