Impact Of Green Energy, Green Innovation, And Fintech on Environmental Sustainability: The Moderating Role of Economic Policy Uncertainty.

Description

This dataset contains panel data for 20 countries over the period 2001–2022. It is compiled from publicly available sources, mainly the World Bank Open Data, Our World in Data, EPU Index and the WIPO Statistics Database. The dataset is designed for empirical analysis of the relationship between: • Environmental indicator (CO2 Emission) • Innovation indicators (Green Innovation) • Financial development indicators (FinTech) • Renewable energy transition (Green Energy) • Key macroeconomic control variables (GDP and Foreign Direct Investments) The data is cleaned, structured, and organized in a country-year panel format suitable for econometric modeling. Research Hypothesis are: H1: Green energy improves environmental sustainability. H2: Economic Policy Uncertainty moderates the direct relationship between green energy and environmental sustainability. H3: Green innovation significantly influences environmental sustainability. H4: Economic Policy Uncertainty moderates the relationship between green innovation and environmental sustainability. H5: FinTech significantly influences environmental sustainability. H6: Economic Policy Uncertainty moderates the relationship between FinTech and environmental sustainability. Importnat Findings are: 1. Green Energy, Green innovation and FinTech drive environmental sustainability 2. Economic Policy Uncertainty moderate outcomes in data distribution 3. Green innovation unpacking the Rebound Effect and Resource Intensity 4. Fintech's Dual Edge: The Tension Between Green Finance and Digital Energy Demands 5. MMQR reveals heterogeneous effects of green drivers on sustainability

Steps to reproduce

Data were compiled from publicly available secondary sources, primarily the World Bank Open Data and WIPO Statistics Database, following a systematic country-year extraction approach. Annual observations for 20 countries (2001–2022) were collected, cleaned, and harmonized to ensure consistency across variables. Data processing and organization were conducted using Microsoft Excel and statistical software (Stata) following standard panel data construction procedures. No experimental instruments or proprietary datasets were used.

Institutions

• The University of Chenab, Gujrat

  Punjab, Gujrat

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