Three essays on anti-consumerism, anti-hedonism and environmentalism, and economic growth

Rapid environmental changes and technological developments are crucial for sustainable economic growth goals. This dissertation aims to highlight the consequences of firms' and consumers' behavior for society in the presence of external influences exerted by environmental doctrines. In addition, it offers a comparison between machine learning and time series-based methodologies in predicting economic growth. The first chapter delves into the dichotomy between hedonic and environmental attributes of goods in a market characterized by vertical differentiation with heterogeneous consumer preferences. It examines how anti-hedonism and environmentalism influence market outcomes and societal welfare, revealing unexpected harmful effects. A relatively high level of environmental doctrines is detrimental to the ecological surplus. The second chapter explores anti-consumerism, distinguishing between its roles as a psychic reward or cost and its impact on pricing strategies, firm profits, and social welfare within markets for horizontally differentiated goods. The analysis demonstrates that the beneficial societal outcomes are predominantly associated with incentive-based (carrot) approaches rather than punitive (stick) measures. The final chapter compares traditional time series analysis with machine learning, incorporating a variety of economic factors for different strategies in forecasting the real United States Gross Domestic Product (GDP). The K-Nearest Neighbour (KNN) model enhances short-term accuracy predictions. In contrast, linear regression, including financial and macroeconomic factors, enhances long-term accuracy, offering valuable insights for data-driven economic decision-making. This dissertation sheds light on consumer behavior, firms strategies, and predictive modeling, suggesting pathways for more sustainable and informed economic practices.