The number of composite indices that are constructed and used internationally is growing very fast; but whilst the complexity of quantitative techniques has increased dramatically, the education and training in this area has been dragging and lagging behind. As a consequence, these simple numbers, expected to synthesize quite complex issues, are often presented to the public and used in the political debate without proper emphasis on their intrinsic limitations and correct interpretations.
In this course on global statistics, offered by the University of Geneva jointly with the ETH Zürich KOF, you will learn the general approach of constructing composite indices and some of resulting problems. We will discuss the technical properties, the internal structure (like aggregation, weighting, stability of time series), the primary data used and the variable selection methods. These concepts will be illustrated using a sample of the most popular composite indices. We will try to address not only statistical questions but also focus on the distinction between policy-, media- and paradigm-driven indicators.

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Liner shipping connectivity indices (UNCTAD) and Human development index (UNDP)

During this week you will be exploring two indices. The first index, the Liner Shipping (Bilateral) Connectivity Index (LSCI/LSBCI) computed each year by UNCTAD since 2004. It provides an overall indicator of a country maritime connectivity related to liner shipping. Throughout this lesson, we give some insights on why the LSCI and LSBCI were developed. We also cover the methodology to build both indices. We then discuss some stylized facts.
The second index presented this week is the Human Development Index (HDI) developed by UNDP. During this lesson, you will be slightly introduced with the history of the HDI. We explain the steps of constructing the HDI, i.e. choosing the three dimensions (health, education and living conditions) composing the HDI and their respective indicators, normalizing the indicators and aggregating the indicators and dimensional sub-indices using different methods. Then, we use a practical example to calculate the HDI for one country. At the end, we discuss some limitations of the HDI and give some elements for future improvement.