2012年-世界发展银行全球_Mashup_Indices_of_Development_32页_238kb

Mashup Indices of Development Summary

Core Content

The document discusses the concept, use, and limitations of "mashup indices of development," which are composite indices that combine multiple indicators into a single measure without strong theoretical guidance. These indices are increasingly used to rank countries on development, but they raise concerns regarding their conceptual clarity, transparency, and robustness.

Main Points

• Definition of Mashup Indices: Mashup indices are composite indices where the choice of indicators and their weights is largely arbitrary, constrained only by data availability. Unlike traditional composite indices (e.g., GDP), they lack a clear theoretical foundation for their construction.

• Purpose and Appeal: These indices are appealing due to their simplicity, collapsing multiple dimensions into one. They are often used in media and policy discussions to provide an overview of country performance, but their details are rarely scrutinized.

• Examples of Mashup Indices:

  • Human Development Index (HDI): Combines life expectancy, education, and GDP per capita.
  • Multidimensional Poverty Index (MPI): Measures deprivation across 10 dimensions, including health, education, and living standards.
  • Ease of Doing Business Index (DBI): Averages rankings across 10 indicators of business environment.
  • Worldwide Governance Indicators (WGI): Aggregates data on six dimensions of governance.
  • Environmental Performance Index (EPI): Combines 25 environmental indicators.
  • Newsweek's "World's Best Countries" Index: Uses 5 categories, including education, health, and economic competitiveness.

• Theoretical Foundations: While some indices claim to be based on theoretical concepts (e.g., HDI based on Sen's capability approach), the connection between theory and practice is often weak or unclear. The document criticizes the HDI and MPI for not clearly reflecting the theoretical underpinnings of their components.

• Tradeoffs and Valuations: The document emphasizes the importance of understanding the tradeoffs (marginal rates of substitution) embedded in mashup indices. These tradeoffs determine how changes in one dimension affect the overall index and are often not transparent. For instance, the HDI implicitly assigns different monetary values to an extra year of life depending on the country's income level.

• Policy Relevance and Transparency: There is a call for greater transparency and documentation of the methodology used in constructing these indices. The lack of clear tradeoffs and robustness testing can lead to misleading country rankings and poor policy decisions.

Key Information

• Parsimony vs. Meaning: While mashup indices are praised for their simplicity, they often lack clarity on what they actually measure, making their interpretation and use questionable.

• Data Sources and Costs: Mashup indices often rely on expert assessments and local data collection, which can be labor-intensive but not necessarily costly. The DBI, for example, uses 8,000 local informants, but the index itself is not expensive to produce.

• Criticism of Current Practices: The document argues that the current industry standards for designing and documenting mashup indices are inadequate, leaving many aspects opaque to users and creating hidden risks in policy and measurement.

• Alternative Approaches: The "dashboard" approach, which monitors individual indicators separately, is contrasted with mashup indices. It is suggested that this approach may be more informative and less prone to misinterpretation.

Conclusion

Mashup indices of development are useful in simplifying complex data into a single measure, but they come with significant limitations. The lack of theoretical grounding, unclear tradeoffs, and limited transparency make them less reliable for policy-making. Future progress in composite indices should focus on aligning measurement practices with economic theory to ensure they are both meaningful and robust.