Corporate Loan Recovery Rates under Downturn Conditions in a Developing Economy: Evidence from Zimbabwe

Frank Ranganai Matenda (), Mabutho Sibanda, Eriyoti Chikodza and Victor Gumbo
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Frank Ranganai Matenda: School of Accounting, Economics and Finance, University of KwaZulu-Natal, Westville Campus, University Road, Westville, Private Bag X54001, Durban 4000, South Africa
Mabutho Sibanda: School of Accounting, Economics and Finance, University of KwaZulu-Natal, Westville Campus, University Road, Westville, Private Bag X54001, Durban 4000, South Africa
Eriyoti Chikodza: School of Agriculture and Natural Sciences, Great Zimbabwe University, Masvingo P.O. Box 1235, Zimbabwe
Victor Gumbo: Department of Mathematics, University of Botswana, Private Bag UB 0022, Gaborone 4775, Botswana

Risks, 2022, vol. 10, issue 10, 1-24

Abstract: In this study, we design stepwise ordinary least squares regression models using various amalgamations of firm features, loan characteristics and macroeconomic variables to forecast workout recovery rates for defaulted bank loans for private non-financial corporates under downturn conditions in Zimbabwe. Our principal aim is to identify and interpret the determinants of recovery rates for private firm defaulted bank loans. For suitability and efficacy purposes, we adopt a unique real-life data set of defaulted bank loans for private non-financial firms pooled from a major anonymous Zimbabwean commercial bank. Our empirical results show that the firm size, the collateral value, the exposure at default, the earnings before interest and tax/total assets ratio, the length of the workout process, the total debt/total assets ratio, the ratio of (current assets–current liabilities)/total assets, the inflation rate, the interest rate and the real gross domestic product growth rate are the significant determinants of RRs for Zimbabwean private non-financial firm bank loans. We reveal that accounting information is useful in examining recovery rates for defaulted bank loans for private corporations under distressed financial and economic conditions. Moreover, we discover that the prediction results of recovery rate models are augmented by fusing firm features and loan characteristics with macroeconomic factors.

Keywords: recovery rates; private non-financial firms; developing economy; determinants; downturn conditions; stepwise ordinary least squares regression model (search for similar items in EconPapers)
JEL-codes: C G0 G1 G2 G3 K2 M2 M4 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:gam:jrisks:v:10:y:2022:i:10:p:198-:d:944577

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