The relevance of macroeconomic data for firm-specific non-financial informationImke Sterf

11 May 2021

Concerns about the impact and consequences of climate change have notably intensified in recent decades. Additionally, the publicity around "sustainable finance" and "ESG investments" has grown immensely in recent years and has become an essential topic on the European policy agenda. Precise and reliable data is crucial to further understand how businesses impact the ecosystem around them. Despite significant developments in the understanding, measurement, and monitoring of environmental impacts, the required availability and quality of this data is currently often unavailable, making informed decisions on ESG investments challenging. Consequently, the need for methods to identify the fundamental causes of environmental and social impacts is becoming increasingly important. In this context, this thesis studies how macroeconomic data for firm-specific non-financial information could be utilized. By applying input-output analysis, macroeconomic datasets could be applied to assess the environmental implications of companies’ complete supply chains. The methodology relies on semi-structured interviews with various experts from organizations that collect macroeconomic data to analyze the critical barriers of the practice. It offers a qualitative approach towards a new way of using existing macroeconomic data and explains the underlying factors that would need to change to make it successful. Key findings reveal that numerous factors hinder macroeconomic data from being utilized. Policymakers must improve the availability and quality of collected information on a macroeconomic level. They need to implement new laws and requirements and start legislative reforms to support the collection of macroeconomic data and further regulate the supply of non-financial information on all levels. Although large amounts of data points are collected, it is not ensured that the reported datasets are useful to others. The macroeconomic data could become more valuable and relevant if policies and regulations were changed.