Agglomeration, transport, and regional development in Indonesia

Journal of Indonesian Economy and Business, 2012

Concentration of manufacturing is an interesting topic in location of economic activity since manufacturing was the leading sector in the Indonesian economy. The previous studies demonstrated that firms were localized in major metropolitan areas as well as a set of emerging regions. The paper aim to complement the findings of the previous studies related to geographical concentration of manufacturing industry by exploring the impact of manufacturing concentration on regional inequality in the regency in Java during the 1998-2007. The Theil index and the location quotient index are employed in order to analysis the inequality and the location of manufacturing industry in Java region. The study found that the Theil index shows an increasing trend implying that the inequality of the manufacturing industry within regencies has increase. While, the inequality between regency shows a decreasing trend over the period of observation implying that the manufacturing industry in Java spreads o...

2012

This article examines the dynamics of employment concentration in Indonesia over the period 1994 to 2004. Using a spatial lag model, we analyze the relationship between districts’ employment growth rates and their spatial characteristics, which includes natural geographic isolation, distance to urban centers and population of surrounding districts. The empirical models are estimated for the entire economy and nine employment sectors. The results suggest distance to larger population centers negatively affects growth. Employment became more evenly dispersed in Indonesian districts during the sample period, but this dispersion was primarily driven by the outward expansion of larger urban districts. It was also found that districts with higher levels of sectoral specialization (lower employment diversity) experienced lower growth rates.

1996

In certain situations, economic liberalization policies can increase the degree of spatial centralization of resources and spatial concentration of manufacturing in large metropolitan areas. In addition, historical patterns of location make it difficult to alter the degree of centralization. This article explores these issues by specifying and estimating a nested logit model of industrial location of manufacturing activity in Java, focusing on the unincorporated sector. The results indicate that plants strongly prefer locations with mature plants in related industries, which offer a built-up stock of local knowledge. In addition, the 1983 liberalization in Indonesia was associated with increased centralization of the unincorporated sector. Although the liberalization gave unincorporated firms better access to government and other centralized services, firms needed to centralize to take advantage of these opportunities because the bureaucratic process is centralized and communications are poor. The relative increased growth of the corporate sector following liberalization may also have helped to further draw unincorporated plants into centralized locations.

Review of Urban & Regional Development Studies, 2000

This paper presents an analysis of regional changes in the spatial pattern of Japanese manufacturing industries and the effect of deregulation of foreign investment in Indonesia during 1984–1994. Empirical analysis in this paper uses data of 560 Japanese manufacturing industries in Indonesia. The result of this study indicates their continuous regional concentration in the core region of Java. The regression analysis indicates that market, agglomeration and infrastructure continue to be the main reasons for the location of Japanese manufacturing industries. The current economic crisis has substantially reduced the level of new investment in the core region of Java.

Jurnal Pendidikan Geografi, 2022

The number of industries in Central Java is expanding, resulting in an improvement in the area's economy. The study's objectives are as follows: (1) to examine the dynamics of manufacturing labor; (2) to examine the spatial concentration of manufacturing industry activity; and (3) to analyze variables impacting industrial sector employment. Between 2005 and 2015, this quantitative study analyzed secondary data. The descriptive analysis, time series analysis, Klassen typology analysis, industry index analysis, and multiple linear regression techniques were employed to accomplish the research objectives. The study's findings are as follows: (1) the number of industries has decreased, particularly since 2007, from 6.9 percent in 2007 to 4.8 percent in 2015; (2) the spatial concentration of the manufacturing industry in Central Java is concentrated in 11 regions: Sukoharjo, Karanganyar,

2008

Abstract Despite a diminishing role in industrial countries, the manufacturing sector continues to be an engine of economic growth in most developing countries. This article surveys the evidence on the determinants of industry location in developing countries. It also employs micro data for India and Indonesia to illustrate recent spatial dynamics of manufacturing relocation within urban agglomerations.

2005

The concentration of spatial economic activities, especially in manufacturing industries has become an interesting phenomenon to be analyzed. In manufacturing industries, spatial concentration is determined by wages, transportation cost, market access, and externalities which relate with localization economies and urbanization economies. The existence of spatial concentration has a relation with industrial specialization which based on industrial structure on that region. The objective of this paper is to describe where the concentration of East Java manufacturing industries is, how the locational distribution of that industries is, and how the relation between the spatial concentration and specialization and industrial structure in East Java is. This paper is using Location Quotient, Herfindahl Index, Elison-Glaeser Index, Krugman regional specialization index and Krugman bilateral index to analyze the data..

2021

This study aims to analyze the determinants of agglomeration in Indonesia by including research variables, namely the Exchange Rate (ER), Agglomeration, Williamson index (IW), Regional Income (RI), Domestic Investment (DI), Length of Road (LR), and Regional Expenditures (RB). The analysis method in this research was to estimate panel data and econometric tests, including heteroscedasticity test, multicollinearity test, Chow test, Hausman test, and t-statistic test. The data were obtained from Bank Indonesia (BI), and the Central Statistics Agency (BPS) from 2010 to 2017. The results of the study showed that agglomeration in Indonesia was affected by changes in the Exchange Rate (ER), Regional Expenditure (RB), Regional Income (RI), Domestic Investment (DI), Length of Road (LR), and Williamson index (IW). An integrated policy needs to be formulated to improve economic efficiency through the development of production chains and the utilization of regional economies to encourage nation...

2004

The regional specialization via differences in transport costs are observed in Japanese manufacturing industries. Concretely, industries with high transport costs for their products, such as iron and steel, petroleum and coal products, remained close to the core region while industries with low transport costs, such as electrical machinery, precision instruments, have relocated to the periphery region. The purpose of this paper is to give a theoretical foundation for this fact by use of a new economic geography model with multiple industries. The urban costs and congestion are explicitly included in the model. We obtain the following results. First, if congestion does not exist, at most one industry disperses when transport and commuting costs are sufficiently small. Furthermore, regional specialization occurs in which industries having higher adjusted transport costs (which are defined as the ratios of transport costs to the number of varieties) than that of the dispersing industry...

2017

Industrial agglomeration has become common discussion topic, particularly in relation to economic growth and the reduction of regional inequality between regions. The phenomenon that occurs at this time that the agglomeration of manufacturing industries in South Sumatra has not fully happened. However, the determination of South Sumatra province as one of the central regions of industrial growth reflects the high economic growth and low levels of income inequality are the effects of the agglomeration of manufacturing industry. The analysis technique used the simultaneous model with panel data interregional in South Sumatra with two-stage least square approach, during the period 2004-2014. The potential agglomeration of manufacturing industry is calculated using the Balassa index, while regional inequality calculated using Williamson index. The results showed that, (1) economic growth (G), income inequality (IW) and population (POP) exhibited significantly effect on agglomeration of ...

Regional Studies, 2009

The objective of this paper is to analyse the influence of agglomeration economies on location decisions taken by new firms inside metropolitan areas. Following the literature, we consider that agglomeration economies are related to the concentration of an industry (location economies) and/or to the size of the city itself (urbanisation economies). As we assume that these economies differ according to firms' level of technology, our sample comprises new firms from high, intermediate and low technology industries. Our results confirm these sectoral differences and show some interesting location patterns for manufacturing firms. Taking into account the renewed interest in the influence of geography and distance in the location of economic activity, we introduce in our estimation the effect of the area's central city as a determinant for the location of new firms in the rest of the metropolitan area. This allows us to determine whether a suburbanisation effect exists and whether this effect remains the same regardless of the industry involved. Our main statistical source provides plant-level microdata for the creation and location of new industrial firms.

SSRN Electronic Journal, 2020

Industrial agglomeration has become common discussion topic, particularly in relation to economic growth and the reduction of regional inequality between regions. The phenomenon that occurs at this time that the agglomeration of manufacturing industries in South Sumatra has not fully happened. However, the determination of South Sumatra province as one of the central regions of industrial growth reflects the high economic growth and low levels of income inequality are the effects of the agglomeration of manufacturing industry. The analysis technique used the simultaneous model with panel data interregional in South Sumatra with two-stage least square approach, during the period 2004-2014. The potential agglomeration of manufacturing industry is calculated using the Balassa index, while regional inequality calculated using Williamson index. The results showed that, (1) economic growth (G), income inequality (IW) and population (POP) exhibited significantly effect on agglomeration of manufacturing industry (IB); (2) agglomeration of manufacturing industry, population, per capita income (YCap t) and a per capita income of the previous year (YCap t−1) a significant effect on economic growth; and (3) economic growth (G t), economic growth in the previous year (G t−1) and agglomeration of manufacturing industry significant influence on income inequality.

Theoretical Economics Letters

This paper investigates the geographic concentration of knowledge and technology-intensive (KTI) industries, covering 0.43 million establishments across various districts of rural and urban areas in India. Using the spatially weighted Ellison-Glaeser index, cartogram and choropleth map results show that few KTI industries are highly geographically concentrated in urban and rural areas, specific to certain districts and a few Indian states. Within highly employable states of India, workers are employed in only a particular location of a few districts. Also, we differentiate between urban and rural concentrated and urban and rural dispersed districts within highly employable states. In addition, results validate the extent of the geographical concentration of KTI industries in rural and urban areas of highly employable Indian states. Further, results exhibit that industries spatially concentrate in only a few locations across specific districts in India, indicating natural advantages and other economic forces are pretty strong in certain areas. Besides, results suggest that the demand-based networks and push-and-pull supply chains are well established in a specific location of a few districts, incentivizing other firms to locate their business, which creates a spatial spillover effect and benefits all economic agents. Empirical results suggest that policymakers in India could unleash the resource potential of spatially concentrated districts by implementing a location-based policy and considering multi-level governance and informal and formal institutions, which could further boost regional economic growth.

Growth and Change, 2019

Connectivity in urban networks is often deemed to be an important feature of economically vibrant cities. Under conditions of contemporary globalization, the importance and geographies of these connections are increasingly variegated. Accordingly, various attempts have been made to analyse the external relations of cities and metropolitan regions, often through the lens of multi-locational firms. Our purpose in this paper is to address the to-date limited empirical knowledge about whether firms originating from different regions (i.e. firms with different headquarter [HQ] locations) create different patterns of inter-urban relations. Drawing on the interlocking network model and using the Jakarta metropolitan area (JMA) as a case study, this paper explores how manufacturing firms with HQs either inside (further differentiating between the JMA and other cities) or outside (further differentiating between East Asian and non-East Asian countries) Indonesia produce different patterns of external relations. Our findings indicate that each category of firms generates unique configurations of inter-urban relations for the JMA at the global and national scales. We argue that these variegated networks patterns not only reflect different locational strategies of firms, but also Indonesia's evolving policy orientations which have complex relations with evolving patterns of economic globalization.

Journal of Economic Geography, 2005

Spatial inequality in developing countries is due to the natural advantages of some regions relative to others and to the presence of agglomeration forces, leading to clustering of activity. This paper reviews and develops some simple models that capture these first and second nature economic geographies. The presence of increasing returns to scale in cities leads to urban structures that are not optimally sized. This depresses the return to job creation, possibly retarding development. Looking at the wider regional structure, development can be associated with large shifts in the location of activity as industry goes from being inward looking to being export oriented.