Toward Sustainable Agricultureof Rice in Asia:
Economic Challenges andPolicy Implications
Editor :Thanh Tam HO

Asia-Japan Research Institute
Ritsumeikan University

Toward Sustainable Agriculture of Rice in Asia

AJI BOOKS

Toward Sustainable Agriculture of Rice in Asia:
Economic Challenges and Policy Implications
EditorThanh Tam HO

Asia-Japan Research Institute
Ritsumeikan University
ISBN 978-4-910550-47-3 (Online)
ISBN 978-4-910550-46-6 (Print)iToward Sustainable Agriculture of Rice in Asia

Toward Sustainable Agriculture of Rice in Asia:
Economic Challenges and Policy Implications

AJI Editorial Office
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Copyright © 2023 Asia-Japan Research Institute, Ritsumeikan University
Note:
Authors’ names in this publication are ordered according to their preference andtheir surnames are capitalized.

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Toward Sustainable Agriculture of Rice in Asia

Contents
Preface and Acknowledgments
Thanh Tam HO

iv

Contributors

viii

Chapter 1. Comparison of Rice Production in China and Japan:
Evidence from a Panel Data Analysis
Qi DONG

1

Chapter 2. Impact of High-Quality Rice Variety on Profit andProfit Efficiency: Evidence from Vietnam
Phuc Trong HO

25

Chapter 3. Drought Effect and Adaptation of Farmers in Northeast
Thailand
Orawan SRISOMPUN

40

Chapter 4. Rice Production for Sustainable Agriculture: Case
Studies in Vietnam and Japan
Thanh Tam HO

57

Chapter 5. The Effect of Risk Preference and Farmer Perception
on Climate Change to Farmer Participation on Farm Insurances
Mohammad RONDHI, Suci Virgianti DIANI, Rizky YANUARTI
73
Chapter 6. From Science to Policy: Sustainable Rice Production in
the Mekong Delta, Vietnam
Melanie CONNOR

86

Concluding Remarks and Discussion
Thanh Tam HO

108

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Toward Sustainable Agriculture of Rice in Asia

PrefaceThis book, entitled “Toward Sustainable Agriculture of Rice in
Asia: Economic Challenges and Policy Implications,” is a record of the
Asia-Japan Research Institute International Workshop held on July 14,
2022, which took place online amid pandemics. This workshop brought
a number of young researchers together in an international scientificexchange with a focus on Asian rice production, innovations, andclimate change adaptation toward sustainable agriculture.
Rice is the staple food for more than half of humanity — with
90% of the world’s crop grown and consumed in Asia. It sustains lives
and livelihoods. How the current level of annual production could be
increased to meet the demand for rice — which is expected to growfaster than the production in most countries — in an environmentallyand economically sustainable way is a challenging question.
The increasing scarcity of natural resources, environmental
degradation, and ecosystem loss have already begun to limit the
expansion of food production. More specifically, climate change
affects agriculture and food systems adversely due to irregular weather
patterns, droughts, floods, and natural disasters. Climate change andits impacts are becoming more severe, devastating rice farms and rural
livelihoods, especially in Asia. Hence, it poses significant challenges toglobal food security and safety. On the other hand, recently, agriculture
has been found to be an increasing contributor to greenhouse gas (GHG)
emissions which may exacerbate global warming. Ten percent of global
methane emissions come from rice production. Hence, strategic policies
to mitigate food safety risks while minimizing environmental impacts inthe era of climate change have become more important.
The good news is that sustainable agriculture can be a solutioniv

Toward Sustainable Agriculture of Rice in Asia

for climate change adaptation and mitigation, ensuring food security,and improving rural livelihoods and climate resilience. It is crucial for
Asian countries, as the major rice producers, to develop sustainableagriculture. Sustainability is now widely accepted as a guiding concept
and goal for our low-carbon economies, agriculture, and the foodsystem. Some approaches are in practice already but conditions are stillchallenging.
This book gives an insight into the current economic and policy
challenges for rice in the era of climate change and towards sustainableagriculture with case studies in China, Japan, India, Thailand, Indonesia,
and Vietnam. In the first chapter, Dr. Qi Dong compares the differencesin rice production and cost efficiency between China and Japan. In
Chapter 2, Dr. Phuc Trong Ho introduces the benefits of high-quality
rice varieties in the Mekong Delta of Vietnam, and in Chapter 3, Dr.
Orawan Srisompun describes how drought affects Thai rice farmers
and their adaptations. In Chapter 4, Dr. Thanh Tam Ho introduces riceproduction towards sustainable agriculture, an economic and policy
challenge in Vietnam and Japan. Dr. Mohammad Rondhi, Suci Virgianti
Diani, and Rizky Yanuarti introduce the effects of risk preferences andperceptions on Indonesian farmer participation in farm insurance in
Chapter 5, and Dr. Melanie Connor shows the roadmap from science
to policy for sustainable rice production in Southeast Asian countries,
with a focus on Vietnam, in Chapter 6. The Concluding Chapter isa summary of the discussion on economic and policy challenges indeveloping Asia rice production. It is my hope that these chapters will
provide meaningful suggestions for promoting sustainable agriculture
and economic development in Asia.
Thanh Tam HOv

Toward Sustainable Agriculture of Rice in Asia

Acknowledgments
This work would not have been possible without the full supportof the Asia Japan Research Institute of Ritsumeikan University andcolleagues of the Institute who helped me prepare and organize theinternational workshop. My overwhelming debt is to Professor Yasushi
Kosugi, Director of the Asia-Japan Research Institute, who has been
supportive of my career goals and given precious encouragement andendless support during the planning and organizing of this workshop.
Also, I would like to express my deepest appreciation for theassistance and guidance of the special advisor, Professor Anthony
Brewer. His dedicated support in shaping the outline, communicatingwith participants, and making this booklet the best possible was greatly
appreciated.
Furthermore, I am very grateful to Professor Koji Shimada for his
devotion and enormous support not only throughout the period of theworkshop, but also throughout my years in academia.
My grateful thanks are also extended to my colleagues at theInstitute for their kind support in running this workshop.
Furthermore, my special thanks should be given to the six guest
presenters: Dr. Qi Dong from the Economic Research Institute forNortheast Asia – Japan, Dr. Phuc Trong Ho from the University of
Economics, Hue University – Vietnam, Dr. Orawan Srisompun from
Mahasarakham University – Thailand, Dr. Mohammad Rondhi fromthe University of Jember – Indonesia, and Dr. Melanie Connor fromthe International Rice Research Institute – Philippines and Institute forDevelopment Studies – United Kingdom, for their participation in ourworkshop at the most inconvenient times due to the considerable timedifferences as well as their much appreciated efforts to contribute theirvi

Toward Sustainable Agriculture of Rice in Asia

chapters to this book.
Finally, I am grateful to my partner and family, who patiently
assisted and encouraged me to keep focused and patient inaccomplishing my task.
Thanh Tam HO

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Toward Sustainable Agriculture of Rice in Asia

Contributors
Dr. Qi DONG
Chapter 1. Comparison of Rice Productionin China and Japan: Evidence from a
Panel Data Analysis
Dr. Qi Dong is an Associate Professor
at the Economic and Social ResearchInstitute for Northeast Asia of the
University of Niigata Prefecture, Japan.
She received her Ph.D. in Agricultural
Economics from the University of Tokyo,
Japan. Her research focuses on labor migration, agricultural capital
investment, and food security. Her current research explores agricultural
corporations and agricultural product exports in Japan.

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Toward Sustainable Agriculture of Rice in Asia

Dr. Phuc Trong HO
Chapter 2. Impact of High-Quality Rice
Variety on Profit and Profit Efficiency:
Evidence from Vietnam
Dr. Phuc Trong Ho is a Lecturer at theFaculty of Economics and Development
Studies, University of Economics, Hue
University, Vietnam. He received his
Ph.D. in Agricultural Economics from the
School of Agriculture and Environment,
University of Western Australia, Australia. His dissertation “Profit
Efficiency and Rice Variety Choice in Rice Farming in Vietnam: A
Stochastic Frontier Analysis Approach,” explored the determinant ofthese inefficiencies and identified potential solutions to enhance farmers’
incomes. His research interests include efficiency and productivity
analysis, impact evaluation of technology adoption, production
economics, and consumer behavior analysis.

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Toward Sustainable Agriculture of Rice in Asia

Dr. Orawan SRISOMPUN
Chapter 3. Drought Effect and Adaptationof Farmers in Northeast Thailand
Dr. Orawan Srisompun is an AssistantProfessor at the Department of Agricultural
Technology, Faculty of Technology,
Mahasarakham University, Thailand.
She received her Ph.D. in Agricultural
Economics at Kasetsart University,
Thailand. Her research focuses on
agricultural production economics and agricultural policy. In 2021, she
was a leader of two projects, “Study on Economics and Social Effects
of Drought and COVID-19 Pandemic on Farmers in the Northeast
Thailand” (funded by the National Research Council of Thailand) and“iCCBA Pilot Project Consultant — Maha Sarakham” under the NDC
Support Project — Delivering Sustainability through Climate FinanceActions in Thailand (funded by UNDP).

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Toward Sustainable Agriculture of Rice in Asia

Dr. Thanh Tam HO
Chapter 4. Rice Production for Sustainable
Agriculture: Case Studies in Vietnam andJapan
Dr. Thanh Tam Ho is a Senior Researcher
at the Ritsumeikan Asia-Japan Research
Organization. She received her Ph.D. in
Economics at Ritsumeikan University.
Her research focuses on climate change
adaptation and mitigation, sustainableagriculture policies, and behavior analysis. Her dissertation, “An Economic
Analysis of Climate Change Response and Rice Farmers’ Behavior in
the Mekong Delta of Vietnam,” explored farmer’s decision-making on
multiple climate change responses and the economic performance inrice farming. Currently, she is conducting a research project related tosustainable agriculture and promotion policy in Japan.

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Toward Sustainable Agriculture of Rice in Asia

Dr. Mohammad RONDHI
Chapter 5. The Effect of Risk Preference
and Farmer Perception on Climate
Change to Farmer Participation on Farm
Insurances
Dr. Mohammad Rondhi is an Associate
Professor at the Department of Agribusiness,
Faculty of Agriculture, University ofJember, Indonesia. He obtained his Ph.D. at the Graduate Schoolof Agriculture, Hokkaido University, Japan. His research interest
is in agricultural economics including agricultural land economics,
agricultural irrigation management, and agricultural institutions. He isa specialist in Computer-aided data analysis and has published several
articles related to agricultural land conversion, climate change, and risk
aversion level.

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Toward Sustainable Agriculture of Rice in Asia

Dr. Melanie CONNOR
Chapter 6. From Science to Policy:
Sustainable Rice Production in the
Mekong Delta, Vietnam
Dr. Melanie Connor is a Senior Social
Scientist researching behavior change
in agriculture. Her research interests
lie in investigating farmer adoption
behavior and constraints, decision-making, and how these interlink with
agricultural policymaking. She currently works at the International Rice
Research Institute and is based in Nairobi, Kenya. She has publishednumerous articles on the impacts of climate change on food security andsustainable rice agriculture.

xiii

Toward Sustainable Agriculture of Rice in Asia

xiv

Chapter 1
Comparison of Rice Production in China and Japan

Chapter 1
Comparison of Rice Production in China andJapan: Evidence from A Panel Data Analysis
Qi DONG
Abstract: Rice is one of the most important staple foods in the world,
especially in Asia. According to the data for 2020 from the Food andAgriculture Organization (FAO), Asia accounts for 89% of worldwide riceproduction and 88% of global rice consumption. Of Asian countries, China
and Japan play significant roles in the production and consumption of rice.
China produces and consumes approximately one-third of Asia’s rice interms of quantity. Although Japan’s percentage is not as large as China’s,
their rice productivity and quality are notable. This study uses a provincial(regional) panel data set on China’s and Japan’s rice production (Japonicarice) to examine cost composition and variation in rice production in
the two countries. The results indicate that the cost-revenue ratio of riceproduction in Japan ranges from 0.96 to 1.42, while in China, it ranges
from 0.64 to 0.92, suggesting Japan’s rice production is economicallyunprofitable, and China’s rice production is about to face the same issue.
Building on this, the study applies DEA (data envelopment analysis) tothe data set to further analyze the differences in rice production efficiency
between the two countries. The results reveal that the estimated efficiency
score of rice production is greater in China (0.92) than that in Japan (0.66).

1. Introduction
Rice is one of the most important staple foods in the world, particularly
in Asia. According to the data published by FAO (2020), Asia accounts for1

Toward Sustainable Agriculture of Rice in Asia

89% of worldwide rice production and 88% of global rice consumption.
While rice is mainly produced and consumed in Asia, its percentage has
been declining in recent years. Of Asian countries, China and Japan are
significant contributors to the production and consumption of Asia rice.
China alone produces and consumes approximately one-third of Asia’s rice.
It is also the largest rice producer globally, accounting for about 30% of
the world’s total production, and is the largest rice consumer, representing
about 30% of global demand in 2021. Although Japan’s percentage is not aslarge as China’s, its rice productivity and quality are impressive.
Figure 1.1 shows rice and other main staple crop production in
China. We can see that rice was once the first staple crop in China, nomatter whether in terms of sowing area or yield. In terms of sown areaof rice, the total percentage increased from about 22% in 1960 to almost
30% in 1980 and then gradually declined in recent years. Since 2000,
the sown area of maize in China has grown rapidly. This is probably
because of an increase in the domestic need for forage. Similarly, it
can be clearly seen that the yield of maize has had a rising trend inrecent years while the rice yield has tended to flatten out. However, riceproduction occupies less land but yields a greater output, indicating the
average productivity of rice is much higher than other staple crops.

Figure 1.1 Rice production in China.
Source: The data are from the annual database of China’s National Bureau of Statistics.

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Chapter 1
Comparison of Rice Production in China and Japan

In fact, China’s rice productivity has more than tripled in the past
several decades as shown in Figure 1.2. Possible reasons are (1) theprevalence of household responsibility system and domestic market
liberation (Lin 1992), (2) support of Government policy (Huang et al.
2006; Huang et al. 2013), (3) the development of high-yielding varieties(Peng et al. 2009), (4) improved crop management practices (Peng etal. 2009), and (5) increased demand for rice. However, China’s riceproduction is currently facing several problems involving off-farm
employment (Peng et al. 2009; Dong et al. 2018), such as labor transfer,a decline in arable land (Zhai and Ikeda 2000), a looming water crisis(Cai 2000; Li 2006; Li and Li 2011), and global climate change (Taoet al. 2003; Lyu et al. 2020). Consequently, Chinese rice is graduallylosing its comparative advantages.

Figure 1.2 Rice productivity in China and Japan.
Source: The data are from the database of the Ministry of Agriculture, Forestry, andFisheries of Japan.

3

Toward Sustainable Agriculture of Rice in Asia

Figure 1.3 shows the trends in the export and import of rice in
China. Before 2010, China exported much more rice than it imported.
Since the early 2010s, due to a slowdown in the growth of riceproduction and a rapid increase in rice consumption, China has changed
from a net exporter of rice to a net importer. In recent decades, China
has sustained a high level of rice self-sufficiency (above 97%) due to the
low level of rice import in the past decades.

Figure 1.3 Export and import of rice in China.
Source: The data are from the annual database of China’s National Bureau of Statistics.

Figure 1.4 shows rice production in Japan. We can see that both thesown area and the rice yield have declined since 1960. The percentage
of rice in the total sown area declined from almost 50% in the late 1970s
to about 37% recently. Meanwhile, the percentage of rice yield declined
from 70% in total in the late 1970s and remains stable at 55%.

4

Chapter 1
Comparison of Rice Production in China and Japan

Figure 1.4 Rice production in Japan.
Source: The data are from the database of the Ministry of Agriculture, Forestry and
Fisheries of Japan.

However, rice is still the most important staple food in Japan.
About 20% of agricultural production is rice, and 70% of agricultural
management entities grow rice. Japan’s self-sufficiency rate for food
is about 38% (calorie-based), but its rice is basically completely selfsufficient (98%, calorie-based). Japan implemented the Acreage
Reduction Policy (Gentan Policy) since 1970, but it was abolished in
2018. Basically, it is a policy to control the amount of rice to prevent
overproduction in Japan. In detail, it requires rice farmers to reduce
their planted areas to avoid rice surplus and price concerns. Gradually,
this may cause rice farmers to lose their enthusiasm for raising their riceproductivity (See Figure 1.2). On the other hand, there are also several
problems with Japan’s rice production, including decreasing domestic
demand and decreasing rice prices which can lead to an opportunity
for exporting Japanese rice. In 2020, Japan exported $64.7 million inrice, making it the 29th largest rice exporter in the world. At the sametime, Japan imported $463 million in rice, becoming the 15th largest
importer of rice in the world in 2020 (OECD 2022) (See Figure 1.5).
Moreover, aging agricultural labor forces, the Fukushima nuclear
5

Toward Sustainable Agriculture of Rice in Asia

disaster (Shimokawa et al. 2018), global climate change (Horie et al.
1996; Nakagawa et al. 2003), and a shortage of forage rice are emerging
issues in producing rice in Japan.

Figure 1.5 Rice import and export in Japan.
Source: The data are from the database of the Ministry of Agriculture, Forestry and
Fisheries of Japan.

There is no shortage of relevant studies on the conditions andproblems of rice production in China and Japan. As for China’s riceproduction, some studies have researched conventional and hybrid
rice (Xu and Jeffrey 1998; Ma and Yuan 2003), fertilizers used in riceproduction (Sun et al. 2019), and farm size and production cost of rice
(Zhang et al. 2019). Regarding Japanese rice production, the existing
literature has been mainly concerned with the effects of the Gentan
policy and the production cost of rice (Kusakari 1989), farm size andthe production cost of rice (Matsukura et al. 2015), and production cost6

Chapter 1
Comparison of Rice Production in China and Japanand forage rice (Senda and Tsunekawa 2015; Tsunekawa 2016). But
there are two questions that remain unanswered, namely: (1) How does
the production cost of rice change in China and Japan, respectively? and(2) Which country is more efficient in rice production, China or Japan?
The significance of this research can be addressed as follows: first,
from the perspective of China, it is important to study and learn aboutsome successful experiences in agricultural production from developed
countries such as Japan and consider the similarity of the natural
endowments of the two countries. Second, Japan has abolished the Gentan
policy, and the alternative option of its rice strategy is to promote theexport of its agricultural products. One of the important target markets
is China. Hence, it is important to compare the production cost andefficiency between China and Japan. Finally, the common issue for global
agriculture is how to tackle global climate change and develop sustainableagriculture. It may require producing enough output for the market, raising
revenue as high as possible for farmers, and stabilizing the market price ofagricultural output. Therefore, this study aims to (1) examine the changes
in the production costs of rice in China and Japan and (2) estimate andcompare the production efficiency of rice between the two countries.

2. Comparisons of Rice Production Costs
This section provides a comparison of rice production costs between
China and Japan, which typically consist of raw materials costs, laborcosts, and land costs. It is important to note that labor costs include wages
paid for family labor, and land costs include the rent paid for owned land.
This study focuses on examining these inputs and chooses the category of
Japonica rice as the research object. The data for China’s rice production
costs are sourced from the National Cost and Profit of Agricultural
Products Materials Compilation and the National Bureau of Statistics,
7

Toward Sustainable Agriculture of Rice in Asia

while the data for Japan’s rice production costs are obtained from thedatabase of the Ministry of Agriculture, Forestry and Fisheries of Japan.
Figure 1.6 shows the total cost of rice production per 10 acres in
Chinese Yuan/ Japanese Yen. In China, the total cost of rice production
per 10 acres has been found to have increased during our observation
period, from 952 Chinese Yuan in 2006 to 2,190 Chinese Yuan in 2018.
Conversely, the rice production cost per unit area has decreased in Japan,
from 148,382 Japanese Yen in 2003 to 132,020 Japanese Yen in 2020.

Figure 1.6 Comparisons of rice production costs (Japonica rice) between China and Japan.
Source: Calculated by the author.

8

Chapter 1
Comparison of Rice Production in China and Japan

Figure 1.7 shows the composition of costs and their changes in the twocountries. In both China and Japan, raw material costs are mainly dominant.
In China, raw materials, labor costs, and land costs have exhibited anincreasing trend since 2006. Moreover, the growth rate of labor expenditure
became higher and even exceeded that of raw materials during 2013–2016.
Since 2017, raw material costs have still been higher than labor costs, but
the gap between them has narrowed. In contrast to China, raw materials
rather than labor costs are the major expense for rice production in Japan.
All costs are leveling off, and especially labor costs and land costs show asimilar variation with less fluctuation and a decreasing trend.

Figure 1.7 Composition changes in rice production costs between China and Japan.
Source: Calculated by the author.
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Toward Sustainable Agriculture of Rice in Asia

Regarding labor input in rice production, family labor remains
the mainstay of labor input in rice farming, both in China and Japan(see Figure 1.8). However, we can also see that family labor input has
significantly decreased in both China and Japan, but employed labor
input remains stable.

Figure 1.8 Comparison of labor input in rice production between China and Japan.
Source: Calculated by the author.

Correspondingly, the hourly wage is rapidly increasing in China but
remaining flat in Japan (see Figure 1.9). As a result, we can infer the10

Chapter 1
Comparison of Rice Production in China and Japanreasons accounting for reduced labor input in China’s rice production
are different from those in Japan’s rice production. Possible explanations
for reduced labor input in China’s rice production are labor migration
and rising labor wages. Conversely, the reasons for reduced labor input
in Japan may be attributed to the aging agricultural population and thereplacement of labor with capital.

Figure 1.9 Comparison of hourly wage in rice production between China and Japan.
Source: Calculated by the author.

Concerning land rent in rice production (see Figure 1.10), we
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Toward Sustainable Agriculture of Rice in Asia

observe that both land rent of owned land and land rent of borrowed
land are increasing in China, primarily due to China’s rapid
urbanization. However, land rent of owned land is decreasing, while theland rent of borrowed land remains flat in Japan. It is interesting to notethat the land rent of owned land is higher than that of borrowed land forboth countries.

Figure 1.10 Comparison of land rent in rice production between China and Japan.
Source: Calculated by the author.

In brief, China’s rice production costs have risen rapidly before
leveling off, whereas Japan’s production costs have decreased to four
12

Chapter 1
Comparison of Rice Production in China and Japan

times as much as China’s. In terms of cost composition, raw materials
have been the main cost for both countries over the years, accounting
for more than 60% in Japan and 43% in China (see Table 1.1). The shareof labor cost is the largest in China (nearly 36%) while the share of raw
materials is the largest in Japan. Labor wages and land rent are risingin China, while they remain level in Japan. In conclusion, China’s riceproduction costs are primarily driven by labor expenses, while Japan’s
rice production costs are mainly influenced by capital and fertilizer
inputs.
Table 1.1 Composition in the amount of money regarding rice production between
China and Japan.
Per 10 ha.
% of Raw Materials% of Labor Cost
% of Land Cost
Total Cost
(current LCU)
Cost Revenue Ratio

China
43.09
35.86
21.04
1701 RMB
0.79

Japan
60.11
29.21
10.68
140925 Yen(6921 RMB)
1.29

Source: Calculated by the author.

Moreover, to measure the efficiency of rice production expenses
in relation to its earnings in the two countries, I calculated the costrevenue ratio of rice production in China and Japan, respectively. The
cost-revenue ratio of China is calculated as 0.79, while that of Japan is
1.29. From this figure alone, it seems that rice production in Japan is
unprofitable. Nevertheless, we should note that the cost includes what
the farmers pay themselves. Namely, the shadow costs consist of wages
paid for family labor, interest paid for owned funds, and rent paid forowned land. If we subtract the shadow costs, we can obtain the costrevenue ratio without shadow costs.
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Toward Sustainable Agriculture of Rice in Asia

The cost-revenue ratio without shadow costs is 0.65 for China and0.84 for Japan, suggesting producing rice is still profitable even if theideal cost is not obtained. And the shadow cost-revenue ratio is 0.14
for China and 0.45 for Japan. This study does not focus on revenue
only because revenue involves more factors such as market stocks,
government subsidies, etc. Interestingly, the following figures show therevenues per 10a, which is higher in China than in Japan (see Figure1.11).

Figure 1.11 Comparison of revenue in China and Japan.
Source: Calculated by the author.

14

Chapter 1
Comparison of Rice Production in China and Japan

Table 1.2 reports the composition in the quantity of input uses
in China and Japan. Labor input in China (on average, 100 hours) ismuch higher than in Japan (on average, 28 hours). Surprisingly, Japan
consumes much more fertilizer input than China, with fertilizer amountsof 64.23 kg and 39.44 kg, respectively. The biggest difference between
both countries is capital input. Especially, Japan consumes more than
three times the capital input (2,084 RMB per 10ha) of China (316 RMB
per 10ha). Rice production in China depends more on labor, while Japandepends more on capital.
Table 1.2 Composition in the quantity of input uses regarding rice production
between China and Japan.
Per 10 ha.
Labor Input (Hours)of which, Family Laborof which, Employed Labor
Seeds (kg)Fertilizer (kg)China
100.41
88.10
12.77
9.15
39.44

Capital (current LCU)

316 RMB

Japan
28.38
26.54
1.83
2.72
64.23
42299 Yen
(2084 RMB)

Source: The data are from the National Cost and Profit of Agricultural Products
Materials Compilation, the National Bureau of Statistics, and the database of the
Ministry of Agriculture, Forestry and Fisheries of Japan.

3. Measurement of Production Efficiency
This study applied data envelopment analysis (DEA), a nonparametric method, to estimate the production efficiency of rice in China
and Japan. DEA was initially proposed by Charnes et al. (1978) to
calculate the operation efficiency of the decision-making unit (DMU) in
public programs to improve the planning and control of these activities.
15

Toward Sustainable Agriculture of Rice in Asia

The efficiency of any DMU is obtained as a maximum of a ratio of
weighted outputs to weighted inputs subject to the condition that thesimilar ratios for each DMU be no more than unity in this method. In
more precise form, it can be expressed as:
𝑢𝑢𝑢𝑢1 𝑦𝑦𝑦𝑦1𝑖𝑖𝑖𝑖 + 𝑢𝑢𝑢𝑢2 𝑦𝑦𝑦𝑦2𝑖𝑖𝑖𝑖 + ⋯ + 𝑢𝑢𝑢𝑢𝑚𝑚𝑚𝑚 𝑦𝑦𝑦𝑦𝑚𝑚𝑚𝑚𝑖𝑖𝑖𝑖
max 𝜃𝜃𝜃𝜃𝑖𝑖𝑖𝑖 =								(1)v,u𝑣𝑣𝑣𝑣1 𝑥𝑥𝑥𝑥1𝑖𝑖𝑖𝑖 + 𝑣𝑣𝑣𝑣2 𝑥𝑥𝑥𝑥2𝑖𝑖𝑖𝑖 + ⋯ + 𝑣𝑣𝑣𝑣𝑛𝑛𝑛𝑛 𝑥𝑥𝑥𝑥𝑛𝑛𝑛𝑛𝑖𝑖𝑖𝑖

subject to𝑢𝑢𝑢𝑢1 𝑦𝑦𝑦𝑦1𝑗𝑗𝑗𝑗 +𝑢𝑢𝑢𝑢2 𝑦𝑦𝑦𝑦2𝑗𝑗𝑗𝑗 +⋯+𝑢𝑢𝑢𝑢𝑚𝑚𝑚𝑚 𝑦𝑦𝑦𝑦𝑚𝑚𝑚𝑚𝑗𝑗𝑗𝑗≤ 1 (𝑗𝑗𝑗𝑗 = 1, … , 𝑡𝑡𝑡𝑡)								(2)u𝑝𝑝𝑝𝑝 ≥ 0 (𝑝𝑝𝑝𝑝 = 1, … , 𝑚𝑚𝑚𝑚)
𝑣𝑣𝑣𝑣1 𝑥𝑥𝑥𝑥1𝑗𝑗𝑗𝑗 +𝑣𝑣𝑣𝑣2 𝑥𝑥𝑥𝑥2𝑗𝑗𝑗𝑗 +⋯+𝑣𝑣𝑣𝑣𝑛𝑛𝑛𝑛 𝑥𝑥𝑥𝑥𝑛𝑛𝑛𝑛𝑗𝑗𝑗𝑗

v𝑞𝑞𝑞𝑞 ≥ 0 (𝑞𝑞𝑞𝑞 = 1, … , 𝑛𝑛𝑛𝑛),

where 𝑦𝑦𝑦𝑦𝑝𝑝𝑝𝑝𝑝𝑝𝑝𝑝 and 𝑥𝑥𝑥𝑥𝑞𝑞𝑞𝑞𝑞𝑞𝑞𝑞 are the known outputs and inputs of the ith DMU,
p denotes the category of outputs and q denotes the category of inputs.

𝑢𝑢𝑢𝑢𝑝𝑝𝑝𝑝 and 𝑣𝑣𝑣𝑣𝑞𝑞𝑞𝑞 are the variable weights of each output and input which
are called virtual multipliers and are to be determined by the solutionof this problem. 𝜃𝜃𝜃𝜃𝑖𝑖𝑖𝑖 is the measured efficiency for the ith DMU.
In this study, I treat each agricultural province/region as a DMU andadopt the output-oriented DEA model with the variable returns to scale(VRS). The output variable is the rice output per 10 acres, while theinput variables are the labor input per 10 acres in agricultural production
activity, agricultural fixed assets costs per 10 acres, energy costs per 10
acres, fertilizer costs per 10 acres, and seeds costs per 10 acres. All data
relating to the amount are deflated to the prices of 2015. Panel data wascollected across provinces in China (2006–2018) and regions in Japan(2005–2020).

16

Chapter 1
Comparison of Rice Production in China and Japan

4. Empirical Evidence
Unsurprisingly, the estimated results from DEA show that the
average efficiency score of rice production is 0.922 in China and muchhigher than that of 0.721 in Japan, suggesting China’s rice production
exhibits greater production efficiency than Japan’s rice production.
However, the summary of the estimated score in Figure 1.12 shows that
there is an upward trend in production efficiency in Japan while it stays
at a stable level in China.

Figure 1.12 Estimated efficiency score of rice production in China and Japan.
Source: Calculated by the author.
17

Toward Sustainable Agriculture of Rice in Asia

Figure 1.13 shows the regional variation in efficiency scores in
China and Japan. Initially, it was thought that regional variation is larger
in China as it has a huge land area and climatic conditions are quite
diversified, especially in the northern and southern regions. However,
the estimated result shows that efficiency variation across regions ismuch larger in Japan. More specifically, rice production in the Hokkaido
region is the most efficient since its farm size is much larger than otherregions in Japan, followed by the Tohoku region.

Figure 1.13 Variation in efficiency score by region.
Source: Calculated by the author.
18

Chapter 1
Comparison of Rice Production in China and Japan

In addition, the findings from Table 1.3 reveal the differences in thefactors influencing rice production efficiency between China and Japan.
The results indicate that the land rent of owned land has a positive andsignificant effect on rice production efficiency in China, while it has anegative and significant effect in Japan. This could be attributed to the factthat increasing the size of farms can enhance rice production efficiency inJapan, but it could have the opposite effect in China due to differences inlabor and capital allocation per unit acreage between the two countries.
Interestingly, the shadow cost-revenue ratio has a significant andnegative effect on rice production efficiency in Japan only. This suggeststhat farmers in Japan may not have sufficient motivation to improve theirproduction efficiency, as they may already be earning enough money andsee little need to work harder to increase efficiency in their rice production.
Table 1.3 Rice production efficiency and its determinant.
VARIABLES
Wage of family labor
Wage of employed laborLand rent of owned land
Land rent of borrowed land
Shadow cost -revenue-ratio
Constant
Observations
Number of dmu
R-squared

China
0.036
(-0.033)-0.045(-0.03)0.0259**(-0.012)0.012(-0.011)-3.703(-27.65)
90.050***(2.704)
120
14
0.144

Japan
-0.001-0.01
0.004-0.003-0.001***(0.000)-0.001*(0.001)-18.860***(6.017)93.390***(9.057)
157
9
0.485

Note: Standard errors in parentheses. *** p<0.01, ** p<0.05, * p<0.1.
19

Toward Sustainable Agriculture of Rice in Asia

5. Conclusion
This study compared the rice production between China andJapan by decomposing the production costs and estimating production
efficiency in rice production. From the decomposition analysis of riceproduction costs, we find that the cost-revenue ratio (with shadow
cost included) in Japanese rice production is much higher than thatin Chinese rice production. However, if the shadow cost is excluded,
the gap between the two countries becomes much less. Moreover,the shadow cost-revenue ratio is much larger in Japan than in China.
It implies that while the costs of producing rice in China are lower,
Japanese rice production is not completely unprofitable once its selfpayments are subtracted.
There are several possible reasons accounting for the higher costrevenue ratio in Japan’s rice production than in China’s rice production.
One possibility is that it is due to most input prices being much lower
in China than in Japan. Especially, labor wages are far lower in China’s
rice sector than that in Japan’s rice sector, and China adopts an intensive
labor input way of producing rice compared with Japan. Hence, eventhough China’s rice sale prices are lower than Japan’s rice sale prices,
production costs are relatively lower in China than in Japan.
Another possibility is that China is producing rice more efficiently
than Japan, which could also make its cost-revenue ratio lower thanJapan’s. To verify this point, we conducted a DEA method to estimate
the rice production efficiency for the two countries. The results fromthe DEA reveal that the estimated efficiency score of rice production
is greater in China (0.92) than that in Japan (0.72). Thus, regardless ofvariety or quality, China produces rice much more efficiently than Japan.
The reasons behind this are that in China, regarding the policy and20

Chapter 1
Comparison of Rice Production in China and Japanfood self-sufficiency aims, the scarce input resources in rice production
resulting from the structural transformation and the changes in the
dietary structure make its rice production more efficient. Furthermore,
the low shadow cost-revenue ratio stimulates its peasants to produce
rice efficiently to acquire more profits. However, in Japan, the acreage
reduction policy (or Gentan policy), the decreasing domestic demand
for rice, the export disadvantage of rice, and the high shadow costrevenue-ratio make the motivation for promoting rice efficiency lessurgent. Hence, even though Japan’s mechanization level is much higher
than China’s, its production efficiency is relatively lower.

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Charnes, A., W. W. Cooper, and E. Rhodes. 1978. Measuring the
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Horie, T., T. Matsui, H. Nakagawa, and K. Omasa. 1996. Effects ofElevated CO2 and Global Climate Change on Rice Yield in Japan.
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Huang, J., S. Rozelle, and H. Wang. 2006. Fostering or Stripping Rural
China: Modernizing Agriculture and Rural to Urban Capital Flows.
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Kusakari, H. 1989. Inasaku Noka kara mita Gentan Seisaku no Keizaisei(Economic Efficiency of Rice Acreage Reduction Policy fromthe Perspective of Farm Scale). Nogyo Keizai Kenkyu (Journal of
Rural Economics), 61(1), pp. 10–18 (In Japanese).
Li, H., and M. Li. 2011. Collective Water Management and Technical
Efficiency in Rice Production: Evidence from China. The Journalof Developing Areas, 44(2), pp. 391–406.
Li, Y. 2006. Water Saving Irrigation in China. Irrigation and Drainage:
The Journal of the International Commission on Irrigation andDrainage, 55(3), pp. 327–336.
Lin, J.Y. 1992. Rural Reforms and Agricultural Growth in China.
American Economic Review, 82(1), pp. 34–51.
Lyu, Y., X. Zhang, X. Yang, J. Wu, L. Lin, Y. Zhang, G. Wang, Y. Xiao,
H. Peng, X. Zhu, and X. Yu. 2020. Performance Assessmentof Rice Production based on Yield, Economic Output, Energy
Consumption, and Carbon Emissions in Southwest China during
2004–2016. Ecological Indicators, 117 <https://doi.org/10.1016/
j.ecolind.2020.106667>.
Ma, G., and L. Yuan. 2003. Hybrid Rice Achievements andDevelopment in China. Hybrid Rice for Food Security, Poverty
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International Rice Research Institute, pp. 247–256.
Matsukura, S., T. Nanseki, Y. Fujii, M. Sato, Y. Chomei, and M.
Miyazumi. 2015. Daikibo Inasaku Keiei ni okeru Gijutsu/Gino
Kojo oyobi Kibo Kakudai no Kosuto Teigen Koka: FAPS-DB wo
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mochiita Simulation Bunseki (Effect of Farming Skill and Farm
Size on Production Costs on Large Rice Farms: A Simulation
Analysis by FAPS-DB). Nogyo Johou Kenkyu (Journal of
Agricultural Informatics), 24(2), pp. 35–45 (In Japanese).
Nakagawa, H., T. Horie, and T. Matsui. 2003. Effects of Climate
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September 2002. International Rice Research Institute (IRRI), pp.
635–658.
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Peng, S., Q. Tang, and Y. Zou. 2009. Current Status and Challenges of
Rice Production in China. Plant Production Science, 12(1), pp. 3–8.
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no Kanosei to Joken: Suri Keikaku-ho no Tekiyo ni yoru Suiden
Siryosaku Keiei no Kihan Bunseki to Siryo Seisan Kosuto (TheViability and Conditions of Fodder Farming on Paddy Fields:
A Comprehensive Economic Evaluation of Fodder Farming on
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Programming Models). Nogyo Keiei Kenkyu (Japanese Journal of
Farm Management), 52(4), pp. 1–16 (In Japanese).
Shimokawa, S., Y. Niiyama, Y. Kito, H. Kudo, and M. Yamaguchi. 2018.
No-tolerant Consumers, Information Treatments, and Demand for
Stigmatized Foods: The Case of Fukushima Nuclear Power Plant
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Fertilizers Contribute to Fertilizer Overuse? Evidence from Rice
Production in China. Journal of Cleaner Production, 219, pp. 677–
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Tao, F., M. Yokozawa, Y. Hayashi, and E. Lin. 2003. Future Climate
Change, the Agricultural Water Cycle, and Agricultural Productionin China. Agriculture, Ecosystems & Environment, 95(1), pp. 203–215.
Tsunekawa, I. 2016. Siryo Youmai no RYutu/Riyo no Jittai to Kosuto
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53(4), pp. 6–16 (In Japanese).
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24

Chapter 2
Impact of High-Quality Rice Variety on Profit and Profit Efficiency

Chapter 2
Impact of High-Quality Rice Variety on Profit
and Profit Efficiency: Evidence from Vietnam
Phuc Trong HO
Abstract: High-quality rice varieties (HQRV) are expected tocontribute more profit than conventional rice varieties. However, theobserved profit gap is not attractive. This study assesses the impactof HQRV adoption on farmer profit and profit efficiency (PE) using
farm-level data from 356 rice farmers surveyed in Vietnam’s MekongRiver Delta. We combine a propensity score matching (PSM) method
and a stochastic profit frontier framework to mitigate the effects of
selection biases and technology gaps. We use the PSM method to finda comparable non-adopter group to control selection bias associatedwith observed variables. A sample selection stochastic frontier model isthen used to correct selection bias stemming from unobserved factors.
Finally, we apply a stochastic meta-frontier approach to compare PE
between groups. The analysis shows that the profit and PE gaps between
the two groups are significantly underestimated if selection biases andtechnology gaps are not considered. A comparison of profit and PE
scores reveals that HQRV adopters, on average, exhibit higher variable
profits than non-adopters (1,085 USD/ha vs. 982 USD/ha) but lower PE
performance (0.61 vs. 0.72), suggesting that adopters will benefit morefrom HQRVs if inefficiencies are eliminated. The results also indicatethat farm size, contract farming, rice plots, and geographical andseasonal factors influence HQRV adoption.

25

Toward Sustainable Agriculture of Rice in Asia

1. Background
Vietnam has been one of the world’s leading rice producers (withnearly 44 million tons) and exporters (nearly 6.1 million tons) for thelast decade (GSO 2018). The Mekong River Delta is the main riceintensified area for export, accounting for approximately 90% of thetotal export volume (accounting for 5.4 million tons of milled rice)(GSO 2018) (Figure 2.1). The observed profitability of rice farming
remains low. One of the main reasons is that rice farmers still use thetraditional low-quality rice varieties. To improve its output quality andprice, the Vietnamese government introduced and encouraged farmers
to adopt high-quality rice varieties and hopefully increase output prices,competitiveness advantage, and farmers’ income. High-quality rice
varieties (HQRVs) are expected to increase profits for rice farmers by30%; however, the profit gap between these varieties and conventional
ones is not as high as expected. The goal of this study is to analyze
and address how much difference in the profit and profit efficiency is
between HQRV adoption and non-adoption.

Figure 2.1 Distribution of rice area in Vietnam.
Source: (Shean 2012)
26

Chapter 2
Impact of High-Quality Rice Variety on Profit and Profit Efficiency

2. Research Approach
A direct comparison of profit and profit efficiency is not accurate
due to (1) facing sample selection bias arising from both observable (e.g.,age, education, and gender) and unobservable (e.g., risk preferences,motivation, and managerial ability) factors and (2) facing a technology
gap between rice variety groups. Hence, to control sample selection bias
and the technology gap between the two rice variety groups, this study
uses a combined framework as applied in Villano et al. (2015). This is
a combination of an impact evaluation technique (i.e., propensity scorematching) and stochastic profit frontier framework to eliminate thepotential effects of self-selection biases.
Step 1. A propensity score matching method (PSM) (Rosenbaumand Rubin 1983) is applied to correct selection bias stemming fromobservable variables.
Step 2. A sample selection corrected stochastic frontier model(Greene 2010) is employed to eliminate selection bias arising fromunobservable factors.
Step 3. A stochastic meta-frontier approach (Huang et al. 2014)
is applied to control the effects of the technology gap and make adirect comparison of profit efficiency between the two groups.

3. Empirical Models(1) Propensity Score Matching (PSM)
The PSM method is implemented to identify comparable adopter
and non-adopter groups using a propensity score or probability
model (Logit or Probit). Here, the Probit model is applied to estimate
propensity scores, which are then used to match adopters and non27

Toward Sustainable Agriculture of Rice in Asia

adopters for farms falling within a common probability range (orcommon support). We tested several matching criteria (e.g., one-to-one,nearest neighbor, radius, kernel, and local linear regression matching),
and the nearest neighbor matching is used because it generates a bettermatched sample. In our case, we used five matches per adopter, with acaliper of 0.005.
The Probit model for matching is expressed as:𝑖𝑖𝑖𝑖								𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝑖𝑖𝑖𝑖 = 1[� 𝛼𝛼𝛼𝛼𝑛𝑛𝑛𝑛 𝑧𝑧𝑧𝑧𝑛𝑛𝑛𝑛𝑖𝑖𝑖𝑖 + 𝑒𝑒𝑒𝑒𝑖𝑖𝑖𝑖 > 0](1)

𝑛𝑛𝑛𝑛=1

where i denotes farm, DHQR is a binary variable, 1 for adopters and
0 for non-adopters. Zn is a vector of explanatory variables for farmers’
adoption decisions, including farm and farmers’ characteristics. α is thevector of unknown parameters to be estimated, and e is the disturbanceterm distributed as N (0,1)(2) Sample Selection Stochastic Frontier (SF) Model
After obtaining a matched sample, matched subsamples can be used
to estimate a stochastic profit frontier model for each group and compare
the results. However, the decisions on HQRV adoption can be affectedby unobserved factors (e.g., managerial ability), which could lead todifferences in efficiency. Thus, the sample selection stochastic frontiermodel proposed by Green (2010) is used to mitigate the potential effects
of self-selection bias from unobserved factors.
The sample selection (Probit) model is described as follows:
𝑑𝑑𝑑𝑑i = 1[𝛼𝛼𝛼𝛼´𝑍𝑍𝑍𝑍i + 𝑤𝑤𝑤𝑤i > 0], 𝑤𝑤𝑤𝑤i~(0,1)
where d is a binary variable equal to 1 for adopters and 0 for nonadopters, Z is a vector of observed explanatory variables, and w is theunobservable error term.
28

Chapter 2
Impact of High-Quality Rice Variety on Profit and Profit Efficiency

Stochastic profit frontier model:

𝜋𝜋𝜋𝜋i = 𝑓𝑓𝑓𝑓 (𝛽𝛽𝛽𝛽; 𝑃𝑃𝑃𝑃i; 𝐹𝐹𝐹𝐹i) 𝑒𝑒𝑒𝑒 (𝑣𝑣𝑣𝑣𝑖𝑖𝑖𝑖 −𝑢𝑢𝑢𝑢𝑖𝑖𝑖𝑖 )(2)(𝜋i, 𝑃i, 𝑍i) are observed only when di = 1 or di = 0, but not bothComposed error structure: vi – uiInefficiency term: 𝑢i ~ 𝑁+(0, 𝜎𝜎𝜎𝜎𝑢𝑢𝑢𝑢2 )Symmetric noise term: vi ~ 𝑁 (0, 𝜎𝜎𝜎𝜎𝑣𝑣𝑣𝑣2 )Error correlation between SF and selection model:(𝑤𝑤𝑤𝑤i, 𝑣𝑣𝑣𝑣i) ~ 𝑁𝑁𝑁𝑁2 [(0,0), (1, 𝜌𝜌𝜌𝜌𝜌𝜌𝜌𝜌v, 𝜌𝜌𝜌𝜌𝑣𝑣𝑣𝑣2 )]where 𝜋i is variable profit (equal to revenue less variable cost), Pi is avector of input prices, Fi is a vector of fixed inputs, and the composederror term comprises the statistical noise term v i and non-negative
inefficiency term ui. α and β are unknown parameters to be estimated.
𝜌 shows the relationship between unobservable error in the sample
selection model and statistical noise in the SF model.
However, PE between adopter and non-adopter groups cannot
be directly compared because efficiency scores are estimated relative
to each group’s frontier, not relative to the meta-frontier and existing
potential technology gaps between farmers using the two rice variety
groups. Therefore, it is necessary to use a meta-frontier approach togenerate a common frontier and estimate the technology gap ratio,
which can construct a measure of overall PE.

(3) Stochastic Meta-Frontier Model
In Step 1, the SF model for each group is estimated:ln 𝜋ji = ln𝑓j(𝛽j; 𝑃ji; 𝑍ji) + 𝑣ji – 𝑢ji			(3)Then, the profit efficiency scores are estimated, PEj:�𝚥𝚥𝚥𝚥 = 𝑃𝑃𝑃𝑃� �𝑒𝑒𝑒𝑒 −𝑢𝑢𝑢𝑢𝑗𝑗𝑗𝑗𝑗𝑗𝑗𝑗𝑗𝑗𝑗𝑗 �(𝑣𝑣𝑣𝑣� − 𝑢𝑢𝑢𝑢�)�
𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝚥𝚥𝚥𝚥𝚤𝚤𝚤𝚤
𝚥𝚥𝚥𝚥𝚤𝚤𝚤𝚤
𝚤𝚤𝚤𝚤
29

Toward Sustainable Agriculture of Rice in Asia

𝚥𝚥𝚥𝚥
In Step 2, the predicted values for adopters and non-adopters 𝑙𝑙𝑙𝑙�
𝑙𝑙𝑙𝑙𝑙𝑙𝑙𝑙= (𝛽j; 𝑃ji; 𝑍ji) are used as the dependent variables in the meta-frontier
estimation:

𝑚𝑚𝑚𝑚
𝑚𝑚𝑚𝑚
m
𝚥𝚥𝚥𝚥
𝑙𝑙𝑙𝑙�
𝑙𝑙𝑙𝑙𝑙𝑙𝑙𝑙 (𝛽j; 𝑃ji; 𝑍ji) = ln𝑓 (𝛽j; 𝑃ji; 𝑍ji) + 𝑣𝑣𝑣𝑣𝑗𝑗𝑗𝑗𝑗𝑗𝑗𝑗 + 𝑢𝑢𝑢𝑢𝑗𝑗𝑗𝑗𝑗𝑗𝑗𝑗 		�𝚥𝚥𝚥𝚥

Next, the technology gap is calculated, 𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝚤𝚤𝚤𝚤 = 𝐸𝐸𝐸𝐸� �𝑒𝑒𝑒𝑒

𝑚𝑚𝑚𝑚−𝑢𝑢𝑢𝑢𝑗𝑗𝑗𝑗𝑗𝑗𝑗𝑗

(4)

𝑚𝑚𝑚𝑚
𝑚𝑚𝑚𝑚
�
�(𝑣𝑣𝑣𝑣�𝚥𝚥𝚥𝚥𝚤𝚤𝚤𝚤 − 𝑢𝑢𝑢𝑢𝚥𝚥𝚥𝚥𝚤𝚤𝚤𝚤 )�

Then, it is possible to calculate meta-profit efficiency (Figure 2.2)

�𝚥𝚥𝚥𝚥 = 𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇�𝚥𝚥𝚥𝚥 × 𝑀𝑀𝑀𝑀𝑀𝑀𝑀𝑀
�𝚥𝚥𝚥𝚥 			(5)			 𝑀𝑀𝑀𝑀𝑀𝑀𝑀𝑀𝑀𝑀𝑀𝑀
𝚤𝚤𝚤𝚤
𝚤𝚤𝚤𝚤
𝚤𝚤𝚤𝚤
Common fron�er

YTechnology gap

Adoptergroup’s fron�er

Adopter
Non-adoptergroup’s fron�er
Proﬁt ineﬃciency
Non-adopter

X
Figure 2.2 Meta-frontier approach.
Source: (Huang et al. 2014)

4. Data and Materials
This study was conducted in the Mekong River Delta. The sampling
method is a three-step stratified random sampling technique. The
sample size of 356 rice farmers was collected from 16 villages in threeprovinces: An Giang (AG), Can Tho (CT), and Bac Lieu (BL) (Figure
30Chapter 2
Impact of High-Quality Rice Variety on Profit and Profit Efficiency2.3), covering three cropping seasons of the production year 2016/2017.
It generated 957 observations, with 414 adopters and 543 non-adopters.
After matching, the remaining sample is 841 observations, with 319
adopters and 522 non-adopters.

Figure 2.3 Rice Crop Map of the Mekong River Delta.
Source: (Nguyen et al. 2015)

As described earlier, the PSM method is used to identify acomparable control group to overcome the bias arising from differencesin observed factors between groups. In this study, the observed variables
included age (years), education (years of formal schooling), experience(years of rice farming), gender (1 for males, 0 otherwise), farm size
(hectares), rice plots (numbers), and contract farming (1 for contract31

Toward Sustainable Agriculture of Rice in Asia

farming, 0 otherwise). Furthermore, two dummy variables of regions(Region 1-AG and Region 2-CT) and crop seasons (Season 2 and Season3) are included to capture the effects of geographical settings and theeffects of seasonal factors. These observed variables are regressed in the
Probit model for the matching process and sample selection SF model.

5. Results
The result from Table 2.1 shows the influencing factors on decisionmaking on HQRV adoption or non-adoption based on the estimations of
Probit selection models for HQRV using a full and matched dataset. It can
be clearly seen that farm size and contract farming have positive effects
on the farmers’ decisions to become adopters, while the number of riceplots, regions, and seasons have negative effects on their decisions.
Table 2.1 Estimates of the Probit model for matching and sample selection model.
Variable
Constant
Age
Education
Experience
GenderFarm size
Rice plots
Contract farming
Region 1 (AG)Region 2 (CT)
Season 2
Season 3
Model properties
Log-likelihood (logL)
X2

Full sample
Coef.†
1.240***
0.006-0.011-0.0020.188
0.068*-0.138***0.631***-1.879***-1.783***-0.345***-0.498***

S.E.
0.419
0.009
0.015
0.008
0.251
0.027
0.036
0.176
0.148
0.148
0.108
0.116

-485.88337.49***Matched sample
Coef.†
S.E.
0.969**
0.437
0.008
0.009
-0.0230.016-0.004
0.009
0.230
0.267
0.072**
0.031-0.156***0.041
0.616***
0.189-1.558***0.159-1.497***0.158-0.428***0.113-0.529***0.120-455.33205.73***32

Chapter 2
Impact of High-Quality Rice Variety on Profit and Profit Efficiency

Pseudo R 2
Observations

0.258
957

0.184
841

Note: ***, **, * represent significant levels at 1%, 5%, 10%, respectively.
Source: Author

The result from Table 2.2 shows the comparisons in profit efficiency
estimation between conventional SF models and sample selection SF
models to select the best-fit model. Firstly, the pooled model is estimatedusing a log-likelihood ratio test to check whether only pooled modelor separate estimation models are necessary. The result shows that it isnecessary to estimate adopters and non-adopters separately. Also, theevidence on self-selection bias from unobservable factors and the log
log-likelihood ratio test also show that it is necessary to additionally run
a sample selection SF model.
Table 2.2 Estimates of conventional and sample selection SF models using matchedsample data.
Conventional SF model
PooledAdopter
Coef.†
S.E.
Coef.†
S.E.
Constant
9.596*** 0.359 9.741*** 0.663
lnPseed-0.084** 0.034 -0.126*
0.066
lnPfertilizer -0.364*** 0.071 -0.398*** 0.118
lnPlabor-0.162*** 0.037 -0.230*** 0.081
lnLand
1.003*** 0.051 0.970*** 0.091
lnCaptal
0.022
0.049 0.048
0.086
Season 2-0.267*** 0.023 -0.335*** 0.040
Season 3-0.279*** 0.025 -0.359*** 0.045
HQRV-0.040*0.021–
Model properties
Lambda (λ)
5.514*** 0.021 6.905*** 0.039
Sigma_u0.555*** 0.017 0.677*** 0.032
Sigma_v
0.101*** 0.009 0.098*** 0.016
Rho(w,v)––
Probot logL––

VariableNon-adopter
Coef.†
S.E.
9.905*** 0.430-0.0170.043-0.328*** 0.083-0.170*** 0.040
1.081*** 0.062-0.0490.062-0.204*** 0.027-0.216*** 0.026–

Sample selection SF model
Adopter
Non-adopter
Coef.†
S.E.
Coef.†
S.E.
10.222*** 0.767
9.931*** 0.496-0.1200.072 -0.020
0.054-0.257**0.106 -0.338*** 0.095-0.279*** 0.092 -0.170*** 0.046
1.041*** 0.099 1.088*** 0.076-0.034
0.096 -0.056
0.075-0.381*** 0.046 -0.195*** 0.040-0.430*** 0.052 -0.206*** 0.040––

4.277*** 0.024
0.445*** 0.018
0.104*** 0.010
–
–

4.654
0.665***
0.143***
0.975***-252.60

33

–
0.016
0.028
0.142

4.264
0.446***
0.105***
0.262-202.72

–
0.010
0.010
0.500

Toward Sustainable Agriculture of Rice in Asia

SF logL-227.43
Total logL-227.43
LR test76.01***
Observations 841-140.00-140.00-49.43-49.43319

522-136.13-388.74
7.74***
319-49.13-251.860.59
522

Note: ***, **, * represent significant levels at 1%, 5%, 10%, respectively.
Source: Author

As expected, all estimates for input prices are negative andsignificant, except for the seed price coefficient in the non-adopter
models. The estimate for the land variable is positive and significant,while the estimate for the capital variable is not. The coefficients forthe two-season dummies are negative and significant in all models,
implying that variable profit tends to be lower outside the main growing
season. The coefficient for the dummy variable of HQRV in the pooledmodels is negative and significant, implying that HQRV adopters exhibit
lower profits than non-adopters.
Then, the stochastic meta-frontier model is run to calculate thetechnology gap ratio (Table 2.3). As expected, all coefficients for input
prices, fixed cost, and season dummy variables are significant at the
1% level and consistent across models. The parameter estimates ofsigma_u and lambda differ significantly from zero at the 1% level,
capturing statistical evidence for the technology gap between the twogroups.
Table 2.3 Estimates of stochastic meta-frontier model.
Variable
ConstantlnPseedlnPfertilizer
lnPlabor

Full sample
Coef.†
10.079***-0.067***-0.338***-0.209***

S.E.
0.047
0.005
0.009
0.005
34

Matched sample
Coef.†
S.E.
10.007***0.042-0.069***0.005-0.332***0.007-0.180***0.005

Chapter 2
Impact of High-Quality Rice Variety on Profit and Profit Efficiency

lnLandlnCapital
Season 2
Season 3
Model properties
Lambda (λ)
Sigma_uSigma_v
Log-likelihood
Observations

1.046***-0.035***-0.268***-0.285***

0.007
0.006
0.005
0.005

1.068***-0.043***-0.261***-0.273***

0.006
0.006
0.005
0.005

7.316***
0.097***
0.013***
1,433.31
957

0.004
0.003
0.002

11.906***
0.096***
0.008***
1,307.76
841

0.003
0.003
0.001

Note: ***, **, * represent significant levels at 1%, 5%, 10%, respectively.
Source: Author

In summary, Table 2.4 compares the profit efficiency between
adopters and non-adopters estimated in all SF models. The resultshows that HQRV adopters perform less profit-efficiently than nonadopters, and that profit efficiency gaps between the two groups are
significantly underestimated if selection biases and technology gaps are
not considered. Specifically, without controlling for any self-selection
bias and technology gap (Model 1), the average profit efficiency scoresfor adopters and non-adopters are 0.67 and 0.70, respectively, with aprofit efficiency gap of 4.6%. When selection bias from observable andunobservable factors was controlled (Model 4), the profit efficiency gap
increased to around 9.5%, with mean profit efficiency scores of 0.68 foradopters and 0.75 for non-adopters. However, that direct comparison
between the two groups is not accurate because it faces the problem of atechnology gap. After correcting for the technology gap (MPE in Model5), the mean profit efficiency for adopters and non-adopters are 0.61 and
0.72, with a profit efficiency gap of 15.4%.

35

Toward Sustainable Agriculture of Rice in Asia

Table 2.4 PE scores for adopters and non-adopters from SF models.
Model
1. Full sample Pooled PE
2. Matched sample Pooled PE
3. Conventional PE
4. Sample selection PE
5. TGR
MPE
Observations

Adopter
Non-adopter Difference in mean
Mean S.D. Mean S.D. Mean (%)
t-statistic†
0.67 0.21 0.70 0.15 -0.03 (-4.55%) -2.76***
0.69 0.20 0.72 0.15 -0.03 (-4.06%) -2.42**
0.67 0.19 0.75 0.15 -0.08 (-10.64%) -6.75***
0.68 0.19 0.75 0.15 -0.07 (-9.50%) -6.12***0.89 0.06 0.96 0.03 -0.07 (-6.87%) -20.19***0.61 0.17 0.72 0.14 -0.11 (-15.36%) -9.90***319
522

Note: ***, **, * represent significant levels at 1%, 5%, 10%, respectively.
Source: Author

The difference in profit efficiency scores between the two groups
is also shown in Figure 2.4, which presents the distribution of profit
efficiency scores between HQRV adopters and non-adopters. The
distribution for the adopter group is more dispersed to the lower value
range, implying an overall lower profit efficiency performance than
the non-adopter group. This suggests that there is statistical evidence
supporting the negative impact of HQRVs on farmers’ profit efficiencies.

Figure 2.4 Distribution of profit efficiency scores for adopters and non-adopters.
Source: Author
36

Chapter 2
Impact of High-Quality Rice Variety on Profit and Profit Efficiency

The results from Table 2.5 show the effects of HQRV adoption on
farmers’ variable profit. The result shows that the difference in actual(observed) variable profit between adopters and non-adopters is around
10.5%. It is obvious that this profit gap is not as attractive as expected(around 30%). This can be a possible reason why the adoption rateof HQRV is not high. However, the underlying reason is that HQRV
adopters perform less efficiently, which makes their profit efficiency
lower than non-adopters. After correcting for self-selection biases
arising from observed and unobserved heterogeneity and the technology
gap, the profit gap increases to around 28%. Particularly, the maximum
variable profit for adopters can be 1,741 USD/ha and higher by 28%
compared to non-adopters (1,358 USD/ha). Currently, compared to thefrontier, adopters can lose 655 USD/ha while non-adopters can lose 376
USD/ha.
Table 2.5 Effects of HQRV adoption on farmers’ variable profit.
Variable

Adopter
Mean S.D.
Observed variable profit (USD/ha) 1,085 463
Frontier variable profit (USD/ha)
1,741 474
Variable profit loss (USD/ha)
655
272
Observations
319

Non-adopter
Mean S.D.
982
363
1,358 404
376
192
522

Difference
Mean (%)†(10.49%)***
103(28.12%)***
382(74.20%)***
279

Note: ***, **, * represent significant levels at 1%, 5%, 10%, respectively.
Source: Author

6. Conclusion
This study analyzes the impacts of HQRVs on rice farmers’ profit
and profit efficiency performance and investigates the determinants of
HQRV adoption decisions.
The results show that farm size, rice plots, contract farming, regions,37

Toward Sustainable Agriculture of Rice in Asiaand seasons significantly influence HQRV adoption decisions. The
observed variable profit of HQRVs (per ha) is only 10.5% higher thanthat of conventional varieties, not as high as expected. This is explainedby the fact that HQRV adopters perform 15.4% less efficiently (0.61)
than non-adopters (0.72). If inefficiency were eliminated, HQRV
adopters could achieve around 28% (382 USD/ha) higher variable profit
than non-adopters.
The results suggest that to better exploit the potential of HQRVs,
policies should be targeted to improve rice farmers’ profit inefficiency
and promote the adoption of HQRVs. The findings recommend thatpolicies should consider increasing farm size and contract farming
to promote the adoption of HQRVs. In addition, HQRVs should be
developed to be better adapted to adverse production conditions.

References

Greene, W. 2010. A Stochastic Frontier Model with Correction for
Sample Selection. Journal of Productivity Analysis, 34, pp. 15–24.
GSO. 2018. Statistical Data: 06. Agriculture, Forestry and Fishing,
1990-2018. General Statistics Office of Vietnam, Vietnam. <https://www.gso.gov.vn>.
Huang, C. J., T. -H. Huang, and N. -H. Liu. 2014. A New Approachto Estimating the Meta-frontier Production Function based on a
Stochastic Frontier Framework. Journal of Productivity Analysis,
42, pp. 241–254.
Nguyen, D. B., K. Clauss, S. Cao, V. Naeimi, C. Kuenzer, and W.
Wagner. 2015. Mapping Rice Seasonality in the Mekong Delta
with Multi-Year Envisat ASAR WSM Data. Remote Sensing,
7(12), pp. 15868–15893.
38

Chapter 2
Impact of High-Quality Rice Variety on Profit and Profit Efficiency

Rosenbaum, P. R., and D. B. Rubin. 1983. The Central Role of thePropensity Score in Observational Studies for Causal Effects.
Biometrika, 70(1), pp. 41–55.
Shean, M. 2012. Vietnam: Record Rice Production Forecast on Surgein Planting in Mekong Delta. Commodity Intelligence Report,
USDA Foreign Agricultural Service. <https://ipad.fas.usda.gov/
highlights/2012/12/Vietnam/>Villano, R., B. Bravo-Ureta, D. Solís, and E. Fleming. 2015.
Modern Rice Technologies and Productivity in the Philippines:
Disentangling Technology from Managerial Gaps. Journal of
Agricultural Economics, 66(1), pp. 129–154.

39

Toward Sustainable Agriculture of Rice in Asia

Chapter 3
Drought Effect and Adaptation of Farmers inNortheast Thailand
Orawan SRISOMPUN
Abstract: The drought situation in Thailand tends to increase infrequency. In 2019, Thailand experienced its worst drought in four
decades. Most of the drought-affected plantations are in the Northeast.
So, drought stress has extensively affected the farmer households withhigh levels of vulnerability to poverty in Northeast Thailand. This study
analyzes the effect and adaptation of drought on farmer households inthe study area. The results revealed that 80% of the farmers affected bydrought in 2019 were small farmers. On average, the decline in paddy
yields caused by drought ranged from 1,757 to 4,661 kilograms perhousehold (equating to approximately 25,840–50,171 Thai baht perhousehold). In addition, drought caused 30.12% of farmers in recognizeddrought areas to have insufficient rice available for consumption.
The agricultural income of farmer’s households in declared drought
areas diminished from 27.82% to 20.49% of total income. Farmers in
irrigated areas adapted most effectively to drought by suspending rice
growing, searching for additional water sources, adjusting the growing
period, reducing the amount of land used for rice growing, adjusting
the rice ecotypes cultivated, cultivating different plants instead of rice,and temporarily changing to rearing livestock and other occupations.
However, more than 50% of farmers lacked crop insurance because
insurance premiums may increase the cost of rice growing. Although
the Thai government has continued measures to mitigate the effects ofdrought, they failed in the long term. It is necessary to have a long-term
40

Chapter 3
Drought Effect and Adaptation of Farmers in Northeast Thailand

plan and extensive investment in drought management, as well as toadjust stakeholders’ strategies throughout the supply chain.

1. Introduction
The frequency of drought situations in Thailand is tending toincrease. In 2019, Thailand experienced its worst drought in four
decades. The drought-affected rice cultivation area is about 3.90 millionrai (1 rai=0.16 hectare), or about 6.60% of the country’s rice-cultivatedarea. The amount of damage is estimated to be approximately 8,900
million Thai baht. Most of the drought-affected plantations were in the
Northeast regions. In 2015, 2018, and 2019, approximately 62.58%,
94.36%, and 76.29% of the total drought-affected rice plantations werein the Eastern region. The total damage from the drought was 3,649
million Thai baht, or accounted for 40.62% of the total damage value ofthe country. The Northeast regions have had a serious drought for a longtime and face problems with poverty and low rice yields (Figure 3.1).

Figure 3.1 Farmers coping with drought. Source: Author

A serious drought in Thailand in 2019 caused a shortage of watersupply for agriculture. Especially, lack of water and weed problems in41

Toward Sustainable Agriculture of Rice in Asia

rice fields are emerging issues. Consequently, the quantity and qualityof rice are adversely affected. In the Northeast region, the main purposeof rice cultivation is mainly for household consumption. If there is riceleft over from consumption and it is assured that the following year’s
rice yield will be sufficient for consumption, then the farmer will sell
the remaining rice to the market. Therefore, drought affects not only
household income but also food security. To cope with drought and its
impacts, farmers applied a variety of coping strategies. They included
additional water sources, adjusting the growing period, reducing rice
area, changing to other plants, keeping livestock and other occupations.
The ability for adaptation is different between resource-based,
economic-based, and social characteristics. The conceptual frameworkof this study is shown in Figure 3.2.

Figure 3.2 Conceptual framework. Source: Author

This study aims to (1) understand the economic and social impactsof the drought situation on farmer households in the Northeast, (2)analyze the pattern of drought adaptation among farmer households
42Chapter 3
Drought Effect and Adaptation of Farmers in Northeast Thailand

in the Northeast, and (3) analyze the factors affecting the farmers’
adaptation to drought problems in the Northeast.

2. Data, Sampling, and Study Area
The sampling method used in this research is the three-step stratified
sampling technique. The first step is to determine the target province
in the survey by integrating data from three sources: the Department ofAgricultural Extension, the Department of Land Development, and theDepartment of Disaster Prevention and Mitigation (DDPM) (Table 3.1).
Table 3.1 Target province in the survey
No. Province

1
2
3
4
5
6
7
8
9
10

Department ofAgricultural Extension
Year
2019
2018
2017



Khonkaen*
Chaiyaphom*Burirum*Nakonratchasima* Mahasarakham*
Nongkai
BuengkanNakornphanom*Sisaket*
Surin*-

Department of
DDPM
Land Development
2004–2014
2019
















-

Score
(Maximum = 5)
5*
3*
5*
4*
5*
2
2
3*
4*
3*

Source: (Srisompun 2021)

The second step is to select the target district from the Departmentof Agricultural Extension database.
The final step is to select the target district (Department ofAgricultural Extension database and suggestions from local government
staff). The samples were divided into two groups: 1) the farmers affectedby drought and 2) the unaffected by drought group, the sampling method
for each group is as follows:
1. Sub-districts representing drought-affected areas must be sub43

Toward Sustainable Agriculture of Rice in Asia

districts that have been affected by drought for at least two years
during the past five years (2015–2019); choose one study area ineach province. A total of eight sub-districts were involved.
2. Sub-districts representing areas not affected by drought must be
sub-districts with no drought-affected areas during the past five
years (2015–2019); select one study area in each province. A totalof eight sub-districts were involved (Figure 3.3).
3. Samples are randomly drawn from the list of farmers receiving
drought compensation. (Department of Agricultural Extension in
2019)

Figure 3.3 Research areas. Source: Adapted from (Boonmas 2021)

This study uses both secondary and primary data. Primary data
was collected from 600 questionnaires of farmers in irrigated andrainfed areas of the Northeast region including eight provinces ofNakhon Phanom, Maha Sarakham, Khon Kaen, Chai Ya Phom, Nakhon
Ratchasima, Burirum, Surin, and Sri Sa Ket.
Factors affecting decision-making on adaptation among farmers indrought situations were analyzed using the logistic regression model.

44

Chapter 3
Drought Effect and Adaptation of Farmers in Northeast Thailand

3. Economic and Social Effects of Drought on Rice FarmHouseholds(1) Drought Effect on Farmers in Northeast Thailand
According to surveyed data, 80% of the farmers affected bydrought in 2019 were small farmers. Thailand has been suffering fromcontinuous drought since 2015, with severe impacts on rice production.
During 2015–2020, most of the surveyed farmers experienced serious
impacts, especially farmers in rainfed areas (Figure 3.4).

Figure 3.4 Proportion of sample farmers who have been affected by drought in
the past six years (2015-2020), by production environment and farm size. Source:(Srisompun 2021)

Paddy quality and yield loss caused by drought varied by farmsize. During the serious drought in 2019, farmers faced a water
shortage for rice cultivation. Consequently, the lack of water adversely
affected rice yield. The average rice yield per Rai and per household in
drought-declared 2019 areas was lower than in 2020 in all production
environments (i.e., rainfed and irrigated) (Figure 3.5). For small farms,
rice productivity in 2019 was also lower than in 2020.
45

Toward Sustainable Agriculture of Rice in Asia

Figure 3.5 Average rice yield of sample farmers in 2019-2020 classified by production
environment, type of water source, and farm size. Source: (Srisompun 2021)

The amount of yield and the damage value of rice yield fromdrought are directly proportional to the size of the planting area.
Especially, yield and rice values of small farms are observed to belower than those of large farms, and the rice yield of large farms is thehighest in terms of both quantity and value. On average, the decline inpaddy yields caused by drought ranged from 1,757 to 4,661 kilograms
per household (equating to approximately 25,840–50,171 baht perhousehold). (Figure 3.6).

Figure 3.6 The impact of drought in 2019 on the quantity and value of rice yields.
Source: (Srisompun 2021)
46

Chapter 3
Drought Effect and Adaptation of Farmers in Northeast Thailand

As mentioned above, rice farmers in Northeast Thailand grow ricenot only for commercial use but also for household consumption. When
there is excess rice left over from consumption and it is assured thatthe following year’s rice yield will be sufficient for consumption, they
will decide to sell the remaining rice to the market. Therefore, serious
droughts in Northeast Thailand adversely affect not only households’
incomes but also their food security. According to the surveyed result,drought caused 30.12% of farmers in recognized drought areas to haveinsufficient rice for household consumption. When comparing the
proportion of farmers whose rice yield was insufficient for consumption,
it was found that the drought-prone areas had a higher proportion of
farmers who were affected than in other areas. Farmers in the rainfed
areas had a higher percentage of rice damage than those in irrigatedareas. Regarding farm size, there was the highest proportion of farmers
whose rice production was insufficient for household consumption,although rice production of small farmers was less affected than that oflarge-scale farmers (Figure 3.7).

Figure 3.7 Proportion of sample farmers whose drought problems resulted ininsufficient rice production for household consumption in 2019. Source: (Srisompun
2021)

To solve the problem of insufficient rice production for household
47

Toward Sustainable Agriculture of Rice in Asia

consumption, most farmers decided to buy milled rice from the market,
while others decided to buy rice from other farmers or borrow fromneighbors or other farmers in the village (Figure 3.8). Especially insome villages, there are rice bank projects that provide rice for farmers
who do not have enough rice for household consumption. However,some farmers became worried about the duration of these projects andthought that they would continuously face insufficient rice for household
consumption when these projects ended.

Figure 3.8 Methods for solving the problem of insufficient rice production forhousehold consumption of the sample farmers in 2019. Source: (Srisompun 2021)

The drought affects not only agriculture but also the natural foodsupply. The result from Figure 3.9 shows that drought-prone areas had
the greatest proportion of farmers affected by the decline in natural
food supply. There were 8.13% of farmers who experienced an average
decrease in the value of food at about 394 Thai baht per household per
year. Farmers in irrigated areas had the largest decline in food value.
Meanwhile, small-scale farmers were seriously affected by drought andhad lower yield values than medium- and large-scale farmers. Most of
the small farms are tended by farmers who practice subsistence farming
and do not focus on commercial production.
48

Chapter 3
Drought Effect and Adaptation of Farmers in Northeast Thailand

Figure 3.9 The proportion of farmers and the value of food for household
consumption decreased by the drought problem in 2019. Source: (Srisompun 2021)

Household income significantly varies by farm size. Large-scale
farmers had the highest average household income of 237,645 Thaibaht/year (44.25% of total income is agricultural income) (Table 3.2). In
2019, the impact of the drought resulted in severe damage to rice yields
and a sharp drop in rice farming incomes. Especially in drought-prone
areas, net income from rice cultivation in 2019 decreased by 7,157 Thaibaht per household and lower than income from rice in 2020 by about
14,392 Thai baht per household. As a result, the proportion of income
from the agricultural sector in 2019 of farmers in drought-declared areas(year experiencing drought) decreased from 27.82% to only 20.49%
of total income. In that case, income from non-agricultural sectors has
become an important source of income for farmers. The cultivation ofother crops such as rubber, sugarcane, cassava, and maize are the main
sources of income for most farmers in the study area, especially in areas
where farmers do not suffer from drought or unstable weather. Other
income sources are about 23,000 Thai baht per household on average,
accounting for 10.11–12.90% of total income. However, the income of
farmers was affected not only due to the decrease in rice production but
49

Toward Sustainable Agriculture of Rice in Asia

also due to the decline in the production of other crops, it was foundthat, for example, in 2019, farmers earned an average of only 5,969 Thaibaht per household or 3.87% of their total income. Table 3.2 reflects aclear picture of the impact of drought on household income sources in
the agricultural sector.
Table 3.2 Income and sources of income of sample farmer households for the year
2019-2020 classified by declared drought areas.
Source of household income

Income (Share (%))
Other areas
2019
2020
Agricultural net income
45.51
41.02
- Rice income
19.88
15.69
- Other crops
10.11
12.90
- Livestock/fishery
3.88
1.81
- Other farm incomes
6.30
5.43
- Non-farm income
5.34
5.19
Non-agricultural net income
54.49
58.98
Income from non-agricultural labor (daily) 8.37
7.76
Salary17.27
19.92
Trading/Business/Services/Handicrafts
11.94
11.97
Remittance
11.44
13.24
Government support
3.36
4.23
Other income
2.12
1.86

Declared drought areas
2019
2020
20.49
27.82
-4.64
4.99
3.87
8.88
4.28
0.63
9.18
7.98
7.80
5.35
79.51
72.18
11.45
9.62
27.31
26.59
11.82
8.90
17.43
15.83
5.40
5.56
6.10
5.67

Source: Author

Farmers with large plantations had the highest average householdincome of 237,645 baht per year, with income from agriculture at
44.25% of total income. Farmers with large farms have a lower relianceon non-farm income than small and medium-sized farms, where theproportion of non-farm income is as high as 72.03% and 71.50% of
total income. In addition, when calculating the change in householdincome by comparing the year that farmers experienced severe drought(2019) and the current year (2020), it was found that the source ofincome from the agricultural sector in 2019 was lower than in 2020,
50

Chapter 3
Drought Effect and Adaptation of Farmers in Northeast Thailand

especially income from rice and income from other crops. The decline
in income becomes more serious among small and medium-sized farms
than large farms. Especially, in drought periods, rice income from small
and medium farms decreased by 5,157 Thai baht per year and 6,388
Thai baht per year, respectively. Moreover, small farms accounted for adecrease in remittance income (Figure 3.10).

Figure 3.10 Changes in household income in the year of drought (2019), by farmsize. Source: Author
Note: Change in income = 2019 household income (drought year) – 2020
household income (non-drought problem)

Large and medium farms had the greatest proportion of farmers
whose rice income was reduced by drought (40.12% and 40.06% of
those in the group, respectively). Moreover, the decrease in rice yieldsof large farms in 2019 was less than that of other sized farms, but theprice of rice that farmers received in 2019 was higher than in 2020.
Therefore, farmers with restricted arable land could earn more from ricein 2019 than in 2020, despite the drought. This is because the average
yield was not much different. Despite being offset by higher rice prices,the drought did not affect the average income of large farmers (Figure3.11).
51

Toward Sustainable Agriculture of Rice in Asia

Figure 3.11 Proportion of sample farmers whose household income is affected bydrought. Source: Author(2) The Factors Affecting Farmers’ Adaptation to Drought
Farmers’ ability to adapt and cope with the effects of drought varies
by the resource base, the economic base, and the social characteristics ofthe household. The survey data revealed that the proportion of farmers
in irrigated areas affected by drought had the greatest proportion of
farmers who adapted to drought (Figure 3.12).

Figure 3.12 Proportion of sample farmers adapted to drought problems. Source:
Author52

Chapter 3
Drought Effect and Adaptation of Farmers in Northeast Thailand

Farmers in the study areas also adapted to drought in various
ways, including suspending rice growing, finding additional water
sources (for example, digging ponds, wells, or groundwater), adjusting
the time of planting or slowing the rice sowing. Some others have
reduced the number of rice cultivation areas, adjusted the use of rice
varieties, adjusted the types of crops that are grown instead of rice orturned to keeping livestock instead of growing rice, especially in therainfed area. Some farmers turned to other occupations outside of the
agricultural sector instead during water shortages (for example, hiringfor construction, trading, housework, security, sewing, other handicrafts,
selling food, driving a car, or working as hired labor in the agricultural
sector.) Although a greater proportion of small farmers are affected bydrought, the adaptation ratio of farmers was not different according tofarm size (Figure 3.13).

Figure 3.13 Adaptation pattern to drought problems of farmers in study area.
Source: Author
Note: Adaptation patterns: 1. Search for additional water sources; 2. Stop growing
rice; 3. Adjust the growing period; 4. Reduce the rice area; 5. Adjust the ricecultivars; 6. Cultivate different plants instead of rice; 7. Change to livestock; 8.
Change to other occupations

53

Toward Sustainable Agriculture of Rice in Asia

The estimated results (Table 3.3) using the logistic regression
model revealed that the factors affecting farmers’ decision-making toadapt to drought were statistically significant. They included production
environment (rainwater/irrigation), number of years experiencing
drought, commercial rice cultivation, main income from non-agricultural
sectors, planning to expand the production area in the farm (cultivation/
raising animals), planning for the offspring to inherit agriculture careers
and the number of smartphones in a household.
Table 3.3 Factors affecting to decision-making on drought adaptation of farmers inthe study area.
Variable

Mean Std. Err. Coefficient estimates Marginal effect model
Coef.
Std. Err. Coef.
Std. Err.

Human capital
Sex
0.613
Age
0.470
Natural capital
Dummy of drought declared area 0.578
Production environment
0.182
The number of droughts (2015– 2.250
2020)
Economic capital
Growing rice for commercial
0.564
Main income from non0.223
agricultural sector
Access to agricultural credit
0.595
Social capital
Farming career is stable
0.899
Planning to expand the rice field 0.541
Planning for the children to
0.719
inherit the agricultural career
A member of a farmer’s group
0.879
Number of smartphones
0.250
Constant
Log likelihood = -353.930

0.021
0.021

0.037
-0.322*

0.191
0.191

0.009
-0.079*

0.047
0.047

0.021
0.016
0.045

0.268
0.197
1.342*** 0.297
0.172*
0.089

0.066
0.328***
0.042*

0.048
0.072
0.022

0.021
0.018

0.520*** 0.201
0.646
0.237

0.127***
0.158

0.049
0.058

0.021

0.313

0.195

0.077

0.048

0.013
0.021
0.019

-0.0580.372*-0.186

0.326
0.198
0.225

-0.0140.091*-0.045

0.080
0.048
0.055

0.308
0.034

-0.0210.014
0.261**
0.129-1.040*** 0.402
LR λ 2 = 79.46***-0.0050.064**

0.003
0.032

Source: Author

54

Pseudo R 2 = 0.1044

Chapter 3
Drought Effect and Adaptation of Farmers in Northeast Thailand

4. Conclusion and Policy Implications
The drought situation in Thailand tends to increase in frequency.
In 2019, Thailand experienced its worst drought in four decades.
80% of the farmers affected by drought in 2019 were small farmers.
Rice quality and yield loss caused by drought varied by farm size. On
average, the decline in paddy yields caused by drought ranged from1,757 to 4,661 kg per household (approximately 25,840–50,171 Thaibaht per household). Drought caused 30.12% of farmers in recognizeddrought areas to have insufficient rice available for consumption;accordingly, 8.13% of farmers experienced reduced food sources,
worth 394 Thai baht per household a year. The agricultural incomeof rice farm households in declared drought areas diminished from27.82% to 20.49% of total income. The Northeast region of Thailand isa significant area for quality rice cultivation. Rice is not only the mainhousehold income for small-scale farms, but also an important staple
food for this region’s residents.
To cope with the impacts of drought, farmers in the study areas
performed various adaptation measures including stopping rice growing,
finding additional water sources (for example, digging ponds, wells, orgroundwater), adjusting the time of planting or slowing the rice sowing,
reducing the number of rice cultivation areas, adjusting the use of rice
varieties, adjusting the types of crops that are grown instead of rice, orturned to keeping livestock instead of growing rice, especially in therainfed area. Some farmers decided to turn to other occupations outsideof the agricultural sector instead during water shortages. To mitigate theeffects of drought, the requirements of some projects were consistent
with the demands of farmers. A long-term plan and extensive investment
in drought management are necessary. The drought allocation budget
process should begin with community-based research to be consistent55

Toward Sustainable Agriculture of Rice in Asiawith the needs and conditions of drought problems in each area.

References

Boonmas, S. 2021. Thailand map. <https://www.dreamstime.com/stockillustration-thailand-map-regions-provinces-image47131359>
Consulate General of the People’s Republic of China in Khon Kaen.
2014. Northeastern Thailand: Brief Introduction <http://khonkaen.
china-consulate.org/eng/lqgk/>
Department of Agricultural Extension. 2019. Official Report on“Database of Drought-Affected Areas for Agricultural Purposes inNortheastern Thailand, 2015-2020” (In Thai).
Department of Disaster Prevention and Mitigation. 2020. DroughtAffected Areas Announcement 2022. <http://portal.disaster.go.th/
portal/public/index.do?ms=1691565428721> (In Thai).
Office of Agricultural Economics. 2020. Monthly Agricultural
Commodity Prices. Retrieved from <http://www.oae.go.th/view/1/
ราคาสินค้าเกษตรรายเดือน/TH-TH> (In Thai).
Srisompun, O. 2021. Final Report of the Project “Study on Economics
and Social Effect of Drought and COVID-19 Pandemic on Farmers
in the Northeast Thailand”. National Research Council of Thailand(In Thai).
TMD. 2010. The Climate of Thailand. <https://www.tmd.go.th/info/%E
0%B8%A0%E0%B8%A1%E0%B8%AD%E0%B8%B2%E0%B8%81%E0%B8%B2%E0%B8%A8%E0%B8%82%E0%B8%AD%
E0%B8%87%E0%B8%9B%E0%B8%A3%E0%B8%B0%E0%B9%80%E0%B8%97%E0%B8%A8%E0%B9%84%E0%B8%97%E
0%B8%A2>

56

Chapter 4
Rice Production for Sustainable Agriculture

Chapter 4
Rice Production for Sustainable Agriculture:
Case Studies in Vietnam and Japan
Thanh Tam HO
Abstract: As climate change poses significant challenges to global
food security and safety, strategic policies to mitigate food safety risks
while minimizing environmental impacts in the era of climate change are
becoming more important. Sustainable agriculture is a potential solution forsequestering carbon as climate change mitigation, improving environmental
health and economic performance, as well as satisfying society’s needfor food security. This research reports on two case studies. The first casewill present climate change responses in the Mekong Delta, Vietnam.
To cope with more frequent and serious salinity intrusion and drought,
national policies promote mitigation strategies with the aims of reducing
GHGs emissions and managing resource uses as well as promoting
adaptation strategies as emergent action for farmers to effectively reduceclimate change vulnerability and enhance resilience. Especially, this study
will focus on how these climate change responses could improve theeconomic performance of rice farmers. The second case will introduce thedevelopment of sustainable agriculture, especially sustainable rice in Shiga
Prefecture, where the unique policy of direct payment was the earliest
and most advanced in Japan and has since been popularly adopted at thenational level. The study concludes with policy implications for both cases.

1. Introduction
In the era of climate change, our food security and safety are being
57

Toward Sustainable Agriculture of Rice in Asia

seriously threatened, while at the same time, it is becoming increasingly
challenging to devise strategies to mitigate food safety risks while
minimizing the environmental impacts. Sustainable agriculture can bepart of the solution.
In Vietnam, due to serious droughts and extreme weather
events during 2016–2017, rice production was remarkably reduced.
Meanwhile, in Japan, heavy rains and windy storms caused by five
typhoons and rainy season fronts brought about 126.4 billion Japanese
yen in agricultural damage in 2017 (MAFF 2018). Consequently, riceproduction was also affected in both countries (Figure 4.1).

Figure 4.1 Rice production in Japan and Vietnam during 2013–2019.
Source: Author

In Vietnam, rice is the most important crop, occupying morethan 90% of total grain food. Vietnam is the world’s third major rice
exporter. In 2020, the country exported 6.2 million tons (3.1 billion
USD), accounting for 13.8% of total production. Recently, Japan’s rice58

Chapter 4
Rice Production for Sustainable Agriculture

exports have grown further. 7,640 tons of Japanese rice were exported in2015. In 2020, Japan exported 19,700 tons of rice (47.79 million USD),
accounting for 0.2% of total production (Figure 4.2).

Figure 4.2 Rice exports in Vietnam and Japan. Source: Author

There are several problems in rice production in both Vietnam andJapan. In Vietnam, serious climate change and extreme weather events(i.e., drought, salinity intrusion), the low efficiency of rice farming (i.e.,
overuse of inputs such as fertilizers and chemical uses), and low qualityof rice are the three main concerns. Whilst, in Japan, a decreasing
demand for rice in the domestic market, an aging population, and adecreasing labor force for agricultural sectors are the main constraints.
This study aims to give an overview by measuring the effects of climatechange responses on rice production in Vietnam and a review of thesustainable agriculture and promotion policy of rice in Japan.

2. A Case Study in Vietnam(1) Background
The Mekong Delta in Vietnam is one of the biggest rice production
regions (GSO 2018), contributing 52% of the total rice production of thecountry, ensuring livelihoods for 60% of its regional residents. Also, it is59

Toward Sustainable Agriculture of Rice in Asia

one of the most vulnerable regions to climate change and sea-level risein the world (Yusuf and Francisco 2010). Rice production potential in
Vietnam is forecast to decline by up to 50% by the year 2100. To copewith climate change and its adverse impacts, adaptation and mitigation
are emergent responses to enhance the resilience of the agricultural
sector, protect the livelihood of poor communities, and ensure foodsecurity and the environment. Therefore, it is necessary to investigate
the effects of climate change responses on rice farming in the Mekong
Delta of Vietnam.
(2) Data and Method
1) Data Collection
The cross-section data of 352 rice farmers in the study werecollected from the field survey in three provinces in the Mekong
Delta: Long An, Ben Tre, and Tra Vinh in February 2018. These threeprovinces were purposively selected as the case studies because they
are representative of each group of low, medium, and high levelsof vulnerability to climate change and have intensive rice farming(2-3 cropping seasons per year). In each province, two districts wererandomly selected, and then two communities were chosen from each
district.
2) Research Approach and Method
Decisions in response to climate change depend on a farmers’ability and motivation. In addition, their ability and motivation also
contribute to different farm performances regarding their choices(i.e., self-selection). These could lead to selection bias. Therefore, themultinomial endogenous treatment effect model (Multinomial ETEM)(Deb and Trivedi 2006a; 2006b) is used to estimate the effects of climate
60

Chapter 4
Rice Production for Sustainable Agriculturechange responses on rice farming and the propensity score analysis
for categorical treatment (Inverse Probability Weighting, IPW) (Guoand Fraser 2015) is also used to check the robustness of the estimatedresults.
3) The Effects of Climate Change Responses
According to the surveyed data, 71% of farmers implemented
climate change responses and 29% did not implement any response.
Climate change responses are different across geographical locations(i.e., provinces with different levels of vulnerability to climate change).
Those climate change responses are divided into four main groups: (1)crop management (i.e., changing rice varieties, changing fertilizer andchemical use, or applying integrated pest management (IPM)), (2) water
management, (3) income diversification, and (4) soil conservation (i.e.,
reduce the farming area of rice, soil preparation) (Figure 4.3).

Figure 4.3 Climate change responses by local Vietnamese farmers. Source: Author
Note: SC – Soil conservation package; ID – Income diversification package; WM –Water management package; CM – Crop management package

61

Toward Sustainable Agriculture of Rice in Asia

The key determinant of multiple choices of climate change
responses (i.e., one package, two packages, and three or more packages)
is sources of information on climate change response. Education andfarm size are also found to influence the multiple choices among rice
farmers. Furthermore, geographical locations (i.e., provincial level orvulnerability level and access to water sources) significantly drive thechoice of multiple climate change responses among rice farmers (Table
4.1).
Table 4.1 Determinants of multiple choices of climate change responses.
Covariate
Category 1
Category 2 Category 3 Category 4
Education
0.00 (0.06)-0.22* (0.12) 0.03 (0.06) 0.04 (0.06)
Age
0.01 (0.02)-0.04 (0.03) -0.00 (0.02) -0.02 (0.02)
Information on CC responses 0.83** (0.37) 1.22** (0.72) 0.66* (0.38) 1.21*** (0.38)
Asset-0.00 (0.00)-0.01 (0.01) -0.01 (0.01) -0.00 (0.00)
Farm size
0.09 (0.15)
0.11 (0.27) 0.09 (0.17) 0.28** (0.16)
Region (Low vulnerability)-0.27 (0.42)
0.71 (0.89) -0.89* (0.7) -1.07** (0.49)
Region (Medium vulnerability) -2.02*** (0.50) -0.51 (0.95) -0.39 (0.44) -0.34 (0.45)
Access to water (Near)
1.46** (0.72) 1.06 (1.21) 1.19* (0.70) 0.35 (0.68)
Access to water (Medium)1.54** (071) -0.23 (1.36) 1.12* (0.70) 0.87 (0.67)
Constant-2,09 (1.27)-0.58 (2.22) -1.45 (1.26) -0.72 (1.15)
Likelihood-ratio chi2 (32)187.27
Probability > chi2
0.00
Pseudo R 2
0.08
Observations
90
12
76
71

Note: ***, **, and * represent significant levels at 1%, 5%, and 10% respectively.
Category 1 - A package related to crop management; Category 2 - A package
related to water management, income diversification, or soil conservation; Category
3 - Two packages; Category 4 - Three or more packages. Source: Author

To measure the benefits of climate change responses on the outcomeof rice farming, both the multinomial ETEM and propensity scorematching (i.e., IPW) are applied. The multinomial ETEM shows amore reliable result compared to the IWP estimates. One up to multiple
62Chapter 4
Rice Production for Sustainable Agriculture

packages of climate change coping practices can significantly improverice yield, profitability, and income, and reduce chemical fertilizer use.
A more comprehensive package would not always result in greater
profitability than a less comprehensive package (Table 4.2).
Table 4.2 Effects of categorical climate change responses on outcomes of rice farming.
OutcomeLn Yield
IPW
Multinomial ETEM
Ln Profitability
IPW
Multinomial ETEM
Ln Income
IPW
Multinomial ETEM
Ln Fertilizer use
IPWMultinomial ETEM

Category 1

Category 2

Category 3

Category 4

0.22*** (0.04) 0.20*** (0.06) 0.22*** (0.05) 0.22*** (0.05)
0.13*** (0.03) 0.11*** (0.05) 0.13*** (0.03) 0.15*** (0.03)
0.46*** (0.11) 0.46** (0.15)
0.14*** (0.04) 0.11* (0.06)

0.50*** (0.12) 0.38*** (0.12)
0.14*** (0.04) 0.14** (0.04)

0.72*** (0.16) 1.50*** (0.15) 0.80*** (0.18) 0.99*** (0.17)
0.19*** (0.05) 0.25*** (0.08) 0.23*** (0.05) 0.26*** (0.05)-0.18*** (0.07) 0.12 (0.15)-0.07*** (0.01) 0.00 (0.02)-0.22*** (0.07) 0.00 (0.01)-0.08*** (0.01) -0.01 (0.01)

Note: ***, **, and * represent significant levels at 1%, 5%, and 10% respectively.
Category 1 - A package related to crop management; Category 2 - A package
related to water management, income diversification, or soil conservation; Category
3 - Two packages; Category 4 - Three or more packages. Source: Author

3. A Case Study in Japan(1) Background
Japan is one of the world’s top five greenhouse gas (GHG) emitters,with nearly 1,200 million tons of CO2 equivalent in 2019. Especially,
GHG emissions from agriculture are the third largest contributor to
global warming in Japan (47.44 million tons of CO2), behind the energy
and industrial sector. In 2019, the largest source of CH4 emissions was
63Toward Sustainable Agriculture of Rice in Asia

rice cultivation, accounting for 46.2%. Japan is the third largest fertilizer
user with nearly 232 kg per ha in 2017 and the second largest pesticideuser, with around 11.85 kg per ha in 2014. The overuse of chemicalfertilizers and pesticides for a long time has resulted in polluting the air,water, and soil.
(2) A Review of Sustainable Agriculture and Promotion Policy
The Japanese government has recognized its responsibility toaddress agri-environmental issues in its domestic agricultural policy.
The importance of biodiversity in Japanese rural areas, including
paddy fields, has recently attracted more attention. Figure 4.4 shows
the historical data of agricultural policies which promote sustainableagriculture involving environmentally friendly agriculture and organic
agriculture.
1992

1999

2005

The
The New
The Basic
Direction for Agricultural
Plan for
New Policy
Basic ActFood,for Food ,&Agriculture,
Agriculture, Three Acts
and Ruraland Ruralon AgriAreas (TheAreas
environment Basic Plan)

2006

2007

2010

2011

2014

Measure to
The Basic
The Act onConserve
Plan for
Basic Policy
The National
theand Improve
Food,
on
DirectPromotion Land, Water, Agriculture,
Promotion
Paymentof Organic
andand Ruralof Organic
ProgramAgriculture Environment
Areas
Agriculture(MCILWE)(Updated)

2015

2020

The Basic
The Basic
Plan forPlan for
Food,
Food,
Agriculture, Agriculture,
and Ruraland Rural
Areas
Areas
(Updated)(Updated)

Figure 4.4 Government policy regarding sustainable agriculture in Japan.
Source: Author

The term “environmentally friendly agriculture” was mentioned forthe first time in The Direction for New Policy for Food, Agriculture,
and Rural Areas by the Ministry of Agriculture, Forestry and Fisheries(MAFF) in June 1992. This policy document was the starting point for
the renewal of the Agriculture Basic Act.
64

Chapter 4
Rice Production for Sustainable Agriculture

Measures for sustainable agriculture during this phase were thedissemination of environmentally friendly farming practices to farmers,
and the promotion of farmers’ awareness of the environment. Since
1999, the Food, Agriculture, and Rural Areas Basic Act and the Three
Acts on Agri-environment have been enacted and seriously focused on
promotion and development.
In 2005, MAFF released a five-year plan, namely the Basic Plan
for Food, Agriculture and Rural Areas (or the New Basic Plan). The
Good Agricultural Practices Harmonious with Environment Plan was
also introduced in the same year. After this, the Act on the Promotion ofOrganic Agriculture was enacted in 2006.
The Measures to Conserve and Improve Land, Water, andEnvironment plan which started in 2007, is known as a subsidy
program. Under this subsidy program, action groups receive financial
aid for collaborative action to maintain and improve farmland and water
resources and for farming activities reducing chemical inputs.
In the Basic Policy for Promotion of Organic Agriculture enacted
in 2014, the main goal is to double the percentage of agricultural land
devoted to organic farming to 1.0% by FY2018.
(3) Shiga Prefecture and Promotion Policies for Sustainable
Agriculture
Lake Biwa, which occupies one-sixth of the entire area of Shiga
Prefecture, is the largest lake in Japan. Lake Biwa was seriously
polluted due to population growth and industrial developments in the
1960s. Also, the extensive use of pesticides and chemical fertilizers in
the agricultural sector was another cause of the water pollution in thelake. Especially, eutrophication spread in the 1970s. In 1977, Lake Biwa
experienced a large-scale freshwater red tide for the first time and such
65

Toward Sustainable Agriculture of Rice in Asia

outbreaks continued up to the 1990s. Recently, however, the number ofdays during which red tides occur and affected areas have decreased.
Blue-green algae first appeared in Lake Biwa in 1983 and has continued
to appear almost every year since then.
Perceiving the importance of Lake Biwa as a water source andfor its biodiversity, the Shiga government has enacted several laws,
regulations, and policies to protect biodiversity and the environment,
especially in water preservation, agriculture, and forestry conservation.
The details are described as follows:• 1979: Ordinance for Eutrophication Prevention in Lake Biwa
• 1980: Clean and Recycling Agriculture• 1984: Landscape Preservation Ordinance• 1985: Special Law for Preserving Lake Water• 1987: Lake Water Quality Conservation Plan
• 1990: Master Plan for Environmental Management of Yodo
River System• 1992: Reed Colony Conservation Ordinance• 2001: Shiga’s Vision for Agriculture and Forestry, especially
Environmentally Friendly Agriculture (EFA)• 2002: Lake Biwa Sport Activities Control Ordinance• 2003: Shiga Prefecture Ordinance Promoting Environmentally
Friendly Agriculture• 2004: Shiga Agri-environmental Direct Payment Scheme• 2007: MCILWE (developed by MAFF) and Development of thePlan for Conservation of the Lake Water Quality in Lake Biwa,
Fifth Period• 2011: The National Policy on Direct Payment Program (MAFF)
and The Lake Biwa Comprehensive Conservation Plan (MotherLake 21 Plan) were revised• 2012: Development of the Plan for Conservation of the Lake
66

Chapter 4
Rice Production for Sustainable Agriculture

Water Quality in Lake Biwa, Sixth Period• 2015: Development of the Plan for Conservation of the Lake
Water Quality in Lake Biwa, Seventh Period• 2017: Development of the Plan for the Lake Biwa Conservation
and Regeneration Measures• 2021: Shiga Prefecture Basic Plan for Agriculture and Fisheries
Based on the definition of sustainable agriculture from thegovernment, Shiga Prefecture set up cultivation standards forenvironmentally friendly agriculture, which include:(i) The amount of chemically synthesized pesticides used isless than half of the normal amount, and the total number ofingredients is seven or less.
(ii) The amount of chemical fertilizer (nitrogen component) is lessthan half of the normal amount, 4kg/10a or less.
(iii) Adopted environmentally friendly cultivation techniques for
Lake Biwa.
(iv) A record is kept of how it was cultivated.
The “Fish Cradle Rice Paddies Project” and Shiga’s Vision for
Agriculture and Forestry, especially Environmentally Friendly
Agriculture (EFA) have been implemented in Shiga since 2001.
Although rice-fish farming, a traditional practice for more than 170
years in Japan, has been declining, it has recently received renewedinterest for its potential as a sustainable agricultural practice. Farmers
enrolling in this project must comply with several conditions including
the use of pesticides that result in the lowest level of fish toxicity andspecific water management to maintain fish habitats. Furthermore,
the Shiga government established the Ordinance for Promotion ofEnvironmentally Friendly Agriculture in March 2003 to proactively
promote “environmentally friendly agriculture” which aims to reduce
the pollution load to Lake Biwa, conserve its biodiversity, and provide
67

Toward Sustainable Agriculture of Rice in Asia

consumers with safe and reliable agricultural products. As early as
2004, Shiga Prefecture started an agri-environmental policy, namely theEnvironmentally Friendly Agriculture Direct Payment Scheme whichis the most advanced policy with the aim of Lake Biwa conservation.
This unique policy by Shiga Prefecture was adopted at the national level
by Measures to Conserve and Improve Land, Water, and Environment(2007–2011) and has developed into the National Direct Payment
Scheme since 2011.
In Japan, Shiga has the largest amount of EFA cultivated area, about
33%. Especially, the total of EFA rice in Shiga is nearly 13,000 ha,
occupying about 44% of the total cultivated area of rice (nearly 30,000ha), and nearly 90% of total EFA farming in Shiga (total of EFA: 14,057ha) (Figure 4.5).

Figure 4.5 Change in the cultivated area of EFA and key policies in Shiga.
Source: (Shiga Prefectural Government Report 2022)

68

Chapter 4
Rice Production for Sustainable Agriculture(4) Environmentally Friendly Agriculture (EFA) andDirect Payment Subsidy Policy in Shiga Prefecture
According to the report from MAFF (2019), EFA significantly
reduces approximately 143,393 tons of CO 2 equivalent per year.
Combining multiple practices simultaneously with organic agriculture
cropping systems is increasingly common to achieve economic andenvironmental viability such as suppressing weeds, pests, and diseasepressure; meeting crop nutrient demands; and optimizing overall crop
productivity. Table 4.3 shows the main EFA farming methods in Shiga
Prefecture and the direct payment subsidy for each farming method.
Table 4.3 Direct payment subsidy for EFA farming methods
Activities

Direct payment Cult ivated Reduction amount ofsubsidy (J PY/ area (ha)GHG emissions perha)unit (ton CO2/ha/year)
IPM practice, manual weeding on
40,0005,996
3.87
ridges and long-term integrated pest
management
Use of slow-release fertilizer and40,0005,005
2.19
long-term mid-drying
Applying compost
44,000697
2.26
Organic farming
30,000–120,000346
0.93
Ecosystem-friendly weed management
40,000243
Planting cover crops
60,000181
1.77
Fish cradle paddy rice
30,000148
No pesticide or chemical fertilizer use
60,000122
Living mulch
32,000–54,000
67
1.02
Others170
Total
12,987

Source: (MAFF 2020) and (Shiga Prefectural Government Report 2022)

According to surveyed data, here is a brief comparison of the
profitability between EFA rice and conventional rice. EFA rice has ahigher profitability at 15,400 Japanese yen/ha (≈102.4 USD/ha) which
includes the direct payment subsidy amount, but it becomes unprofitable69

Toward Sustainable Agriculture of Rice in Asia

when the labor cost (i.e., both hired and family labor) is included (Table
4.4).
Table 4.4 An example of cost and benefit of EFA rice, Shiga Japan.
Item
Environmental-friendly rice Conventional rice
Average yield (ton/ha)
5,000.95
5,000.98
Selling price (JPY/60kg)
10,70010,400
Sale (JPY/ha)
891,670866,670
Direct payment subsidy (JPY/ha)
40,0000Total income (JPY/ha)
931,670866,670
Labor (man-hours)
124
21
Seeds and seedlings cost (JPY/ha)
164,434
164,434
Fertilizer cost (JPY/ha)
112,000
62,400Agricultural chemical cost (JPY/ha)
28,80028,800Herbicide cost (JPY/ha)
25,00025,000
Cost for using drying facility (JPY/ha) 145,660
145,660
Total cost (JPY/ha)
475,800
426,200
Profitability (JPY/ha)
455,870
440,470

Source: (Shiga Prefectural Government Report 2022)

According to the Shiga Prefecture Report and the present study’s
survey (2022), Shiga rice farmers have a high awareness of sustainableagriculture. Their motivations for implementing sustainable agriculture
are to protect Lake Biwa, add to the value of rice on the market,
and produce safe products. However, there are several challenges
to developing sustainable agriculture, especially for sustainable riceproduction: (1) It is time- and labor-consuming, (2) profitability is
low if the labor cost is included, and (3) there is an aging agricultural
population and shortage of labor force in the agricultural sector.

4. Conclusion
Climate change and coping strategies are emerging concerns inagriculture, especially in developing countries. In Vietnam, climate
70

Chapter 4
Rice Production for Sustainable Agriculturechange responses are beneficial for rice farmers in avoiding losses ofyield, improving profitability and income, and reducing fertilizer use.
There is a need to improve rice quality (i.e., rice variety, safety) andits stability. Sustainable agricultural practices with certification are
still limited in Vietnam. Also, there is a need to design an appropriate
policies to promote sustainable agriculture, especially rice.
In Japan, current agricultural policies effectively promote sustainableagriculture and add to the value of Japanese rice. Nevertheless, newchallenges may arise from the situation of depopulation and aging
in rural communities, a decline in the total area of cultivated rice, ashortage of labor, and a decline in rice consumption due to changes in
dietary habits. Therefore, policies for promoting sustainable agriculture
should pay attention to the public concern over the economic impacts
on the quality of the global commons. In order to make agriculture
sustainable smart agriculture should be considered to assist in solving
the problem of the shrinking labor force and improving efficiency. In
addition, adopted policies should include conversion to other strategic
crops such as wheat, soybeans, rice for processing, and also keeping
livestock. Moreover, innovations and technologies developed in Japansuch as digital tools and pest management should be considered forcountries facing the same challenges, especially developing countries
like Vietnam.

References

Deb, P. and P. K. Trivedi. 2006a. Maximum Simulated Likelihood
Estimation of a Negative Binomial Regression Model with
Multinomial Endogenous Treatment. The Stata Journal, 6(2), pp.
246–255.
71

Toward Sustainable Agriculture of Rice in Asia———. 2006b. Specification and Simulated Likelihood Estimationof a Non-Normal Treatment-outcome Model with Selection:
Application to Health Care Utilization. The Econometrics Journal,
9(2), pp. 307–331.
GSO. 2018. Social and Economic Situation in 2017. Vietnamese
General Statistics Office. <https://www.gso.gov.vn/en/data-andstatistics/2019/10/report-social-and-economic-situations-in-2017/>
Guo, S., and M. W. Fraser. 2015. Propensity Score Analysis: Statistical
Methods and Applications (Advanced Quantitative Techniques in
the Social Sciences). Los Angeles, CA.: SAGE Publications, Inc.
Ministry of Agriculture, Forestry, and Fisheries (MAFF). 2018. FY2017
Summary of the Annual Report on Food, Agriculture and Rural
Areas in Japan. <https://www.maff.go.jp/e/data/publish/attach/pdf/
index-93.pdf>———. 2019. Direct Payments for Environmentally Friendly
Agriculture. <https://www.maff.go.jp/e/policies/env/sustainagri/
directpay.html>———. 2020. Statistics. <https://www.maff.go.jp/e/data/stat/index.
html>
Nishizawa, E. 2015. Agri-environmental Policies of Japan and Shiga
Prefecture. Journal of International Economic Studies, 29, pp.
23–34.
Shiga Prefectural Government Report. 2022. Chapter 3-12 Environmentallyfriendly Agriculture. <https://www.pref.shiga.lg.jp/file/attachment/
45609.pdf>
Yusuf, A. A., and H. Francisco. 2010. Climate Change Vulnerability
Mapping in Southeast Asia. Laguna, Philippines: Economy andEnvironment Program for Southeast Asia (EEPSEA).

72

Chapter 5
The Effect of Risk Preference and Farmer Perception on Climate Change to
Farmer Participation on Farm Insurances

Chapter 5
The Effect of Risk Preference and Farmer
Perception on Climate Change to Farmer
Participation on Farm Insurances
Mohammad RONDHI, Suci Virgianti DIANI,
Rizky YANUARTI
Abstract: Agricultural farming is one of the most vulnerable sectors inIndonesia since weather, pests, diseases, and other factors may directly
affect crop yield. Since 2015, the national policy for climate change
adaptation has provided agricultural insurance for rice farmers. This
study aims to explore how farmers perceive the impacts of climatechange on rice farming and investigate factors influencing farmer’s
participation in the national insurance scheme. Logistic regression andpropensity score matching (PSM) were used to analyze the factors
influencing participation in farm insurance and the impact of farminsurance on farmer income. The results revealed that risk preference,
age, and education have positive effects on farmers’ willingness toparticipate in farm insurance, while land ownership has a negative
effect on it. Furthermore, farmers’ incomes were significantly different
between national insurance participants and non-participants. Finally,
it is concluded that the national insurance program is important for rice
farmers in medium and high-risk areas.

1. Introduction
Agricultural farming is a risky business since weather, pests,
73

Toward Sustainable Agriculture of Rice in Asia

diseases, and other factors may directly affect crop yields (Cline 2007;
Nordhaus 1991). Rice is one of the staple foods in Indonesia which
relies on the climate conditions. Changes in rainfall intensity andfrequency can cause extreme weather such as floods and droughts which
also affect irrigation water availability and adequacy. Accordingly,
adverse weather causes production loss (Surmaini et al. 2011).
The impact of adverse climate change (CC) on farming isdetermined by the vulnerability of farmers which has three interrelated
functions: exposure to hazard, sensitivity to damage, and ability tocope (IPCC 2014). One of the ways to reduce the impact of CC is bypromoting adaptive strategies (Jamshidi et al. 2019). Some studies
justify that farm adaptation to CC in farm practices can reduce farm
losses (Khanal et al. 2018). Adaptation can be classified as autonomous
adaptation, and planned adaptation (Stage 2010). While in autonomous
adaptation farmers practice adaptation strategies based on theirknowledge independently, in planned adaptation, the government plays
an important role in planning and implementing an adaptation policy.
One of the adaptation policies run by the government is farminsurance. Since 2015, the Indonesian government has actively
supported the implementation of national agricultural insurance,
locally called Asuransi Usaha Tani Padi (AUTP), especially for paddy
farming. The insurance provides subsidies for rice farmers with 80%
premium payment while the rest is paid independently by the farmers
themselves. However, from 2015 to 2018 the number of farmers
participating in farming insurance is still low, only 3–4% (Table 5.1).
Although the percentage seems to be increasing, it is still low comparedto other sectors and other countries. This research aimed to find out
the reason why farmers’ participation is low and to find an alternative
solution.

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Chapter 5
The Effect of Risk Preference and Farmer Perception on Climate Change to
Farmer Participation on Farm Insurances
Table 5.1 Paddy rice area in Indonesia based on participating in agricultural
insurance.
Year
2015
2016
2017
2018
Total

Paddy Area (Ha) Registered Area (Ha)14,116,638
233,500
15,156,166
307,217
15,712,015
997,961
15,994,512
806,199.64
60,979,331
2,344,877.64

Percentage (%)
1.65
2.02
6.58
5.04
3.82

Source: Ministry of Agriculture, Indonesia, 2018.

2. Rice Farming, National Policy, and Farmer’s
Perception
In Indonesia, rice productivity varies from area to area and year toyear. On average, rice productivity in Indonesia was around 5 tons per
ha in 2015, decreasing in 2016–2017, and slightly increasing in 2018.
Therefore, there are some hypotheses that rice productivity may dependon areas, environmental factors such as climate change, and input uses
as macro conditions. Rice productivity in Java is higher than outside ofJava. Especially, rice productivity in Java and Sulawesi is higher thanin other areas due to better agricultural infrastructures for irrigation.
Meanwhile, Sumatra and Kalimantan have low rice productivity due
to many areas being used for plantation crops (i.e., palm oil trees, andforestry).
In addition, most farmers in Indonesia manage their own land (70%),
while others are renting (18%), and sharecropping (10%) (Table 5.2).
Sharecropping is high in some areas such as Sumatra and Java while
it is low in some other areas such as Maluku and Papua. The question“How do they manage their farming?” was raised. The answer is thatit mainly depends on ownership. It means that farmers who have theirown land can access and manage their farms easily, but for farmers who
75

Toward Sustainable Agriculture of Rice in Asia

are leasing or sharecropping, it still depends on their location.
Table 5.2 Land management and sharecropping.
RegionSumatraJava
Kalimantan
Sulawesi
Bali & Nusa
Tenggara
MalukuPapua
Indonesia

Own
14,452 (23.39%)
24,708 (39.99%)
6,646 (10.76%)
7,535 (12.20%)

Lease
5,826 (36.90%)
4,976 (31.52%)
1,243 (7.87%)
1,414 (8.96%)

Sharecropping
3,101 (33.16%)
3,319 (35.49%)
829 (8.87%)
676 (7.23%)

Ratio
2
3
4
4

7,064 (11.43%)

2,222 (14.07%)

1,270 (13.58%)

3747 (1.21%)632 (1.02%)
61,784 (70.75%)

72 (0.46%)
35 (0.22%)
45,788 (18.08%)

57 (0.61%)
99 (10.6%)
9,351 (10.71%)

6
5
3

Source: Statistics Indonesia (BPS), 2014.

In Indonesia, the non-irrigated area is around 55%, higher than theirrigated area of 45%. The percentage of irrigated land in Java is higher
than outside of Java (Table 5.3).
Table 5.3 Share of cultivated land in Indonesia.
RegionNon-irrigated land
Sumatra13,674 (28.61%)
Java
16,466 (34.45%)
Kalimantan
3,212 (6.72%)
Sulawesi
8,757 (18.32%)
Bali & Nusa Tenggara
4,988 (10.44%)
Maluku226 (0.47%)
Papua
477 (1%)Indonesia
47,800 (54.73%)

Irrigated land
9,791 (24.77%)
16,720 (42.30%)
8,776 (14.08%)905 (2.29%)
5,608 (14.19%)
651 (1.65%)
291 (0.74%)
39,530 (45.27%)

Ratio
13
9
5
96
8
3
16
12

Source: Statistics Indonesia (BPS), 2018.

(1) The Strategic Goals and Targets of RAN-API
Indonesia is one of the agricultural countries most vulnerable to76

Chapter 5
The Effect of Risk Preference and Farmer Perception on Climate Change to
Farmer Participation on Farm Insurances

climate change and its impacts. To mitigate the negative impacts ofclimate change, the Government of Indonesia has formulated a national
action strategy plan, namely the Nation Action Plan for Climate Change
Adaptation (RAN-API). The existence of seven main programs supports
these strategies, including: 1) Adapting the food production system toclimate change, 2) Expanding the area of food production, 3) Improving
and developing climate-proof agricultural infrastructure, 4) Food
diversification, 5) Developing innovative and adaptive technologies, 6)
Developing information and communication systems (for climate andtechnology), 7) Establishing supporting programs. Some areas received
government subsidies.

Figure 5.1 The strategic goals and targets of RAN-API. Source: (BAPPENAS)

More specifically, since 2015, the Indonesian government has
implemented a national agricultural insurance scheme locally called77Toward Sustainable Agriculture of Rice in Asia

Asuransi Usaha Tani Padi (AUTP), especially for paddy farming. The
insurance scheme as a financial instrument provides subsidies that will
help farmers who experience crop failure owing to climate change toenhance their capacity and continue their farming activities. The farmers
only need to pay 20% of the insurance premium of Rp 200,000 or
US$13 per ha. It is quite a small amount of money when compared torice productivity and profit. The rest, 80% of the insurance premium,
will be subsidized by the government. When crop failures caused byclimate change occur, the insurance payment is about one-third of total
productivity and nearly US$700. It is much higher than the insurance cost.
Regarding climate change perceptions, farmer’s perception was
identified to be influenced by demographic, institutional, environmental,
and psychological/social factors. Environmental factors seem to be
macro-conditions, while demographic and psychological factors canbe maintained and depend on environmental and institutional factors.
Therefore, the perceived impact of climate change can increaseautonomous adaptation and affect adaptation outcomes (Rondhi et al.
2019). When the way to adapt to climate change is correct, the benefits
for rice production will come. However, incorrect ways of adapting
to climate change (or maladaptation) can lead to a decline in riceproduction.

Figure 5.2 Climate risk perception. Source: Author
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Chapter 5
The Effect of Risk Preference and Farmer Perception on Climate Change to
Farmer Participation on Farm Insurances(2) Research Site and Method
The study was conducted in Jember District, East Java, Indonesia,
through interviews with 87 rice farmers. The study uses the logistic
model to identify farmers’ perceptions and influencing factors. The
regression model is expressed as follows:

Where Y i presents AUTP participation (1 = participation, 0
otherwise), X1 – risk preference, X2 – age of rice farmers (years), X3 –total area (ha), X4 – education (years), X5 – family members (persons),
D 1 – farmer perception (Dummy variable with 1 = 51-100%, 0 =0-50%), and D2 – land ownership (Dummy variable with 0 = own, 1 =not own). Furthermore, propensity score matching (PSM) was applied
to explain the impact of farmer’s participation in farm insurance on farmincome.

3. Results and Discussion(1) Perceived Impact of Climate Change on Rice Farming inIndonesia
Climate change and its impacts in the study are related to drought,
flood, and pest attacks. Figure 5.3 shows that farmers in some areas (i.e.,West Kalimantan) perceived a high impact of climate change where
drought is dominant compared to others. Meanwhile, farmers in someother areas (i.e., Java) perceived the low impact of climate change,
where flooding is more predominant than droughts and pest attacks.
Farmers in west Borneo Island (West Kalimantan) and Riau Island
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Toward Sustainable Agriculture of Rice in Asia

perceive a higher impact of drought than others. East Kalimantan andSouth Sumatra provinces face a higher flood risk than others. On theother hand, rainfall and pest attacks occurred in all provinces at low
levels.

Figure 5.3 The percentage of farmers perceived the impacts of climate change inIndonesia. Source: Author

As mentioned above, for risk preference, this study divides risk
preference into risk-averse farmers (who avoid risks and have a low-risk
tolerance) and risk-takers (farmers who are more willing to take risks).
The average age of surveyed rice farmers is 50 years old. Most of therice farmers surveyed have attended mainly elementary school (37%)
and senior high school (29%). The average number of family members
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Chapter 5
The Effect of Risk Preference and Farmer Perception on Climate Change to
Farmer Participation on Farm Insurances

is around four people. Regarding the perception of CC, more than 70%
of farmers perceived the impacts of CC. The majority of farmers (73%)
cultivate rice in their own land (Table 5.4).
Table 5.4 Descriptive statistic.
Variable
Risk preference (X1)
Risk averse
Risk takerAge (year)
Area (ha)Education (X4)
Not primary
Elementary
Junior high school
Senior high school
University/academy
Family member (X5)
Perceptions (D1)
Yield decreasing 1–50%
Yield decreasing 51–100%
Land ownership (D2)
Own
Rent/share

Average (frequency)
71
16
50
0.1–0.5
6
37
11
29
4
4
16
71
73
14

Source: Field Survey, 2020.

(2) Factors Affecting Farmer’s Participation in AUTP Insurance
The results from Table 5.5 show that risk preference has a positive
significance on participation in a farming insurance scheme. Thismeans that risk-taking farmers have low participation, while riskaverse farmers tend to participate in insurance. In some areas with highimpacts of climate change, farmers also tend to participate in insurance.
In addition, there is a positive relationship between farmers’ ages and81

Toward Sustainable Agriculture of Rice in Asia

their participation in AUTP insurance. This means that an increase in
the age of rice farmers can increase the probability of participatingin the national insurance of the Indonesian government. It shows thesame trend as for the education variable. It means that education canalso facilitate participation in national insurance schemes. Importantly,
the variable of land ownership has a negative impact on insurance
participation. This means farmers renting land or sharecropping are lesslikely to participate in farming insurance, while farmers owning land are
more likely to participate in a farming insurance scheme.
Table 5.5 Result of logistic model.
Variable
Risk preference (X1)
Age (X 2)
Area (X3)
Education (X4)
Family member (X5)
Perceptions (D1)Land ownership (D2)Constant

B
0.640
0.079
-0.2330.181
0.120-1.205-2.010-4.955

S,E,
0.208
0.027
0.645
0.079
0.224
0.928
0.779
1.801

Wald
9.468
8.679
0.131
5.260
0.286
1.684
6.664
7.566

Df
1
1
1
1
1
1
1
1

Sig,
0.002**
0.003**
0.717
0.022**
0.592
0.194
0.010**
0.006

Exp(B)
1.897
1.082
0.792
1.198
1.127
0.300
0.134
0.007

Source: Field Survey, 2020.

(3) Discussion
Risk-averse farmers tend to participate in farm insurance, especially
farmers whose plots are in areas affected by climate change risks suchas pest attacks and flooding. The government has a specific programfor each area in Indonesia due to the specific characteristics of theenvironment in each respective area. Generally speaking, this finding
supports previous research (Vassalos and Li 2016; Rondhi et al. 2019).
Farmers who have experienced farm failure tend to be risk averse andtend to participate in farm insurance.
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Chapter 5
The Effect of Risk Preference and Farmer Perception on Climate Change to
Farmer Participation on Farm Insurances

Land-owning farmers tend to participate in farm insurance, as they
have full access to the management of their land, while land-sharing
farmers or land-renting farmers do not have much access to land. Hence,
they are less likely to participate in farm insurance. Land-sharing or
land-renting farmers perceive that an insurance claim will be paid after
they harvest the crop, and at that time, the farmer does not have the rightto manage the plot. Therefore, those farmers prefer not to participate infarm insurance.
There is a difference in income between AUTP and non-AUTP
farmers by Rp 895,052. The result shows that AUTP farmers receive
more income (Rp 6,956,096) than non-AUTP farmers (Rp 6,061,044).
Those farmers manage their farms as recommended by good practices(GAP). Moreover, AUTP farmers receive insurance claims for farm
failures. The ease of making claims due to farm failure raises farmers’
eagerness to participate in farm insurance.

4. Conclusion
This study attempted to find out the factors influencing rice farmers’
decisions on insurance participation in Jember District, East Javaof Indonesia. The national insurance program can partially enhance
farmers’ adaptation capacity to climate change to ensure their livelihood.
However, actual participation in insurance schemes is still low among
rice farmers.
The findings indicate that farmer determinants to participating in
AUTP insurance are risk preference, age, education, and land ownership,
while farmers’ perceptions and the number of family members do notaffect their participation. Risk-averse farmers and land-owning farmers
tend to participate in farm insurance. Importantly, the AUTP program
should be addressed to rice farmers in medium and high-risk areas.
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Toward Sustainable Agriculture of Rice in Asia

References

BPS-Statistics Indonesia. 2018. Statistical Yearbook of Indonesia. SubDirectorate Compilation and Publication (ed.). Jakarta, Indonesia:
BPS-Statistics Indonesia. ISBN 0126-2912.
———. 2014. Rice Farm Household Survey (Survei Usahatani
Tanaman Padi).
Cline, W. R. 2007. Global Warming and Agriculture: Impact Estimatesby Country. Washington, DC: Center for Global Development &Peterson Institute for International Economics. ISBN 978-0-88132403-7.
Fahad, S. and J. Wang. 2018. Farmers’ Risk Perception, Vulnerability,
and Adaptation to Climate Change in Rural Pakistan. Land Use
Policy, 79, pp. 301–309.
IPCC. 2014. Climate Change 2014: Impacts, Adaptation, andVulnerability. Part A: Global and Sectoral Aspects. New York:
IPCC. <http://wedocs.unep.org/handle/20.500.11822/19908>(accessed on 30 March 2019).
Jamshidi, O., A. Asadi, K. Kalantari, H. Azadi, and J. Scheffran. 2019.
Vulnerability to Climate Change of Smallholder Farmers in the
Hamadan Province, Iran. Climate Risk Management, 23, pp. 146–
159.
Khanal, U., C. Wilson, V. N. Hoang, and B. Lee. 2018. Farmers’
Adaptation to Climate Change, Its Determinants and Impacts on
Rice Yield in Nepal. Ecological Economics, 144, pp. 139–147.
Mase, A. S., B. M. Gramig, and L. S. Prokopy. 2017. Climate Change
Beliefs, Risk Perceptions, and Adaptation Behavior among
Midwestern U.S. Crop Farmers. Climate Risk Management, 15, pp.
8–17.
Ministry of Agriculture. 2018. Agricultural Statistics. A. A. Susanti,
and B. Waryanto (eds.). Jakarta, Indonesia: Center for Agricultural
84

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The Effect of Risk Preference and Farmer Perception on Climate Change to
Farmer Participation on Farm Insurances

Data and Information System (Ministry of Agriculture). ISBN
9798958659
Ministry of National Development Planning/National Development
Planning Agency (BAPPENAS). 2012. National Action Plan for
Climate Change Adaptation (RAN-API), p. 57.
Rondhi, M., A. F. Khasan, Y. Mori, and T. Kondo. 2019. Assessing
the Role of the Perceived Impact of Climate Change on National
Adaptation Policy: The Case of Rice Farming in Indonesia. Land,
8(5), p. 81.
Nordhaus, W. D. 1991. To Slow or Not to Slow: The Economics of The
Greenhouse Effect. The Economic Journal, 101(407), pp. 920–937.
Stage, J. 2010. Economic Valuation of Climate Change Adaptation.
Annals of the New York Academy of Sciences, 1185, pp. 150–163.
Surmaini, E., E. Runtunuwu, and I. Las. 2011. Upaya sektor Pertaniandalam Menghadapi Perubahan Iklim (Efforts of Agricultural
Sector in Dealing with Climate Change). Jurnal Penelitian dan
Pengembangan Pertanian, 30, pp. 1–7. (In Indonesian).
Vassalos, M. and Y. Li. 2016. Assessing the Impact of Fresh Vegetable
Growers’ Risk Aversion Levels and Risk Preferences on the
Probability of Adopting Marketing Contracts: A BayesianApproach. International Food and Agribusiness Management
Review, 19(1), pp. 25–42. <https://www. ifama.org> (accessed on
15 October 2018).

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Chapter 6
From Science to Policy: Sustainable Rice
Production in the Mekong Delta, Vietnam
Melanie CONNOR
Abstract: Over the last decades, Vietnam has benefited from a rapid
intensification of rice production that has led to environmental
degradation and adverse health effects. As a result, complex sustainable
rice farming packages such as the national program “One Must Do, Five
Reductions” (1M5R) have been introduced, but adoption still appears
to be low. The technology package includes the reduction of fertilizers,
pesticides, post-harvest losses, water use, and seed rates. An additional
requirement is the use of certified seeds. This chapter will cover the
diffusion and adoption process and will specifically focus on adoption
constraints, and how they can affect policy outcomes and adaptations.
The chapter will highlight the outcomes from various policy-supported
initiatives and unpack plausible pathways that generated the widespread
adoption of 1M5R in different provinces.

1. Introduction
There are a lot of different ways that we engage knowledge ofscience with policy. There is a great deal of literature in different modes
explaining how policymakers use that scientific knowledge to create
various interdisciplinary themes, not only in economics. In this chapter
I would like to discuss the “Knowledge supply mode.” (Figure 6.1)

86

Chapter 6
From Science to Policy

Figure 6.1 Engaging evidence with policy. Source: Author

At the International Rice Research Institute, we provide a lot of
information to policymakers and expect them to use that knowledge
to make new policies. For instance, how will this knowledge influence
farmers to implement that policy and change their behavior? As a
psychologist, I am interested in studying farmers’ behavior, behavioral
change, and how behavior affects their decision-making.
What we need to have to make effective policy is useable evidence.
Here I would like to show you some case studies in the past seven years
87Toward Sustainable Agriculture of Rice in Asiawith the Closing Rice Yield Gaps in Asia with Reduced Environmental
Footprint Project (CORIGAP) (Figure 6.2). CORIGAP aims to improve
food security and gender equity, and to alleviate poverty by optimizing
yield and sustainable rice production in China, Myanmar, Thailand,
Indonesia, Sri Lanka, and Vietnam. Especially, the CORIGAP programaims to explore how to: (a) Reduce yield gaps with the aim to strengthen
future food security and (b) Increase environmentally sustainable riceproduction in intensive lowland systems.

Figure 6.2 CORIGAP Sites. Source: https://ricetoday.irri.org/wp-content/
uploads/2017/02/CORIGAP-map.jpg

2. The Approach of Adaptive Research
The study uses an adaptive research approach. Farmer participatory
88Chapter 6
From Science to Policy

research needs assessment, field plots, adaptive research, and crosssite visits. Especially, for the bottom-up approach to provide
recommendations to policymakers and all farmers, we use disciplinary
knowledge produced by scientists from the International Research Rice
Institute (IRRI).
Aligned with national best management initiatives for lowland
irrigated rice, we assisted with rice farm development in Vietnam(1 Must Do, 5 Reductions), Myanmar, Thailand, Indonesia (BestManagement Practices (BMP)); China (3 controls technologies +Alternate Wetting and Drying (AWD) for irrigation water saving). This
study is focused on the Mekong Delta of Vietnam (Figure 6.3).

Figure 6.3 Map of research area, Mekong Delta of Vietnam. Source: Author

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Toward Sustainable Agriculture of Rice in Asia

3. Challenges and Research for Development(1) Current Challenges
There are some challenges in rice production in the Mekong Delta, Vietnam,
including: input overuse and environmental degradation, climate change andincreased natural disasters, rising sea levels and soil salinization, particularlyin the Mekong River Delta, and increasing crop residue and rice straw.
(2) Research for Development and Activities
The program introduces new sustainable, climate-smart technologies
and practices, and hopes that farmers can adopt these technologies(Figure 6.4). In detail, these technologies and practices include using adrum seeder, alternate wetting and drying (AWD), a flatbed dryer, laser
land leveling, ecologically based rodent management, HYVs, IRRI, asuper bag, a mechanical transplanter, a solar bubble dryer, IRRI Rice
Knowledge Bank, a lightweight thresher, and a combine harvester.

Figure 6.4 The development of integrated programs that use new technologies andpractices to increase sustainability. Source: Author
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Chapter 6
From Science to Policy

The Vietnam Government has introduced a national policy,
namely “One Must Do – Five Reductions,” which aims to promote
the use of best management practices in lowland rice cultivation.
This includes the use of certified seeds as well as the reduction ofseed rates, fertilizer use, pesticide use, irrigation water use, and postharvest losses (Figure 6.5). However, it can be clearly seen that there
are different values. For instance, seed rates are sometimes set at a
maximum of 100 kg per ha but can increase to 120 kg per ha. This isbecause farmers could apply these different seed rates for different
rice crop seasons. The adoption can be seen as a function of Yes vs.
No, or Adoption vs. No adoption. Therefore, our study focuses on
how we can specifically define the adoption at a specific level for eachcategory. The reduction of fertilizer use, defined as adoption 1M5R,
is set at the level of 100–110 kg per ha. The adoption of pesticide
reduction is defined as: i) the use of a maximum 1–3 insecticide
application(s) and no insecticide before 40 days of seeding (DAS), ii)
the use of maximum 3 fungicide applications and none within 20 days
before harvesting, iii) the use of maximum 2 fungicide applicationand none after flowering. Regarding the reduction of water use, theadoption is defined as a minimum of two dry-downs in the Dong
Xuan (Winter-Spring) crop season, a minimum of one dry-down in
the He Thu (Summer-Autumn) crop season, or the use of safe AWD
with water tubes.

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Figure 6.5 One must do – five reductions and adoption of innovation (1M5R).
Source: Author

Figure 6.6 shows the framework for the adoption of innovation(1M5R) and its process.

Figure 6.6 Adoption of an innovation (1M5R). Source: Author
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4. Case Studies in Vietnam(1) Case 1: Qualitative Analysis of the Diffusion and Adoption
Constraints in Vietnam
1) Data Source
Data was collected from 155 farmers and extension officers from
MARD in 17 focus group discussions and analyzed by thematic content
to know how those different stakeholders perceive the adoption of
the 1M5R. Almost all farmers followed all requirements, especially
fertilizer and pesticide reduction, and post-harvest loss reduction.
However, farmers meet difficulties in applying AWD and reducing theseed rates.
There are some influencing factors mentioned in the group
discussions: Social networks including other farmers, friends, millers, andtraders can influence their willingness to adopt in practice.
 Information access such as weather forecasts, pest forecasts,
access to markets, cropping calendar and extension services caninfluence farmers’ adoption.
 Farming systems such as soil type, access to irrigation, andtransportation methods might have a big influence on farmers’
adoption or non-adoption.
 Access to equipment such as drum seeders, laser levelers, andcombine harvesters might negatively affect the post-harvest
losses.
2) Summary of Results
A multi-stage process consisting of several workshops for multiple
stakeholders and several farmers’ focus groups is important for the93

Toward Sustainable Agriculture of Rice in Asia

effective implementation of the 1M5R in order to bring beneficial
results. The qualitative analysis shows that external factors seem to be
the main barriers. In the case of water reduction and reduction of seed
rate, external factors such as the geographical location of the farm,land preparation, and access to machinery must be addressed further
by the government and public-private partners. Knowledge provision,
demonstration fields, and access to extension services are important toincrease the adoption of sustainable rice farming practices.
(2) Case 2: Vietnam – Adoption of 1M5R
1) Data Source
Adoption and barriers to adoption of the five reduction
requirements and the use of certified seeds specified under 1M5R
were investigated by means of a survey questionnaire created using
CommCare (Dimagi), a widely used data collection platform,
predominantly for monitoring health information in developing
countries (Agarwal et al. 2016). There was a total of 465 participants— 94% male with a mean age of 50.9 (Standard deviation = 12.4). In
addition, there was a training session for enumerators to use the survey
application before conducting the survey.
According to surveyed data (Figure 6.7), 91% of farmers havebeen using certified seeds with 37% using high-yielding varieties.
Farmers have also reduced their seed rate (86%). However,considering a seed rate of ≤100kg/ha, only 4.7% (n = 22) of the
farmers applied that. There are a number of farmers who reported thatthey have reduced their pesticide use (74.4%), including fungicides(88%), herbicides (94%), insecticides (90%), rodenticides (62%), andmolluscicides (93%). 74% of participants reported that they reduced
their fertilizer use, but only 45% of the participants reported reducing
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their water use and 35% of the farmers reported to be applying AWD
in their fields.

Figure 6.7 Summary of surveyed data on 1R5M adoption in the study sites.
Source: Author

All farmers who adopted practices were still using them in 2019 andreported to be willing to continue using them.
2) Benefits and Barriers
Rice farmers perceived a variety of benefits when adopting thesingle requirements specified under 1M5R. Most of the farmers
perceived for each requirement that “it is easy to apply 1M5R,” “Labor
costs are lower,” “It is less expensive,” and “It fits my crop pattern”(Figure 6.8).

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Figure 6.8 Benefits of 1M5R adoption. Source: Author

Farmers also perceived some barriers to adopting the 1M5R. The
main barriers to using certified seeds were “Technology is not suitable
for my field conditions,” “It’s too expensive,” and “It doesn’t satisfy mypreferences.” Farmers reported several barriers to reducing seed rates
and fertilizer use including “Weather conditions do not permit it,” “Itdoesn’t fit my cropping pattern,” and “It produces a low yield.” Barriers
to reducing water use were “It doesn’t fit my cropping pattern,” “It’s too
difficult to apply,” and “Weather conditions do not permit it” (Figure
6.9).

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Figure 6.9 Barriers of adoption 1M5R. Source: Author

3) How often were Certain Combinations Adopted?
When analyzing the requirements using AWD and a seed
rate of ≤100kg/ha, the use of certified seeds occurs more often in
combination with the reduction of fertilizer and pesticides, andthe use of a combine harvester, whereas the use of AWD (water
use reduction) and the reduction of seed rate remain separate
and, therefore, used less frequently in combination with the otherrequirements (Figure 6.10).

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Figure 6.10 Combination adopted. Source: Author

4) Factors Influencing the Adoption of 1M5R
A linear regression model was used to investigate the factors
influencing how many elements of 1M5R were adopted by rice farmers.
For the adoption analysis of generally phrased requirements, farmers’satisfaction, the ease of 1M5R, non-rice income, and education weresignificant predictors. Meanwhile, for the adoption of the requirements
using AWD and a seed rate of 100kg per ha, farmers’ years of farming
become an additional predictor apart from three predictors of the ease of
1M5R, non-rice income, and education (Table 6.1).
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Table 6.1 Influencing factors on 1M5R adoption(A) Adoption generally phrased (B) Adoption for requirements using ADW
requirements, r2 = 24.9%
and a seed rate of 100kg/ha. R2 = 23.5%
Beta
t
p
Beta
t
p
Total area
0.008
0.521
.603
0.010
0.852
.395
Years of farming
0.008
1.787
.075
0.007
1.913
.056
Expectations
0.016
0.188
.851
0.086
1.242
.215
Saticsfaction
0.206
2.280
.023
0.065
0.879
.380
Ease of 1M5R
0.530
6.462
.000
0.418
6.163
.000
Average yield
0.089
1.610
.108
0.038
0.828
.408
Non-rice income
0.470
4.194
.000
0.006
3.680
.000
Province
0.093
0.789
.431
-0.024-0.243.808
Education
0.218
3.173
.002
0.130
2.298
.022
Member of cooperative 0.184
1.481
.139
0.005
0.048
.961
Subjective knowledge -0.126-1.008
.314
0.018
0.170
.865

Note. N = 464. Variable province was coded 1 = An Giang, 2 = Can Tho. Variable
non-rice income was coded 0 = no, 1 = yes.
Source: Author

The results from seven logistic regression models for seven rice
farming practices were summarized in Figure 6.11. The use of certified
seed was significantly affected by farmers’ education and the ease of
1M5R, while the reduction of seed rates was significantly influenced bytheir satisfaction and the ease of 1M5R. In addition, the ease of 1M5R
strongly affected their willingness to reduce fertilizer use, pesticide use,water use, and AWD. Moreover, the higher the percentage of their nonrice income, the more their willingness to reduce fertilizer use, pesticideuse, water use and AWD. Meanwhile, satisfaction and average yield are
influencing factors in the reduction of fertilizer use, while expectations
and satisfaction are other key factors in the adoption of AWD.

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Figure 6.11 Summary results of the regression model. Source: Author(3) Case 3: Vietnam – Psychological Factors Influencing the Acceptanceof Sustainable Farming Practices
1) Household Survey 1a) Study Site and Data Collection
The survey was conducted in three provinces of the Mekong Delta— An Giang (n = 38, 17 cooperative farmers), Can Tho (n = 35, 10
cooperative farmers), and Tien Giang (n = 38, 18 cooperative farmers)in 2018. The majority of participants were male (91%). The mean age
was 51.5 years.
b) Sustainable Farming Practices
A total of eight sustainable farming practices with respect torice straw were introduced to farmers for assessing their acceptance.
They include on-field practices and off-field practices (Figure 6.12).
Regarding on-field practices, there are two main managements: 1)
the incorporation of rice straw into the field which can improve soil
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fertility and nutrient balance. However, the speed of degradation canvary, and an increase in organic matter in irrigated soil can increase
GHG emissions; and 2) rice straw burning which is a quick, simple, andaffordable method of reducing biomass quantities in the field, but thiscauses GHG emissions and release of pollutants. Meanwhile, the offfield practices involve composting rice straw, rice collection methods,
anaerobic digestion – biogas production, mushroom production, andcattle feed.

Figure 6.12 On field and off field practices. Source: Authorc) Method – Fact Sheets
All fact sheets regarding rice straw management had the sameformat and started with a short introduction to the management practice.
After this short explanation, a colored picture of the management
practice followed. The second half of the fact sheet showed the specificfeatures of the straw management practices in bullet-point format which
include benefits, risks, costs, and GHG emissions (Figure 6.13).

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Figure 6.13 Fact sheets. Source: Authord) Theoretical Framework

Figure 6.14 Theoretical framework. Source: Authore) Results
Results show that farmers often burn their rice straw even though102Chapter 6
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they perceive high risks, few benefits, and expressed low levels of
acceptance for rice straw burning. However, acceptance of rice straw
management practices differs between practices, and their behavioral
intentions are high. All other management practices are perceived tohave high benefits and relatively low risks — practice depends on, andwhether farmers know about the management option.
The perceived benefits were a strong predictor for farmers’
acceptance of all other rice straw management practices. The results ofthe study also show that risk perceptions were weak but a significant
predictor for the acceptance of rice straw incorporation into the soil,
straw burning, biogas production, and cattle feed.
Furthermore, knowledge about climate change was also a predictor
for the acceptance of straw incorporation into the soil, composting,cattle feed, baling, compacting, and mushroom production.
The results show that support from institutions is a significant
predictor for baling and compacting rice straw. Farmers need support
from different actors; especially from the government and research
institutions to have access to straw collection machinery sinceparticipants are all small-holder farmers and have limited access tomachinery.
Farm size has a negative impact on the incorporation andcomposting, while only rice yield had a positive significance for biogas
production. Therefore, it is necessary to carefully take into accountdifferent factors for different practices and policies.
2) Household Survey 2a) Data collection
Data were collected from 180 farmers twice (in 2015 and 2019)using a tablet-based questionnaire. They were classified into a project
and a control group. The sampling is by purposive geographic selection,103

Toward Sustainable Agriculture of Rice in Asiaand project farmers were selected randomly from the farmers’ list, andcontrol farmers were purposively matched. Especially, the selection of
farmers was based on the local extension staff’s network of farmers who
proactively participated in commune-level farming activities such as
training facilitated by the extension staff.
b) Results- There were no sociodemographic and farm-specific differences
between the farmer groups in both survey years.
- Adoption rate was high for combine harvesters, drum seeders,AWD, and improved varieties → there were no significant
differences between farmer groups.
- Farmer profitability increased by 5.7% and rice yield by 4.7%.
- Socioeconomic and agronomic differences between farmer groups
in both survey areas: (1) project farmers applied lower quantities of
inputs, (2) project farmers’ yield and rice income were also lower.
(4) Case 4: Consumer Acceptance and Willingness to Pay for Sustainably
Produced RiceThe Sustainable Rice Platform (SRP) standards — the world’s firstsustainable production standard for rice — has recently been introduced
in Vietnam, but the market demand and potential for price premiums
for SRP-certified rice are not known (My et al. 2018, 2021). This study
aims to examine the relationship between climate change knowledge
and consumer willingness to pay for SRP-certified rice in Vietnamese
supermarkets. Data for the study was collected from 410 consumers
through a questionnaire survey. Most participants were female (86.3 %),and the average age was 41.7 years.

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1) Theoretical Framework
The conceptual framework for this study is presented in Figure
6.15. This study attempts to investigate the influence of knowledge(i.e., about climate change and of sustainably produced rice), attitudes
towards sustainable production, and socio-demographic and economic
variables on consumers’ willingness to pay for sustainably produced
rice. Especially, consumer’s evaluations of three different attributes of
the SPR standard will be investigated, namely consumers’ perception of
ecological production, ethical production, and low-emission production.

Figure 6.15 Conceptual framework of the study; determinants of consumer’s
willingness to pay for SRP labelled rice (adapted from My et al. 2018; 2021)

2) Results
The results of this study show that consumers are willing to pay a
29% price premium for sustainably produced rice. Knowledge aboutclimate change and its impacts positively influenced willingness to pay.
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Especially, focusing on the country’s contexts is extremely importantfor policy implications and finding some similarities for applying in the
Vietnamese context. Moreover, household income positively influenced
willingness to pay. If consumer demand for sustainably produced rice
can be increased, production will need to follow. The findings of thisstudy are important for policymakers to increase the inclusiveness of
SRP rice by creating an enabling environment for investment in the
supply and demand for SRP rice.

5. Conclusion
In summary, the 1M5R program is suitable for farmers’ conditionsin the Mekong Delta. This program has been strongly and consistently
supported by MARD, particularly by the Department of Crop
Production and Plant Protection. The program is now a provincial
regulation and policy and has also been modified for application in Lao
PDR and Thailand.

References

Agarwal, S., A. E. LeFevre, J. Lee, K. L. Engle, G. Mehl, C. Sinha, and A.
Labrique. 2016. Guidelines for Reporting of Health Interventions
using Mobile Phones: Mobile Health (mHealth) Evidence
Reporting and Assessment (mERA) Checklist. BMJ, 352.
Connor, M., A. H. de Guia, R. Quilloy, H. V. Nguyen, M. Gummert, andB. O. Sander. 2020. When Climate Change is not PsychologicallyDistant-Factors Influencing the Acceptance of Sustainable
Farming Practices in the Mekong River Delta of Vietnam. World
Development Perspective, 18, 100204.
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Connor, M., L. A. Tuan, A. H. De Guia, and H. Wehmeyer. 2021.
Sustainable Rice Production in the Mekong River Delta: Factors
Influencing Farmers’ Adoption of the Integrated Technology
Package “One Must Do, Five Reductions” (1M5R). Outlook on
Agriculture, 50(1), pp. 90–104.
GSO. 2020. General Statistics of Vietnam. General Statistics Office ofVietnam. <http://www.gso.gov.vn>
Ministry of Industry and Trade. 2017. <http://moit.gov.vn>
My, Nguyen H. D., Matty Demont, Ellen J. Van Loo, Annalyn de Guia,
Pieter Rutsaert, Tran Huu Tuan, and Wim Verbeke. 2018. What isthe Value of Sustainably-produced Rice? Consumer Evidence from
Experimental Auctions in Vietnam. Food Policy, 79, pp. 283–296.
My, Nguyen H. D., Matty Demont, and Wim Verbeke. 2021. Inclusivenessof Consumer Access to Food Safety: Evidence from Certified Ricein Vietnam. Global Food Security, 28, 100491.
Tuan, L. A., H. Wehmeyer, and M. Connor. 2021. “One Must Do, Five
Reductions” Qualitative Analysis of the Diffusion and Adoption
Constraints in Vietnam. Development in Practice, 32(6), pp. 768–780.
United States Development of Agriculture (USDA), Foreign Agricultural Service (FAS). 2019. Grain and Feed Annual. <https://www.fas.usda.gov/data>
World Bank. 2012. Vietnam Rice, Farmers and Rural Development: From
Successful Growth to Sustainable Prosperity. Hanoi: World Bank.
———. 2016. Vietnam Development Report. Washington, DC: World
Bank.

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Concluding Remarks and Discussion
Thanh Tam HO
Climate change poses significant challenges to global food security
and safety. Strategy policies to mitigate food safety risks while
minimizing environmental impacts in the era of climate change are
becoming more important. Sustainable agricultural practices arepotential solutions for sequestering carbon as climate change mitigation,
improving environmental health and economic performance, as well
as satisfying society’s need for food safety. Identifying not only thefarmers’ decision-making but also the consumers’ preferences for safe
food can provide academic insights into understanding the potential
strategies for a safe products market. Nevertheless, the diversity andheterogeneity of agricultural systems characterized by geographicalregions or across countries might imply diversified policy implications
for climate change adaptation and developing sustainable agriculture.
This booklet is a record of the AJI International Workshop which
was held online under the restraints of the COVID-19 pandemic, withthe aim of promoting international communication and academic
collaboration among young researchers in Asian Universities andInstitutions. Furthermore, it is my hope that this opportunity will drive
sustained and long-term connections through collaborative research
projects in the near future. Our discussion mainly concentrated on threeissues.

1. Climate Change and Challenges to Agriculture

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Concluding Remarks and Discussion

Climate change has become a major threat to global agricultural
production and food security. Recently, extreme weather events suchas drought, severe floods, and storms have increased in frequency andintensity, seriously damaging agricultural production. Increases in floods
and droughts are anticipated due to variations in rainfall patterns, anddry seasons are expected to become longer in the future. Developing
regions of the globe are more sensitive to climate variability and change
as these regions implement old technologies, whereas developed regions
can mediate climate-driven extremes through the implementation ofmodern technologies. Consequently, climate change would pose a direct
and severe challenge to rice production, especially in Asian countries— the main rice production region of the world. Indirectly, the priceof rice and the rural livelihoods of rice farmers would also be affected.
Therefore, it is urgent to develop agricultural systems that are moresustainable and resilient to climate change.
Dr. Orawan Srisompun addressed the drought situation and its
negative impacts on rice production in Thailand. Climate change
adaptation (i.e., stopping rice growing, finding additional water
sources [i.e., digging ponds, wells, or groundwater], adjusting the timeof planting or slowing the rice sowing, reducing the number of ricecultivation areas, adjusting the use of rice varieties, adjusting the typesof crops that are grown instead of rice, or changing to livestock insteadof growing rice) were ascertained as practices to cope with insufficient
rice for consumption and agricultural income for farm households.
Importantly, she mentioned that a long-term strategy plan for climatechange, especially drought management, is necessary to ensure rural
livelihood, especially income and self-sufficiency.
Dr. Mohammad Rondhi et al. reported on Indonesian farmers’
decision-making on farming insurance as an adaptation measure toclimate change. Participation in farming insurance might be attractive
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for risk-averse and land-owning farmers. A high level of risk aversion
would be of concern for the policymakers as it potentially hinders
farmers’ adoption of new technologies. They discussed the specificprogram from the government for each specific area in Indonesia. They
concluded that the government should pay more attention to farmers
with rented or sharecropping land and high-risk aversion as the targets
for improving farmers’ participation in the government’s agricultural
insurance scheme.
Climate change adaptation is essential for sustaining agricultural
productivity, reducing vulnerability, and enhancing the resilience ofagricultural systems. Building adaptation and mitigation in agricultural
systems requires simultaneous attention to increasing production
by adopting varieties of technologies, adopting sustainable land
management practices, building on and using local knowledge andsocial culture, and formulating enabling policy and institutional setups.
Improving resilience and farmers’ adaptive capacity to cope with climate
risks has become increasingly important not only in Asian countries but
also in other vulnerable regions and communities.
Recently, awareness of agriculture in harmony with the environment
and its biodiversity has continually risen. Though several adaptation
options are available in agriculture, not all of them can be applied to all
locations, as they are mostly location-specific. Therefore, cooperationand collaboration among institutions at international and national levels
are extremely important for coping with the challenges of climatechange, food security, and food safety at the cross-country level.

2. Towards Sustainable Rice Agriculture
Today’s unsustainable farming practices put global food security
at risk. This would adversely impact the world’s most vulnerable
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Concluding Remarks and Discussion

populations, including rice farmers. The global population is expected
to exceed nine billion by 2050, and even more people will rely onrice for nutrition. As one of the most important food staples, we must
transform the rice sector to feed the world sustainably. Although rice
is a staple food for many in Asia, smallholder farmers still face many
challenges, including decreasing yield productivity from the effects ofclimate change and the pressure to meet the rising demand for food as
the world’s population continues to grow.
It is important to have an intimate understanding of farmers’
immediate needs. With farmers’ means of support as a priority,
positioning climate-smart agriculture solutions as directly beneficial tofarmers’ livelihoods is necessary to get greater engagement. Therefore,
the integration of adaptation and mitigation strategies is a primarychallenge to promote sustainability and productivity.
With the global demand for rice continuing to rise and limited
potential to expand yields in traditional producers such as China, thecountries of mainland Southeast Asia are poised to take center stage as
the world’s rice bowl if they can increase their resilience to social andenvironmental pressures. However, climate change and labor shortages
threaten rice production in a region that feeds an ever-larger share of
the world’s rice consumers. Major rice producers such as Thailand andVietnam produce rice for their own populations, as well as exporting toother regions, while other traditional producers in the region, such as
China, India, and Indonesia, are increasingly turning to imported rice tokeep their populations fed.
Dr. Phuc Trong Ho proposed the adoption of high-yielding andhigh-quality rice varieties in the Mekong Delta as a solution forincreasing rice production to meet the increasing consumption demandof population growth. In developing countries like Vietnam, policies
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Toward Sustainable Agriculture of Rice in Asia

as reducing land fragmentation to speed up the adoption of highquality rice varieties. Furthermore, high-quality rice varieties should
be developed with consideration for adapting to adverse production
conditions and climate change impacts.
Moreover, Dr. Melanie Connor stressed that it is essential todevelop rice and protect its sustainability for global food security andenvironmental conservation with the consideration of policymakers andscientists not only in Asia, but also in Africa. Improving sustainable riceproduction in Africa through capacity development and innovation isanother challenge. Sub-Saharan Africa is the world’s most food-insecure
region. In order to secure a stable supply of food for the region andachieve the eradication of hunger, food production technology that canadapt to the increasingly unstable growing environment and effectively
utilize limited resources such as water and nutrients is required. To thisend, it is important to develop new technologies and knowledge thatwill lead to increased production of rice, a key crop in the region, andimproved food self-sufficiency and nutrition for the people, with theaim of building a sustainable food production system centered on ricecultivation.
Furthermore, strengthening social norms for motivating farmers’
intentions and their behaviors toward sustainable agriculture is
extremely important. Especially, establishing trust among farmers
is another issue which should be focused on, and this can be done
by working closely with farmers’ associations and investing indemonstration farms to “show by doing.”

3. Economic Challenges and Policy Aspects
The major concern about the economic sustainability of rice farmingis that subsidies are necessary if the price of rice is to be kept low. The
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Concluding Remarks and Discussionsocial, political, and economic importance of rice in all of the major
rice-producing countries is such that their governments seek to ensurethat sufficient rice is available at a price all can afford.
Dr. Qi Dong addressed the importance of resource input use andrice production efficiency with a comparison between China and Japan.
Especially, the scarce input resources in rice production resulting fromstructural transformations and changes in dietary structure constitutethe main differences in rice production between the two countries. The
shadow costs can lead to a significant gap between the two countries
and affect rice farmers’ enthusiasm. In addition, the costs for sustainable
rice farming seem to be remarkably high compared to conventional
rice farming. High labor costs and a shrinking labor force are emerging
issues, more so in a developed country like Japan than in developing
countries.
This author also addresses the economic aspects of climatechange adaptation in reducing productivity loss as well as improving
farmers’ profitability. Nevertheless, promotion policies are facing
several challenges not only in developed countries like Japan but also
in developing countries like Vietnam. More specifically, the Japanese
direct payment policy can be a solution for ensuring farmers’ income
and their motivation toward sustainable agriculture. Nevertheless, thequestion of how the government with their direct payment policies canreally achieve the sustainable production of rice in the long term should
be tackled.
Meanwhile, promotional policies for sustainable rice farming ororganic farming could add value to production. For specific regions likeThailand and Vietnam, developing local rice varieties (i.e., droughttolerant, salt-tolerant, pest-tolerant) should be focused on. Large-scale
farming policies are necessarily different across regions. Thailand’s
farmers, especially those in the Northeast regions, would not benefit
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from economies of scale, while Vietnam’s farmers, especially thosein the Mekong River Delta regions, would benefit from increasing
farm scales. Agricultural innovation and technology should be paid
more attention not only at the national level but also at the local level.
Simultaneously, policy recommendations for sustainable rice farming
should be involved at transnational levels.
Importantly, our discussion not only shared academic knowledge
linked to the various situations of Asian rice but also aimed at theestablishment and activation of researcher networks, even under
the constraints of the COVID-19 pandemic. An international andmultidisciplinary research approach towards sustainable rice agriculture
is definitely important for our future collaboration. It is necessary tomention here that the inequities within countries and across countries
in Asia and how these are potentially exacerbated by existing sociopolitical systems should be given more attention in future research.

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ONLINE ISBN 978-4-910550-47-3
PRINT ISBN 978-4-910550-46-6
Asia-Japan Research Institute, Ritsumeikan University