The role of economists in policy – a view from USAID Steve O’Connell* Chief Economist, USAID UNU-WIDER 30 th Anniversary Helsinki, September 17, 2015 Disclaimer: The views expressed here are my own and do not constitute official policy of USAID or the US Government.
The role of economists in policy making (Ahluwalia paper) Translating policy objectives into targets We partner to end extreme poverty Macroeconomic policymaking and promote Fiscal, monetary and exchange-rate policies resilient, Growth policies democratic Sectoral policies societies while Energy and water advancing our security and Other dimensions prosperity. The balance between government and market USAID Mission Independent evaluation of policies and programs Statement Educating the public about the importance of policy January 21, 2014 Warning against bad policies “We partner” in 2 senses: Solidarity with the global community (in line with the 2030 Agenda) 2 With domestic actors, who matter most for sustainable outcomes.
A multi-dimensional definition of extreme poverty “Extreme poverty is the inability to meet basic consumption needs on a sustainable basis . People who live in extreme poverty lack both income and assets and typically suffer from interrelated, chronic deprivations, including hunger and malnutrition, poor health, limited education, and marginalization or exclusion.” USAID’s Vision for Ending Extreme Poverty / September 2015 3
Something is going right Source: USAID’s Vision for Ending 4 Extreme Poverty , Sept 2015
Contributions to global growth 5 Source: https://en.wikipedia.org/wiki/World_economy (caveat emptor ... the cite is to the IMF’s World Economic Outlook dataset)
Success raises ambitions … but also shifts the ground Extreme poverty (& depth) continues to shift towards SSA Among countries with high headcount ratios (SSA + Haiti), increasing overlap between extreme poverty and natural resource dependence. Increasing overlap of extreme poverty with fragility and conflict. Primacy of the political settlement and state-society relations. Key trends conditioning the global effort to eliminate XP Security concerns Climate change Urbanization Youth bulge New development actors, public and private Technology is overcoming distances: of people to people, people to markets, people to governments. 6 See USAID’s Vision for Ending Extreme Poverty , September 2015
Translating policy objectives into targets (Focusing on $1.25) What are the right intermediate targets? What is the appropriate balance between delivering consumption benefits to the poor, building their assets, and transforming their economic opportunities? [ Redistribution With Growth , 1974] What is the appropriate balance between external partners and host governments in financing and/or delivering benefits to the poor? What concept of inclusion should donors target in countries where the median voter is not extremely poor? A key role for economists: think in general-equilibrium and dynamic terms, and promote indirect routes when the evidence is strong. Growth was overwhelmingly crucial for achieving MDG #1. “Institutions rule.” USAID’s ‘theory of change’ for ending XP reflects the evidence on primacy of inclusive and sustainable growth, underpinned by effective 7 governance and accountable institutions .
Growth and institutions in a theory of change “no one -size-fits-all has worked [for countries] in reducing extreme poverty to date.” USAID’s Vision 8
How have economists shaped USG’s positioning on growth? Global Health (PEPFAR, Maternal and Child Health) Feed the Future “Zones of influence” to discipline evaluation. Education Emphasis on learning rather than enrollments (Pritchett). Global Climate Change MCC Dollar and Kraay, Collier, and many others on aid effectiveness. Institutional design: goal dependence and instrument independence. Growth diagnostics a la Hausmann, Rodrik and Velasco (2005) Power Africa Growth diagnostics 9
But very strong practical pressures to target benefits Much of the best evidence is not about system properties, because it’s hard to randomize those. In fact our understanding of the causes and consequences of distributional outcomes – a system property par excellence – remains strikingly limited. How in practice do we pursue the “inclusive” in “inclusive growth”? “No known correlates” ( Chandy): 40 years after Redistribution With Growth we’re still searching for robust determinants of the poverty elasticity of growth. Tremendous scope for good descriptive data work: AERC and others on national transfer accounts, Nora Lustig and associates on fiscal incidence, Inchauste & co-authors on household-level drivers of poverty reduction. 10
Micro evidence on labor earnings and ‘ transfers+pensions ’ FGT1 is Contributions of earnings & transfers to reducing XP closely $1.25-a-day line, 18 developing countries, 2000s related to 150 the “person - 100 equivalent poverty headcount 50 ratio” of Castleman, 0 Foster & Smith -50 (2015) Earnings: Headcount E: FGT1 E: FGT2 Transfers: Headcount T: FGT1 T: FGT2 11 Source: Inchauste et al. (2014), Table 3.B.1. Outliers not shown.
… additional practical pressures to target benefits Accountability: much harder to convincingly claim impact via indirect channels, even if those channels are crucially important. Public service delivery: program outputs are readily measurable. Capacity building: fundamentally important but outcomes very elusive to quantify. Spatial concentration of within-country programming: find the poorest? Feed the Future: focus on high-potential zones or high-poverty zones? Cross-country selectivity: XP need and development effectiveness may be inversely correlated. Poverty concentrated in countries that fail the MCC scorecard. Fragile and conflict-affected states: public service delivery just requires ‘permission’ and can be efficacious where the local system is not (Kenny)? 12
… with such a low line, is a B.I.G. inevitable? Number of poor and daily gaps at $1.25-a-day (2005 PPPs) Region #countries Npoor (m) Gap ($/day) Gap($, total) East Asia and Pacific 12 150.4 0.25 13.5 Europe and Central Asia 28 2.2 0.35 0.3 Latin America and Caribbean 25 27.1 0.59 5.8 Middle East & North Africa 11 5.5 0.26 0.5 South Asia 6 391.8 0.26 37.7 Sub-Saharan Africa 43 397.2 0.51 74.3 TOTAL 125 974.2 0.37 132.1 TOTAL (2014 international $) 157.6 TOTAL (2014 US$, factor 1/2.25) 70.0 13 Source: Calculated from World bank PovCalNet data using Don Sillers’s poverty calculator
$1.25 a day is not much, and neither is twice $1.25 Number of poor in developing countries at various poverty lines (2005 PPPs) $1.25 $2.00 $4.00 $10.00 Region #countries Npoor (m) Npoor (m) Npoor (m) Npoor (m) East Asia and Pacific 12 150 430 1,033 1,686 Europe and Central Asia 28 2 10 49 229 Latin America and Caribbean 25 27 54 151 372 Middle East & North Africa 11 5 37 163 289 South Asia 6 392 961 1,463 1,583 Sub-Saharan Africa 43 397 589 759 827 TOTAL 125 974 2,082 3,619 4,986 14 Source: Calculated from World bank PovCalNet data using Don Sillers’s poverty calculator
Costing a costless B.I.G. Cost of a costlessly and perfectly targeted basic income guarantee in 2011 ($billions, in 2005 international dollars at various poverty lines) Region #countries $1.25 $2.00 $4.00 $10.00 East Asia and Pacific 12 13.5 92.9 643.9 3801.3 Europe and Central Asia 28 0.3 1.8 22.2 328.2 Latin America and Caribbean 25 5.8 16.8 89.6 679.3 Middle East & North Africa 11 0.5 5.6 81.1 617.5 South Asia 6 37.7 228.3 1171.9 4569.9 Sub-Saharan Africa 43 74.3 212.0 720.4 2485.8 TOTAL 125 132.1 557.4 2,729.1 12,482.1 TOTAL (2014 international $) 157.6 665.1 3,256.5 14,894.2 TOTAL (2014 $, factor 1/2.25) 70.0 295.6 1447.3 6619.6 15 Source: Calculated from World bank PovCalNet data using Don Sillers’s poverty calculator. The PPP adjustment factor of 2.25 is consistent with April 2015 WEO data.
THANK YOU 16
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