2005年-世界发展银行全球_Efficiency_of_Public_Spending_in_Developing_Countries___An_Efficiency_Frontier_Approach_69页_748kb

Efficiency of Public Spending in Developing Countries: An Efficiency Frontier Approach Summary

Core Content

This paper investigates the efficiency of public spending in developing countries, focusing on health and education sectors. It aims to quantify efficiency by comparing observed input-output combinations with an efficiency frontier, defined as the maximum attainable output for a given level of inputs. The study uses data from 140 countries over the period 1996-2002 and applies two non-parametric methods: Free Disposable Hull (FDH) and Data Envelopment Analysis (DEA). The paper also explores the factors influencing cross-country variations in efficiency scores.

Main Points

• Efficiency Measurement: Efficiency is measured as the distance between observed input-output combinations and the efficiency frontier. Both input inefficiency (excess input consumption) and output inefficiency (output shortfall) are scored.
• Methodologies: The study employs FDH and DEA techniques to estimate efficiency frontiers. FDH assumes free-disposability of resources and is less restrictive, while DEA assumes convexity and uses a piecewise linear frontier.
• Efficiency Frontiers: The paper constructs efficiency frontiers for nine education output indicators and four health output indicators. These indicators include primary and secondary school enrollment, literacy rates, life expectancy, and disability-adjusted life expectancy (DALE).
• Empirical Results: Countries with higher public expenditure levels and higher wage bills tend to have lower efficiency scores. Additionally, higher aid dependency, HIV/AIDS prevalence, and income inequality are associated with lower efficiency.
• Limitations: The study acknowledges limitations in data homogeneity, aggregation levels, and the inclusion of non-monetary factors. It also notes that the non-parametric methods are sensitive to sampling variability and outliers, and that dynamic factors are not adequately addressed.

Key Information

• Efficiency Scores: Efficiency scores are calculated for both input and output. A score of one indicates a country is on the frontier, while scores below one indicate inefficiency.
• FDH vs. DEA: FDH tends to assign efficiency to more decision-making units (DMUs) than DEA. This difference is illustrated with examples of countries like Mexico, which appears as a benchmark due to its low spending and low output.
• Variables and Data: The study uses a range of variables including public spending per capita, per capita GDP, urbanization rates, and income inequality. The data is sourced from various international assessments and government budgets.
• Regional Analysis: Results are clustered regionally, including Africa (AFR), East Asia and Pacific (EAP), Latin America and the Caribbean (LAC), Middle East and North Africa (MNA), and South Asia (SAS).
• Statistical Methods: The paper uses a Tobit panel approach to analyze the variation in efficiency scores and introduces confidence intervals for efficiency estimates using Monte-Carlo procedures.

Efficiency Change Over Time

• The paper explores how expenditure efficiency has evolved over time, noting that efficiency frontiers may shift outward, indicating improved productivity.
• The analysis suggests that while public spending can increase productivity, it does not guarantee better outcomes without efficiency improvements.

Explaining Inefficiency Variation

• Factors Influencing Efficiency: The study identifies several factors that affect efficiency, including expenditure levels, wage bill composition, aid dependency, HIV/AIDS prevalence, and income inequality.
• Urbanization and Bureaucracy: The degree of urbanization and the quality of bureaucracy are highlighted as important variables in explaining efficiency differences.
• Non-linearity and Censoring: The authors consider non-linear relationships and address the issue of censored efficiency scores (ranging from 0 to 1).

Conclusion and Future Work

• The paper concludes that efficiency in public spending is crucial for achieving development goals, and that various factors influence it.
• It suggests that future research should focus on addressing the limitations of current methods, such as incorporating dynamic elements and improving data quality for more accurate comparisons.

References

• Farrell, 1957
• Charnes, Cooper, and Rhodes, 1978
• Banker, Charnes, and Cooper, 1984
• Gupta and Verhoeven, 2001
• Evans and Tandon, 2000
• Jarasuriya and Woodon, 2002
• Greene, 2003
• Afonso, Schuknecht, and Tanzi, 2003
• Afonso and St. Aubyn, 2004
• Crouch and Fasih, 2004
• Murillo-Zamorano, 2004
• Simar and Wilson, 2000
• Haque, Pesaran, and Sharma, 1999
• Wagner's Hypothesis: Tested and found to be valid at the cross-country level.

Methodology Overview

• FDH Method: Assumes free-disposability of resources and is used to estimate efficiency frontiers for single input-output cases.
• DEA Method: Assumes convexity and uses a piecewise linear frontier to compare efficiency across DMUs.
• Efficiency Calculation: Efficiency scores are calculated using ratios of observed inputs and outputs to the frontier. For example, input efficiency is defined as OR/OP, and allocative efficiency as OS/OR.
• Scale Efficiency: The paper distinguishes between technical efficiency and scale efficiency, noting that constant returns to scale (CRS) technical efficiency is the product of variable returns to scale (VRSTE) and scale efficiency (SE).

Limitations and Challenges

• Data Homogeneity: Cross-country comparisons assume homogeneity in production technology, which may not hold due to differences in input quality and factor composition.
• Aggregation Issues: The study uses aggregated public spending, while output indicators are more detailed. This can lead to biased efficiency scores.
• Non-Monetary Factors: The inclusion of non-monetary factors like teacher-student ratios and adult literacy rates complicates the analysis.
• Dynamic Elements: The study notes that dynamic aspects of public spending and output are not well addressed by the current non-parametric methods.

Summary of Findings

• Higher public expenditure is not always correlated with higher efficiency.
• Countries with higher income inequality, higher HIV/AIDS prevalence, and higher aid dependency tend to have lower efficiency scores.
• The orthogonalization of public expenditure relative to GDP improves the distribution of efficiency scores by reducing skew towards extreme inefficiency.
• The paper highlights the importance of efficiency in public spending for achieving educational and health outcomes and suggests that future research should focus on improving data quality and incorporating dynamic elements.