(cap) and its impact on inclusive growth - european …cap) and its impact on inclusive growth...
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EU’s Common Agricultural Policy
(CAP) and its Impact on Inclusive
Growth
Initial findings
Not for quotation
For comments only
June 2017
Why is the World Bank interested in
contributing to the mid-term review of the
CAP? World Bank has a long history of supporting agricultural and rural
development all over the world
International experience could provide insights
World Bank has supported agricultural development in some of the New
Member States (viz. Bulgaria, Romania, Croatia, Cyprus, Latvia, Slovakia)
Regular Economic Report Series addresses EU-wide policy issues:
– RER 2: Sustaining Recovery, Improving Living Standards (Fall 2015)
– RER 3: Growth, Jobs and Integration: Services to the Rescue (Fall 2016)
– Planned RER 4: the EU’s CAP and its Impact on Inclusive Growth (Fall 2017)
Inclusive growth: successful structural transformation, which starts in agriculture
Before economic transformation takes off, agriculture:
– large shares in economic output and the labor force
– but the share in economic output less than its share in the labor force,
– lower productivity of labor than in industry and services.
Industrial growth takes off:
– industry, and in particular manufacturing, increases its share in the economy
– pulls labor out of agriculture more or less rapidly.
Services takes over…
However, there are no shortcuts to getting it right:
– moving people from farms to factories to offices is difficult
– poverty reduction starts in agriculture, which then allows people to accumulate
the resources needed to successfully move out of agriculture (see for instance
China, next slide)
– in middle income countries, agriculture remains important for jobs and poverty
reduction
Sources: Kuznets and Chenery, and Timmer, 2009; Stiglitz, 2016; WDR 2008
Structural transformation: China lifted 600 million people out of poverty.
Agriculture is first poverty “responder”: 300 million lifted out of poverty due to higher
incomes in rural areas, not through migration
Manufacturing is the second: 300 million people migrated from farms to factories.
Source: Urban China 2014
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Marginal product of labor in relation to total across sectors in China
Agriculture Industry Services
2nd industry
to services
The 1st transformation
from agriculture to
industry
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GDP growth originating in agriculture is more
inclusive
Source: Ligon and Sadoulet, 2007. Background paper to the WDR 2008 (see website)
Based on data from 42 countries (1983-2003)
How does agriculture support
inclusive growth? On farm, by raising agricultural profits and labor incomes
– With agricultural wages often the reservation wage for unskilled laborers economy-wide
Locally, by raising non-farm profits and labor income via strong multipliers: – Local agricultural growth multipliers generally vary from around 1.5 to
2.0
– Local consumption linkages even larger than production linkages
– Non-farm component of the rural economy is most dynamic and productive when farming is thriving (Datt and Ravallion, 1996)
– Farm households themselves diversify income sources to manage risk and seasonality
– Few industries locate to rural areas due to lack of economies of scope
Sources: Johnston and Mellor (1961), Delgado and Alfano (1994), WDR 2008, Delgado et al.
(1998), Block and Timmer (1994)
Agriculture in the EU Agriculture (narrowly defined as primary production):
– 1.4 percent of GDP
– 4 percent of total employment\
In 2010, in terms of numbers, 97 percent of all holdings were family farms:
– only 16 percent of total agricultural labor was performed by non-family workers
– Family farm households diversify their income sources (see next slide)
– Share of corporate farming in terms of area can be high in some NMS
Agriculture and agri-food businesses:
– 6 percent of GDP
– nearly 25 percent of total employment
Important social protection function for poor or vulnerable rural households:
– even in high-income countries, e.g. Greece after economic crisis
Contributes to rich variety of landscapes and habitats.
Farming is only part of farm
household income
Period Farming Off-farm
Investment and
property Transfers Others Total
Austria 2004-6 54 30 17 100
Denmark 2004-6 42 43 7 7 0 100
Finland 2003-5 27 42 18 13 0 100
France 2003 53 31 9 8 100
Germany 2003/4-5/6 80 20 100
Ireland 2004/5 32 45 2 19 2 100
Netherlands 2004/6 74 11 15 100
Poland 2003/6 67 8 21 3 100
UK 2002/3-4/5 40 28 21 11 0 100
average 52 30 11 13 7 100
Source: OECD, 2009
Farm Family Income (FFI) in Euro per Family Work Unit (FWU)
The European Model of
Agriculture
Competitiveness Sustainability Multifunctionality Across all regions
• Increase productivity
• Stabilize markets
• Availability of supply with affordable prices
• Improving rural livelihoods
Pillar I • Direct Payments – decoupled and coupled to
production
• Common Market Organizations
Pillar II Rural Development
Policy
Common Agricultural Policy (CAP) Shared Values, Common Objectives, 2 Financial Instruments
The Early
Years – 60s
Over
production
Exploding
expenditure
International
friction
Structural
measures
CAP in the
80s
Reduced
surpluses
Income
stabilisation
Budget
stabilization
Environment
and rural
measures
1992
Reform
Deepening
the reform
process
Food safety
and quality
Rural
development
as a 2nd Pillar
Reduction of
couples
payments
Consumer
concerns
Enhanced rural
development
WTO
compatibility
2003
Reform
Greening
Producer
organizations
Young farmers
Innovation &
research
Stability funds
2013
Reform
Food supply
Improving
productivity
Market-
stabilisation
Product
support
Agenda 2000 Agenda 2000
Market support
Enhancing production
capacity
Market orientation &
limiting public spending Diversity, competitiveness,
sustainability
Reforms of the CAP
CAP Pillar 1: decoupled payments
largely replaced coupled payments
Source: EC, staff calculations
Result: less distortions EU agricultural commodity prices
no longer very much above international prices
Source: EC, staff calculations, 2017.
7/5/2017 14
World Bank study on role of the CAP Assessing past impact on inclusive growth to distill policy
suggestions for the future on:
– Poverty
– Agricultural productivity
– Agricultural employment (including family labor)
– Local economic growth and rural employment
Methodology:
– Overall approach: time series of countries and regions (NUTS 1, 2 and 3)
– with the “treatment” (CAP programs) coming in at different years, and at
different intensities and mixes
– Not a “snapshot”, not a simulation
Methodology
Heterogeneity—in local conditions and how CAP is implemented—is a blessing and a curse:
– Correlation patterns need stakeholder and local knowledge to interpret and draw policy lessons
– Attribution and causality will be impossible to establish…
Data on farm and non-farm income are incomplete, while definitions vary by country
Poverty in the EU:
absolute poverty levels differ starkly
Note: (1) Data source: EU-SILC 2011, Eurostat; (2) Absolute poverty line: $21.7 PPP2011; (3)
Relative poverty line: 60% of national median
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Pove
rty
(per
cen
t)
Population at risk of poverty NUTS 3 regions
Agriculture and poverty are not
correlated…
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Nu
mb
er o
f p
oo
r
0 20 40 60 80 100Agriculture share of area
Number of poor Fitted values
Number of poor and agriculture share of area (zoomed)
Very small farms are in areas of high
poverty…
but so are very large farms
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20
25
30
35
Pover
ty r
ate
0 100 200 300Average plot size (hectare)
Predictive Margins with 95% CIs
Agricultural jobs and income reduced poverty (2009 to 2013; in percentage points of changes in poverty)
20 Note: (1) Data source: EU SILC, Eurostat 2010-2014 (Survey years); Shapley Decomposition, author’s own calculation.
Anchored poverty to 2009 relative threshold (income year)
In contrast to non-agricultural jobs and average earnings (2009 to 2013; results in percentage points of changes in poverty)
21
Note: (1) Data source: EU SILC, Eurostat 2010-2014 (Survey years); Shapley Decomposition, author’s own calculation.
Anchored poverty to 2009 relative threshold (income year)
Regions with higher household diversification
have greater poverty reduction
22
Notes:
(1) Panel Fixed Effects; All regressions include year fixed effects; (2) Anchored Relative Poverty line (60% of
median at 2011); (3) Data Source: EU-SILC, Eurostat; (4) Symbols: ** P<0.01, * P<0.05, +P<0.1
(1) (2) (3)
Poverty rate Poverty rate Poverty rate
Share of individuals living in agriculture households 0.64+ 0.18 0.50+
Household diversification index -1.71* -0.96+
GDP per inhabitant -0.01** -0.01**
Share of inhabitants with secondary education 0.06 0.05
Share of inhabitants with tertiary education -0.00 -0.01
Unemployment rate
R-Squared:
Within 0.38 0.44 0.45
Between 0.18 0.14 0.16
Overall 0.25 0.14 0.17
Observations 928 928 928
CAP payments go to areas of absolute
poverty
23
(3.1.1) (3.1.2) (3.1.3) (3.1.4) (3.1.5) (3.1.6) (3.1.7) (3.1.8) (3.1.9) (3.1.10)
LABELS Poverty rate Poverty rate Poverty rate Poverty rate Poverty rate Poverty rate Poverty rate Poverty rate Poverty rate Poverty rate
Total CAP payments 1.40e-08 1.60e-08*
Pillar 1 CAP payments 7.92e-09 1.12e-08+
Pillar 2 CAP payments 1.07e-07** 1.01e-07**
Pillar 1 coupled CAP payments -6.55e-08 -4.78e-08
Pillar 1 decoupled CAP payments 1.30e-08 1.43e-08
Population density(Inhabitants per hectare); 0.0970* 0.0944* 0.0965+ 0.0814* 0.107*
Gross Domestic Product(Purchasing power
standard (PPS) per inhabitant)
-0.000144+ -0.000147+ -0.000139* -0.000146* -0.000150*
Poverty line -0.000378* -0.000347* -0.000844** -0.000358* -0.000489*
Number of zero-beneficiaries 1.214+ 1.240+ 2.993 1.320+ -1.323
Constant 13.22** 22.12** 13.58** 22.09** 12.01** 28.83** 13.94** 22.60** 13.51** 25.12**
Country fixed effects Y Y Y Y Y Y Y Y Y Y
Observations 1,150 1,150 1,150 1,150 1,150 1,150 1,150 1,150 1,150 1,150
Adj R-squared 0.261 0.322 0.257 0.318 0.281 0.326 0.260 0.320 0.259 0.306
Note:
(1) Data source: EU 2011 Poverty Map (DG-REGIO and World Bank), 2010 Farm Structure Survey (Eurostat), and EU National Statistic
Institutes (Eurostat);
(2) Symbols: ** p<0.01, * p<0.05, + p<0.1;
(3) Missing observations in agricultural indicators are treated as zero;
(4) Luxemburg, Cyprus Republic, Croatia and Estonia are not being analyzed here
Note: All regressions include year fixed effects
CAP payments are associated with areas in
which poverty has fallen the fastest
24
(1) (2) (3) (4) (5) (6) (7) (8)
Poverty rate Poverty rate Poverty rate Poverty rate Poverty rate Poverty rate Poverty rate
Poverty rate
Total payments -0.05+ -0.05* -0.05** -0.05** -0.04 -0.04
Payments to pillar1 -0.02 -0.08+ -0.02 -0.10* -0.03
Payments to pillar2 -0.02 -0.08+ -0.02 -0.10* -0.03
Coupled payments -0.02 0.03 -0.01
Decoupled payments 0.01 0.05 0.01
Agricultural employees 0.02 0.02 0.02 0.02 0.02 0.02 0.02 0.02
GDP per inhabitant -0.01* -0.01* -0.01* -0.01* -0.01* -0.01* -0.01* -0.01*
Share of inhabitants with secondary education
0.14+ 0.14* 0.14* 0.14* 0.14* 0.14* 0.14* 0.14*
Share of inhabitants with tertiary education
0.05 0.05 0.04 0.04 0.06 0.05 0.05 0.05
Unemployment rate 0.18 0.18 0.18 0.18 0.19 0.18 0.18 0.18
R-Squared:
Within 0.47 0.47 0.47 0.47 0.47 0.47 0.47 0.47
Between 0.40 0.39 0.40 0.40 0.40 0.39 0.40 0.39
Overall 0.41 0.40 0.41 0.41 0.41 0.40 0.41 0.41
Observations 803 803 803 803 803 803 803 803
Literature Review on CAP impact
Growth: little to mixed impact
– Studies using simulation, mathematical and/or partial equilibrium modelling: mixed impact
– Survey data based methods: little impact
Productivity: negative impact
– Overall, negative; coupled: negative, but decoupled more positive
Employment:
– Pillar 1: negative impact
– Pillar 2: mixed impact
Gender, youth:
– CAP drives up land prices, which constrains access for these groups
CAP direct payments are biased towards large land holdings:
– About 80 percent of payments (70 percent of the CAP or 28 percent of the total EU budget),
go to only 20 percent of the farmers
Growth, productivity and jobs:
preliminary results
Panel regression at NUTS 2 regional level (EU28; 1989-2013)
CAP components:
– Pillar I payments (coupled and decoupled subsidies)
– Pillar II
Impact on:
– regional GDP growth;
– agricultural productivity, as measured by agricultural VA per worker; and
– the share of agricultural labor as a share of total labor
In Old Member States (OMS) and New Member States (NMS)
Regional GDP Growth CAP expenditures are positively correlated with regional GDP growth,
– findings measure “gross effects”, without taking into account the negative
effects of taxation for financing of these expenditures
Regional GDP is lower in regions with a high share of agricultural
employment
– because of lower productivity in agriculture compared to other sectors
– are CAP payments keeping resources in low-productive activities?
Growth effect is stronger for “non-distortionary” CAP support (which
includes both pillar 2 payments and decoupled pillar 1 payments)
– In OMS, where Pillar 1 historically was mostly coupled payments
(“distortionary”), Pillar 2 effects are stronger
– In NMS, where Pillar 1 is mostly decoupled, little difference between Pillars
Agricultural Productivity
In theory, effects of CAP payments on agricultural productivity:
– Negative by distorting optimal resource allocation—especially for coupled
payments
– Positive by reducing credit constraints—especially for decoupled and in regions
with strong credit constraints, like NMS
– Positive by mitigating risk—especially for decoupled
OMS: we find no significant impact of CAP payments on productivity
– Do the negative effects offset the positive effects?
NMS: strong positive impact of CAP payments on productivity
– Possibly because NMS has most payments are decoupled (Pillar 1 and 2) and
thus less distortionary)
Hypothesis: decoupling of CAP contributed to positive effect on
agricultural productivity
Agricultural Employment
In OMS: CAP payments tend to reduce outflow of labor of agriculture
– Only non-distortionary subsidies (Pillar 1 decoupled and Pillar 2) have a
significant effect
– Do decoupled, non-distortionary payments stimulate higher productivity
agriculture, in contrast to the coupled payments which keep farmers in low
productivity agriculture?
In NMS: no impact of CAP payments on agricultural employment
– Is increased productivity effect offset by shift from labor to other inputs (land
and capital), as payments were linked to land?
– Is there a bias of CAP payments to larger, less labor-intensive farms?
Growth, productivity and jobs: preliminary CAP policy suggestions
Three indicators of “jobs and growth”: regional GDP, agricultural labor
productivity and agricultural employment
Hypothesis:
– Non-distortionary policies (decoupled payments in Pillar 1 and investment
support in Pillar 2) performed better than coupled payments.
Policy implications:
– continue reform shift from coupled payments to decoupled payments (in Pillar
1) and to rural development and other measures (in Pillar 2)
– target payments better to poverty reduction and job creation
7/5/2017 31
Overall strategic agenda To meet the challenge of inclusive growth:
– Rural and agricultural growth is needed
– As part of successful structural transformation
Macro agenda:
– Reduce urban bias in basic services, e.g. health, education (including life-long learning), internet.
Sector agenda:
– Rural roads, electricity and communications, including internet
– Rural finance, savings and insurance, risk management
– Agricultural extension and technology transfer
– Support environmental services more efficiently by better targeting CAP payments
– Add value to basic farm products through quality labels, short supply chains, on-farm diversification, producer organizations, etc.
Timeline
Further analysis (July, 2017)
Field visits and revised analysis (August, 2017)
Draft report for comments (early September, 2017)
Review workshop (mid September, 2017)
Final report (mid October, 2017)
Team Rogier van den Brink, Hans Kordik and Joao Pedro Wagner De Azevedo (co-
Task Team Leaders, World Bank)
Team members: Jo Swinnen, Maria Garrone, Dorien Emmers (University of
Leuven), Attila Jambor (Corvinus University, Budapest), Alessandro Olper
(University of Milan), Matija Laco, Marianne Grosclaude, Paul Andres Corral
Rodas, Emilia Skrok and others (World Bank)
Reviewers: Tassos Haniotis, Director for Strategy, Simplification and Policy
Analysis of DG AGRI (European Commission), Holger Kray (Lead Agriculture
Economist, World Bank), Csaba Csaki (Professor at Corvinus University), Hans
Binswanger (University of Pretoria) and Alan Mathews (Department of
Economics, Trinity College Dublin)
Advisor: Dacian Julien Cioloș (former European Commissioner for Agriculture
and Rural Development and Prime Minister of Romania)