Human Indonesia Development

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The quality of human resource in Indonesia, measured by the Human Development Index (HDI), lies in the medium range. In 2005, the HDI of Indonesia (72.8) ranks 107th in the world (Human Development Report, UNDP, 2007). Moreover, Java represents the most developed areas in Indonesia, but its HDI is far below the international standard (HDI above 80). The HDI for DKI Jakarta province, which has the highest HDI in Indonesia, is only 76.1 (Table 1.1).


The comparison of human development within Java also shows an imbalance between the urban and rural areas. Most regencies in Java that are located far from capital province belong to the lower-middle HDI category while the regencies or municipalities that are near the capital province tend to belong to upper-middle category. The spatial pattern of HDI in Java stated in Figure 1.1. This imbalance in human development is primarily the result of imbalance in educational achievement, in particular in mean years of schooling, along with achievements in living standards, as reflected in per capita consumption. Based on this fact, human development in Java still needs more attention to be paid. Development literature recognizes that infrastructure serves as a catalyst to economic development, by improving access to resources and enhancing the impact of intervention. The infrastructure refers to the facilities and mechanisms that ensure education, health care, community development, income distribution, employment and social welfare.

Infrastructure services affect people in many ways. People use infrastructure services to warm and light their homes; to consume and produce their products; to communicate each other, give information, and study at school, home, and work. Infrastructure services also help people to take a travel to work, to school, or to going somewhere. In addition, the availability of infrastructure services such as transportation services needed to distribute raw materials to factories and finished products to market affects profitability and competitiveness of businesses. The difference of regency characteristics in this region may affect the difference of infrastructure availability and human resources.

This research aims to explore the relation between the availability of various infrastructure networks and the level of human development in Java. The general objective is to analyze the relation between infrastructures availability and human development in Java by types of infrastructure.

The organization of this study is as follows. Following this introductory chapter, chapter 2 provides a literature review on human development and infrastructure. Chapter 3 explains the detail of methodology and data set used in this study. Chapter 4 presents the empirical result of this study. Finally, chapter 5 provides concluding remarks and policy implications.



Indonesia consist five main islands in order of size. The islands are Kalimantan, Sumatra, Irian Jaya, Sulawesi, and Java respectively. Java is located midway down the Indonesian archipelago and covers an area of approximately 132,246 km2. Java is the site of its capital city, Jakarta. Despite being Indonesia's third largest landmass, Java is the most populous Indonesian island and its 128 million inhabitants comprise around 59 percent of the republic's population as we can see in table 2.1. Java is divided into six provinces: DKI Jakarta, West Java, Central Java, DI Yogyakarta, East Java, and Banten. In this study, Java is including Madura island.

Despite Java is smaller island among the five main islands in Indonesia, but the number of population is largest. The large of number population cause the ethnic composition in Java is comparatively homogeneous. The Javanese and Sundanese are two ethnic groups that native to the island. Madurese is a third group who lives in the island of Madura that located in north east coast of Java.

More than 90 percent of populations in Java are Muslims. There are Christian communities especially in the larger cities. Roman Catholic is mostly in some rural areas of south-central Java. There are also small Hindu enclaves that scattered throughout Java and a large Hindu population along the eastern coast nearest Bali, especially around the town of Banyuwangi. Buddhist communities also exist primarily among the Chinese Indonesian.

Java is the most economically developed of Indonesia. The contribution of Java's economy is significant to Indonesian economy that contributes around 59 percent. In 2005, the gross regional domestic product (GRDP) at current price of Java achieves 1,571 trillion rupiahs. The DKI Jakarta province has highest GRDP compared with others province in Java or in Indonesia.



3.1. Human Development

Over the last decades, the view on economic development has profoundly changed because of two different issues that emerged in the literature: the concepts of human development and sustainable development. The human development (HD) paradigm developed by UNDP focuses on how development can enlarge people's choices by expanding freedoms and capabilities. The human developed paradigm is based on the concept of human well being (e.q, Sen 1982, 1985).


The United Nations Development Programme (UNDP) has carried out the measurement of human development index (HDI) at the aggregate level in 1990. The index has become a major technique for measuring human welfare. The growing popularity of the technique indicates that the HDI is a huge success. It has become an annual event to produce HDI for countries of the world by the UNDP. In addition, country-based human development reports are been conducted to focus on the status of the human development indices within nations of the world. With this approach, human development does not concern with not only in terms of the income of the people but also in terms of other welfare variables that directly influence quality of human beings. These other variables, in addition to income, are health and education. The higher the HDI is the higher the quality of human life and the lower the level of deprivation and poverty among the people.

The implication of this index is that human development is higher if more people are educated and if people lead a longer life as result of better medical service, better sanitation and dependable access to clean drinking water.

3.2. Infrastructure and Human Development

Infrastructure has been defined in terms of the physical facilities (roads, airports, utility supply systems, communication system, water and waste disposal system, education, public health facilities, etc), and services (water, sanitation, transport, energy) flowing from those facilities (Sida, 1996; ESCAP and AITD, 2003). Therefore, we can derive the evaluation on the impact of the infrastructure investment on development can be evaluated from how the availability of infrastructures can help the communities to get the opportunity in direct and indirect ways in raising income, access to education and access to health facilities. For example, better access to infrastructure increases productivity by lowering input costs. This will lead to income increase.

Infrastructure development is important factor for economic development. The theme of 1994 World Development Report is infrastructure and development, emphasizes on providing infrastructure services to get together the demands of businesses, households and other users as one of the major challenges development of economic. The quality of life for a community and its productivity are determined by quality of infrastructure services.

Infrastructure consists of economic infrastructure and social infrastructure. Both of infrastructures can influence significantly to economic development and the quality of life. The economic infrastructure consist public facilities such as telecommunications, water supply, and sanitation; public works such as roads, dam and irrigation networks; and other transport sectors such railways, urban transport, ports, etc. Social infrastructure consist the provision of health care and education.

The government plays a key role in human resource development of the people. As the government has more money to finance public services such as education and transfer such as employment compensation, welfare and social security, the human resource development improves. There are two ways relation between economic growth and human development (Ramirez et all, 1998). One of government role is to provide public goods for people such as infrastructures, water and sanitation, road, bridge, etc. The availability of good infrastructures in regions can attract private and public investments, which are required in the economic development.

Role of government is very important in providing infrastructures that enables rural and urban society to improve their living standard. It is necessary to analyze the need of different infrastructures between urban and rural areas including the differences between urban poor and rural poor society. Economic and Social Commission for Asia and the Pacific (ESCAP) and AITD (2003) suggests that empowerment of local government and community participation is necessary to bring success of infrastructures development. There are two aspects of empowerment. First is political power in delegating the tasks to local government through appropriate regulation. Secondly, devolution of financial resources is necessary to local institutions. It encourages their ability to initiate infrastructures development projects that are suitable for their own regions for growth and poverty reduction.

The choices of appropriate infrastructure programs are often based on cost-benefit analysis. However, ESCAP and AITD (2003) notes that “cost-benefit analysis of infrastructure programs poses several difficulties because of complexities of identifying multifaceted benefits and measuring them in dynamic world”. Therefore, for the case of Indonesia, it can be more appropriate to present the analysis at regency level.

There are only a few studies of the transmission mechanism of infrastructures on human development. The degree and magnitude of the effectiveness of alternative infrastructure investment vary across regions and sectors. For example, Chi Seng Leung and Peter Meisen (2005) show that increasing electricity consumption per capita can directly stimulate faster economic growth and indirectly achieve enhanced social development, especially for medium and low human development countries. There is a significant association between electricity consumption and the United Nations' Human Development Index.

The infrastructure of roads appears to have strong indirect and direct effects on poverty reduction, and these are even clearer when we combine the roads with complementary investments, such as schooling. Rural infrastructure investments can improve to higher farm and non-farm productivity, employment opportunities, and increased income, thereby reducing poverty and increasing human development by raising mean income and consumption (Ali and Pernia, 2003). Duffy-Deno and Eberts (1991) also find that public infrastructure has positive and statistically significant effects on per capita personal income. According to Fan, S and Zhang, X (2004), rural infrastructure and education play a more important role in explaining the rural nonfarm productivity. The rural nonfarm economy is a major determinant of rural income, investing more in rural infrastructure is key to an increase in overall income of the rural population. Ezcurra, R. et al, 2005 find that public infrastructure can reduce private costs and finally increases productivity.

Estache and Fay (1995) found that improved access to roads and sanitation has been a key factor of income convergence for the poorest regions in Argentina and Brazil. Beside that, infrastructure access can increase the value of the possessions of the poor. Therefore, the income and the purchasing power parity of the poor will increase.

Angrist and Lavy (1999), and Case and Deaton (1999) summarize some recent evidence on a causal relationship between spending on school facilities and improvements in attendance, especially of poor children. Lokshin and Yemtsov (2005) also find that improvements in school infrastructure produced nontrivial benefits in school enrollment rates, increased school attendance, and reduced health risks for school-age children. A better transportation system and road network also help raise school attendance. According to Leipziger et al. (2003), electricity also improves more time people for study and the use of computers.

In the health facilities, access to safe water and sanitation plays a key role. The consumption of infrastructure services by households such clean water and sanitation contributes to economic welfare because it is essential for health and creates environmental amenities. Behrman and Wolfe, 1987; Jalan and Ravallion, 2002, summaries that access to safe water have contributed significantly to reduce child mortality.



A measure of human development measurement used in this study is human development index (HDI) by United Nation Development Programme (UNDP). The HDI measures the average achievements of a country or a region in three basic dimensions of human development:

• A long and healthy life, as measured by life expectancy at birth.

• Knowledge, as measured by the adult literacy rate (with two-thirds weight), and means years schooling.

• A decent standard of living, as measured by adjusted real per capita expenditure (PPP rupiah).

Before the HDI is calculated, each of these dimensions needs an index. To calculate these dimension indices (the life expectancy, education and PPP indices), minimum and maximum values (goalposts) are chosen for each underlying indicator.


Infrastructure facilities can be understood largely as public infrastructural inputs from the supply side. However, depending on the nature of services delivered, infrastructure can be broadly divided into physical, social and financial categories - all economically desirable. Physical infrastructure consists of transport (railways, roadways, airways, and waterways), electricity, irrigation, telecommunication, and water supply. Despite their very direct impact on production through external economies, they are beneficial for “crowding in” of private investment (both domestic and foreign) in the concerned geographical region. In a “cumulative causation” fashion, physical infrastructure contributes to economic growth through lower transaction cost, and generates “multipliers” of investment, employment, output, income and ancillary development.

Meanwhile, social infrastructure improves the quality of life through enrichment of human resources in terms of education, health, housing, recreation facilities and the like. This is primarily responsible for higher concentration of better human resources in a region, and helps improve productivity of labor. Finally, financial infrastructure incorporating banking, postal and tax capacity of the concerned population represents the financial performance of the state. These three taken together represent the relative income generating capability of a state within a country or a country within a region.

The infrastructures that are covered in this study focuses on four basic types of infrastructure development in Java: electricity, clean water supply, road network, and school building. The share of households using electricity presents the infrastructure of electricity; the share of households with access to safe water presents the infrastructure of clean water supply; total road length per square kilometer represents road network; and the number of classroom in senior high school represents the school facilities.

  • Analytical Framework

Analytical framework that used in this study stated in Figure 4.1. This figure shows that infrastructure development has influence to human development. The research to investigate a relationship between infrastructure and human development can be implemented by two channels: direct channel and indirect channel. Indirect approach sees that human development is impact of infrastructure development. Infrastructure development could result an increase in human development. The final links are to real income/consumption of the poor and, consequently, poverty reduction and human development (Ali and Pernia, 2003).

The links can be illustrated with an example. For example, a road investment could result in an increase in agricultural productivity, non-farm employment and productivity, directly increasing the wages and employment of the people and, hence, their economic welfare. This is the (direct) income distribution effect. Moreover, higher productivity and expanded employment direct to higher economic growth, affecting the supply and prices of goods and, thus, the people's well-being. This is the (indirect) growth effect. On other hand, a road investment could also result in an ease access to education and health facilities. Similar links can arise from electricity, water supply and education facilities investment.

  • Model Specification

This study employs the panel data econometric approach. One of the advantages of using panel data a large number of data points will be available, which increases the degrees of freedom and reduce the collinearity among explanatory variables. It is improving the efficiency of econometric estimates. Using panel data also provides a means of resolving or minimizing the magnitude of a key econometric problem that frequently arises in empirical studies, namely, bias estimation caused by omitted variables (unobserved time invariant factors) that are correlated with explanatory variables.

Three kinds of estimation techniques are used in this paper. They are Ordinary Least Squares (OLS) model, Fixed Effects model and Random Effects models. An advantage of using panel data is the introduction of unobserved factors that affects the dependent variables in the model. Fixed effects estimator is appropriate if unobserved factors assumed have correlation with the explanatory variables in any period. However, time invariant variables are not allowed in fixed effects model. If we assume that the unobserved effects are uncorrelated with explanatory variable, random effects model is more appropriate.

Multiple Regressions used to look into how the infrastructure availability affects human development. In this study, we employ five regression models to examine the relationship between infrastructures availability and human development index. The first model analyzes the effect of infrastructures availability to human development index (HDI). The second model through the fifth model investigates the relationship between infrastructures and each components of HDI. The components of HDI are life expectancy, adult literacy rate, mean years of schooling and real per capita expenditure (PPP).

First, the following model estimates the relationship between infrastructures and HDI:



L_HDI: Logarithm of Human Development Index

L_ELECT: Logarithm of the share of households using electricity

L_ROAD: Logarithm of total road length per square kilometer

L_WATER: Logarithm of the share of households with access to safe water

L_EDUC: Logarithm of number of classroom in senior high school per total population age from 16 to 18 years old

The second through the fifth model analyze the relationship between infrastructure availability and each components of HDI. The models are:






L_LIFE: Logarithm of life expectancy

L_LITERACY: Logarithm of adult literacy rate

L_MYS: Logarithm of means years schooling

L_PPP: Logarithm of real per capita expenditure (PPP thousand rupiahs)

  • Data Source

The research will be carried out using secondary data that are gathered from some institutions. The data of human development index (HDI) is obtained from BPS-Statistics Indonesia, National Development Planning Agency (Bappenas), and United Nation Development Programme (UNDP). The data of the share of household using electricity and access to safe water are collected from BPS-Statistics Indonesia. The data of total length of road are gathered from Ministry of Public Works and Ministry of Transportation. The data of number classroom are obtained from Ministry of Education.

  • The Sample

The dataset in this study covers all regency or municipalities in island of Java, except Kepulauan Seribu regency since the data of road network in this regency is not available. Java consists of 6 provinces and 115 regencies/municipalities. The model of this study is constructed with panel data set for 114 regencies/municipalities in Java. Due to the availability of data, the data set ranges from 2002 to 2005.

All infrastructures variables have positive sign coefficient correlation due to human development index and each components of HDI. This means that infrastructures availability has a positive relation with human development index and each components of HDI. A better level of infrastructures availability makes a better HDI level. The variable of household with using electricity among the independent variables has highest correlation with dependent variables.



The hypothesis of this study is that infrastructures availability has a positive correlation with the human development. Thus, in the model, the coefficients of infrastructures are expected to be positive. After regression of the first model through the fifth model explained in the previous section, Hausman test performed for all models. The hausman test result reject the null hypothesis that unobserved individual effects are not correlated with the independent variables. In this case, the random effect estimation is not consistent, but fixed effect model consistent. A consistent result which shows fixed effect is preferable to random effect for all the models is obtained. Therefore, the interpretation will be based on the result of fixed effect only while OLS and random effect result are presented but not referred.

All variables have expected signs, and statistically significant. The outcome of each independent variable is explained as follow:


The first variable is the share of households using electricity denoted by ELECT. The result shows that this variable has positive sign and significant at 1% significance level. The coefficient of this variable, which is the elasticity, is less than one. Therefore, the percent increases in HDI corresponding to 1% increase in the share of households using electricity will be lower than 1%.

WATER, represents the share of households with access to safe water, which is defined as the percentage of households who consume tap water, packaged water, water pumps, protected wheels, or protected springs with distance to septic is more than 10 meters. This variable is significant at 1% significance level and has positive sign as expected. However, the magnitude of the coefficient is relatively small compared with other coefficients.

ROAD is the variable which presents the total road length per square kilometer. The regression result shows that it is positive and significant at 1% level. The magnitude of coefficient in fixed effect estimation is 0.046. Hence, an increasing 1% of total road length per square kilometer will corresponding to 0.046% increase in HDI.

Number of classroom in senior high school presents the infrastructure of education facilities. The system of vocational education in Indonesia is divided into 3 levels; elementary school, junior high school and senior high school. Children in elementary school are at age 7-12 and those in junior high school are at 13-15. Meanwhile the senior high school students are at age 16-18. In Indonesia compulsory basic education consists of nine years: six years of elementary school and three years of junior high school. Since the implementation of the system in 1994, many local governments give subsidies to this level education; elementary school and junior high school. Furthermore, the local government implements free school to this level. Therefore, the infrastructures of education facilities in this level already enough. Based on this fact, the infrastructure in the level of senior high school is only included in this study.

The parameter estimate of the number of classroom in senior high school per total population age from 16 to 18 years old has the expected sign and it is statistically significant related to human development index. This result shows that education facility is one of important factor to determining human development index. In addition, the result further implies that better school facilities can improve human development through human development index.

The estimated values for all the variables have expected signs. Moreover, all variables are statistically significant at 1% significance level. The coefficient of all variables, which are the elasticity, is relatively small.

We find that the coefficients are positive as expected and statistically significant at 1% significant level, except the variable of L_WATER and L_ROAD which significant at 5% significant level. In general, we verify that better infrastructures availability leads to positively on adult literacy rate.

we report the relationship between infrastructures and mean years schooling. According to the result, all the estimates are positive and significant. The variable of the share household using electricity has the largest coefficient. In the fixed effect estimation, its coefficient is 0.463, suggesting that 1% increase in the share of households using electricity is associated with 0.463% a rise in mean years schooling.

Therefore, all variables of infrastructure have positive correlation with real per capita expenditure (PPP). Variable L_ELECT has the highest correlation with the real per capita expenditure compare with others independent variables.



The aim of this study is to explain the relationship between infrastructure availability and human development index (HDI). For this purpose, we employ panel data that cover 114 regencies in Java from 2002 to 2005. We estimate the models using pooled ordinary least squares (OLS), fixed effects and random effects methods. First, we investigate the relationship between infrastructure availability and human development index in Java. We then examine the relationship between infrastructure availability and each component of HDI. The infrastructures we consider in the thesis are electricity, clean water supply, road network, and the number of classroom in senior high school in Java.

The results of the empirical analysis show that all variables of infrastructures availability do have significant positive correlations with the human development index in Java. An increase in infrastructures availability leads to an increase HDI as a whole and an increase in each component of HDI. The electricity network, which is represented by the share of households using electricity has the highest correlations with the HDI compared with others types of infrastructure.


We also find that infrastructures have positive correlations with social development indices (life expectancy at birth, literacy rate, and means years of schooling). Moreover, infrastructures have positive correlations with real per capita expenditure as well.

The main implication of the study is that infrastructures development needs more attention from the government. Furthermore, in the regional autonomy era, the local government needs to design a policy that can reinforce the infrastructure development. The infrastructure development is a catalyst to developing human resource.


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