The Political Economy of Statistical Capacity: A Theoretical Approach

Abstract

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The Lure of Ill-Fitting Unemployment Statistics: How South Africa’s Discouraged Work Seekers Disappeared From the Unemployment Rate

“…International organisations such as the International Labour Organisation (ILO), the United Nations, and later the International Monetary Fund, the World Bank and the Organisation for Economic Co-operationand Development proselytised for their use and the developmentalist ideas underlying them (Masood 2016). Such governance by numbers has extended further with Millennium Development Goals and Sustainable Development Goals, which champion indicators as tools for economic and social development (Taylor 2016). Indeed, global benchmarking has emerged as a prominent allpurpose mode of transnational governance (Desrosières 1998, Davis et al 2012, Jany-Catrice 2012, Broome and Quirk 2015, Cooley and Snyder 2015, Kelley 2017, with indices covering everything from gender equality and business climates to financial opacity and good governance.…”

The Colombian Observatory of Science and Technology: Between Relevant Context and Internationally Comparable Indicators

“…NSSs are composed by NSOs as well as other agencies that provide official statistics for specific sectors, as is the case of STI. Taylor (2016) proposes that the output of NSOs should have a certain number of qualities including timeliness, efficiency, modernity, professionalism, and independence. He further states that "to meet these objectives, NSOs need to comply with international standards, guarantee that production and performance standards are high, ascertain that users are satisfied by the data and the methodologies used to aggregate it, and most importantly, ensure that the credibility of its procedures is unquestioned" (Taylor, 2016: 11-12).…”

“…In that sense, in the indicator production process, "credibility is both an instrumental end and a good" (Taylor, 2016: 12). Taylor (2016) makes a theoretical analysis on the political economy factors that affect the building of statistical capacity by governments, placing emphasis on the importance of reliable data as central to public policy formulation, monitoring, and evaluation. There is no unique definition of capacity; therefore it is a controversial concept.…”

“…There is no unique definition of capacity; therefore it is a controversial concept. Certainly, we can associate it with autonomy, impartiality, and discretion, and when looking at desired outcomes, with quality, efficiency, and effectiveness (Taylor, 2016). State capacity can be associated with a professional bureaucracy with autonomy from political power.…”

“…It implies both having enough human and budgetary resources, and an institutional framework that ensures the autonomy of the NSO and its NSS coordinator role." Taylor (2016) notes that the production of statistical data faces two political economy tensions. On the one hand, since there is no market incentive to collect and produce data, production of statistics is considered a public good.…”