makingit_20_pp38-41_policybrief.qxp_print 17/11/2015 08:59 Page 38
POLICY BRIEF
Monitoring industrialization: a statistical perspective By SHYAM UPADHYAYA, Chief of the Statistics Unit, United Nations Industrial Development Organization While the adoption of the Agenda 2030 at the United Nations in September attracted wide media attention, the international statistics community has been working behind the scenes to develop a framework of indicators that will help governments and international development partners monitor the progress in achieving the Sustainable Development Goals (SDGs). At the very outset of the discussions about the SDGs, the United Nations Industrial Development Organization (UNIDO) carried out a statistical analysis and presented sound evidence of the relationship between industrialization and the well-being of society. There is a
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strong correlation between human development and the level of a country’s industrialization. As a country industrializes, it acquires the resources necessary to improve people’s living conditions. With an increase of manufacturing value added (MVA) per capita of 1% annually, the proportion of a population that lives below the ‘poverty line’ decreases by nearly 2%. Similarly, with a one percent growth of MVA per capita, the number of deaths related to armed conflict falls by 4.5%. Gender inequality is widely recognized as one of the chief factors impeding human development. The UN Development Programmes Gender Inequality Index, i.e. a composite measure reflecting inequality in achievements between women and men in three dimensions: reproductive health,
empowerment and the labour market. The Index shows that gender inequality is highest in least developed countries and lowest in industrialized countries. There are 17 Sustainable Development Goals (SDGs) with 169 targets, whereas the eight Millennium Development Goals (MDGs) had 21 targets. Consequently, the number of indicators to be monitored will be much larger than the 50 MDG indicators. It will be necessary to develop the statistical capacity to produce the data necessary to compile the statistics needed for SDG monitoring. It will require much greater efforts by, and increased resources for, the national statistical offices and international data producing agencies. The challenge is to develop a set of indicators that cover all the targets while minimizing the reporting burden on