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Research Agenda

 Research Agenda for KCP II





  • Understanding the relationship between change in an economy’s structure and broader development goals, including poverty reduction
  • Roles of states, markets, and the private sector in promoting economic transformation (Hard vs. soft industrial policy)
  • Appropriate policies at each stage of development & comparative advantage
  • Governance issues for industrial upgrading and structural change
  • Role of agriculture versus other sectors; sector priorities and trade-offs
  • Green growth
  • Growth identification and facilitation
  • Light manufacturing study in Africa
  • Structural transformation in Africa


  • Macro data, especially on the sector composition of output
  • Better data on infrastructure investments
  • Better data on policy interventions over time
  • Firm-level data, especially to study productivity growth and firm-industry dynamics
  • Informal sector data to analyze the factors behind entry into and exit from informality
  • Household-level data (archival + new) to link to welfare outcomes and integrate with macroeconomic/sector/public finance data, including sub-national
Relevant country types:  Low-income predominantly agrarian or resource-rich economies seeking to move into middle-income status; and middle-income economies seeking to upgrade industries and diversify from manufacturing into services.
2. Opportunities 
  • Better understanding why some countries and places attain faster poverty reduction and more inclusive development than others at a given rate of economic growth
  • Governance challenges in ensuring better education, health, and social protection
  • Information to strengthen provider incentives
  • Better social protection
  • Policies to enhance access to finance
  • More inclusive global integration and/or regional integration, linked to global markets
  • Local governance and citizen participation
  • Rural development and sound natural resource management
  • “Clean energy” technologies: effects on the economy and access to energy; speed and composition of investment matter
  • Household, facility-level, public expenditure tracking, service delivery data
  • Data disaggregated by gender
  • Financial services data
  • New measures of inequality of opportunity


Relevant country types:  High levels of inequality and/or slow rates of poverty reduction, poor performance in moving toward MDGs, and regions with low levels of educational attainment and high infant mortality rates.
3. Risks 
  • More effective and cost-efficient social protection, including more automatic stabilizers in poor countries
  • Understanding the global financial crisis
  • Fragile and conflict-ridden states
  • Managing new and existing environmental risks
  • Addressing financial-sector vulnerabilities in light of the crisis
  • Global governance reform and policies to support new multi-polar growth and interconnected risk
  • Managing macro-financial risks posed by globalization
  • Major clean energy scale-up to limit global warming
  • Food price volatility: causes and impacts
  • More effective and cost-efficient social protection
  • Dynamics of poverty; everyday “micro risks”
  • Recovering from crises
  • Post-crisis perspectives on macroeconomic management
  • Panel data sets tracking the same households or firms over time
  • Addressing core data weaknesses in fragile states
  • Better data on environmental and natural resource risk factors, their consequences, and the costs of amelioration
  • Data on trade flows and trade policies; made available at no cost


Relevant country types: Fragile states; resource-rich economies; regions exposed to extreme weather conditions such as floods or drought; and regions highly integrated with global trade, financial markets, or movement of people.
4. Results 
  • Developing reliable measures of country performance, including benchmarking and identifying comparators
  • Monitoring impacts of crises, including on poverty and human development
  • Broader approach to “evaluation,” drawing on richer economic modeling, more diverse types of data, multiple disciplines, and tailored to strategic knowledge gaps in these areas
  • New types of data (mixed qualitative-quantitative methods)
  • New modeling tools suitable for “non-assigned” interventions
  • Different types of results measures (rates of return, poverty,  and other human development indicators)
  • Better data on poor people (poverty mapping and improving data quality)


Relevant country types: All developing countries, countries with a high share of aid-to-GDP, and regions where aid results are weak.

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