Insurance and Financing in Long-term Agricultural Decision Making in Transition

Economies- The Case Of Croatia

Njavro, Maa, Van Asseldonk, Mb. and Meuwissen, M.b

a Faculty of Agriculture University of Zagrebb Institute of Risk Management in Agriculture, Wageningen University

FUR XII 2006 at LUISS in Roma  12th International Conference on the Foundations and Applications of

Utility, Risk and Decision Theory

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Content1. Introduction 7. Hail insurance 2. Rural Finance in Croatia

Agricultural Lending Crop Insurance

8. On-farm strategy- Hail Nets

3. Objectives 9. Leverage 4. Methodology

Stochastic simulation SERF

Growth model

10. Conclusions and Recommendations

5. Risk Management Model

11. References

6. Stochastic Inputs 12. Contact details

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Introduction [1]•Market failures of agricultural risk sharing instruments, such as crop insurance and agricultural finance, in transition economies of Central and Eastern Europe hamper efficient risk management.

•Apart from hail insurance, other forms of agricultural insurance products and hedging instruments are only limited available.

•In combination with a constraint external fund inflow investments are often postponed thereby deteriorating farms’ competitiveness.

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Introduction [2]

•In order to improve farms’ competitiveness in the process of EU accession, policy makers’ have initiated incentive programs for investments in agriculture (so called “Operational Plans”).

•Plans aim to stimulate investments in order to create a viable production sector.

•Impacts are questionable in the current state of risk management markets!

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Rural Finance in Croatia

Financial sector•The financial sector in Croatia constantly grows and develops in quality and quantity terms.•Highly competitive and innovative market that has already reached EU standards. Commercial banks (mainly in foreign ownership) are the major players in the financial sector. •Their credit policies are mainly oriented to households and the share of household loans in total bank financing is 49.6%. Networks of the banks’ branches bring financial products to almost every corner of Croatia.

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Rural Finance in Croatia- Agricultural Lending [1]- Supply side1. Agricultural policy reform- Model of capital

investment• Step ahead from classical subsidized and directed

credit program. • It is aimed at encouraging the development of

business relations between commercial banks and farmers.

• The model can be described as the assigning of irretrievable capital (25% out of total loan) from the budget of the Republic of Croatia.

2. EU Pre- accession program- SAPARD

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Rural Finance in Croatia- Agricultural Lending [2]- Supply side“Operational Plans”To date, two programs have been launched, one for establishing perennial crops and another for cattle production.

OPERATIONAL PLAN PERENNIAL CROPS CATTLE Purposes Investments in establishing

new plantations, buying agricultural land, machinery and equipment,

Investments in buildings, livestock, equipment and agricultural land

Repayment period Olive groves: 15 years including grace period (5 years) Investments in existing orchards:10 years including grace period (2 year) Other investments: 12 years including grace period (3 years)

12 years (including grace period)

Grace period 2 years Interest rates 4% 4% Max amount of a loan 1,5 million kunas (natural

persons*) 3,5 million kunas (legal persons**)

3,5 million kunas

Entitled to borrow Family farms, trade companies, craftsmen, cooperatives

Family farms, trade companies, craftsmen

Croatian National Bank- Exchange rate on 21.06.2006. Euro: Kunas = 1: 7,254437

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Rural Finance in Croatia- Agricultural Lending [3]- Demand side

The main constraints are:

• The lack of collateral and non-

functioning land market,

• Unfavorable farms’ structure,

• Lack of business history,

• Lack of clear presentations of

business ideas through business plans.

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Rural Finance in Croatia - Crop Insurance•Agricultural insurance (crop insurance against unfavorable weather condition and livestock insurance) is undeveloped in Croatia.•Apart from hail insurance, other forms of agricultural insurance products and hedging instruments are of limited supply. •Statistics show a low uptake of crop insurance and a small land area covered by insurance. •Limited supply of agricultural insurance, but premium subsidies (introduced in 2003) positively influence supply.

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Objectives

Microeconomic analysis of risk sharing tools (insurance and financial leverage) and their effects in apple production

Potential actions in risk transfer markets in the light of EU accession will be suggested.

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Methodology [1]- Stochastic simulation

The purpose of stochastic simulation in risk analysis is to determine probability distributions of consequences for alternative decisions to enable good and well-informed choice (Hardaker et al., 2004, p.158).

“Particularly useful for problems that involve risks, are dynamic and have discrete decision variables”…

“Given our need to study finance, legal and human resources risks, simulation needs to be re-evaluated.”

(Musser and Patrick, 2002)

@RISK 4.5 for Excel www.palisade.com

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Methodology [2a]- Stochastic dominance Stochastic Dominance – considers the full range of the simulated distributions.

Quantitatively superior because every point is used and compared one-to-one with every point of another distribution.

www.simetar.com

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Methodology [2b]- Stochastic efficiency with respect to the functionCompares alternatives in terms of certainty

equivalents (CEs).

Form of utility function: negative exponential

Risk aversion coefficients : Richardson’s rule is based on Meyer’s constant relative risk aversion

Risk aversion coefficient Overall mean of random variable 1.0 if overall mean of random values is 0 to

10 0,1 if overall mean of random values is 10 to

100 0,01 if overall mean of random values is 100

to 1,000.00 0,001 if overall mean of random values is

1,000.00 to 10,000.00 0,0001 if overall mean of random values is

10,000.00 to 100,000.00 0,00001 if overall mean of random values is >

100,000.00

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Methodology [2c]- Risk premium

• Risk Premium (RP) - calculate the risk premium between each of the scenarios and a Base scenario.

• Risk Premiums equal the difference between the CE’s for the risky scenarios.

RPG to F = CEG – CEF

• Base scenario should be the current situation or the scenario picked best by CE or stochastic dominance

Richardson, J.W. (2005)

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Growth modelGrowth model (g) expresses the rate of growth of equity capital as a function of the rate-of return on assets, the interest rate on debt, the rates of taxation and consumption

g = ( r Pa – i Pd) (1- t)(1- c)

r = the average (stochastic) net rate of return on total assets over the investment’s expected life i = interest rates (4,5%)

t= the average rate of income taxation (20%) c = the average rate of withdrawals for family consumption, dividends

and other non-business flows (0%) Pa= the average ratio of assets to equity

Pb= the average ratio of debt to equity, the leverage ratio

σg= σr Pak

k = (1-c) (1-t)

(Barry et. al, 2000)

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Risk Management Model in Apple production

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Risk Management Model

Investment in apple orchard (5 ha)

•- “Naive”•- Hail insurance•- Hail nets•- Hail nets + hail insurance

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Stochastic Inputs [1]Climate risks

0

0,2

0,4

0,6

0,8

1

0 1 2 3 4

probability of occurance

frost hail

Source: Croatian Hydro meteorological Institute www.meteo.hr

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Stochastic Inputs [2]• Yields- CDF

0

0,1

0,2

0,3

0,4

0,5

0,6

0,7

0,8

0,9

1

0 10000 20000 30000 40000 50000 60000

kg/ha

Pro

b

Yield 1st class

Source: RM Model (@Risk simulation, 5000 iteration)triangular distribution based on expert advice and case study data

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Stochastic Inputs [3]

0,00

0,10

0,20

0,30

0,40

0,50

0,60

0,70

0,80

0,90

1,00

hail frost hail and frost without climate risks

Average

5th Percentile

25th Percentile

75th Percentile

95th Percentile

Share of the first class apples (%) under different risks

Source: RM Model (@Risk simulation, 5000 iteration)triangular distribution based on expert advice and case study data

Simetar© graphical tools

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Stochastic Inputs [4]

Prices

Average Distribution @Risk funkcija Price I class-fall 4,40 Normal =RiskNormal(4.40, 0.50)

Price I class-spring 5,54 Normal =RiskNormal(5.54, 0.49) Price- second class 1 Normal =RiskNormal(1, 0.25)

Source: based on Market information system in Agriculture dana (weekly data)www.mps.hr/tisup

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Hail insuranceInsured sum: between 50,000.00 and 100,000.00 kunas per

hectare (@RiskSimtable function)

Damages- normal(50%, 20%)Deductibles Premium rate* (quantity + quality

insurance 0 0,19 5 0,15 10 0,11 15 0,09

* 5th premium class (on scale from 1 to 15)Source: Croatia osiguranje d.d., Insurance Company

No of combination= 24

Premium subsidy: 25% (state level)

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Hail Nets

No of combination= 5

AREA UNDER NET (HA) 1 2 3 4 5 Investment (kunas)

954,077.25 1,034,077.25 1,114,077.25 1,194,077.25 1,274,077.25

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Selected Risk Management Strategies

Descriptive statistics• Net present Value

Name Mean*** Std Dev CVHailInsurance I * 246.543,94 480.184,55 194,77HailInsurance II ** 237.053,27 478.697,33 201,94

HailNets 4 ha 480.565,84 473.588,57 98,55HailNets 5ha 519.974,58 472.179,26 90,81

Naive 250.751,41 527.479,85 210,36Insurance (1 ha)+nets(4ha) 449.988,35 470.717,64 104,61

* Insured sum: 50.000,00 kunas, deductibles 15%** Insured sum: 50.000,00 kunas, deductibles 15%*** Discount rate= 4%

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Selected Risk Management Strategies• SERF analysis and Risk Premium

Neg. Exponential Utility Weighted Risk Premiums Relative to Naive

-100.000,00

-

100.000,00

200.000,00

300.000,00

400.000,00

500.000,00

600.000,00

0 2E-06 4E-06 6E-06 8E-06 1E-05 1E-05 1E-05 2E-05

ra

HailInsurance I HailInsurance II HailNets4

HailNets5 Naive Insurance (1 ha)+nets(4ha)

Stochastic Efficiency with Respect to A Function (SERF) Under a Neg. Exponential Utility Function

-1.400.000,00

-1.200.000,00

-1.000.000,00

-800.000,00

-600.000,00

-400.000,00

-200.000,00

0,00

200.000,00

400.000,00

600.000,00

800.000,00

0 2E-06 4E-06 6E-06 8E-06 1E-05 1E-05 1E-05 2E-05

ra

HailInsurance I HailInsurance II HailNets4

HailNets5 Naive Insurance (1 ha)+nets(4ha)

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Financial Leverage

Scenario Sources of funds I External funds to 90% of

total investment II 30% of own capital III Own capital

Risk Management strategies taken in consideration: 1. hail insurance I, 2. hail net 4 ha, and 3. Insurance (1ha) + hail net (4 ha)

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Growth model

Source: Simulation model (5000 iteration)

Naive Hail insuranceHail insurance

(1ha)+ nets (4ha) Hailnets4Scenario I growth rate -4,74% 0,48% 4,21% 2,98%

st.dev. 0,30% 1,47% 0,18% 0,15%Scenario II growth rate -5,19% 0,01% 4,01% 2,52%

st.dev. 0,39% 0,21% 0,13% 0,09%Scenario III growth rate -0,08% 0,00% 2,14% 1,01%

st.dev. 0,11% 0,32% 0,05% 0,03%

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Growth Model- “Naive”

Source: Simulation model (5000 iteration), Simetar© graphical tools

PDF

-50,00% -40,00% -30,00% -20,00% -10,00% 0,00% 10,00% 20,00%

growth

Scenario I Scenario II Scenario III

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Growth Model- hail insurance

Source: Simulation model (5000 iteration), Simetar© graphical tools

PDF

-0,002000% -0,001500% -0,001000% -0,000500% 0,000000% 0,000500% 0,001000%

Scenario III

PDF

-0,02000% -0,01000% 0,00000% 0,01000% 0,02000% 0,03000%

Scenario II

PDF

-4,00% -3,00% -2,00% -1,00% 0,00% 1,00% 2,00% 3,00% 4,00% 5,00%

Scenario I

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Growth Model- hail insurance (1 ha) and hail nets (4 ha)

Source: Simulation model (5000 iteration), Simetar© graphical tools

PDF

-10,00% -5,00% 0,00% 5,00% 10,00% 15,00% 20,00%

growth

Scenario I Scenario II Scenario III

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Growth Model- hail nets (4 ha)

Source: Simulation model (5000 iteration), Simetar© graphical tools

PDF

-10,00% -5,00% 0,00% 5,00% 10,00% 15,00%

growth

Scenario I Scenario II Scenario III

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Conclusions•“Naïve” strategy, the most common, represents all its weakness.

•Insurance protects from shortfalls, stabilize financial indicators and liquidity. Premium subsidy made a great influence on the results. Higher subsides (>25%) enables greater coverage in terms of insured sum and lower on no deductibles.

•Hail nets positively influences yields, ratio of extra quality fruits and possibility for storing which has been only indirectly considered.

•In combination with insurance, hail net is dominant strategy.

•The main problem with insurance is number of perils covered. Perils, like frost usually remain uncovered. Active protection against frost is possible however with additional investment and possible higher exposure to financial risk.

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Conclusions• Sources of external financing and interest rates seem not

to be a problem at the moment. Nevertheless, access to agricultural credits is still constrained.

• Hail insurance stabilizes income enabling positive risk/return for borrowers and for lenders.

• In order to accelerate growth, higher leverage is necessary. Results showed that efficient risk management strategies (hail insurance and hail nets) enables higher financial leverage without significant influence on farm risk position.

• Outreach of agricultural credits is influenced by the collateral that borrowers can offer. A deficiency in or an absence of collateral influences use of own financial sources slowing down business development, specialization, modernization and rural development in all.

• Policy makers need to have it in mind in creation in conduction EU pre-accession programs!

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References1. Barry P.J., Ellinger P.N., Hopkin J.A., Baker C.B.(2000): Financial

Management in Agriculture, Interstate Publishers, Inc., Danville, Illinois, USA

2. Hardaker, J.B., Huirne, R.B., Anderson, J.R., Lien, G. (2004): Coping with risk in agriculture. CABI Publishing, London, UK.

3. Just, R.E. i Pope, R.D. (edit.) (2002): A Comprehensive Assessment of the Role of Risk in U.S. Agriculture, Kluwer Academic Publishers, USA

4. Palisade Corporation (2004): Guide to Using @RISK, Risk Analysis and Simulation Add-In for Microsoft® Excel, Version 4.5, USA

5. Rejda, G.E. (2005): Principles of Risk Management and Insurance, Addison Wesley, London, UK

6. Republic of Croatia, Ministry of Agriculture, Forestry and Water Management of the Republic of Croatia (2004). Operativni plan podizanja trajnih nasada., Zagreb, Croatia. http://www.mps.hr/pdf/publikacije/op_prog_trajni_nasadi.pdf

7. Richardson, J.W., Schumann, K., Feldman, P. (2004): Simetar©, simulation & econometrics to analyze-Users manual. Simetar Inc. USA, p 46.

8. van Asseldonk, M.A.P.M., Meuwissen, M.P.M., Huirne, R.B.M.(2001.): Stochastic Simulation of Catastrophic Hail and Windstorm Indemnities in the Dutch Greenhouse Sector, Risk Analysis, Vol 21. no.4, p. 761-769

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Correspondence address

Mario Njavro, PhD

Faculty of Agriculture University of Zageb

Svetosimunska c. 25

10000 Zagreb, Croatia

tel: +385 1 23 93 762

fax: +385 1 23 93 745

mnjavro@agr.hr

http://agririsk.agr.hr or http://www.agr.hr/cro/curriculum/njavro_mario.htm