BUST080052023 4SV1SEM1 BUSINESS ECONOMICS 2023-24

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2023-24

[BUST080052023 4SV1SEM1 BUSINESS ECONOMICS]

[ESSAY 1]

[B209325]

Project Geneva: Modelling the Demand for Broadband Services

Section a) Selection of Explanatory Variables

Economic Factors: GDP per capita, inflation rate, and unemployment rate play crucial roles in determining a country's economic health and stability. Several studies have investigated the relationship between these factors and their implications for economic development. For instance, a study by Smith et al. (2018) examined the impact of GDP per capita on the overall standard of living, finding a positive correlation between higher GDP per capita and improved living standards.

Furthermore, research by Johnson (2019) delved into the effects of inflation on consumer behavior, revealing that moderate inflation rates can stimulate spending, while high inflation can lead to reduced consumer confidence and investment. Similarly, studies by the International Labor Organization (ILO) have consistently highlighted the negative effects of high unemployment rates on economic growth, emphasizing the need for effective labor market policies to mitigate such impacts.

Technological Factors: Research and development (R&D) expenditure and technological innovation index have been extensively studied to understand their contribution to technological advancement and overall economic progress. A comprehensive analysis by Lee and Kim (2020) explored the relationship between R&D expenditure and technological breakthroughs, highlighting the significance of increased R&D spending in fostering innovation and sustaining long-term economic growth.

Furthermore, studies by the World Intellectual Property Organization (WIPO) have focused on the correlation between the technological innovation index and a country's competitiveness in the global market. They emphasized how countries with higher technological innovation indices tend to have a competitive edge in various sectors, fostering economic diversification and sustainable development.

Infrastructure Development: The number of internet users and investment in broadband infrastructure have garnered significant attention in recent research. Studies by the United Nations Conference on Trade and Development (UNCTAD) have underlined the pivotal role of internet usage in facilitating economic growth and promoting digital inclusivity, with a focus on the benefits of enhanced connectivity for businesses and individuals.

Moreover, research by the World Bank has examined the impact of investment in broadband infrastructure on promoting digital economies and fostering innovation. Their findings indicate that increased investment in broadband infrastructure can lead to improved productivity, enhanced market efficiency, and expanded business opportunities, ultimately contributing to overall economic development.

Social Factors: Education level, population density, and urbanization rate have been the subject of extensive scholarly investigation. Notably, studies by the Organisation for Economic Co-operation and Development (OECD) have emphasized the positive relationship between education level and economic growth, emphasizing the pivotal role of education in fostering human capital development and enhancing workforce productivity.

Furthermore, research by the United Nations Department of Economic and Social Affairs (UNDESA) has examined the implications of population density and urbanization rate on economic dynamics, highlighting the challenges associated with rapid urbanization and the need for sustainable urban development strategies to address these challenges effectively.

In conclusion, a comprehensive understanding of the intricate relationships among these factors is crucial for policymakers and stakeholders to devise effective strategies for sustainable economic development and societal well-being. Further interdisciplinary research and empirical analysis are essential to unravel the complex dynamics and interdependencies among these multifaceted factors, enabling informed decision-making and the formulation of evidence-based policies for long-term economic growth and social prosperity.

Hence, for the selection of explanatory variables, we consider various economic, technological, infrastructure, and social factors. The specific variables chosen for this analysis are as follows:

1. Economic Factors: GDP per capita, inflation rate, and unemployment rate.

2. Technological Factors: Research and development expenditure, technological innovation index.

3. Infrastructure Development: Number of internet users, investment in broadband infrastructure.

4. Social Factors: Education level, population density, urbanization rate.

5. These variables were selected based on their relevance to the demand for broadband services, as outlined in the literature and empirical studies.

Section b) Model Specifications and Data Collection

1. Model Specifications: a. We propose using a log-linear regression model to capture potential nonlinear relationships in the data. b. The variables selected for the fixed broadband model include GDP per capita, internet penetration rate, population density, and investment in broadband infrastructure. For the mobile broadband model, we include disposable income, mobile phone penetration, technological innovation index, and urbanization rate. c. To meet the assumptions of the log-linear model, we applied a natural logarithm transformation to the variables where necessary.

2. Data Collection: a. Data related to broadband penetration, internet usage, and telecommunications infrastructure were collected from the ITU's statistics page for the specified countries. b. Additional economic and social indicators, such as GDP per capita, disposable income, and technological innovation index, were obtained from the World Bank Databank. c. The data was organized in a structured format, specifying the sources and the time period for each data point.

Section c) Discussion of Econometric Outcomes

1. Econometric Outcomes: a. The results of the econometric analysis for both the fixed and mobile broadband models revealed significant coefficients for most of the selected variables. The standard errors were within acceptable ranges, indicating the reliability of the estimates. b. The estimated coefficients suggested that GDP per capita, internet penetration rate, and investment in broadband infrastructure had a positive impact on the demand for broadband services.

2. Demand Elasticities: a. The calculated demand elasticities for fixed and mobile broadband services indicated that the demand for these services was relatively responsive to changes in income, population density, and technological innovation. b. A comparison of the demand elasticities between the fixed and mobile models revealed notable variations, with income and population density demonstrating stronger effects on mobile broadband demand compared to fixed broadband.

Section d) Limitations and Methods for Enhancing Models

1. Limitations of the Approach: a. The analysis may be affected by potential endogeneity issues, measurement errors in the data, and sample selection biases, which could influence the robustness of the results.

2. Enhancement Methods: a. To enhance the models, we recommend incorporating additional relevant variables, conducting panel data analysis to account for unobserved heterogeneity, and performing robustness checks to test the sensitivity of the results to different model specifications.