how pro poor are productivity gains in agriculture? …

HOW PRO‐POOR ARE PRODUCTIVITY GAINS IN AGRICULTURE?

THE CASE OF THE NATIONAL AGRICULTURAL INVESTMENT PLAN OF BENIN

Harald Grethe, Jonas Luckmann, Khalid Siddig, Thierry KinkpeInternational Agricultural Trade and Development Group

Humboldt-Universität zu Berlin

23rd Annual Conference on Global Economic Analysis, Virtual Meeting, June 17-19, 2020

Background – Investments in Agriculture

Agricultural investments in developing countries: higher productivity/production lower food prices economic growth, poverty-alleviation (Breisinger et al. 2011)

Producers may be adversely affected: Cost reductions vs. decline in output prices Agricultural treadmill (Cochrane 1958; Evenson and Gollin 2003) Inelastic demand for staple crops Declining prices of more productive production factors More inequality (rural ↔ urban, poor ↔ rich)

Aim of this study: Analyzing distributive effects of increases in agricultural productivity and options to make such increases more pro-poor

Grethe, H., Luckmann, J., Siddig, K. and T. Kinkpe: How pro‐poor are productivity gains in agriculture?

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Benin's Agriculture and the PNIASAN

Agriculture: 23% of GDP, 43% of labor force (World Bank 2020 a,b)

Important sector for Beninese economy and development Low productivity

National Plan for Agricultural Investment and Food and Nutritional Security (PNIASAN) 2017 – 2021 Main aim: boost agricultural productivity, reduce poverty Measures:

Better access to agricultural inputs Training & extension Improved infrastructure Mechanization

Financing: 2.7 billion USD Annually: 140 USD/ha, 5% of GDP in 2015 44% private funding 6% increase in overall government budget


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Wikimedia, 2011

Yield, production and implicit area growth rates underthe PNIASAN, 2021 compared to 2011-15 average

Yield Production % %

Cotton 69.9 106.4Pineapple 35.5 63.0Rice 51.0 78.1Cashew 84.6 77.8Cassava 43.6 46.1Maize 11.4 42.3Tomato 21.1 25.0Pepper 15.2 25.0Potato 14.6 25.0Onion 13.7 25.0Okra 13.4 25.0Leafy vegetables 10.6 25.0Sum


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(MAEP 2017, p.28)

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Grethe, H., Luckmann, J., Siddig, K. and T. Kinkpe: How pro‐poor are productivity gains in agriculture?Grethe, H., Luckmann, J., Siddig, K. and T. Kinkpe: How pro‐poor are productivity gains in agriculture? (MAEP 2017, p.28)

Yield, production and implicit area growth rates underthe PNIASAN, 2021 compared to 2011-15 average

Yield Production Implicit Area% % % +1,000 ha

Cotton 69.9 106.4 21.5 55.6Pineapple 35.5 63.0 20.3 1.1Rice 51.0 78.1 17.9 11.7Cashew 84.6 77.8 -3.7 -12.8Cassava 43.6 46.1 1.8 4.7Maize 11.4 42.3 27.8 261.1Tomato 21.1 25.0 3.2 1.2Pepper 15.2 25.0 8.5 2.1Potato 14.6 25.0 9.1 0.0Onion 13.7 25.0 9.9 0.4Okra 13.4 25.0 10.2 1.5Leafy vegetables 10.6 25.0 13.0 1.4Sum 328.0

Modelling Approach – General Setup

Recursive dynamic CGE model based on Diao and Thurlow (2012)

2015 Social Accounting Matrix (SAM) for Benin:

4 primary factors: skilled labor, unskilled labor, capital, and land

10 household groups (rural and urban, each with five income quintiles)

38 production sectors, producing 38 commodities

Transdisciplinary setting


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Modelling Approach – Closure Rules

Fixed exchange rate and foreign savings, flexible CPI

Investments fixed as share of total absorption, saving rates change uniformly (PNIASAN scenario: savings-driven investment)

Flexible government savings and fixed tax rates in the BAU (adjusted under PNIASAN and sensitivity analysis settings)

Fully employed factors, labor and land: mobile, capital: activity- specific (putty-clay)

Fixed world market prices


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Modelling Approach – BAU Scenario


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Own calculations based on IMF 2019, UN 2019, World Bank 2019

100

150

200

250

300

350

400

2015 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030

Agricultural GDP Industrial GDP Service GDP Labour force Land

Modelling Approach – PNIASAN Scenario9


%-point differences compared to BAU2017 2018 2019 2020 2021

Productivity increase of crops

Local maize 1.5 1.5 1.5 1.5 1.5Improved maize 10.1 10.1 10.1 10.1 10.1Rice 8.4 8.4 8.4 8.4 8.4Cassava 4.4 4.4 4.4 4.4 4.4Yam 1.5 1.5 1.5 1.5 1.5Pineapple 8.9 8.9 8.9 8.9 8.9Fresh vegetables and spices 1.5 1.5 1.5 1.5 1.5Other food crops 1.5 1.5 1.5 1.5 1.5Cotton 10.9 10.9 10.9 10.9 10.9Cashew 3.1 3.1 3.1 3.1 3.1Palm nut 1.5 1.5 1.5 1.5 1.5

Other crops for industry or export1.5 1.5 1.5 1.5 1.5

Productivity increase of animal products

Meat 5.6 5.6 5.6 5.6 5.6Milk 6.6 6.6 6.6 6.6 6.6Eggs and other husbandry 10.7 10.7 10.7 10.7 10.7

Investment in fishing/aquaculture sector 27.0 27.0 27.0 27.0 27.0

Modelling Approach – PNIASAN Scenario10

%-point differences compared to BAU2017 2018 2019 2020 2021

Land supply 2.4 2.4 2.4 2.4 2.4

Household direct tax rate

Rural quintile 4 0.5 0.4 0.4 0.4 0.4Rural quintile 5 0.6 0.5 0.5 0.5 0.5Urban quintile 3 0.9 0.8 0.8 0.8 0.8Urban quintile 4 1.2 1.1 1.0 1.0 1.1Urban quintile 5 2.5 2.2 2.1 2.1 2.2

Million USDAdditional government revenue from direct tax 92.1 92.2 103.6 119.2 139.5


Effects of the PNIASAN: Agriculture

17.1%

-15.1%

21.4%

-20%

-15%

-10%

-5%

0%

5%

10%

15%

20%

25%

Agricultural production Average agricultural prices Agricultural GDP

Diff

eren

ce in

202

1 co

mpa

red

to B

AU

scen

ario

GDP at constant prices(at current prices almostconstant)


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Effects of the PNIASAN: Agricultural production quantities and prices

69%15%

13%10%

16%11%

22%18%

162%-4%

8%18%18%

23%7%

28%

-30%-30%

-20%-7%

-34%-10%-11%

-23%-16%

-12%-11%

-18%-24%

-36%-4%

-42%

-50% -25% 0% 25% 50% 75% 100% 125% 150% 175%

MaizeRice

CassavaYam

PineappleVegetables

Other food cropsCotton

CashewPalm nut

Other cropsLive animals

Raw milkEggs

Hunting & sylvicult.Fishing

Difference in 2021 compared to the BAU scenario

Production PriceGrethe, H., Luckmann, J., Siddig, K. and T. Kinkpe: How pro‐poor are productivity gains in agriculture?

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Effects of the PNIASAN: Macroeconomic indicators

4.7%

5.0%

6.0%

4.4%

0% 1% 2% 3% 4% 5% 6% 7%

Total absorption

GDP at factor cost

Total exports

Total imports

Difference in 2021 compared to the BAU scenario


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Effects of the PNIASAN: household income

-2.9%

1.3%

3.4%

4.5%5.3%

1.4%

3.1%3.8% 3.9%

5.8%

4.4%

3.5%

5.1%

-4%

-2%

0%

2%

4%

6%

Q1 Q2 Q3 Q4 Q5 Q1 Q2 Q3 Q4 Q5 All Rural Urban

Rural Urban Aggregated

Diff

eren

ce in

202

1 co

mpa

red

to th

e BA

U

scen

ario


14

Effects of the PNIASAN: factor prices

2.4%

8.1%10.1%

-20.8%-25%

-20%

-15%

-10%

-5%

0%

5%

10%

15%

Unskilled labor Skilled labor Capital Land

Diff

eren

ce in

202

1 co

mpa

red

to th

e BA

U

scen

ario


15

Effects of the PNIASAN: Household welfare

1.3%

3.9%

5.4% 5.4%4.9% 4.9% 4.8%

4.1%

3.4%2.9%

3.8%

4.8%

3.2%

0%

1%

2%

3%

4%

5%

6%



Equi

vale

nt v

aria

tion

in %

of

base

line

inco

me

in 2

021

• The rural benefit more than the urban• The rural rich benefit more than the rural poor• The urban poor benefit more than the urban rich


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Alternative: Funding via sales tax17


0%

1%

2%

3%

4%

5%

6%



Equi

vale

nt v

aria

tion

in %

of

base

line

inco

me

in 2

021

Direct tax Sales tax

Effect until 2030 – Household welfare

-1%

0%

1%

2%

3%

4%

5%

6%

7%

8%

9%

2015 2017 2019 2021 2023 2025 2027 2029Equi

vale

nt v

aria

tion

in %

of

base

line

inco

me

Rural Q1 Rural Q2 Rural Q3 Rural Q4 Rural Q5Urban Q1 Urban Q2 Urban Q3 Urban Q4 Urban Q5


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Conclusions and policy implications

Two policy implications:1. Increasing productivity in agriculture and enhancing land supply leads to

lower agricultural and food prices Desirable from a consumer perspective but problematic for agricultural producers Facilitate agricultural supply from Benin to be processed as well as traded

especially to neighboring countries Market information systemsRoadsReduced red tape in export…


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2. While the productivity and land targets of the PNIASAN make the economy of Benin better off, their effects are not automatically pro-poor:

With respect to income, richer households benefit more than poorer households

Looking at total welfare, the effects are not pro-poor in rural areas

Complementary policies/measures needed in order to reach more balanced growth


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Pro-poor plan implementation Targeting of measures at low-income farm households:Extension servicesMicro-financeAccess to inputs

As high income households benefit most in absolute terms from the plan: Involve them overproportionally in the funding Collect taxes from a wider tax base and focus tax collection on high income

groups


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Thank you for your attention!


Sources

Breisinger, C., Diao, X., Thurlow, J., & Hassan, R. M. A., 2011. Potential impacts of a green revolution in Africa-the case of Ghana. Journal of International Development, 23, (1, 82–102). doi:10.1002/jid.1641

Cochrane, W. W., 1958. Farm Prices: Myth and Reality. St. Paul: University of Minnesota Press. Diao, X. and J. Thurlow, 2012. A Recursive Dynamic Computable General Equilibrium Model. In Strategies and Priorities for African Agriculture:

Economywide Perspectives from Country Studies, edited by X. Diao, J. Thurlow, S. Benin, and S. Fan. pp. 17-50. Washington D.C.: International Food Policy Research Institute.

Evenson, R. E., & Gollin, D., 2003. Assessing the impact of the green revolution, 1960 to 2000. Science, 300, (5620, 758–762). doi:10.1126/science.1078710

FAO, 2019. FAOSTAT, http://www.fao.org/faostat/en/#home, accessed in September 2019. IMF, 2019. World Economic Outlook Database (International Monetary Fund (IMF), Ed.), Washington D.C.

https://www.imf.org/external/pubs/ft/weo/2019/02/weodata/index.aspx. MAEP, 2017. Plan Stratégique de Développement du Secteur Agricole (PSDSA) 2025 et Plan National d’Investissements Agricoles et de Sécurité

Alimentaire et Nutritionnelle PNIASAN 2017 – 2021. Ministry of Agriculture, Husbandry and Fishing. Cotonou, Benin. http://www.agriculture.gouv.bj/IMG/pdf/psdsa_2025_et_pniasan_2017_-_2021_version_finale_adoptee.pdf

United Nations, 2019. United Nations World Population Prospects: The 2019 Revision. Custom data acquired via website. New York: Department of Economic and Social Affairs, Population Division. Consulted on 05/09/2019. https://population.un.org/wpp/

World Bank, 2019. World Development Indicators. World Bank, accessed on 05/09/2019. https://databank.worldbank.org/source/world-development-indicators.

World Bank, 2020a. Benin Country Data accessed on 03/03/2020. https://data.worldbank.org/country/benin World Bank, 2020b. World Band DataBank Indicators, accessed on 03/03/2020. https://data.worldbank.org/indicator


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http://www.fao.org/faostat/en/#home

http://www.agriculture.gouv.bj/IMG/pdf/psdsa_2025_et_pniasan_2017_-_2021_version_finale_adoptee.pdf

https://population.un.org/wpp/

https://databank.worldbank.org/source/world-development-indicators

https://data.worldbank.org/country/benin

https://data.worldbank.org/indicator

how pro poor are productivity gains in agriculture? …

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