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on our empirics models employees, import, irm age, wage, export status, industry location and foreign
investment are also obtained from BPS survey.
4. Analysis of the Results
In this study, technical effciency estimator is measured through DEA input oriented approach, which
will produce eficiency at CRS and VRS assumption. For the sample of pulp and paper industry for each of
the years are obtained by comparing each irm with the best practice in the particular year. The results show
the average eficiency from range years 2005 - 2009 are 71 if assumed CRS and 79 if assumed VRS
. It means that averagely irms use input 29 and 21 over from 0 best practice irm. The level could
be associated with the fact that average utilization level of pulp industry 77 and paper industry 86.
Ministry of industry[1]. Eficiency can be improved by eliminating ineficiency in using input factors
eficient to VRS and increasing operation scale eficient to CRS. The eficiency level can be showed
annnually and based on sub-sectors as presented in Figure 1. Figure 1 a shows technical eficiency trend
luctuated in observed year, and last decreased in 2009. Figure 1 b shows pulp industry ISIC 21011
reached the highest eficiency. This can associated to the fact that pulp industries have large operation scale
and face limited pulpwood supply. The results of calculation TFP Malmquist and its
decomposition are presented in Table 1. Table 1. Annual Total Factor Productivity and its
Component from year 2005 to 2009
Year effch
techch pech
sech tfpch
2005 - 2006 1.139
0.889 1.077
1.057 1.013
2006 - 2007 0.852
1.124 0.921
0.925 0.957
2007 - 2008 1.197
0.762 1.084
1.103 0.911
2008 - 2009 0.758
1.512 0.832
0.911 1.146
Mean 0.987
1.072 0.979
0.999 1.007
Table 1 displays productivity changes of Indonesian pulp and paper industry over the period 2005–
2009, as represented by the Malmquist input-based productivity. A greater-than-one Malmquist index
denotes improvement in the relevant performance. There were two periods
2005 – 2006 and 2008 - 2009
showing productivity gains. Productivity gains in 2005 – 2006 came from the eficiency change, while in
2008 - 2009
came from the technical change. On average over 2005 – 2009, TFP growth is driven by technical change
rather than technical eficiency. An improvement in technical eficiency requires improvement in quality
and saving of inputs include capital, labor, material and energy. For the irms whose production is right
on the frontier i.e. eficiency scores equal to 1, the strategy for increasing their productivity is to improve
the technology innovation. Scale eficiency change tended to constant over period 2005–2009.
To identify the factors that may contribute to eficiency and productivity, Equation 7 and 8 are
estimated. We has considered the classical assumptions in the model include multicolinearity, autocorrelation,
and heteroscedasticity. By results of hausman test and
redundant ixed effect test, we ind the ixed effect with cross section weighted as the best model. The
results of the estimation are presented in Tabel 2. The estimation results show that variable EMP,
AGE, and PIMP signiicantly determine eficiency TE-CRS and TE-VRS. While variable AGE, WPL,
CON and TP signiicantly affect productivity. The high R-squared value for all models indicate high
percentage of dependent variable variation can explained by independent variable in the model. The
probability F-statistic values indicate that independent
variabels all together signiicantly affect dependent variabel. Variable EMP employee has a negative
impact on eficiency but does not signiicantly affect irm productivity. This indicate that higher amount of
employees, eficiency will decrease and productivity will keep constant. This result is line with Diaz
[20] and Aggrey [21]. Pulp and paper industry is capital-intensive in nature so that increasing amount
of employees is not effective to improve eficiency
Figure. 1. a Annual Eficiency Level ; 1 b Eficiency Level Based on Sub-Sectors 5 digits ISIC
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and productivity. Diminishing marginal productivity of labor may be occurred due to the industry is
categorized into medium and large industry based on amount of employees. In our sample, the proportion
number of large irms 57 and medium irm 43. But according to Jajri [22], high skill workers technicians,
supervisors, and analysts can be complement to high technology. Variable AGE irm age has a negative
impact on eficiency and productivity, it means that if the irms get older, eficiency and productivity will
decrease. From eficiency point of view, the result is line with Margono [7] in chemical industry. While
for productivity, the result is line Alviya [] in wood manufacturing industry, Kadarsyah [9] in foot-ware
industry and Margono [7] in chemical industry. This result undirectly shows indications of deteriorating
production machines. Ministry of industry [2] found a gap of technology capability between old mill and
new one. In general, new mills employ new machine
equipment, while old mills varied in their machine performance.
Variable CON market concentration does not signiicantly affect irm eficiency but signiicantly
affect productivity negatively. The market structure of pulp and paper industry is strong oligopoly. Putra
[12]. These concentration level need controlled by the government in order to maintain competitiveness
climate that can contribute to increase the productivity. Variable PIMP percentage of material import has a
negative impact on eficiency. This inding is line with Ray [23] and Farrel [14], increasing input is inversely
proportion to eficiency input based. Moreover if US dollar value increased, it will make higher
cost to irms. Other variables DLOC dummy for industrial location, DEXP dummy for export status,
and DFINV foreign investment status does not signiicantly affect irm eficiency and productivity. In
our sample, the majority of mills are located in outside of industrial park approximately 88. The irms
prefer their mill near from raw material resources pulpwoods. Integrated pulp-paper mills are located
in Sumatera and Kalimantan. While the non-integrated paper mills are spread in Java Banten, West and
East Java. Proportion of exporting-irms are smaller approximately 28 than nonexporting-irms. This
fact may cause exporting-irms do not signiicantly show the higher performance than nonexporting-irms.
According to previous empirics literatures, export could increase irm eficiency and productivity due to
high quality standard and tight competition in global market. The coeficient on DFINV has the expected
positive sign but is not statistically signiicant. From observation, share of foreign-irm only 13. Majority
of empiric researchs indicated that foreign ownership had effect to irm eficiency and productivity due to
easiness of technology transfer . Lastly, variable TP technical progress and
WPL wage per labor have a positive impact on productivity. Technical progress is closely related to
capital intensity. It means adapting new technology and innovation activity in the capital intensive irms
will improve productivity. This result is line with technical progress concept in Nicholson [24] and
empirical result Jajri [22]. The government can help the industry through programs of machines
restructurization or eliminating of import tax of capital goods. Increasing research dan development RD
fund to research centers, universities that coorporate with the industry are also needed. While variable
WPL can determine productivity that line with Yasar [25]. WPL indirectly represents worker skill . The
efforts to improve worker skill for instance education, Table 2. Results of Eficiency and Productivity Determinant Regression
TE-CRS Coeficient Probability
TE-VRS Coeficient Probability PROD
Coeficient Probability C
2.7407 0.0000
C 2.2882
0.0000 C
5.7243 0.0000
EMP -0.1497
0.0145 EMP
-0.1901 0.0001
EMP -0.0619
0.4248 AGE
-0.7646 0.0000
AGE -0.5074
0.0000 AGE
-1.2441 0.0000
CON -0.0195
0.4018 CON
0.0127 0.3196
WPL 0.3245
0.0000 PIMP
-0.0027 0.0097
PIMP -0.0022
0.0133 CON
-0.0719 0.0000
DLOC -0.0573
0.5068 DLOC
-0.0077 0.7629
TP 0.0815
0.0000 DEXP
0.0501 0.4618
DEXP 0.0670
0.2776 DLOC
-0.4400 0.5550
DFINV 0.0303
0.4717 DFINV
0.0145 0.5705
DEXP -0.0154
0.7886 DFINV
0.0731 0.6110
R-Squared 0.8303 R-Squared
0.8308 R-Squared 0.9914
Prob F-stat
0.0000 Prob
F-stat 0.0000
Prob F-stat
0.0000 signiicant at 1 level
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training, and courses can contribute to productivity in workplace. Management programs such as increasing
wage periodically, incentives, and promotion should pay attention.
5. Conclusions and Policy Implications