the role of publicpolicy in risk management: the case of ... · • 2. evolutionof risk management...
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The role of public policy in riskmanagement: The case of the
Hungarian Risk Management System
„Risk in the food economy – theory and practice”
Jachranka, 23th to 25th November 2016
Anikó Juhász, Gábor Kemény, András Molnár, Anna Zubor-Nemes
Outline of the presentation
• 1. Grounds of high risk exposure in Hungary• 2. Evolution of risk management tools – an overview• 3. Management of crop production risks – the MKR• 4. Operation of MKR between 2012 and 2015• 5. Future plans developing risk management tools in MKR
Hungary – why so important to tackle risks?
• Landlocked position• Far from markets• High cropland ratio – greatcrop production potential
• Continental/pannonian climate = high crop yieldvolatility
Hungary – why so important to tackle risks?
Source: EU FADN, Eurostat
‐40
‐30
‐20
‐10
0
10
20
30
40
50
2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014
Wheat price deviations from EU average (in percent)
(DEU) Germany (FRA) France (NED) Netherlands
(OST) Austria (BEL) Belgium (ITA) Italy
(HUN) Hungary‐40
‐30
‐20
‐10
0
10
20
30
40
2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014
Corn price deviations from EU average (in percent)
(DEU) Germany (FRA) France (NED) Netherlands
(OST) Austria (BEL) Belgium (ITA) Italy
(HUN) Hungary
‐25
‐20
‐15
‐10
‐5
0
5
10
15
20
25
2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014
Wheat yield deviations from MS's average (in percent)
(DEU) Germany (FRA) France (NED) Netherlands
(OST) Austria (BEL) Belgium (ITA) Italy
(HUN) Hungary
‐50
‐40
‐30
‐20
‐10
0
10
20
30
2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014
Corn yield deviations from MS's average (in percent)
(DEU) Germany (FRA) France (NED) Netherlands
(OST) Austria (BEL) Belgium (ITA) Italy
(HUN) Hungary
‐60
‐40
‐20
0
20
40
2004 2005 2006 2007 2008 2009 2010 2011 2012 2013
Milk Farm Net Income deviations fromMS'saverage (in percent)
(DEU) Germany (FRA) France (NED) Netherlands
(OST) Austria (BEL) Belgium (ITA) Italy
(HUN) Hungary
‐60
‐40
‐20
0
20
40
60
2004 2005 2006 2007 2008 2009 2010 2011 2012 2013
Fieldcrop Farm Net Income deviations from MS's average (in percent)
(DEU) Germany (FRA) France (NED) Netherlands
(OST) Austria (BEL) Belgium (ITA) Italy
(HUN) Hungary
• Lower prices• Greater crop yield variability• Greater income variability
‐80‐60‐40‐200
20406080
2004 2005 2006 2007 2008 2009 2010 2011 2012 2013
Granivores Farm Net Income deviations fromMS's average (in percent)
(DEU) Germany (FRA) France (NED) Netherlands
(OST) Austria (BEL) Belgium (ITA) Italy
(HUN) Hungary
Evolution of production risk management scheme in Hungary• I. step – 1997‐2003 – 30 % flat rate subsidy to insurance fees • Problems: continuous mismatch between risks covered by insurances and damages caused by risks, only 30‐40% penetration
Hail and storm21%
Frost (at winter and spring)16%
Drought42%
Water (flood, inland water and heavy rain)
18%
Other3%
Average proportion of damages caused by adverse climatic events
Hail87%
Frost5%
Storm5%
Other3%
Average proportion of risks covered by insurances
Evolution of production risk management scheme in Hungary• II. step – 2007‐2011 – National Damage Mitigation Fund against all risks• Problems: low penetration, very high compensation claims vs. low rateof damage mitigation, high administration burden, reduced number of insured farmers
0%
20%
40%
60%
80%
100%
120%
0,0
20,0
40,0
60,0
80,0
100,0
120,0
140,0
160,0
2007 2008 2009 2010 2011
Claims and payments in the NMF
Mitigation payments Compensation claims Rate of mitigation (right axis)
Evolution of production risk management scheme in Hungary• III. step – since 2012 – Agricultural Risk Management System (MKR)• Two pillars: I. pillar – Compulsory National Damage Mitigation Fund
Mitigation over 15% loss of farm level AND 30% loss of crop level by all climatic risksII. pillar – Voluntary insurance subsidised by the stateCompensation over 30%/50% loss of crop level by 8 risktypes
• Common risk definitions, common reference crop yields• Interdependencies – only 50% of mitigation payments withoutinsurance, the compensation payment is deductable from mitigationpayments
Structure of MKREAFRD + national sourcefee subsidy (65% : 35%)
National Damage Mitigation Fund –farmers + state aid
(50% : 50%)
Farmers
Private insurancecompanies
Public damagerequierementsjustification
A, B, C insurance typesregulated by the state(min. 55% : 40% : 30%
rate of subsidy)
Insurancefee
Crop lossescaused byadverse c. events
Compensationpayments
Mitigationpayments
Compensationclaims
I. pillar
II. pillar
Information about the insurance contract and the compensation payments
Operation of MKR
• Members of the system:• 77 thousand farmers• 11 insurance companiesand mutual funds
• 19 regional governmentoffices
• 8 central offices and institutes ARDA
Market insurance
MRD
AKI IGCRS HMS GDWM
Regional government offices
Insurance contracts
Insurance claim reporting
Insurance compensation
Client registration
Damage notification
Damage claim notification
Insurance contract
data
Insurance compensation
data
Common Master Data Management System
Customer register
Register of activitiy area
Farmers
InterfaceElectronic notice of loss and subsidy claim declaration for
farmers
Interface
Statistical and
reporting system
Agricultural risk management data
baseControl of damage
determination
FADN data collection
Professional supervision and coordination of
damage determination
Functional supervision and coordination of damage
determination
Interface Interface Interface Interface Interface Interface
Improved FADN (plot-level yield data
collection)
Agricultural Risk Management
Systems
Analysis of profit, cost and income data
Remote sensing damage assessment
method
Operation of Remote Sensing Damage
Assessment Ssystem
Satellite images
Remote sensing damage
assessment software and data
processing
Basic meteorological data services for the
determination of damage
Extended Meteorological Data Collection System
Damage determination workflow supporting software
Meteorological data processing method
Meteorological data storage ICT
infrastructure
Operation of Damage Mitigation Fund, management of
compensation contributions, determination, payment and accounting of compensation or/and insurance subsidies
Improved compensation and
subsidy management system
Improved claim management
system Determination of damage
Damage determination control supporting ICT
infrastructure and software
Operation of the Hungarian FADN System
Payment of mitigation
contribution
Basic data services of inland water for the
determination of damage
Extended Defence Information System
Interface
General management of Agricultural Risk Management System (supervision, analysis
and planning)
Login to Compensation System (EK)
Determining the amount of
compensation contribution
Payments of compensation
Interface
HCA NFCSO
Covered risks in MKR
RisksHail, Storm, Fire
Winter/springfrost
DroughtHeavyrain, flood
Inlandwater
I. pillar >15% farm level, >30% crop level
II. pillar>30% croplevel
>50% croplevel
>50% croplevel
>40% croplevel
‐
Private add. i.
>5% to <30% crop level
‐ ‐ ‐ ‐
Wheat, 2010 June in inland water
Corn crashed by hail, June 2010Browned apple flowers afterspring frost, April 2012
Corn, August 2011
Sunflower, August 2011
Corn, June 2010 after heavy rain
Wheat, 2010 June in inland water
Payment versions in MKR• I. pillarwithoutinsurance
hail fire storm winter frost drought inlandwater
heavyrain
yield
average yield (100%)
damage mitigation(reduced by 50%)
springfrost
flood
30% deductable
damaged yield: 45%
Payment versions in MKR
A i. payments
• I. pillar• II. pillar
• A insurance
average yield (100%)
30% deductable
50% deductable
damaged yield: 45%
hail fire storm winter frost drought inlandwater
heavyrain
springfrost
flood
yield
damage mitigation
Payment versions in MKR
Private add. i. payments
• I. pillar• II. pillar
• A insurance• +privateadditional i.
average yield (100%)
30% deductable
50% deductable
damaged yield: 45%
hail fire storm winter frost drought inlandwater
heavyrain
springfrost
flood
yield
A i. paymentsdamage mitigation
5% deductable
Main indicators of the first pillar (2012‐2015)
74,177,6 78,3
72,5
0
10
20
30
40
50
60
70
80
90
2012 2013 2014 2015
thou
sand
Number of agricultural producers
87,893,7 92,6 91,8
0
10
20
30
40
50
60
70
80
90
100
2012 2013 2014 2015
per cen
t
The proportion of agricultural area covered by firstpillar
0
5
10
15
20
25
30
2012 2013 2014 2015
HUF billion
Financial sources of first pillar
Sources of currentyear
Sources fromprevious years
93,9
28,4
11,8
61,8
0
10
20
30
40
50
60
70
80
90
100
2012 2013 2014 2015
thosuand
hectare
Damaged area in case of first pillar
7 411
2 453
1 199
6 050
0
1000
2000
3000
4000
5000
6000
7000
8000
2012 2013 2014 2015
HUF million
Mitigation benefits in case of first pillar
• Number of participants has been changed in the periodof 2012‐2015. Memberscovered 66,6 per cent of producers in 2015.
• Increasing financial sources
• The weather conditionswere in 2012 and 2015 more unfavourable thatresulted in greaterdamaged area and highermitigation benefits
Main indicators of the second pillar• Number of insurancecontracts significantlyincreased
• Income from insurancefee also significantly rose
• The insurance paymentswere the highest in 2015 because of unfavourableweather conditions
1 896,0
8 194,0
7 302,0
8 664,0
0
1000
2000
3000
4000
5000
6000
7000
8000
9000
10000
2012 2013 2014 2015
Number of insurance contracts
1467
3724
5658 5746
0
1000
2000
3000
4000
5000
6000
7000
2012 2013 2014 2015
HUF million
Income from insurance fee
512
908
634
1 513
0
200
400
600
800
1000
1200
1400
1600
2012 2013 2014 2015
HUF million
Insurance payments
Insurance payments 2012 and 2015
Drought; 9,3%
Storm; 5,5%Heavy rain; 0,5%
Flood; 1,2%
Spring frost; 1,5%Fire; 0,5%
Hail; 81,7%
Insurance payments by risks (2012‐2015)
3 13
153
415
32
159
597
888
11 98
512
765
24 140
866
1 458
‐
200
400
600
800
1 000
1 200
1 400
1 600
Mikro Small Medium Others
HUF million
Insurance payments by sizes (2012‐2015)
2012 2013 2014 2015
Future plans developing risk management tools in MKR• Establishment of III. pillar – Income Stabilisation Tool
• Target groups: dairy, pig and poultry farmers – they could’nt be members of pillar I. and II.
• Reforming of „pillar IV.” – subsidised credits for damaged farmers• Connection of occurence of damages and crediting of farmers
• Establishment of „pillar 0.” – the hail protection system covering allthe country
• Installation of ground generators
http://ec.europa.eu/agriculture/agri‐markets‐task‐force/index_en.htm
AMTF – team of 12 members, 1 year mandate (2016)
H. Giesen A.L. Paumier D. Dobbin A. Babuchowski I. Samir Phil Hogan C. Veerman E.V. Cabrero A. Juhász T. Iwarson L.FrescoDE ‐ pork FR ‐ cereal IE – milk PL – ex‐MoA SK – Chamber DG‐Agri NL – ex‐MoA ES‐MoA HU‐AKI SE‐ StockExch NL‐WUR
Task: report with concrete legal and policy advice
Risk management is a priority conclusion of AMTF• Mandatory inclusion of measures in MS RDP • Monitoring and evaluation systems that map all relevant data linked to the
occurrence of risks. • Minimum thresholds applying to crop losses for insurance purposes could
be revised to make the tool more attractive to users. • EU co‐financing of reinsurance schemes should be assessed. • Resource shift towards an integrated risk management policy at EU level. • Possibility of using simplified loss calculation and reimbursement options. • Set up an EU platform allowing the exchange of best practices of MS• Including tax averaging.
Thank you for your attention!