The Importance of Reliability and Construct Validity in Multidimensional Poverty Measurement: An Illustration Using the Multidimensional Poverty Index for Latin America (MPI-LA)
以拉丁美洲多维贫困指数为例，论证了在贫困测量中应用可靠性（内部一致性）和建构效度等标准测量理论的重要性，并发现该指数不可靠且维度结构无效。
The empirical properties of a multidimensional poverty index require robust assessment. However, poverty research is yet to systematically implement measurement theories and practices that have been proven to be successful in other fields. Measurement theory has been developed over more than 100 years to produce indexes that are scientific (falsifiable) in that researchers put under scrutiny whether their value judgements and assumptions result in scales that have high internal consistency (reliability) and capture the phenomenon they aim to measure (validity). The paper uses the Multidimensional Poverty Index for Latin America (MPI-LA) to illustrate the importance of adopting sound measurement practices. The MPI-LA aims to be an improvement over the widely applied Unsatisfied Basic Needs (UBN) approach. However, its empirical development was based on ad hoc non-standard methods and principles, making the conclusions of the developer’s analyses unfalsifiable and prone to confirmation bias. This analysis includes six countries and two time periods. The findings suggest that the MPI-LA is an unreliable measure of poverty and that the pre-specified dimensional structure is invalid. The paper illustrates how standard principles like reliability and validity can be used to inform the discussion about the statistical properties of a given poverty index.