The Impact of Big Data on Economic Forecasting and Policy Making (Published)
The advent of big data has revolutionized various fields, including economic forecasting and policy making, by offering unprecedented access to vast amounts of information and sophisticated analytical tools. This transformation is reshaping how economists predict economic trends and how policymakers design and implement effective strategies. Traditionally, economic forecasting relied on historical data analysis and econometric models, which, despite their utility, faced significant limitations. Data scarcity, time lags, and accuracy issues often hindered precise forecasting. However, the rise of big data, fueled by technological advancements and the proliferation of digital information, has introduced new dimensions to economic analysis. Sources of big data now encompass social media, financial transactions, the Internet of Things (IoT), and extensive government and public data, providing real-time insights into economic activities. The integration of big data into economic forecasting employs various advanced techniques and tools. Machine learning and artificial intelligence (AI) algorithms can process and analyze massive datasets, identifying patterns and trends that were previously undetectable. Data mining techniques enable the extraction of valuable information from large and complex datasets, while real-time analytics facilitate immediate decision-making based on current data. For instance, predictive analytics in stock markets can forecast price movements with greater accuracy, while analysis of consumer spending patterns offers valuable insights into retail trends. Economic policy making benefits immensely from the incorporation of big data. Data-driven decision-making allows for the design of policies that are more responsive to real-time economic conditions and tailored to specific contexts. By continuously monitoring and evaluating policy impacts through real-time data, policymakers can adjust strategies promptly, ensuring greater effectiveness. This dynamic approach contrasts sharply with traditional methods, which often relied on delayed and less comprehensive data. In monetary policy, real-time analysis of inflation indicators allows central banks to adjust interest rates more precisely. Social policies also benefit, as big data helps identify and address welfare needs more effectively, ensuring that resources are allocated where they are most needed. The benefits of incorporating big data into economic forecasting and policy making are manifold. Enhanced accuracy and precision in predictions lead to better-informed decisions. Timeliness and responsiveness are significantly improved, allowing for proactive rather than reactive strategies. Comprehensive insights from diverse data sources provide a holistic view of economic conditions, while advanced predictive capabilities enable the anticipation of future trends. However, the integration of big data also presents challenges. Data privacy and security concerns are paramount, as the collection and analysis of large datasets raise ethical and legal issues. Ensuring data quality and reliability is critical, as inaccuracies can lead to misguided decisions. Technical barriers, such as the need for specialized skills and infrastructure, can impede the effective use of big data. Addressing these challenges requires robust frameworks for data governance and continuous investment in technology and skills development. Looking ahead, the future prospects of big data in economic forecasting and policy making are promising. The integration of emerging technologies such as blockchain and advanced AI will further enhance data security, transparency, and analytical capabilities. Global collaboration and data sharing initiatives will enable more comprehensive and accurate economic analysis. As policymakers and economists continue to adapt to this data-driven paradigm, the ongoing transformation promises to yield more effective and efficient economic strategies, ultimately fostering greater economic stability and growth. Big data is transforming economic forecasting and policy making by providing deeper insights, enhancing accuracy, and enabling more responsive and effective strategies. While challenges remain, the continuous evolution of technology and data practices holds great potential for the future of economics.
Keywords: Big Data, Forecasting, Impact, Policy
Impact of Globalization on the Economic Development of Nigeria (Published)
This research aims to investigate the effects of globalization on Nigeria’s economic development. Globalization has helped Nigeria, a developing nation, compete with other established nations, according to various opinions on its effects, both positive and negative. The study’s goal was to determine the impact of globalization on the Nigerian economy. The researcher consequently evaluated the body of studies on how globalization has affected Nigeria’s economic progress. Thus, the notions of globalization and development, as well as various aspects of Nigeria’s development, are critically analyzed, as is the effect of globalization on the global economy. The outcome showed that all traditional economic development factors, including private investment, public investment, and debt series, as well as indicators of economic integration (trade openness and financial integration), were non-stationary. The study also proved that trade openness significantly boosted Nigeria’s economy. However, at a 10% threshold of importance, the effect of financial integration on the economy is negligible. The study came to the conclusion that if Nigeria’s economy completely integrated with the rest of the globe, it would gain more from globalization. Therefore, the report advocated for the elimination of all restrictions on commerce and money flow. The growth of the Nigerian economy to keep up with globalization is recommended based on analysis of the effects of globalization on economic development. It was therefore deduced that “if appropriate measures are not implemented, Nigeria may not participate in this process, leading to the globalization of poverty rather than wealth”.
Keywords: Development, Economic, Globalization, Impact
Impact Analysis of Mede Telila Small Scale Irrigation Scheme on House Poverty Alleviation: Case of Gorogutu District in Eastern Haratghe Oromia National Regional State Ethiopia (Published)
The main objective of the study was to access the impact of Mede Telilasmall-scale irrigation scheme on household poverty alleviation in Gorogutu District of Eastern Hararghe, Oromia National Regional State, Ethiopia. To achieve the objective of the study, data were collected from 200 households, 100 from participants and 100 from non-participants in the irrigation scheme, in the study district. Descriptive statistics, the Foster, Greer and Thobeck (FGT) poverty indices and Propensity Score Matching (PSM) were used to analyze the data. The study revealed that the small-scale irrigation scheme significantly reduced the incidence, the depth and the severity of households’ poverty in the study district. The empirical model also revealed that access to the irrigation scheme significantly influenced the households’ consumption expenditure level. The Average Treatment effect of Treated (ATT) indicated that, the per capita consumption expenditure of irrigation users is 25% more than non-users of irrigation. These results indicate that the small-scale irrigation scheme improved the livelihood of households in the study district.
Keywords: Consumption Expenditure, Ethiopia, Gorogutu, Household Poverty, Impact, Irrigation Scheme