In this paper we propose a data-driven approach for the construction of survey-based indicators using large data sets. We make use of agents’ expectations about a wide range of economic variables contained in the World Economic Survey, which is a tendency survey conducted by the Ifo Institute for Economic Research. By means of genetic programming we estimate a symbolic regression that links survey-based expectations to a quantitative variable used as a yardstick, deriving mathematical functional forms that approximate the target variable. We use the evolution of GDP as a target. This set of empirically-generated indicators of economic growth, are used as building blocks to construct an economic indicator. We compare the proposed indicator to the Economic Climate Index, and we evaluate its predictive performance to track the evolution of the GDP in ten European economies. We find that in most countries the proposed indicator outperforms forecasts generated by a benchmark model.
Human Rights to Water and Sanitation (HRWS) have been consolidated as relevant frameworks to measure different levels of services. It is essential to move forward with specific initiatives that interpret the content of these human rights and operationalize them through specific metrics. However, some critical issues emerge in attempting this. Different approaches are proposed in this article to tackle this challenge: (1) utilizing a participatory technique to discuss the relative importance of the normative criteria to define water and sanitation services, (2) defining a short list of key indicators to measure the different dimensions of HRWS, and (3) assessing the impact of different weighting systems in the constructing an aggregated index, which has been proposed as a useful tool to monitor water, sanitation, and hygiene (WASH) from a rights perspective. Two municipalities (in Mozambique and Nicaragua) were selected as initial case studies. The results suggest that there is a common understanding among the experts about prioritization of the HRWS criteria. Differences in the relative importance given to the HRWS criteria can be explained due to the particularities of the local context. Further, the research suggests that expert opinions may be partially conditioned by targets and indicators proposed at the international level. Although the influence of weighting techniques on aggregated measures and their utilization in the decision-making process are limited, this methodology has a great potential for adapting specific WASH metrics to different regional, national, and/or local contexts taking into account the HRWS normative content.
Measuring access to water in the Sustainable Development Goals era involves taking into account the human rights framework. Therefore, its content should be considered to conceptualize the level of service through adequate indicators and to follow-up inequities reduction at global, national and local level. This research develops and tests a methodology to measure intra-community disparities based on human right to water normative criteria through a stratified sampling, splitting households served by community based organizations and those self-provided. This approach implies considering much reduced populations, thus special care needs to be taken with sample sizes and uncertainty of estimators. The proposed methodology is practical to locate and accurately characterize minority sectors within rural communities and allows moving beyond central-tendency estimators. It implies higher costs for field data collection than traditional approaches, but this can be assumed given the relevance of the approach from a human rights perspective, which calls for adequate tools for equity-oriented policy making at local level. The research point out how results might be used to shape decision-making processes.