Assessing Sustainable Development of Isolated
Communities: The Role of Electricity Supply
Summary
The term ‘rural development’ refers to initiatives undertaken aiming to improve the
quality of life of non-urban communities. Sustainable development (SD) of rural
communities is directly linked to the communities’ skills for adapting themselves to
changing conditions in constructive ways. Different studies have shown that one
important factor contributing to the development and growth of rural communities is
power supply (Berglund & Soderholm, 2006; B. Borroto, Borroto, & Vazquez, 1998;
DFID, 1997). However, assessments on the influence of power supply over rural
development have fallen short of expectation as they have been too technical,
mainly using econometric approaches or coefficients based on misery line. This
paper seeks to contribute from a holistic approach to identify economic and social
development in which energy is a crucial factor that contributes to human, social,
and economic development, all supported on information technologies and
mechanization processes, thus enabling sustainable development.
Keywords: Off-grid communities, sustainable development, rural electrification,
sustainable livelihoods (SL) framework, system dynamics.
Introduction
Energy supply contributes to the economic and social development of isolated
communities (Ozturk, 2010; Painuly & Fennhann, 2002; Rozakis, 1997; Siemons,
2001; Utlu & Hepbasli, 2007). However, there are other elements are required for
sustainability, including the application of electricity to processes that add value to
a community (J. A. Cherni et al., 2007; J. a. Cherni & Hill, 2009; Henao, Cherni,
Jaramillo, & Dyner, 2012; Singh & Hiremath, 2010). The literature has shown the
need to evaluate the evolution of energy technology over time (BID, 1998;
Goldemberg, 2000), but this does has not addressed the need of engaging with
sustainable development. Rather, this emphasizes the development of particular
elements of the community by neglecting a systemic approach, which limits the
broad approach required to address development issues.
SL is primarily and specially about people. SL also contributes to better define
institutional agreements that may promote strategies to overcome poverty and to
improve communities’ quality of life. Its aim is to achieve a realistic understanding
of the strengths of communities (capital endowments) and their possibilities to use
these for better livelihood (DFID, 2002). The SL framework below (see Figure 1)
can be useful to the identify goals, opportunities, and development priorities in
order to accelerate progress and to eventually eradicate poverty.
Bo:a==
Figure 1 Sustainable Livelihoods framework (DFID, 2002)
On the side of communities and their needs, development in rural areas is a
holistic problem that integrates relevant factors such as education, health, social
capital, economic means, and environment. In this paper, we focus on how energy
supply may contribute to rural development. This is done by demonstrating how
different elements contribute to the development and how these evolve over time in
a simulated environment. This simulation through an SD model incorporates the
ways in which behaviors may contribute to reinforce the build-up of the
communities’ endowments — i.e. capitals (human, social, financial, natural, and
physical (see DFID, 2002)). To this end, different approaches and methodologies
are discussed in the next sections regarding the problematic situation analysis of
the communhity’s SL.
Problem Situation
Maslow (2000) has established that human needs are prioritized according to
some categories. These categories range from the most basic ones (physiological),
through the ones that determine safety, shelter, and love, up to those related to
self-esteem and those related to achieving the potential of individuals in society
(see Figure 2). In these sense, and according to Sen (1999), freedom ultimately
promotes the emergence of development as most actions carried out by people
seek for a level of sustained welfare (Pg. 3, Sen, 1999). The actions of individuals
are motivated by the satisfaction of needs, and eventually targeted by providing
safety and means for survival. Particularly, individuals within off-grid and poor
communities look for solutions (social, economic, natural and others), so they are
able to move upwards in Maslow’s pyramid.
Safety
(Shelter, removal from danger)
Physiological
(Health, food, sleep)
Figure 2: Pyramid of Maslow (Maslow, 1943)
Under this theoretical framework, the role of energy technology is understood as
means for sustainable development wherein communities may freely progress
upwards in the pyramid of needs, and may assess the impact as well as the
boundaries that limit the development of the respective communities (Abualkhair,
2007; Singh & Hiremath, 2010). In this sense, rural communities are not only
determined by their physical or geographical endowments, but they may also take
responsibility for the ways in which technology is managed. This can be measured
in terms of technical and technological capabilities, which might be learned and
developed, and by the level of freedom that might be attained by individuals
(Robledo & Ceballos, 2008). However, as long as energy technology provides
means to attain freedom (welfare), it also entails responsibilities regarding its
maintenance and sustainability.
This leads us to our model-based approach framed within the systems-thinking
methodology (Berglund & Soderholm, 2006; Hjorth & Bagheri, 2006). This
approach adds conceptually some problematic situations, uncertainty, and
numerous interactions between system components — in terms of a theoretical
model — that address isolated rural communities.
Methodology
Our dynamic hypothesis is proposed in Figure 3. As shown, energy is necessary
for satisfying basic needs (physiological and safety needs), which in turn contribute
to the development of social and economic activities, thus attaining freedom for
individuals and developing social welfare. The eventual satisfaction of needs and
the use of energy lead to further energy needs, which justifies additional power
capacity. This capacity can be affordable by increasing communities’ income
generated by the growth of their economic activities. By meeting needs, it also
becomes evident the emergence of some freedom that supports possibilities
towards technology learning and efficient satisfaction of needs at all levels of the
Maslow’s pyramid (Maslow, 1943).
Subsidies
Electricity demand of
surrounding countries
Energy \ +
fF b)
i)
Pressure on construction a] of basic +
Baamal of new electric — needs (Maslow) Energy de
investment i cooking)
+ Economic activity 4)
/ Ke! Rural development
Social activity (community capacities)
(Social i a
ee
Figure 3. Development supported by energy technology.
The diagram shows a set of cycles in which the most important are the central
ones, which involve elements of Maslow’s pyramid. These include the satisfaction
of physiological, security, and belonging needs. When these needs are satisfied,
rural development is boosted and freedom of individuals is more likely to be
achieved.
When the community makes progress towards development, income improves as
the product of more diversified economic activities. This increases the
communities’ abilities to afford electric energy enabling the exchange of goods and
services. It is important to note that subsidies from the State also facilitate the
communities’ access to energy technologies, fostering energy demand for
subsistence as a consequence. Furthermore, social activities are embodied into
groups or associations. These strive for the consecution of more energy-related
infrastructure and for the acquisition of external investment, which increases, at
long term, greater investment in energy capacity. By taking into account such
energy demand, in conjunction with electricity supply, the community's energy
deficit is determined, which exacerbates Maslow’s pyramid of needs.
Simulation model
Social development and basic satisfactions are mapped as levels depend on the
energy technology in place. Income level is a result of the community’s economic
activity. Electricity capacity is expanded depending on the community’s demand
and its payment capacity. In this way, Maslow's pyramid is incorporated as part of
the SL framework (Maslow 1943).
Social capital is influenced by a number of factors, including support groups
(technical and technological knowledge about energy), which meet sustainability
needs. Human capital depends on information technologies that contribute to
learning processes. Surrounding communities are exogenous to the system.
Social, human, and financial capitals — as part of the Sustainable Livelihoods
(DFID, 2002) framework — are central in the model as they represent the variables
that directly influence development in accordance to the aforementioned
hypothesis.
Results
For the analysis of results, it has been necessary to identify the impact of the
availability and consumption of energy in rural communities.
Considering Maslow's perspective, Figure 4 shows that, with the impact, there is a
long-term satisfaction starting with physiological needs. Needs satisfaction is more
compelling as the community focuses its efforts on improving the quality of food
when adopting different ways of cooking, preserving, and marketizing aliments.
Maslow's Needs
1
0.75
0.5
0.25
0
0 36 72 108 144 180 216 252 288 324 360
Time (Month)
Social needs satisfied : High aceptance Dmnl
Physiological needs satisfied : High aceptance Dmnl
Security needs satisfied : High aceptance Dmnl
Figure 4. Maslow’s needs satisfaction.
This improvement has a direct impact on security needs. This can be explained by
the fact that when physiological needs are satisfied, the community actions focus
more on improving housing and night illumination, and meeting different needs that
could not be supplied before due the basic need of purchasing food for
subsistence. Later, with the satisfaction of social needs (group membership),
resources availability that permit the creation of new operation partnerships,
maintenance, and improvement of human relations within the community is
identified. This set of changes improves communication dynamics of the
community, potentiates its income from available resources, and makes the very
community a development focus within the region. This makes this grow to change,
because after energy adoption this level can overcome surpassing previous limits.
Energy helps community to grow in this needs, in use of energy, related to
acceptance and use.
Capitals
1
0.75 a a
0.5
0.25
0
0 36 72 108 144 180 216 252 288 324 360
Time (Month)
Social capital : High Dmnl
Human capital : High Dmnl
Financial capital : High Dmnl
Natural capital : High Dmnl
Physical capital : High Dmnl
Figure 5. Capitals.
The measure using capitals allow to make an analysis in a wide approach,
reviewing aspects not shown in the dynamic hypothesis. Social capital are related
directly to belonging needs and the rest of capitals are related to rural
development. In addition, the model shows that, due to a greater amount of energy
available, long-term income increases. This may be because the accessibility to
different means of generating income is possible, creating a new culture of
exploitation around electric power. As shown in Figure 5, after a small foreign
investment in maintenance and energy, operation training is accomplished leading
to a steady income increase related also to commercial exchange with neighboring
communities, the exploitation of resources and better use of them. All this takes
place with various forms of energy exploitation, either by creating nightly meeting
points and or by establishing partnerships aimed at better managing new
revenues. For the natural capital the use of resources like water or even gas in
energy generation slowly decreases the natural resources of the region, but at the
same time this allows to the community to grow in physical capital and financial
capital, related to the use of energy and the increase in generation in all the time of
this simulation.
However, the demand for energy increases as time passes by since the attraction
of foreign population leads these energy requirements to grow steadily. This
generates a cycle of reinforcement, which makes the external investment
necessary. However, at long term, this can be replaced by a transfer of income
from the community to training processes and teaching technology management.
Moreover, given that the ownership rate of energy technology is superior due to
human capital accumulation (represented by the newly acquired technical skills of
the community), it can be seen that there is a decrease in energy deficit combined
with strong pressure for the construction and improvement of existing energy
technology (see Figure 6). At the same time is shown that income per capita goes
down, because this energy deficit affect negatively the income, related directly to
the new uses of energy that cannot be achieved.
Economic activity - New capacity
800 Dollars
80,000 kWhour/mes
400 Dollars
40,000 kWhour/mes
0 Dollars
0 kWhour/mes
0 36 72 108 144 180 216 252 288 324 360
Time (Month)
Income percapita : Tendencial Dollars
New capacity kWh : Tendencial kWhour/mes
Energy deficit : Tendencial kWhour/mes
Figure 6. Energy changes
With respect to capitals, these emerge from the satisfaction of needs proposed by
Maslow. This occurs possibly because when individuals have a good satisfaction
level satisfaction of physiological needs, they switch to training people in the
community in technology management, which is ultimately the human capital.
Besides, this capital enables the creation of partnerships, which are based on the
need to belong to groups (Belonging needs) of people, generating automatically an
improvement in social capital.
The creation of support groups is present at the beginning of the simulation, but as
time goes on, given the capabilities of the community, these groups are turned into
collective knowledge, allowing easy maintenance and operation of energy
technology, which reduces the need for conducting on-going support programs.
Finally, the expected behaviour from the inclusion of energy technology in a rural
community is to be accompanied by comprehensive support programs, pending
knowledge appropriation, and further emergent needs in communities. In these
ways, maintenance by local authorities interested in developing and meeting the
needs of the community and other surrounding communities.
Conclusions
Poverty, which has been discussed by various authorities from scholar and social
viewpoints, is directly linked to quality of life. Solving poverty certainly allows full
development in terms of basic needs and proper social relationships. In the model
presented here, poverty is classified as a cluster of factors that are discussed from
a global perspective linked to the evolution of capital. Since they all have a growing
tendency, they can demonstrate that energy, based on the previous model,
contributes to better development.
The conceptualization of the problem, from external and internal components,
necessarily imply that communities need to develop knowledge by their own
means, in the case there are complex technological capabilities as a source of
resources to sustainable development.
Management of technological capabilities is supposed to accumulate knowledge
through learning, which entails sharing internal and external sources for synergy
between the parties. Hence, building complex technological capacity can be
positively related to technological success.
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Max Conventional Max Organic Yield
Per Acre
: mri
Conventional + _
Yield
|crop Price Per Q
+ Conventional
Revenue
Adjustinent Time
5
Eagan tin As)
"lor Organic Adoption
Exogenous Cost
fer Acro
Conventional
Exogenous Cost
Per Acre Organic
‘Conventional Prof Alractivendas of attctveness Organic Prof
aa / cael
Weightofprofit _ Weight of _
onatiractiveness motivation on
Percent of Costs
Spent on Fertilizer
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Figure 7: Dynamic Model of Adoption of Organic Farming
Model Parameterization
Table 1, below, shows the values used to initialize the model, and the associated ra-
tionale or source for each variable. Key control variables (e.g., exogenous switches) are
discussed below.
. Yield Potential: the maximum yield achievable for a given farming paradigm is
determined exogenously, and conventional and organic maximum yields can be
set independently.
° Cost Per Acre of Farming: the cost per acre of faming under each system is
determined exogenously and can be set independently. Both organic and conven-
tional farming systems require additional inputs beyond fertilizer or manure, and
needs for each farming system may be different.
. Percent of Costs Spent on Fertilizer: as a conventional farmer uses more (less)
fertilizer, total costs increase (decrease). The model therefore allows for exoge-
nous determination of the percent of total costs that a farmer spends on fertilizer.
Table 1: Model Parameterization
Model Parameter Initial | Units Rationale
Value
Acres Under Organic 0 Acres |Most farmers start with conventional
practices, and then shift to organic for
economic or emotional reasons
Acres Under Conventional 2 Acres |1-2 acre is average farm size of wheat
farms in Haryana
Adjustment Time ll Years |Assume farmers only make decisions
between seasons
Crop Price 600 | Rs/Q |WheatBazar data for Haryana
Range: 600-900Rs/Quintal
Max Conventional Yield Per, 40 | Q/acre |WheatBazar data for Haryana
Acie Range: 40-50Q/acre
Max Organic Yield Per Acre| 40 | Q/acre |Range of 32- 60;
20% lower or higher than conventional
Exogenous Cost Per Acre | 15000 |Rs/acre|WheatBazar data for Haryana
Conventional Range: 15,000-20,000
Exogenous Cost Per Acre | 15000 |Rs/acre|WheatBazar data for Haryana
Organic
15/30
Range: 15,000-20,000
Percent of Required Ferti- 1 Dmnl |Start with 100% optimal practices
lizer Actually Applied Per
Acre
Percent of Required Ma- 1 Dmnl | Start with 100% optimal practices
nure Actually Applied Per
Acre
Percent of Costs Spent on | 0.30 | Dmnl /27 crops studied by Tej Pratap 2006
Fertilizer report fertilizer costs at 25-50% of the
total costs with a mean value of 30%.
Soil Health Organic Per 0 Dmnl |Soil health will accumulate according to
Acre initial fertilization.
Soil Health Conventional f Dmnl | Perfect soil health due to optimal ferti-
Per Acre lization.
Time for Organic Soil to 3 Years |3-4 years (Clark et al., 1998; personal
Develop conversations)
Time for Organic Soil to 3 Years |Assume same as development time
Degrade
Time for Conventional Soil 1 Years |Time is < one year: assumption is that
to Develop impact from chemical fertilizer is real-
ized immediately
Time for Conventional Soil J Years |Time is < one year: assumption is that
to Degrade
impact from chemical fertilizer is real-
ized immediately
ANALYSIS AND RESULTS
In this section, we perform model analysis in three stages. First, we demonstrate that
the model is intendedly rational. Then, we present a base case where the dynamic model
reproduces WBB behavior when switching from conventional to organic farming under the
condition of excessive fertilization. Finally, we perform sensitivity analyses to study how
various parameters affect the WBB Dynamics, namely: the level of over fertilization, the
cost of organic manure, the efficiency of the package of practices used during conversion,
and the rate at which the farmer switches to organic regime.
Intended Rationality
To demonstrate that the model behaves as intended, we present two cases: farming
under effective conventional practices, and farming under excessive use of chemical
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fertilizer. Appendix II offers the model parameterization to help the reader reproduce all of
the runs presented in this section.
Effective Conventional Practices
When a farmer is applying the correct amount of chemical fertilizer relative to the
amount required, soil health, and therefore yields and profits, is maximized. In this
scenario, shown in Figure 8 below, organic farming isn’t relatively more attractive and
therefore the entire farm continues under conventional practices without switching to
organic farming. The profit for the farmer, given parameterization in Table 1, in this case is
Rs. 18,000 per year.
Good Agricultural Practices (GAP)
(no adoption of organic farming)
2 acres | Acres Under Conventional: 2 20,000 Rs
Profit: 18,000 Rs
1 acres 15,000 Rs
Desired Organic Acres: 0 10,000 Rs
0 acres
0 4 8 12 16 20 24 28 32 36 40
Time (year)
Figure 8: Dynamics of Good Agricultural Practices (GAP Farming)
Over Fertilization
Figure 9 and Figure 10, below, show model behavior under over fertilization. In this
case, the farm begins under conventional farming with no fertilizer use until year 10,
followed by arise in Percent of Required Fertilizer Applied, adimensionless
quantity, from zero to two (i.e., 0-200%) between years 10-30, and then remaining at
200% for the rest of the run. In other words, each plot below can be viewed in two halves:
under fertilization occurs when the fertilizer applied is below 1, and over fertilization
occurs when above 1.
In Figure 9, we see the farmer switch from conventional to organic farming when over
fertilization reaches nearly 180%. The binary choice formulation of the relative attractive-
ness of the two systems, discussed above, builds in certain hysteresis, which can be seen in
the real world. As many factors affect agricultural productivity, farmers tend to wait and
watch before deciding to switch.
Figure 10, presented right below Figure 9 for easier visualization of under and over
fertilization scenarios, shows the behavior of yields and profits from two systems. At year
10, when the Percent of Required Fertilizer Applied begins to rise above
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zero, farm productivity increases, and the Conventional Yield (in Quintal, Q),and
hence the Conventional Profit (in rupees, Rs), rise until about year 14. After this
point, yield (and hence revenue) saturates, even though the fertilizer application continues
to rise (see years 14-24), whereas the profit plummets because of the rising cost of
fertilizer. When very high amounts of fertilizer are applied, Conventional Yieldalso
plummets, and the farmer switches to organic farming with proper application of manure.
2° acres
2 Dmnl
\ acres Under
Conventional
1 acres
1 Dmni 1
% of Required j
Fertilizer Applied 1 Acres Under
i Conventional
1
0 acres Under Fertiliza j Over Ferfilization
0 Dmni L
4 8 12 16 20 24 28 32 36 40
Time (year)
Figure 9: Over Fertilization and Switch to Organic Farming
30,000 & Organic
D Deal Yield (Q)
Conventional Yield (Q)
22,300 Rs
60 Q
1.5 Dmnt_ | Conventional Profit (Rs)
Organic
a Ay Profit (Rs)
1 Dmnl
% of Required
es a Fertilizer Applied
5 Dmni \
eS Under Ferilizapén \ Over Fert}lization
0 Dmni 4
4 8 2 16 20 24 28 32 36 a
Time (year)
Figure 10: Over Fertilization, Yields and Profits
Base Run: Worse-Before-Better
One commonly cited situation in which organic farming becomes more attractive
than conventional farming is when excessive amounts of chemical fertilizer have
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been applied, degrading soil health and subsequently decreasing yields. We use this
common condition to produce our base case. To produce this base case, we set the
fertilizer use at a threshold> beyond which the economics of organic farming become
more attractive than those of conventional farming and a transition to organic
occurs. The excessive use of fertilizer causes soil health to degrade, thereby causing
conventional per acre yields to decrease. The transitioned is enabled by an
exogenous switch at time ten to produce a more controlled condition that we will
study under sensitivity in the following sections. The lower yields, combined with
increased costs of fertilizer, cause profits to drop to a value of Rs. 3,600 (i-e., much
smaller than the maximum possible profit of Rs. 18,000).
Total Farm Profits
20,000
15,000 Profit Reaches
Rs18,000
2 10,000
5000
0 4
o 4 8 (2 6 20 2 28 32 36 40
Time (year)
Worse-Before-Better Dynamics
Organic Adoption Begins
3600 \ S77
3550 \ PA Depth of WBB
Total Profit Trough
(Rs) (Loss in Profits)
saso rofit Exceeds
Pre-Adoption Level
3400: Duration of WBB
(Time to return to pre-transition profits)
Df oP oP GP AP GP OP NP OO Pv
easy Og os s
oF NPP PP FAP
Years Into Transition
Figure 11: Before-Better Dynamics of Transition Due to Excessive Fertilizer Use
Figure 11, above, shows how excessive chemical use can trigger adoption of
organic practices, and the associated worse-before-better dynamics (WBB) that
5 Current model calibration experiences this threshold when fertilizer use is 180% of required, and
cost of fertilizer comprises 30% of total costs.
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occur during the transition to organic farming. During the transition, WBB behavior
occurs as initially soil health is degraded and yields suffer, and ultimately effective
use of manure-based fertilizers restores soil health and increases yields. Over the
first six months of the transition, profits decrease as it takes time for the application
of manure to replenish the depleted organic carbon. However, as soil health
recovers, the organic yield surpasses the previous conventional yield, the farmer no
longer has to pay for inputs, and profits soon recover and, after two years reach Rs.
3,605, exceeding the pre-transition level. As soil health continues to develop and
more land is moved into organic practices, profits continue to increase, eventually
reaching Rs. 18,000.
Two parameters are of interest in studying the WBB Dynamics. First is “Duration
of WBB,” the time it takes for Total Profit to equal or surpass its pre-adoption value.
Second is “Depth of WBB Trough,” the difference between the pre-adoption value of
Total Profit and the lowest value of Total Profit during the WBB phase.
Both of these parameters determine the level and duration of economic losses that
farmers must endure when transitioning to organic farming. Several factors affect
these parameters and determine the severity of the WBB period. We will now study
the impact of these factors on WBB dynamics.
Sensitivity Analysis: Impact of Parameters on WBB
Below, we discuss the sensitivity of WBB dynamics to four different conditions: degree of
over fertilization prior to switching, cost of organic inputs, time to improve soil health, and
the rate at which the farmer adopts organic farming.
Impact of the Level of Over Fertilization and Feasibility of Switching
Figure 12, below, shows how the level of over fertilization that a farmer has indulged in
prior to switching to organic farming affects the duration and the depth of the WBB trough.
This plot is produced by exogenously varying the percent of fertilizers applied relative to
that required.
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Total Profit
20,000
10,000
| No Over Fertilization (OF) ZZ
g 0 fisocor—t (a)
Depth of WBB
Trough
-10,000
-20,000 t Duration of WBB 1
9 10 11 12 13 14 15
Time (year)
Average Soil Health
8
6
Below Threshold Over Fertilization (OF) 7
= 180% OF
B4 aS
195% OF —
(b)
2
0
9 10 11 12 13 14 15
Time (year)
Figure 12 a, b: Impact of Excessive Chemical Fertilizer Usage on Profits and Soil Health during WBB
Figure 12(a) shows that the level of initial over fertilization has a profound impact on
the viability of transitioning to organic farming for a smallholder farmer. First, excessive
fertilization can turn farming into a losing proposition to begin with (i.e., negative Total
Profit), and enduring a subsequent WBB transition would be further devastating for a
smallholder farmer. This situation is not imaginary; it has been witnessed in cases where
smallholder farmers get trapped in extreme indebtedness, and often consider ending their
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lives.® In such situations, short-term financial assistance is necessary for farmers to endure
WBB dynamics. Conversely, we observe that it is best to transition to organic farming when
soil health has not yet degraded severely (see 180% OF plot in Figure 12 a, b). Transition-
ing at such a juncture reduces the depth of trough, potentially making it affordable for a
smallholder farmer. It also allows for sufficient time for the transition.
As such, the above insight is qualitative—meaning, it is not about the exact value of
overfertilization as much as extreme vs. low levels of it. However, it is noteworthy that,
unfortunately, such discussion about over fertilization and its impact on the feasibility of
transition to organic farming is absent in the existing literature.
Impact of Organic Costs
There are a number of factors that influence the characteristics of the WBB transition
under excessive chemical use. The base scenario described above assumes that the cost of
organic farming is the same as that of conventional farming (i.e., Rs. 15,000 minus the cost
of excessive fertilizer). However, organic farmers may experience higher costs, for example
from increased labor requirements for weed and pest management (FAO, 2002; Foster et
al., 2006), or because purchase of off-farm manure is necessary. In contrast, the cost of
organic farming may be lower, for example in cases where on-farm labor and manure are
available or when water requirements are reduced as soil health develops (IAASTD, 2008).
Figure 13, below, shows the WBB dynamics under changes to organic costs (i.e., 10% and
20% cost increases and decreases).
Total Profit with Variation in Organic Costs
15,000
20% decrease
Profit 10% decrease
(Rs) 10,000 Base (15,000 Rs)
10% increase
20% increase
5000
2
11
Time (years)
Figure 13: Changes to WBB Dynamics with Variation in Organic Costs
As the cost of organic farming increases, the duration of the WBB period increases
significantly, and the depth of the WBB period increases slightly (Figure 13). Conversely, as
6 Unfortunately, farmer suicides in India have received much press
(https://en.wikipedia.org/wiki/Farmers%27_suicides_in_India). While reasons behind this phenom-
enon are complex, low farm productivity due to excessive reliance on chemicals is certainly one of
them.
22/30
costs decrease, the farmer experiences a shorter, slightly less severe drop in profits during
the WBB period. For a smallholder farmer, understanding, and reducing, the costs
associated with organic farming can increase the viability of transitioning to organic
farming. Further, policies such as subsidies for organic inputs, or village-level infrastruc-
ture to support organic farming (i.e., organic manure production and distribution from cow
shelters), could significantly improve farmer profits during transition to organic farming.
Impact of Time to Improve Soil Health (i.e., Efficiency of the Package of Practices)
The dynamics of the transition to organic farming also change depending on how long it
takes the soil health to develop. Figure 14, below, shows the dynamics of the WBB period
for soil health development times between one and five years.
Total Profit with Variation in Soil Health Development Times
15,000
year
., 10,000
Profit !9:0%
Base (3 years)
(Rs)
4 years
5 years
5000
9 10 11 12
Time (years)
Figure 14: Changes to WBB with Variation in Soil Health Development Times
As the time for soil health to develop increases, the depth and duration of the WBB
period increase, reducing farmer profits and decreasing the viability of transition to
organic farming. There are many factors that influence the time necessary for soil health to
develop under organic farming. The maximum achievable yield is not necessarily the same
across organic and conventional practices, and further, achievable yield depends on the
package of practice a farmer adopts and is capable of following through. For example,
research indicates that the achievable performance (i.e., yield) of a farming system depends
on the type and appropriateness of the seeds with respect to the farming context (Murphy
et al., 2007)’. Further, the amount of manure applied relative to the amount needed will
impact soil health development time. Farmers may not know how much manure they need
to apply, or may not have sufficient manure available. Finally, variation in soil types (e.g.,
7 Under the current model calibration, a full transition to organic does not occur unless the max or-
ganic yield is within 9% of the max conventional yield. As only a partial transition occurs, a sensitivi-
ty analysis is not included, despite the presence of worse-before-better behavior.
/30
across regions) and cropping patterns will impact the rate at which soil health develops.
Additional research on soil health development times across organic farming conditions in
India, as well as best practices for effectively communicating this information to smallhold-
er farmers, is therefore necessary to create conditions under which soil health develops
optimally, and farmers can experience less severe WBB periods.
Impact of Adoption Rate
The rate at which a farmer adopts organic practices also impacts the dynamics of the
WBB period during transition. Figure 15, below, shows how faster adoption creates a
deeper, but shorter, WBB period.
Total Profit with Variation in Rate of Organic Adoption
8000
6 month adjustment time
6000 Base (1 year adjustment time}
1.5 year adjustment time
2 year adjustment time
2.5 year adjustment time
Pr
ro
9 10 11 12
Time (years)
Figure 15: Effect of Adoption Rate on WBB
The depth of the drop in profits is determined by the amount of land that is initially
transitioned. When the transition begins, the yield from the land in transition will fall, as it
is no longer receiving synthetic fertilizer and has not yet had time to build soil health under
organic practices. It may therefore be tempting for a farmer to leave some land under
conventional practices, thereby lessening the steepness of the drop in income, and
extending the total time of the transition. This extension may ultimately be detrimental,
however, as it takes longer for the farm to return to the same levels of yield and therefore
profits. This occurs because when the conventional land is ultimately transitioned, it will be
ina worse (i.e., more degraded) condition, thereby increasing the time it takes to build soil
health, increase yield, and achieve profitability. A farmer will therefore realize the
maximum total yields more quickly if more acres are transitioned earlier. This makes
sense, as soil health does not start to develop until land is placed under organic practices
and manure is applied, thereby building organic carbon in the soil, and ultimately
improving yields. This means that if a farmer can survive the short-term loss in profits, it is
advantageous to initially, quickly, convert land to organic. Policies and training programs
that help farmers understand these tradeoffs in context of their individual situations will
24/30
therefore have significant positive impact on a farmer’s ability to minimize WBB dynamics
during transition.
Impact of Health-Based Transition on WBB
Farmers in India are increasingly concerned about the health risks introduced by
excessive chemical fertilizer use. As chemical exposure increases and farmers attribute
health problems to conventional farming practices, organic farming becomes more
attractive. Field observations and interviews indicate that perceived health risks are often
strong enough to motivate farmers to adopt organic practices. Figure 16, below, shows the
transition to organic farming under high-levels of perceived health hazard. This plot looks
very similar to the Adoption Rate Sensitivity plot above (Figure 15) with one notable
difference: the total profit at the time of transition in the plots below is Rs. 18,000 (the
maximum possible profit). In other words, in Figure 16, below, the transition to organic
farming is purely due to motivational factors, not economics. However, the resulting
economics of WBB are considerably different. When farmers perceive extreme health
hazards and transitions to organic farming rapidly, the depth of trough, or the losses they
incur, are large- nearly 50%. Yet, the total profits in this case are much higher than in all
above cases, as farmers do not experience an initial drop in profitability due to excessive
fertilizer use and the associated cost increases.
Total Profit
20,000
Low but Perceivable
Exogenous
Health Hazard
17,250
fe 14,500
11,750
Extreme
Exogenous
Health Hazard
9000
9 10 11 12 13 14 15
Time (year)
Figure 16: Transition to Organic Farming due to Perceived Health Risks
CONCLUSION
In this final section, we present a summary of the findings, as well as limitations and
suggestions for further research and model expansion.
25/30
Summary and Implications
The dynamic model developed in the current effort demonstrates the necessary condi-
tions for worse-before-better dynamics during transition from conventional to organic
farming, as well as conditions under which transition is more viable. When a farmer uses
excessive quantities of synthetic fertilizer, soil health degrades and both yield and total
profit decrease. Once a threshold is reached, organic farming can become a more attractive
option. If a farmer transitions to organic practices under these conditions, worse-before-
better behavior will ensue. The viability of a transition to organic farming depends upon
organic farming conditions and practices. Specifically, the per acre cost of organic farming,
time for soil health to recover, and rate at which land is converted, can decrease or increase
the duration and depth of the worse-before-better trough, as well as the profit level
ultimately achievable. Figure 17, below, summarizes the results of the above sensitivity
analyses in terms of both the duration (i-e., time to return to re-transition profitability,
shown on the x-axis) and depth (i.e., loss in profits, shown on the y-axis) of the WBB period.
Sensitivity Analysis Summary:
Effect of Time to Build Soil Health, Organic Costs, and Adoption Rate
1400
Default Case:
1 yr adoption AG me .
1200 3 yr to build soil health air
15000 Rs in Organic costs We
1000 ne]
109
Depth of WBB yr, 10% Bee rons
Trough (Rs) 800 = > ; ise "
20%
[Profits Lost] a SH Times
600 ive BISY [Organic Costs
‘.Adpotion Rate
400
o os 1 1s 2 258 3 35 4 45
Duration of WBB (yrs)
[Time to return to pre-transition level of profits]
Figure 17: Effect of Soil Health Times, Organic Farming Costs, and Adoption Rate on WBB Depth and
Duration
Decreasing soil health development time (blue diamonds, above), for example through
effective application of farming practices and optimal selection of inputs, can reduce both
the depth and duration of the WBB period. Similarly, decreasing the cost of organic farming
(red squares, above), for example by using on-farm inputs such as byproducts of animal
husbandry, can improve profitability during the WBB period. Finally, smallholder farmers
can impact the depth and duration of the WBB period by controlling the rate at which they
adopt organic practices (green triangles, above). The rate of adoption has a strong
correlation with soil health development time: adopting organic practices slower than the
rate at which soil health develops will increase the duration but decrease the depth, while a
faster adoption will decrease the duration but increase the depth. The above dynamic
26/30
complexity suggests that policies and training programs that help farmers to not only
understand these tradeoffs, but also create optimal transition conditions, are therefore
necessary to enable farmers to transition to organic farming with minimized WBB
dynamics.
Organic farming may also become attractive for non-economic reasons; however, a
farmer’s motivation must be sufficiently strong to induce adoption. Abrupt transition due
to motivational factors can have significant losses (i.e., deeper WBB trough), but transition-
ing at an appropriately slow rate will keep overall profits higher. As such, voluntary
transition due to motivational reasons is far better than that after delinquency from
excessive fertilizer use. Excessive fertilizer use, a condition that happens frequently with
smallholder farmers in India (IAASTD, 2008), is not only extremely detrimental to the
environment and the health of farmers and their families (Yedla and Peddi, 2003;
Amundson, 2015), but can also significantly exacerbate the loss of profits during transition
to organic farming, or even make transition untenable. It is therefore important to educate
farmers about the crucial importance of following optimal fertilizer regimens in order to
maximize both profitability and health.
Overall, this research observes that, while organic farming promises environmental and
health benefits, easing the adoption of organic practices requires understanding and
systematically managing the economics of the transition (i.e., the WBB scenario). In India,
farmer behavior may be influenced by numerous context-dependent factors; however, in
the end a single farmer ultimately decides how to allocate his land along the spectrum of
available agricultural practices-- a decision that, collectively, has a global environmental
impact. Consequently, conditions must be created for them to perceive the transition to
organic farming economically attractive and viable. Currently, the economics of worse-
before-better scenario are unfavorable for transition to organic farming under the
conditions of excessive fertilization, inadequate package of practices, and miscalculated
rates of adoption. Understanding these factors and devising policies to manage them is
necessary to enable individual farmers to mitigate the risk of transitioning to organic
farming. Our effort in this research take a step in the direction of assisting policymakers
and NGOs in enabling smallholder farmers to transition to more sustainable and profitable
agriculture.
Limitations and Next Steps
The current model, while useful, can be improved to overcome its limitations. Future
work is necessary to refine and expand the dynamic model, including:
+ Use a three-stock aging chain to explicitly differentiate acres in transition and
the soil health dynamics associated with transition. Using three stocks will rep-
resent both the physical dynamics-- that soil in transition is still recovering from
chemical practices, while soil under organic practices has developed soil health--
and perceptions such as farmer and certification distinctions between organic
production and land in transition.
o Allow conversion back to organic to capture conditions under which,
and effects of, farmers abandoning organic practices.
27/30
Incorporate additional management techniques. For example, the
combined use of synthetic fertilizer and manure has been shown to be
more effective than either treatment alone (Bajpai et al., 2006; Singhal et
al., 2012). Similarly, tilling, cover cropping and intercropping practices
change soil health dynamics and costs. Additional data collection on the
ranges of variable and fixed costs and management practices is necessary,
as costs associated with both conventional and organic farming also de-
pend on the farming context and practices (Nemes, 2009).
Represent multiple seasons, as farmers plant more than one crop per
year (e.g., wheat and cotton rotation), and complementary crop combina-
tions can complement each other to enhance soil health (e.g., legumes fix-
ing nitrogen).
Move beyond yield per acre of a single crop, as total productivity is a
more accurate metric for determining profitability in organic systems
(Seufert, 2012).
Include a learning curve structure to capture how a farmer can reduce
costs as experience accumulates (Sterman, 2000).
Explicitly model market dynamics for organic products. Local buyers
may be willing to pay price premiums for organic products as they devel-
op trust in the farmer’s practices. Certification may also allow a farmer to
sell organic products at a premium to institutional buyers.
Incorporate motivation for conventional farming, including chemical
company advertising and government subsidies for fertilizer and seeds.
Debt dynamics, for example borrowing to cover the cost of synthetic in-
puts, should also be modeled.
28/30
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