(ISSN:
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ANALYSIS ON CONCENTRATION AND
EFFICIENCY OF MEAT PROCESSING
INDUSTRY IN INDONESIA
Jafrizal,
Bernadette Robiani, Azwardi, Suhel
Faculty
of Economics, Universitas Sriwijaya
Sumatera
Selatan Province, Indonesia
drh_jafrizal@yahoo.co.id
ABSTRACT
The purpose of the
study is to find out correlation between industrial concentration and
efficiency as well as variables that affect concentration and efficiency of
meatprocessing industry in Indonesia. The data used are the result of the
1999-2013 annual survey for big and medium-scale industry by Indonesian Central
Bureau of Statistics. In order to estimate efficiency value, Data Envelopment
Analysis-Malmquist (DEA-Malmquist) and input-oriented Variable Return to Scale
(VRS)model are used.On the second stage, the equation is estimated using the
Three Stage Least Square(3SLS) regression. The findings show that industrial
concentration is 61.8%including tight oligopoly and industrial efficiency is
95.9% (inefficience) that is within the Increasing Return to Scale (IRC)
condition. Concentration and efficiency are affecting each other. Efficiency
has negative influence towards concentration. Colusion has positive significant
influence towards concentration. Concentration is significantly lower after the
implementation of anti monopoly and meat import quotasregulation. Colusion,
industrial concentration and import intensity have positive significant
influence towards efficiency. Monopoly is significantly lower after the
implementation of anti monopoly regulation and the implementation of meat
import quotas does not have any influence towards industrial efficiency.
Keywords: Concentration, efficiency, collusion, regulation,
Data Envelopment Analysis (DEA), Three Stage Least Square(3SLS).
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1. INTRODUCTION
Processing
industry including meat processing industry is one type of industry that has
significant influence towards the national economy. Meat processing industry is
one type of food industries that has significant influence towards economy
(Lambert, 1994; Ali, 2007; Knudson, et al.,2010; Ali and Pappa, 2011).In
Indonesia, it was established in 1942 and becomes the future of the national
industry as it has promising market in the future. Studies conducted in the
last decades focus on performance of processing industry in Indonesia by
analyzing growth of efficiency and productivity(see: Aswicahyono, 1998; Basri,
2001; Margono and Sharma, 2006; Ikhsan, 2007; Probowo dan Cabanda, 2011;
Setiawan, 2013; serta Ndari and Permono, 2014).
There
are some studies about Indonesian processing industry that focus on efficiency,
productivity, industrial concentration, colusion and regulation. Bird (1999);
Kuncoro (2007) and Indonesian Bank (2008)reprted that between 1975- 2006
majority of meat processing industry in Indonesia has relatively high
concentration (higher than 60%) in oligopoly market structure. Higher
concentration results in higher market forces but unfortunately it may cause
higher possibility for colusion. Industry with high concentration generally
encounters high entry barrier and has low technical efficiency (Bain,1956 as
cited in Martin,1999;Kuncoro, 2007; Setiawan, et al, 2012).
Capital
intensity is an entry barrier that may block potential to enter the industry.
Higher capital intensity means higher concentration (Martin, 1999) .
Zainalabidin (2015) states that capital intensity has positive influence
towards meat processing industry concentration. Different finding is reported
by Singh (2011) that capital intensity has negative influence towards
industrial concentration and other variables such as import intensity, market
intensity, vertical integration and economic scale play important role to
develop industrial market structure in post-liberalization era.
Ikhsan
(2007) explains that in general technical efficiency and economic scale have
negative contribution towards processing industry between 1988 to 2000.Similar
thing is reported by Probowo and Cabanda (2011) that between 2000 and 2005, the
national processing industry faces negative technical efficiency growth.
Different finding is reported by Saputra (2011) that between 1990-2001
processing industrial subsector in general has positive efficiency. National
Development Agency (2010) also reports positive technical efficiency growth
between 2000-2007. Ndari and Permono (2014) reported that between 2000 to 2004
the national meat processing industry has positive efficiency and technical
change as well as negative efficiency change. Between 2005 to 2009, the
subsector has positive efficiency and negative technical change.
Policy,
regulation and government policy can affect industrial structure and
performance. According to Pradiptyo (1996), government policy has significant
role to create oligopolistic/ monopoly industrial structure. Arnoldet al.
(2008) found out that in industrial level, there is inefficient allocation of
resources in companies located in the countries of which regulations do not
lean towards the market. Regulations can also be violated by certain people to
strengthen their position and gain control of companies towards market
(Setiawan, 2013).
There
are some policies established by the government that may affect industrial
performance such as the 1999 Decree number 5 about the prohibition of monopoly
and unhealthy market competition as well as the Ministry of Agriculture’s
Decree number59/Permentan/ HK.060/8/2007 on beef import quotas. Target of those
policies is to develop healthier market competition and decreasing amount of
imported beef and meat so that Indonesia can only import at most 10% of the
national beef consumption. As the consequence, meat used for consumption and
raw material for particular industry is limited.
Some
other countries have also conducted studies to analyze efficiency of
meatprocessing industry. In USA, Lambert (1994) revealed that
chicken-processing industry grows more than meat-processing industry and there
is inefficiency in employee input and raw materials. Xia and Buccola (2002)
also describe that increasing capital has relative development towards
employees and raw materials for processing industry in the United Statesjuga .
In India, Ali (2007) reported that between 1980 to 2003, there is inefficiency
in terms of capital input and employees as well as low growth of productivity.
Goncharuk
(2009)revealed that there is efficiency growth in Ukraine as the effect of
decreasing use of capital and employees input. Keramidou et al.,(2011)
describe that there was inefficient use of capital and employees input in
meatprocessing industry in Greece between 1994 and 2007. In Spain, Kapelko, et
al.,(2012)mention there is technical efficiency growth and scale efficiency.
Yodfiatfinda et al.(2012) argue that the biggest contributor towards the growth
in Malaysian food processing industry is technical efficiency.
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The
basis of the study is Structure- Conduct -Performance (SCP) paradigm that
involves correlational identification between industrial structure and
performance (Bain, 1951).The model is developed based on Martin (1999)and
Carlton and Perlof(2005) who develop framework for industrial organizationby
making very simple causal influence with linear model that influences
structure, behavior and performance suitable with the real-life situation as
well as revealing the growth of industrial development due to role of the
government in market development. Several previous studies are Maudos (1998);
Gumbou and Moudos (2000); Ollinger, et al.,(2005); Byeongyong, et al., (2005);
and Setiawan, et al., 2012a); Setiawan, M., (2013), among others.
Industrial
performance in the study used Farrel’s model of estimation (1957) with
microeconomics approach. Farrell (1957) divides corporate efficiency into two
components, technical and allocative efficiency. Both components are then
combined with economic efficiency. Sengupta (1995) andCoelli et al., (2005)
divide efficiency into three components namely Allocative Efficiency (AE),
Economic Efficiency (EE) and Technical Efficiency (TE).
Related
to the elaboration, purpose of the study is to analyze correlation between
industrial concentration and efficiency and some factors affecting
concentration and efficiency of meat processing industry in Indonesia between
1990 to 2013.
2. RESEARCH METHOD
Data
Data
used in the study are secondary data about Indonesian meat processing based on
the result of the 1990-2013 annual survey for big and medium-scale industry by
Indonesian Central Bureau of Statistics using the 2009 KBLI category of
which code is 10130.The data consist of input and output value
(Indonesian Central Bureau of Statistics, 2015).
Concentration
Ratio (CR) refers to market power measured using ratio of
production from 4 biggest companies(CR4) towards total production
of meatprocessing in Indonesia.
Colusionrefers to active correlationof company in the
industry to gain input, decrease output and increase price in
order to get normal demand and supply law.Colusion value is estimated based on
the Clarke et al., (1984) and Demsetz (1973)’s degree of colusion model
represented by the following equation:
|
0 ≤ ≤ 1
and.................................
|
(1)
|
where
∏ refers to profit, R refers to revenue, ∏/R refers to profit revenue ratio or
profit rate and finally H is Herfindahl Index (HI) that refers to total of
market share squared by number of companies in one
industry. As an
addition,
refers to degree of colusion and η
refers to elasticity of demand towards change of price. The higher
(the closer it is to 1) is the more profitable
an industry is (the closer it is to monopoly profit that is indicated by
colusion. The lowest
score is, the lower possibility colusion takes
place. The
calculation goes
with assumption that elasticity of demand is unitary. Unitary elastic demand
takes place if change of demand equals to change of price. Unitary elasticity
demand coefficient equals to one (η = 1), which means 1% increase of
price is followed by 1& decrease of demand and vice versa.
Import
Intensity refers to national
imported beef volumein one year.
Regulation
or rules issued by government related to monopoly
that us the 1999 Decree number 5 as the first regulation (RAM),
regulations related to export and import of meat and its products as well as
regulations that set a limit for or decrease import quotas namely Peraturan
Menteri Pertanian Nomor 59/Permentan/HK.060/8/2007as the second
regulation (RKID). The influence of regulation is analyzed using regulation
dummy. Year after the regulations is implemented equals to 1 and year before
the implementation of the regulation equals to 0.
Efficiency
refers to level of input utilization to get
output suitable with optimum resources. It can be seen based on
technical efficiency and allocative efficiency. In order to estimate
efficiency, Banker, Charnes and Cooper (1981)’s method is used since the method
has added DEA measurement method for variable return to scale (VRS) case.The
model distinguishes pure technical efficiency and scale efficiency as well as
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identifies whether
the result of the scale is increasing, decreasing or constant. As the effect,
linear CRS assumption should be changed by increasing N 1 ‘ÊŽ=
1. Therefore, input-oriented DEA VRS is as follow:
TE vrs Ó¨,ÊŽ= min Ó¨ st– yi + YÊŽ≥ 0
Ó¨xi
-Xλ ≥ 0
N1’λ = 1 λ
≥
0...........................................................................................................(2)
where
N 1 equals to N x 1 vector from 1.θ refers toinputof technical
efficiency below VRS, which is 0 ≤ θ ≤ 1. Similar to the previous cases, when θ
equals to one, the company is within frontier, while λ vector isN x 1,
the measurement that defines linear combination of company from nth company.
Capital
Intensity Ratio (CIR) refers to total
assets turnover, which is turnover of all assets of the company
based on the capital and divided by production cost (Setiawan et al.,( 2012b,
2013); Ullah et al., (2013); Keramidou et al., (2010)).
Method of
Analysis
Model
of equation in meat processing industry in Indonesia is the development of
emphirical models by Banker and Natarajan (2008), Keramidou et al.,(2010),
Keramidou et al., (2011a, 2011b), Johnson and Kuosmanen (2012), Ohlan (2013),
Cummins and Xie (2013) and Setiawan et al., (2012b and 2013). Therefore, the
model of equation in the study is as follow:
|
CR4t= c10 + c11 Colusiont + c12 Efft + c 13 CIRt + c14 RAMt + c15 RKIDt + e1,t..........................
|
(2.3)
|
|
Efft = c30 + c31 CR4t + c32 Colusiont + c33 Import + c34 RAMt + c35 RKIDt + e3,t...................
|
(2.4)
|
For
model of equation simultaneous with overidentified condition of the equation,
Three Stage Least Square (3SLS) with AR (2) model as error corrector is used to
estimate the parameter.
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3.
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FINDINGS AND DISCUSSION
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Description of Variable
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The statistical description of variables can be explained as in
Table 1.
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Table1.Statistical Description of Variables between 1990 to 2013
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Variable
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Average
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Std. Deviation
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Minimum
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Maximum
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Concentration (CR4)
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0.6246
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0.1085
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0.4433
|
0.8111
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|
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Colusion (Colusion)
|
0.2617
|
0.1268
|
0.0649
|
0.4867
|
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Efficiency
(Eff)
|
0.9569
|
0.0405
|
0.8543
|
1
|
|
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Capital
Intencity Ratio (CIR)
|
0.5648
|
0.3941
|
0.2070
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2.0185
|
|
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Import Intencity (Import)
|
1.47 e+07
|
4.43e+07
|
0.1903
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2.13e+08
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Sources: the Researchers
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Concentration
National
concentration of four largest company (CR4) in meatprocessing industry between
1990 to 2013 is 62.46% and therefore, it is categorized as tight oligopoly
(Jaya, 2008). High industrial concentration is suitable with studies conducted
by Bird (1999) and Setiawan (2013). Such condition is the result of 24.26% of
Minimun Efficiency of Scale (MES). When percentage of MES is higher than 10%,
there is high entry barrier; in big-scale economy it is going to be more
difficult for new company to get into the industry (Bank of Indonesia, 2008).
Meatprocessing
industry has natural characteristics, capital and production intensive. It can
be seen vaed on the percentage of Capital Intensity Ratio towards production
that is 56.48%. Huge capital needed for production results in difficulty for
new corporation to enter the industry.
High
barrier for both MES and CIR scores becomes the reason why new company
encounters a lot of difficulties to get into the industry. Average number of
companies in the industry within the duration of the study is 24 units or there
is 11.3% growth per year. High entry barrier and few companies within the
industry results in high industrial concentration. It is in line with Bird’s
(1999) study.
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Table2. Average of
Industrial Concentration, Minimum Efficiency of Scale (MES), Capital Intensity
Ratio (CIR) and Business Unit between 1990 to 2013
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1990-2013
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CR4 (%)
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MES (%)
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CIR (%)
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Observation
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(Unit)
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Average
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62.46
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24.65
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43.98
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24.00
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Sources: The
Researchers
Efficiency
Change
in efficiency, either technical efficiency or scale efficiency is development
of productivity elaborated in Total Factor Productivity (TFP). It is in line
with Kumbhakar and Lovell (2000)’s conceptand used empirically by Coelli et al.
(2005) who divided TFP into 3 (three) components namely change in technology,
technical efficiency, and scale of efficiency (economic scale).
Table 3.
Average Efficiency of Meatprocessing Industry between 1990 to 2013
|
1990-2013
|
Efficiency (%)
|
|
IRS
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CRS
|
DRS
|
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||
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CRS
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VRS
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Scale
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Unit
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Unit
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Unit
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||
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||||||
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Rata-Rata
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89,38
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95,69
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93,36
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18
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1
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5
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Legend:
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Scale
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= Scale
Efficiency = crs/vrs
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IRS
|
= Increasing
Return to Scale
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CRS
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= Constant
Return to Scale
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DRS
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= Decreasing
Return to Scale
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VRS
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= Variable
Return to Scale
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Tech = Technology
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∆
|
= Change/
Growth
|
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|
Source:
The Researchers
Based
on Table 3, it can be seen that average efficiency of meatprocessing industry
in Indonesia between 1990 to 2013 with CRS model is 89.38% which means 10.62%
of input can still be optimized with the assumption that all companies are
operated within optimum scale. Based on VRS model, the average is 95.69% which
means there is 4.3% inefficiency with the assumption that companies do not
operate within optimum scale due to xome existing obstacles. Furthermore,
average efficiency scale of93.36% (less than 100%) means the industry is within
inefficiency scale.
Possible
cause is the fact that meatprocessing industry involves various technology in
the process of production so that engine and electronic devices heavily
influence increasing production of the industry. Other factors that increase
productivity of the industry are supply and demand of processed meat. In terms
of change in efficiency, it can be seen that the companies have yet been able
to operate within their optimum capacity. They adopt “learning by doing”
concept when they involve technology in their productions. As an addition,
economic environment that causes inflation and fluctuation for the national
currency also influences selection of input of which source is imported goods.
Analysis
of the Findings
Based
on the output of Table 4, it can be concluded that collusion has positive
signbificant influence towards concentration(CR4).It is in line with the
findings of Nurdianto (2004)’s study that collusion has positive influence towards
development of industrial concentration. Collusion also has significant,
positive correlation towards efficiency (Eff).It happens since collusion is not
the trigger that develops high concentration in the industry; when collusion
becomes the trigger that develops high industrial concentration, it can be
inferred that collusion will decrease efficiency. The collusion does not
actually happen in meat processing industry that is in line with the findings
of Nurdianto (2004)’s study.
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Table 4. Regression Results
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Endogenous Variable
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Exogenous Variable
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CR4
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Efficiency
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Coef
|
t-Stat
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Prob.
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Coef
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t-Stat
|
Prob.
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C
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1.324
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5.383
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*
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1.113
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1.896
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*
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CR4
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-0.268
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-3077
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*
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Collusion
|
0.362
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4.635
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*
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0.232
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2.157
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*
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Efficiency
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-0.835
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-3403
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*
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CIR
|
0.166
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3.283
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*
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Import
|
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-3.39E-10
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-1.645
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*
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RAM
|
-0.101
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-2201
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*
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-0.069
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-3440
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*
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RKID
|
-0.135
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-2198
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*
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-0.002
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-0.184
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AR1
|
1.335
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6.924
|
*
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AR2
|
-0.881
|
-4219
|
*
|
-0.373
|
-1629
|
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R-squared
|
0.749
|
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|
0.555
|
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Adjusted
R-squared
|
0.624
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|
0.377
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Mean
dependent var
|
0,618
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0.959
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S.D
dependent var
|
0.111
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0,041
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S.E. of
regression
|
0.068
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0.033
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Durbin-Watson
stat
|
2.071
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2.135
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Mean
dependent var
|
0.618
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0.959
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S.D.
dependent var
|
0.111
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0.041
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Sum
squared resid
|
0.065
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|
0.016
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Source: The Researchers
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Based
on estimated value of the variables in Table 4, it can be seen that average
concentration that is obtained from the concentration of four largest companies
(CR4) is 61.8% and the standard deviation is11.1%. According to (2008),
concentration of the industry can be categorized as tight oligopoly. Bain
(1956) as cited in Zainalabidin, et al., (2015) states that concentration of
the industry is categorized as moderate since there is a little difference in
goods produced by different companies in the industry. The companies are able
to decide quality and price without affecting the whole market. High
concentration affects efficiency of the industry. Average efficiency of 95,9%
and the standard deviation of 4.1% mean efficiency is still below 100 and there
is 4.1% inefficiency with the assumption that company does not operate within
the optimum scale due to existing problems. Implications of negative growth of
efficiency or below 100% means need to improve human resource’s skills so that
they can adapt to the rapid growth of technology.
Based
on the result of regression, it can be obtained that efficiency (Eff)has
significant negative influence towards concentration (CR4)and so does
concentration (CR4) towards efficiency (Eff). It is in line with Byeongyong and
Weiss (2005)who explain that efficiency has negative influence towards CR4; it
means efficient company allocates resources and has wide market coverage so it
will have lower production efficiency compared to its competitors and causes
increasing concentration. Company that operates within high industrial
concentration does not have any pressure to increase its technical efficiency.
It shows negative correlation between concentration and efficiency because high
concentration is considered as barriers for company to have competition. Gumbau
and Moudos (2002) as well asSetiawan (2013) argue that in competitive company
there is negative correlation between concentration towards efficiency; it
means huge market a company has causes inefficient allocation of resources and
will increase price flexibility where increasing price will be much faster than
decreasing price. It is in line with the statement that companies operated
within high industrial concentration do not have any pressure to increase their
technical efficiency.
Collusion
has positive significant influence topwards CR4 and efficiency (Eff). Collusion
happens because huge companies in the industry work together only when they
look for raw materials but they never work together in terms of production and
making decision about price. Scarcity of raw materials causes more
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barriers to get to
the industry that eventually increases concentration. Similar finding is
elaborated by Nurdianto (2004) but Bain (1956) stated in Kuncoro (2007), Sawyer
(1991) and Church and Ware (2000) have different hypothesis. Collusion does not
actually happen because collusion index of meat processing industry is 0.32
(32%) indicating that the collusion is categorized as low (lower than 0.5 or
50%). When an industry has high concentration, companies within the industry
will practice collusion in order to get higher profit and sacrifice consumer’s
need. As a conclusion, the theory suitable for Indonesian meat processing
industry is Market Power Theory. It happens because the government has
established imported meat quotas in 2007 so that limited input of raw materials
encourages companies to work together and established organizations such as
National Meat Processor Association Indonesia (NAMPA Indonesia).
Collusion
has positive significant influence towards efficiency. It happens since
collusion in meat processing industry is vague. The collusion does not decide
price and production instead it facilitates companies within the industry to
obtain raw materials with competitive prices and means of technology to aid
production. Being a member of the associations results in earning meat quotas
in competitive, fair prices and exchange of information especially one related
to machinery and the latest technology in the industry as well as availability
of meat as raw materials in order to increase efficiency in production and use
company resources.
CIR
has positive significant influence towards CR4.Regression coefficient for CIR
is0.1615 (positive); it means one point increase of CIR will be followed by
0.1615 point increase of CR4 and at the opposite, one point decrease of CIR
will be followed by 0.1615 point decrease of CR4. It is in line with the
hypothesis that CIR has influence towards concentration so the higher CIR in
the industry, the higher concentration the national meat processing industry
has. When there a company shoukd prepare high amount of capital to get into an
industry, new competitor will be more reluctant to get involved in the industry
that will cause high industrial concentration. It is line with Waldman and
Jensen (1998). It also happens because meatprocessing industry is a capital
intensive industry so that companies that have huge capital will likely
dominate production and the market .
CIR
be a barrier for new companies to get into the industry . Capital Intensity
Ratio is the company's efforts in the use of all of its assets to generate
sales . Higher Capital Intensity Ratio (CIR) means more efficient use of the
asset. The value of the average Capital Intensity Ration during the is 0.56 or
about 56% of the capital required for production. The high value of Capital
Intensity Ration will reduce profit margins so that the industry is less
productive or less efficient because it inhibits new companies to enter the
industry and will encourage high concentration of the industry. The findings
are in line with those of Setiawan (2013).
Import
has negative significant influence towards efficiency (Eff). It is in line with
the hypothesis and findings of studies conducted by Parameswaran (2002), Goldar
(2002) andUllah et al., (2013).It is due to increasing demand for imported meat
that will affect the price of imported beef in the exporter countries .
Importing meat is conducted to meet the demand from hotels, restaurants ,
caterer, household , and industry. Huge amount of imported meat for catering
and household will result in shortage of imported meat for the industry.
Importedmeat limitation will cause competition for the quota of imported
meat.It may cause increasing price for imported meat. In addition , imported
meat is also highly sensitive to changes in the exchange rate so that changes
in exchange rates will also affect the price of imported meat itself.
Price
of imported meat will result in high local meat and high price of imported meat
from the importer will also have contribution in increasing price of imported
meat(Ilham, 1998; Pakpahan, 2012). Another possibility is that intensity of
variation meat more particularly trimming mear dominantly used for industrial
purpose is heavily influenced by import quotas so that it cannot meet utility
of meatprocessing industry between 1990 to 2013 of 75.7%. Such condition may
reduce efficiency of the national meatprocessing industry in Indonesia.
There
is significant negative change of concentration (CR4)once the
anti-monopoly regulation (RAM)is established. Similar thing works for
efficiency (Eff) that has significant and negative influence. The
findings are in line with those of Setiawan, et al., (2012). The
establishment of the 1999 Regulations number 5 aims at preventing both monopoly
and collusion in the industry. It happens because ever since the anti-monopoly
regulation was established in 1999, the national economy had yet been
stabilized as the effect of the 1997 economic crisis. As the effect, many
companies did not produce their products up to their capacity due to high
operational cost and price of raw materials. The effect of the phenomenon is
inefficiency.
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Once
it was established, the Imported Meat Quota Regulation (RKID)has
negative significant influence towards CR4, while it does not have any
influence towards efficiency (Eff).It is different from findings of
studies conducted by Pradiptyo (1996), and Bird (1999). These results are
different because the imported quotas regulation imposed by the Indonesian
government affects the availability of meat consumption and large enterprises
that use imported meat. After the government set limitationfor imports of meat
, the concentration is decreasing significantly but the difference was not
significant to the decrease of efficiencymeaning that producers of meat
processing experience difficulties in obtaining raw materials to meet the
production capacity. The decrease in production by large companies provide
medium-sized companies the opportunity to increase production so that the
concentration of the industry reduces. For medium-sized companies that use
local meat as raw materials can still maintain a fixed level of output by
making efficiency in during operations. When inefficiency takes place, input in
terms of profit will decrease too (Marhendra., 2014) .No significant difference
in terms of efficiency after the regulations have been established may happen
due to the realization of the import which do not conform to the import quota
that has been set. Realization of the import is in fact greater than the quota
so that the needs of the industry can still be met despite of some increase in
terms of price.
4. CONCLUSIONS AND SUGGESTIONS
Conclusion
Based
on the analyses, it can be concluded that the concentration of the national
meat processing and meat preserving industry between 1990 to 2013 is 61.8%. The
concentration increases due to increase in collusion and Capital Intensity
Ratio (CIR),while efficiency will reduce concentration. Once
anti-monopoly and imported meat quotas regulations have been established, there
is significant change in concentration.
Furthermore,
the average efficiency of meat processing and meat preserving industry in
Indonesia between 1990-2013 is 95.9% (efficiency is lower than 100%) that means
there is 4.1% of inefficiency with the assumption that company does not operate
within optimum scale due to some obstacles. Low efficiency causes high
concentration and intensity of imprted meat. Efficiency will increase through
cooperative work (collusion) by transfer of technology between companies.
Efficiency is getting lower after the implementation of anti-monopoly and meat
imported quotas regulations.
Suggestions
It
is suggested that the efficiency of meat processing and meat preserving
industry in Indonesia can still be increased by improving management, training
for employees especially those responsible for production and selecting raw
materials with competitive prices. High dependency of the national meat
processing industry for imported meat and imported goods may become issues once
the currency rate of Rupiahs against US$ is getting weaker. Thus it is expected
that the government encourage the industry that still uses imported meat as raw
materials to export their products in order to give added value for the the
trade balance and also to prepare infrastructure for the livestock industry and
slaughterhouses to be able to provide raw materials and goods specifically for
industrial processing and preservation of meat in the country.
Moreover,
the government should decrease industrial concentration in order to create
healthy competition that will lead to increasing efficiency of the national
meat processing and meat preserving Industry in Indonesia. One of the methods
is implementation of the market -friendly regulations. Regulation that limits
household consumption for household should be established so that it is
expected that the national industry will grow. As an addition, the government
should also apply the regulations specific to the importation of industrial raw
materials in accordance with the capacity of the industry so that efficiency
can be increased until the the national livestock industry can provide the
needs of the industry.
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