The absence of sound sampling procedures and statistical analyses to estimate solid waste generation in many developing countries has resulted in incomplete historical records of waste quantity and composition. Data is often arbitrarily aggregated or disaggregated as a function of waste generators to obtain results at the desired spatial level of analysis. Inference fallacies arising from the generalization or individualization of results are almost never considered. In this paper, Panama, one of the fastest-growing developing countries, was used as a case-study to review the main methodological approaches to estimate solid waste generation per capita per day, and at different hierarchical levels (from households to the country). The solid waste generation intensity indicator is used by the Panamanian waste management authority to run the waste management system. It was also the main parameter employed by local and foreign companies to estimate solid waste generation in Panama between 2001 and 2008. The methodological approaches used by these companies were mathematically formalized and classified as per the expressions suggested by Subramanian et al. (2009). Seven inference fallacies (ecological, individualistic, stage, floating population, linear forecasting, average population and mixed spatial levels) were identified and allocated to the studies. Foreign companies committed three of the seven inference fallacies, while one was committed by the local entity. Endogenous knowledge played an important role in these studies to avoid spatial levels mismatch and multilevel measurements appear to produce more reliable information than studies obtained via other means. (c) 2021 Elsevier Ltd. All rights reserved.
- Developing countries
- Inference fallacies
- Multilevel analysis
- Solid waste generation intensity