Multiple Indicator Cluster Survey, Mokhotlong, Lesotho.
Ministry of Health, Maputo, Mozambique.
J Glob Health. 2021 Jan 30;11:04003. doi: 10.7189/jogh.11.04003.
The DHS wealth index - based on a statistical technique known as principal component analysis - is used extensively in mainstream surveys and epidemiological studies to assign individuals to wealth categories from information collected on common assets and household characteristics. Since its development in the late nineties, the index has established itself as a standard and, due to its ease of use, has led to a large and welcome increase in the analysis of inequalities. The index is, however, known to present some serious limitations, one being a bias towards patterns of urban wealth: the so-called "urban bias".
We use 10 data sets - 5 MICS (Multiple Indicator Cluster Survey), 4 DHS (Demographic and Health Survey) and one HBS (Household Budget Survey) - to demonstrate that urban bias continues to be a prominent and worrying feature of the wealth index, even after several methodological changes implemented in recent years to try to reduce it. We then propose and investigate an approach to improve the performance of the index and reduce the urban bias. This approach involves the use of ordinal rather than dummy variables, of a polychoric instead of a product-moment correlation matrix, and the use of two principal components rather than one. These approaches are used jointly to produce the polychoric dual-component wealth index (P2C).
The P2C index enables a larger proportion of the variance of the asset variables to be accounted for, results in all assets contributing positively to the wealth score, exploits added analytical power from ordinal variables, and incorporates the extra dimension of wealth expressed by the second principal component. It results in a better representation of typically rural characteristics of wealth and leads to the identification of more plausible distributions of both the urban and rural populations across wealth quintiles, which are closer to expenditure quintiles than the standard DHS index.
The P2C wealth index can be easily applied to mainstream surveys, such as the MICS and DHS, and to epidemiological studies; it yields more credible distributions of rural and urban subpopulations across wealth quintiles. It is proposed as an alternative to the DHS wealth index.
基于主成分分析这一统计技术的 DHS 财富指数被广泛应用于主流调查和流行病学研究中，用于根据常见资产和家庭特征信息将个体分配到财富类别中。自 90 年代末开发以来，该指数已确立其作为标准的地位，并且由于其易于使用，导致对不平等现象的分析大幅增加，受到广泛欢迎。然而，该指数已知存在一些严重的局限性，其中之一是对城市财富模式的偏向：所谓的“城市偏见”。
我们使用了 10 个数据集 - 5 个 MICS（多指标类集调查）、4 个 DHS（人口与健康调查）和 1 个 HBS（家庭预算调查） - 来证明，即使近年来为尝试减少这种偏差而实施了多项方法学变革，城市偏见仍然是财富指数的一个突出且令人担忧的特征。然后，我们提出并研究了一种改进指数并减少城市偏见的方法。该方法涉及使用有序而不是虚拟变量，使用偏相关矩阵而不是乘积矩相关矩阵，以及使用两个而不是一个主成分。这些方法联合使用以产生偏相关双成分财富指数（P2C）。
P2C 指数使更多的资产变量方差得以解释，使所有资产对财富得分都有积极贡献，利用有序变量的附加分析能力，并纳入第二主成分所表示的财富的额外维度。这导致对财富的典型农村特征的更好表示，并导致在财富五分位数中对城市和农村人口的更合理分布的识别，与标准 DHS 指数相比，这更接近支出五分位数。
P2C 财富指数可以轻松应用于主流调查，如 MICS 和 DHS，以及流行病学研究；它产生了更可信的农村和城市子群体在财富五分位数中的分布。它被提议作为 DHS 财富指数的替代方案。
