The Causation Effect between ESG and Profitability

One-Step Causation and Self-Reinforcing Cycles

In Damodaran’s post and video session about ESG, he often highlights the causation between being “good” (practicing strong ESG principles) and being “profitable.” It is true that many articles claim companies with good ESG practices are more likely to achieve superior profitability. However, the causation direction may be different. It could be that companies with higher profitability simply have more resources to brush up their ESG marketing and practices.

This perspective raises the classic statistical pitfall of reverse causation or endogeneity, where it’s unclear if ESG practices lead to profitability or if profitability enables stronger ESG initiatives. However, if we focus solely on causation direction, we risk missing the broader point.

Mutually Reinforcing Cycles

There is a type of relationship like this often described as mutually reinforcing or self-reinforcing cycles. In this dynamic, two factors drive each other in a continuous loop, making it difficult (or irrelevant) to determine which is the true origin. Instead of focusing on the “first cause,” the key is to engage with the cycle to achieve a desired outcome.

For example:

  • Companies with strong ESG practices may experience enhanced reputations, customer loyalty, and operational efficiencies that improve profitability.
  • Increased profitability, in turn, provides companies with more resources to further invest in or promote their ESG practices.

This cycle creates a feedback loop where both ESG and profitability can grow together, and the origin point becomes less relevant than engaging with the cycle to produce desired results.

Statistical Testing for Self-Reinforcing Cycles

To analyze this type of relationship, several statistical tests and models are well-suited for examining the reciprocal or cyclical influence of ESG and profitability:

  1. Cross-Lagged Panel Analysis
    This test uses time-lagged data to analyze if each variable predicts changes in the other over time.

  2. Vector Autoregression (VAR)
    A dynamic model that allows each variable to be expressed as a function of its own past values and the past values of the other variable, revealing potential reinforcement.

  3. Structural Equation Modeling (SEM)
    SEM can help model the complex, bi-directional relationship between ESG and profitability, including indirect effects and latent variables that might influence both.

  4. Granger Causality Test
    Running this test in both directions (e.g., from ESG to profitability and vice versa) can provide preliminary insights into whether changes in one precede the other, even if it does not confirm true causation.

Big Picture Takeaway

Instead of identifying a single cause, the goal is to understand and leverage the ESG-profitability cycle to support a company’s long-term objectives. This perspective encourages a pragmatic approach where the focus shifts to participating in and amplifying the cycle rather than proving which factor is primary. This way, companies can create a sustainable impact that aligns ESG goals with financial performance.