zakat and productivity

Productivity growth of zakatinstitutions in Malaysia

An application of data envelopment analysis

Norazlina Abd. WahabIslamic Business School, Universiti Utara Malaysia, Kedah, Malaysia and

IIUM Institute of Islamic Banking and Finance,International Islamic University Malaysia, Kuala Lumpur, Malaysia, and

Abdul Rahim Abdul RahmanKulliyyah of Economics and Management Sciences,

International Islamic University Malaysia, Kuala Lumpur, Malaysia

Abstract

Purpose – The purpose of this paper is to analyze the changes in productivity of zakat institutions inMalaysia from 2003 to 2007. The data consist of a panel of 14 State Islamic Religious Councils (SIRCs)in Malaysia. Efficiency is measured by the Malmquist Index, using a data envelopment analysis (DEA)technique.

Design/methodology/approach – This paper uses Malmquist Productivity Index, using a DEAtechnique. The Malmquist productivity measures are decomposed into two components: efficiencychange and technical change index.

Findings – The results showed that total factor productivity (TFP) has increased slightly for thewhole industry, which is mainly due to the technical change rather than the efficiency change. Furtherdecomposition of the efficiency change into its pure technical and scale efficiency components suggestthat the pure efficiency is found to be a more important source of efficiency change than scaleefficiency component.

Originality/value – This paper investigates the productivity and efficiency of zakat institutions inMalaysia. It will be of value to provide evidence to the policy makers to improve the efficiency of theinstitutions.

Keywords Zakat, Total factor productivity, Efficiency, DEA, Malaysia, Productivity rate

Paper type Research paper

1. IntroductionZakat is one of the five basic pillars in Islam. The term zakat has three differentconnotations; linguistically, theologically and legally. Linguistically, zakat meanscleansing or purification of something from dirt or filth. Theologically, it meansspiritual purification resulting from giving of zakat. Legally, zakat means transfer ofownership of specific property to specific individuals under specific conditions. It is anobligation of Muslims to give a specific amount of their wealth (with certain conditionsand requirements) to beneficiaries called al-mustahiqqin with the main objective of theachievement of socio-economic justice (Muhammad, 1980). Zakat institutions aretrusted bodies that manage zakat in Muslim countries.

In Malaysia, such zakat institutions are State Islamic Religious Councils (SIRCs). Theinstitutions are expected to play a key role in promoting the socio-economic objectives ofzakat in Malaysia. Thus, it is of prime importance that these institutions are being managed

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Zakatinstitutionsin Malaysia

197

Studies in Economics and FinanceVol. 29 No. 3, 2012

pp. 197-210q Emerald Group Publishing Limited

1086-7376DOI 10.1108/10867371211246876

effectively and efficiently. Being a public service organization which is accountable to thestakeholders and Muslim public at large, these zakat institutions have been subjected tointense public scrutiny and criticism. Cursory examination would see various partiesquestioning the efficiency and effectiveness of these institutions in managing zakat affairsof their respective states. Given this continuously arising public concern, it is irony andsurprising to find that research attempting to explore the efficiency of these zakatinstitutions is almost non-exist. Hence, this paper can be considered as the first to explorethe productivity growth of zakat institutions in Malaysia. The structure of this paper is asfollows. The next section provides an overview of the Malaysian zakat industry andliterature on zakat and efficiency. Section 3 discusses the methodology and input-outputspecification. Section 4 reports the findings and the last section concludes.

2. Literature reviewIn Malaysia, all aspects pertaining to the administration of zakat are under thejurisdiction of the states through the SIRCs. There are a total of 14 SIRCs, one for eachof the 13 states and one for the federal territory. Due to the demand of more efficientand effective collection and distribution of zakat funds in Malaysia, some of thereligious councils have corporatized an institution that responsible on the matter ofcollection (and distribution) part of zakat in those particular states. Eight religiouscouncils have so far corporatized, starting with Pusat Pungutan Zakat (PPZ), WilayahPersekutuan in 1991, followed by Pusat Pungutan Zakat Selangor, Pahang and PulauPinang in 1995, and lastly Pusat Pungutan Zakat Negeri Sembilan and Melaka in 2000(Ahmad et al., 2006). It was followed by Tabung Baitulmal Sarawak in 2001 and thelatest was Pusat Zakat Sabah that has been corporatized in 2007.

Most studies conducted on zakat in Malaysia concentrates on various areas includingtheoretical (Mujitahir, 2003; Tarimin, 1995), legal and compliance (Idris et al., 2003;Ahmad, 2004), accounting (Rahman, 2003; Ismail and Sanusi, 2004), management(Nik Mustapha, 1991) and Muslim awareness and payment behaviour (Nor et al., 2004;Ahmad and Wahid, 2005; Idris et al., 2003). However, there are very few studies thatexamined the performance of zakat institutions. Some studies focused on the performanceof zakat collection and distribution (Noor et al., 2005) and some other studies measure theimpact of privatisation on the performance of zakat institutions (Nor et al., 2001; Ahmadand Wahid, 2005). It can be seen that there is no study which comprehensively examiningthe efficiency of Malaysian zakat institutions.

In terms of efficiency, economic efficiency is defined in economic theory as a termdescribing how well a system is performing, in generating the maximum desired outputfor given inputs with available technology. Efficiency is improved if more output isgenerated without changing inputs. An economic system is more efficient if it canprovide more goods and services for society without using more resources. For instance,Husain et al. (2000) and Ibrahim and Salleh (2006) are among studies that explores theefficiency of public sector in Malaysia. Husain et al. (2000) that studied the efficiency ofRoad Transport Department (RTD) using data envelopment analysis (DEA) found outthat out of 46 service units, only 11 service units score above 50 percent of efficiencyscores. Ibrahim and Salleh (2006) for instance, in their studies of local governments inproviding local public goods and services, found that the overall result showed that mostof the local governments in Malaysia are cost inefficient, and that municipality councilswere more inefficient than the district councils.

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3. Research methodology and input-output specificationThis paper aims to investigate the efficiency of all SIRCs in Malaysia. The studyadopts the generalized output-oriented Malmquist index, developed by Fare et al. (1989),to measure the contribution from the progress in technology (technical change) andimprovement in efficiency (efficiency change) to the growth of productivity inMalaysian zakat industries. The Malmquist indexes are constructed using the DEAand estimated using a program developed by Coelli (1996) called DEAP version 2.1.Following Fare et al. (1989), the Malmquist index of total factor productivity growth iswritten as follows:

M 0ðxt; y t; xtþ1; y tþ1Þ ¼

D tþ10 ðx tþ1; y tþ1Þ

D t0ðx

t; y tÞ

£Dt

0ðxtþ1; y tþ1Þ

Dtþ10 ðxtþ1; y tþ1Þ

!Dt

0ðxt; y tÞ

Dtþ10 ðxt; y tÞ

!" #1=2ð1Þ

where M is the Malmquist productivity of the most recent production point (x tþ1,y tþ1) relative to the earlier production point (x t, y t). The notations ðDt

0ðxtþ1; y tþ1Þ

represent the distance from the period (t þ 1) observation to the period t technology.The first ratio on the right hand side of equation (1) measures the change in relativeefficiency (i.e. the change in how far observed production is from maximum potentialproduction) between years t and t þ 1. The second term inside the brackets(the geometric mean of the two ratios) captures the shift in technology (i.e.movements of the frontier function itself) between the two periods evaluated at xt andxtþ1. That is:


Dt0ðx

t; y tÞ¼ Efficiency change

Dt0ðx

tþ1; y tþ1Þ


!Dt

0ðxt; y tÞ

Dtþ10 ðxt; y tÞ

!" #1=2

¼ Technical change

Essentially, the former investigates how well the production function processconverts inputs into outputs (catching up the frontier) and the later reflects theimprovement in technology. According to Fare et al. (1994), improvements inproductivity yields Malmquist index values greater than unity. Deterioration inperformance over time is associated with a Malmquist index less than unity. Thesame interpretation applies to the values taken by the components of the overall TFPindex.

Four distance measures that appear in equation (1) are calculated for each operatorin each pair of adjacent time periods using mathematical programming technique.Assume that there are f ¼ 1,. . ., F firms that produce r ¼ 1, . . . , R outputs ytf ;r usingn ¼ 1, . . . , N inputs xtf ;n at each time period t ¼ 1, . . . , T. Under DEA, the referencetechnology with constant return to scale (CRS) at each time period t from the data canbe defined as:


199

Gt ¼ xt; y t : ytr #XFf¼1

ztf ytf ;r

" #r ¼ 1; . . . ;R

XFf¼1

ztfx

tf ;n # xtn n ¼ 1; . . . ;N

ztf $ 0 f ¼ 1; . . . ;F

ð2Þ

where ztf refers to weight on each specific cross-sectional observation. The assumptionof CRS may be relaxed to allow variable return to scale (VRS) by adding the followingrestriction: XF

f¼1

ztf ¼ 1ðVRSÞ ð3Þ

Following Fare et al. (1994), this study used an enhanced decomposition ofthe Malmquist index by decomposing the efficiency change component calculatedrelative to the CRS technology into a pure efficiency component (calculated relative tothe VRS technology) and a scale efficiency change component which captures changesin the deviation between the VRS and CRS technology. The subset of pure efficiencychange measures the relative ability of operators to convert inputs into outputs whilescale efficiency measures to what extent the operators can take advantage of returns toscale by altering its size towards optimal scale.

Construction of the Malmquist index of firm f0 between t and t þ 1 needs fourdistance functions that calculated using DEA approach, that is:

Dt0ðx

t; y tÞ; Dtþ10 ðxt; y tÞ; Dt

0ðxtþ1; y tþ1Þ; Dtþ1

0 ðxtþ1; y tþ1Þ

These distance functions are the reciprocals of the output-based Farrell’s measure oftechnical efficiency. The non-parametric programming models used to calculate theoutput-based Farrell measure of technical efficiency for each firm f 0 ¼ 1, . . . , F, isexpressed as:

Dt0ðx

tf t ; y

tf t Þ

h i21

¼ max1f 0 ð4Þ

Subject to:

1 f 0ytf ;r #XFf¼1

ztf ytf ;r r ¼ 1; . . . ;R

XFf¼1

ztf ytf ;n # xtf ;n n ¼ 1; . . . ;N

XF

f¼1

ztf ¼ 1 VRS

ztf $ 0 f ¼ 1; . . .F

ð5Þ

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The computation of Dtþ10 ðxtþ1; y tþ1Þ is similar to equation (5), where t þ 1 is

substituted for t. The calculation of two mixed-distance function of the Malmquistindex can be achieved by comparing observations in one time period with the bestpractice frontier of another time period. The inverse of the mixed-distance function forobservation f0 can be obtained from:

Dt0 xtþ1

f t ; ytþ1f t

� �h i21¼ max1f 0 ð6Þ

Subject to:

1 f 0ytþ1f ;r #

XFf¼1

ztf ytf ;r r ¼ 1; . . . ;R

XFf¼1

ztf ytf ;n # xtþ1

f ;n n ¼ 1; :::;N

XF

f¼1

ztf ¼ 1 VRS

ztf $ 0 f ¼ 1; . . .F

ð7Þ

To measure changes in scale efficiency, the inverse output distance functions under theVRS technology will be calculated by adding equation (3) into the constraints inequations (5) and (7). Technical change (TECHCH) is calculated relative to the CRStechnology. Scale efficiency change (SECH) in each time period will be constructed asthe ratio of the distance function satisfying CRS to the distance function under VRS,while the pure efficiency change (PEFFCH) is defined as the ratio of the own-perioddistance functions in each period under VRS. With these two distance functions withrespect to the VRS technology, the decomposition of equation (1) will become:

M0ðxt; yt; xtþ1; ytþ1Þ ¼

D t0ðx

tþ1;y tþ1Þ

Dtþ10 ðx tþ1;y tþ1Þ

� �D t

0ðxt ;y tÞ

D tþ10 ðx t ;y tÞ

� �� 1=2

£D t

0ðxt ;y tÞ

D tþ10 ðx tþ1;y tþ1Þ

� �

£D tocðx

t ;y tÞ

D tþ10 ðx t ;y tÞ

Dtþ1o ðx tþ1;y tþ1Þ

Dtþ1oc ðx tþ1;y tþ1Þ

Dtocðx

t ;y tÞ

Dt0ðx

t ;y tÞ

Dtoðx

tþ1;y tþ1Þ

Dtocðx

tþ1;y tþ1Þ

� �ð8Þ

where:

Dt0ðx

tþ1; y tþ1Þ


!Dt

0ðxt; y tÞ

Dtþ10 ðxt; y tÞ

!" #1=2

¼ Technical change

Dt0ðx

t; y tÞ


!¼ Pure efficiency change

Dtocðx

t; y tÞ

Dtþ10 ðx t; y tÞ

Dtþ1o ðxtþ1; y tþ1Þ

Dtþ1oc ðxtþ1; y tþ1Þ

Dtocðx

t; y tÞ

Dt0ðx

t; y tÞ

Dtoðx

tþ1; y tþ1Þ

Dtocðx

tþ1; y tþ1Þ

!1=2

¼ Scale efficiency change


201

where EFFCH denotes the efficiency change calculated under the CRS technology andPEFFCH is efficiency change calculated under VRS (Fare et al., 1994).

Due to data availability issues, three outputs and two inputs are considered for thisstudy to investigate efficiency of 14 SIRCs in Malaysia for the period of 2003-2007. Thereare two main approaches in the literature to the choice of inputs and outputs in DEA,namely the production approach and the intermediation approach. Under the productionapproach, an institution is defined as a producer. The intermediation approach on theother hand, assumes that a firm act as an intermediary. For the purpose of this study, theproduction approach will be adopted in the definition of outputs and inputs used wherebyit assumes that zakat institutions are primarily producing zakat funds and zakat payers(in a way of dakwah, promotion and, etc.) and distribute it to the asnaf. Hence, theoutputs used in this study are total collection of zakat, total distribution of zakat and totalnumber of zakat payers, while the inputs are number of staff and total expenditure[1].

Based on Table I, of all 14 SIRCs, Selangor is found to have the highest figure for mostvariables used since the state of Selangor is the largest concentration of Muslimpopulation in Malaysia with 16.75 percent of Muslim population in 2007 (Department ofStatistics Malaysia, 2010). On the other hand, Perlis is found to have the lowest value ofoutputs and inputs, simply due to the fact that the state of Perlis is the smallest statein Malaysia with the smallest Muslim population in the country (which recorded only1.21 percent of total Muslim population in 2007) (Department of Statistics Malaysia,2010). TE and TD are very close since distributed zakat funds are considered part of theexpenditure spent by the religious councils in the management of the council’s affairs.

4. Results and analysisi) Production frontier and efficiencyThe basic component of the Malmquist Productivity Index is related to measures ofefficiency. This study initially reports the efficiency of the 14 SIRCs (firms) from the year2003 to 2007 in Tables II and III under the constant returns to scale (CRS) and variablereturns to scale (VRS), respectively. The values of unity imply that the firm is on thefrontier in the associated year, while the value less than unity imply that the firm isbelow the frontier or technically inefficient. Thus, the lower the values from unity, themore inefficient it is compared to the values closer to unity.

Based on Tables II and III, Johor, Pulau Pinang, Kedah and Sarawak are consistentlyefficient, both under CRS and VRS version of technology. In addition, Kuala Lumpur andSelangor are also found to be consistently efficient under VRS version of technology. Onthe contrary, Negeri Sembilan, Melaka, Kelantan, Terengganu and Perak are the leastefficient institutions for CRS and VRS version consistently.

Mean Median Maximum Minimum SD

InputNo. of staff 127 100 461 22 91Total expenditure 37,742,331 25,727,861 214,767,671 1,957,135 42,735,550OutputTotal collection 42,079,560 27,771,981 202,193,541 5,102,537 42,224,646Total distribution 32,111,273 20,392,516 174,520,057 3,036,304 34,232,324No. of zakat payers 304,079 62,408 2,100,562 1,482 505,887

Table I.Descriptive statistics ofinputs and outputs of theSIRCs, 2003-2007

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The values in Tables II and III show the percentage of the realized output level comparedto the maximum potential output level at the given input mix. For instance, in 2004, NegeriSembilan produced 78.1 percent of its potential output level and Perlis produced85.5 percent of its potential output under CRS version. Under VRS of the same year, Melakaproduced 51.8 percent of its potential output while Selangor produced at its maximumpotential output, 100 percent. As indicated by the weighted geometric mean in Tables IIand III, the average efficiency for the whole industry slightly increase for the period2003-2004, but showed a slight decrease in 2005-2006. On average, efficiency performanceof Malaysian zakat institutions was relatively higher based on VRS than on CRS.

ii) Productivity performance of individual institutionTables IV-VI report the performance of the institutions from the year 2003 to 2007in terms of TFP change and its two subcomponents, technical change and efficiency

No. SIRCs 2003 2004 2005 2006 2007

1. Kuala Lumpur 0.977 0.926 1.000 0.885 0.7022. Selangor 1.000 0.881 0.752 0.834 0.7483. Negeri Sembilan 0.677 0.781 0.671 0.686 0.6754. Melaka 0.497 0.513 0.529 0.562 0.4835. Johor 1.000 1.000 1.000 1.000 1.0006. Pahang 0.954 1.000 1.000 0.801 0.7887. Kelantan 0.325 0.363 0.337 0.336 0.3318. Terengganu 0.783 0.795 0.596 0.623 0.5939. Perak 0.568 0.647 0.607 0.600 0.608

10. Pulau Pinang 1.000 1.000 1.000 1.000 1.00011. Kedah 1.000 1.000 1.000 1.000 1.00012. Perlis 0.836 0.855 0.881 1.000 1.00013. Sabah 0.722 0.836 1.000 0.898 0.97714. Sarawak 1.000 1.000 1.000 1.000 1.000

Mean 0.810 0.828 0.812 0.802 0.779

Table II.Efficiency of the State

Religious Councils(SIRCs), 2003-2007 (CRS)

No. SIRCs 2003 2004 2005 2006 2007



Mean 0.845 0.882 0.846 0.856 0.874

Table III.Efficiency of the State

Religious Councils(SIRCs), 2003-2007 (VRS)


203

change, respectively. The value of the Malmquist TFP productivity index and itscomponents that less than unity implies a decrease or deterioration in productivity.Conversely, values greater than unity indicate improvements of productivity in therelevant aspect. Subtracting 1 from the number reported in the table gives an averageincrease or decrease per annum for the relevant time period and relevant performancemeasure. Note that these measures capture performance relative to the best practice inthe sample.

Table IV reveals the changes in the Malmquist-based total factor productivityindex. As shown in the results, Kelantan and Perak had positive productivity changesfor all years of 2003-2004, 2004-2005, 2005-2006 and 2006-2007. In contrast, PulauPinang recorded slight deterioration in TFP for years 2003-2006. However, there weresome improvements of TFP change for Selangor. In addition, Perlis had the highestaverage TFP growth at an annual rate of 9.8 percent, Perak came next with an annual

No. SIRCs 2003-2004 2004-2005 2005-2006 2006-2007 Mean



Mean 1.038 0.969 1.027 1.065 1.024

Table IV.SIRCs relative MalmquistTFP change betweentime period t and t þ 1,2003-2007

No. SIRCs 2003-2004 2004-2005 2005-2006 2006-2007 Mean



Mean 1.004 0.998 1.035 1.104 1.035

Table V.SIRCs relative technicalchange between timeperiod t and t þ 1,2003-2007

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rate of 9.3 percent and Kelantan ranked third with an annual rate of 6.7 percent.Overall, the TFP change slightly decreases by 3.1 percent in 2004-2005 but slowlyincreased after that.

The Malmquist TFP index is further decomposed into two components, technicalchange and efficiency change. Technical change measures the benefits of bettertechnology and capital equipments or simply put innovation (the frontier effects) whileefficiency change is attributed to the practices of best available techniques, whichinvolve the efficient use of inputs (catching up effect). The decomposition of TFP wouldmake a distinction in terms of policy formulation since changes in either one componentwill require different policy direction. The results of technical change and efficiencychange are reported in Tables V and VI. Table V presents the index values of technicalprogress/regress as measured by average shifts in the best practice frontier fromperiod t to t þ 1. According to the results, Pahang, Kelantan and Perak arethe institutions that experienced technical progress from year 2003 to 2007, while theother institutions experienced both technical progress and regress.

Over the period of analysis, Sarawak recorded the highest change in technicalprogress (17.8 percent) in 2003-2004 and Pahang recorded the highest change intechnical progress (18.9 percent) in 2004-2005, Kedah recorded the highest change intechnical progress (23.8 percent) in 2005-2006 while Kuala Lumpur recorded the highestchange in technical progress (23.3 percent) in 2006-2007. Table IV also displays thattechnical progress has been experienced by nine institutions (2003-2004), seveninstitutions (2004-2005), eight institutions (2005-2006) and 11 institutions (2006-2007).On the average, the year 2004-2005 is found to has been the year of technical regress(20.2 percent) while the other periods the institutions recorded technical progress. Out of14 institutions, three institutions (Melaka, Johor and Sabah) are found to have technicalregresses. Pahang is found as the most technical progressive institution (10.7 percent)while Sabah is found as the most technical regressive institution (29.0 percent).

Table VI displays changes in relative efficiency for each individual institution.The results indicate considerable variation across institutions and times. Only fiveinstitutions (Johor, Pulau Pinang, Kedah, Perlis and Sarawak) are found to be efficient

No. SIRCs 2003-2004 2004-2005 2005-2006 2006-2007 Mean



Mean 1.034 0.971 0.992 0.965 0.990

Table VI.Changes in SIRCs relative

efficiency between timeperiod t and t þ 1,

2003-2007


205

(and therefore showed no change in efficiency) in all periods from 2003 to 2007. For theother institutions, there are periods with positive, negative or no changes in efficiency.For the whole period of analysis, the results further indicate that, on average, Sabahrecords the highest efficiency change with 7.9 percent, followed by Perlis with4.6 percent, Perak with 1.7 percent and Kelantan with 0.5 percent six institutions(Kuala Lumpur, Selangor, Negeri Sembilan, Melaka, Pahang and Terengganu) are foundto be the institutions that experienced efficiency deterioration with 27.9 percent,27.0 percent, 20.1 percent, 20.7 percent, 24.7 percent and 26.7 percent, respectively.Of all the periods of 2003-2007, only the period of 2003-2004 record a positive efficiencychange while the other periods record negative efficiency change.

In order to identify a change in scale efficiency, the efficiency change is furtherdecomposed into two subcomponents, namely pure efficiency change (PEch) and scaleefficiency change (SEch), the results of which are reported in Table VI. The subset ofpure efficiency change measures the relative ability of operators to convert inputs intooutputs while scale efficiency measures the extent the operators can take advantage ofreturns to scale by altering its size towards optimal scale.

Based on Table VII, the results show that the scale efficiency appears to be lessimportant source of growth to efficiency change as compared to the pure efficiencychange component for most zakat institutions in Malaysia. Four institutions( Johor, Pulau Pinang, Kedah and Sarawak) recorded no changes in annual growthfor both the pure and scale efficiencies during the period of 2003-2007. Relative toother institutions, Kuala Lumpur records the highest deterioration of scale efficiencyof 20.203 percent in 2006-2007. In terms of pure efficiency, Terengganu records thehighest deterioration by 20.31 percent in 2004-2005. In contrast, Kelantan records thehighest growth in scale efficiency with 27.5 percent in 2004-2005 while Sabah recordsthe highest growth in pure efficiency with 21.6 percent in 2003-2004. During the entireperiod of study, only the years between 2004 and 2005 is identified as the yearsof pure efficiency deterioration as well as the years of scale efficiency improvement.

2003-2004 2004-2005 2005-2006 2006-2007No. SIRCs PEch SEch PEch SEch PEch SEch PEch SEch

1. Kuala Lumpur 1.000 0.948 1.000 1.080 1.000 0.885 1.000 0.7932. Selangor 1.000 0.881 1.000 0.854 1.000 1.008 1.000 0.8983. Negeri Sembilan 1.152 1.002 0.896 0.958 1.027 0.997 1.004 0.9794. Melaka 1.041 0.991 1.023 1.009 1.120 0.949 0.899 0.9555. Johor 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.0006. Pahang 1.000 1.048 1.000 1.000 0.893 0.897 1.077 0.9137. Kelantan 1.156 0.966 0.728 1.275 1.194 0.834 1.110 0.8888. Terengganu 1.079 0.941 0.689 1.088 1.144 0.915 1.111 0.8569. Perak 1.141 0.998 0.896 1.047 1.014 0.974 1.175 0.862

10. Pulau Pinang 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.00011. Kedah 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.00012. Perlis 1.000 1.022 1.000 1.030 1.000 1.136 1.000 1.00013. Sabah 1.216 0.952 1.065 1.123 1.000 0.898 0.996 1.09214. Sarawak 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000

Mean 1.054 0.981 0.943 1.029 1.025 0.968 1.025 0.942

Notes: PEch – pure efficiency change; and SEch – scale efficiency change

Table VII.Changes in efficiencycomponents by SIRCsbetween time period t andt þ 1, 2003-2007

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Overall, the results suggest that the technical and size of the institutions do matterin determining the institutions’ productivity and efficiency level.

We now turn our discussion on the developments of the returns to scale of zakatinstitutions in Malaysia. The following Table III displays the results of developmentsin returns to scale of zakat institution in Malaysia.

Table VIII displays the results of zakat institutions returns to scale. As the tableshows, over the five periods, the zakat institutions were experiencing a U-shape trendof inefficient zakat institutions, from 67.2 percent in 2003 and 64.3 percent in 2004, to42.9 percent in 2005 before it rose up to 64.3 percent in 2006 and 2007. It is apparentfrom the table that, the number of zakat institutions experiencing economies of scale(IRS) has decreased substantially from two (14.3 percent) in year 2003 to none(0 percent) in 2006 and in 2007, after it rose up to four (28.6 percent) in 2005. In contrast,zakat institutions that are experiencing diseconomies of scale (DRS) dominate theinefficient zakat institutions in all years except in 2005. For instance, in year 2003, therewere six (42.85 percent) zakat institutions experiencing diseconomies of scale and itrose up to eight (57.1 percent) in 2004 and nine (64.3 percent) in 2006 and 2007 before itdeclined to two (14.3 percent) in 2005. The share of scale efficient zakat institutions(operating at CRS) on the other hand, are quite stable, where the share of efficient zakatinstitutions has increased from six (42.85 percent) in year 2003 to eight (57.1 percent) inyear 2005 before it declined to five (35.7 percent) in year 2007. Hence, there are a lot ofimprovements should be undertaken by zakat institutions to improve overall efficiencyif scale inefficiency resulted from the scale inefficient institutions could be undertaken.

iii) Productivity performance of the industryTable IX summarizes the performance of Malmquist productivity index of the zakatinstitutions in Malaysia between 2003 and 2007. On the average, Perlis records thehighest growth in TFP with 9.8 percent while Sabah and Perlis records the highestgrowth in efficiency (7.9 percent) and technical changes (10.7 percent), respectively.Johor, on the other hand, records the lowest growth in TFP with 25.5 percent which ismainly due to technical regress (25.5 percent).

On average, the improvement of TFP of zakat institutions in Malaysia is mainlydue to technical change (3.5 percent) while efficiency change contributed a negativechange (20.1 percent). Furthermore, the efficiency change is largely contributed bypure efficiency (1.1 percent) while scale efficiency contributed a negative change(20.2 percent) to the efficiency change. This indicates that the size of the institutionsdoes not matter in affecting efficiency changes. The findings of substantial growth intechnical change and negative growth in efficiency components suggest that anincrease in TFP of zakat institutions in Malaysia is due to improvement in technical

2003 2004 2005 2006 2007No. of

ZIs %shareNo. of

ZIs %shareNo. of

ZIs %shareNo. of

ZIs %shareNo. of

ZIs %share

CRS 6 42.9 5 35.7 8 57.1 5 35.7 5 35.7DRS 6 42.9 8 57.1 2 14.3 9 64.3 9 64.3IRS 2 14.2 1 7.2 4 28.6 0 0 0 0Total 14 100 14 100 14 100 14 100 14 100

Table VIII.Returns to scale in zakatinstitutions in Malaysia


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aspect rather than the innovation in efficiency components. On average, zakat institutionsin Malaysia are found to be experiencing a technical progress.

5. ConclusionThe results from this study have important implications for the Malaysianzakat industry. As a whole, TFP has increased (of at least 2.4 percent) throughout theperiod of 2003-2007. It should also be noted that the very presence of TFP growth in theindustry was mainly due to technological improvement (3.5 percent). This resulttherefore indicates that the Malaysian zakat industry has great potential to furtherincrease its output through an improvement in the technology and capital equipments.Further decomposition of the efficiency change into its pure technical and scale efficiencycomponents suggest that during the period of study, pure technical efficiency hasresulted in Malaysian zakat institutions to increase. Comparing among the SIRCs, it isfound that Perlis records the highest growth in TFP with 9.8 percent, followed by Perak,Kelantan, Negeri Sembilan and Pulau Pinang. It seems to show that corporatization ofsome SIRCs does not affect the productivity and efficiency of the institutions. However,further study needs to be conducted to confirm the hypothesis.

In terms of the returns to scale, the results suggest that most zakat institutions wereoperating at non-CRS. Hence, there are a lot of improvements could be undertaken byzakat institutions to improve overall efficiency if scale inefficiency resulted from the scaleinefficient institutions could be undertaken. Owing to its limitations, the paper could beextended in a variety of ways. First, the scope of this study could be further extended toinvestigate factors that influence the productivity and efficiency of the institutions.Second, future research into the efficiency of zakat institutions could be extended to theeffect of efficiency of zakat institutions on social performance of Muslim society inMalaysia. Despite these limitations, the findings of this study are expected to contributesignificantly to the existing knowledge on the operating performance of zakat institutionsin Malaysia.

No. SIRCs TFPCH TECHCH EFFCH PECH SECH



Mean 1.024 1.035 0.990 1.011 0.980

Notes: TFPCH – total productivity change, TECHCH – technical change, EFFCH – efficiencychange, PECH – pure efficiency change, and SECH – scale efficiency change

Table IX.Summary of Malmquistproductivity index ofSIRCs means, 2003-2007

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Note

1. Total expenditure (TE) is the input that refers to overall expenditure spent by the religiouscouncil (and its subsidiary) in managing all its responsibility.

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Further reading

Farrell, M.J. (1957), “The measurement of productive efficiency”, Journal of the Royal StatisticalSociety A, Vol. 120, pp. 253-81.

Idris, K.M. and Ayob, A.M. (2002), “Peranan Sikap dalam Gelagat Kepatuhan Zakat PendapatanGaji” (“The role of behaviour on compliance behaviour of zakat on employment income”),Analisis, Vol. 9 Nos 1/2, pp. 171-91.

About the authorsNorazlina Abd. Wahab is a Lecturer at the Islamic Business School in the College of Business,Universiti Utara Malaysia, and a PhD Candidate at the IIUM Institute of Islamic Banking andFinance, International Islamic University Malaysia. Norazlina Abd. Wahab is the correspondingauthor and can be contacted at: [email protected]

Professor Abdul Rahim Abdul Rahman is a Professor at the Kulliyyah of Economics andManagement Sciences, International Islamic University Malaysia.

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