Ekonomi dan Keuangan Volume 41, Nomor 2, 1993

The Spatial Distribution of Manufacturing Industries: An Analysis of Central

Piet Rietveld Daniel D. Kameo

ABSTRAK

Artikel ini menganaiisis distribusi spasiai kegiatan manufaktur di Jawa Tengah menurut Kabupaten - berdasarkan data 1988. Kedua penulis menemukan bahwa lokasi industri umumnya berorientasi pada daerah perkotaan. Lebih dari 25 persen perusahaan industri beriokasi di daerah-daerah Kotamadya. Angka tersebut lebih besar jika kabupaten-kabupaten yang berbatasan dengan kotamadya ikut dimasukkan.

Kecenderungan ini berkaitan erat dengan ketersediaan faktor-faktor produksi. terutama infrastruktur. Lokasi industri akan mengarah ke daerah-daerah yang memiliki fasiiitas teiepon, jalan. air dan listrik yang lebih baik. Dalam kaitan ini. daerah perkotaan jelas lebih baik daripada daerah pedesaan.

1 This paper is partly based on the study "Analisis Perkembangan Lokasional Industrialisasi di Jawa Tengah," Department of Economics, Universitas Kristen Satya Wacana, Salatiga, 1992. This Study contains contributions by Daniel Kameo, M.A., Gatot Sasongko, M.S., Yos Indrajit SE, and Prof. Drs. Sadyadharma. Youdi Schipper and Niels Vtaanderen contributed to the statistical analysis in Section V.

211 Rietveld dan Kameo

I. INTRODUCTION The manufacturing industry has been a very dynamic sector in the Indonesian economy during the past two decades. During the 1970's this development was overshadowed by the extremely rapid development of the oil sector, but after the stagnation of the international oil market in 1982, manufacturing has become a leading sector in economic growth in Indonesia. Part of the manufacturing growth is immediately related to the use of natural resources, mainly oil and timber. This growth of resource based activities took place especially on the islands of Sumatra and Kalimantan. But footloose industries, being much less dependent on natural resources have been very dynamic too. These footloose industries, which are mainly located on Java, produced ever increasing production volumes to come to meet domestic demand. Some of these sectors (clothing, textiles, footwear) started to become major exporters in the 1980's. From a spatial perspective the growth oh the manufacturing sector was beneficial for resource rich regions such as Sumatra and kalimantan. The eastern part of Indonesia could only benefit to a limited extent. The island of Java was also a major beneficiary of the dynamics in the manufacturing sector, i.e., for the footloose activities. The cities of Jakarta, Bandung and Surabaya and their surrounding areas developed into large industrial centers giving the provinces of West and East Java a clear industrial face. In , on the other hand, the manufacturing sector has a much more modest presence. As indicated in Table 1, Central Java remains far behind West and East Java in terms of non-oil manufacturing output. When oil processing is taken into account, the Central Java share in total output increases somewhat due to the presence of petro-chemical activities in Cilacap. In this respect. Central Java is an exception compared with the other parts of Java where oil related manufacturing is absent. Oil processing plants are primarily located on Sumatra and Kalimantan. In terms of total manufacturing employment, the position of Central Java is of about the same level compared with that of West and East Java. Obviously, average output per worker is lowing Central Java and the share of small scale firms is high in this province. Another difference between Central Java on the one hand and East and West Java on the other hand concerns the existence of a clear industrial center. In central Java there is no outstanding industrial center of a size comparable with Jakarta, Bandung or Surabaya. The province's capital city, , never had a strong industrial base and specializes in services and trade. The city of Yogyakarta, Located near Central Java, specializes in tourism and education. The province of central Java has a number of centers of more limited size, however, such as , Kudus, Salatiga, and , each with its own profile of

212 The Spatial Distribution of Manufacturing Industries

Tabel 1 Regional Distribution of Manufacturing Activity in Indonesia, 1985

Perc»rlllig4rffN^tiku«tlT<^

Quputt in Large, Errrpfoyment in Regfon in Large and llifedium Scaie ' iiMcH^um, and Smafi Large, *4edfufri,an{S ln(histry(Exoiuciing $cate indu$i]> Smsk Scale IndusUy OS) (IftctudingoR}

Jakarta 18.7 12.1 12.2 West Java 26.9 16.8 21.0 Central Java/ 7.6 11.1 21.6 Jogjakarta East Java 21.1 13.5 23.4 Sumatera/Kaliman- 21.9 43.9 16.9 tan Rest of Indonesia 3.7 2.7 4.9 Total Indonesia 100.0 100.0 100.0 specialization. These cities are located in the Northern and Eastern part of the province. In addition, the oil related activities in Cilacap on the south coast should be mentioned. Another way to illustrate the lack of interest from large investors to invest in Central Java is provided by investment figures of the regional investment board (BKPMD). As indicated in Table 2, West Java (including Jakarta) has been able to attract the lion's share of investments for which BKPM approval is necessary (almost 70%). The share of Central Java is only 6% for domestic investment and 7% for foreign investments. It is important to observe that Central Java never was a major area of large scale manufacturing activity. It was always dominated by West

Tabel 2 Regional Distribution of Approved BKPM Investments (1968-1989)

Oopwstielnvftstnient Foreign Invwtnwd

Jakarta 9.8 West Java 37.1

Central Java/Jogyakarta 6.5 East Java 10.1 Sumatera/Kalimantan 28.2 Rest of Indonesia 8.3 Total Indonesia 100.0 Source: BPS, BKPM

213 Rietveld dan Kameo and East Java. The high level of regulated in manufacturing as well as the strong bureaucracy have certainly stimulated investors to located near the spatial center of government power, i.e., the Jakarta region. That major improvements have been realized in infrastructure has been improved as witnessed for example by the container facilities in the port of Surabaya and the toll road in the Surabaya area. But also in Central Java infrastructure underwent major improvements not as spectacular as in East and West Java (cf also Dick and Forbes, 1992). The present level and quality of Central Java infrastructure certainly allow higher levels of large scale manufacturing activity; nevertheless, it seems that infrastructure remains a bottleneck in further economic development all over Java. This is of course no surprise since the recent levels of economic growth in the private sector are so high that it was difficult to match these by investments in the public sector. Infrastructure will continue to play a main role in Indonesian economic policy, therefore, and it may be expected to have a considerable influence on spatial development patterns, not only at the high levels of spatial aggregation here, but also at the lower inter-Kabupaten level. It is to this level that the present paper will be addressed. This paper aims at analyzing the spatial distribution of manufacturing activity in Central Java at the kabupaten level. Trends in investments will be studied in section 11. In section 111 we discuss the spatial distribution of large and medium scaled manufacturing activity, followed by a discussion of small scale industry in section IV. Section V contains a statistical analysis of location patterns with special attention to the role of infrastructure as a location factor. Section VI concludes.

II. INVESTMENT TRENDS IN THE MANUFACTURING INDUSTRY Data from the Regional Investment Coordination Board (BKPMD) show that both foreign investment (PMA) and domestic investment (PMDN) significantly since early Pelita 1 to 1989. In that period, the domestic investment increased from the total of Rp. 88.454 billion in Pelita 1 and Pelita 11 to more than double that amount, Rp 199.625 billion in Pelita 111, and again that amount increased more than double, Rp 461.400 billion in Pelita IV. In the year 1989 alone, the realized domestic investment reached Rp. 314.000 billion. Foreign investment has also experienced a significant increased since Pelita 1. Although it has been concentrated only in nine regions, the total amount has increased from Rp 73.541 billion in Pelita 1 to the total of Rp 316.061 billion in Pelita IV. In the year 1989 alone, foreign investment reached the total of Rp 429.000 billion. At the level of central Java, the shares of domestic and foreign investment were 55% and 45%. The spatial distribution of the two categories was rather different, however. For PMDN, 71% of the total investment was invested in rural

214 The Spatial Distribution of Manufacturing Industries areas (Kabupaten) while most of the PMA, 64% was invested in the urban areas (Kotamadya). In addition, it must be noted that the investment disparities among regions are relatively high. In total, 83% of the investment, PMA and PMDN is concentrated in only eight regions, namely Kotamadya Semarang, Kotamadya Surakarta, Kotamadya Salatiga, Kabupaten Kendal, Cilacap, Semarang, Karanganyar and Kabupaten Sukoharjo. Gradually a process of deconcentration has taken place as can be seen from the coefficient of variation as an indicator of interregional disparities. The coefficient of variation for the total investment in Pelita 1 and Pelita 11 is 2.8, which later decreased to 2.0 in Pelita III and 1.9 in Pelita IV. i

III. SPATIAL DISTRIBUTION OF MEDIUM AND LARGE SCALE INDUSTRIES AND EMPLOYMENT ABSORPTION Data from the 1988 central Java Industrial statistics show that there are clear spatial concentrations of manufacturing activity among the 35 regencies/municipalities in central Java. Food, beverages and tobacco (ISlC 31) manufacturing, although relatively equally distributed, are still concentrated in certain regions. More than 45% of the total establishments are concentrated in Kabupaten Klaten, Kabupaten Boyolali, Kabupaten Kudus, Kabupaten Pati and Kotamadya Semarang. Despite the concentration pattern, ISlC 31 industries can be found in all 35 regions. Industries of other ISlC categories have more distinct concentration patterns with more or less half of the establishments concentrated in no more than four regions. More than 40% of the textile, wearing apparel and leather industries (ISlC 32) are concentrated in only three regions, Kabupaten Batang, Kotamadya Surakarta and Kotamadya Semarang. Wood and wood products and furniture industries (ISlC 33), shows a more striking concentration with almost 60% of 162 industries concentrated only in Kabupaten Banyumas, Kabupaten Pati and Kotamadya Semarang. A similar concentration pattern applies for paper products and printing manufacture (ISlC 34) with 64% of a total of 80 companies located in Kotamadya Semarang, Kotamadya Surakarta and Kabupaten Pati. As shown in Table 3, chemical and chemical products, rubber and plastic products (ISlC 35) is also concentrated in three regions, but the other 60% is almost equally distributed in other regions. As for manufacture of fabricated metal products, machinery and equipment (ISIC 38), 65% of the total of 117 establishment are concentrated in four regions. An exception is found for industries of non-metallic mineral products (mainly bricks and tiles) with almost 50% of this ISIC 36 concentrated only in Kabupaten . Basic metal industry (ISIC 37) is the least of all because until 1988 there were only two

215 Rietveld dan Kameo

Tabel 3 Regions with Industrial Concentration (Medium and Large Firms) by ISIC Categories. 1988

Region RegionaA Shares of-the Total NuRdreroTEitoMehm^ tnCentni Javg

91 32 iliii 34 iiili 97 llllll 93

L/ A . • Kotamadya I. Semarang 9.3 28.8 23.7 50.0 23.9 2. Surakarta 16.5 20.0 9.5 11.1 13.5 3. legal 37.8 4. Pekalongan 10.7 Kabupaten

5. Kudus 8.1 7.4 28.4 50.0 6. Banyumas 19.8 7.4 7. Kebumen 49.8 8. Boyolali 13.7 9. Klaten 13.4 7.4 8.6 10.Batang 17.3 11. Pati 6.6 15.0 17.1 12. Pati 7.8 IS.Brebes 7.4 6.8 M.Banjarnegara 8.1 Total Share 40.0 75.6 73.5 63.8 40.6 49.8 100 72.6 59.4

Total Number of Es• 910 626 162 80 148 221 117 37 tablishments in Central lava Source: Survai Tahunan Industri Jawa Tengah, 1988 Note: Only shares higher than 5% are mentioned and they are included in the top three to seven highest rank establishments, one located in Kabupaten Kudus and the other in Kotamadya Semarang. In general, it can be concluded that industrial location in central Java tends to be urban oriented. More than 25% of the total establishments are located in Kotamadya, not counting those Kabupaten that are on the periphery of the Kotamadya. In 1988, medium and large scale industries in Central Java absorbed a total of 296.500 workers. As shown in table 4 below, it is clear that ISIC 31 and ISIC 32 dominated the employment absorption with 38.2% and 34.5% of total employment. In ISIC 31, clove cigarette industries alone absorbed 37.2% of the total work force, followed by sugar industries (15.8%), tea processing industries (10.1%), and tobacco drying and processing tobacco (8.1%). For ISIC 32, employment absorption was dominated by weaving industries, (55.2%), yarn and thread manufacturing (17.5%), and batik industries (9.4%).

216 The Spatial Oistribudon of Manufacturing Industries

Table 4 Employment Absorption in Medium and Large Scale Industries, by ISIC Categories, 1988

ISIC Total EiAoiovinant * r

31 11,100 38.2 32 102,100 34.5 33 14,000 4.5 34 8,400 2.8 35 29,300 9.8 36 13,000 4.4 37 500 0.2 38 12,500 4.3 39 3,600 1.3 Total 296.500 100.0

Source: SUtistik Industri Jawa Tengah 1988 VI. THE SMALL SCALE AND COTTAGE INDUSTRY It is clear that labor productivity in small and cottage industries is very low compared to medium and large scale industries. The number of workers is so large however that total output is of a level comparable to that of large and medium scale industry. In 1988, the small firms are estimated to contributed to contribute 41% of the manufacturing sector. From the employment absorption point of view, small and cottage industries have played a very important role. In 1988 for example, from the total of 2.211.000 workers in the industrial sector, 1.968.000 or almost 90% were engaged in small and cottage industries. Food industries contribute the largest portion to total output (41.3%), followed by construction materials and chemicals (27.3%) and textile and leather industries (15.5%). In terms of number of establishment and employment, especially for cottage industries, the 1987 Home Industry Survey data shows that from a total of 445.000 establishments employing 904.500 workers, central Java ranks first among the 27 provinces in the country. The difference with East Java and West Java, which are ranked second and third, rank is rather big. These provinces are reported to have "only" 275.200 and 229.700 establishments employing 571.200 and 493.100 workers respectively. The distribution of small and cottage industries is relatively equal within the central Java province: much more equal than the spatial distribution of large and medium scale industry. Nevertheless, small industries are concentrated in Kotamadya Semarang, Kotamadya Surakarta, Kabupaten Boyolali, Kabupaten Kudus, Kabupaten Pekalongan and Kabupaten Semarang. Cottage industries are concentrated in four kotamadya (Salatiga, , Pekalongan and ).

217 Rietveld dan Kameo

In terms of number of establishments, 76% of the small scale industries and 77.3% of the cottage industries are dominated by food, beverages and tobacco manufacturing (ISIC 31); textile, wearing apparel and leather (ISIC 32); and wood, wood products and furniture industries (ISIC 33). A similar pattern of domination is found in medium and large scale industries, as shown in Table 4. While location wise, data show no indication of parallel industrial concentration patterns, as one would have expected, between small and medium/large scale industry. This show that there is little or no interdependence between small and medium/large industry of the same ISIC category.

V. AN EXPLANATORY ANALYSIS OF INDUSTRIAL LOCATION IN CENTRAL JAVA After the descriptive sections 2-4 we continue with a more analytical approach to the distribution of industrial activities in Central Java. We will use four groups of explanatory variables: 1) infrastructure, 2) demand, 3) urbanization economics, and 4) region specific dummies. These variables form together a locational profile indicating the criteria which are important for firms considering locations for a production plan. A definition of the variables used can be found below. All variables are measured at the kabupaten level. Infrastructure variables: Xi : percentage share of households with telephone connection X2 : percentage share of villages with connection to the public electricity network ^3 : road density (measured in kilometers asphalt road per square km) ^4 . distance to the nearest seaport (measured in km) Yj : distance to the nearest airport (measured in km) Demand: . distance to the nearest large city (measured in km) Urbanization economies: Xj : urbanization ratio (share of population living in municipalities which are urban according to the BPS definition) Xg : suburbanization dummy (=1 for kabupaten bordering a large city; = 0 elsewhere) Regional specific dummies: Xg : Kudus dummy (= 1 for kabupaten Kudus, = 0 elsewhere) XiQ-. Salatiga dummy (=1 for kotamadya Salatiga; = 0 elsewhere)

218 The Spatial Distribution of Manufacturing Industries

Table 5 Correlation Matrix of Location Factors (Coefficients X lOO)

Yi Xs X* Ah Xa Xt Ah x»

too 45 23 3969 56 -7 -16 -9 40 -1 -3 98 100 60 79 55 -21 -31 -31 67 1 1 63 40 A 100 100 68 -1 7 -17 -32 7Z o U ZU -3 67 -7 -43 -41 73 / 4 7 7 C 1 / 100 1 -26 -29 39 I A 5 if A -12 4S 100 -28 14 -24 2 -4 -5 100 63 -10 -30 -10 -11 100 -32 -24 -4 -5 100 15 2 36 100 -6 -6 100 -3 100

All variables have been defined in such a way that they are independent of the size of the regional unit concerned. The infrastructure variables relate to telephone, electricity, roads, seaports and airports. The seaports considered are Semarang, Tegal and Pekalongan on the North coast and Cilacap on the South coast, airports are found in semarang and Surakarta. For the computation of shortest distances the airport of Yogyakarta is also taken into account. The variables measure the availability and/or these infrastructure components. Reliable data on infrastructure quality are in general not a variable. Unfortunately, data on the supply of water in the public network or from wells are not available. Since large urban centers form an important part of the market of many industries, the distance to the nearest large city (Semarang, Surakarta of Pekalongan) is used as an approximation of the demand side. Urbanization economies relate to the benefits industries experience because they are located in an urban area. Among these benefits are the easy access to various services and the supply of relatively well skilled labor. Two variables have been proposed to take the urbanization economies into account. One relates to the urbanization rate which may vary from as low as 5 per cent for kabupaten without a significant urban center (such as Boyolali or Demak) to 100 per cent for a kotamadya such as Surakarta. Note that not all kotamadya have an urbanization rate of 100 per cent: for kotamadya Semarang it is only 80% (for an explanation, refer to Rietveld, 1988). The other urbanization variable relates to suburbanization of industries. Those kabupaten which border kodya Surakarta (Sukohardjo, Karanganyar), kodya Semarang (Kajiupaten Semarang), and kodya Pekalongan (kabupaten Pekalongan) receive a

219 Rietveld dan Kameo

Figure 1 Overlap in Location Profile

Infrastructure Urbanization Economies 1 2 3 o 4 8 J V \ f 6 9 10

Demand Region Specific \^ Dumrnies J value equal to 1 for this dummy variable. The other kabupaten receive a value of zero. Regional specific dummies have been formulated for kabupaten Kudus and kotamadya salatiga. The reason will become clear below: these regions give rise to large outliners in the statistical analysis. In these cities specific factors seem to be at work - not captured by the other variables which lead to a high level of industrial activity. Apart from infrastructure, little attention is paid to other inputs such as labor and raw materials. The reason is that there is an excess supply of labor all over central Java so that its role as a location factor is most probably small, except for particular sectors where specific skills are needed. The neglect or raw materials can be defended since there are few raw materials in Central Java which are of particular importance for large scale industry (possible exceptions are sugar and tobacco pro-cessing). The large majority of large scale industry in Central Java is footloose. In 1988 the penetration of telephones (Xf) in some rural kabupaten is still very low (about 1%). The average value in the kotamadya is about 15%. For roads (Xf) and electricity (.^2) a similar gap exists between urban and rural areas, but the difference is less marked for electricity. Accessibility of nodes in networks such as seaports (A'4) airports (Xfj follow a rather different pattern since 1.) not all kotamadya are located near these facilities, and 2.) there are kabupaten which are located very near to these facilities. A similar reasoning holds true for the distance to nearest large city variable (Xg), since not all kotamadya can be termed a large city. Finally, the urbanization rate {X-j) follows a pattern which is similar to the infrastructure variables {XyX-f).

220 The Spatial Distribution of Manufacturing Industries

The interrelationships between the independent variables are shown in Table 5 by means of the correlation coefficients. The interrelationships mentioned above are clearly visible in the correlation matrix. Two clusters of closely related variables exist (cf. also Fig.2): Cluster A: X,, X2, X3, X7 with an average correlation of about .75. Thus the spatial distribution of telephone, electricity and roads and the degree of urbanization are closely related.this means that the infrastructure variables group and the urbanization economies variables group are to a certain extent overlapping. - Cluster B Xj (distance to nearest airport) and Xg (distance to nearest large city) with a correlation coefficient of .63. The correlation coefTicients between the other pairs of variables are much smaller. Due to high correlation coefficients in these clusters, it appears to be impossible to estimate the influence of each variable separately. This multicollinearity problem forces one to drop some of the variables and to consider the remaining ones as representative for the total group of variables in a cluster. The dependent variables has been formulated as follows: Fj: Total realized investments for which BKPM approval was received between 1968 and 1988 per capita ( Rp 1000 per person) ¥2'. employment in large and medium scale industry as a percentage of the total labor force. As shown in Table 6 the distribution of BKPM approved investments per capita is very uneven. It is (Approximately) zero in a considerable number of rural kabupaten, especially at the South coast of Central Java. High values are recorded for the large cities of Semarang and Surakarta and surrounding kabupaten. Also in Cilacap investment activity has been high. The very high figure for Salatiga must be a coincidence of a large textiles plant in a relatively small city, leading to a high per capita value.lt is important to note that these investment data do not cover total manufacturing investment. Small scale industry is excluded. These data are obviously strongly influenced by capital-intensive sectors. Besides, it should be noted that BKPM investment data are not restricted to manufacturing but also include limited numbers of projects in agriculture (e.g. plantations), hotels and real estates. The volume of employment in large and medium scale industry as a percentage of the total labor force (F2) is below 10% in most kabupaten. This underlines that large and medium scale manufacturing is of limited importance as an absorber of employment in most kabupaten.

221 Rietveld dan Kameo

The highest values are usually found in the large cities and the surrounding kabupaten. For Kudus and exceptionally high value is found. This is caused by the presence of a large scale labor intensive tobacco industry here. The presence of this sector in Kudus is a combination of historical reasons and localization economies leading to an attractive locational profile for the tobacco industry and related manufacturing activities. The correlation between F, and F2 is of a medium size (.45) indicating that the spatial distribution of investment and employment are to some extent similar but certainly not identical. (See Table 6). For example, the labor intensive industry in Kudus does not give rise to large investments, and the capital intensive industry in Cilacap does not generate much employment. An investigation of the simple correlation coefficients between Fi and F2 on the one hand and X, to XJQ on the other hand reveals that with the exception of the dummy variables, employment and investment follow largely the same pattern. Employment and investment are positively related with the infrastructure components telephone , electricity and roads and with the urbanization rate. They are negatively related with distance variables (airport, nearest large city). These results are fully supported by location theory. For a more in depth investigation we need a multivariate analysis, however. The results of such an analysis, taking into account the multicollinearity problem mentioned above, are presented in Tables 7 and 8. Table 7 shows that infrastructure plays a clear role as a key factor in investment decisions of firms. Road play a significant role, where it should be remarked that roads (X3) may also be assumed to represent electricity and telephone. The distance to both seaports and airports has the expected negative sign. For the logarithmic transformation of distances slightly better t values were obtained, compared with a linear specification. Suburbanization of investments indeed seems to take place, as can be inferred from the estimation result for Xg. Finally, the Salatiga dummy is highly significant and contributes largely to the high value of R'. If Salatiga would be deleted as an explanatory variable, one would only achieve a value for R' of around .45. The estimation results for employment in a large and medium scale industry are presented in Table 8. It appears that variables from the infrastructure cluster Xj, X2, X3 and X7 play a significant role, but it is not possible to disentangle each variable's separate contribution. Distance to infrastructure nodes X4 and Xj have again the expected negative sign, although their t values are not entirely satisfactory. Specifications with log (distances) did not give rise to better estimation results. The coefficient of - .0001 indicates that - ceteris paribus - an increase in distance to a seaport with 100 km leads to a decrease in F2 of .10%. Suburbanization of manufacturing activity

222 The Spatial Distribution of Manufacturing Industries

Table 6 Distribution of Investments and Employment in Manufacturing Industry

BKPM mtatmtS* 1868 1988 Empfaymeni In Urge and iOeatiOR Rpl 000 per capita Medium Scale Industry BP* J Perceriags of Tout l^abour Pores

KABUPATEN

4 Z-|l4.-4n 1 •> 1 1 99 1. cilacap 1 d 1 A 1 2. Banyumas .U . / 7 g 1 1 3. Purbalingga .1 A 4. Banjarnegara 1 9 A3 . 1 3 5. Kebumen g .95 .1 7 4 6. Purworejo 3.3 .31 7. wonosooa R1 8. Magelang 8.4 1 OA 9. Boyolali C fl 7 AR 4 A ^ 1 4tMn 7 (\ 1 A5 10.Klaten * * C , . IA A^ a« 4A B 7 C fl 1 3 71 A./ 1 11 .Sukoharjo 7 1 z. wonogin . J 43 .7 All 1 j.^dTdngdnyar 3.77 17. jragcn 43 8 .25 * C AA^k Bk ^k «k Vk 11 A' 09 1o.croDogan .1/7 IA Rtors 4 .14 17.Rembang 1.0 .29 18.Pati 8.8 1.31 19.Kudus 77.9 11.6 20.)epara .0 1.68 21.Demak 23.0 .26 22.Semarang 185.1 2.20 23.Temanggung 5.5 .69 24.Kendal 2.2 2.39 25. Banlang 391.7 2.28 26.Pekalongang 106.6 2.56 27.Pemalang 25.6 .87 28.Tegal 23.7 .98 29.Brebes .6 .46 KOTAMADYA

30.Magelang 12.6 31.Surakarta 440.4 32.Salatiga 4395.5 33.Semarang 250.5 34. Pekalongan 35.9 35. Tegal IL2_ Source: BPS, BKPMD

223 Rietveld dan Kameo

Tabel 7 Regression Analysis of Location Factors Influencing Investment Decission in Cenral Java, 1988

OependflfltVsnatiie ||||||;||||||i)/ir|i6^

Constant 82 (1.93) 304 (3.19) Road Density Xa 2.6 (4.05) 2.0 (3.02) Distance to Sea Port X4 -9.51 (-1.52) log X4 -0.29 (-2.37) Distance to Airport X5 -0.32 (-1.20) LogXs -0.40 (-2.37) Suburbanization 127 (2.67) DUmmy Xs Salatiga Dummy X10 4117 (42.0) 4180 (45.7) R' 0.99 0.99 is clearly relevant (XgJThe estimates indicate that in kabupaten bordering to large cities such as Karanganyar, Sukohardjo, etc. employment in large and medium scale industry is about 1.5% above the level one would expect for similar kabupaten not bordering to large cities.. Given the low average value for large industry employment shares, this, is quite a considerable difference. The result for the Kudus dummy indicates that large scale industry is more than 9% higher in Kudus than one would otherwise expect.

VI. CONCLUDING REMARKS In this study we have analyzed the spatial distribution of manufacturing activity in Central Java. Manufacturing is oriented towards areas with a reasonable quality of infrastructure (roads, telephone, electricity). Also the accessibility of seaports and airports plays a role in location choice.

Tabel 8 Regression Analysis of Location Factors Influencing Investment Decission in Cenral Java, 1988

DependentVbte VbniMit

Constant 1.28 (2.43) 1.15 (2.50) Telephone Xi 12.2 (3.71) Road Density X3 -0.03 (3.85) 0.01 (1.51) Distance to Seaport X4 -0001 (-2.25) -0001 (-1.54) Distance to Airport X5 -0001 (-1.06) -0001 (-1.85) Urbanization Rate X7 -1.51 (2.81) 4.0(5.10) Suburbanization Dummy Xa 9.44(2.81) 1.49 (3.15) Kudus Dummy X9 9.44 (9.80) 9.11 (10.27) R^ 0.88 0.91

224 The Spatial Distribution of Manufacturing Industries

Table 9 Bottlenecks in Infrastructure for Manufacturing Investment in Central Java (Based on Interviews with 24 Entrepreneurs)

tnfras«1r«ctttr« Type Number ef Tknee en tnliraelrariure Type ie (h>r«iclered M BeMene^ is liwMitm«tte

1. Electricity 10 2. Land Acquisition 9 3. Telecommunication 6 4. Roads 6 5. Water 4 6. Seaport 2 Source: UKSW (1992)

Time series data on investments indicate a trend towards a more even spatial distribution of industrial activity. It appears to be difficult to disentangle the role of infrastructure categories such as roads, telephone, electricity in the location process because these variables are strongly correlated. We plan to carry out another phase of the study in which entrepreneurs are directly interviewed about location choice, an example of a first test with such an approach is given in Table 9. Among the infrastructure type most frequently mentioned as a bottleneck in investment are electricity, telecommunication and roads. Also land-related bottlenecks appear frequently.

225 Rietveld dan Kameo

References

Kameo, D., Gatot Sasongko, Yos Indrajit and Sadyadharma, Analisis Perkembangan lokasional Industrialisasi di Jawa Tengah, Salatiga: Fakultas Ekonomi Universitas Kristen Satya Wacana, 1992.

Hill, Hal. "Manufacturing Industry," in anne Booth (ed). The Oil Boom and After, Indonesian Economic Policy and Performance in the Soeharto Era, Singapore: Oxford University Press, 1992, 204-257.

Dick, Howard and Dean Forbes. "Transport and Communications: a Quiet Revolution," in: Anne Booth (ed). The oil Boom After Indonesian Economic Policy and Performance in the Soeharto Era, Singapore: Oxford University Press, 1992, 258-282.

Fakultas Ekonomi, Strategi Pengembangan Investasi Jawa Tengah, Universitas Kristen Satya Wacana and Badan Koordinasi Perencanaan Modal Jawa Tengah, 1992.

Rietveld, Piet. Urbanization Patterns in Indonesia, Bulletin of Indonesian Economic Studies, 24 (1988), 73-95.

Sensus Ekonomi 1986: Hasil Pendaftaran Perusahaan/Usaha, Kantor Statistik Propinsi Jawa Tengah, 1987 .

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