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Reproducibility package for Do Banks Overestimate Green Credit Risk? Evidence From SME Lending

2026
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Reference ID
RR_WLD_2026_716
Author(s)
Sandeep Singh, Patrick Zeitinger, Robert Schulz, Florian Egli
Metadata
JSON
Created on
Sep 07, 2026
Last modified
Sep 07, 2026
Page views
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  • Overview
  • Reproducibility Package
  • Description
  • Scope and coverage
  • Disclaimer
  • Access and rights
  • Contacts
  • Information on metadata

    • Overview

    Abstract

    Using a novel ten-year panel of over 43,000 small and medium-sized enterprises (SMEs) rated under the same risk model across 11 countries, we find that banks systematically overestimate the default risk of green SME borrowers. This credit risk misperception arises because credit models assign identical expected default probabilities to green and non-green borrowers, yet green SMEs exhibit a 13.7% lower default hazard than non-green peers at the same risk rating. Exploiting granular use-of-proceeds data absent from prior work, we show this effect is driven by energy-related investments: renewable energy (52%) and energy efficiency (16%) are associated with substantially lower default hazard, while other green investment categories show no significant effect. This pattern is consistent with a hedging mechanism against energy cost volatility and survives within-firm identification, matching on observables, and country-level subsamples. Incorporating green investment types into bank credit risk models would improve market efficiency, reduce the cost of capital for energy-related green SME borrowers, and thereby accelerate the decarbonization of the SME segment.

    Reproducibility Package

    Scripts
    Get Reproducibility Package
    File name
    RR_WLD_2026_716
    Zip package
    RR_WLD_2026_716.zip
    Title
    Reproducibility package for Do Banks Overestimate Green Credit Risk? Evidence From Sme Lending
    Date
    2026-09
    Dependencies
    Stata dependencies are listed in the ado folder.
    Instructions
    See README in reproducibility package.
    Notes
    Computational reproducibility verified by Development Impact (DECDI) Analytics team, World Bank.
    Source code repository
    Repository name URI
    Reproducible Research Repository (World Bank) https://reproducibility.worldbank.org
    Software
    Name
    Stata
    Version
    19.5 MP

    Reproducibility

    Technology environment

    Paper exhibits were reproduced on a computer with the following specifications:
    • OS: Windows 11 Enterprise
    • Processor: Intel(R) Xeon(R) Gold 5218 CPU @ 2.30GHz (2.30 GHz) (2 processors)
    • Memory available: 16 GB
    Technology requirements

    Runtime ~ 1 hour and 5 minutes
    Reproduction instructions

    To reproduce the findings in this paper, a replicator must:

    1. Secure Access to Data: Access the dataset "Loans_merged_2015.dta" not included in the package. See the Datasets section for more details
    2. Open the do file main, update the directory on line 23, install the required directories and run the script

    Since all data is restricted, the package includes the outputs produced by the replicators, which can be used to review the results presented in the paper

    Data

    Datasets
    Name
    ProCredit Group SME Loan Portfolio Panel 2015-2024
    Note
    Data accessed continuously by the authors 2023-2026 under a data use agreement between Patrick Zeitinger and ProCredit Group. Proprietary internal credit database covering 783,188 contract-year observations; 155,357 unique SME clients; 12 countries (11 after Germany drop); 2015-2024. Format: Stata binary (.dta), approximately 1.8 GB. Key variables include: contract identifier, client identifier, calendar year, country (Bank variable), sector (ISIC), internal risk classification (RC_EOY, RC_initial), binary default indicators (default_nextyear, default_thisyear), green loan type indicators (EEtype, REtype, GRtype), outstanding principal (EUR), eco-classifier codes (ProCredit green taxonomy sub-subcategories), and financial statement ratios (CurrentRatio, RoAA, DebtEBITDA). Variable labels are embedded in the Stata file; a codebook is available from the authors upon request. Researchers interested in access should contact ProCredit Holding AG: Robert Schulz (robert.schulz@procredit-group.com) or the legal department (PCH.Legal@procredit-group.com). Access requires execution of a Data Use Agreement/NDA and may take several weeks to arrange. Steps 1-4 of the data pipeline (how raw ProCredit database extracts were cleaned, merged, and aggregated to produce Loans_merged_2015.dta) are documented in Code/00_data_documentation.do, which cannot be executed without direct access to the ProCredit database. Loans_merged_2015.dta serves as the reproducible starting point in the sense of the WB FAQ on starting points for reproducibility packages. File location: Data/Loans_merged_2015.dta.
    Access policy
    Data access was granted directly to the study authors by the data owners/managers. It was obtained with a custom data license that does not allow for redistribution and it is not included in the reproducibility package.
    License
    Custom License
    Citation
    ProCredit Group. 2024. "SME Loan Portfolio Panel 2015-2024" [Proprietary dataset]. ProCredit Holding AG, Frankfurt am Main, Germany. Accessed by the authors under a data use agreement between Patrick Zeitinger and ProCredit Group, 2023-2026.
    Data statement

    All data is restricted and has not been included in the reproducibility package. For more details, please refer to the README file.

    Description

    Output
    Type
    Working Paper
    Title
    Do Banks Overestimate Green Credit Risk? Evidence From SME Lending
    Description
    Policy Research Working Papers (PRWP)
    Authors
    Author Affiliation Email
    Sandeep Singh World Bank ssingh13@ifc.org
    Patrick Zeitinger School of Social Sciences and Technology, Technical University of Munich patrick.zeitinger@tum.de
    Robert Schulz ProCredit Holding AG Robert.Schulz@procredit-group.com
    Florian Egli School of Management, Technical University of Munich florian.egli@tum.de
    Date of production

    2026-09-04

    Scope and coverage

    Geographic locations
    Location Code
    World WLD
    Keywords
    Green Loans Credit Risk Esg Risk Smes
    Topics
    ID Topic Parent topic ID Vocabulary Vocabulary URI
    G21 Banks • Depository Institutions • Micro Finance Institutions • Mortgages G2 Journal of Economic Literature (JEL)
    Q56 Environment and Development • Environment and Trade • Sustainability • Environmental Accounts and Accounting • Environmental Equity • Population Growth Q5 Journal of Economic Literature (JEL)
    O16 Financial Markets • Saving and Capital Investment • Corporate Finance and Governance O1 Journal of Economic Literature (JEL)

    Disclaimer

    Disclaimer

    The materials in the reproducibility packages are distributed as they were prepared by the staff of the International Bank for Reconstruction and Development/The World Bank. The findings, interpretations, and conclusions expressed in this event do not necessarily reflect the views of the World Bank, the Executive Directors of the World Bank, or the governments they represent. The World Bank does not guarantee the accuracy of the materials included in the reproducibility package.

    Access and rights

    License
    Name URI
    MIT License https://opensource.org/license/mit
    World Bank IGO Rider https://github.com/worldbank/metadata-editor/blob/main/WB-IGO-RIDER.md

    Contacts

    Contacts
    Name Affiliation Email
    Sandeep Singh World Bank ssingh13@ifc.org
    Reproducibility WBG World Bank reproducibility@worldbank.org

    Information on metadata

    Producers
    Name Abbreviation Affiliation Role
    Reproducibility WBG DECDI World Bank - Development Impact Department Verification and preparation of metadata
    Date of Production

    2026-09-04
    Document version

    1
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