Skip to content


This page includes information on publications, project reports, the software environment, and background information on the methodology.

Software downloads

The R code underlying the PACTA tool for equity and corporate bond portfolios can be downloaded from GitHub here.

Please note that while the methodology is available for anyone to apply, data licensing means we are not able to directly share the underlying asset level and financial data that drives the tool. If you are interested in accessing the necessary data, please contact us.

Background information

This section explains the general modelling principles, data sources, global parameters, and caveats of the scenario analysis tool (PDF available). It aims to shed more light on the methodology, key features, and parameters of the analysis and to help you to understand the analysis results.

A detailed description of the result interpretation, modelling principles, and data used, as well as a paper that presents the methodology and the underlying equations, can be found in the XYZ (Paris Agreement Capital Transition Assessment Background Briefing and The alignment of global equity and corporate bonds markets with the Paris Agreement – A new accounting framework).

The following briefly summarizes the key modelling principles in PACTA:

  • Allocating scenario values to benchmark portfolio: PACTA calculates the expected benchmark exposure for each technology in the specific asset class by taking the current exposure in the respective asset class and geography and multiplying the rate of change of the technology as provided by the scenario (e.g. the IEA’s 1.5°C compatible NZE 2050 scenario). The build-out percentages follow a simple “”market share approach”” under which the companies in the investable universe are assumed to adjust production capacity in line with the scenario, consistent with their market share, i.e. the market shares of all companies remain constant for the benchmark;
  • Allocating asset-level production data to companies along the ownership tree: The model assesses the scenario alignment of financial portfolios with a 5-year forward-looking time horizon. this period is limited to the time horizon of capital expenditure planning for which data can be tracked at a meaningful level. While this time horizon may differ across sectors, a homogenous period is chosen to allow for the comparability of results;
  • The model applies traditional financial accounting principles, notably where possible the equity ownership principle (e.g. 1% ownership of a company assumes 1% ownership of assets). Where data is not available, the majority owner is allocated 100% of the ownership. Ownership along the different levels of the ownership tree is determined based on financial data.

PACTA uses a general methodological framework which compares the technology build-out plans with climate scenarios, as explained before. While this core methodology is set, there are several parameters that can be set to answer specific research questions. The model parameters that can be set include:

  • The scenario against which the portfolio is compared can be chosen to reflect a specific decarbonization transition pathway and the corresponding technology assumptions as accurately as possible. This also ensures the impact of underlying scenario assumptions can be analysed and compared;
  • Allocation Method used to allocate company build out plans to the portfolio. This choice determines whether the assessment reflects the contribution of the portfolio to the transition (ownership approach) or the exposure of the portfolio to transition risk (portfolio weight approach);
  • The scenario geography can be set to show the alignment of the portfolio scoped to regionally specific scenario benchmarks and the production capacity within that same region based on location of physical assets. This can, for instance, be used to highlight the most relevant regions to act on;
  • The equity market shows the regionally specific alignment of the portfolio based on company domiciles, highlighting how geographic investment mandates impact alignment results;
  • Benchmark portfolio to either assess the current build out plans of the analysed portfolio against its own scenario-compatible values (referred to as the “Aligned Portfolio”), or to compare the portfolio to a specific benchmark such as an asset class appropriate market portfolio under a scenario-compatible decarbonization pathway (“Aligned Benchmark”);
  • Peer group allows the comparison of the portfolio with a set of the most relevant peers available (subject to data availability, which may be restricted depending on the context of the analysis).

Scenarios represent potential sector and technology pathways to reach certain climate targets. While being based on the best available scientific research, there remain uncertainties around the outcomes. Furthermore, different scenarios can lead to the same climate outcome via different pathways. This is due to varying assumptions on future technological developments, preferences, as well as economic, social and other assumptions.

The most prominent climate technology pathways providers are the IPCC scenario community (i.a. IIASA, PIK) as well as the International Energy Agency (IEA). There are also several other organizations that publish technology roadmaps. Some of which are available in the PACTA tool, e.g. by the Joint Research Center (JRC) of the European Commission.

PACTA currently offer two different accounting principles that can be applied to allocate production and capacity build out plans to a portfolio:

  • Portfolio Weight approach. This approach calculates the exposure of the portfolio to technologies based on the weighting of each position within the portfolio. The technology exposure is calculated as a weighted technology share (i.e. percentage production values weighted by financial exposure). The weighting of the technology share is determined by the share of the financial value of the holding of a company in the portfolio. The portfolio weight’s focus on relative exposure means that it relates more to transition risk;
  • Ownership approach. This approach calculates the exposure of the portfolio to technologies based on the portfolio’s ownership in companies. The technology exposure is presented in absolute values (e.g. oil production in barrels of oils per day). The ownership weight’s focus on share of production owned means that it relates to the contribution of the portfolio to the low-carbon transition.

The scenario geography is based on the asset location (i.e. production location) and allows a deep dive into the regionality of the production, technology mix and scenario alignment of your portfolio.

The regional granularity of the scenarios differs for each sector: the automotive sector, for example, usually only has one target as it is a global sector; whereas the power sector in some scenarios has a regional breakdown up to the country level.

The equity market selection determines the investible universe in terms of company domicile. Effectively, it will only keep companies that are headquartered in the region corresponding the the equity market. This means that this filter does not restrict the asset location, but the location of the company headquarters and differs in that sense from the scenario geography.

This selection is only available for equity portfolios (or the equity part of your portfolio).

The Benchmark Portfolio parameter allows the comparison of the alignment of the analyzed portfolio over the next five years with the benchmark of your choice from the list of available options.

In the volume trajectory chart, one line represents the portfolio being analyzed. Thus, this line represents the prospective production plans of the companies that make up the portfolio, and this information can be compared with the line that represents the prospective production plans of the companies that make up the benchmark.

In the future technology mix graph, it is possible to understand what the technology mix should be like for the portfolio if the companies that make up the portfolio were aligned with the scenario used for the analysis. This principle can also be applied to the benchmark.

Peer group comparison is exclusively available within the PACTA Coordinated Projects, a program specifically designed for governmental entities, and is not accessible to general users. This feature enables financial institutions within the same jurisdiction to compare their outcomes with those of their peers. The results of financial institutions within a particular group, such as banks, pension funds, insurance companies, and others, are anonymized and aggregated at the peer group level. Consequently, financial institutions can assess their own performance in relation to the aggregated results of their peer group within their jurisdiction. The anonymized and aggregated outcomes are presented in interactive reports exclusively for participants, while a meta-report is also generated to evaluate the alignment of the jurisdiction’s groups with different climate scenarios. For more information please access the dedicated page for PACTA Coordinated Projects.

Data sources

The model sources, where possible, forward-looking asset – level data for key technologies (e.g. future production plans) in order to provide geography-specific assessments for climate-relevant sectors mapped to the company level. It bypasses wherever possible backward-looking, corporate level reporting, although such reporting can be used for validating forward – looking parameters (e.g. GHG emissions). The analysis relies on the following data sources:

  • Asset Impact for asset-based company data
  • FactSet for financial and fund data
  • ISS for non-PACTA sector emissions data
  • IEA for their WEO and ETP scenario data
  • NZA for their GECO scenario data

Data coverage

The coverage both in terms of production data covered by the asset level data bases as well as the coverage of financial instruments in the sector is presented in the following document.

thumbnail of Coverage Charts Dashboard

Caveats/notes on interpreting the results

The following briefly highlights key caveats to the model and the results:

  • The forward-looking data is based on current ‘revealed’ plans from companies and is subject to change. The estimates should thus not be interpreted as final predictions, but rather the current plans of companies if they don’t change. Another way to interpret the results is the call for action with regard to the required change to align with the 2°C economic trend. Given the 5-year time horizon, there is a high degree of certainty that plans will still change in some way over time. Similarly, the participating financial institutions can of course alter their portfolio exposures over time. The analysis however seeks to be a point in time assessment of future exposures under current conditions.
  • The model takes a diversified ‘market portfolio’ as a basis, focusing on key technologies reflected in the IEA roadmaps. By extension, thematic portfolios invested in breakthrough technologies and/or SRI portfolios with a range of environmental, social, and governmental considerations may not value these elements.