A Multi-Factor analysis of profitability drivers of local rabbit production in Zamboanga Peninsula Region, Mindanao , Philippines

Abstract

Literature supporting empirical evidence on the financial viability of rabbit production in the Philippines is limited. This study was conducted to examine the profitability drivers of rabbit production in the Zamboanga Peninsula, focusing on its potential as a sustainable alternative to traditional livestock production, protein source and its capacity to augment household income. The research employed MRL (multiple linear regression) analysis to identify key factors influencing profitability, utilising a sample of 123 rabbit raisers randomly selected from the list in the Provincial Agriculture Offices. Data were collected during the first half of 2024 through personal interviews with the aid of an interview schedule validated by experts. Model specification was done to ascertain heteroscedasticity and multicollinearity issues in the data. The loglog model for expense categories and log-linear for profitability drivers having the lowest Akaike information criteria (AIC) were chosen for its better fit, providing a more accurate representation of the data. Results indicate that larger farms achieve significantly higher gross and net incomes, benefiting from economies of scale. Expense categories such as feed cost, veterinary expenses and labour costs positively and significantly influenced profitability, while outlay on utilities and cost of stocks negatively affected financial performance. The study also revealed that farming experience, feeds used, training attendance, breed type and marketing practices do not significantly influence profitability, implying that management practices and operational scale are more important considerations for rabbit profitability. Knowing the relationship and influence of these profitability drivers of rabbit production can help identify strategies to optimise returns, support the adoption of rabbit farming and improve the livelihoods of rural households in Philippines. The findings suggest the expansion of rabbit farming operations of up to more than 100 head per farm to optimise profitability.

Full text

World Rabbit Sci. 32: 279-293 279
MULTI-FACTOR ANALYSIS OF PROFITABILITY DRIVERS OF LOCAL RABBIT PRODUCTION IN
ZAMBOANGA PENINSULA REGION, MINDANAO, PHILIPPINES
Rovelito L. Narita
Department of Agribusiness, College of Business Administration, Jose Rizal Memorial State University, Tampilisan Campus, Tampilisan,
Zamboanga del Norte, 7116 Philippines.
Abstract: Literature supporting empirical evidence on the financial viability of rabbit production in the
Philippines is limited. This study was conducted to examine the profitability drivers of rabbit production
in the Zamboanga Peninsula, focusing on its potential as a sustainable alternative to traditional livestock
production, protein source and its capacity to augment household income. The research employed MRL
(multiple linear regression) analysis to identify key factors influencing profitability, utilising a sample of 123
rabbit raisers randomly selected from the list in the Provincial Agriculture Offices. Data were collected during
the first half of 2024 through personal interviews with the aid of an interview schedule validated by experts.
Model specification was done to ascertain heteroscedasticity and multicollinearity issues in the data. The log-
log model for expense categories and log-linear for profitability drivers having the lowest Akaike information
criteria (AIC) were chosen for its better fit, providing a more accurate representation of the data. Results
indicate that larger farms achieve significantly higher gross and net incomes, benefiting from economies of
scale. Expense categories such as feed cost, veterinary expenses and labour costs positively and significantly
influenced profitability, while outlay on utilities and cost of stocks negatively affected financial performance.
The study also revealed that farming experience, feeds used, training attendance, breed type and marketing
practices do not significantly influence profitability, implying that management practices and operational scale
are more important considerations for rabbit profitability. Knowing the relationship and influence of these
profitability drivers of rabbit production can help identify strategies to optimise returns, support the adoption
of rabbit farming and improve the livelihoods of rural households in Philippines. The findings suggest the
expansion of rabbit farming operations of up to more than 100 head per farm to optimise profitability.
Key Words: economies of scale, multiple linear regression, rabbit raising, profitability, Asia.
INTRODUCTION
In the Philippines, addressing poverty and ensuring food security remain significant challenges. Given its dense
population and a significant portion residing in rural regions, securing access to nutritious food is imperative to
enhance livelihoods and mitigate food insecurity (Bairagi etal., 2022).
As a response to the challenging impact of poverty, nutrition and the need for alternative protein sources, the
Department of Agriculture (DA) has turned its attention to rabbit farming as a viable solution. The onslaught of African
Swine Fever, which has significantly impacted the local pork industry, leading to soaring pork prices, heightened the
urgency to explore alternative sources of meat and income for Filipino households (Gomez, 2024). Rabbit farming
emerges as a promising avenue to address this pressing issue.
World Rabbit Sci. 2024, 32: 279-293
https://doi.org/10.4995/wrs.2024.21913
WRSA, UPV, 2003
Cite as: Narita R.L. 2024. Multi-Factor analysis of profitability drivers of local rabbit production in Zamboanga Peninsula Region,
Mindanao, Philippines. World Rabbit Sci., 32: 279-293. https://doi.org/10.4995/wrs.2024.21913
Correspondence: R.L. Narita, rovelito.narita@jrmsu.edu.ph. Received June 2024 - Accepted August 2024.
https://doi.org/10.4995/wrs.2024.21913
World
Rabbit
Science

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World Rabbit Sci. 32: 279-293280
The Department of Agriculture in their directives suggest Filipinos should venture into rabbit raising as an alternative
source of income and protein. The agency’s MC No. 20 s. 2022 (Department of Agriculture, 2022) acknowledges the
increasing interest of many Filipino farmers in raising rabbits for meat production due to the ease in propagation and
minimal production costs and hence the agency has initiated eorts to support importation of rabbit breeding stocks.
The endeavour to explore alternative sources of income and food, such as rabbit farming, arises from various factors.
Challenges like diminishing agricultural land, environmental limitations and the repercussions of natural calamities
often impede conventional livestock production methods. As a result, households seek alternative avenues to augment
their income while diversifying their food sources.
Rabbit farming has the capacity to contribute significantly to Sustainable Development Goals objectives such as
reducing poverty, enhancing food and nutrition security, and ultimately striving towards the goal of zero poverty
(United Nations, 2024)
The profitability of smallholder agribusiness ventures, particularly in the context of rabbit production, has garnered
considerable scholarly attention worldwide. Studies such as those by Karikari and Asare (2009) provided an economic
analysis of smallholder meat rabbit production in Ghana, highlighting that intensive breeding programmes could
significantly enhance profitability, evidenced by a shorter payback period and increased annualised rate of return.
Wongnaa etal. (2023a) explored the viability of commercialising rabbit production, noting that commercialised rabbit
producers in Ghana exhibited higher gross margins and net income compared to non-commercialised producers. This
study also emphasised the integration of rabbit production with other enterprises and the importance of institutional
support for market infrastructure and governmental policies. Complementing this, Mukaila (2023) investigated the
economic performance of small-scale rabbit production in Nigeria, revealing that stock size, education and labour
availability positively influenced profitability, while mortality and feeding costs were significant negative factors.
Adanguidi (2020) analysed the profitability and competitiveness of rabbit value chains in Benin, and found that
processed rabbit meat was the most profitable and competitive, with feed outlay constituting a significant portion
of production costs. Meanwhile, Paladan (2022) identified management practices as a critical component in rabbit
farming in the Philippines, noting that inadequate knowledge and market reliability posed significant challenges.
The socioeconomic characteristics influencing rabbit production profitability were further examined by Adedeji etal.
(2015) in Nigeria, who found a positive correlation between gross margin and years of experience, despite the
constraint of an unreliable market.
Dionisio et al. (2023) highlighted the demographic characteristics and marketing practices of rabbit raisers in the
Philippines, revealing that most of them sold live animals primarily at their residences during the pandemic due to
safety related concerns. Wongnaa etal. (2023b) also investigated the welfare impacts of commercialising rabbit
production in Ghana. Findings revealed that commercialisation led to increased household income and reduced food
expenditure, though non-food expenditures were higher.
Zamaratskaia et al. (2023) underscored the potential of rabbit meat in maintaining food security in Ukraine,
emphasising its ecient feed conversion and lower resource usage compared to traditional meats. However, Esmail
etal. (2023) noted that consumer acceptability of rabbit meat in the Philippines was hindered by its limited market
availability.
Ayeni etal. (2023) demonstrated the positive impact of rabbit production on rural household income in Nigeria,
identifying factors such as age, extension interactions and credit access as significant determinants of income.
Despite these studies, a gap remains in empirical evidence regarding the profitability and sustainability of rabbit
farming in the Philippines, particularly in the Zamboanga Peninsula Region. Understanding the specific drivers of
profitability and the challenges faced by rabbit farmers in this region is essential for guiding policy interventions and
supporting the growth of the industry.
To better understand the financial dynamics of rabbit farming, this study draws on the concept of economies of scale.
Economies of scale refers to the cost advantages that enterprises gain as they increase their scale of operation,
leading to lower per-unit costs (Smith, 1776, as cited in Samuelson & Nordhaus, 2010). Originally introduced by

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World Rabbit Sci. 32: 279-293 281
Adam Smith in the Wealth of Nations through the pin factory example, the concept explains how increased production
volumes can enhance profitability by spreading fixed cost over more units. The relationship is central to the profitability
analysis in this study, as it examines how larger operations can achieve better economic outcomes.
In the case of rabbit farming, economies of scale can play a significant role in driving profitability. Larger farms are
likely to benefit from various factors that reduce the average cost per unit of output, including fixed costs distribution,
specialisation and eciency, market access and bargaining power. Larger farms can spread fixed costs (e.g., housing,
equipment) over a greater number of rabbits, reducing the cost per rabbit. Larger farms often have the advantage of
purchasing feed and other inputs in bulk at lower prices. As farms increase in size, they may adopt more specialised
production techniques and management practices that enhance eciency and output. Larger operations might have
better access to markets and greater bargaining power, allowing them to secure better prices for their products and
inputs.
Recognising the imperative of addressing this need, this study is conceptualised to provide concrete insights into
the profitability of rabbit farming for farmers and enthusiasts. It draws upon the experiences of rabbit raisers who
participated as respondents, thereby contributing valuable empirical evidence to the scientific literature on rabbit
production in the country. This study specifically addresses research questions such as: Which specific expense
category in rabbit production exhibits the highest or has the most significant impact on profitability? Does profitability
vary significantly among small, medium and large-scale production levels? How do various factors such as years of
experience, rabbit breed, feed types, marketing practices and training attendance collectively impact profitability in
the local rabbit production of Zamboanga Peninsula Region, Philippines?
MATERIALS AND METHODS
Study area
Zamboanga Peninsula, located in the southern part of the Philippines, comprises three provinces: Northern
Zamboanga, Zamboanga Sibugay and Southern Zamboanga (Figure 1).
The region is characterised by a tropical climate, with significant rainfall throughout the year and a pronounced
dry season. Agriculture is a major economic activity, with the region known for its diverse crops, predominantly
rubber, coconut and rice (PhilAtlas, 2024). Livestock farming, particularly rabbit raising, is emerging as an important
supplementary source of income for many households (Braganza, 2024). The area’s population is predominantly
rural, with a rich cultural heritage and a strong sense of community.
Figure 1: Map of Zamboanga Peninsula, Philippines (Google Maps, 2024).

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World Rabbit Sci. 32: 279-293282
Sampling procedure and data collection
The study employed a multi-stage random sampling technique, obtaining 123 rabbit raisers as respondents from the
top 5 producing municipalities among the three provinces of the region. Sample size was determined using Cochran’s
formula. Participants were located through coordination with local agricultural oces and barangay (neighbourhood)
key informants, usually the barangay or village ocials. They were reached personally in their homes and in their
farms. Data gathering occurred from January to May 2024.
The interviews were conducted using a pre-structured questionnaire, which was validated by experts in the field
to ensure its relevance and inclusiveness in capturing the necessary information regarding rabbit production. The
questionnaire was divided into two main sections. The first section collected data on the respondent’s socioeconomic
and demographic characteristics, including age, gender, education level, household size and income source. The
second section focused on the financial aspect of rabbit production, where respondents provided detailed information
on cost incurred (such as feed, labour and veterinary expenses) and returns derived from rabbit raising. For the
financial data, respondents were asked to recall their cost and revenues from the last six months, ensuring that
information gathered reflected recent and relevant experiences.
Participation in the study was voluntary and informed consent was obtained from all respondents prior to their
inclusion. Respondents were assured of anonymity and confidentiality of their responses and data were collected and
handled in accordance with ethical standards to protect the privacy and rights of the participants.
Data treatment
Expense Category
Profitability is analysed using several financial metrics like Net Profit, Gross Profit Margin, Return on Investment (ROI),
and Per Unit Profit. These metrics were chosen to capture dierent aspects of profitability, to provide a detailed picture
of the economic health and eciency of rabbit raising.
Net Profit was calculated as the dierence between total revenue and total expenses, reflecting the actual profitability
after accounting all the costs. Gross Profit Margin is the percentage of revenue that remains after subtracting the
variable costs (i.e., feed, veterinary expenses and labour), indicating how eciently the operation generates profit
from its income. ROI measured the profitability of the investment in rabbit raising, indicating how well the investment
was utilised to generate profits. Per Unit Profit calculated the profit generated per rabbit, helping to understand
profitability at a micro-level.
To determine the impact of each expense category on profitability, MRL analysis was employed. This statistical
technique allows for estimation of the relationship between the dependent variable (profitability) and multiple
independent variables (expense categories).
The original regression model is expressed as follows:
Profitability= β0+β1 FeedCosts+β2CostofStocks+β3VeterinaryExp+β4InfrastructureInvt+
+β5LabourCosts+β6Transpo Exp+β7Utilities Exp+ε (1)
where: β0 is the intercept; β1…7 are the coecients for each expense category; and ε is the error term.
Determinants (Drivers) of Profitability
The dependent variable in this study, profitability, is a continuous variable representing the net profit from rabbit
production. The independent variables were treated as follows:
Production level. A categorical variable which was divided into three categories based on the number of rabbits raised:
small farms (<50 head), medium farms (51-100 head), and large farms (>100 head). This categorisation allowed for
the analysis of profitability across dierent scales of production.
Years of Experience. This continuous variable captured the number of years the farmer had been involved in rabbit
raising, providing insight into how experience impacts profitability.

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World Rabbit Sci. 32: 279-293 283
Breed Type. This categorical variable was coded to reflect dierent breeds of rabbits raised, such as 1 for New
Zealand White, 2 for American Chinchilla; 3 for Satin Rabbit; 4 for Flemish Giant; 5 for Champagne d’Argent. This
coding facilitated the examination of breed-specific eects on profitability.
Feeds Used. Various feed types used by the farmers were categorised, such as 1 for commercial pellets; 2 for forages
or cut and carry; 3 for combination. This is to analyse their impact on production eciency and profitability.
Marketing Practices. Dierent methods used for marketing rabbit products were categorised, such as 1 for Relationship
Marketing/word of mouth; 2-Direct selling; 3- Buyer contact (physical), 4- Internet/Social Media Marketing; to assess
how marketing strategies influence profitability.
Training Attendance. This categorical variable indicated whether the farmer had attended any training sessions on rabbit
production (coded as 1 for Yes and 0 for No), allowing for the analysis of the eect of training on rabbit profitability.
The original regression model is expressed as follows:
Profitability= β0+β1Production level+β2Years of Raising Rabbit+β3Breed Type+β4Feeds used+
β5Marketing Practices+β6Training Attendance+ε (2)
where: β0 is the intercept; β1…6 are the coecients for the determinants of profitability; and ε is the error term.
Model specification for expense categories and profitability
The primary statistical analysis used in this study was MRL (multiple linear regression), which allowed assessment of
the impact of various independent variables on the dependent variable, profitability.
To ensure the robustness and validity of the regression model, the researcher explored four functional forms: linear,
log-linear, linear-log and log-log models. These dierent functional forms were tested to determine the best model
specification. The selection criteria for the best model included adjusted R², mean squared error (MSE), log-likelihood
ratio and Akaike information criteria (AIC).
Based on these criteria, the log-log model was identified as the best model to use. The log-log model had the lowest
AIC value, and log-likelihood suggesting it provided the best fit for the data among the four functional forms. Although
the adjusted R² was not the highest, the log-log model resolved issues of heteroscedasticity and multicollinearity
better than the other models. The significant P-values from the F-test also indicated that the model was statistically
significant (Table 1).
The transformed MRL model is based on the log-log model and is hence used in the discussion of results and is
specified below:
Log(Profitability)= β0+β1log(FeedCosts)+β2log (CostofStocks)+β3log (VeterinaryExp)+
β4log (InfrastructureInvt)+β5log (LabourCosts)+β6log (Transpo Exp)+β7log (Utilities Exp)+ε (3)
where: Log (Profit)- is the natural logarithm of the variable profit; β0 is the intercept; β1…7 are the coecients for the
determinants of profitability; and ε is the error term.
Table 1: Comparison of model fit statistic using the four functional forms on the expense categories of rabbit
production, Zamboanga Peninsula, 2024.
Model fit measures Linear-linear model Log-linear model Linear-log model Log-log model
Adjusted R20.912 0.344 0.580 0.485
F-test (prob>F) 0.00 0.00 0.00 0.00
MSE 6647.1 0.882 14475 0.780
Heteroscedasticity (hettest) 0.000 0.656 0.000 0.740
Multicollinearity (VIF*) 4.89 4.93 3.10 3.09
Log-likelihood –1253.03 –118.68 –1348.75 –107.13
AIC values 2522.062 253.368 2713.508 230.250
MSE: mean square error; VIF: variance inflation factor; AIC: akaike information criterion.

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Model specification for profitability drivers
In analysing the profitability drivers, independent variables included both continuous and categorical variables,
such as farm size, years of experience, breed type, feed types, marketing practices and training attendance. Since
most of these regressors are categorical variables, model transformation using the dierent functional forms is
not applicable.
Upon examining feasible functional forms, the log-linear model exhibits a significantly higher adjusted R² of 0.61
compared to 0.26 for the linear-linear model, indicating its superior ability to explain the variance in profitability.
Additionally, the log-linear model demonstrates a substantially lower MSE of 0.68 compared to 19 172 for the
linear-linear model, signifying its better predictive accuracy. The higher log-likelihood value of –94.44 for the
log-linear model, in contrast to –1383.85 for the linear-linear model, further supports its superior fit to the data.
Moreover, the multicollinearity issue was assessed using the variance inflation factor (VIF), and the Breusch-Pagan
test for heteroscedasticity. The log-linear model eectively addresses heteroscedasticity, as indicated by the
non-significant P-value of 0.89 for the heteroscedasticity test, whereas the linear-linear model exhibits significant
heteroscedasticity.
Heteroscedasticity refers to the problem where the variance of the residuals is not constant across all levels of the
independent variables. This can lead to inecient estimates and aect the validity of hypothesis tests. To address
this issue, the profitability data was transformed using a log-linear model. This transformation helps stabilise
the variance and improves the model fit and statistical power, making the regression results more reliable and
interpretable (Gujarati, 2021).
Lastly, the log-linear model boasts a substantially lower AIC value of 202.87 compared to 2781.71 for the linear-
linear model, suggesting a better balance between model fit and complexity. Consequently, considering these
comprehensive evaluations, the log-linear model emerges as the preferred choice for the final model specification.
The comparison of model fit statistics using linear and log-linear functional forms for profitability drivers of rabbit
production is shown in Table 2.
The transformed MRL model is specified as follows:
Log (Profitability)= β0+β1Farm Size+β2No of Years Raising Rabbit+β3Breed of Rabbit+β4Feeds Used+
β5Marketing Practices+β6 Training Attendance+ε (4)
where: Log (Profit) is the natural logarithm of the variable profit; β0 is the intercept; β1…7 are the coecients for the
determinants of profitability; and ε is the error term.
After the transformation, the model obtained a X 2=0.02 and (P<0.89) indicating that the heteroscedasticity issue
was resolved.
The analyses were carried out using Stata 18.0 software.
Table 2: Comparison of model fit statistic using linear and log-linear functional forms for profitability drivers of rabbit
production, Zamboanga Peninsula, 2024.
Model fit measures Linear-linear model Log-linear model
Adjusted R20.26 0.61
F-test (prob>F) 0.00 0.00
MSE 19172 0.68
Heteroscedasticity (hettest) 0.00 0.89
Multicollinearity (VIF) 1.05 1.07
Log-likelihood –1383.85 –94.44
AIC values 2781.71 202.87
MSE: mean square error; VIF: variance inflation factor; AIC: akaike information criterion.

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World Rabbit Sci. 32: 279-293 285
RESULTS AND DISCUSSION
Demographic characteristics of rabbit raisers
Rabbit raisers in the area are dominated by a young population, with 68.3% being 35 yr old or younger. This is
followed by 13.8% aged between 56 and 65 yr, and a very small proportion of 0.81% aged above 66 yr (Table3).
This trend towards youth involvement in rabbit farming aligns with findings from Mukaila (2023) in Nigeria, where
a significant portion of rabbit farmers were also found to be in their early adulthood, attracted by the relatively low
capital investment required and the potential for quick returns. Similarly, Chiron etal. (2022) found that younger
French rabbit farmers are more inclined to adopt innovative and pro-welfare practices compared to their older
counterparts. This finding highlights how age influences not only the decision to enter rabbit farming but also the
willingness to embrace new and improved practices, indicating that younger farmers are often more open to change
and innovation in their farming methods.
Gender distribution shows a higher number of male respondents, with 61.8%, compared to 38.2% female. This is
consistent with the gender dynamics observed in similar studies across various countries. For instance, Adedeji etal.
(2015) noted that men were more likely to be engaged in rabbit farming in Nigeria, a trend that may be attributed to
traditional gender roles in agriculture. However, the relatively significant participation of women (38.2%) in this study
signifies the potential gender-inclusive development in the rabbit farming sector.
Marital status revealed that 64.2% of rabbit raisers are married, while 34.2% are single. Only a small fraction is
widowed (1.6%). Ayeni etal. (2023) in Nigeria, has a similar finding that married individuals were more engaged
in smallholder rabbit farming. This could suggest that married individuals see rabbit farming as a stable source of
additional household income.
The majority of rabbit raisers come from small households, with 73.2% having 1 to 3 members, 21.9% having 4 to 7
members, and only 4.9% belonging to larger households of 8 to 10 members. This contrasts with studies from other
regions such as Wongnaa etal. (2023), where larger household sizes were common among rabbit farmers.
Educational attainment among rabbit raisers is relatively high, with 55.3% college graduates and 27.6% having
attended some college. Only a small portion have completed high school, with 10.57% high school undergraduate
and 4.1% high school graduates. This suggests that rabbit raisers in the study area are generally well-educated, in
contrast to the findings of Karikari and Asare (2009) that a significant number of rabbit raisers had a lower educational
level.
Experience in rabbit raising ranges from having 1 yr or less with 47.2, 43.9% with 2-3 yr, and only 8.9% having 4-5 yr
of experience. This indicates that many rabbit raisers are relatively new to the activity. This is consistent with Paladan
(2022), where many rabbit farmers in the Philippines were found to be new to the activity, possibly due to the growing
awareness and promotion of rabbit farming as an alternative livelihood. The low experience levels imply the need for
training and capacity building to improve productivity and profitability.
Membership in organisations is notably low, with only 14.6% belonging to a group. This is also true in the northernmost
part of the Philippines, as noted by Dioniso etal. (2023). The lack of organisational involvement could limit access
to resources, market opportunities and collective bargaining power, which are crucial for scaling up operations and
enhancing profitability.
When it comes to breeds, the New Zealand White utilised primarily for meat production is the most popular, raised by
68.3% of the respondents. Other breeds include American Chinchilla (6.5%), Satin Rabbits (4.1%), Flemish Giants
(4.9%), and Champagne d’Argent (8.1%). This diversity in breeds indicates a mix of purposes, including both meat
production and pet markets.
The experimental findings of Fadare and Fatoba (2018) indicate that the New Zealand White and Havana Black breeds
are particularly advantageous in humid tropical environments, demonstrating superior reproductive traits compared to
the Californian and Palomino Brown breeds. Understanding breed-specific performance can help in making informed
decisions regarding breed selection and programme implementation that would be best suited in local conditions in
tropical regions like the Philippines.

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Table 3: Demographic characteristics of rabbit raisers, Zamboanga Peninsula, Philippines, 2024 (n=123).
Characteristics Frequency (f) Percentage (%)
Age
1- 35 years and below
2- 36 to 45 yr
3- 46 to 55 yr
4- 56 to 65 yr
5- 66 yr and above
84
9
12
17
1
68.29
7.32
9.76
13.82
0.81
Sex
1- Male
2- Female 76
47 61.79
38.21
Marital status
1- Single
2- Married
3- Widow(er)
42
79
2
34.15
64.23
1.63
Household size
1- 1 to 3 members
2- 4 to 7 members
3- 8 to 10 members
90
27
6
73.17
21.95
4.88
Educational attainment
1- Elementary graduate
2- High School undergraduate
3- High School graduate
4- College undergraduate
5- College graduate
3
13
5
34
68
22.44
10.57
4.07
27.64
55.28
No. of years raising rabbit
1- 1 yr or less
2- 2-3 yr
3- 4-5 yr
58.
54
11
47.15
43.90
8.94
Organisation membership
1- Member (with)
2- Not a member (without) 18
105 14.63
85.37
Breeds raised
1-New Zealand White
2- American Chinchilla
3- Satin Rabbits
4- Flemish Giants
5 -Champagne d‘Argent
84
8
5
6
10
68.29
6.50
4.07
4.88
8.13
Average area used for rabbit production
1- 100 m2 and below
2- 101 m2 to 250 m2
3- 251 m2 to 500 m2
4- 501 m2 and above
99
6
6
12
80.49
4.88
4.88
9.75
Income source
1- Wage/salary
2- Property income
3- Farm income
4- Pension
46
24
50
3
37.40
19.51
40.65
2.44
Trainings attended on rabbit production
1- None
2- DA/govt agency sponsored
3- YouTube
4 - Facebook
99
4
15
5
80.49
3.25
12.20
4.07
DA: Department of Agriculture.

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World Rabbit Sci. 32: 279-293 287
Regarding the area utilised for rabbit production, 80.5% of raisers use spaces of 100m² or less, while only small
percentages use larger areas: 4.9% for both 101-250m² and 251-500m², and 9.8% for 501m² and above. This
implies that most rabbit farming operations are relatively small-scale. This is comparable to findings by Adanguidi
(2020) in Benin, where small-scale production was also prevalent. Small-scale operations could imply limited
production capacity, but they also entail easier management and lower overhead costs, which are critical factors for
new or resource-constrained farmers.
Income sources among rabbit raisers are diverse, with 40.7% relying on farm income, 37.4% on wages or salaries,
19.5% on property income and 2.4% on pensions. This means that rabbit raising is often supplemented by other
income streams or an additional or alternative source just like in Ghana, as reported by Wongnaa (2023b), where
rabbit farming is often supplemented by other income stream.
Training attendance related to rabbit production is low, as 80.5% of respondents have no formal training. A small
portion has received training from government agencies such as the Department of Agriculture (3.3%), while others
have turned to YouTube (12.2%) and Facebook (4.1%) for information. This is a common issue in many developing
regions, as mentioned by Zamaratskaia etal. (2023) in Ukraine, where lack of formal training was a significant barrier
to productivity. The critical need for formal training programmes is evident, as they are essential for improving rabbit
farming practices and profitability, particularly in regions where rabbit farming is still emerging as a mainstream
agricultural activity.
Cost and return analysis
Table 4 presents a comparison of the profitability across farms sizes: small (less than 50 head), medium (51-100
head), and large (greater than 100 head). Gross income, expenses, net income, gross profit margin, returns on
investment and per unit profit are scrutinised to determine trends in profitability among these categories.
Table 4 illustrates that as farm size increases, so does gross income. Large farms boast significantly higher gross
income figures compared to their smaller counterparts, indicative of their larger-scale operations and sales volumes.
This points to the potential advantages of scale in generating revenue within the agricultural sector.
Table 4: Average cost and return analysis of rabbit raising across farms in Php (1 PHP=0.016 EUR), Zamboanga
Peninsula, Philippines, 2024 (n=123).
Particulars
Small farms
(<50 head)
(n=74)
Medium
(51-100 head)
(n=44)
Large farms
(>100head)
(n=5)
Gross income 10 872.87 30 961.52 155 160.10
Less: (Expenses)
Cost of stocks 3383.03 11 545.45 33 000.00
Feed cost 1189.26 3794.57 11 900.00
Veterinary expenses 307.78 529.84 2100.00
Transport expenses 399.80 342.50 1180.00
Labour cost 3600.00 3600.00 23 240.00
Infrastructure expenses 345.14 463.47 2760.00
Utilities 189.18 309.81 1090.00
Total cost 9414.19 20 585.64 75 270.00
Net income (Profit) 1458.69 10 375.86 79 920.10
Gross Profit Margin 1803.82 10 839.35 82 650.10
Returns on Investment (%) 13.42 33.51 51.51
Per Head Profit 145.87 207.52 799.20

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World Rabbit Sci. 32: 279-293288
These findings align with the research by Tey and Brindal (2015), which states that larger operational scales and
greater operational eciency positively impact farm profitability. The study highlights that farms leveraging economies
of scale and enhancing input-output eciency tend to be more profitable. This is evident in the higher gross income
reported for larger farms in this study, which suggests that scaling up operations provides tangible financial benefits
and underscores the advantages of larger-scale agricultural practices in achieving improved revenue outcomes.
Moving on to expenses, it becomes evident that larger farms incur substantially higher costs across various categories
such as stocks, feed, labour and infrastructure. This is expected, as larger operations require more resources and
infrastructure to maintain and expand production. Despite these elevated costs, large farms manage to maintain
higher net incomes, underscoring their ability to eectively manage expenses and generate considerable profits.
Moreover, this corroborates the findings of Scialfa etal. (2022) in Argentina, which revealed that while small-scale
operations can contribute to farm diversification and income, they often face significant economic challenges. The low
profit margin per rabbit, as evidenced by the mere USD 0.06 per animal, stresses the importance of achieving higher
productivity and better feed eciency to enhance profitability. This reinforces the idea that while both large and small-
scale operations have the potential for profitability in rabbit farming, the scale of operation significantly influences the
degree of financial success and that small-scale operations must navigate the delicate balance of costs and returns
to remain viable and profitable.
The analysis of gross profit margin reveals that large farms outperform small and medium farms in terms of eciency
in cost management and revenue generation. Large farms exhibit the highest gross profit margins, indicating that
a significant portion of their revenue surpasses the costs associated with production. Baruwa (2014) provides a
comprehensive analysis of rabbit farming profitability in Nigeria, detailing that an enterprise with 100 matured rabbits
achieved the highest returns, with a profit margin of 41.06% and a return per Naira invested of 1.7. This highlights the
critical role of ecient cost management and revenue generation in achieving high profitability. He also emphasised
the benefits of economies of scale, as larger farms tend to show better financial performance.
Moreover, ROI demonstrate that large farms yield the highest returns relative to their initial investment. This suggests
that the investments made in expanding and operating large-scale farms are yielding substantial profits, reinforcing
the notion of scalability and eciency in resource utilisation.
These findings align with the analysis of commercial rabbit breeding enterprises in the Central Federal District of
Russia by Velkina and Nifontova (2021) where profitability was closely tied to eective sales revenue management
and cost control. The study identified that enterprises saw profit increases due to positive dynamics in sales, further
emphasising the importance of strategic management in maximising ROI. Conversely, the identification of profitability
growth reserves in less successful enterprises highlights that even smaller or less profitable farms can improve their
financial outcomes through targeted adjustments.
Finally, the per unit profit analysis reveals that large farms achieve the highest profitability on a per unit basis. This
signifies that, despite the higher initial investment and operational costs, large farms are able to achieve economies
of scale and optimise production processes to generate higher profits per unit of output (Eady and Prayaga, 2000;
Sánchez etal., 2022; Wongnaa, 2023a).
Contribution of specific expense category to profitability
Table 5 presents the outcomes of the MRL analysis, shedding light on how various expense categories influence
rabbit profitability. Each regression coecient reflects the estimated eect on profitability, with positive coecients
indicating a direct impact and negative coecients suggesting the opposite. Standard errors oer insights into the
precision of these estimates, with lower values indicating higher reliability. Moreover, P-values help assess the
statistical significance of each coecient, highlighting expenses that significantly aect profitability.
In this analysis, a negative non-significant constant term (β0) is observed. This represents the baseline profit when
all other expense categories are zero. Its negative value indicates that without accounting for specific expenses, the
model predicts a negative profitability. This further tells us that there are fixed costs or unaccounted factors that
inherently drive the profitability to be negative, or it could be an artefact of the data used to train the model, reflecting
scenarios where profitability is low even when expenses are minimal. Cartuche etal. (2014) identified that there

A reference on profitAbility of rAbbit production in the philippines
World Rabbit Sci. 32: 279-293 289
are various traits, such as feed conversion rate, number of kits born alive, and daily gain during fattening, which
significantly influence profitability. The negative constant term in this analysis can be seen as a reflection of the
broader impact of unmeasured traits or fixed costs, just as Cartuche’s study highlights how specific economic weights
and traits measure changes in profit. Both analyses underscore the importance of considering all influencing factors
and traits to accurately assess and enhance profitability in rabbit production systems.
Expenses such as feed cost, veterinary expenses, transport cost, labour cost and infrastructure (housing) expenses
obtained positive coecients. This suggests that an increase in these expense categories is associated with a rise
in profitability. However, only feed cost, veterinary expenses and labour cost are statistically significant. This means
that in every 1% increase in feed cost, the profitability increases by approximately 0.56%. Since this increase is
statistically significant (P<0.05), this indicates that feed cost is a significant predictor of profitability. However, the
eect size suggests a moderate eect of feed cost on profitability. This finding negates the result of Mukaila (2023)
in their study investigating the economic performance of small-scale rabbit production agribusiness enterprise in
Nigeria, which found that feed cost is an inhibiting factor of profitability at par from high mortality due to disease
outbreaks. The study obtained a Return on Capital Invested of 1.7, and Operating Ratio 0.4, suggesting that rabbit
production is highly profitable and a lucrative venture.
For veterinary expense, it indicates that for every 1% increase, the profitability increases by approximately 0.56%.
This suggests that veterinary expenses significantly contribute to profitability with a moderate eect size. In Mukaila
(2023) veterinary expense is highlighted as an enhancing factor for profitability, as producers who invest in veterinary
care can reduce mortality rates and disease outbreaks, leading to healthier rabbits and higher profitability.
Labour cost has a regression coecient of 0.44. This implies that for every 1% increase in labour cost, profitability
increases by approximately 0.44%. Importantly, this increase is statistically significant (P<0.05), indicating that
labour cost is a significant predictor of profitability. The substantial impact of labour costs on profitability was found
out by Cartuche etal. (2014) in their study on economic weights in rabbit meat production. The study indicates that
labour costs constitute 18% of total production costs, emphasising their significant role in overall profitability.
On the other hand, utilities expenses have a negative coecient, indicating that an increase in utilities expense is
associated with a decrease in rabbit profitability. However, this decrease is not statistically significant (P>0.05).
For the expense category, Cost of Stocks, the regression coecient is –0.13. This means that for every 1% increase
in the cost of stocks, the profitability decreases by approximately 0.13%. However, this decrease is not statistically
significant at the conventional significance level (P>0.05), as evidenced by the P-value of 0.36. The finding is
consistent with the observation that larger stock sizes, which benefit from economies of scale, contribute positively
to profitability (Mukaila, 2023). Aminu etal. (2020) emphasise stock size as a significant factor influencing income.
This supports the idea that eective management of stock size, which often involves economies of scale, can have
a substantial impact on profitability. Just as Mukaila (2023) highlights the importance of stock size in enhancing
Table 5: MRL result on the impact of expense categories on rabbit profitability (n=123). Dependent variable: Profit.
Expense category Coecient Standard error P-value Eect size (partial eta squared)
Constant –2.765 1.679 0.103
Cost of stocks –0.125 0.137 0.366
Feed cost 0.566 0.190 0.004 0.091
Veterinary expenses 0.559 0.200 0.007 0.082
Transport expenses 0.127 0.170 0.456
Labour cost 0.448 0.241 0.046 0.045
Infrastructure expenses 0.208 0.150 0.169
Utilities –0.225 0.250 0.371
Adjusted R2(%) 48.5
AIC 230.25
Log-likelihood ratio –107.13
AIC: Akaike information criterion.

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World Rabbit Sci. 32: 279-293290
profitability, the findings of Krupová etal. (2020) underline the need for careful management of stock-related costs
to optimise economic performance, calculating that the economic value of a trait, such as stock size, represents a
significant change in profit per doe, per year when the trait mean is increased by one unit.
The adjusted R-squared value, standing at 48.5%, and AIC value of 230.25 justifies the robustness of the regression
model in explaining the variability in rabbit profitability based on these expense categories.
Profitability drivers
In Table 6, the profitability drivers of rabbit raising were examined through an MRL analysis.
The constant term is highly significant, with a coecient of 6.14 (P-value <0.001), indicating a positive baseline level
of profitability independent of other factors. This further tells us that even when the eects of these identified factors
are unaccounted for, there remains a fundamental level of profitability that is not explained by the variables included
in the regression analysis.
Among the regressors, production level stands out, with a significant positive coecient of 1.4409, (P-value <0.001).
This means that a one-unit increase in the production level is associated with approximately a 144.1% increase in
profitability, holding other factors constant. The study of Wongnaa etal. (2023b) supports that commercialisation led
to increased household income. Economic theory supports that as production volume increases, the per-unit cost
decreases, leading to higher profit margins. Larger farms can leverage their size for better market access, competitive
pricing and risk diversification, all contributing to greater profitability (Samuelson and Nordhaus, 2010).
In contrast, the number of years of raising rabbits, with a coecient of 0.0020 and a high P-value of 0.986, is not
significant, implying that experience alone does not substantially impact profitability. This finding suggests that in
rabbit raising, profitability can be achieved regardless of the raiser’s experience. Profitability does not vary significantly
between raisers with extensive experience and those with little to no experience, which negates the results of Adedeji
etal. (2015) in Nigeria, who found a positive correlation between gross margin (profitability) and years of experience.
Training attendance, with a positive coecient of 0.0423 and a P-value of 0.596, seems to have no significant impact
on rabbit profitability. It is evident in the study area that many rabbit raisers lack formal training in rabbit production
and instead acquire their knowledge from watching videos on YouTube and other online platforms.
Similarly, the breed of rabbit, with an almost negligible coecient of 0.00067 and a P-value of 0.999, shows
no significant eect on profitability. This implies that the choice of rabbit breed does not significantly determine
profitability. It is observed that some raisers opt for breeds such as Champagne d’Argent and Flemish Giants for pet
purposes, obtaining higher returns, as pet-type rabbits command higher prices. Conversely, breeds like New Zealand
White and American Chinchilla are primarily used for meat production. This conveys that while the breed does not
significantly impact overall profitability, the intended market (pet vs. meat) plays a crucial role in determining the
financial outcomes for rabbit raisers.
Table 6: MRL result on rabbit profitability drivers (n=123). Dependent variable: Profit.
Variables Coecient Standard error P-value Eect size (partial eta squared)
Constant 6.1434 0.365 0.000
Production level 1.4409 0.119 0.000 0.622
Nº of years raising rabbit 0.0020 0.117 0.986
Training attendance 0.0423 0.079 0.596
Rabbit breed 0.0006 0.043 0.999
Feeds used –0.009 0.047 0.841
Marketing practices employed 0.0618 0.067 0.361
Adjusted R2(%) 61.08%
AIC 202.87
Log-likelihood ratio –94.44
AIC: Akaike information criterion.

A reference on profitAbility of rAbbit production in the philippines
World Rabbit Sci. 32: 279-293 291
The feeds used have a negative but insignificant coecient of –0.0096, suggesting that variations in feed types do
not notably influence profitability. In the study area, raisers utilise various feeding strategies, including commercial
feeds alone, own formulations, cut and carry forage and a combination of commercial feeds and forage. This basically
implies that higher profitability is geared towards combined feed types of commercial and forage/grasses, but is
not statistically significant. Unlike the findings of Micheni etal. (2020), which emphasised the importance of feed
quality (commercial) in enhancing profitability in rabbit farming, this study shows that the type of feed used does not
significantly impact profitability. This divergence may be due to the dierent feeding practices and the quality of feed
available in the study area compared to those in the referenced research.
Rabbits require a balanced diet that includes a variety of grasses and other feeds to support optimal growth and
development. The combination of these elements ensures that rabbits receive the necessary nutrients to maintain
health and enhance productivity (Lukefahr, 2022).
Marketing practices employed have a positive coecient of 0.0618, but this too is not statistically significant
(P=0.361), implying that while marketing might contribute positively, its impact is not strong enough to influence
profitability.
The study reveals that the marketing strategies employed by rabbit raisers in the area include relationship marketing/
word of mouth, direct selling, contact buying (physical) and internet/social media marketing. Among these strategies,
social media and internet technology have significantly aided the marketing aspect of rabbit production. This finding
suggests that while these marketing strategies contribute to some extent, their overall impact on profitability is not as
substantial as might be expected. One possible reason is that the market for rabbit meat is still relatively niche, and
traditional marketing methods may not yet be fully optimised. However, the high price of rabbit meat in the locality,
particularly in Zamboanga City supermarkets, where it commands a price of about Php 450.00 (0.016 EUR) per kilo,
indicates an unsaturated demand. This high price point suggests that rabbit meat has great potential in the market.
Along these lines, rabbit farmers require assistance and guidance in both rabbit production techniques and marketing
strategies from governmental bodies and other organisations in the Philippines to foster more prosperous rabbit
farming ventures (Dionisio etal., 2023).
These findings are consistent with the insights from Trocino etal. (2019), which emphasise the importance of
understanding global production trends and market dynamics. The dominance of China and North Korea in rabbit
meat production entails substantial competitive pressures for the Philippines. This international context underscores
the need for Philippine producers to refine their marketing strategies and production methods.
The decreasing production shares in the EU, as noted by Trocino etal., indicate that while traditional markets may
be contracting, there could be emerging opportunities for Philippine producers to capture niche markets or leverage
higher local prices. The unsaturated demand, highlighted by the high local prices, suggests that there is potential for
increased profitability if the market can be more eectively penetrated and optimised.
The adjusted R-squared value of 61.08% indicates that the model explains a substantial portion of the variability in
rabbit farm profitability, but other unexamined factors likely also play a role. These findings suggest that rabbit farmers
should focus on scaling their operations and optimising overall management practices rather than relying solely on
experience, specific breeds or feed types to drive profitability.
CONCLUSION AND RECOMMENDATION
The study on the profitability of rabbit raising in Zamboanga Peninsula, Philippines, reveals that the production level
or number of animals raised is a significant determinant of profitability, with larger farms achieving higher gross
incomes, net incomes and returns on investment compared to small and medium-sized farms. Factors such as cost
of stocks, veterinary expenses, transport costs and labour costs were found to positively influence profitability, while
utilities expenses had a negative impact. The regression analysis suggests that while certain expenses are critical
to profitability, the scale of operations plays a more crucial role in enhancing profitability. Variables such as years of
experience in rabbit raising, breed selection and the type of feed used did not significantly impact profitability. Training

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World Rabbit Sci. 32: 279-293292
attendance and marketing practices also showed non-significant eects on profitability. While certain variables may
not directly influence profitability, the high demand and favourable pricing of rabbit meat in local markets present
opportunities for profitability enhancement.
Based on the findings, rabbit farmers should consider expanding their production to achieve greater economies of
scale. Investments in larger-scale operations can lead to better profitability. Focusing on ecient cost management in
areas such as feed, labour and veterinary care can further enhance profitability. It is also recommended that farmers
should attend training sessions to stay updated on best practices in rabbit farming, although the study found that
experience alone did not significantly impact profitability, it remains important for improving production practices.
Marketing strategies should be diversified to include both traditional and digital methods to maximise market reach.
In general, strategic scaling and ecient resource management are key to boost profitability in rabbit farming.
Acknowledgement: The author would like to extend his sincere gratitude to Dr. Arvin B. Vista, his professor, for his invaluable
guidance deepening his knowledge and skills in econometrics, model specifications and in the field of research in general. He is
also grateful to Mr. Keir A. Balasa for his meticulous editing and assistance with references and to Mr. Eric John M. Gonzaga for
the technical assistance in rabbit production. To the Municipal Agriculture Oces and Provincial Agriculture Oces and the rabbit
raisers in the entire region, thank you for the support and accommodation during the field interview. Thank you all for your invaluable
contributions.
Authors contribution: Narita R.: conceptualization, methodology, data curation, writing – original draft and writing – review &
editing.
Declaration of Interest: The author declares that there are no conflicts of interest related to the authorship or publication of this
article. The research was conducted independently, and there are no financial, personal or professional interests that could be
perceived to influence the research outcomes.
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