MIF and MIFER explanation

Beyond the Buzzwords: Understanding Measurable Impact Funds (MIFs) and the MIFER Standard

The world of sustainable investing is at a crossroads. While more capital than ever is flowing toward investments labeled "ESG," "sustainable," or "impact," investors are increasingly asking a critical question: Is my money truly making a difference?
The unfortunate reality is that the current landscape is fraught with ambiguity. Vague claims, inconsistent ratings, and a lack of standardized metrics have given rise to "impact washing"—the practice of overstating or misrepresenting the positive impact of an investment.1 Investors are left to navigate a confusing market, unable to verify if their capital is driving tangible change or simply funding a clever marketing campaign.3
At Impacta.io, we believe a new standard is necessary. We are moving beyond the limitations of traditional ESG and impact funds by introducing a framework built on mathematical clarity and radical transparency: Measurable Impact Funds (MIFs) and the Measurable Impact Fund Efficiency Ratio (MIFER).

What is a Measurable Impact Fund (MIF)?

A Measurable Impact Fund (MIF) is a new class of investment vehicle where the positive impact of every dollar is quantified and tracked. Unlike conventional funds, MIFs possess a dual valuation:
Net Asset Value (NAV): This is the traditional financial valuation, representing the market value of the stocks held within the fund's portfolio.
Impact Value: This is the fund's value measured in tangible, real-world impact units.
For example, in a Climate Change Abatement MIF, an investment of £270 might correspond not only to £270 of market value in the fund's underlying stocks but also to the purchase of one metric tonne of CO2 emission savings.
Each MIF is composed of a carefully selected portfolio of publicly traded companies. These companies are chosen for two key reasons: first, for their proven merits in the fund's specific impact area (like CO2 abatement or providing clean water), and second, for their financial robustness. This ensures that the companies have the financial strength to survive and deliver on their projected future impact.

What is the Measurable Impact Fund Efficiency Ratio (MIFER)?

The MIFER is the proprietary engine that powers our MIFs. It is a clear, first-principles metric that shows how efficient an investment in a company is at creating a specific positive outcome.4
MIFER = Market Value of a Company / The Company's Future Measurable Impact
For instance, within a Clean Water and Sanitation MIF, the goal is to maximize the number of new people who gain access to clean drinking water for every pound invested. To calculate the MIFER for a company in this fund, we divide its market value by the marginal number of new individuals who will gain access to drinking water in the foreseeable future as a result of that company's operations.
A lower MIFER is better, as it signifies that less capital is required to achieve a unit of positive impact.
This calculation is not a simple guess. It is the result of deep research techniques that incorporate reinforcement learning models, direct company interviews, and all publicly available data to forecast a company's future impact with a high degree of confidence.5 This methodology was first defined for climate-abatement funds and has since been expanded to other critical impact areas.5

The MIF Advantage: Why It Surpasses ESG and Conventional Impact Funds

MIFs and the MIFER standard were designed to directly address the critical flaws in today's sustainable investing landscape.

1. From "Impact Washing" to Verifiable Proof

The Problem: The sustainable investment market is plagued by "impact washing," where managers make misleading claims about a fund's benefits to attract capital, often without evidence.1 Many funds blur the lines between ESG integration—which is about managing financial risk—and true impact investing, which is about intentionally creating positive outcomes.7
The MIF Solution: MIFER replaces vague promises with mathematical proof. It provides a direct, quantifiable link between an investment and a tangible result, such as a tonne of CO2 removed or a person provided with clean water.5 This moves the conversation from marketing narratives to data-driven conviction, ensuring every claim is backed by rigorous analysis.

2. From Aggregate Confusion to Apples-to-Apples Comparison

The Problem: ESG ratings are notoriously inconsistent. Different rating agencies use different data, apply different weightings, and focus on different attributes, leading to "aggregate confusion" where the same company can receive vastly different scores.5 This lack of standardization makes it nearly impossible for investors to make reliable comparisons.9
The MIF Solution: MIFER provides a single, standardized, and transparent yardstick: the cost per unit of impact. This allows for a direct, apples-to-apples comparison between different companies and funds. An investor can clearly see which investment is projected to be the most efficient at achieving a specific goal, removing the guesswork inherent in opaque ESG scores.

3. From Indirect Proxies to Real-World Outcomes

The Problem: Many ESG metrics and "impact" funds focus on indirect proxies rather than real-world change. For example, a fund might divest from high-emission assets to lower its portfolio's carbon footprint, but this doesn't reduce emissions in the real economy—it simply transfers ownership of those assets.7 Furthermore, ESG ratings often measure the world's potential impact on a company's bottom line, not the company's positive impact on the world.11
The MIF Solution: MIFs are built to finance tangible, physical outcomes. The methodology is product-focused, analyzing the lifecycle impact of a company's actual products and services, not just its corporate policies.5 The objective is to channel capital toward companies that are actively solving problems, ensuring that your investment contributes to measurable progress in the real world.

4. From Black Boxes to Radical Transparency

The Problem: The methodologies behind ESG ratings are often a "black box," relying on opaque algorithms and subjective weightings that are hidden from investors.5 This lack of transparency can conceal biases and makes it difficult to trust the results.11
The MIF Solution: The principle behind MIFER is simple and transparent. While the underlying analysis is complex, the output is a clear and understandable ratio. We believe that investors have a right to know how their impact is being measured. Our commitment is to provide that clarity, building a foundation of trust through data.
By focusing on quantifiable efficiency and real-world results, Measurable Impact Funds represent the necessary evolution of sustainable finance—a shift from ambiguity to accountability.

Referenced Sources and Further readings

• Adisorn, Thomas, Lena Tholen, and Thomas Götz. "Towards a digital product passport fit for contributing to a circular economy." Energies, 14(8):2289, 2021.1
  Bataille, Chris, Céline Guivarch, Stephane Hallegatte, Joeri Rogelj, and Henri Waisman. "Carbon prices across countries." Nature Climate Change, 8(8):648-650, 2018.1
• Berg, Florian, Julian F Koelbel, and Roberto Rigobon. "Aggregate confusion: The divergence of esg ratings." Review of Finance, 26(6):1315-1344, 2022.1
  Best, Rohan and Qiu Yue Zhang. "What explains carbon-pricing variation between countries?" Energy Policy, 143:111541, 2020.1
  
• Bolliger, Guido and Dries Cornilly. "Sustainability attribution: The case of carbon intensity." The Journal of Impact and ESG Investing, 2021.1
  
• Bolton, Patrick and Marcin Kacperczyk. "Do investors care about carbon risk?" Journal of financial economics, 142(2):517-549, 2021.1
  
• Cepni, Oguzhan, Riza Demirer, and Lavinia Rognone. "Hedging climate risks with green assets." Economics Letters, 212:110312, 2022.1
  
• Chatterji, Aaron K, Rodolphe Durand, David I Levine, and Samuel Touboul. "Do ratings of firms converge? implications for managers, investors and strategy researchers." Strategic Management Journal, 37(8):1597-1614, 2016.1
  
• Dortfleitner, G, G Halbritter, and M Nguyen. "Measuring the level and risk of corporate responsibility-an empirical comparison of different esg ratings approaches." Journal of Asset Management, 17(7):450-466, 2015.1
  
• Engle, Robert F, Stefano Giglio, Bryan Kelly, Heebum Lee, and Johannes Stroebel. "Hedging climate change news." The Review of Financial Studies, 33(3):1184-1216, 2020.1
  
• Galatola, Michele and Rana Pant. "Reply to the editorial "product environmental foot-print-breakthrough or breakdown for policy implementation of life cycle assessment?"" The International Journal of Life Cycle Assessment, 19:1356-1360, 2014.1
  
• Hicks, John R and Roy GD Allen. "A reconsideration of the theory of value. part i." Economica, 1(1):52-76, 1934.1
  
• International Organization for Standardization. "Greenhouse Gases: Carbon Footprint of Products: Requirements and Guidelines for Quantification." 2018.1
  
• Mach, Petr. "The application of lagrange multipliers in consumer choice theory." Economic Studies & Analyses/Acta VSFS, 16(1), 2022.1
  
• Pazos, Jay. "Introducing the Climate Efficiency Ratio (CER): A New Metric for developing Climate-Finance Applications." SSRN, 2023.1
  
• Renneboog, Luc, Jenke Ter Horst, and Chendi Zhang. "Is ethical money financially smart? nonfinancial attributes and money flows of socially responsible investment funds." Journal of Financial Intermediation, 20(4):562-588, 2011.1
  
• Semenova, Natalia and Lars G Hassel. "On the validity of environmental performance metrics." Journal of Business Ethics, 132:249-258, 2015.1
  
• Starks, Laura T. "Environmental, social, and governance issues and the financial analysts journal." Financial Analysts Journal, 77(4):5-21, 2021.1
  
• Sutton, Richard S and Andrew G Barto. Reinforcement learning: An introduction. MIT press, 2018.1
  
• Tyndall Centre for Climate Change Research and W Neil Adger. "The Stern Review on the economics of climate change." 2006.1
  
• Vandenbergh, Michael P, Thomas Dietz, and Paul C Stern. "Time to try carbon labelling." Nature Climate Change, 1(1):4-6, 2011.1
  
• Young, Martin R. "A minimax portfolio selection rule with linear programming solution." Management science, 44(5):673-683, 1998.1