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Soc Sci Med. 2015 Apr;131:164-72. doi: 10.1016/j.socscimed.2015.03.007. Epub 2015 Mar 5.

Estimating unbiased economies of scale of HIV prevention projects: a case study of Avahan.

Author information

1
Social and Mathematical Epidemiology Group, Global Health and Development Department, London School of Hygiene and Tropical Medicine, 15-17 Tavistock Place, WC1H 9SH London, United Kingdom. Electronic address: Aurelia.lepine@lshtm.ac.uk.
2
Social and Mathematical Epidemiology Group, Global Health and Development Department, London School of Hygiene and Tropical Medicine, 15-17 Tavistock Place, WC1H 9SH London, United Kingdom.
3
Social and Mathematical Epidemiology Group, Global Health and Development Department, London School of Hygiene and Tropical Medicine, 15-17 Tavistock Place, WC1H 9SH London, United Kingdom; St. John's Research Institute, Department of Epidemiology and Biostatistics, St. John Nagar, Bangalore 560034, India.
4
Joint Program on the Science and Policy of Global Change, Massachusetts Institute of Technology, 77 Massachusetts Avenue, Cambridge, MA 02139, USA.
5
University of Otago, Department of Economics, PO Box 56, Dunedin 9054, New Zealand.

Abstract

Governments and donors are investing considerable resources on HIV prevention in order to scale up these services rapidly. Given the current economic climate, providers of HIV prevention services increasingly need to demonstrate that these investments offer good 'value for money'. One of the primary routes to achieve efficiency is to take advantage of economies of scale (a reduction in the average cost of a health service as provision scales-up), yet empirical evidence on economies of scale is scarce. Methodologically, the estimation of economies of scale is hampered by several statistical issues preventing causal inference and thus making the estimation of economies of scale complex. In order to estimate unbiased economies of scale when scaling up HIV prevention services, we apply our analysis to one of the few HIV prevention programmes globally delivered at a large scale: the Indian Avahan initiative. We costed the project by collecting data from the 138 Avahan NGOs and the supporting partners in the first four years of its scale-up, between 2004 and 2007. We develop a parsimonious empirical model and apply a system Generalized Method of Moments (GMM) and fixed-effects Instrumental Variable (IV) estimators to estimate unbiased economies of scale. At the programme level, we find that, after controlling for the endogeneity of scale, the scale-up of Avahan has generated high economies of scale. Our findings suggest that average cost reductions per person reached are achievable when scaling-up HIV prevention in low and middle income countries.

KEYWORDS:

Avahan; Causal inference; Cost data; Economies of scale; Efficiency; HIV prevention; India; Scale-up

PMID:
25779621
DOI:
10.1016/j.socscimed.2015.03.007
[Indexed for MEDLINE]

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