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Environmental Quality in Indonesia: Disruption by Economic Agents

  • AZWARDI, Azwardi (Department of Economy, Faculty of Economy, Sriwijaya University) ;
  • SUKANTO, Sukanto (Department of Economy, Faculty of Economy, Sriwijaya University) ;
  • ADNAN, Nazeli (Department of Economy, Faculty of Economy, Sriwijaya University) ;
  • KURNIAWAN, Arika (Department of Economy, Faculty of Economy, Sriwijaya University)
  • Received : 2021.08.20
  • Accepted : 2021.12.30
  • Published : 2022.01.30

Abstract

Purpose: This study aims to determine the effect of economic agents, such as the amount of government expenditure on the environment, households, manufacturing industry, and shipping activities; on environmental degradation in Indonesia. Research design, data, and methodology: This study is conducted with 264 observations from panel data of 33 provinces during 2010-2017. Environmental degradation is measured by using the environmental quality index collected from Indonesian Ministry of Forestry and Indonesian Central Bureau of Statistics. Three testing models are used to test the panel data, namely Common Effect Model (CEM), Fixed Effect Model (FEM), and Random Effect Model (REM). Results: The research findings show that the amount of government expenditure on the environment, households, and shipping activities have a negative and significant effects on environmental degradation, while the number of manufacturing industry has positive and significant effect on environmental degradation. Unlike the previous studies, the result also shows that government expenditure on environmental has a positive and significant effect on environmental quality index. Conclusion: It can be concluded that even though Indonesian government spent a low budget on environment, their environmental regulation has succeeded both in reducing environmental degradation and increasing the environmental quality as indicated by Indonesian environmental quality index.

Keywords

1. Introduction

With a gross domestic product of 56 million rupiahs, Indonesia became one of the countries with highest economic growth in Southeast Asia in the first quarter of 2019. The economic growth projected by the increase in economic activity, such as production, consumption and distribution, leads to wellness of human-beings, giving positive impact to economic growth in Indonesia (World Bank, 2020). Economic growth also brings negative impacts along with those positive impacts. One of those negative impacts is the environmental degradation which in turn raises issues of sustainability (Wang & Chuang, 2011; He & Wang, 2012).

The global increase of good and services demand, which in turn leads to the increase of economic activities and production, causes environmental degradation (Rahman, 2020; Shahbaz, Khan, & Ali, 2017). The aspect of environmental degradation can be seen through the degradation and depletion in air, water, soil, and land quality (Tietenberg & Lewis, 2012). The rapid growth of population, economic, and the use of high technology combined with the depletion of natural resources result in high rate of pollution (Perman, Ma, & McGilvary, 2003). Human activities in economic, agriculture, industry and transportation have a significant impact on air and water pollution. The air and water pollution bring another important issues in sustainable economic development, increasing public anxiety about global warming. Output production activity and economic growth caused the increasing of environmental degradation (Chaudhry, Tanveer, & Naz, 2017). Jakarta, the capital city of Indonesia as well as the center of economic activity, is listed as one of the most polluted cities.

Not only causing the the air and water pollution, the human activities along with oher industrial and governmental activities, such as house building and infrastructure constructing, change the land use. The economic growth in line with the deforestation (Damania, Russ, & Wheler, 2018), causing the clearing of lots of forest and land to support the economic growth, which in turn threatening the amount of land that provide clear air. Indonesia suffered land loss 328.724 acres in 2019 as the result of the forest, resulting in 3 million people affected by air pollution. Environmental quality in Indonesia can be measured by the value of environmental quality index (Indonesia Ministry of Forestry). The index measures the quality of air, water and land cover, which means the lower environmental index presented the higher environmental degradation and the lower quality of environment. Indonesia’s environmental quality index in 2017 present the improvement but the value 66, 46 still indicated the low environmental quality.

Table 1: Environmental Quality Index (Aggregate and Disaggregate) in Indonesia 2016-2017

OTGHDI_2022_v12n1_17_t0001.png 이미지

Source: Forestry Ministry of Indonesia, 2017

The environmental degradation not only caused by the household, industry and government activities but also the policy regarding the environment. The government expenditure to help improving environmental quality also plays an important roles. Environmental degradation such as destruction of forests and soil and extinction of flora and fauna is a problem that must be taken into account by academics, economists and policy makers (Azam, Gigot, & Witte, 2016). Environmental degradation plays a significant role that affected the sustainable growth and development. Some studies namely He and Wang (2012); Suparmoko (2000); and Chen, Huang, and Lin (2019) have empirically explored the linkage of economic growth and air pollutant (emissions) using Kuznet curve hypothesis. In short, previous studies limited the linkage between emissions and economic growth, focusing on confirmed the validity of environmental Kuznet curve (EKC). The quantitative study about the economic activities (production, consumption and distribution) in Indonesia still has limited explanatory variables. This study focusing on how the economic activities variable linkage to the environmental degradation, using government expenditure on environment, number of household, number of manufacture industry, and shipping activities.

2. Literature Review

Most of the previous empirical studies explain the environmental degradation projected to the carbon emissions associated with the economic growth. The most popular study which prove the Environmetal Kuznet Curve, first proposed by Grossman and Krueger (1991), and Stern (2004). This study explains that economic growth causes the environmental degradation in early stages, and slowly decreased as economic growth increases. The other previous studies use the air pollutant (carbon emissions). He and Wang (2012), for example, develop the study using panel data to analyze the important factors that caused the U-turn in Environmental Kuznet Curve (EKC) for developing country. They analyze the important role of economic structure, development strategy and environmental regulation and their effects to the environmental quality and economic growth with the different variation in each stages of economic growth. The environmental degradation and economic growth are both studied in different approach.

Mohammed, Guo, and Haq (2019) finds that the coefficient of government expenditure has a significant positive effect on increased pollution. This finding is consistent with Bernauer and Koubi (2006); Lopez and Palacios (2010) which states that government expenditure reduces environmental quality. Lopez, Galinato, and Islam (2011) argued that government expenditure causes environmental degradation, unless it is shifted towards social and public goods that produce lower pollution. On the other hand, Halkos and Paizanos (2013) stated that government expenditure has no significant effect on carbon emissions. Halkos (2012) found direct effects of negative government expenditure on both SO2 emissions and CO2 per capita.

Ivanova, Stadler, and Steen-Oslen (2015) stated that household expenditure has a positive and very significant relationship to environmental impacts. The results of elasticity show that the strong and significant relationship between household expenditure and its impact on the environment is driven by an increasing demand for non primary consumer goods. Castellani, Beylot, and Sala (2019) through a process-based LCA approach and input-output tables identified food consumption as the main driver of direct emission impacts. Shivashankara and Siddegowda (2011) concluded that the main threat to household environmental conditions is population density, where household environmental problems are most severe in low income households.

Singh, Kumari, and Nandan (2016) states that the production of electronic waste has become a global environmental problem because certain electronic components of the product contain hazardous materials that threaten human health and the environment. Hoque, Mohiuddin, and Su (2018) stated that pollution carried out by industry has a big impact on human health and the natural environment resulting in socio-ecological problems and creating large social costs in developing countries. Harun, Taha, and Salaam (2013) showed that the goods production process has an impact on the environment, depending on the choice of materials and the design of a product, as the manufacture of a product is directly connected to the amount of carbon emitted from the use of electrical energy during the production process. Linder (2017) stated that port has an impact on emissions arising from activities or operations. The invention of the Vessel Speed Reduction (VSR) program resulted in significant emission reductions.

The relationship between economic development and environmental quality was studied by Bashir, Susetyo, and Suhel (2021), who found that a relationship between economic growth and CO2 emissions reveals in the environmental Kuznets curve in Indonesia. Therefore, policies are needed to be taken in order to limit the impact of urbanization by increasing awareness to maintain environmental quality and greater use of energy. In addition, energy conservation policies are needed in all sectors, especially the electricity, industry, and transportation sectors. Consistent with this, Yessekina and Urpekova (2015) discuss trends in world energy consumption in the transportation sector and emphasize their dependence on fuel. The article also describes the dynamics of energy use and CO2 emissions from transportation which found that a number of problems in the transport sector hinder the implementation of energy efficiency measures and measures to reduce CO2 emissions. A broader study related to economic development in terms of tourism and environmental degradation was analyzed by Lee and Syah (2018) who found that there is a long-term balance relationship between tourism revenue, environmental degradation, and economic growth in Indonesia. In that case, when tourism growth in the economy starts to materialize, it shows that environmental degradation is increasing inversely in the model, which in turn has a negative impact on the environment. In line with this (Islam, Ahmed, & Saifullah Huda, 2017) reveals that carbon emissions have a consistent impact on industrial production over time, whereas industrial production has a high impact on emissions in the short term that fades in the long run which is in line with the environmental hypothesis in Kuznets Curve (EKC). Carbon emissions increase with GDP per capita and at the same time, their low long-term impact on the industry index suggests there may be other sources of pollution as economic income increases. The same result was revealed by Hojjat (2014) which found that there was a potential impact of economic growth and development on environmental quality.

3. Empirical Methodology and Data

This study analyzes the economic condition, economic activity and environmental degradation in Indonesia using panel data of 33 provinces during 2010-2017 with the total 264 observations. Environmental degradation measured by the environmental quality index. The economic agents that affected environmental degradation are measured using the government expenditure for environment, number of household, number of manufacture industry, and shipping activities. To analyze the impact of environmental degradation and other regressors, we use following model:

\(\begin{aligned} \ln I K L H_{i t}=& \propto+\beta_{1} \ln P P L_{i t}+\beta_{2} \ln J R T_{i t} \\ &+\beta_{3} \ln J I_{i t}+\beta_{4} \ln A P_{i t}+e_{i t} \end{aligned}\)       (1)

where: ∝ is defined as a constant, while β1 , β2, β3,and β4 are the coefficients, and i and t are the provinces and 2010-2017. IKLH is environmental damage which is proxied by environmental quality index value. PPL is the government spending on the environment, the JRT is the total number of households, JI is proxied by the total number of industrial manufacturing industry, the AP is the total shipping activities, and eis is the error term.

The data used in this study were collected from Indonesian Ministry of Forestry and the Indonesian Central Bureau of Statistics. This research uses natural logarithmic data transformation for each variable used. The panel data are tested using three models, namely the common effect model (CEM), fixed effect model (FEM) and random effect model (REM) including the Chow test, the Hausman test and the Lagrange Multiplier test. Definition and measurement of variables, as well as initial hypotheses which are denoted by a positive or negative sign, can be seen in Table 2 as follows.

Table 2: Operational Definition of Variables, Measurement and Hypotheses

OTGHDI_2022_v12n1_17_t0002.png 이미지

Source: Badulescu & Simut, 2019; Ng, Zhang, & Afenyo, 2018; Yang, Lee, & Wang, 2018; Siddegowda, 2011; Barr, 2007.

Referring to previous research and previous theories in particular by Badulescu and Simut (2019), Ng, Zhang and Afenyo (2018), Yang, Lee, and Wang (2018) Siddegowda (2011), and Barr (2007) which empirically measures environmental degradation in terms of economic factors, namely environmental government expenditures, the number of households, the number of manufacturing industries, and shipping activities. Thus, the conceptual framework can be described in Figure 1 as follows:

OTGHDI_2022_v12n1_17_f0001.png 이미지

Figure 1: Research Model

The relationship between exogenous variables and Endogenous Variables produces perspective a hypothesis to measure environmental degradation from the economic agents. In detail, the hypothesis can be a description of the relationship between these variables. A specific summary of the list of hypotheses that refers to previous research can be explained in Table 3:

Table 3: Research Hypotheses

OTGHDI_2022_v12n1_17_t0004.png 이미지

4. Results and Discussion

This study aims to determine the effect of government expenditure in terms of the environment, the number of households, the number of industries and agricultural areas on the environmental quality index of 33 provinces in Indonesia during the 2010-2017 period. The estimation used the fixed effect model, the random effect model, and the method robust least square. Table 4 shows descriptively all the variables, both dependent and independent. Minimum, maximum, mean, and standard deviation values to be analyzed empirically.

Table 4: Descriptive Statistics

OTGHDI_2022_v12n1_17_t0003.png 이미지

Source: Proceed Data, 2020

The results of Chow, Hausman and LM tests show that the best model is the fixed effect model which is shown from the p-value of the Chow test which is smaller than the level of significance and the p-value of the Hausman test which is greater than the level of significance. Meanwhile, based on LM test, it shows p-value <0.05, which indicates that the best model based on LM testing is the random effect model. The conclusion of the results of the three tests is the fixed effect model which is chosen for the interpretation of the results (Table 5).

Table 5: Estimation Result of Fixed Effect Model and Random Effect Model

OTGHDI_2022_v12n1_17_t0005.png 이미지

Note: *, ** and *** denote a significance level of 10%, 5% and 1% respectively

Source: Data Processed, 2020

In estimation, the selected model is the fixed effect model based on the results of the Hausman and F tests. Table 5 shows that all independent variables can explain the variation in the dependent variable by 53.44 percent. Meanwhile, simultaneously it shows a high f-statistical value so it can be said that all variables have a significant effect simultaneously on the environmental quality index variable. All variables except shipping activities (AP) have a statistically significant effect, as shown in Table 5 as follows.

Using robust least square to estimate the consistency of the model, the results show that government expenditure from the environmental side and the number of households will reduce environmental quality. The estimation results indicate the increasing of these variables will reduce the quality of the environment in Indonesia as measured by the environmental quality index.

In Table 6, it can be seen that our findings on government expenditure on environmental quality contradict previous studies by He and Wang (2012) who found that government expenditure positively affects environmental quality. In fact, government budget that allocated for environmental functions in the 2018 is very small, namely 15.7 trillion rupiahs. Compared to the total central expenditure budget which reached 1,454.5 trillion rupiahs, the environmental function budget allocation is only 1.07 percent (Indonesian Ministry of Finance, 2018).

Table 6: Estimation Results of Robust Least Square

OTGHDI_2022_v12n1_17_t0006.png 이미지

Note: *, ** and *** denote a significance level of 10%, 5% and 1% respectively

Source: Data Processed, 2020

The number of households has a significant and negative effect on environmental quality in Indonesia. The number of households clearly has a very high relationship to environmental quality in an area. Research by Shivashankara and Siddegowda (2011) discussing environmental and household problems in developing countries found that the lack of facilities with poor living conditions causes the quality of the environment to deteriorate. This household behavior is very different in developed countries that concerned about the environment. Barr (2007) found that the United Kingdom has implemented waste recycling and almost all people care about the environment by reducing household waste, both garbage and household production.

According to Indonesian Environmental Statistics (2018) sources of air pollution can come from transportation, industry, burning waste, and household activities. This finding supports previous studies that found economic activities by households, especially household behavior, cause environmental degradation. The increasing number of industries can cause the decrease of environmental quality, but the stringent government regulation for industries, the less environmental damage that can occur. Indonesia has strict regulations that can force companies to pay attention or provide solutions for the environment which are regulated in Presidential Regulation Number 28 in 2008, concerning national industrial policies regarding the provision of facilities to industries that protect the environment.

Shipping activities have an impact on environmental degradation. Environmental degradation caused by these activities is water pollution and air pollution, especially carbon emissions (Lindstad & Eskeland, 2016). However, this result contradicts the study by Ng, Zhang, and Afenyo (2018), and Yang, Lee, and Wang (2018) which proved that port activity is a tool to mitigate environmental degradation, especially climate change and function in the transportation and economic system make it a key factor in sustainable development (Bjerkan & Seter, 2019). However, it contradicts with this study, which empirically proves that shipping activities in Indonesia will reduce the environmental quality index. It proves that Indonesian shipping activities are still categorized as traditional shipping which causes a decrease in environmental quality (Parmawati & Kurnianto, 2019). Environmental degradation caused by shipping can be mitigated if it meets 4 categories, namely (i) port management and planning, (ii) power and fuel, (iii) marine activities, and (iv) land activities (Bjerkan & Seter, 2019; Ng, Zhang, & Afenyo, 2018; Yang, Lee, & Wang, 2018).

5. Conclusion

This study determines the effect of government expenditure on environment, the number of households, the number of industries, and shipping activities on the environmental quality index in Indonesia using panel data regression with Robust Test approach. Empirically, it shows that government expenditure on environment, the number of households, and shipping activities have a negative and significant effect on environmental quality, while the number of industries has a positive and significant effect on environmental quality. The results of this study are generally contradict Badulescu and Simut (2019) who found that regulations related to government budgets will reduce pollution, in terms of improving health. The results of this study are consistent to Badulescu and Simut (2019) who said that government expenditure has a positive impact on environmental degradation or government expenditure reduces environmental quality. Indonesia is still categorized as having low environmental budget-related regulations (Ministry of Finance, 2018). The environmental quality is determined by household behavior, on which Indonesia is categorized as having low concern for the environment from the household side seen from the second-highest level of pollution after China. Indonesian regulations relating to household pollution are contained in the Government of Indonesia's Long-Term National Urban Development Plan 2015-2045, which obliges households to reduce plastic and marine debris by 70 percent by 2025 (World Bank, 2018). The role of port activities in improving the environment has not succeeded yet because it has not fulfilled 4 categories, namely (i) port management and planning, (ii) power and fuel, (iii) marine activities, and (iv) land activities.

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