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Sustain inabilit ity and Profitabil ility Cacao in in In Indonesia: Farmers and In Industry Perspective toward Improve Competitiv iveness Nunung Nuryartono & Research team International Ce In Center for or Applie ied Fin Finance

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Sustain inabilit ity and Profitabil ility Cacao in in In Indonesia: Farmers and In Industry Perspective toward Improve Competitiv iveness

Nunung Nuryartono & Research team

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Outline

  • Background
  • Framework
  • Research Results
  • Discussion

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Background

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200.000 400.000 600.000 800.000 1.000.000 1.200.000 1.400.000 1.600.000 1.800.000 2.000.000 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 Area (ha) Production (ton)

Source : Ministry of Agriculture (2016)

0,00 0,10 0,20 0,30 0,40 0,50 0,60 0,70 0,80 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 Produktivitas

Source : Ministry of Agriculture (2016)

  • 1. Decreasing in Production, Planted Area and Productivity

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2. . Under Capacit ity of In Industry ry

Year 2009 2010 2011 2012 2013 2014 2015 2016 Number of company Unit 15 15 16 16 18 19 20 20 Number pf Labour people 4000 4000 4300 4300 5300 5800 6000 6000 Investment million USD

  • 250

330 495 570 600 635 635 Installed Machine Capacity (1000) Ton 345 345 560 660 735 765 800 800 Used capacity (1000) Ton 130 151 268 310 324 391 426 392 Utility % 37 43 47 47 44 51 53 49

Source: AIKI (2017)

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3. . Pri rice volatility

In International and Do Domestic Price rice

10000 20000 30000 40000 50000 60000 Jan-08 Mei-08 Sep-08 Jan-09 Mei-09 Sep-09 Jan-10 Mei-10 Sep-10 Jan-11 Mei-11 Sep-11 Jan-12 Mei-12 Sep-12 Jan-13 Mei-13 Sep-13 Jan-14 Mei-14 Sep-14 Jan-15 Mei-15 Sep-15 Jan-16 Mei-16 Sep-16 Jan-17 Mei-17 Rp/Kg International Price Domestic Price

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  • 4. Agriculture and Environment

Source: International Energy Agency 2016.

Foods and agricultural products are the fundamental consumption by people. It is still have a lot of primary needs for life.

=

Foods and agricultural products are the fundamental consumption by people. It is still have a lot of primary needs for life. In International Ce Center for

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  • 1. Is growing cacao profitable and farmers still interested?
  • 2. How industry response dynamic of domestic supply?
  • 3. Do Cacao contribute toward green development?
  • 4. How domestic market link to international market

Research Questions

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Framework

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Vulnerability Context Shock Trend Seasons

Physical Human Social Natural Financial LIVELIHOOD ASSETS PORTOFOLIO

Livelihood Strategies Policies, Institution and Processes: ▪ Social

✓ Household ✓ neighbourhood

▪ Government

✓ Central and local ✓ Laws/policies ✓ culture

▪ Private Sector

✓ markets Livelohood Outcomes

  • Income
  • Well-being
  • Vulnerability

1 Sustainable Livelihoods Framework In International Ce Center for

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Sustainable Development Environtment Social Economics Global Warming Greenhouse gases are predominantly Carbon Dioxide

Environment Problem

Economics growth Consumption Carboon Footprint

  • Food Consumption
  • Non Food Consumption
  • Consumption for Education
  • Consumption for Health
  • Consumption for Energy and Transportation

calculation of carbon dioxide in greenhouse gases with a carbon footprint approach

  • 2. Sustainable Development Paradigm

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  • 3. Porter Diamond Model

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Research Results

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Variabel Coefisien Standar Error Z P>|Z| Marginal Effect Education 0,7456687 0,2851498 2,62 0,009 0,2150269 Age 0,4714165 0,5125924 0,92 0,358 0,1359414 Income 0,4341688 0,145213 2,99 0,003 0,1252004 Dependency Ratio

  • 0,0437945

0,0752637

  • 0,58

0,561

  • 0,0126289

Financial Literacy 1,693.992 0,8194665 2,07 0,039 0,4884931

Notes: * are significant at 5% Source : Primary Data (processed, 2017)

Livelihood : Access Capital Access to formal financial services is influenced by Education, Income and Financial Literacy

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  • There is no

no rel elationship between nutritional status (body mass index) and work productivity

  • There is a

a rel elati tionship between blood pressure and amount of cocoa picked per day (kilograms).

  • There is a

a rel elati tionship between central obesity and number of absent day due to sick

Rela elationship ip betw tween nutri triti tional statu tus, hea ealt lth statu tus, food consumption, lif lifes estyle e to work pro roductivit ity

Nutritional Status Work Productivity Health Status Work Productivity

  • There is no relationship between lifestyle and work productivity
  • There is no relationship between food consumption (energy

adequacy, protein adequacy, fat adequacy and iron adequacy) to work productivity Food Consumption Work Productivity

Lifestyle

Rela elationship ip betw tween poo

  • or die

iet t and hea ealth lth status (cen (central ob

  • bes

esit ity and hyperten ension)

Work Productivity

  • There is no relationship between poor diet and health

status (central obesity). Poor diet Health status (central obesity) Poor diet Health status (hypertension)

  • There is no relationship between poor diet and health status

(blood pressure, systolic, diastolic and central obesity).

Livelihood : Human Capital

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Liv Livelih lihood : : Physical l Cap apital Hig igh quali ality se seed is is im important for production efficiency

District Village Clon Sulawesi 1 dan Sulawesi 2

Efficiency value Maximum Efficiency Value Minimum Efficiency Value Efficienc y = 1 Efficienci < 1

Anreapi Kalapa Dua 0,937 1 0,852 3 4 Duampanua 0,924 1 0,397 7 1 Mapili Sattoko 0,800 1 0,07 6 4 Landi Kanusuang 0,858 1 0,393 6 11 Mean 0,879 1 0,420 5,5 5 District Village Local Clon

Efficiency value Maximum Efficiency Value Minimum Efficiency Value Efficie ncy = 1 Efficienci < 1

Anreapi Kalapa Dua 0,755 1 0,170 7 13 Duampanua 0,833 1 0,411 8 13 Mapili Sattoko 0,872 1 0,1 7 11 Landi Kanusuang 0,789 1 0,43 4 10 Mean 0,812 1 0,277 6,5 11,7

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Carbon Footprint : Consumption and Production Side

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The determinants of household carbon footprint

Variabel Independent Dependend Variable LnCo2 I II III lnexp 0.873 poor 0.060

  • 0.626

Expenditure quantile 2 0.449 3 0.502 4 0.799 5 1.137 hhsize

  • 0.014

0.119 age 0.002

  • 0.002

hheduc elementary

  • 0.214
  • 0.004

Secondary

  • 0.319
  • 0.273

High school

  • 0.263
  • 0.203

At least college

  • 0.354

0.288 HH.married 0.315 0.163 HH.female 0.142

  • 0.226

asset index

  • 0.011

0.031 cons

  • 6.064

8.439 8.377 R-Squared 0.681 0.333 0.466

Description: The bold issignificant at 5 percent

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Quantile Regression Estimates

Variabel independent OLS q1 q2 q3 q4 q5 coef se coef se coef se coef se coef se coef se lnexp 0.872662 0.096071 0.9125 0.157082 0.887722 0.096325 0.873674 0.133041 0.939358 0.172942 0.864684 0.190282 poor 0.059972 0.114253 0.063966 0.186812 -0.00992 0.114555 0.089633 0.158221 0.168802 0.205674 0.219746 0.226296 hhsize

  • 0.01392 0.027215 0.008608 0.044499 -0.00762 0.027287 0.028769 0.037688 -0.05119 0.048992 -0.06465 0.053904

age 0.002045 0.003218 -0.00107 0.005261 -0.00304 0.003226 8.88E-05 0.004456 0.002248 0.005792 0.00771 0.006373 assetindex

  • 0.01144 0.024428 -0.02475 0.039942 -0.01406 0.024493 0.009795 0.033829 -0.00452 0.043975
  • 0.035 0.048384

d_married 0.315053 0.220212 0.027649 0.360061 0.182505 0.220794 0.351906 0.304955 0.220886 0.396417 0.399556 0.436162 d_female 0.142149 0.253631 0.22075 0.414703 0.229683 0.254301 0.284184 0.351234 -0.09416 0.456576 -0.37705 0.502353 d_noschool 0.353534 0.251218 0.082016 0.410757 -0.04116 0.251882 0.518827 0.347892 0.613832 0.452232 0.265301 0.497574 d_elementary 0.139216 0.19557 0.00718 0.31977 -0.04933 0.196087 0.128115 0.27083 0.214855 0.352057 -0.03661 0.387355 d_sltp 0.034556 0.213228 -0.08175 0.348641 -0.15758 0.213791 0.079863 0.295283 0.140019 0.383844 -0.20999 0.422329 d_slta 0.090317 0.214802 0.048156 0.351215 -0.12135 0.215369 0.229545 0.297463 -0.01885 0.386677 -0.17094 0.425447 d_college 0(omitted) 0(omitted) 0(omitted) 0(omitted) 0(omitted) 0(omitted) _cons

  • 6.41772 1.696711 -7.01313 2.774235 -6.39537 1.701196 -6.72554 2.349648
  • 7.1599 3.054352 -5.61073 3.360587

Observation 116 116 116 116 116 116 Pseudo R-Sq 0.62 0.486 0.445 0.401 0.38 0.426

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Production side

  • Cacao agro forest sequestered more carbon stock in total and each carbon

pool as well as tree, root, herbacious, and necromass rather than Cacao- gamal shaded

  • Cacao agro forest released carbon footprint less than Cacao-gamal shaded
  • Fertilizer has big influence for rising Green House Gas (GHG) emmission in

both cultivatation system

  • Cacao agro forest having more yield of cocoa bean despite applied less

proportion of input. Moreover also has more carbon stock rather than Cacao-gamal shaded.

  • Tree diversity as an environmental component has been strong correlation

to support in rising of carbon stock

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Market and Industry

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Indonesia’s export quantity of cocoa and cocoa preparation (HS 18)

  • 50.000.000,00

100.000.000,00 150.000.000,00 200.000.000,00 250.000.000,00 300.000.000,00 350.000.000,00 400.000.000,00 450.000.000,00 500.000.000,00 2008 2009 2010 2011 2012 2013 2014 2015 2016 Kilogram COCOA BEANS COCOA PASTE COCOA BUTTER COCOA POWDER CHOCOLATE

Export Tax Figure 1. Export quantity of cocoa products, 2008-2016. Source: Ministry of Trade In International Ce Center for

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In International and Do Domestic Pric rice

20000 40000 60000 Jan-08 Mei-08 Sep-08 Jan-09 Mei-09 Sep-09 Jan-10 Mei-10 Sep-10 Jan-11 Mei-11 Sep-11 Jan-12 Mei-12 Sep-12 Jan-13 Mei-13 Sep-13 Jan-14 Mei-14 Sep-14 Jan-15 Mei-15 Sep-15 Jan-16 Mei-16 Sep-16 Jan-17 Mei-17 Rp/Kg International Price Domestic Price

20000 40000 60000 Rp/Kg Farmers price APKAI International Price

In International and Farmers Pric rice

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  • Volatility of farmer > domestic > international price
  • Farmer price shows the highest risk.
  • Ivory Coast and Ghana imposed policy of minimum price to keep the farmers price (Abbott 2013)

Volatili lity of farmer pric ice , , Exp xport tax x valu lue, , and In International pric ice

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500 1000 1500 2000 2500 3000 3500 4000

  • 10.000,00

20.000,00 30.000,00 40.000,00 50.000,00 60.000,00 70.000,00 80.000,00 90.000,00 JANUARI MEI SEPTEMBER JANUARI MEI SEPTEMBER JANUARI MEI SEPTEMBER JANUARI MEI SEPTEMBER JANUARI MEI SEPTEMBER JANUARI MEI SEPTEMBER JANUARI MEI SEPTEMBER JANUARI MEI SEPTEMBER JANUARI MEI SEPTEMBER JANUARI MEI SEPTEMBER 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 US$/MT Ton Export Quantity Import Quantity Reference Price

BK 0% BK 10% BK 15% BK 5%

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No. Company Name Location Installed capacity Info 1 PT.Bumitangerang Mesindotama (BT cocoa) Tangerang 150,000 2

  • PT. Golden Harvest

Tangerang 140,000 3 PT.Asia Cocoa Indonesia Batam 120,000 4

  • PT. Barry Callebaut Indonesia (ex.PT.GFI)

Bandung 100,000 5 PT.Kalla Kakao Industry (Ex.PT.Industri Kakao Utama) Kendari 24,000 6 PT.Cocoa Ventures Indonesia Medan 20,000 Stop Production Temporarily 7 PT.Makassar Berkat Kakao Industri Makassar 20,000 Stop Production Temporarily 8 PT.Kopi Jaya Kakao Makassar 20,000 Stop Production Temporarily 9 PT.Effem Indonesia ( Mars ) Makassar 17,000 10 PT.Budidaya Kakao Lestari Surabaya 12,000 Stop Production Temporarily 11 PT Jaya Makmur Hasta (ex. PT CWM) Tangerang 12,000 Stop Production Temporarily 12 PT.Teja Sekawan Cocoa Industry Surabaya 12,000 Stop Production Temporarily 13 PT.Unicom Kakao Makmur Sulawesi Makassar 10,000 Stop Production Temporarily 14 PT.Kakao Mas Gemilang Tangerang 6,000 15 PT.Mas Ganda Tangerang 6,000 Stop Production Temporarily 16 PT.Hope Indonesia ( ex.PT.Poleko ) Makassar 6,000 Stop Production Temporarily 17

  • PT. Barry Comextra Indonesia

Makassar 45,000 18

  • PT. Jebe Koko

Surabaya 40,000 19 PT.Cargill Indonesia Surabaya 30,000 20 PT.Transmar Cocoa Makassar 10,000 TOTAL 800,000

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Firm strategy (-) Weak structure of the national cocoa industry (+) Competition of domestic industry Demand condition (-) Domestic consumption is still low (+) There is a tendency to use cocoa-based products as a lifestyle Related and Supporting Industries (-) Lack of cacao planting activities that supply raw materials for cocoa processing industry (+) Developing a derivative industry based on processed cocoa products Government (-) Lack of government policy in maintaining the availability of quality raw materials and sustainable (+) Conducive business environment and support the development of industry Chance (+) Increasing of world demand (+) Export tax policy Factor condition/Production Element Basic element: (-) Lack of good quality cocoa seeds (+) Avability of cocoa development area Senior elements: (-) Lack of human resources of cocoa producer and capital access (+) Avability of product information, domestic cocoa industry, and cocoa processing business associations

Competitiveness Analysis for Indonesia’s Cocoa Beans Processing Industry based on Porter Diamond Model

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Discussion

THANK YOU

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