A survey on critical factors influencing agricultural insurance

Abstract

Agricultural business is a very high-risk job and an increase demand for agricultural products from one side and steady increase in production cost and weather changes, on the other side, have motivated many to use insurance for agricultural products. Insurance plays an important role in influencing crop production and insured satisfaction or farmers. The purpose of this research is to find critical components in agricultural insurance. Based on an exploration of the literature review and interviews, the proposed study of this paper extracts 24 variables and using factor analysis, we select the most important factors, which are grouped in seven categories. The implementation of our factor analysis has revealed uncertainty, moderator, market equilibrium, risky environment, empowering factor, education, training, structural hazards and natural ecosystems as the most important factors influencing agricultural industry.

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*Corresponding author.
E-mail addresses: a-valipour@agri-bank.com (A. Valipour)
© 2013 Growing Science Ltd. All rights reserved.
doi: 10.5267/j.msl.2012.11.002
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Management Science Letters 3 (2013) ***–***
Contents lists available at GrowingScience
Management Science Letters
homepage: www.GrowingScience.com/msl
A survey on critical factors influencing agricultural insurance
Naser Azada, Gholamreza Heidari Kord Zangeneha, Seyed Mohsen SeyedAliAkbara and Ali Valipourb*
aDepartment of Management, Islamic Azad University, South Tehran Branch, Tehran, Iran
bMaster student, Department of Management, Islamic Azad University, South Tehran Branch, Tehran, Iran
C H R O N I C L E A B S T R A C T
Article history:
Received June 25, 2012
Received in revised format
28 October 2012
Accepted 30 October 2012
Available online
November 2 2012
Agricultural business is a very high-risk job and an increase demand for agricultural products
from one side and steady increase in production cost and weather changes, on the other side,
have motivated many to use insurance for agricultural products. Insurance plays an important
role in influencing crop production and insured satisfaction or farmers. The purpose of this
research is to find critical components in agricultural insurance. Based on an exploration of the
literature review and interviews, the proposed study of this paper extracts 24 variables and
using factor analysis, we select the most important factors, which are grouped in seven
categories. The implementation of our factor analysis has revealed uncertainty, moderator,
market equilibrium, risky environment, empowering factor, education, training, structural
hazards and natural ecosystems as the most important factors influencing agricultural industry.
© 2013 Growing Science Ltd. All rights reserved.
Keywords:
Agricultural products
Insurance
Factor analysis
1. Introduction
Agricultural business is a very high-risk job and an increase demand for agricultural products from
one side, steady increase in production cost and weather changes, on the other side, have motivated
many to use insurance for agricultural products (Mahul & Vermersch, 2000; Wong, 2002; Hau,
2006). During the past few years, there have been several studies associated with agricultural
products. Juyun (2010) discussed how to deal with non-systemic risk in agricultural industry using
agricultural insurance. He explained that China's agricultural insurance did not have financial subsidy
model, policies lack effective security as well as a comprehensive policies of agricultural insurances.
This makes it difficult to make some changes on the situation of insufficient effective demand and
supply (Hart et al., 2001; Machnes, 1995). Therefore, the government of China must make some clear
optimization path of support model, optimize the financial subsidy, build an efficient monitoring
mechanism among peasants. Juyun (2010) further discussed that it is necessary to have good planning
for reaching virtuous cycle among farmers, agriculture, agricultural insurance, agricultural credit,
promote the sustainable development of agricultural insurance.

Yang (2010) reviewed agricultural risk management strategies implemented by farm households and
some of the unique problems related to agricultural insurance. More specifically, he discussed the
experience of developed countries to make the case for why such methods could not work well in
lower-income countries. Yang (2010) introduced some innovations, which implement index-based
insurance products, and presented a pricing model for weather index derivatives deduced with utility-
based pricing. Zeng and Mu (2010) investigated China's policy-oriented agricultural insurance
development effectiveness by studying policy objectives as the evaluation criteria, and excavated out
the main existence and potential problems.
Yuanchang and Jiyu (2010) analyzed the optimal boundary of the fiscal subsidies based on the
welfare loss framework in agricultural insurance. They reduced the benefit loss due to asymmetric
information, optimized the efficiency of fiscal transfers, enhanced the farmers’ welfare, and gave
insights on how to promote our political subsidies in agricultural insurance. Dick and Wang (2010) in
a comprehensive survey considered international experiences in developing agricultural insurance,
the governments’ interventions and investigated the relationship between the rapid expansion of the
Chinese agricultural insurance market and these issues.
Qing-song (2010) analyzed characteristics of farmer behavior in agricultural insurance and the factors
influencing their behavior. He analyzed the risk preferences of individual farmer based on Von-
Norman-Morgenstern utility model and reported that under the present stage, different factors
influence agricultural insurance behavior. Sai et al. (2010) explored some important factors, which
influence a the farmers buying or not buying agricultural insurance and provided some suggestion on
how to develop the agricultural insurance in China for policy makers.
Cole and Gibson (2010) described crop revenue insurance, discussed the relative importance of
different factors in successful contract writing and presented a robust analytical procedure for
assessing combined crop yield and price risks. Cao and Zhang (2010) analyzed insurance companies
and mutual relationships between the government, analyzed how to revise its strategy to achieve a
balanced process and proposed some policy recommendations to optimize the level of three well-
beings. Wang et al. (2010) investigated the suitability of the Survival Analysis model for the crop
insurance program design. They focused mainly on the catastrophic risk premium rate estimates
under the condition of 70% yield coverage for rice, corn and sorghum in Panjin of Liaoning province,
China. Their results indicated that the estimated premium rates for each crop were consistent with the
currently prevailed crop insurance premium rate in Panjin.
Qingshui and Xuewei (2010) performed an empirical based on the questionnaire survey and statistical
data over the peiord 1998- 2009, and then reported four problems on agricultural insurance
development and five original causes. Yang et al. (2010) investigated the nonparametric density
function model and estimated the probability of yield loss rate at 3 proposed levels for grain crop,
wheat, corn, rice and cotton respectively from 13 provinces in the Major Grain-Producing Area. They
concluded that the current crop insurance coverage level under normal years could not generate an
efficient inducement for farmers to buy insurance contracts. They suggested that it was essential to
carry out positive and conditional forced insurance, provided a larger portion of premium subsidy to
the Major Grain-Producing Area by central government and improved the basic agricultural
production conditions to expand crop insurance participation.
Pasaribu (2010) discussed the agricultural development policy of Indonesian government to reach
self-sufficiency in rice. However, he discussed that rice production growth was critical to increase
availability, accessibility, and affordability following the effect of global climate change (Nelson &
Loehman, 1987). He formulated a model to obtain knowledge about insurance application and
reported that rice farm insurance scheme could successfully work with three-way coordination active
roles of the government, the farmers and the insurance company.

N. Azad et al. / Management Science Letters 3 (2013)
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2. The proposed study
The proposed study of this paper investigates the impact of important factors on agricultural industry.
The proposed study designs a questionnaire consists of 30 questions in Likert scale. We have used
Cronbach alpha to verify the reliability of the questionnaire and it yielded 0.855, which is well above
the minimum desirable level of 0.70. Since factor analysis is sensitive against Skewness of the data,
we have decided to remove four questions from the survey. Next, the implementation of factor
analysis has determined seven factors where each one includes three to four variables.
3. The results
In this section, we present details of our survey on factor analysis.
3.1. Uncertainty
The first variable of the factor analysis is associated with uncertainties surrounding agricultural
industry. This factor includes four variables including risk management, Control of damage by
insurance, Stabilizing farmers' incomes and introducing good mechanisms for comparing risk.
Cronbach alpha has been calculated as 63.3% and Table 1 shows details of our findings.
Table 1
Details of factor analysis for uncertainties surrounding agricultural industry Accumulated % of variance Eigen value Factor Weight Option
27.229 27.229 6.094
0.603 Risk Management 1.123 Control of damage by insurance 1.059 Stabilizing farmers' incomes 0.539 Introducing good mechanisms for comparing risk
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As we can observe from the results of Table 1, in terms of uncertainty, using insurance to control
damage is the most important factor followed by stabilizing farmers' incomes, risk management and
introducing good mechanisms for comparing risk.
3.2. Moderator
The second variable of the factor analysis is associated with moderators surrounding agricultural
industry. This factor includes three variables including risk diversity, risk transfer and Precautionary
savings. Cronbach alpha has been calculated as 54.2% and Table 2 demonstrates details of our
investigation.
Table 2
Details of factor analysis for moderator factors in agricultural industry Accumulated % of variance Eigen value Factor Weight Option
33.608 6.379 1.914
0.621 Risk diversity 0.633 Risk transfer 0.735 Precautionary savings
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The results of Table 2 show that precautionary savings is the most important factor followed by risk
transfer and risk diversity as moderator in our survey.
3.3 Market equilibrium
Market equilibrium is the third components of factor analysis and it includes three factors where
Cronbach alpha is reported as 50.2% and details are given in Table 3 as follows,

Table 3
Details of factor analysis for market equilibrium factors in agricultural industry Accumulated % of variance Eigen value Factor Weight Option
39.768 6.160 1.845
0.941 Loan repayment capacity 0.864 Help stabilize and balance the cost 0.835 Balancing supply
As we can observe from the results of Table 3, Loan repayment capacity, Help stabilize and balance
the cost and Balancing supply are three the most important factors of our investigation.
3.4. Risky Environment
Risky Environment is the fourth item in our survey with four factors including exposure to
environmental with high risk, Exposure to environmental with low risk, existence of supportive view
and imposing the law of the greater participation, less risk. In this section, Cronbach alpha is reported
as 71.0% and details are given in Table 4 as follows,
Table 4
Details of factor analysis for Risky Environment in agricultural industry Accumulated % of variance Eigen value Factor Weight Option
44.556 4.788 1.436
0.346 Exposure to environmental with high risk 0.314 Exposure to environmental with low risk 0.393 Existence of supportive view 0.378 The greater participation, less risk
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3.5. Empowering factor
Empowering factor is the fifth item in our investigation with four factors including exposure to
environmental with high risk, Exposure to environmental with low risk, existence of supportive view
and imposing the law of the greater participation, less risk. In this section, Cronbach alpha is reported
as 71.0% and details are given in Table 4 as follows,
Table 4
Details of factor analysis for Risky Environment in agricultural industry Accumulated % of variance Eigen value Factor Weight Option
48.793 4.237 1.271
1.016 Distribution of risk among other insurance firms 0.982 Change in credit status of insurance firms 0.765 Reduction in dependency of farmers to loan payers 0.924 Improving insurance firms' positions
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The results of our survey have indicated that distribution of risk among other insurance firms is the
most important factor followed by change in credit status of insurance firms and Improving insurance
firms' positions.
3.6 Education and training
Education and training is the sixth components of factor analysis and it includes three factors where
Cronbach alpha is reported as 58.0% and details are given in Table 6 as follows,
Table 6
Details of factor analysis for education and training factors in agricultural industry Accumulated % of variance Eigen value Factor Weight Option
52.794 4.001 1.2
0.726 Mitigate risk 1.271 Forced changes in cropping patterns 1.2 Encouraged to adopt procedures to deal with risk

N. Azad et al. / Management Science Letters 3 (2013)
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As we can observe from the results of Table 6, forced changes in cropping patterns is the most
important factor followed by encouraged to adopt procedures to deal with risk and Mitigate risk.
3.7 Structural hazards and natural ecosystems
Structural hazards and natural ecosystems is the last item for the implementation of the factor
analysis, which includes three factors and Cronbach alpha is reported as 58.6% and details are given
in Table 7 as follows,
Table 7
Details of factor analysis for Structural hazards and natural ecosystems factors in agricultural industry
Accumulated % of variance Eigen value Factor Weight Option
56.538 3.744 1.123
0.494 Price fluctuations 0.423 Global warming and weather changes 0.517 Consolidated agricultural supply
Among the factors reported in Table 6, consolidated agricultural supply is the most important factor
followed by price fluctuations and global warming.
4. Conclusion
In this paper, we have presented an empirical survey to detect important factors influencing
agricultural production. The implementation of our factor analysis has revealed seven factors
including uncertainty, moderator, market equilibrium, risky environment, empowering factor,
education and training and structural hazards and natural ecosystems. In terms of uncertainty, using
insurance to control damage is the most important factor followed by stabilizing farmers' incomes,
risk management and introducing good mechanisms for comparing risk. Precautionary savings is the
most important factor followed by risk transfer and risk diversity as moderator in our survey. Loan
repayment capacity, help stabilize and balance the cost and balancing supply are three the most
important factors of our investigation. Finally, in terms of risky environment in agricultural industry,
distribution of risk among other insurance firms is the most important factor followed by change in
credit status of insurance firms and improving insurance firms' positions.
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