Keunggulan Komparatif dan Kompetitif Industri Feedlot Indonesia

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COMPARATIVE AND COMPETITIVE ADVANTAGES OF

FEEDLOT INDUSTRY, INDONESIA

LABUDDA A.S. PARAMECWARI

GRADUATE SCHOOL

BOGOR AGRICULTURAL UNIVERSITY

BOGOR


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STATEMENT OF THESIS, SOURCE OF INFORMATION AND

COPYRIGHT*

I hereby declare that thesis titled Comparative and Competitive Advantage of Feedlot Industry Indonesia was independently composed by me under the advisory committee supervision and has not been submitted to any other universities. Source of information derived or quoted from works published and unpublished from other writers have been mentioned in the text and listed in the bibliography at the end of this thesis.

I hereby assign the copyright of my thesis to the Bogor Agricultural University

Bogor, May 2015

Labudda A.S. Paramecwari

NIM H451110331

* Copyright transfer due to the collaborative research work with other parties outside the Bogor Agricultural University should be based on a related agreement


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Feedlot Industry Indonesia. Supervisors by RACHMAT PAMBUDY, NUNUNG KUSNADI, STEFAN SCHWARZE, AND BERNHARD BRÜMMER.

Meat is the main commodity traded in the world concerning its economic value. Unfortunately, smallholder farmers in Indonesia have not been able to respond to demand for beef looking at the high import levels. Thus, feedlots have an important role for supplying these commodities through better technology. However, it is still arguable if Indonesian feedlots industry has comparative and competitive advantages. In addition, also unknown whether the policies implemented support the competitiveness of Indonesian feedlots. Therefore, this study aims to assess the comparative and competitive advantage of Indonesian feedlots industry and evaluate government policies related to beef and cattle.

To measure, this study includes three provinces which are the major producer and consumer of meat in Indonesia; Banten, Lampung and West Java. Comparative and competitive advantages as well as the impact of policies on industrial feedlots Indonesia analyzed using the Policy Analysis Matrix (PAM).

This study shows that feedlots have a comparative and competitive advantage according to the value of the DRC and the PRC that is less than one. In addition, government policy has been supporting the achievement of comparative and competitive advantage of Indonesian feedlots industry. This is demonstrated through the analysis of government policy on the input and output of beef cattle.

Inputs and output policy has protect the beef cattle business, thus feedlots in Banten, Lampung and West Java gain profit to 1 437 964, 1 763 357, and 1 196 335 IDR/cattle, respectively. The presence of input and output policies increase value added benefit and give positive impact on the cost of production, for it lowering production costs as much as 16 percent to Banten, 19 percent to Lampung, and 13 percent for West Java. Furthermore, the results of sensitivity analysis explains that the price of feeder cattle give effect on competitiveness. Keywords: Competitive Advantage, Comparative Advantage, Feedlot


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RINGKASAN

LABUDDA A.S. PARAMECWARI. Keunggulan Komparatif dan Kompetitif Industri Feedlot Indonesia. Dibimbing oleh RACHMAT PAMBUDY, NUNUNG KUSNADI, STEFAN SCHWARZE, AND BERNHARD BRÜMMER.

Daging merupakan komoditas utama yang diperdagangkan di seluruh dunia karena bernilai ekonomis dan bernutrisi. Sayangnya, peternakan rakyat di Indonesia belum mampu merespon permintaan daging sapi terlihat dari level impor tinggi sehingga feedlot memiliki peran penting dalam penyediaan komoditas tersebut melalui teknologi yang lebih baik.

Namun, masih dipertanyakan bilamana industri feedlot Indonesia memiliki keunggulan komparatif dan kompetitif. Selain itu, belum diketahui pula apakah kebijakan yang diterapkan mendukung daya saing feedlot Indonesia. Oleh sebab itu, studi ini bertujuan untuk menilai keunggulan komparatif dan kompetitif industri feedlot indonesia serta mengevaluasi kebijakan pemerintah terkait daging dan sapi potong.

Untuk mengukurnya, studi ini meliputi tiga provinsi yang menjadi produsen dan konsumen utama daging di Indonesia, yaitu Banten, Lampung, dan Jawa Barat. Keunggulan komparatif dan kompetitif serta dampak kebijakan terhadap industri feedlot Indonesia dianalisis menggunakan Policy Analysis Matrix (PAM).

Penelitian ini menunjukkan bahwa feedlot memiliki keunggulan komparatif dan keunggulan kompetitif dinilai dari nilai DRC dan PRC kurang dari satu. Selain itu, kebijakan pemerintah telah mendukung tercapainya keunggulan komparatif dan keunggulan kompetitif industri feedlot Indonesia. Hal ini dibuktikan melalui analisis kebijakan pemerintah terhadap input dan output sapi potong. Kebijakan input dan output telah cukup memproteksi dan melindungi usaha sapi potong, sehingga pelaku usaha feedlot di Banten, Lampung, dan Jawa Barat memperoleh keuntungan berturut-turut sebesar 1 437 964, 1 763 357, and 1 196 335 IDR/ekor.

Adanya kebijakan input dan output sapi potong meningkatkam nilai tambah keuntungan serta memberikan dampak positif terhadap biaya produksi, sebab menurunkan biaya produksi sebanyak 16 persen untuk Banten, 19 persen untuk Lampung, dan 13 persen untuk Jawa Barat. Lebih jauh, hasil analisis sensitifitas menjelaskan bahwa harga sapi bakalan berpengaruh terhadap daya saing.


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© Bogor Agricultural University Rights Reserved, 2015

Copyright Reserved

It is prohibited to quote part or all of this paper without including or citing the source. Quotations are only for purposes of education, research, scientific writing, preparation of reports, critics, or review an issue; and those are not detrimental to the interest of the Bogor Agricultural University.

It is prohibited to announce and reproduce part or all of this paper in any form without the permission of the Bogor Agricultural University.


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COMPARATIVE AND COMPETITIVE ADVANTAGES OF

FEEDLOT INDUSTRY, INDONESIA

LABUDDA A.S. PARAMECWARI

Thesis

as one of requirements to obtain a degree of Magister Sains

in

Study Program of Agribusiness

GRADUATE SCHOOL

BOGOR AGRICULTURAL UNIVERSITY

BOGOR


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Examiner Commission on Affairs of Master Thesis Examination: Dr Ir Anna Fariyanti, MSi


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Title of Thesis : Comparative and Competitive Advantage of Feedlot, Indonesia Name : Labudda A.S. Paramecwari

Student ID : H451110331

Approved by, Advisory Committee,

Dr Rachmat Pambudy, MS Dr Ir Nunung Kusnadi, MS

Chairman Member

Prof Dr Bernhard Brümmer Dr Stefan Schwarze

Member Member

Acknowledge by, Coordinator of

Agribusiness Program,

Dean of Graduate School,

Prof Dr Ir Rita Nurmalina, MS Dr Ir Dahrul Syah, MScAgr


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ACKNOWLEDGEMENT

First, I would like to praise Allah SWT because of his mercy I could finish this thesis. I would like to thank my supervisors in Bogor Agricultural University, Dr. Rachmat Pambudy and Dr. Nunung Kusnadi for supporting and encouraging me in finishing my master thesis. I would give my deepest appreciation to my supervisors in Göttingen University, Prof. Dr. Bernhard Brümmer and Dr. Stefan Schwarze, for guiding and helping me so that I can finish this research. I would sincerely thank Dr. Suharno and Dr. Anna Fariyanti as examiner commisions for their suggestion during my thesis examination.

I would especially like to thank Prof. Dr. Rita Nurmalina, MS and Prof. Dr. Stephan von Cramon Taubadel in respect to Sustainable International Agriculture (SIA), the joint degree program between Magister Science of Agribusiness, Bogor Agricultural University and Master of International Agribusiness and Rural Development, University of Göttingen. For the contribution in the data collection process, I would also like to acknowledge with much appreciation to Mrs. Intani Dewi and Mr. Galih Sudrajat, and Mr. Sichi Yantika for his information about technical aspect about feedlots.

I would like to express my gratitude to BU-BPKLN and Directorate General of Higher Education Indonesia for funding my study both in Bogor Agricultural University and University of Göttingen. Last but not least, a huge thank you to all my friends: The MSA Joint Degree 2 and 3, SIA 2012, MSA IPB, PPI Göttingen, and all of my friends during my study in Germany. I am grateful for the support of my family. I dedicate my work to my family who always encourage and support me throughout my study in University of Göttingen.

Bogor, May 2015


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CONTENTS

CONTENTS X

LIST OF TABLE IX

LIST OF FIGURES X

LIST OF APPENDICES X

LIST OF ABBREVIATION X

1 INTRODUCTION 1

Background 1

Problem Statement 6

Research Objectives 7

Scope of Research 7

Benefit of Research 7

2 LITERATURE REVIEW 8

Competitiveness Study Using Various Methodology 8

PAM Study for Beef Sector in Indonesia 9

3 THE BEEF TRADE 10

Overview of World Beef Trade 10

Beef Market Overview in Indonesia 12

Indonesian Government Policy related to Live Cattle and Beef Trade 18

4 FRAMEWORK 18

Concept of Competitiveness 18

Agricultural Policy Analysis 19

Concept of Policy Analysis Matrix 23

Operational Framework 24

5 METHODOLOGY 25

Data Description 25

Data Processing 25

Determination of Output, Tradable Input, and Domestic Factor 25

Determination of Private and Social Cost 26

a. Shadow Exchange Rate 26

b. Output social price 27

c. Tradable input social price 27

d. Domestic factor social price 27

Determination of Private and Social Profitability 28

Data Analysis 28

Competitive Advantage 28

Comparative Advantage 29

Impact of Policy Analysis 29

a. To Output 29

b. To Input 30

c. To Output and Input 30


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6 RESULTS 32

Characteristic of Feedlot 32

Private and Social Cost 33

Private and Social Profitability 34

Comparative and Competitive Advantage of Feedlot Industry 36

Impact of Policy 37

Impact to Output 37

Impact to Input 39

Impact to Input & Output 41

Policy Scenario and Sensitivity Analysis 42

7 CONCLUSION AND RECOMMENDATION 44

Conclusion 44

Policy Recommendation 44

Limitations 45

BIBLIOGRAPHY 46

APPENDICES 50

BIOGRAPHY 62

LIST OF TABLE

1. Selected feed type in the feed ratio of common Indonesian Feedlot 14 2. List of Harmonization System (HS) code for beef cattle and products 15

3. Classification of Commodity Price Policy 19

4. Structure of PAM 23

5. Data Description 25

6. Allocation of Production Cost to Tradable and Non-Tradable Component 26

7. Policy Analysis Matrix 28

8. Number of firms according to cattle ownership 32

9. Number of workers according to employment status and education level 33 10. Feed consumption in kg per cattle according to feed classification 33 11. Private and Social Average Budget of Feedlots (IDR/cattle) 34 12. PAM for Banten, Lampung, and West Java (IDR/cattle) 35 13. Private and Social Benefit Cost Ratio of Indonesian Feedlot Industry 36 14. Indicator of Competitiveness of Indonesian Feedlot Industry 36

15. Indicator of Policy Impact to Output 38

16. Indicator of Policy Impact to Input 39

17. Indicator of Policy Impact to Output and Input 41

18. Impact of Policy Scenario to Competitiveness in Lampung, West Java,

and Banten 42

19. Impact of Feeder Cattle Price and Exchange Rate to


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LIST OF FIGURES

1. Indonesian Beef Production, Consumption, and Import 2 2. Comparison of local and imported beef price 2010-2011 3

3. Cattle and Feedlots Distributions in Indonesia 6

4. Market Share of Major Beef Trader in the World 11

5. World Beef Distribution Flow 12

6. Supply chain of domestic cattle (left) and imported cattle (right) 13

7. Imported beef supply chain in Indonesia 15

8. Comparison of local and imported beef and edible offal price 16

9. Beef Supply Chain in DKI Jakarta 17

10. Mechanism of Subsidy Policy on Output to producer 20 11. Mechanism of Subsidy Policy on Output to Consumer 21

12. Mechanism of Trade Policy on Output 22

13. Mechanism of Subsidy Policy on Tradable Input 22

14. Mechanism of Subsidy Policy to Non-Tradable Input 23 15. Operational framework of Comparative and Competitive Advantage

of Feedlots 24

LIST OF APPENDICES

1. National and Provincial Regulation related to Beef and Trade 50

2. Valuation of Shadow Exchange Rate (SER) 2011 52

3. Valuation of Beef Import Parity Price 53

4. Valuation of Feeder Cattle Import Parity Price 53

5. Valuation of Medicine Social Price 54

6. Fuel and Domestic Factors Social Price 54

7. Policy Scenario 56

LIST OF ABBREVIATION

ADG : Average Daily Gain

BSE : Bovine Spongiform Enchelopathy

CV : Comanditaire Venootschap

CIF : Cost, Insurance, Freight

DKI : Daerah Khusus Ibukota (Capital City) FMD : Foot and Mouth Disease

HS : Harmonized System

IDR : Indonesian Rupiahs Lw : Live Weight

PO : Peranakan Ongole


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1

INTRODUCTION

Background

Beef is an important commodity in the world. People in developed and developing countries consumed almost 80 kg per year and 32.5 kg per year, respectively. It collectively accounts to 60 percent of world’s beef consumption (FAO 2013). Beef is generally traded from the developing countries, accounted in volume for almost 57 percent of world’s beef export in 2013 (FAO 2014). GDP of beef exporting country like Brazil and Australia are largely supported by this sector. MLA (2013) reported that Australia’s beef and veal export value is accounted for 5.06 billion USD in 2012-2013, slightly higher than Brazil’s with 3.96 billion USD (USMEF 2014).

Both developed and developing countries stimulate massive beef production by considering the importance of those as valuable commodities in economic terms. For over decades, Brazil have been investing largely in the animal genetics improvement and better feeding management. Expansion of soybean manufacturing has driven the country to have lower feed cost than that in other competing producers and thus made them as the leading nation in world’s beef trade. The market liberalization force countries to address the quantity and quality issue of product to fill the market niche as much as possible, so that they could gain greater benefit when they traded internationally.

These enthusiasms also inspire the developing nation’s net importer, particularly Indonesia, to begin producing beef both for domestic and export market. This motivation is interpreted as supplying the food both in independent and sustainable way through the self-sufficiency program. It is hoped that Indonesia will be less reliant to food production of other countries by reducing import down to 10 percent and largely supported by the domestic production for the remaining.

However, efforts of boosting beef production through self-sufficiency program were unsuccessful due to low level of cattle productivity and high rate of calf mortality (Nixon and Whitehead 2013). Management of artificial insemination program was practically unclear and the straw quantities were limited, which resulted to low cattle’s productivity rate. Yusdja et al (2004) stated that prevention of productive cow slaughtering was failed because poor farmers tend to sell their livestock when they encounter financial difficulties. Farmers in developing countries generally keep cattle as the prime input for husbandry in terms of utilization for beef production, as a machinery-substitution for ploughing agricultural land, and high value assets.

Statistics Indonesia (2013) illustrated that Indonesian beef industry is dominated by the small holder with small farm size. The traditional beef cattle grower is equal to 5.078.979 households while commercial growers are 109 companies1. The traditional growers commonly owned on average 2-4 cattle (Boediyana 2007). As a consequence, the cost per animal unit is bigger. Study of Rizsqina et al (2011), Thawaf et al (2006), and Trestini (2006) suggested that herd size have a positive correlation with output, income and farm efficiency. The herd


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with 5 animals or less resulted to low efficiency according to benefit-cost ratio and low farmer’s return. Even, in the case of Rizsqina (2006), the sample farmer experienced a loss in their business. Trestini (2006) who studied the correlation between herd size and technical efficiency implies that the average technical efficiency is 62.6% on the sample farm with cattle less than 10 Animal Unit (AU) but progress up to 95.2% when herd size is more than 100 AU. This explanation implies that small farm size was less efficient and restricts rapid production.

The total beef production in Indonesia grows 6.76 percent per year between 2008 and 2012. The domestic beef production in 2010 increased dramatically in compared to prior year from 213 to nearly 350 thousand tons (Figure 1). BAPPENAS (2013) mentioned this great domestic beef production increase was due to beef and cattle import restriction. As a consequence, the ex-domestic cattle are merely utilized to produce beef with an average growth of 19.5 percent between 2008 and 2012, while the ex-imported cattle utilization dropped to 24.71 percent. On the other side, beef consumption rise on average 8.1 percent per year. Though, high domestic consumption without significant production to supply beef compels government to allow imports.

Enormous import quantities induce the government to strictly control the number of imported live cattle and beef. Since 2010, the government gradually reduces imports through the application of quota policy. Feeder cattle import is reduced 33 percent from 600.000 heads (equal to 110.000 tons of beef) in 2010 to 400.000 heads (equal to 72.000 tons of beef) in 2011 (MOT 2011). In 2012, the quota is reduced down to 34.000 tons of beef. The quota policy had lifted in the beginning of 2013 and has been replaced with price reference policy. Thus, import will be permitted if the beef price in traditional market has reached 15 percent above IDR 76.000 per kg.

Figure 1. Indonesian Beef Production, Consumption, and Import

Source: BAPPENAS (2013), MOT (2011)

0 100.000 200.000 300.000 400.000 500.000 600.000 -100.000 200.000 300.000 400.000 500.000 600.000

2008 2009 2010 2011 2012

Q u a n ti ty ( T on s) Q u a n ti ty ( T on s)


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Other issues beside production scarcity is the high beef price. Figure 2 below implies that local beef price in the market is above the imported beef. Though it might also reflect higher demand for local beef, higer logistic cost could also expressed in the market price. Ilham (2009) mentioned that high domestic beef price are resulted from the marketing cost such as illegal levies, retribution, and high transportation cost. He also mentioned that beef price increase influence higher poultry product price, thus it is important to maintain beef price.

Jan Feb Mar Apr Mei Jun Jul Agust Sep Okt Nop Des Jan Feb Mar Apr Mei Jun Jul Agust Sep Okt Nop Des

2010 2011

import parity 37.9 40.3 42.6 44.9 43.7 40.6 40.0 41.6 41.5 42.0 42.3 46.5 51.0 50.0 50.2 50.9 47.6 46.0 46.6 46.9 46.3 47.4 51.3 52.4 domestic 61.9 61.9 61.4 62.0 61.8 61.6 62.3 62.8 66.5 65.2 65.3 64.8 65.2 65.6 65.5 65.7 65.5 65.7 66.6 68.8 69.0 67.0 67.2 67.9

30.000 35.000 40.000 45.000 50.000 55.000 60.000 65.000 70.000 75.000

P

r

ic

e

(

ID

R

/k

g

)

Figure 2. Comparison of local and imported beef price 2010-2011

Source: MOT (2012)

Feedlots have important role to boost beef production as small farmers have limited ability to supply beef through better feeding and management. Feedlots have merely strict nutrient rules and feed ingredient selection for cattle feeding than smallholders. Willis (2009) implied that feedlots in Indonesia commonly used Elephant Grass, Corn Silage, Corn Stover, Pollard, Kopra Meal, Palm Kernel Cake, Brewers’ Grain and mineral additives in their feed ration. He also added that the feed ration are generally energy-rich because the abundance amount of dried tapioca pulp (onggok) and tapioca chips (gaplek) that commonly used as concentrates in feedlots, particularly in Lampung Province and Java Island.

Unlike smallholders, feedlot operates in a large herd size. APFINDO has 26 members with holding capacity of 1.25 million cattle per year in optimum function (in average 44 thousand cattle per member). Feeders are almost 100 percent imported but recent regulation has to take it at least 10 percent from local feeder producer. Each breed types has different average daily gain (ADG) which decide the fattening period and finisher’s final weight.

Despite the highlight of feedlots in comparison with household-size farmers, feedlots are facing several constraints to accelerate the beef sector development. Some concerns of Indonesian feedlot industry are cattle specifications and continuity2. The accepted cattle weight in feedlot is


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approximately 280-350 kg. The local feeder weight is usually lower than 250 kg. As a result, the lower initial weight, the longer fattening period, the higher cost for feeding, labor, and medicine.

In terms of continuity, finding domestic producers who could provide large cattle numbers and relatively uniform feeder with fast preparation process and exact transport costs (i.e. 5.000 cattle in a single delivery) are tough. By contrast, the importers can relatively easy to handle this requirement with faster responses and lower delivery cost.

To overcome these difficulties, government set a policy to support producers through price regulation and trade protection. The price regulation is imposed to input and output in the form of subsidy/tax such as subsidy of fuel and electricity while the trade policy is imposed at the border (such as import quota). This type of policy is also accompanied with other beef production-enhancement regulation, including the breeding program in prioritize province including West Java and Lampung. In such a way, the domestic producer is expected to obtain a gain from affordable input cost and adequate profit from the sales.

Thawaf, et al. (2012) stated that feedlot in West Java contributed to absorption of labor; increase market access of small holder farmers through partnership, and at the same time supplying beef demand that cannot be fulfilled by local producers through their investment. In Australia, feedlot industry also plays a role for development of the meat quality standard (ALFA 2006). To conclude, the role of feedlot is not only for supplying beef for domestic and foreign market, but also to broader extent such as employment, investment, and guarantee system. Thus, their existences are essential for sustainable beef production in Indonesia.

Study of comparative and competitive advantage of livestock and livestock product in Indonesia are mostly focused on the farmer level farm on districts. For instance study of Indrayani (2011) in Agam district, Hayandani (2013) in Indragiri Hulu district, Rouf (2014) in Gorontalo district. However, study of comparative and competitive advantage at the firm-level in Indonesia is scarce, unlike those in many developed countries. The study of Perdana (2003) and Yuzaria and Suryadi (2011) give an insight of how the firm-level competitiveness assessment has been done at feedlot in West Java.

Competitiveness factor assessment was mostly rooted to Porter’s Diamond elements: 1) Resource endowment, 2) demand pattern, 3) product specialization, 4) technological superiority, and 5) trade policy (Gupta 2009). Available local breed cattle, alternative feeds, growing demand, technology status, and beef and cattle policy related in Indonesia will improve competitiveness.

As mention earlier, Indonesia has several local breed of beef cattle. MOA and Statistics Indonesia (2011) stated population of Bali cattle, PO/Ongole, and Madura cattle are respectively 4.8 million head (32.31 percent), 4.3 million (28.88 percent), and 1.3 million (8.67 percent). Local cattle is more adapted to tropical climate and well response to low quality feeds. Its growing population gives opportunity for feedlots to rely on these local cattle instead of imported ones. Though, lower average daily gain prevents feedlots to utilize this breed.

Feed also plays a role as large as breed in beef production. Feedlots commonly use high protein feeding such as concentrate and small portion of forages, which take 60 percent of the production cost, particularly when the


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material is imported. Indonesia’s pastures and non-pastures could carry up to 19 million cattle (Rouf 2014).

The industrial waste to be used as alternative feed remains on research level and applies on a very limited location. Study of Khasrad, et al. (2005), Santi (2008), and Badarina and Sutrisno (2009) suggest that most of the industrial waste are complementary thus it needs to combined with other feed types and concentrate. Most of it needs additional processing like fermenting, ammoniating, or ensiling. In most work, adding industrial waste in feed ration does take effect. Fermented rice straw and concentrate resulted to 1.34 kg ADG of sample BrasPO (Brahman-Angus-PO) cross and 0.67 kg to sample PO. The lower ADG of 0.33-0.34 kg are shown in sample Bali cattle fed with fermented rice straw added with rice bran, forages and probiotics (Sugama and Budari 2012). Feeding 40 percent of Palm Oil Frond to sample PO gives ADG of 0,829 kg (Sianipar 2009). Moreover, its cheap price is noticeable option for production cost-saving and could be great source of competitiveness.

Productive, qualified, yet low-cost of labor are another source of competitiveness because they more quickly to adapt to new technology which boost productivity. Rouf (2014) stated that minimum labor wages per month in Indonesia is lower in comparison with Vietnam, Thailand, Cambodia, and Malaysia. Low labor cost should benefited feedlots to gain competitiveness due to lower cost of production.

Technology in breeding, feeding, and management will give great impact to competitiveness. Ministry of Agriculture have breeding program to boost cattle population and productivity, such as artificial insemination and releases new breed with favorable specification for sales. Through this program, the crossbred has better carcass percentage. MOA (2012) reported that study of 172 crossbred with live weight of 370.24±75.61 kg have carcass up to 190.46±42.75 kg or dressing percentage of 51.30±3.37 percent. This figure is the highest among other breed such as Bali Cattle, Madura Cattle, PO/Ongole, and Friesian Holstein.

The demand pattern also plays role on competitiveness. Porter (1990) stated that strong domestic demand creates pressure for innovation by challenging company to meet domestic consumer’s high standard as an insight of more sophisticated world’s consumer. As in Indonesia, the consumer demanding fresh instead of frozen meat which challenge the producer for fast delivery with good quality of meat. Unlike most of the foreign market, the butcher in traditional market rarely differentiated price of each beef cut except in the departement store. The high demand of some edible offal is some fulfilled by imported supply, and so does for restaurant and hotel. With increasing domestic and foreign tourist coming to indonesia, the demand for high quality of beef will increase. The producers will be benefited if they could provide this beef type.

Rouf (2014) implies that the impact of policy to competitiveness are vary. Russian government subsidy on dairy industry increase revenue, while transfer from consumer will increase with lower competitiveness level. Similarly, in Indonesia, the quota policy protect the local producer while the transportation retribution and tax for veterinary medicine hamper production.

In order to measure Indonesian feedlot industry’ competitiveness, this research took representative provinces according to feedlot industry (number of firms) and cattle population (head) as illustrated in Figure 3. Industry in this term


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is all companies in province who fattening beef cattle. The selected provinces are Banten, Lampung, and West Java. They not only act as producers for national but also for their regional consumption. The local cattle population is growing up to 7.8 percent from 2011 to 2012. They collectively contribute to more than a quarter of the average beef production in Indonesia between 2009 and 2013. Their location to the main market (particularly DKI Jakarta) and availability of alternative feed such as industrial waste, forages, grains, and tubers are also beneficial to beef producers.

Figure 3. Cattle and Feedlots Distributions in Indonesia

Source: Statistics Indonesia (2012), with modification

Studying comparative and competitive advantage of feedlot would be very useful for acknowledging the potential of bigger market share in comparison with foreign firms, better allocation of resource used, and answer whether it is better to produce within the country or purchase commodity from foreign country.

This study is organized in seven chapters. The next chapter point out earlier studies to compare results and discover the source of competitiveness. The third chapter gives an overview of beef trade in the world and Indonesia. Chapter four illustrates the framework which link theory and evident of competitiveness and policy analysis to draw recommendation for future regulation. The fifth chapter demonstrates the methodology to measure competitiveness and analyze policy. The interpretation of indicators in these subjects will be revealed in chapter six. Finally, chapter seven will conclude the competitiveness status and impact of policy to the Indonesian feedlots.

Problem Statement

According to description on the background, the feedlots are having a great role to improve beef productivity and competitiveness through more feeding practice, management, and technology in comparison with smallholders. However, low local cattle productivity due to genetics and environmental factors, input supply quality and continuity may restrict feedlot’s performance that leads to its level of competitiveness.


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Government efforts to boost competitiveness, too, can either regenerate or degenerate the profitability and cost efficiencies of feedlots. If they are benefited from the policy practices then such regulation are plausible. It means that under the existing policies and technology, a feedlot can operate efficiently and has a competitive advantage. In contrast, if the existence of policy impedes the feedlots to gain profit then the policy efficacy should be evaluated.

Therefore, further assessment is needed to evaluate whether feedlots have comparative and competitive advantage under the applied policy and whether changes in policy and production component will affect competitiveness. Further comparison of the competitiveness indicator and policy impact between provinces will be enacted to arrange a hierarchy that reveal which province create greater profit, which province that have more comparative and competitive advantage, and which province that gain larger benefit from the application of regional and national policy than others. Thus, the Policy Analysis Matrix (PAM) will be employed to correspond with these following questions:

- Does Indonesian feedlots have comparative and competitive advantage?

- What are the impacts of policy to the profitability and competitiveness of Indonesian feedlots?

- What are the impact of production variable adjusment to comparative advantage of Indonesian feedlots?

Research Objectives

- To assess competitive and comparative advantage of Indonesian feedlots. - To analyze the impact of policy to the profitability and competitiveness of

Indonesian feedlots.

- To evaluate the impact of adjustment in production variable to

comparative advantage.

Scope of Research

The research deals with the assessment of competitive and comparative advantage of feedlots gates particularly on Banten, Lampung, and West Java Province. It covers the aggregate measurement of feedlot performance during 2011. All data, input and output information and the policy to be evaluated were also associated to this year.

Benefit of Research

This thesis is expected to be particularly benefited researcher, company, and government. It is hoped to be one example for researcher on how PAM is performed to measure comparative and competitive advantage of feedlot companies and conduct further research to complete shortcomings of this study. For companies, it is expected to give an overview about their performance and their company’s relative competitiveness level. Government could also take advantage of this research to (re-) evaluate policy as this thesis reviewed both regional and national policies beef sectors. Comparison of provinces will help both local and centre government to decide the best resource allocation for each province to have better comparative and competitive advantage.


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2

LITERATURE REVIEW

Competitiveness Study Using Various Methodology

The most interesting question of earlier studies was to what extent does one country/region is comparatively more competitive than others. Thus, competitiveness study has been conducted with various methodologies across countries. Several authors have demonstrated the use of Competitiveness Index (CI) using large data set such as Wanti (2013) and Coronel, Procopio, & Lίrio (2013). Wanti (2013) investigated several most potential provinces in Indonesia to increase competitiveness according to the prioritized province for artificial insemination program between 1999 and 2010. She reported that the prioritized province (i.e. West Java and Lampung) presented higher potential increase in competitiveness than those which did not receive the program, despite some constraints due to high feeder cattle price and low feed availability. Thus, the continuity of breeding program will contribute the competitiveness level in Indonesia beef sector as a whole.

Coronel, Procopio, & Lίrio (2013) took a broader example of international competitiveness between Brazil and Australia between 1999 and 2009. They claimed that Australia was more competitive than Brazil in terms of productive structure (i.e. product diversification) and free of FMD. These quality and product standard of Australian beef were more acceptable to European and East-Asian Countries, as well as to Indonesia, and thus made Australia gained advantage in the international competition.

Fertȍ & Hubbard (2002), Sarker & Ratnasena (2014), Doanh (2011), and Tereszczuk & Mroczek (2014) employed Revealed Comparative advantage (RCA) for competitiveness study. Their findings suggested that although RCA provided an insight of sector’s competitiveness, it was not sufficient to present the potential impact of government intervention to support sustainability in the international market. Moreover, it ignores the possibilities of imported commodities (such as beef in this research) to have competitiveness when the export value of the respective product is small or even zero. As Tereszczuk and Mroczek (2014) mentioned its indicators shows how competitive a country with certain product in international market. This defect, then, will be invalid for measuring the net importing countries competitiveness.

Policy Analysis Matrix has been used commonly to measure relative competitiveness in many countries. Comprehensive information about the difference between actual and efficiency price, profitability, and incentive from government intervention are displayed in single matrix. Elbadawi et al (2013) used PAM to explain comparative advantage in two sheep producers states in Sudan; Gadarif and North Kordofan. Based on informations on the matrix, Domestic Resource Cost (DRC) as comparative advantage indicator are known 0.26 for Gadarif and 0.18 for North Kordofan. North kordofan possess higher comparative advantage in sheep production due to cheaper input price as they rely on natural resources. However, the tax there was also higher than Gadarif which reflected in distribution cost to the export gate EPC. Further, they also analysed the impact of 30% appreciation of Sudanese Pound to comparative advantage. Both states experienced improvement in comparative advantage.


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Lanfranco et al (2014) used PAM to evaluates Uruguay beef export chain competitiveness. They expand the standard matrix to explore the detail of profitability and incentive from farm to the export gate. They found that government intervere the beef producer in the form of Value Added Tax (VAT). They also notice some factors responsible for the difference between actual and social price are capital cost increase, labor social charge, high finisher cost, and container freight.

In conclusion, previous researches above suggest that beef competitiveness are generally determined by various factors, such as impact of policy, product characteristics, technology, and the trade pattern of a country.

PAM Study for Beef Sector in Indonesia

All researches presented in the previous section demonstrate the competitiveness assessment in various techniques. However, the best methodology to evaluate both competitiveness and government intervention is PAM. The study was first introduced by Monke and Pearson, which demonstrated how to measure the divergence due to policy intervention in input and output in a single matrix.

The study of beef sector competitiveness using PAM has been conducted in several areas in Indonesia, such as Agam District, West Sumatera province (Indrayani 2011) Indragiri Hulu District, Riau province (Hayandani 2013), Bandung Regency, West Java province (Perdana 2003) and West Java province (Yuzaria & Suryadi 2011). These studies have suggested that these research locations have comparative and competitive advantage, presented by the PCR and DRC ratio which are less than one.

Despite studies conducted by Indrayani (2011) and Hayandani (2013) which suggested that it is better to produce beef within Indonesia, they also stated that more government intervention is needed to protect the domestic producer due to 30 percent reliance of import and support to producer to compete with the foreign products. Further, Indrayani (2011) and Hayandani (2013) used the matrix policy to evaluate government intervention. They suggested that government efforts to output such as import restriction and non-tariff barrier cause domestic price of beef higher than the border price and thus, benefit the producers.

Moreover, input policy such as regional retribution, feeder cattle criteria, and medicine costs drive the private price to be higher than their social price. The subsidy to fuel and fertilizer were running inefficiently and thus have a small impact on input cost. The overall impact of policy to output and input were dominantly due to the subsidy to fuel in the output sector and non-tariff barrier.

The impact of import duty removal has been done by Perdana (2003) and Hayandani (2013). Perdana (2003) suggested that level of private profit was increase due to lower tradable input cost (imported feeder cattle) while Hayandani (2013) who used local feeder cattle presented unchanged private profitability.

Deeper analysis of comparative and competitive advantage of feedlot industry has been performed by Perdana (2003) and Yuzaria & Suryadi (2011) through splitting the imported feeder cattle and the domestic one. Their aim was to investigate performance of feedlots using either local or imported feeder cattle. The studies of Perdana (2003) indicate that both local and imported cattle are


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competitive and efficient since it uses domestic resources, although, the local cattle is more efficient using cheaper feedstock such as hay. On the other hand, Yuzaria & Suryadi (2011) affirmed that local cattle feedlots have less comparative advantage than import cattle feedlots. In conclusion, PAM study in several regions in Indonesia have shown both comparative and competitive advantage, thus further study particularly the competitiveness of production and consumption area and government intervention on output and input sector is needed.

3

THE BEEF TRADE

This section pointed out major trader of beef, recent situation of world’s beef industry, related international policy, historical and forecasted market trends, and most importantly, how those are relating to Indonesia. Moreover, more detailed Indonesia’s beef market summary including beef supply chain will be described.

Overview of World Beef Trade

The world beef trades were almost significantly unchanged over the past 5 years. Between 2010 and 2014, the total production grows from 64.975 to 65.719 thousand tons, or increases about 1.14 percent (FAO 2013). The growth reflects a slight adjustment in the production which was accomplished by exporting and importing countries, as a result of internal and natural factors.

Figure 4 summarizes the beef market shares of selected countries between 2010 and 2014. Brazil, with worldwide share of 21 percent, is predicted to continue being the top exporting country in 2014, followed by India, Australia, US, and New Zealand. On the importer’s side, the biggest demand comes from Russia and US, Japan, Hong Kong, Korea, and EU.

Food Agriculture Policy Research Institute (2002) suggested that import and export ability depend on world economic situation, exchange rate, and disease-related issues. The weakening of Peso in Argentina and Real in Brazil is predicted to accelerate the export quantity from these countries (USDA 2013). Further, Meat Industry Association (2013) reported that the FMD-recovery in Uruguay and more moderate import restriction on BSE-related case by Japan are predicted to give positive response on the US and Canadian beef export.


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Figure 4. Market Share of Major Beef Trader in the World

Source: USDA (2014)

The beef trade flow between countries in 2012 can be seen on Figure 5. Brazilian and Indian beef are shipped to meet the demand in Venezuela, Angola, and Middle East. FAO (2013) had predicted that cattle abundance is the major driver of export growth in Brazil. Further, the tremendous export growth is shown by India. India’s delivery to the international market today rises almost twice larger compare to 2010, or accounted to more than 20 percent share of beef world trade. USDA (2014) reported that India is competitive because of their product differentiation and their strategic location to the South Eastern Asia and Middle Eastern market, such as Malaysia, Philippines, Vietnam, and Egypt.

Australian beef, which is delivered to Japan, Republic of Korea, and Taiwan, is predicted to shift up in order to meet the demand from China, as Chinese consumer is growing concern on poultry product following the Avian influenza outbreak (USDA 2014). Indonesia is also predicted to share bigger import on Australian beef, following the removal of Indonesia’s quota policy imposed between 2011 and middle 2013. Since then, Indonesia applies price based policy which allows import if the beef price at traditional market goes above 10-15 percent from benchmark price IDR 76.000 per kg. Thus, the import flow from Australia is expected to increase.


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Figure 5. World Beef Distribution Flow

Source: Claxton (2012)

The EU and the US have been both major exporter and importer of beef. On the export side, the EU is predicted to expand export as a result of steady domestic demand and increase availability of slaughter cattle while the US will be decrease due to low cattle number and high cattle price. On the other hand, both the EU and the US import are anticipated to be stagnant. In the case of the EU, larger High Quality Beef quota―rise from 20.000 MT to 48.200 MT―seems not change much of the imported quantity (Flach 2013). Declining of the US import is associated with the limited supplies from Canada, Australia, and New Zealand (USDA 2014).

Beef Market Overview in Indonesia

Beef is accounted for 7 percent of total fresh meat consumption and 18 percent of total meat production in Indonesia. Beef production were 545.6 thousand tons in 2013, increased from 508.9 thousand tons in the previous year, as a result of incline cattle population in major producing provinces, from 612 thousand to 636 thousand cattle (DGLAHS 2013). The production and consumption figure showed that beef have great difference. However, it does not mention about how the beef finally comes from farmers to the consumer’s tables. An agribusiness approach, then, is adopted to illustrate the beef chain in Indonesia.

Feedlots production structures, in principle, consist of feeders, feeds, medicine, equipment, and capital. Feeders are purchased both from local farmers and foreign traders. Its breed type choice depends on each feedlots’ preferences. Most of it considers the price, initial weight, and potential gain. Commonly observed imported breed are Australian Commercial Cross (ACC), Brahman Cross (BX) while the local breed are Bali cattle, Madura cattle, PO, Limousine, and Sumbawa Cattle.


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There is a slight different between domestic and imported feeder cattle supply chain as shown in Figure 6. Particularly due to the small cattle ownership, farmers sell their livestock to “Blantik”, a person who collects cattle from the farmers, resale it to larger cattle trader (i.e. trader who collect and distribute throughout other province) or sales yard. Some also bring the finisher directly to the abattoir. Existence of sales yard, or in Indonesian terms refer to “Pasar Hewan”, is vary among provinces. As Soedjana, et al (2012) reported, there are 85 sales yards in West Java spread in 23 regions. About 80 percent of the cattle traded there are feeder or breeder for feedlot and breeding. Similarly, Banten has active sales yard. The imported cattle (BX) are rarely seen on this sales yard because it directly purchased by the abattoir, butcher, or feedlots and will be slaughtered in near abattoir. Thus, the cattle number slaughtered usually higher than the cattle population. On the other hand, Lampung and DKI Jakarta does not have well-function sales yard, thus the cattle transaction take place in the abattoir.

The cattle imports from Australia go to Indonesian market through main ports in Indonesia; Tanjung Priok port in Jakarta and Panjang port in Lampung. Soedjana, et al (2012) reported that after all the requirements to harbor are fulfilled, a day before arrival the ships spoke person contact with Panjang port officer. Docking fee for ship for cattle is 910 IDR/cattle/day and 715 IDR/cattle/day for service. The cattle’s unloading cost is 40.000 IDR/cattle and the process should be finished within four hours to be transported with truck to the feedlots. Panjang port also rent small and big truck with capacity of 13 cattle and 20 cattle worth for 60.000 IDR/cattle. Another cost for delivery to the feedlot is illegal levies, charged at least 20.000 – 25.000 IDR/truck along its way to feedlot.

Figure 6. Supply chain of domestic cattle (left) and imported cattle (right) in Indonesia

Source: BAPPENAS (2013) Quantity

Farmers

Blantik

Butcher/Abat toir Sales yard

Retailer/ Traditional

Consumer

Meatball Vendor, Restaurant, Food Stall, Catering

Australian Exporters

Indonesian Feedlots

Retailer, Traditional

Market Butcher

Consumer

Retailer, Supermarkt

Hotel, Restaurant

Meatball Vendor, Food Stall


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Feed that is used in feedlots are classified information because it is the key aspect of feedlots performance in raising cattle with maximum average daily gain and at the same time, giving out minimum feed cost possible. Its price and quantity depend on feedlots’ production type, whether it is grain based or grass based. Deblitz (2011) mentions that the sample feedlots in his study are having a contract with farmers and agriculture industry to supply their side-product for cattle feed. The typical ration in most of Indonesian feedlot as stated in Willis (2009) is shown in Table 1.

Table 1. Selected feed type in the feed ratio of common Indonesian Feedlot

Feed Type Ration Inclusion (percent)

Roughage

 Chopped grass  Corn Stover

10-20 5-15 Energy Concentrates

 Dried Tapioca Pulp (Onggok)  Dried Tapioca Chips (Gaplek)

20-45 20-45 Protein Meals

 Kopra Meal  Palm Kernel Cake  Soybean Meal

5-15 2-10 0-5 Wet By-Products

 Brewer’s grain 5-20

Mineral Additives  Limestone  Salt  Premix

0.75-1.5 0.25-0.5 0-0.10

Urea 0.5-1.2

Source: Willis (2009)

The feedlot operates for 90-100 days per period of production with an average daily gain of 1.0-1.5 kg (Deblitz 2011). Not all feedlots have integration with abattoir; thus, sometimes, the beef processor or trader helps them to distribute beef to the consumers, particularly for the traditional market. Some feedlots who had a contract with abattoir marketing beef. Price is determined according to deal. The price is in IDR per kg per live weight or in the form of carcass. Hadi et al (2001) stated that cattle produce meat, side product such as skin, head, legs, bones, and edible offal (i.e. liver, tongue), and waste product like feces and urine. Table 2 shows beef product and its derivation that traded in Indonesia.


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Table 2. List of Harmonization System (HS) code for beef cattle and products HS Code Product Name

020120000 Meat of bovine animals, fresh or chilled other cuts with bone in 020130000 Meat of bovine animals, fresh or chilled boneless

020210000 Meat of bovine animals , frozen carcasses & half-carcasses 020220000 Meat of bovine animals , frozen other cuts with bone in 020230000 Meat of bovine animals, frozen boneless

020621000 Edible offal of bovine animals, frozen tongues 020622000 Edible offal of bovine animals, frozen livers 020629000 Other edible offal of bovine animals, frozen 0102291010* Finisher (ready-to-slaughter)

0102291090* Feeder (cattle weighted under 350 kg)

Source: MOT (2011)

* Notes: The HS code for beef cattle (finisher), breeder, and feeder (cattle with <350 kg) is

identical in the ministry of agriculture’s regulation No. 85 in 2013. Thus, it is adopted

from Rouf (2014).

Beside meat that come from domestic production, imported meat is also taken place in Indonesian market. However, the import purposes are specifically for industry, hotel, restaurant, and catering, as shown in Figure 7. It is not right to imported beef for traditional market as it will drop domestic beef price. Detailed description of each product imported to Indonesia that goes to specific market is organized in Ministry of Trade Regulation No. 24 in year 2011.

Figure 7. Imported beef supply chain in Indonesia

Source: BAPPENAS (2013)

Beef cattle offal are benefited beef wholesaler because it gives bigger revenue than the meat itself. The market for edible offal is considerably promising. Statistics Indonesia (2011) showed that the production of edible offal is in total 37.758.407 kg with an average price of 40.176 IDR/kg. Figure 8 indicate that the highest edible offal price was in Bengkulu, Sumatera, and the lowest price is in Bali. The edible offal also imported from foreign country. For

Foreign Beef Exporters Indonesian Beef

Importer Agent

Supermarkets Beef Processing Industry (NAMPA) Consumer

Hotel Restaurant,


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instance, the price of imported frozen tongues and frozen livers are respectively 25.632 IDR/kg and 18.323 IDR/kg3.

Figure 8. Comparison of local and imported beef and edible offal price during 2011 in Indonesia

Source: (a) MOA (2013), (b) Statistics Indonesia (2011)

Beef consumers are concentrated in Java, particularly in DKI Jakarta and West Java. Thus, cattle and beef trade movements are towards these area. Before 2000, DKI Jakarta was supplied by the provinces in the eastern part of Indonesia but recently, East Java and Nusa Tenggara mainly shipped cattle to Kalimantan and Sulawesi Island, as the demand in Jakarta has been overtook by imported beef and cattle (Soedjana et al. 2012).

Figure 9 implies that beef in DKI Jakarta, the central consumption area, is supplied by the individual seller, the feedlots, and the seller in cattle market. Similar to Lampung, DKI Jakarta did not have particular cattle market. However, provincial government imposed that all cattle from outside Jakarta were gathered in one abattoir, CV. Dharma Jaya, thus this abattoir has a function as a cattle market.

Most of the farmers in DKI Jakarta are also beef seller. Soedjana, et al. (2012) reported that those farmers have employees in the production center to give information about beef and cattle availability. Cattles which are distributed using truck from production center (particularly NTB, NTT, and Lampung) need to be complemented with legal administration and letter of recommendation from quarantine agency for transit. After the slaughtering process in abattoir is done, the beef are distributed to the market. As for DKI Jakarta, frozen beef also enters the chain as it is preferable to DKI Jakarta’s consumer as well.

31 USD = IDR 8779.49

-10.000 20.000 30.000 40.000 50.000 60.000 70.000 80.000 90.000

Sumatera Java Bali & Nusa Tenggara

Kalimantan Sulawesi Maluku & Papua Local Beef (a) Local Offal (b) Import Beef (b) Import Offal (b)


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Figure 9. Beef Supply Chain in DKI Jakarta

Source: Soedjana, et al. (2012)

Australia has been the major supplier of live cattle to Indonesia while in the case of bovine meat, has also been supported by New Zealand and US. In the middle of 2011, Australia banned the export of live cattle due to animal treatment-related case in several Indonesian abattoirs. The embargo had caused lower deliveries from Lampung to DKI Jakarta which implies that Lampung feedlots were growing a great number of Australian cattle. However, the embargo only last for a month, as Indonesia could provide traceability and reconsideration of Australian government due to the large live cattle market share to Indonesia. Thus, the export ban has lifted. Recent US beef export were discounted to 12.679 kg, or trimmed to almost 65 percent of the export volume to Indonesia in comparison with the export volume in 2011 (UNCOMTRADE 2014), particularly after the discovery of BSE. The market was slowly restored in June 2013.

The search for alternative supplier is worthwhile, although beef from major producers in the world, such as Brazil and India could not simply enter the Indonesian market due to the non-tariff restriction. These countries could not provide the FMD-free qualification as Indonesia imposes the country-based system for beef importer, which permit only non-FMD and non-BSE countries to supply beef for Indonesia. Moreover, the government also prefers halal4 beef to non-halal one, as the important attribute attached to the imported product. High distribution costs from North American countries also hinder the possibility to carry out trade, as well.

4 Cattle are slaughter under islamic law

Sales yard outside Jakarta

Individual Farmer outside

Jakarta

Feedlots Farmers/Cattle Seller in Jakarta

Butcher

Abattoir

Beef Market

Frozen Beef Imports

West Java

Retailers

Meatball Vendor

Restaurant


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Indonesian Government Policy related to Live Cattle and Beef Trade

Recent government regulation is related to any efforts to improve supply ability of cattle and beef. The intervention schemes are mostly aimed to influence price of output and input, along with trade policy to protect domestic producers. Entire regulations added with descriptions are written in Appendix 1.

In the input sector in relate to trade intervention, government also set a rule where the imported feeder cattle’s live weight must not exceed 350 kg, less than 30 months of age, and have minimum 60 days of fattening in feedlots. Additionally, feedlots have to purchase 10 percent of feeder cattle from domestic producer in order to get higher import quota proportion from the government. Between 2010 and 2013, government also rules quota for imported cattle that depend on the feedlot’s holding capacity and other requirements. In order to maintain the livestock supply, government prohibited slaughtering productive cows. Most of the feed regulations are particularly on technical and safety requirement, but regulation on many imported product are not listed specifically on the law manuscript. Imported premix and worm control are known to have 0% tariff. Government gives 5 percent import tariff to biological medicines and plus 10 percent value added tax to pharmaceutical medicines and premix.

In the output sector, government of Indonesia restricts import through tariff and non-tariff regulation. The tariff rate of imported beef is 5 percent. Government also imposes policy that BSE, RVF, CMD, and FMD-related product are restricted to Indonesia. Other intervention is imposed by each regional government. For instance, retribution for health-checking, rent fee for abattoir facility, post-mortem check, or even recommendation letter to distribute meat or cattle in and out of the region. Each region impose different tariff for these services. The highest service tariff is in South Lampung, overall 60.000 IDR/cattle while in Banten and Bandung is 15.000 IDR/cattle.

4

FRAMEWORK

In this part, the policy impact using PAM will be explained in brief. This framework focuses on how the mechanism to understand how the policy is formed and its impact on output and input both for producers and consumers.

Concept of Competitiveness

International trade has been stimulated particularly due to difference in domestic resource and technology among countries. Potential domestic resource and technology will determine whether a country is having an advantage to produce goods within themselves or instead purchasing them. If the cost to produce goods within is higher than to buy them, the country is better to allocate the domestic resource to produce other products which have competitiveness in the world market.

The best allocation of resource along with technology, business practices, demand pattern, product specialization, and government policy will influence the level of competitive and comparative advantage. Competitive advantage is an indicator of whether a country commodity will be successful to compete in the


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international market (ADB 1992). Competitive advantage is measured based on the price paid to producer for production factors and the output sold to consumer, under the assumption that system were intervene by government regulation.

A comparative advantage, in contrast, excluded all government intervention and therefore the measurement is based on the efficiency price. Comparative advantage is used to determine whether a country has economic advantages for expanding production and producing commodity with a comparatively lower cost than the social opportunity costs of other alternatives (ADB 1992). To conclude, country will gain competitiveness if the production of certain commodities is profitable both when they are measured at actual market prices and in their efficiency prices.

Agricultural Policy Analysis

Government uses instrument by influencing the cost of purchased input and output price for various objectives, such as promoting growth, improving nutrition status, etc. The significance of government intervention is analyzed through identifying the effect of policy changes to these objectives. Monke & Pearson (1989) explained the effect of this change by organizing the price policies according to policy mechanism (subsidy and trade), recipient of the policy (producers or consumers), and commodity group (importable or exportable), which is illustrated in Table 3.

Table 3. Classification of Commodity Price Policy

Instrument Policies affecting

producers

Policies affecting consumers Subsidy policies: Producer subsidies Consumer subsidies 1. That do not change

domestic actual prices

On importable goods (S+PI, S-PI)

On exportable goods (S+CE, S-CE) domestic market 2. That do change

domestic actual prices

On exportable goods (S+PE, S-PE)

On importable goods (S+CI, S-CI)

domestic market Trade policies (all of

which- change domestic market prices)

Restrictions on imports (TPI)

Restrictions on exports(TCE)

change domestic market

Source: Monke & Pearson (1989)

Where:

S : Subsidy policy C : Policy affecting consumers [(+) = subsidy, (-) = tax] I : of importable goods

T : Trade policy E : of exportable goods


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Output Policy Subsidy

Subsidy on importable and exportable goods is given to both producer and consumer (Figure 10a). Koo and Kennedy (2005) stated that the subsidy will help to reduce the quantity of imported goods, in this case, imported beef. Subsidy on importable commodity given to producers increases the output price (Pp) beyond

its world price (Pw). With higher beef price, the producer increases the beef

supplied (Q1-Q2). However, as a result of equal consumer beef price with the

international beef price, the demand remains unchanged (Q3) and the import

quantity depresses from Q3-Q1 to Q3-Q2. Subsidy causes the previously imported

beef (with opportunity cost of Q1CBQ2) replaced by domestic beef production

(with opportunity cost of Q1CAQ2). Although the efficiency depletion occurs

(CAB), subsidy has accelerated domestic beef production (Monke & Pearson 1989).

Figure 10b illustrates the mechanism of subsidy on exportable output to producers. Koo and Kennedy (2005) mentioned that subsidy on exportable goods aim to promote the export commodity’s competitiveness at international trade. In the case of beef as exportable goods, subsidy increases the beef domestic price (Pd) beyond its world price (Pw) (Monke & Pearson 1989). As a consequence,

producers are encouraged to supply beef in larger quantities (from Q1-Q3 to Q2

-Q4). However, consumers deal with more expensive beef price and thus reduce

their consumption (from Q1 to Q2).

(a)S+PI (b)S+PE

Figure 10. Mechanism of Subsidy Policy on Output to producer

Source: Monke & Pearson (1989)

Subsidy on importable output to consumer process is depicted in Figure 11a. The subsidy causes the beef domestic price (Pd) to drop below its world price

(Pw). As a consequence, the beef consumption increase (from Q3 to Q4) but it

pushes down domestic production (from Q1 to Q2). Further, tighter domestic

production and higher demand will trigger greater quantity of imported beef (from Q1-Q3 to Q2-Q4). Both consumers and producers loss efficiency which shown by

the area of BAF for producers and EGH for consumer (Monke & Pearson 1989). Figure 11b portrays the process of subsidy on exportable output to consumer. The subsidy drives consumer’s prices (Pc) to decline below its world


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However, the supply remains unchanged because domestic price (Pd) is equal to

world price (Pw).

(a)S+CI (b)S+CE

Figure 11. Mechanism of Subsidy Policy on Output to Consumer

Source: Monke & Pearson (1989)

Wild and Wild (2014) stated that despite of the benefit to encourage export flows or slowing down import flows, subsidy leads to resource wastefulness and create an unfavorable impact for developing countries. Developed countries (such as the EU and the US) has applied heavy support to production in the form of direct payment and export subsidies. In the international market, it is hard for the developing countries to compete with them due to higher commodity price. Therefore, the WTO set a countervailing duty which allows the injuried country to put extra charges (from the duty) on the imported product from the respective subsidized exporting country.

Trade policy

Trade policy can be imposed in the form of restriction to import and export. Import and export restrictions are usually the application of tariff (tax, ad valorem) and non-tariff barrier (quota, bans, halal-requirement). Figure 12a represents the mechanism of beef’s import tariff. It caused the domestic price (Pd)

to go beyond the world price (Pw) and thus makes the import quantity decline

(from Q3-Q1 to Q2-Q4). As a consequence, the domestic production is increases

(from Q1 to Q2). The transfer income goes to consumer (PdABPw), to producer

(PdEFPw), and to government budget (EABF). However, the efficiency loss also

occur (EFG for producer and ABC for consumer) (Monke & Pearson 1989). The export restriction mechanism to output is illustrated in Figure 12b. The restriction causes the domestic beef price (Pd) to be less than the global beef

price (Pw). Subsequently, the beef consumption will increase (from Q1 to Q2)

while the domestic production will fall (from Q3 to Q4). Thus, the exportable

goods will be reduced (from Q1-Q3 to Q2-Q4). The transfer income to consumer

(PdABPw), to producer (PdEFPw), and to government budget (EABF) occur

(Monke & Pearson 1989). Wild and Wild (2014) mentioned that rescuing the local producers from the imported product is one of the reasons why government use tariff and non-tariff barriers. Along with domestic policy to regulate trade, every country also bounded by trade agreement in global business through WTO such on agricultural product.


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(a) TPI (b) TCE Figure 12. Mechanism of Trade Policy on Output

Source: Monke & Pearson (1989) Input Policy

Subsidy or Tax to Tradable Input

The mechanism of subsidy apply to tradable input is describes in Figure 13a. In this case, tradable input are feeders. The subsidy on feeders, for example due to the will reduce costs of production and thus shifts down the supply curve (Monke & Pearson 1989). As a result, feeders supplied will expand (Q1-Q2). Cost

before and after subsidy (Q1ACQ2 and Q1ABQ2) causes a drawback in efficiency

(CAB). While, levies implemented to tradable input will increase cost of production and thus shift up the supply curve. Consequently, quantity supplied will dwindle (Q1-Q2). This cost adjustment also causes deficiency, shown by area

CAB (Figure 13b).

(a) S+TI (b) S-TI

Figure 13. Mechanism of Subsidy Policy on Tradable Input

Source: Monke & Pearson (1989)

Subsidy or Tax to Non-Tradable Input

Subsidy to non-tradable input mechanism is shown on Figure 14a. The illustration implies that subsidy benefits both producer and consumer because it improves supply capacity of producer (Q1 to Q2) due to more favorable price (Pp).

For consumers, it cuts down the price (Pc). However, inefficiency also occurs for


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In contrast, tax to non-tradable input reduces consumer and producer’s surplus, as shown in Figure 14b. The producer experience a loss due to a lower output price (Pd to Pp) while consumer price is higher (Pd to Pc). Moreover,

consumers also attained a fall in efficiency (BAC) and the producers get lack efficiency (BAD) (Monke & Pearson 1989).

(a) S+N (b) S-N

Figure 14. Mechanism of Subsidy Policy to Non-Tradable Input

Source: Monke & Pearson (1989) Concept of Policy Analysis Matrix

Monke and Pearson (1989) introduced PAM to best analyze firm’s profitability and impact of government policy in a single matrix. PAM consists of rows and columns that reflect commodity price and quantity information (Table 4). The first row reflects the revenue, cost, and profit measured at a market price. The second row represents similar categories, but measured at its social price. The last row equals to difference between the first and the second row.

Table 4. Structure of PAM

Description Revenues (Rev) Cost of Inputs Profits (П) Tradable (T) Domestic Factors (DF)

Private Price (p) Revp CTp CDFp Пp

Social price (s) Revs CTs CDFs Пs

Transfers (t) Revt CTt CDFt Пt

Source: Monke & Pearson (1989)

Private prices reflect the actual firm budget and thus also include the government policy to output and input. On the other hand, Social price reflect price of commodities excluding all government intervention to output and input. Pearson et al. (2003) suggested employing import or exporting price of commodity as comparison because it tells the amount of foreign exchange saved (or obtained) if replacing a ton of import (or export) by producing an additional ton of importable goods (or exportable goods). As domestic factors usually have no international price, social prices are estimated by excluding all divergences (such as policy and market failure) from their private prices. If the divergence is


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effortful to measure, estimating social price can be done by the observable private price. Moreover, the social valuation must stand on the convertibles exchange rate, as the official exchange rate usually does not reflect the true rate of currency being exchanged. Transfer occurs due to policy and market failure. It implies any government intervention which made the market price deviate from its efficiency price, for instance tax, subsidy, or trade restriction (Pearson et.al, 2003). Thus, the value in PAM bottom row is the foundation for policy analysis.

Operational Framework

Figure 15. Operational framework of Comparative and Competitive Advantage of Feedlots


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5

METHODOLOGY

Data Description

Data were obtained from 47 active beef cattle company in Banten, Lampung, and West Java. All production structure cost and revenue were collected by enumerator of Indonesian Bureau of Statistics during 2011. The data description is explained in Table 5.

Table 5. Data Description Data Title Description Primary Data

Finisher Main output of feedlots. Because the information is not

available, it is assumed that all cattle have an average weight of 450 kg.

Feeder Main input of feedlots. Because the information is not

available, it is assumed that all cattle have an average weight of 300 kg.

Feeds Including Forages, Industrial Waste, Grains, Legumes, Tubers, Meal, and Concentrate

Medicine Categories:

Biological Availability: Including Vaccine

Pharmaceutical Availability: Including Hormones/Vitamin, Premix: Including Feed Additive & Supplement

Worker Daily employee Water

and Electricity

Water and Electricity consumption during 2011. Only the Electricity from National Electricity Company is taken into account.

Fuel Including Gasoline and Diesel Fuel

Capital Including expenditure on Spare parts, refinement, livestock service, Land/Building rent, Machinery and Equipment, Indirect Taxes, Depreciation

Secondary Data

CIF Price of Feeder (HS 0102) and Beef (HS 0201), Volume and Value of Import and Export, Annual Exchange Rate, Employment Rate, Distribution cost, Trade Policy (i.e.: Retribution for Animal Slaughtering, Import Tariffs, etc.)

Data Processing

Later, the production cost structure is analyzed in order to divide input and output to tradable goods and domestic factor components.

Determination of Output, Tradable Input, and Domestic Factor

Output is determined by the result of production process, in this case, beef. As for input, Pearson et al. (2003) suggested an approach for disaggregating input into tradable and non-tradable (domestic) component. The tradable goods consist of each exported and imported goods, act as a substitution which related to other goods that being exported or imported, or other commodities which is protected by the government. By contrast, the domestic factor component consists of each


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POLICY SCENARIO 2

30% Reduction of cattle

A.

Banten

Feedlot Budget

Banten Quantity Privat Price/Unit Social Price/Unit Privat Cost Social Cost FINISHER CATTLE 70.928 12.038.691 8.816.253 853.874.255.903 625.314.795.909

FEEDER CATTLE 87.902 9.060.012 7.234.274 796.391.362.822 635.905.706.293 FEEDS

FORAGES 4.736.270 187 187 884.506.000 884.506.000 INDUSTRY WASTE 3.479.112 1.031 1.031 3.588.060.000 3.588.060.000 GRAINS 57.680 700 700 40.376.000 40.376.000 LEGUMES - - - - -TUBERS 15.120.000 280 280 4.233.600.000 4.233.600.000 MEAL - - - - -CONCENTRATE 866.530 2.143 2.143 1.856.869.000 1.856.869.000

MEDICINE

BIOLOGIC 0,7 17.240.000 16.378.000 12.068.000 11.464.600 PHARMAEUTICAL 0,7 340.620.000 306.558.000 238.434.000 214.590.600 PREMIX 0,7 587.000.000 528.300.000 410.900.000 369.810.000

FUEL

GASOLINE 13.184 4.500 8.452 59.327.100 111.429.478 DIESEL FUEL 59.690 4.500 9.080 268.606.800 541.988.832

WATER 165.916 1.000 1.000 165.920.000 165.920.000 ELECTRICITY 548.509 981 1.800 538.140.000 987.316.200 WAGES 84.881 47.703 74.704 4.049.080.000 6.340.922.874 CAPITAL 1 11.197.000.000 11.197.000.000 11.197.000.000 11.197.000.000

PAM

revenue

tradable input cost factor cost

profit

private

853.874.255.903

250.510.155.746

573.424.093.975

29.940.006.181

social

625.314.795.909

202.624.406.398

461.084.134.405

(38.393.744.894)

transfers

228.559.459.993

47.885.749.349

112.339.959.570

68.333.751.075


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B.

Lampung

Feedlot Budget

Lampung Quantity Privat Price/Unit Social Price/Unit Privat Cost Social Cost FINISHER CATTLE 45.026 8.949.854 9.285.720 402.976.126.204 418.098.828.720

FEEDER CATTLE 62.344 5.079.794 7.161.628 316.694.677.136 446.484.536.032 FEEDS

FORAGES 375.711 979 979 367.821.069 367.821.069 INDUSTRY WASTE 6.311.039 1.444 1.444 9.113.140.316 9.113.140.316 GRAINS - - - - -LEGUMES - - - - -TUBERS 6.753.243 1.564 1.564 10.562.072.052 10.562.072.052 MEAL - - - - -CONCENTRATE 489.762 2.047 2.047 1.002.542.814 1.002.542.814

MEDICINE

BIOLOGIC 0,7 2.500.000 2.375.000 1.750.000 1.662.500 PHARMAEUTICAL 0,7 207.180.000 186.462.000 145.026.000 130.523.400 PREMIX 0,7 121.090.000 108.981.000 84.763.000 76.286.700

FUEL

GASOLINE 12.606 4.500 8.452 56.727.000 106.545.912 DIESEL FUEL 132.370 4.500 9.080 595.665.000 1.201.919.600

WATER

-ELECTRICITY 42.112 1.039 1.800 43.754.368 75.801.600 WAGES 36.418 12.896 14.180 469.646.528 516.407.240 CAPITAL 1 10.314.000.000 10.314.000.000 10.314.000.000 10.314.000.000

PAM

revenue

tradable input cost

factor cost

profit

private

402.977.021.189

116.937.287.885

232.514.019.581

53.525.713.724

social

418.099.749.426

156.507.316.306

323.367.066.536

(61.774.633.416)

transfers

(15.122.728.237)

(39.570.028.421)

(90.853.046.956)

115.300.347.140


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C.

West Java

Feedlot Budget

West Java Quantity Privat Price/Unit Social Price/Unit Privat Cost Social Cost FINISHER CATTLE 83.611 8.164.688 9.023.153 682.656.121.000 754.433.054.116

FEEDER CATTLE 113.812 5.327.151 7.350.940 606.291.560.000 836.622.242.904 FEEDS

FORAGES 26.646.382 149 149 3.981.971.000 3.981.971.000 INDUSTRY WASTE 14.291.256 786 786 11.231.591.000 11.231.591.000 GRAINS 316.421 120 120 37.912.000 37.912.000 LEGUMES 17.248 1.111 1.111 19.166.000 19.166.000 TUBERS 2.982.651 492 492 1.467.676.000 1.467.676.000 MEAL 2.571.093 1.648 1.648 4.237.625.000 4.237.625.000 CONCENTRATE 12.153.211 2.342 2.342 28.460.012.000 28.460.012.000

MEDICINE

BIOLOGIC 0,7 239.310.000 227.344.500 167.517.000 159.141.150 PHARMAEUTICAL 0,7 234.300.000 210.870.000 164.010.000 147.609.000 PREMIX 0,7 605.050.000 544.545.000 423.535.000 381.181.500

FUEL

GASOLINE 92.593 4.500 8.452 416.666.250 782.591.810 DIESEL FUEL 156.454 4.500 9.080 704.040.750 1.420.597.780

WATER 42.183 994 1.000 41.950.000 42.183.000 ELECTRICITY 833.750 1.353 1.800 1.127.800.000 1.500.750.000 WAGES 318.441 8.296 42.061 2.641.810.000 13.393.936.218 CAPITAL 1 28.840.000.000 28.840.000.000 28.840.000.000 28.840.000.000

PAM

revenue

tradable input cost

factor cost

profit

private

682.656.121.000

228.942.399.000

457.055.652.000

(3.341.930.000)

social

754.433.054.116

299.056.956.111

618.287.130.033

(162.911.032.028)

transfers

(71.776.933.116)

(70.114.557.111)

(161.231.478.033)

159.569.102.028

Competitiveness Indicators

Banten

Lampung

West Java

PCR

0,95

0,81

1,01

DRC

1,09

1,24

1,36


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Appendix 8. Sensitivity Analysis

SENSITIVITY ANALYSIS 1

Feeder cattle CIF price change

Notes: Initial CIF price: 2.68 USD/kg

A.

Policy Analysis Matrix for SA1 (CIF +10%: 2.95 USD/kg)

Province

Revenue

Cost of Input

Profit

Tradable

Factor

Private Price

Banten

12 038 691

2 878797 6 513 296

2 646 598

Lampung

8 949 854

2 006918 3 679 454

3 263 481

West Java

8 164 688

2 208670 4 082 134

1 873 884

Social Price

Banten

8 816 253

2 545739 5 767 709

502 805

Lampung

9 285 720

2 851982 5 638 087

795 651

West Java

9 023 153

3 033562 6 015 133

-25 542

Transfer

Banten

3 222 438

333 058

745 587

2 143 793

Lampung

-335 866

-845 063 -1 958 633

2 467 830

West Java

-858 465

-824 892 -1 932 999

1 899 426

B.

Policy Matrix for SA1 (CIF -10%: 2.41 USD/kg)

Province

Revenue

Cost of Input

Profit

Tradable

Factor

Privat Price

Banten

12 038 691

2 878 797

6 513 296

2 646 598

Lampung

8 949 854

2 006 918

3 679 454

3 263 481

West Java

8 164 688

2 208 670

4 082 134

1 873 884

Social Price

Banten

8 816 253

2 122 216

4 779 489

1 914 549

Lampung

9 285 720

2 428 459

4 649 866

2 207 395

West Java

9 023 153

2 610 039

5 026 913

1 386 202

Transfer

Banten

3 222 438

756 581

1 733 807

732 050

Lampung

-335 866

-421 540

-970 412

1 056 087


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SENSITIVITY ANALYSIS 2

Official Exchange Rate Change

Notes: Baseline OER: 8 779.49 IDR/USD

A.

Policy Matrix for SA2 (OER+10%: 9 657.44 IDR/USD)

Province

Revenue

Cost of Input

Profit

Tradable

Factor

Private Price

Banten

12 038 691

2 878 797

6 513 296

2 646 598

Lampung

8 949 854

2 006 918

3 679 454

3 263 481

West Java

8 164 688

2 208 670

4 082 134

1 873 884

Social Price

Banten

9 667 767

2 545 738

5 767 709

1 354 320

Lampung

10 137 233

2 851 981

5 638 086

1 647 166

West Java

9 874 667

3 033 561

6 015 132

825 973

Transfer

Banten

2 370 924

333 058

745 588

1 292 278

Lampung

-1 187 379

-845 063

-1 958 632

1 616 315

West Java

-1 709 979

-824 891

-1 932 998

1 047 911

B.

Policy Matrix for SA2 (OER-10%: 8 691.70 IDR/USD)

Province

Revenue

Tradable

Cost of Input

Factor

Profit

Private Price

Banten

12 038 691

2 878 797

6 513 296

2 646 598

Lampung

8 949 854

2 006 918

3 679 454

3 263 481

West Java

8 164 688

2 208 670

4 082 134

1 873 884

Social Price

Banten

8 731 101

2 312 801

5 224 188

1 194 112

Lampung

9 200 568

2 619 044

5 094 565

1 486 958

West Java

8 938 001

2 800 624

5 471 612

665 765

Transfer

Banten

3 307 590

565 996

1 289 108

1 452 486

Lampung

-250 714

-612 126

-1 415 111

1 776 523

West Java

-773 313

-591 954

-1 389 478

1 208 118


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BIOGRAPHY

The Author was born in Bandung on 14

th

of February 1989. The author

obtained her Bachelor Degree of Animal Husbandry in University of Padjadjaran

in 2010.

In 2011, the author aims for a Master Degree in Master Science of

Agribusiness in Bogor Agricultural University (BAU) funded by BU-BPKLN. On

her second year of study, the author participate in the joint-degree program

between Master Science of Agribusiness Bogor Agricultural University, Indonesia

and International Agribusiness and Rural Development (IARD), Georg-August

Universität Göttingen, Germany for Sustainable International Agriculture Study

Program. This opportunity was financially supported by the Indonesian

Directorate General of Higher Education (DIKTI). Between 13 and 15 August

2014, the author took part in International Workshop on Tropical Bio-Resources

for Sustainable Development organized by South East Asia Germany (SEAG)

Indonesia and Career and Development Alumni (CDA BAU) with the support

from German Academic Exchange Service (DAAD). The paper on

“Competitiveness and Policy Impact Analysis of Feedlots in Lampung”

is written

in collaboration with Dr Rachmat Pambudy, MS and Dr Ir Nunung Kusnadi, MS