2014年-IMF国际货币组织全球_Assessing_Countries’_Financial_Inclusion_Standing_31页_951kb

Summary of "Assessing Countries' Financial Inclusion Standing—A New Composite Index"

Core Content

This paper introduces a new composite index of financial inclusion, developed by the IMF's Statistics Department using factor analysis to address the limitations of previous indices, particularly their lack of a robust weighting methodology. The index is designed to provide a more accurate and comprehensive measure of financial inclusion, enabling regular surveillance and policy analysis.

Main Purpose

• To construct a composite index that addresses the weighting and substitutability issues in previous financial inclusion indices.
• To use factor analysis (FA) to identify financial inclusion dimensions and assign appropriate weights.
• To rank countries based on the composite index to assess their financial inclusion standing.

Key Dimensions of Financial Inclusion

The paper defines financial inclusion in terms of three main dimensions:

1. Outreach – The ability to access financial services.
2. Usage – The extent to which individuals and firms use financial services.
3. Quality – The adequacy of financial services in meeting consumer needs.

However, due to limited data availability, the quality dimension is not included in the index computation.

Variables and Data Sources

The index is constructed using four variables, all of which are sourced from the IMF's Financial Access Survey (FAS) and the World Bank's World Development Indicators (WDI):

Note: The number of accounts is excluded to avoid potential bias.

Methodology

The index is computed through a five-step process:

1. Normalization of variables – Variables are normalized using the "distance to a reference" method, where each variable's reference point is set as the maximum value across countries. This ensures scale invariance.
2. Statistical identification of dimensions – Factor analysis is used to group variables into two dimensions: Outreach and Usage.
3. Weights assignment – Weights are assigned to both variables and dimensions based on their statistical properties.
4. Functional form of the aggregator – A weighted geometric average is used to compute the composite index, in contrast to the simple geometric mean used in other indices.
5. Index aggregation – The composite index is derived from the non-linear aggregation of the intermediate sub-indices.

Results and Findings

• The factor analysis confirms the separation of variables into two distinct dimensions: Outreach (dominated by branches and ATMs per square kilometer) and Usage (dominated by household depositors and borrowers per 1,000 adults).
• The index is computed for four years (2009–2012) and is based on data from 23 to 31 countries each year.
• Country rankings are derived from the composite index, which provides a more nuanced view of financial inclusion than previous measures that lacked proper weighting.
• The index is sensitive to changes in the data and offers a more dynamic assessment of financial inclusion across time and countries.

Policy Implications

• The composite index provides a useful tool for policymakers to monitor and improve financial inclusion.
• It highlights the importance of both access and usage in the financial system.
• The methodology can be extended to include more variables and dimensions in the future.

Limitations and Considerations

• The index is based on limited data, as not all countries report the required variables simultaneously.
• The exclusion of the quality dimension is due to data scarcity.
• The index assumes that the identified dimensions align with the theoretical framework of financial inclusion.

Conclusion

The paper presents a more robust and data-driven composite index of financial inclusion that overcomes the shortcomings of earlier indices by incorporating a proper weighting mechanism. This index can be used for regular surveillance and policy analysis to improve financial inclusion globally.