A Quantitative Study on the Utilization of ESG Financial Market Performance Metrics in Forecasting Finland's Economic Trajectory

Abstract

This thesis investigates the utility of ESG (Environmental, Social, and Governance) financial market performance metrics in forecasting economic trajectory, particularly that of Finland’s. Inherently shaped by The Nordic Welfare Model, Finland’s economy has endured persistent stagnation post-2008 financial crisis, attributed to the culmination of ageing population, static labour productivity and inadequate investment. In light of the emergence of ESG-oriented finance in recent years, this study seeks to assess the potential predictive relationships between ESG financial metrics and key macroeconomic indicators, specifically GDP, inflation and employment. This analysis is supplemented by a comparison to traditional financial market performance, and five-year economic forecasts generated using two models incorporating ESG metrics. The scope of the study consists of quarterly data from Q1 2011 to Q4 2024, focusing on domestic aggregate macro data, which excludes sector-level and pillar-specific ESG data. The scope also excludes any aim to prove causality, rather focusing on correlation, and explicitly accounting for structural breaks in the time series, treating the temporal sequence as a monolith.

The research rationale is reinforced by Stakeholder Theory (Freeman 1984) and Creating Shared Value (Porter & Kramer 2011), which forms the cornerstones of the theoretical framework. The framework is further complemented by relevant academic research and a contextual link to the mechanisms of The Nordic Welfare Model, allowing for a rational formulation of a hypothesis that Finnish ESG-screened firms exhibiting strong financial performance would correlate with thriving economic growth, and vice-versa. The variable chosen to represent those firms is a gross index OMXSUSTAINFIGI, which represents Finnish companies screened for defined ESG criteria. The variable was controlled with a global ESG index and compared to a Helsinki Stock Exchange all-share index OMXHGI. The empirical analysis was conducted in Python through econometric methods. The main tool applied was the Vector Error Correction Model (VECM) to test both short-term dynamics and long-run equilibrium relationships. Stationarity was tested using the Augmented Dickey-Fuller test, and cointegration was assessed via the Johansen method. Model accuracy was evaluated using RMSE and MAE.

The results suggest that ESG performance demonstrates a moderately to significantly positive link to GDP and employment in the short run and to GDP and inflation in the long run, though short-term correlations diminish once controlling for global influences. ESG-based models performed competitively with traditional benchmarks, particularly in forecasting GDP and inflation, though they underperformed in predicting employment. Employment was the only variable found to adjust significantly to restore long-run equilibrium. Forecasts project modest economic recovery over the next half-decade, though all models exhibited systematic forecast biases. It was concluded that ESG financial performance holds value as a complementary tool in macroeconomic forecasting, particularly in sustainability-oriented economies such as Finland. However, limitations such as potential structural breaks in the time series and the requisite for disaggregated ESG data were noted as areas for further research.