A REVIEW INPUT FACTORS ELASTICITY AND RETURN
TO SCALE OF COOPERATIVE: A SURVEY ON INDONESIAN SAVINGS-LOAN COOPERATIVES
Johnny Walker Situmorang
Ministry of Cooperative and SMEs RoI,
Indonesia
E-mail: jwalker@situmorang.web.id
Submission: 27/04/2018
Revision: 02/05/2018
Accept: 14/05/2018
ABSTRACT
This study aims to reveal the production function, return to scale, and
production factors elasticity of cooperative by using Indonesia financial
service cooperative (IFSC) which has a single business in the field of
financial service as a sample of research. Using panel data, this study results
both labour and capital factors have a significant influence IFSC production. The IFSC industry condition is increasing
return to scale (IRS). Production elasticity of capital is higher than labour
force so that IFSC business expansion is faster with increasing IFSC capital.
The cooperative financial services industry condition is increasing return to
scale that enables IFSC business expansion.
Given the availability of IFSC resources and its operating environment,
IFSC's business expansion strategy should be more labour-intensive than
capital-intensive, employing more labour than capital. The government should
provide support for improving human resource capacity.
Keywords: cooperative, production function, return to scale, elasticity
JEL classification: C51, D01,
D24
1. INTRODUCTION
As
a business entity, the Indonesia cooperative operates as a non-cooperative
entity, such as a limited company. Legality of the existence of Indonesian
cooperatives engaged in the field of financial services is the Act 25 of 1992
on Cooperatives and Government Regulation No. 9 of 1995 on the Implementation
of Savings and Loan Cooperative Business.
The
distinguish cooperatives with non-cooperative enterprises is the social content
based on cooperative principles that show ownership of cooperatives with
membership systems, and the dimensions of democracy in decision-making based on
"one man one vote" in the Meeting of Members. The Indonesian
cooperatives content a social dimension with principles in conducting business
that aims to enhance their members’ welfare (SWASONO, 1988, 2015).
Cooperatives
are inclusive financial institutions because of their direct involvement in
creating financial access of the poor and low-income people (MUBYARTO, 1988;
MUNKER, 1997; NASUTION, 1990; RAHARJO, 2010a, 2010b; SITUMORANG, 1985, 2011a,
2014).
IFSC
has been massively operating in rural and urban areas involving millions of
people both as members of the IFSC as well as the community so-called inclusive
finance. Until 2015, the number of
active cooperatives in the country reached 150,223 units with 37.78 million
members or 252.49 members per cooperative and they created business
transactions amounted to IDR266.13 trillion (USD19.71 billion) with total
assets of IDR242.45 trillion (USD17.96 billion).
They
employed 537,234 people or 3.38 people per cooperative with productivity
reached IDR495.37 million (USD36,694.13) per worker (SITUMORANG, 2017a,
2017b). IFSCs raise public funds,
particularly from it members, and redistribute the funds for productive,
consumptive, and investment financing.
Source of fund from banking is limited because interest rate relatively high
(SITUMORANG, 2007).
IFSC
gets revenues on loan services and pays expenses on collected funds. Therefore, the production process must be
efficient so that IFSC able to compete in competitive money market. Estimation of production function is one way
to improve efficiency. The problem of
this research is how IFSCs production function.
This
study aims to determine the production function of IFSC and its estimation
reveals the elasticity of production and economics scale of financial services
industry cooperative Indonesia. The results of this research will be useful for
improving the efficiency of IFSC and as input for the government to formulate
the regulation, policy, and strategy of IFSC development towards global market.
2. LITERATURE REVIEW
Revealing
elasticity of production factors and economic scale is very interesting in
microeconomics and practices. Using
production function, we can find both the elasticity of factors and economic of
scale.
The
previous studies which investigated return to scale related to the economies of
scale of microfinance institutions suggested that microfinance institutions
such as credit unions (CUs) and cooperatives need to scale up in order to
increase their efficiency. This is related to the nature of the institutions
which are not entirely profit seekers.
Zacharias
(2008) has examined the scalability of microfinance institutions globally and
found that operational efficiencies are positively correlated with firm size,
which means that bigger microfinance institutions are associated with smaller
average costs.
Bolli
and Anh (2012) used a production function approach with the same panel data,
and their findings suggest that microfinance institutions need to either grow
or merge in order to exploit its potential source of efficiency gains due to
its increasing return to scale.
Hartarska,
et al. (2012, 2013) have also identified an increasing return to scale and
input price elasticity of microfinance institutions and suggested the needs of
the institutions to grow or consolidate in order to benefit from lower average
costs. An empirical study by Chen (2017) that examined the economies of scale
of CUs in the United States also shows that larger CUs are operated more
efficiently than their smaller counterparts are in term of operating cost. The economics of scale does matter to higher
efficiency of microfinance institution.
Despite
various previous studies on the economies of scale of microfinance
institutions, there are still few studies which are specifically focused on
cooperatives or CUs. Koot (1978) investigated the economics return to scale of
United States CUs by using a derivation of Cobb-Douglas function. It shows that CUs, unlike the banking
institution, were subject to a decreasing return to scale.
Wolken
and Navratil (1980) challenged this Koot's model by including the factor price
with wage rate, and it shows that CUs reap small but statistically significant
economies of scale. A recent study by
Hartaska, et al. (2012), that used global data of cooperatives to examine the
nature of this industry, has identified that the cooperatives run at an
increasing return to scale that leads consolidation or expansion among the
players in order to lower the cost.
There
were previous studies on cooperatives in Indonesia which have used cost
functions to estimate the efficiency and scale of the industry. Situmorang
(1989) found that the rural bank industry in Indonesia operated on a decreasing
cost to scale. Similarly, multi-business village unit co-operatives (VUCs)
operated on a decreasing cost to scale (SITUMORANG, 1989, 1991, 2010, 2011b,
2011c, 2013).
The
result study of Situmorang (2018) with using Learning Curve model revealed that
Indonesian financial services cooperative is in condition increasing cost to
scale but still relatively efficient.
3. ANALYTICAL FRAMEWORK
In
the competitive market, a business entity always strives to maximize profit or
minimize the cost. On the perspective of microeconomics, business efficiency
can be explained by examining both their production side and their cost side (KOUTSOYIANNIS,
1982).
The
economic scale analysis is useful to sketch the nature of an industry when the
average business size of firms in the industry increases if a double of production inputs and determines
the competitiveness of the industry. This theory is valid in the real world,
but to test it, data must be available (NICHOLSON, 1979).
The
production side approach estimates the efficiency through production function,
while the cost side approach estimates the cost function. The return to scale
describes the output response to a proportionate increase of all input. Returns to scale are easily defined for
homogeneous production functions (HENDERSON; QUANDT, 1980). Assume using inputs
X1 and X2, thus
Q
= f(tX1,tX2) = tkf(X1,X2) ……………………………………………… (1)
where
t is positive real number and k is a constant.
If both inputs are increased by the factor t, output is increased by the
factor tk. If output
increases by the same proportion, return to scale are constant. They are increasing if output increases by a
greater proportion and decreasing if it increases by smaller proportion.
Returns
to scale increasing if k > 1, costant if k = 1, and decreasing if k <
1. Homogeneous production function satisfies
the condition of the degree of homogeneity by Euler’s theorem ε1 + ε2
= k. The increasing return to scale
(IRS) shows the economies of scale with high economic power (Gelles and
Mitchell, 1996).
The
production function with homogeneous of degree one is known by Cobb-Douglas
Production Function (CDPF). Homogeneity
of degree one is often assumed for production function and the long-run
production function is assumed as a homogeneous to degree one. Allen (1956) had made mathematical properties
of production function homogeneous to degree one.
Econometrics
makes it easy to analyze the production process. Euler’s theorem can be used to
determine the symmetry of the stages of the production for the input that is
assumed variable in the short-run and the input that is assumed fixed in the
short run. Marginal product of factors
is diminishing and less than average products in the stage-2, namely rational
region (DOLL; ORAZEM, 1984).
Economies
or diseconomies of size refer to the impact of output expansion upon average
cost. The inputs are combined along the
long-run expansion path in any ratio that minimizes the cost at each level of
output. If the production functions exhibit
indivisibilities or smoothly increasing return to scale, a technical externality
exists.
The
increasing return to scale and perfectly competitive input markets, average
cost declines over the relevant range. A
technical externality causes market failure either because it leads to monopoly
or because free competitive enterprise is not viable at marginal cost price (FERGUSSON;
COULD, 1975).
4. METHOD OF ANALYSIS
The
disclosure of the production function of the IFSCs in this research is using
the approach of microeconomics, statistical, and econometric analysis (HILL et
al., 2012). Generically, the production function is a power function and the
input factors affecting output.
According to this theory, the production function is shown by the
following general equation model
Q
= f(L, K, M,…,..) …….……………………………………………….. (2)
where
Q is the output that influenced by input factors L (labor), K (capital), M
(material), and so on. If using inputs L
and K, the power function of equation is
Q
= ALαKβ ……………………………………………………………… (3)
where
“A” is the estimated coefficient technology and parameters α and β are the
estimated coefficient of inputs of L and K.
The equation (3) is non-linear function can be transformed to be linear
function by Ln – Ln model, that is
LnQ
= lnA + αlnL + βlnK …….………………………………………… (4)
In
this research, we use inputs L and K, so the equation (4) is applied to
estimate the IFSC production function where unit of Q is loans in IDR million,
L is outpouring of man hours (MH), and K is equity in IDR million, ceteris
paribus. The elasticity of IFSC inputs
production are
∂lnQ/∂lnFi
= εi …………………………………………………………. (5)
where
Fi is the factors i of L and K.
The economics of scale is determined based on Euler’s theorem by
∑
εi = α
+ β ………………………………………………………. (6)
If
εi < 1, that is decreasing return to scale (DRS), εi =
1 is constant return to scale (CRS), and εi > 1 is increasing
return to scale (IRS).
Business
planning bases on business growth can be derived by the equation (3). The growth model is
Gq
= εlgl + εkgk ………………………………………………………… (7)
where Gq is the total growth of
business, gl and gk are the growth of L and K,
respectively.
The
economic efficiency is to maximize profit by constraint budget. To determine economic efficiency is to use
the following equation by La-grange multiplier, that is
Max
La = ALαKβ + ꭓ(C0 – wL – rK) ………….……………………….. (8)
where
λ is La-grange multiplier, C0 is constraint budget, w is nominal
wage of labor, and r is rent of capital. Equation (9) will drive efficiency
condition using each input production, that is
VMPi
= ri ………………………………………………….…… (9)
or
PqMPi
= ri ….…………………………………………. ……
(10)
where
VMPi is value of marginal product of input i, ri is rent (price) of
input i, that is nominal wage (W) and rent (r), Pq is price of
output, and MPi is marginal product of input i. The equation (10) denotes input factors demand
function.
To
profit maximize, equation (8) derivates the function of the expansion path of
business, ie
K
= f(L) ………………………………….…………………… (11)
or
K
= δL ……………………………………………………… (12)
where
δ is the relation coefficient of K and L, ratio capital and labor or marginal
capital related labor for expansion.
5. DATA
To
operate equation (4), the data used is secondary data from the survey in 2014.
The secondary data sourced from formal reports of each sample cooperative in
The Annual Cooperative Board Accountability Report (ACBAR) in 2011 - 2013. Data in the form of data panel, namely
combined cross section data from 39 IFSCs samples and time series data 2011 –
2013, so that available 117 units of data observation.
The
sample selection is based on the distribution and variety of IFSCs in several
provinces of Indonesia, namely North Sumatra, Central Java, West Kalimantan,
Central Sulawesi, and East Nusa Tenggara. Sampling technique through IFSCs
sample frame with simple random sampling which registered. Data processing
based on the software Eviews which appropriates to process the data panel (AGUNG,
2009).
6. RESULTS OF RESEARCH
6.1.
Sample
performance
Table
1 shows the statistical performance of the FSC sample in this study. During
2011 - 2013, the average outpouring of worker is 65.211.90 man-hours per year
with the lowest of 1,824.0 man-hours and a maximum of 893,760.0 man-hours. The
employment outpour is equal to the employment of 465.8 workers per cooperative.
The
use of FSC capital for production process is an average of IDR17,535.56 million
(USD1.3 million) per annum with a minimum capital of IDR12.07 million
(USD894,074.0) and a maximum of IDR267,822.63 million (USD1.3 million). The use of labor and capital resulted in
output per FSC on average of IDR44.118.16 million (USD3.27 million) with a
minimum output of IDR6.30 million (USD466,667.0) and a maximum of
IDR1,015,638.06 million (USD75.23 million).
The
performance of labor, capital, and output of FSC is very varied with the
coefficient of variation each more than 200%.
That is, the spread of data of each object is very far from the average
value. The high diversity of research and resource areas is shown by skewness
and positive value data kurtosis which means the distribution is not norm or
not symmetrical and the data distribution is leaning to the left where the mean
value is greater than the median. The overall performance of the sample based
on IFSC labor, capital, and output is seen in Appendix-1.
Table 1: Descriptive Statistical Performance of IFSC
Sample, Years 2011 – 2013
Items |
L (MH) |
K (IDR million) |
Q (IDR million) |
Average |
65,211.90 |
17,535.56 |
44,118.16 |
Minimum |
1,824.00 |
12.07 |
6.30 |
Maximum |
893,760.00 |
267,822.63 |
1,015,638.06 |
Standard of Deviation |
130,381.56 |
44,642.73 |
149,581.43 |
Skewness coefficient |
4.00 |
3.91 |
5.36 |
Kurtosis coefficient |
18.76 |
16.19 |
29.66 |
The
money market faced by cooperatives can be shown by the interest expenses and
the interest revenue channeled by the IFSC to members and communities or the
IFSC lending rates. The difference between interest rates on loans and deposits
is the net interest margin (NIM) of IFSC.
The
development of interest expense during 2011-2013 is much lower than interest
rate and tends to rise. In 2011, the average interest expense per cooperative
was 5.38% per annum, then increased to 6.1% in 2012, and increased again to
8.81% in 2013. Average of the
cooperative's savings interest rate is 6, 76% a year or 0.56% per month. The
deposit interest rate is very low, which is why the funds collected in the
cooperative are cheap funds.
Unlike
the interest expense, the cooperative loan rates are high but tend to decrease
during 2011-2013. In 2011, the average interest rate was 29.80%, down to
28.33%, and down again to 24.16%. The average interest revenue rate per annum
during this period is 27.43% or 2.29% per month. Thus, the margin obtained by
the cooperative was 24.41% in 2011, then decreased to 22.23%, and decreased
again to 15.35%. The average margin rate is 20.66% a year or 1.72% per month.
Positive developments occurred as margins narrowed and declined, as well as the
cost of funding and loan interest fell further. This is also an indication that
efficiency and cooperative management are increasing.
Figure 1: Trend of Loan Rate, Cost of Fund, and NIM of
Cooperative Sample, Years 2011 – 2013 (%)
The determination
of the interest rate of the IFSCs is the result of the agreement of the member
of the cooperative when the Annually Members Meeting (AMM). The AMM is the
highest forum of decision-making that should be implemented by board of
management of cooperatives.
For members of
the cooperative, high interest rates are not disputed by members because they
are associated with high risks, the easy procedure of obtaining loans, loyalty,
and compensation for saving and borrowing according to the cooperative
principles obtained when AMM is exercised.
Accessibility to these cooperative finances emphasizes character,
capability, and relationships within group members.
6.2.
Estimation
of IFSC production function, elasticity, and economic of scale
Using the
equation (4), the estimated IFSC production function is revealed from this
study, as shown in Table-2. The estimated validity was very high with R-squared
and adjusted R-squared coefficients of 0.8517 and 0.8491, respectively. That is 84.91% of data can explain the
estimation. Sum squared resid (SSR) or RSS (residual sum square) as a measure
of data fit and analysis model. The smaller the RSS, the more suitable data and
models.
The data and
model match rate is 99.84. Confidence on the estimate is seen at an estimated
Likelihood Log value of -156.74. The higher the likelihood log value the
stronger the confidence in the factors affecting the output of the cooperative.
Hypothesis test shows the overall model estimation is very significant with the
value of F-sta of 327.38
Partially, the
estimation result of labor and capital has significant effect on cooperative
output with probability of 0.00% far below the error rate (α) 5%. Likewise the constant is significant with α =
2.77% (t-stat is greater than t-table). The mean predicted dependent variable
(output) is 8.2774 or IDR3,933.95 million (US $291,403.9) per cooperative with
standard deviation of 2.4092 or IDR11.13 million (US$824.08).
Akaike
information criterion (AIC) and Schwarz criterion (Bayesian Information
Criterion / BIC) are the criteria for selecting estimation models where smaller
AICs and BICs are better model choices. The selection of cost estimation model
models for both AIC and BIC are 2,7306 and 2,8014, respectively. The test
whether there is autocorrelation with the use of time series data is with
Durbin-Watson stat (D-W sta). With D-W stat 0.5927, no data autocorrelation
occurs. With the difference between
actual and predicted dependent variables then the estimation accuracy is due to
square-error of 26.03%.
Table 2: Estimation of IFSC
Production Function
Dependent
Variable: LnQ |
|
|
||
Method:
Panel Least Squares |
|
|
||
Sample:
2011-2013 |
|
|
||
Periods
included: 3 |
|
|
||
Cross-sections
included: 39 |
|
|
||
Total
panel (balanced) observations: 117 |
|
|||
|
|
|
|
|
|
|
|
|
|
Variable |
Coefficient |
Std.
Error |
t-Statistic |
Prob. |
|
|
|
|
|
|
|
|
|
|
LnL |
0.510908 |
0.081158 |
6.295259 |
0.0000 |
LnK |
0.620338 |
0.045954 |
13.49906 |
0.0000 |
C |
-1.401398 |
0.628250 |
-2.230638 |
0.0277 |
|
|
|
|
|
|
|
|
|
|
R-squared |
0.851712 |
Mean dependent var |
8.277350 |
|
Adjusted
R-squared |
0.849111 |
S.D. dependent var |
2.409200 |
|
S.E.
of regression |
0.935841 |
Akaike info
criterion |
2.730563 |
|
Sum
squared resid |
99.84092 |
Schwarz criterion |
2.801388 |
|
Log
likelihood |
-156.7380 |
Durbin-Watson stat |
0.592754 |
|
F-statistic |
327.3881 |
|
|
|
Prob(F-statistic) |
0.000000 |
|
|
|
|
|
|
|
|
From the
estimation result in Table 2, production function estimated of IFSC according
to equation (4) is
LnQ = -1.4014 +
0.5109L + 0.6203K ………………………… (13)
and its power
function as equation (3) is
Q = 0.2463L0.5109
K0.6203 …...........…………………………………….… (14)
where the
coefficient of technology is 0.2463, εl = 0.5109, production
elasticity of labor, and εk =
0.6203, production elasticity of capital.
The equation for growth estimation is
Gq
= 0.5109gl + 0.6203gk
………............……………………..……..
(15)
To determine the
level of economic efficiency depends on budget constraint and the prices of
input. From this study, during 2011 –
2013 the cost of IFSC deposits is as the capital price (r) of 6.76%, the wage
labor (w) is IDR19,233.0 (USD1.43) per working hour. While the average interest
rate of IFSC is 27.43% per year. If the
available budget is IDR100.0 million (USD 7,407,41) then the equation for determining
economic efficiency is
Max La = 0.2463L0.5109 K0.6203
+ ꭓ(100,000,000 – 19,233L – 0.0676K) ............. (16)
To profit
maximize, equation (16) derivates the function of the expansion path of
business, ie
K = 19.70L ….………….............………………………………
(17)
If the budget line increases then the
production process changes in the combination of inputs that increase from the
previous isoquant. Any additional one man-hour labor outpouring will raise
capital by Rp19.70 to keep it efficient.
7. DISCUSSION
7.1.
Meaning
of production function coefficients estimation
The estimation
result in equation (13) shows CDPF with the function coefficient "A"
= 0.2463 as the technology coefficient. That is, if L and K are each worth zero
then the production is amounted of Rp0.2463 or increased production if there is
a change in technology.
The production
elasticity of labor and capital is 0.5109 and 0.6203 indicating the diminishing
marginal product of labor and capital, the value is under one, is within the rational area of its
production function. The addition of each one of these factors leads to a
smaller increase in production.
The production
elasticity of labor force of 0.5109 indicates that each labor input increases
by 1%, the production will increase by 0.5109%.
Production elasticity of capital of 0.6203 shows a change in capital
input of 1% resulting in additional production of 0.6203%. The capital input is
more elastic than labor when changes in inputs occur.
The condition of
cooperative financial services industry is Increasing Return to Scale (IRS)
because the amount of production elasticity of labor and capital is greater
than one, that is 1.1312 (= 0.5109 + 0.6203).
As labor and capital increase by 1% simultaneously then production
increases by more than 1%, ie 1.13%.
The coefficient
of business expansion path of 21,597.36 is the relation dimension of K and
L. If one unit (man-hour) input L
increases then K increases by IDR 21,597.36 (US $1.6) in order to remain
economically efficient. This IFSC
industrial study finding is in line with
the previous research in abroad.
7.2.
IFSC
business expansion and economic efficiency determination
The condition
increasing return to scale of IFSC shows the IFSC industry is on an economies
of scale. The large business scale of
IFSC is more efficient and competitive than small-scale enterprises. This
allows IFSC to enlarge its business scale continuously. IFSC business planning
is evident from the growth of its business. Projected growth of IFSC business
as equation (16).
Planning IFSC
business development is an indicative planning because it depends on the vision
and mission and the availability of corporate resources. Scenarios are visible
from business orientation, ie, labor-intensive or capital-intensive
scenarios. Labor-intensive scenarios are
oriented towards more labor usage so that growth plans are higher than capital
growth. While the capital-intensive
scenario uses more capital than labor so that the growth plan is bigger than
the labor force.
Table 3: IFSCs Business
Growth Projection Based on Growth Equation
No |
Expansion Scenarios |
εl |
εk |
gl |
gk |
Gq |
1 |
Labor intensive |
0.5109 |
0.6203 |
10% |
5% |
10.73% |
2 |
Capital intensive |
0.5109 |
0.6203 |
5% |
10% |
13.18% |
Counted by equation (16)
Table 3 shows the IFSCs business planning scenario based on the
estimation of production function. With
the production elasticity of labour and capital of 0.5109 and 0.6203, the labour-intensive
growth scenario with 10% employment growth plan and 5% growth of capital then
the growth of IFSC business is 10.73%.
The scenario of capital-intensive growth with 5% labor and 10% capital
growths then IFSC business growth is 13.18%. The capital-intensive growth
scenario gives higher business growth than labour-intensive growth scenarios
because of the influence of capital higher than the labour force on production.
Enterprise management, in accordance with business philosophy that the
business always to maximize profit, is generally more likely to choose a
capital-based strategic plan in the production process. It is also supported by the ease of
procurement of physical capital and its control.
But for companies incorporated as cooperatives, capital factor becomes
the main obstacle and faces society with abundant labour. So IFSC as a social
business entity should use planning with labour-intensive scenario to expand
its business.
The efficiency of the company is seen from the technical and economic
sides. Technical efficiency is a necessary condition and economic efficiency as
a sufficient condition. From the
estimation result of IFSC production function revealed IFSC is in economic
efficiency because MPl and MPk it is smaller than one, in rational area of
production.
The level of economic efficiency can be known from the Lagrange
multiplier with the budget constraint (budget line). The barometer of IFSC
competition is the money price in the market and the factor prices of
production, labor and capital. Economic efficiency also shows technical
efficiency.
According to determine the level of economic efficiency, its depends on
budget constraint and the prices of input.
The derivation of equation (17) produces an equation of efficiency as
equations (10) or (11), and (18), so that the level of input use, production
level, and maximum profit can be known.
For example, in the budget of IDR100.0 million (USD7,407.41), the economic
efficiency of IFSC is the use of labor force of 4,630.2 man-hour (MH) and
capital of IDR161,944,608.0 (USD11,995.8) and output of IDR2,272,423.96.0
(USD168.33). IFSC has achieved maximum profit even though it could be negative
profit (loss), zero profit (breakeven), or positive profit (gain).
8. REMARKS
From the results of this study can
be seen IFSC production function where labour and capital production factors
have a significant affect its production. The production elasticity of labour
and capital shows the IFSC production process in a rational production area.
But the production elasticity of capital is higher than labour. For the
cooperative business expansion, the effect of using capital is greater than
using labour. The IFSCs industry is in the condition of the increasing return
to scale (IRS) or condition of economies of scale. In the business planning of IFSC, the
expansion of cooperative business still gives bigger benefit to cooperatives. The results of this study indicate that the
increasing return to scale condition of IFSCs industry is in line with the
results of research in various countries.
From these conclusions, IFSC can be an efficient large-scale enterprise.
To achieve economies of scale, IFSC management should develop a business
continuously to achieve business capacity.
By looking at the internal and external environments of the IFSC, it is
advisable that IFSC's business development strategy be pursued through labour-intensive
to enable cooperatives to absorb local labour and increase the added value of
IFSC. The implications of the policy should be that the government supports the
IFSC in improving human resource capacity through employment training.
REFERENCES
AGUNG,
I. G. N. (2009) Time series data analysis using eviews. statistics
in practice. John Wiley & Sons
Ltd.
BOLLI,
T.; ANH V. T. (2012) On the Estimation Stability of Efficiency and Economies of
Scale in Microfinance Institutions (Working Paper). Zurich: KOF Swiss Economic Institute. Avaliable: https://doi.org/10.3929/ethz-a-006909474.
Access: April 24, 2018.
CHEN,
SU-JANE. (2017) Does Size Matter? Economies of Scale in the Credit Union
Industry. International Journal of
Trade, Economics and Finance, v. 8,n. 6, p. 258-262. Available:
http://www.ijtef.org/index.php?m=content&c=index&a=show&catid=88&id=
916. Access: April 24, 2018. doi:10.18178/ijtef.2017.8.6.575.
DOLL,
J. P.; ORAZEM, F. (1984) Productions
economics. Theory With Applications,
Second Edition. John Wiley & Sons.
FERGUSON,
C. E.; GOULD J. P. (1975) Microeconomic
theory, Fourth Edition.
GELLES,
G. M.; MITCHELL D. W. (1996) Returns to Scale and Economies of Scale: Further
Observations. The Journal of Economic
Education, v. 27, n. 3, p. 259-261,
Published online: 10 Jul 2014. Available:
https://www.tandfonline.com/doi/abs/10.1080/00220485.1996.10844915. Access: 20 March 2018
HARTARSKA,
V.; NADOLNYAK, D.; XUAN S. (2012) Efficiency in Microfinance Cooperatives. American Journal of Development Studies,
v. 1, n. 2, p. 52-75. Available:
http://ried.unizar.es/index.php/revista/article/viewFile/52/17. Access:
February 8, 2018.
HARTARSKA,
V.; XUAN S.; MERSLAND, R. (2013) Scale economies and input price elasticities
in microfinance institutions”. Journal
of Banking & Finance, v. 37, n. 1, p. 118-131. Available:
http:doi:10.1016/j.jbankfin.2012.08.004. Access: February 8, 2018.
HENDERSON,
J. M.; QUANDT, R. E. (1980), Microeconomic
theory. A mathematical approach, Third edition. International Student Edition, McGraw-Hill
Book Company
HILL,
R. C.; GRIFFITHS, W. E.; GUAY C. L. (2012).
Principles of Econmetrics,
Fourth Edition. International Student
Edition. John Wiley & Sons
Australasia Pty, Ltd, Sidney, New York, London, Toronto.
KOUTSOYIANNIS,
A. (1982) Modern microeconomics, Second Edition.
KELLER,
G. (2005) Statistics for management and economics, 7th Edition, International
Student Edition (ISE).
MUBYARTO (1998) Reformasi
sistem ekonomi. dari kapitalisme menuju
ekonomi kerakyatan. Penerbit Aditya
Media.
MUNKER,
HANS-H. (1997) Past Present and Future
of the Co-operative Business. University of Marburg, Germany. Paper
presented at the Asia Pacific Cooperatives and Small & Medium Enterprises
Network Conference, Jakarta: July 14
– 15.
NASUTION,
M. (1990) Keragaan koperasi unit desa
sebagai organisasi ekonomi perdesaan.
Disertasi program Dokor Jurusan Perencanaan Wilayah Perdesaan, Fakultas
Pascasarjanan IPB. Bogor.
NICHOLSON,
W. (1979) Intermediate microeconomics
and its application, Second Edition. The Dryden Press, Hinsdale, Illinois
RAHARDJO,
D. (2010a) Ekonomi politik perkoperasian indonesia. Prosiding
Seminar Ekonomi Politik Perkoperasian Indonesia. Ibnoe Soedjono Center bekerjasama dengan
GKBI.
RAHARDJO,
D. (2010b) Koperasi dalam ruang publik. Prosiding Seminar Ekonomi Politik
Perkoperasian Indonesia. Ibnoe Soedjono
Center bekerjasama dengan GKBI.
SITUMORANG,
J. W. (1985) Koperasi dalam pembangunan.
Paper Staff Balitbangkop & PKM.
SITUMORANG,
J. W. (1989) Skala ekonomi bank
perdesaan. Studi kasus BKPD di Kabupaten
Ciamis, Jawa Barat. Tesis Program
Magister Sains, Fakultas Pascasarjana IPB, Bogor.
SITUMORANG,
J. W. (2007) Sukubunga Perbankan Masih Penghambat Pembiayaan KUKM
Indonesia. Infokop-Media Pengkajian KUKM edisi Desember 2007 no 28 tahun XXI;
hal 121-131: ISSN: 0126-813X (Akreditasi LIPI).
Deputi Bidang Pengkajian UKMK, Kemenneg KUKM. Jakarta.
SITUMORANG,
J. W. (2010) Analisis Tipologi dan Posisi Koperasi: Studi Kasus Koperasi
Penerima Program Perkassa di Jawa Timur.
Proceeding THE 4TH CONFERENCE
ON MANAGEMENT RESEARCH. SUSTAINABLE
COMPETITIVE ADVANTAGE IN CHALLENGING MARKET ENVIRONMENT; 2010; p1-13: ISSN:
2086-0390; PPM School of Management, Jakarta.
SITUMORANG,
J. W. (2011a) Koperasi dan Penanggulangan Kemiskinan di Indonesia: Tinjauan
Probabilitas Tingkat Anggota Koperasi dan Tingkat Kemiskinan Provinsi. Jurnal-Pengkajian
KUKM September 2011; v. 6, p. 43-69; ISSN 1978-2896; Deputi Bidang
Pengkajian Sumberdaya UKMK, Kementerian KUKM. Jakarta.
SITUMORANG,
J. W. (2011b) Estimasi Fungsi Usaha Koperasi Dengan Model Power Function Multiple Regression
Terhadap Koperasi Berprestasi Tahun 2009”.
Prosiding SEMINAR NASIONAL
DALAM RANGKA FORUM TAHUNAN PENGEMBANGAN IPTEK NASIONAL (NSTD Forum). Jakarta:
LIPI.
SITUMORANG,
J. W. (2011c) The Economic of Scale And Scope and Business Diversified of
KUD. Paper KONGRES ILMU PENGETAHUAN NASIONAL V 3 - 7 September. Jakarta, 6 September 1991c.
SITUMORANG,
J. W. (2013) Uang, Koperasi, Dan Moneterisasi Perekonomian “Akar Rumput”. Infokop-Media
Pengkajian KUKM Oktober 2013 Edisi v. 23, n. 1: hal 97-113; ISSN 0216-813X
(Akreditasi LIPI). Deputi Bidang Pengkajian Sumberdaya UKMK Kementerian
KUKM. Jakarta.
SITUMORANG,
J. W. (2014) Telaahan Perkembangan Ilmu Ekonomi Global dan Kaitannya dengan
Pembangunan Koperasi Indonesia. Paper LAPORAN KINERJA APARATUR SIPIL
NEGARA TAHUN 2014. Deputi Bidang
Pengkajian Sumberdaya UKMK, Kementerian KUKM.
Jakarta, Desember.
SITUMORANG,
J. W. (2014) Survai Posisi Strategik Koperasi Menuju Skala Besar. Aplikasi Model McKinsey-GE Terhadap Beberapa
Koperasi Calon Skala Besar di Beberapa Provinsi”. JurnaL-PKUKM,
volume 9, hal 1-22. ISSN 1978-2896.
Deputi Bidang Pengkajian Sumberdaya UKMK, Kementerian KUKM. Jakarta, Desember.
SITUMORANG,
J. W. (2017a) Peran Koperasi Dalam
Perekonomian. Kementerian Koperasi
dan UKM RI. ISBN 978-602-5449-02-4. Jakarta.
SITUMORANG,
J. W. (2017b) Posisi Strategis Koperasi
Jasa Keuangan Sebagai Lembaga Keuangan Inklusif. Kementerian Koperasi dan UKM RI. ISBN 978-602-5449-03-1. Jakarta.
SITUMORANG,
J. W. (2018) Learning Curve Estimation of Indonesia Financial Service
Cooperative. Survey on Indonesia
Savings-Loan Cooperative. International Journal of Small and Medium
Enterprises and Business Sustainability, v. 3, n. 01 p. 61-85, March
2018. E-ISSN: 2442-9368. CISBucs University. of Trisakti, Jakarta,
Indonesia-University Social Sciences, Warsaw, Poland.
SWASONO,
S. E. (1998) Demokrasi Ekonomi: Komitmen dan Pembangunan Indonesia. Pidato
PENGUKUHAN JABATAN GURU BESAR TETAP ILMU EKONOMI PADA FAKULTAS EKONOMI
UNIVERSITAS INDONESIA. Jakarta, 13 Juli.
SWASONO,
S. E. (2015) Pidato Akademis Sambutan
Promosi Doktor Untuk Anna A. Susanti. Paper SIDANG AKADEMIS UNIVERSITAS BINA
NUSANTARA DALAM RANGKA UJIAN PROMOSI DOKTOR.
Universitas Indonesia. Jakarta, 30 Mei.
Wolken,
J. D.; Navratil, F. J. (1980) Economies of Scale in Credit Unions: Further
Evidence. The Journal of Finance, 35(3), 769. Avalaible: https://onlinelibrary.
wiley.com/doi/abs/10.1111/j.1540-6261.1980.tb03497.x. Access: April 24, 2018. doi:10.2307/2327497.
ZACHARIAS,
J. (2008) An investigation of Economies of Scale in Microfinance Institutions. Working Paper: GLUCKSMAN INSTITUTE FOR
RESEARCH IN SECURITIES MARKETS. New York Avalaible:
http://web-docs.stern.nyu.edu/ glucksman/docs/Zacharias2008.pdf. Access: April 24, 2018.