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Regional favoritism in access to credit

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If the man at the top comes from a certain area of Zambia… you find that the people who come after him are all from the same area… It is just a matter of helping someone because he is from the area, do[ing] a favor for him.

Daniel Posner, Institutions and Ethnic Politics in Africa

Abstract

We examine the effect of regional favoritism on the access of firms to credit. Using firm-level data on a large sample of 29,000 firms covering 47 countries, we investigate the hypothesis that firms in the birth regions of national political leaders have better access to credit. Our evidence suggests that firms located in birth regions of political leaders are less likely to be credit constrained. We further find that firms in leader regions feel less discouraged in applying for loans and also get preferential lending from banks.

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Notes

  1. For evidence regarding European democracies, see e.g. Baskaran and Lopes da Fonseca (2021) for Germany, Carozzi and Repetto (2016) for Italy, and Fiva and Halse (2016) for Norway.

  2. For more information on the dataset, see http://www.enterprisesurveys.org/data.

  3. An alternative strategy would be to add in country-region fixed effects to compare firms in the same region of the same country at points in time when the leader is from that region compared to other regions. However, our sample has a limited number of countries with two waves of survey results associated with two different leaders and with the leaders coming from two different regions.

  4. See for example Rostamkalaei et al. (2020).

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Authors and Affiliations

  1. Paris School of Business, 59 Rue Nationale, 75013, Paris, France

    Francis Osei-Tutu

  2. EM Strasbourg Business School, University of Strasbourg, Strasbourg, France

    Laurent Weill

  3. Moscow State Institute of International Relations, MGIMO University, Moscow, Russia

    Laurent Weill

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  1. Francis Osei-Tutu
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Correspondence to Laurent Weill.

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We thank the Associate Editor who provided very valuable comments that greatly improved our work. We are also grateful for the insights of Denis Davydov, Sami Vähämaa, Nguyen Nguyen, and other participants at the Southern Finance Association Meeting in Key West (November 2022) and seminars at BOFIT (Helsinki, January 2023), and the University of Vaasa (January 2023).

Appendix

Appendix

Variable

Definition and sources

Dependent variables

 

Constrained

Dummy = 1 if the firm needing bank credit applied for loan and was denied or refused to apply, and zero otherwise. Source: WBES

Constrained (alternative)

Dummy = 1 if the firm reports access to credit as a moderate, major, or very severe obstacle, and zero otherwise. Source: WBES

Apply

Dummy = 1 if the firm needed loans and applied for credit, and zero otherwise. Source: WBES

Approved

Dummy = 1 if the firm applied for loan and received at least one line of credit, and zero otherwise. Source: WBES

Firm variables

 

Leader region

Dummy = 1 if a firm is located in the region where the leader of the country was born, zero otherwise

Firm size

Number of full-time permanent employees. Source: WBES

Age

Age of the firm. Source: WBES

Sole proprietorship

Dummy = 1 if a firm is a sole proprietorship, and zero otherwise. Source: WBES

Partnership

Dummy = 1 if a firm is a partnership, and zero otherwise. Source: WBES

Audited

Dummy = 1 if the firm’s financial statements were checked and certified by an external auditor, and zero otherwise. Source: WBES

Experience

Top manager’s number of years of experience in the sector. Source: WBES

Foreign-owned

Dummy = 1 if at least 50% of the firm’s ownership is held by foreigners, and zero otherwise. Source: WBES

Exporter

Dummy = 1 if at least 10% of the firm’s annual sales is derived from direct exports, and zero otherwise. Source: WBES

State-owned

Dummy = 1 if at least 50% of the firm’s ownership is held by the government, and zero otherwise. Source: WBES

Subsidiary

Dummy = 1 if a firm is part of a large group, and zero otherwise. Source: WBES

Capital city

Dummy = 1 if firm is located in capital city, and zero otherwise. Source: WBES

Corruption

Dummy = 1 if a firm perceives corruption to be a very severe or major obstacle, and zero otherwise. Source: WBES

Working capital

Proportion of goods and services paid for after delivery. Source: WBES

Competition

Captures firm’s perceived degree of competition in the informal sector. Source: WBES

Political connections

Dummy = 1 if a firm has secured (or attempted to secure) a government contract within the past 12 months, and zero otherwise. Source: WBES

Sales growth

Average regional-level growth in firm’s sales over three years. Source: WBES

Electricity

Extent to which electricity is a constraint to the operations of firms in a region. Source: WBES

Informal credit

Average number of firms in a region that finance part of their working capital or fixed assets with funds from money lenders, friends, or relatives. Source: WBES

Country variables

GDP growth

GDP growth rate. Source: WDI

Credit/GDP

Domestic credit to the private sector as a share of GDP. Source: WDI

Inflation

Inflation rate. Source: WDI

Rule of law

Measures the perceptions of the extent to which people have confidence in and abide by the rules of society. Source: World Governance Indicators

Collectivism

Measure of collectivism culture. Source: Hofstede Insights

Tenure

Number of years the leader has held office. Source: Dreher et al. (2020)

Education in economics

Dummy = 1 if leader has higher education in economics or management, zero otherwise. Source: Baturo (2016). Completed with hand-collected online data on the personal biographies of leaders

Democracy

Index to measure democracy. Source: Polity Project

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Osei-Tutu, F., Weill, L. Regional favoritism in access to credit. Public Choice (2024). https://doi.org/10.1007/s11127-024-01155-3

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