MEASURING THE EFFICIENCY OF THE PRIMARY COOPERATIVES IN THE

FEDERATION OF DAVAO DAIRY FARMERS COOPERATIVES [1]

Ricalde, Ruby Grace J., Legaspi, Luyjilene V., Morales, Dianne D.

Bachelor of Science in Agribusiness Economics

School of Management

University of the Philippines Mindanao

ABSTRACT

The Philippines is an agricultural country and the dairy farming is one of the

industries which provide vigor to the economy. The Federation of Davao Dairy

Farmers Cooperatives (FEDDAFC) is one of the producers of fresh cow’s milk

in the Philippines and the only one in Davao City. All the eight dairy

cooperatives under the FEDDAFC were considered. This study aims to measure

the technical efficiency of the primary cooperatives under FEDDAFC; identify

which among the cooperatives is/are the most technically efficient and

inefficient; examine the potential of milk production if dairy farms could

operate efficiently; and provide recommendations to improve the production of

every cooperative. The technical efficiency was measured through the output-

oriented model using Data Envelopment Analysis Program (DEAP) to obtain

the most efficient cooperative using the inputs, namely grass, cow, farmer, and

water, and output (milk) in terms of liters. Results show that the mean values

of technical efficiencies under Constant Returns to Scale (CRS) and Variable

Returns to Scale (VRS) which are 0.693 and 0.855, respectively. Calinan Dairy

Farmers Cooperative (CDFC) is the most efficient with CRS and VRS of 1

because of the efficient allocation of inputs. It is followed by Malagos Dairy

Cooperative (MDC), Aklat Dairy Cooperative (ADC) and Riverside Dairy

Farmers Cooperative (RIDAFCO). Wangan Dairy Farmers Cooperative

(WADAC), Cadalian Dairy Farmers Cooperative (CADAFCO), Biao Joaquin

Dairy Farmers Cooperative (BJDAFCO) and Tacunan Dairy Farmers

Cooperative (TADAFCO) are the inefficient cooperatives. Therefore, it implies

that these inefficient cooperatives can further increase their outputs by

undertaking their opportunities and proper usage of their resources by allocating

their inputs proportionally. Results show that WADAC should mimic the

practices of CDFC and ADC; BJDAFCO and TADAFCO should follow CDFC,

ADC, and RIDAFCO; and CADAFCO should also follow CDFC, MDC and

RIDAFCO to operate efficiently within the FEDDAFC. Given that these

inefficient cooperatives will implement these changes, their outputs will

increase from 11 to 37 percent.

[1] A research paper in ABE 134: Applied Linear Programming for Economists under Prof.

Jon Marx Sarmiento, Second Semester of Academic Year 2014-2015

2

INTRODUCTION

BACKGROUND OF THE STUDY

The Philippines is a developing country with rich agricultural lands all throughout the

archipelago. Being an agricultural country, the government’s initiative is to develop

organizations for big dairy productions in the country given the increasing need of milk

products by the Filipino people with the continuous population growth.

Milk production has changed shape as the time goes by. During the 15th century, raw

milk was collected from dairy animals and sold without pasteurization. Soft cheese from

carabao’s milk was then manufactured and enjoyed by the people. Then, the first milk

processing plant was established during the early 1900’s by N.S. Schober and M. Teague,

which is a privately-owned firm. This introduced pasteurization and processing to the raw milk

(National Dairy Authority, 2015).

During the 1962, initiatives to develop public-owned milk processing plants have

started in the Philippines. The Dairy Training and Research Institute (DTRI) was established

with the assistance of the United Nations Development Program. The Institute serves as a

specialized research, training and extension unit of the College of Agriculture at the University

of the Philippines, Los Banos (UPLB). Slowly, companies, both public and private, have

opened new milk processing plant, bought the others, and changed names (NDA, 2015).

The Davao Dairy Development Foundation was established in 1990 through the

increased support of the private sector. Then, the National Dairy Development Act of 1995

(RA 7884) was signed into law on February 20, 1995. It took effect on March 12, 1995, legally

creating the National Dairy Authority (NDA). It is tasked to ensure the accelerated

development of the Philippine dairy industry (NDA, 2015).

Improvement of the milk production in Davao City was pioneered by the NDA under

the Department of Agriculture (DA) in 1990. Lectures were first conducted to the farmers in

Calinan, Davao City to raise interest in dairy farming and to inform them of the opportunities

of venturing the said new industry. Since NDA is a government institution, subsidies were

given to these farmers in terms of acquiring imported cows from New Zealand in a 50-50

scheme. This means that the government pays the 50 percent of the cow’s price, while the

remaining 50 percent was borrowed by the farmers from the government and will mature in 8

years (Ricalde, Canceran, et al., 2014).

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The Federation of Davao Dairy Farmers Cooperative (FEDDAFC) is a secondary

cooperative located at Barangay Malagos, Baguio District. It started out as a single cooperative

known as the Wangan Dairy Cooperative (WADAC) located at Barangay Wangan, Calinan

District, in 1990. WADAC initially had 25 members and 75 cows (human-cow ratio was 1:3).

The NDA helped the farmers in establishing the cooperative through providing them seminars

and workshops that supplemented their knowledge in managing the herd and basic treatments

for few animal diseases. The Philippines-Australia Community Assistance Program (PACAP)

also helped the cooperative through its technical assistance, dairy cow management and loan

services. In addition, the Dairy Development Foundation of the Philippines (DDFI) also offered

dispersal program to the cooperative. The availability of the dispersal is achieved after a series

of trainings offered by the DDFPI and PACAP, which includes organizational training,

technical training, and leadership training to be applied in the cooperative (Oracion, Estacio, et

al., 2013).

FEDDAFC then expanded to 3 other members namely: the Calinan Dairy Farmers

Cooperative (CDFC) in Barangay Calinan Poblacion, Calinan District; Malagos Dairy

Cooperative (MDC) in Barangay Malagos, Baguio District; and the Riverside Dairy Farmers

Cooperative (RIDAFCO) in Barangay Riverside, Calinan District. Since then, it has expanded

further, adding five more cooperatives: Biao-Joaquin Dairy Farmers Cooperative (BJDAFCO)

in Barangay Biao-Joaquin, Calinan District; Cadalian Dairy Farmers Cooperative

(CADAFCO) in Barangay Cadalian, Baguio District; Tacunan Dairy Farmers Cooperative

(TADAFCO) in Barangay Tacunan, Tugbok District; Aklat Dairy Cooperative (ADC) in

Barangay Tamugan, Baguio District; and Dacudao Dairy Farmers Cooperative (DDFC) in

Barangay Dacudao, Calinan District. Currently, FEDDAFC has the total of eight primary

cooperatives: CDFC, MDC, RIDAFCO, BJDAFCO, CADAFCO, TADAFCO and ADC,

eliminating the DDFC since it now merged with CDFC.

The FEDDAFC serves as the main plant wherein the cow’s milk gathered from these

different cooperatives are delivered for processing, value-adding and marketing.

STATEMENT OF THE PROBLEM

According to the Board of Investments (2011), there is an average 2% increase in the

local consumption of milk annually. Whereas, data from NDA shows that Philippine local milk

production as a whole is projected to increase in the succeeding years (Ang, 2013). There has

4

been also a consistent increase of dairy animals by 5% since 2010. However, it did not translate

to a consistent 11% increase in production. This means that even though the number of dairy

animals had increased, their milk producing capabilities have not been optimized as reflected

in the inconsistency of local production increase (Gines, n.d.).

The inefficiency of the dairy cooperatives, which are the biggest contributors to the

local production, is the main reason why the average Philippine milk production per animal (8

liters/day) remains low (Gines, n.d.). Dairy cooperatives, like the cooperatives under the

FEDDAFC, are not able to optimize the milking ability of the animals, and the usage of the

other inputs, making their outputs inconsistent. In addition to this, according to Acting Officer

In-charge of FEDDAFC, farmers inclined with the cooperatives are slowly losing interest in

the dairy milk production due to differences in the traditional and efficient way of milk

production. Figure 1 shows the irregular trend of the milk outputs of FEDDAFC (in Liters)

from January 2014 to April 2015.

Figure 1. Trend of monthly milk outputs of FEDDAFC (in Liters) from January 2014 to April 2015

SIGNIFICANCE OF THE STUDY

The results of the study have important implications in terms of adapting new practices

and techniques, eliminating technical inefficiencies, and combining proper inputs to improve

milk production of the cooperatives. Also, this study will serve as a primary step in improving

dairy milk production in the future.

0.00

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Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Jan Feb Mar Apr

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OBJECTIVES OF THE STUDY

This study aims to:

1. Measure the technical efficiency of the primary cooperatives under FEDDAFC;

2. Identify which among the cooperatives is/are the most technically efficient;

3. Identify which among the cooperatives is/are technically inefficient;

4. Examine the potential of milk production, if dairy farms could operate efficiently; and

5. Provide recommendations to improve the production of every cooperative.

SCOPE AND LIMITATIONS

This study only accounts for the output and inputs of milk production in measuring all

the efficiency indices of FEDDAFC. It does not consider other factors such as the social and

intellectual characteristics of the farmers, farm practices of each farmer, the volume of milk

rejects due to microbial count, the breed of the cow each farmer in the cooperative owns and

other factors that likely affect the efficiency of milk production. Also, other inputs like the

costs on feeds, medicines, vitamins, artificial insemination and other related inputs were not

considered due to lack of data available.

The major limitation in this study is that it only uses the non-parametric approach in

which it is conceptually difficult to separate the effects of uncontrollable environmental

variables and error measurements from the effect of differences in farm management and the

presence of outliers.

METHODOLOGY

DATA

The main material of the study consists of the data, specifically the inputs and outputs

of milk production in each primary cooperative, were gathered through personal interview with

the Acting Officer-in-charge of FEDDAFC and the Quality Management assistant of NDA –

Mindanao. All the eight (8) primary cooperative-members of FEDDAFC were considered.

Some of the dairy farmer-members per cooperative were also interviewed.

6

VARIABLES

One output and four input variables are used. These variables are listed below.

Output – average quantity of the milk in Liters produced by each primary cooperatives

that are delivered to FEDDAFC per month

Cows – number of milk-producing cattle per cooperative

Farmers – number of cooperative members that are engaged into dairy farming which

are treated as the total labor involved

Grass – approximated area of grassland in hectares per cooperative that are used to

feed the cows

Water – approximated volume of water in Liters used by the cows in liters per

cooperative per month

Data gathered were tabularized in Table 1.

Table 1. Monthly Outputs and Inputs of the primary cooperatives in FEDDAFC from January

2014 to April 2015.

Output Inputs

Milk

delivered

Cows Farmers grass Water

DMU Cooperative (in L/month) (in ha) (in L)

1 CDFC 7708 62 28 13.40 68820

2 MDC 4018 55 17 10.10 61050

3 WADAC 3908 45 26 12.80 49950

4 CADAFCO 3199 47 16 9.80 52170

5 BJDAFCO 2933 41 17 10.10 45510

6 ADC 2267 25 16 9.80 27750

7 RIDAFCO 2176 40 12 8.60 44400

8 TADAFCO 1036 34 16 9.80 37740

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METHOD

In this study, the efficiency of the dairy cooperatives under FEDDAFC were measured

through Data Envelopment Analysis (DEA) software version 2.1 developed by Coelli (1996),

a non-parametric measurement method to measure the relative efficiency of economical

decision making units (DMUs) similar to one another in terms of goods and services they

produce. DEA uses linear programming as an efficiency measurement technique based on the

combinations of inputs and outputs that are greater than 1 (Uzmay, et al., 2009). DEA focuses

on the individual farm performance to discover the best practices in farm management. Advice

for the individual cooperatives, regarding how technical inefficiencies can be eliminated, can

be provided by identifying benchmark peers for farms of different scale (Carter, 2004). A

relative measure, the technical efficiency (TE) of a primary cooperative relative to others in the

sample, is derived. TE measures by how much each input can be reduced (or output increased)

to produce an efficient outcome. TE can be decomposed to determine the contribution of pure

technical factors (PTE) and scale efficiency (SE) to the overall level of efficiency (Fraiser,

2005).

The output-oriented DEA model is used to obtain separate estimates of TE and SE using

the Variable Returns to Scale (VRS) and Constant Returns to Scale (CRS) assumptions. This

is because the output-oriented DEA model maximizes the proportional increase in output while

remaining within the production possibility set. The proportional increase in output is obtained

when output slack is zero. This method considers the observed production relative to the

corresponding potential production, given the quantities of the inputs used (Theodoridis &

Psychoudakis, n.d,).

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RESULTS AND DISCUSSION

In this section, the measures of technical efficiency obtained using output-oriented VRS

and CRS DEA models are discussed. The technical scores of the primary cooperatives are

reported in Table 2. Results show that the mean values of technical efficiencies under CRS and

VRS are 0.693 and 0.855. This means that on the average, the cooperatives under FEDDAFC

are relatively inefficient with a mean SE at 0.802.

Table 2. Mean Technical Efficiency of the primary cooperatives.

DMU Cooperative CRS VRS SE

1 CDFC 1.000 1.000 1.000

2 MDC 0.859 1.000 0.859

3 WADAC 0.699 0.750 0.931

4 CADAFCO 0.726 0.894 0.813

5 BJDAFCO 0.627 0.830 0.755

6 ADC 0.730 1.000 0.730

7 RIDAFCO 0.659 1.000 0.659

8 TADAFCO 0.245 0.366 0.671

Mean 0.693 0.855 0.802

Note: CRS = technical efficiency from CRS DEA

VRS = technical efficiency from VRS DEA

SE = scale efficiency = CRS / VRS

The mean TE of the cooperatives under VRS frontier at 0.855 indicates that the

cooperatives are using their resources efficiently but can further improve their opportunities by

increasing their output of milk delivery to the FEDDAFC with the same proportion of their

inputs. However, as seen in Table 2, MDC, WADAC, CADAFCO, BJDAFCO, ADC,

RIDAFCO, and TADAFCO has an SE that is less than 1 which means scale inefficiencies.

These scale inefficiencies can either be due to the cooperative is relatively smaller compared

to the other cooperatives and is operating in increasing returns to scale or the cooperative is

relatively larger and is operating in a decreasing returns to scale. Thus, the result of the study

9

show that these said cooperatives are operating in an increasing returns to scale since the

cooperatives’ SE is less than 1.

CDFC, MDC, ADC and RIDAFCO are the most efficient cooperatives among the 8

cooperatives since these four cooperatives have a TE of 1 under the VRS frontier. In line with

this, only CDFC is operating efficiently under the CRS frontier while the other 7 cooperatives

exhibits an increasing returns to scale. Moreover, only CDFC is the model cooperative among

the cooperatives operating under FEDDAFC with SE of 1. This is because CDFC has the

greatest volume of milk produced, maximizing the use of its amounts of inputs. One of the

factors for the efficiency of CDFC is the merger with DDFC.

On the other hand, it implies that MDC, WADAC, ADC, TADAFCO, RIDAFCO,

CADAFCO, and BJDAFCO can further increase their outputs by undertaking their

opportunities and proper usage of their resources. Thus, results show that WADAC should

follow the practices of CDFC and ADC; BJDAFCO of CDFC, ADC and RIDAFCO; and

CADAFCO of CDFC, MDC and RIDAFCO to operate efficiently within the FEDDAFC (See

Appendix – Summary of Peers).

Furthermore, the suggested number of inputs per cooperative that would give the

cooperatives their better output is summarized in the Table 3 below. Input slacks were observed

for WADAC for farmer and grass inputs with 3.514 and 1.054, respectively (See Appendix –

Summary of Input Slacks). This suggests that WADAC is not using its resources properly and

can still produce more with their proportion of inputs.

Table 3. Suggested number of inputs per cooperative under FEDDAFC per month.

DMU Cooperative Cows Farmers Grass

(in hectares)

Water

(in Liters)

1 CDFC 62 28 13.4 68820 2 MDC 55 17 10.10 61050 3 WADAC 45 22 11.75 49950 4 CADAFCO 47 16 9.80 52170 5 BJDAFCO 41 17 10.10 45510 6 ADC 25 16 9.80 27750 7 RIDAFCO 40 12 8.60 44400 8 TADAFCO 34 16 9.80 37740

This means that the farmer input of WADAC should be reduced by 4. Also, grass input

of the same cooperative should be reduced by 1.05 hectares. This means that WADAC is not

using these inputs efficiently and proportionally. Thus, these inputs are neglected. Therefore,

10

the right combination of inputs as shown in Table 3 (See also Appendix – Summary of Input

Targets) must be implemented in order for the FEDDAFC to operate efficiently as a whole.

Thus, if the ideal combination of inputs per cooperative is implemented, there would

be a significant increase in the outputs of WADAC by 25 percent, CADAFCO by 11 percent,

BJDAFCO by 17 percent, and TADAFCO by 37 percent as shown in Table 4. Hence, making

these inefficient firms operate efficiently.

Table 4. The difference between the ideal and actual outputs of milk per liter per cooperative.

DMU Cooperative Ideal

Output (IO)

Actual Output

(RO)

Difference of

IO and AO

Percentage

Increase

1 CDFC 7708.29 7708.29 0 0

2 MDC 4018.99 4018.99 0 0

3 WADAC 5208.63 3908.01 1300.62 25

4 CADAFCO 3580.45 3199.63 380.82 11

5 BJDAFCO 3535.03 2933.78 601.25 17

6 ADC 2267.86 2267.86 0 0

7 RIDAFCO 2176.49 2176.49 0 0

8 TADAFCO 2834.90 1036.54 1798.36 37

The TE estimated for the CRS and VRS, which are 0.693 and 0.855 is consistent with

the theory that VRS frontier is more flexible and captures the data in a more well-rounded way

than of the CRS. The mean TE of the cooperatives under the FEDDAFC indicates that the

cooperatives are relatively inefficient. Only CDFC is fully technically efficient under CRS

while CDFC, MDC, ADC, and RIDAFCO are fully technically efficient under VRS.

11

SUMMARY AND CONCLUSION

Due to the decreasing number of farmers engaging in milk production under the

FEDDAFC and with the increasing demand of milk in Davao City, there is a threat that the

proceeding supply of milk can no longer meet the increasing demand of the consumers. Thus,

FEDDAFC is faced with the dilemma of finding the solution for this problem. As the main

producers of milk under FEDDAFC, the eight member cooperatives, CFDC, MDC, WADAC,

ADC, TADAFCO, RIDAFCO, CADAFCO, and BJDAFCO were subjected to output-oriented

VRS DEA to assess whether they are operating efficiently or not and as to suggest the ideal

output per cooperative given their respective inputs.

Results show that FEDDAFC is currently operating inefficiently with a mean technical

efficiency under VRS of 0.855. However, there is still an opportunity wherein it could operate

efficiently since the inefficient firms exhibits an increasing returns to scale. In addition, CFDC

is the model cooperative among the 8 cooperatives under FEDDAFC with a scale efficiency of

1, while CFDC, MDC, ADC, and RIDAFCO are operating efficiently relative to the other 4

cooperatives under the VRS frontier.

Thus, the results of the study also show that WADAC should follow the practices of

CDFC and ADC; BJDAFCO and TADAFCO of CDFC, ADC and RIDAFCO; and CADAFCO

of CDFC, MDC and RIDAFCO to operate efficiently leading to an increase of their outputs of

milk delivered to the FEDDAFC plant.

Moreover, if the above changes are to be implemented, the increase in the outputs of

the 4 inefficient cooperatives will range from 11 to 37 percent. These changes in the outputs of

the cooperatives will surely benefit not only FEDDAFC but also the milk products and by-

products consumers in Davao City.

12

RECOMMENDATIONS

Based on the results of the study, the MDC, WADAC, ADC, TADAFCO, RIDAFCO,

CADAFCO, and BJDAFCO should produce more outputs of milk per liter delivered to the

FEDDAFC since these cooperatives inhibits increasing returns to scale with the same

proportion of their inputs. Also, WADAC should follow the outputs of CDFC and ADC,

BJDAFCO should follow the outputs of CDFC, ADC, and RIDAFCO, and CADAFCO should

follow the outputs of CDFC, MDC, and RIDAFCO to be technically efficient under the

FEDDAFC.

The increasing demand for fresh cow’s milk and the inefficiency of the individual

cooperatives show that more actions and efforts should be exerted in order to support the

cooperatives to be efficient. NDA should provide more assistance through imposing policies

and giving advices to the farmers regarding proper farm management and allocation of inputs.

An effective plan that involves exponentially increasing the number of small scale farmers and

cooperatives is needed to increase the production sufficiency ratio. Increasing the physical

number of dairy animals and the per head milk productivity through breeding and selection

will also play a part. Encouraging more farmers to engage into dairy farming should also be

done. Conducting more research is also necessary to further analyze the situation and provide

solutions and recommendations for the betterment of the dairy industry.

On the other hand, the dairy farmers of the eight member cooperatives under

FEDDAFC, should allow the NDA and other institutions to intervene with them through

embracing the policies, programs and advices being introduced to them. As cited by Gines

(n.d.), Stanton, E. & Stanton, S. (2011) said that efforts of the government to create projects

and campaigns for the betterment of the dairy industry have been put to waste. It is either

because of the facilitating agencies have not been concentrating in fully spreading, teaching

and implementing these practices; or because of the dairy farmers who are still sticking to their

traditional practices. Further studies and series of trials were done before these policies and

courses are introduced. Institutions like the NDA are there to provide assistance and support.

Unfortunately, mostly of the dairy farmers are not willing to adopt to some of the

recommendations because they still stick to their own traditional practices.

For future researchers, qualitative data such as the farm practices of each cooperative,

age bracket and educational background of the farmers, etc. should be considered in assessing

the technical efficiency of the cooperatives. Other inputs, like the amount of feeds, cow breeds,

volume of milk rejects due to microbial count, etc. should also be used to come up with better

13

results and conclusion. Moreover, allocative and cost efficiencies of each cooperative can also

be derived through getting the costs of each inputs used. Future researchers can also use other

methods, such as the parametric Stochastic Frontier Approach (SFA), which is a more reliable

method in agricultural applications because it can measure the error, missing variables and

weather that are likely to play a significant role in agriculture (Coelli, 1995), to compare with

the results of this study. For the efficiency of FEDDAFC as a whole, future researchers are also

recommended to take into account the privately-owned dairy farms, other than the cooperatives

involved in this study, that also contribute to the milk supply of FEDDAFC.

14

REFERENCES

Ang, P. (2013). Philippine dairy and products annual situation and outlook. USDA Foreign

Agricultural Service Global Agricultural Information Report.

Board of Investments. (2011). Philippine Dairy Industry. Retrieved May 2015.

Carter, A. (2004). Investigating technical and scale efficiency of dairy farms in south-western

Victoria: a non-parametric approach.

Coelli T.J. (1995). Recent Developments in Frontier Modelling and Efficiency Measurement,

Australian Journal of Agricultural Economics 39: 219-245.

Coelli, T. (1996). A Guide to DEAP Version 2.1: A data envelopment analysis computer

program. CEPA Working Paper 96/08, Centre for Efficiency and Productivity

Analysis. University of New England.

Fraiser, I. & Graham, M. (2005). Efficiency measurement of Australian dairy farms: national

and regional performance. Australasian Agribusiness Review, 13 (ISSN 1442-6951)

University of Melbourne. Retrieved May 2015 from

http://www.agrifood.info/review/2005/Fraser_Graham.html

Gines, K.A. (n.d.). The dairy industry: a chemical process industry report. Retrieved May

2015 from https://www.academia.edu/11996734/The_Dairy_Industry_A_Chemical_

Process_Industry_Report_with_focus_on_drinking_milk_cheese_and_ice_cream

National Dairy Authority (2015). Retrieved May 2015 from http://gwhs

stg01.i.gov.ph/~ndagovph/index.php?option=com_content&view=article&id=51&Ite

mid=211&lang=en

Oracion, A.M., Estacio, E.M., et al. (2013). Supply chain of milk bar. ABE 102 term paper

class of 2012-2013, University of the Philippines Mindanao.

Ricalde, R.G.J., Canceran, D.C., et al. (2014). Analysis on the supply chain of milk in davao city.

Retrieved May 2015 from

https://www.academia.edu/12406492/Analysis_on_the_Supply_Chain_of_Milk_in_Dava

o_City

Theodoridis, A.M. & Psychoudakis, A. (n.d,). Efficiency measurement in Greek dairy farms:

stochastic frontier vs. data envelopment analysis. International Journal of Economic

Sciences and Applied Research 1 (2): 53-6.

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Uzmay, A., Koyunbenbe, N., et al. (2009). Measurement of efficiency using data

envelopment analysis (DEA) and social factors affecting the technical efficiency in

dairy cattle farms within the province of Izmir, Turkey. Journal of Animal and

Veterinary Advances 8 (6): 1110-1115, 2009.

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APPENDIX

Results from DEAP Version 2.1

Instruction file = f-ins.txt

Data file = f-dta.txt

Output orientated DEA

Scale assumption: VRS

Slacks calculated using multi-stage method

SUMMARY OF OUTPUT SLACKS:

firm output: 1

1 0.000

2 0.000

3 0.000

4 0.000

5 0.000

6 0.000

7 0.000

8 0.000

mean 0.000

SUMMARY OF INPUT SLACKS:

firm input: 1 2 3 4

1 0.000 0.000 0.000 0.000

2 0.000 0.000 0.000 0.000

3 0.000 3.514 1.054 0.000

4 0.000 0.000 0.000 0.000

5 0.000 0.000 0.000 0.000

6 0.000 0.000 0.000 0.000

7 0.000 0.000 0.000 0.000

8 0.000 0.000 0.000 0.000

mean 0.000 0.439 0.132 0.000

SUMMARY OF PEERS:

firm peers:

1 1

2 2

3 1 6

4 1 7 2

5 1 7 6

6 6

7 7

8 1 6 7

SUMMARY OF PEER WEIGHTS:

(in same order as above)

firm peer weights:

1 1.000

2 1.000

3 0.541 0.459

4 0.192 0.623 0.185

5 0.241 0.473 0.287

6 1.000

7 1.000

8 0.110 0.561 0.329

PEER COUNT SUMMARY:

(i.e., no. times each firm is a peer for another)

firm peer count:

1 4

2 1

3 0

4 0

5 0

6 3

7 3

8 0

SUMMARY OF OUTPUT TARGETS:

firm output: 1

1 7708.290

2 4018.990

3 5208.633

4 3580.452

5 3535.030

6 2267.860

7 2176.490

8 2834.895

SUMMARY OF INPUT TARGETS:

firm input: 1 2 3 4

1 62.000 28.000 13.400 68820.000

2 55.000 17.000 10.100 61050.000

3 45.000 22.486 11.746 49950.000

4 47.000 16.000 9.800 52170.000

5 41.000 17.000 10.100 45510.000

6 25.000 16.000 9.800 27750.000

7 40.000 12.000 8.600 44400.000

8 34.000 16.000 9.800 37740.000