Building Statistical Capacity in MCC Countries. Guyslain Ngeleza

Transcription

1 Building Statistical Capacity in MCC Countries Guyslain Ngeleza

2 MCC model was intended to be evidence based First layer: Evidence that MCC is Addressing Poverty Second layer: Evidence that MCC Invests in Right Countries (Best Governed Countries) Third layer: Evidence that MCC Makes Investments that Spur Economic Growth Fourth layer: Evidence that MCC Meets Implementation Targets and Projects Have Long term Impacts

3 Investments that Spur Economic Growth MCC was created under the premise that private sector should be main driver of economic growth The key questions are: What are the factors that are deterring private investments in an eligible country? o What are the investment proposals that would relax some of the constraints preventing private investments? o Would the projects proposed yield sufficient return?

4 Constraints Analysis In MCC countries, as in most developing countries: Long list of potential constraints to private investments The key questions is: How to prioritize? MCC uses the Hausmann-Rodrik-Velasco (HRV) methodology: Suggests alternative explanations of why private investment is low Proposes a methodological approach to create platform to discuss which explanation has precedence over the alternatives

5 Alternative Explanations

6 Which Explanation Has Precedence?

7 Properties of a Potential Binding Constraint 3. Agents in the Economy Should be Attempting to Overcome or Bypass the Constraint E.g. if Electricity infrastructure is a biding constraint, it is expected that Many businesses investing in their own generators 4. Agents Less Intensive in a Binding Constraint Should be More Likely to Survive and Thrive, and Vice Versa E.g. A Small share of country value added in industries that are dependent on external finance would signal that finance may be a constraint

8 Economic Rates of Return and Beneficiaries Analysis MCC use the Costs-Benefits Analysis to determine the Economic Rate of Returns (ERRs) of projects Propose plausible scenario of what would happen in the next 20 years without the projects Develop plausible scenario of what would happen in the next 20 years with the projects Calculate ERR comparing the two scenario MCC has a requirement that every project that is funded by MCC resources must have an economic rate of return of at least 10%. Which segment of the population, according to poverty category, will benefit from MCC projects?

9 Data Challenges MCC needs: Cross-country datasets: comparable data Difficult to obtain time series sectoral data, but variation across sector E.g. Financial data easier to find compare to infrastructure data Outdated household survey: income distribution data Unreliable popular press and grey literature

10 MCC Initiatives MCC relies on ad hoc surveys: E.g. in Benin, Nepal, Senegal: ad hoc willingness to pay for energy surveys E..g. in Niger: ad hoc Farm operator survey MCC recent initiative: incorporate statistical capacity building as a separate activity in MCC compacts E.g. Niger compact (US $ 5 million)

11 Building Niger s Statistical Capacity to Bolster the Agricultural Sector

12 Increasing Niger s Statistical Capacity to Bolster the Agricultural Sector One of the barriers to smart development of a more resilient agricultural sector: lack of reliable and comprehensive data to inform policies and public spending. MCC experience during compact has been: basic data on crop production and yield is sparse. If such data is available, it tends to cover only a limited number of crops, Quality and reliability are low. Niger Compact includes a very important investment that will bolster the country s statistical capacity The compact will help provide a framework for Niger s national statistical system to generate and apply the basic data needed to guide decisionmaking. Far-reaching impact, allowing Niger to better use data to achieve and measure progress toward global initiatives like the Sustainable Development Goals (SDGs).

13 Building Niger s Statistical Capacity to Bolster the Agricultural Sector First step: develop a master plan to improve the capacity to collect, analyze, and report high-quality data Review existing global initiative on statistical capacity building Explore potential partnership with existing global initiatives Conduct an assessment to determine current and emerging need of statistical capacity building The master plan will guide investments in Niger s statistical capacity. This may include: developing relevant, timely, accurate and productive sector data, including data disaggregated by income level, gender and age. measuring economic growth and poverty reduction. developing the Nigerien Government s monitoring and evaluation capacity.