Road Infrastructure and Spatial Economic Dependence in the Western Region of Java

Journal of Indonesian Economy and Business Volume 30, Number 3, 2015, 239 – 246 ROAD INFRASTRUCTURE AND SPATIAL ECONOMIC DEPENDENCE IN THE WESTERN REGION OF JAVA Siti Herni Rochana Institut Teknologi Bandung ([email protected]) B. Kombaitan Institut Teknologi Bandung ([email protected]) Eka Purwanda STIE STEMBI Bandung ([email protected]) ABSTRACT The western region of the island of Java consists of three provinces, namely: West Java, Banten, and Jakarta, is a region that contributes significantly to the GDP of Indonesia. In 2010 the contribution of the three provinces was 33.94% of the total GDP, and the remaining 66.06% came from the other 30 provinces. In spite of its high contribution, in terms of the value added by the western region of Java, there are inequalities between the regions. In the year 2010, Jakarta’s per capita income was ten times, or more, than that of Lebak. The existence of this problem in the income disparity between the regions in western Java raises questions relating to the spatial economic dependence of the western region of Java. The unit analysis of the research is all the districts/cities in West Java, Banten, and Jakarta. The measurement used for the spatial economic dependence is Moran’s Index. Spatial variables were comprised in the spatial weight matrix (matrix-W), which was formed using three approach- es: based on the distance, the neighbourhood, and the road transportation network. The economic variables in this study are the level of income per capita and economic growth. The results showed spatial economic dependence, based on distance and neighbourhood, tended to be low. Whereas, the spatial economic dependence based on road connectivity, especially freeways, showed a moderate correlation. Keywords: road infrastructure, spatial economic dependence, Moran’s Index, western region of Java. INTRODUCTION inces shows that the three provinces have high West Java, Banten, and Jakarta are provinces intensity economic activities. This is not sur- producing high added value in Indonesia. The prising because the country's capital Jakarta is contribution of the three provinces to Indonesia's the centre for government and business, while GDP is quite large (Figure 1). The GDP of West West Java and Banten are districts/cities adja- Java, Banten, and Jakarta in 2010 were cent to Jakarta. IDR308.96 trillion, IDR83.80 trillion and Behind the high output in West Java, Banten, IDR391.53 trillion respectively. These figures and Jakarta, there are inequalities between the represent the percentage proportions 13.37%, districts/cities. In 2010, based on current prices, 3.63%, and 16.94% of Indonesia's GDP respec- the level of income per capita of DKI Jakarta tively. The total GDP contribution given by the was the highest at IDR89.92 million, while the three provinces was 33.94%, with the remaining lowest income per capita was in Lebak regency 66.06% coming from the other 30 provinces. at the level of IDR6.45 million. Given these fig- The high GDP generated from these three prov- ures, it can be said that the level of income per 240 Journal of Indonesian Economy and Business September capita of Jakarta was about 14 times that of Leb- The problem of the regional income disparity ak. Large differences in the per capita income in the western region of Java raises a question levels of the two areas show that the disparities about connectivity and trade relationships. If the between the regions are quite striking. This ex- transportation accessibility links among the re- ample of inter-regional income disparities be- gions are available equally in all directions, the tween Jakarta and Lebak raises great concerns difference in the revenues of adjacent regions because the geographical distance between the should not be great. The income gap between the two areas is not so far. The distance between regions of West Java, Banten, and Jakarta raises Jakarta and Lebak is approximately 131 kilo- many questions relating to economic dependen- meters. The per capita income gap between the cies (trade relations) and inter-regional transport regions in the study area showed the presence of connectivity in the western region of Java. a regional income disparity problem. Theoretically, spatial economic relations can THEORETICAL FRAMEWORK be explained from the theory of trade and eco- The economic theory that explains the effect nomic geography. Dixit and Norman (1980) of road infrastructure on economic spatial de- stated that the areas having trade relations tend pendence can be seen in Figure 2. Road infra- to have the same relative prices for goods and structure can reduce transportation costs. The factors of production, including wages. Because new economic geography theory (Krugman, wages are a source of income, it can be said that 1991; Fujita et. al., 1999) explains that a low in areas that have trade relations, then incomes cost for transportation will create and establish should be relatively equal in those areas. trade relations between regions. Trade between The new economic geography (Fujita et al., regions would then equalize the price of the fac- 1999) stated that inter-regional trade will occur tors of production, including wages and interest if transportation costs are low enough so that the rates. The factor of price equalization can lead to inter-regional trade is economically feasible. spatial economic dependency. Transportation costs are the determining factor for trade relations. If the transportation costs are 1. Transportation Costs and Trade too expensive, then trade is not economically The new economic geography was formed feasible. If the transportation costs are low, then by Krugman (1991) and then Fujita et. al. trade will be economically feasible. Transport (1999). This theory explains the connection be- costs are very closely related to infrastructure, tween transportation costs and trade relations. particularly the roads. Good infrastructure for Low transportation costs can create trade rela- transport will cause low transportation costs. tions and form an agglomeration built core and Conversely, poor infrastructure causes high also periphery formations. Conversely, high transportation costs. transportation costs can impede trade relations so that regions will produce goods in an autarky manner. Consumer utility is a function of the quantity of goods manufacturing (M) and agricultural goods (A) in the form: U = M µ A1−µ (1) where 0 <µ <1. Manufactured goods will vary in a condition of increasing returns in a monopolis- tic competition. The production of manufactured Source: Statistics Indonesia goods follows the equation: Figure 1. GRDP contribution of West Java, Banten, and Jakarta to Indonesia’s GDP in 2010 2015 Rochana et al. 241 1/ n ρ The profit function is revenue from the sale M = ⎡ m(i)ρ di⎤ , 0 < ρ <1 ⎣⎢∫0 ⎦⎥ of manufactured goods, minus the cost of labour: M M M M M While the budgetary constraints faced by πr = pr qr − wr (F + c qr ) . The profit maxi- consumers are: mization is obtained from: M M M A n (7) Y = p A + p(i)m(i)di pr = c wr / ρ ∫0 By entering the price equation (7) into the From the results of the consumers’ optimi- zation, the demand functions for manufactured profit function: goods and agriculture goods are: M M M ⎡qr c ⎤ π r = wr ⎢ − F⎥ (8) p( j)−σ σ −1 m( j) = µY for j ∈[0,n] (2) ⎣ ⎦ G−(σ −1) The balance of the manufacturer (at the zero (1− µ)Y profit condition) is obtained: A = (3) p A q∗ ≡ F(σ −1)/cM (9) By entering the manufacturing demand func- M tion (2) and agriculture (3) into the utility func- l∗ ≡ F + c q∗ = Fσ (10) tion resulting from the indirect utility function as Using the price equation (7), it can also be follows, we get: found that the wage of manufacturing workers in U = µ µ (1− µ)(1−µ)YG−µ ( p A)−(1−µ) (4) the North is as follows: M R M 1 1 1/ µ A (1−µ) w = [ Y (T ) −σ Gσ − ] σ ] (11) Where G ( p ) is the cost of living index. r ∑s=1 s rs s Equation (4) shows that consumer utility is af- fected by the price index. The form of the trans- 2. Trade and Factor Price Equalization portation costs in the core periphery models is Dixit and Norman (1980) built a proposition iceberg where transportation costs are entered as that trade would make the factor price equaliza- a multiplier of the home price. As an example, if tion. Suppose a country produces goods named 1 M a a the price of goods produced in the North is pr , and 2, respectively priced at p1 and p2 under and the transportation costs from North to South the condition of autarky and p1 and p2 under the M is Trs , then the price of goods delivered to the condition of balanced trade. While the imports South will be for the two goods are m1 and m2. The feasible condition for trade is therefore: pM = pMT M (5) rs r rs a a ( p1 − p1)m1 + ( p2 − p2 )m2 ≥ 0 (12) By including the transportation costs (5), the demand function for manufactured goods is: The prices of the goods are a reflection of the wages, which can be written as follows: R qM = µ Y ( pMT M )−σ Gσ −1T M (6) r ∑s=1 s r rs s rs p1 = b11w1 + b12w2 (13) On the other hand, companies use the fixed p = b w + b w (14) labour input F and marginal imput CM so that the 2 21 1 22 2 amount of labour used is shown in the following Where bij is the input coefficient denoting the equation: amount of factor j required for a unit output of good i.

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