Abstract
Global awareness of the urgent need to decarbonize the economy has been growing. Although legislative and regulatory actions have been lagging, some businesses have emerged as leaders in this process. In particular, financial institutions as information producers and resource allocators play an important role. In order to accelerate the global transition to a low-carbon economy, market participants need to develop the ability to identify and support firms that are leading on climate change action. Using CDP data on ten climate change action metrics for 2013, the authors apply the dichotomous Rasch model to rank the overall climate change action performance of U.S. financial firms across multiple dimensions of this effort. Simultaneously, the results identify the climate change action metrics for which success was most difficult to achieve. The authors show that investors, managers and regulators should consider ranking firms using this more comprehensive methodology rather than the CDP’s Performance Band or the CDP’s Disclosure Score alone when assessing firm leadership in this area. While this study focuses on financial firms, a similar analysis could be conducted for ranking firms in other industries as well. The authors’ results are important for investors, managers and regulators charged with firm performance evaluation and resource allocation in the face of growing pressures to decarbonize the global economy
Highlights
Global awareness of the urgent need to decarbonize the economy has been growing (SDSN, 2014), and numerous global and local organizations have emerged to address the challenge
Performance rankings generated with a simple Rasch model identify the financial firms that succeed relative to their peers across a range of climate change action (CCA) metrics
The standardized fit statistics for the Rasch methodology, infit t and outfit t, for the difficulty hierarchy all lie between +2 and -2, indicating that the ten CCA metrics fit the requirements of the Rasch model for this sample[10]
Summary
Schellhorn and Sharma (2013) have previously used a range of financial metrics and a Rasch model to rank the multi-dimensional financial performance of firms in individual industries. A dichotomous Rasch model predicts the probability of a person’s success on a test that consists of several items by simultaneously measuring person ability and item difficulty. Managers’ ability to move their firms into CCA leadership positions, corresponds to person ability, and the difficulty of earning a favorable reading on a particular CCA metric corresponds to the difficulty of finding the correct answer to a test item. Any application of the Rasch model requires a certain relationship among the data In this application, the probability of a given firm’s success is a logistic function of the difference between the estimated ability of the firm to lead on CCA performance and the estimated CCA metric difficulty. The following section explains the CCA metrics data that were provided by financial firms to CDP and are used in our analysis of the firms’ leadership performance on CCA
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