Unveiling Behavioral Economics through meat consumption in the EU by examining macroeconomic and ESG Factors with multiple econometric models
Description
Research Hypothesis and Objectives This study investigates the determinants of meat consumption in the European Union (EU) by integrating macroeconomic and ESG (Environmental, Social, and Governance) factors within a behavioral economics framework. The key research question is: How do economic conditions, environmental sustainability factors, and demographic characteristics influence meat consumption patterns in the EU? The main hypotheses tested include: Economic factors: GDP and GDP per capita (PPP-adjusted) positively influence meat consumption, while unemployment reduces it. Environmental factors: Methane emissions correlate positively with meat consumption, while livestock availability affects demand. Policy factors: Government expenditure and inflation may impact consumption patterns. Demographics: Population growth and income classification influence meat demand. Data Description The dataset consists of panel data from 27 EU member states (2000–2021), with 580 observations. Sources include World Bank, FAO, Eurostat, and the European Environment Agency. Key Variables: Dependent: Meat consumption (kg per capita per year). Independent: GDP, GDP per capita (PPP), unemployment, inflation, livestock availability, methane emissions, government expenditure, and population growth. Findings and Interpretation GDP per capita and GDP PPP are strong predictors of higher meat consumption, while unemployment negatively impacts demand. Methane emissions significantly correlate with meat consumption, linking livestock production to environmental degradation. Livestock availability influences demand, though less than economic conditions. Government expenditure and inflation show no significant effect. Population growth does not directly affect meat consumption, and income ranking is not a strong determinant. Policy Implications Sustainability strategies: Carbon pricing for high-emission livestock and incentives for plant-based diets. Economic measures: Strengthening employment programs to maintain dietary stability. Environmental regulations: Stricter livestock emission policies and investments in alternative protein sources. Conclusion This dataset offers valuable insights for policymakers and researchers on economic, environmental, and policy-driven influences on food consumption. It can be used to develop predictive models, assess economic policies, and analyze sustainability strategies for balancing meat consumption with environmental goals.
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Data Collection and Reproducibility This study employs a structured econometric approach to analyze meat consumption patterns in the European Union (EU), integrating macroeconomic, environmental, and demographic factors. The dataset was compiled using publicly available and standardized sources, ensuring reproducibility and comparability across EU countries. Data Sources and Collection Process The dataset consists of panel data from 27 EU countries spanning 2000–2021, obtained from the following authoritative sources: World Bank Open Data: GDP, GDP per capita (PPP-adjusted), unemployment rate, inflation, and population growth. Food and Agriculture Organization (FAO): Annual per capita meat consumption and livestock production index. Eurostat: Government expenditure on economic and agricultural policies. European Environment Agency (EEA): Methane emissions from livestock agriculture. The dataset was structured in balanced panel format, allowing for the analysis of both cross-country and time-series variations in meat consumption determinants. Methodology and Analytical Framework To ensure data accuracy and consistency, the following protocols were applied: Data Cleaning & Standardization: Missing values were handled using linear interpolation when necessary, ensuring a complete dataset for econometric modeling. Software Used: The data was processed using R and Stata, which facilitated statistical analysis, hypothesis testing, and model validation. Econometric Models: Three regression models were estimated: Fixed Effects (FE) Model to control for country-specific unobserved heterogeneity. Random Effects (RE) Model selected via the Hausman Test for efficiency in capturing between-country variance. Generalized Estimating Equations (GEE) to correct for autocorrelation and ensure robust standard errors. Multicollinearity & Model Diagnostics: Variance Inflation Factors (VIF) were used to assess multicollinearity among predictors, while QIC and QICC criteria guided model selection. Reproducibility and Use Cases The dataset can be replicated using publicly accessible economic and environmental databases. Researchers can: Extend the analysis by incorporating additional behavioral or nutritional factors influencing meat consumption. Validate findings by applying alternative econometric techniques such as machine learning models. Use it for policy simulations to predict how macroeconomic shifts or environmental regulations may affect meat consumption trends in the EU. By offering a transparent methodology, standardized data sources, and reproducible modeling techniques, this study provides a reliable framework for analyzing the economic and environmental drivers of food consumption in the EU.
Institutions
- Geoponoko Panepistemio Athenon Schole Epharmosmenon Oikonomikon kai Koinonikon Epistemon