2004年-世界发展银行全球_The_Determinants_of_Financing_Obstacles_36页_256kb

Summary of "The Determinants of Financing Obstacles"

Core Content

This paper investigates the determinants of financing obstacles faced by firms across 80 countries, using a unique firm-level survey dataset from the World Business Environment Survey (WBES). The study aims to assess the effectiveness of a priori classifications in identifying financially constrained firms and to explore the factors that influence the extent of these financing obstacles.

Main Viewpoints

• A Priori Classifications: The study confirms that firm characteristics such as age, size, and ownership are effective in distinguishing between financially constrained and unconstrained firms. Older, larger, and foreign-owned firms report fewer financing obstacles.

• Empirical Methodology: The authors use an ordered probit model to estimate the relationship between financing obstacles and firm characteristics. They also control for country and sector-specific variables to isolate the effects of firm-level factors.

• Self-Reported Obstacles: The WBES data allows firms to self-report the severity of financing obstacles, which is a more direct measure than previous methods that inferred constraints from financial statements.

• Economic Development: The paper finds that institutional development is the most important country-level characteristic explaining cross-country variation in financing obstacles. Financial development indicators such as private credit, stock market development, and legal system efficiency are also significant.

• Firm-Level Predictors:

  • Size is a strong predictor of financing obstacles, with smaller firms facing more constraints.
  • Age is negatively correlated with financing obstacles, suggesting that older firms are less constrained.
  • Ownership matters, with foreign-owned and listed firms reporting lower obstacles, while government-owned firms report higher ones.

• Sectoral Differences:

  • Firms in the agricultural and construction sectors report higher financing obstacles.
  • Service sector firms report lower obstacles.
  • Manufacturing firms also report higher obstacles.

• Limitations: The study acknowledges that self-reported data may not always reflect actual constraints, and that dividend payouts could not be tested due to the lack of data in the WBES.

Key Information

Data Overview

• The WBES survey includes over 10,000 firms from 80 countries.
• Firms are asked to rate the severity of financing obstacles on a scale from 1 (no obstacle) to 4 (major obstacle).
• 80% of firms are classified as small or medium, while 20% are large.
• 40% of firms are in the service sector, 30% in manufacturing, and 10% are listed.

Variables Used

• Firm Characteristics:

  • Log of age
  • Log of sales or size dummies (small, medium, large)
  • Sector dummies (agricultural, construction, service, manufacturing)
  • Ownership dummies (government-owned, foreign-owned, multinational, listed, business group)

• Country-Level Variables:

  • Private credit (as a share of GDP)
  • Value traded (as a share of GDP)
  • Law and order (trust in legal system)
  • Institutional development (composite index of political, regulatory, and economic institutions)
  • GDP per capita

Findings

• Size, Age, and Ownership are the most robust predictors of financing obstacles.
• Institutional development is the most significant factor at the country level.
• Foreign ownership and listing reduce financing obstacles, especially in areas like collateral and corruption.
• Government ownership increases financing obstacles, though this effect is not always statistically significant.
• Sectoral differences are evident, with manufacturing, agricultural, and construction firms facing more obstacles than service firms.

Conclusion

The paper highlights the importance of firm-level characteristics and country-level institutional development in determining the extent of financing obstacles. It suggests that while traditional classifications like size, age, and ownership are effective, other classifications used in the literature may not be as reliable. The study also underscores the value of direct self-reporting by firms in measuring financial constraints and the need to consider institutional environments when analyzing firm financing behavior.

Methodological Notes

• The study uses multivariate analysis to control for confounding variables.
• It acknowledges the limitations of self-reported data, but also notes that these reports are often linked to actual growth constraints.
• Clustered error terms are used to account for within-country correlation in firm responses.