Carbon dioxide emissions and the Swedish regions

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Core driving forces of CO₂ emissions

This chapter presents some of the key determinants of carbon dioxide emission that are suggested by theory and previous literature, including (i) GDP, (ii), Population, ,Urbanization (iv) Industry structure and (v) Human capital. The relationship between GDP and CO₂, in context of the EKC and the relationship between economic growth and environmental impact, is presented in more detail. Furthermore, the relevance of the suggested driving forces and their application to the empirical analysis in the case of Sweden and its regions is also discussed.

Economic growth

The projected effects of the global warming, such as the change of precipitation patterns and hence shifts in agriculture patterns, will alter the living conditions for a lot of people around the world, particularly in the developing countries (Sida, 2010). In addition to a need of a healthy environment, the need for economic growth in the developing countries is extremely important as well. To achieve sustainable development the theory argues that the three pillars, economic growth, society and the environment need to be combined and reinforce each other (Hacket, 2003). However, it is often argued to be a tradeoff between economic growth and environmental quality and the question whether a mutual achievement is actually possible has been widely debated in decades (Pasche, 2002).
Economic growth, represented by the development of income per capita, is signifying the level of affluence and is hence one of the factors identified as one of the core driving forces of environmental degradation (Stern et al, 1992). A number of studies have been made to try to understand the relationship between economic development and environmental degradation and the results differ (Cole et al, 1997, Shi 2003, Dietz and Rosa 1997). While some extreme arguments suggest that rapid economic growth is the solution to environmental problems, others argue that economic growth is the evil behind them. One thing is nevertheless agreed upon, income and the level of economic development is to some extent affecting the environment (Grossman and Krueger, 1995).
Several studies has been done within the framework of the Environmental Kuznets Curve hypothesis, suggesting an inverted U shaped relationship between income per capita and pollution, as an indicator of economic degradation, as displayed in figure 2 (Pasche, 2002).
The concept has been developed by Radetzki (1990) and Panayotou (1992) and is influenced by the income-inequality relationship recognized as the Kuznets Curve hypothesis (Kuznets, 1955). According to Panayotou (1992) the EKC suggest a non-monotonic relationship between GDP per capita and level of pollution, where the emissions subsequently diminishes after a certain level of income.
The explanations for a positive relationship between economic growth, GDP per capita, and emissions is rather straight forward. Industrialization and rapid economic growth increases the pressure on the environment in terms of heavy production and increased demand for energy and transportation. Furthermore, increased affluence is argued to increase the level of consumption and hence production and subsequent generate more waste and more emissions. These arguments hence suggest a monotonic relationship between GDP per capita and CO₂ emissions (Panayotou, 1997).
On the other hand, a more optimistic view exists and opponents argue that economic development in fact can reduce the impact on the environment and decrease emissions. This view is, as mentioned, supported in a number of EKC studies as a non-monotonic relationship has been identified. The reasoning behind this relationship originates from modernization theory, arguing at the other extreme that the best way to solve environmental problems is through increased economic growth. Modernization theory argues that production functions are limited before industrialism and carbon dioxide emissions are low, due to more simple technologies and agriculture as the major economic activity (Shandra et al, 2004). The economic development and the proposed relation to environmental degradation, here referred to the emissions of CO₂, is showed in figure 3. As countries grow, energy intensive production increases and the industrial process subsequently increase the emissions of carbon dioxide. Finally, as the industrialism matures the emissions and environmental degradation diminishes.
The major argument behind a non-monotonic relationship is based on a structural transformation and a change in how and what we produce. According to Pasche (2002) the reasons for the supporting evidence of an EKC is (i) the shift of economic activities to a less energy and pollution intensive production and (ii) the growing environmentally friendly technological progress. Underlying reasons is that countries in the mature phase are subject of a structural shift to a more service and information based economy and increasing innovation of more energy efficient technologies. Moreover, a further explanation for the relationship between GDP per capita and environmental degradation is linked to preferences. The reasoning is based on positive income elasticity, and a shift in demand, towards higher environmental quality, as a country gets wealthier (World Bank, 1992). An additional explanation is that countries at higher levels of income outsource heavy industry production and instead import energy intensive goods from less developed countries (Panayotou, 1992).
The proposition that economic growth eventually results in decreased emissions is confirmed for a number of environmental indicators, such as carbon monoxide and sulfur dioxide in a number of cross-national studies (Grossman & Krueger, 1995), (Seldon & Song, 1994). Results show that the relationship is non-proportional in contrast to the findings of the IPAT identity. As mentioned previously, this suggests that emission levels are not fixed along a countries development path. The threshold or turning point of emissions, at a certain level of income, differs in the studies and for different indicators of environmental degradation.
There are however many critics to the EKC, Cole et al (1997), Heenrink et al (2001) and Coondoo and Dinda (2002), have found evidence of a monotonic relationship between income and emission. Furthermore, the anticipated turning points are in many studies not realistic to be attainable. Another major critic of the EKC is that although it has been identified for a number of greenhouse gases, it tends to have a weak application to the most prominent greenhouse, CO₂. Carbon dioxide is one of the environmental indicators associated with an unattainable turning point (Panayotou, 1992). However, in the case of Sweden, an EKC is argued to exist and there is a trend of decreasing emission of carbon dioxide along with economic growth (Lundström, 2008).
Although the effect of economic growth and affluence diverges, the literature suggests that GDP to some extent determine and influence the level of environmental pollution in a country. Hence is GRP per capita regarded as a relevant variable to be included in the proceeding study investigating the factors determining CO₂ emissions in Swedish municipalities. The relationship is expected to be positive and an increase in income per capita will increase the emissions of CO₂. The relationship is furthermore expected to be approximately proportional, however is a non-monotonic relationship expected to prevail. In line with the EKC hypothesis, the level of emissions is expected to decline as the regions gets wealthier, indicated by a negative sign of GRP per capita². Carbon dioxide emissions are furthermore suggested to be explained by the level of population and the relationship is discussed in the next section

Population

The rationale behind the inclusion of population, as a variable affecting the amount of emissions of carbon dioxide in Swedish regions, are based on the old Malthusian view of population growth and most importantly because, it is widely acknowledged as one of the core driving forces of economic degradation. Furthermore, as population is one of the three key determinants in the original IPAT identity, it is generally included in studies investigating the underlying driving forces behind anthropogenic emissions (Dietz and Rosa, 1997).
The significance of population growth and its impact on the environment was early realized by the British economist Thomas Malthus who argued that environmental quality in terms of natural resources would be exhausted as the population grows (Malthus, 1768). This focus on shortages has according to Shandra et al (2004) been extended, in more modern neo-Malthusian theory, to argue that population dynamics is also contributing to economic degradation in general, including emissions of carbon dioxide as well.
A number of studies Dietz and Rosa (1997), Cropper and Griffiths (1994) and Cole and Neumayer (2004) has recognized a relationship between population and carbon dioxide emissions, as well as other indicators of environmental quality. All these studies found a monotonic relationship and the majority of them assume that the elasticity of emissions of CO₂ is unitary with respect to a change in population (York et al, 2003). However, some studies, for example Shi (2003) found that the emissions have increased more than proportionately to population growth the last decades. Shi (2003) studied the relationship for countries with different level of development and found specifically evidence of increased emissions due to population growth in less developed countries.
The explanations for a positive relationship between population and environmental degradation is summarized by Birdsall (1993) in two mechanisms, (i) the pure arithmetical effect on GHG’s emissions as more people demanding fossil fuel intensive energy and (ii) the impact of a growing population on deforestation. The first one simply argues that increased population, at a given level of per capita income, results in increased burning of fossil fuels due to the increased demand for energy, both in industry production, in households and for transportation purposes. The increased burning of fossil fuels in turn emits more carbon dioxide. The second mechanism, deforestation, refers to the complete removal of forests, without any replanting, and is one of the key contributors to the greenhouse effect. Birdsall (1993) argues that CO₂ emissions increase as the population grows due to the need of land for crops, houses and for the burning of wood. Deforestation is especially a serious problem in developing countries where poverty, lacking land security and poor government policies is more present.
On the other hand, as in most cases there are critics to the proposed relationship, and the effect of population on the amount of CO₂ emissions are in a few studies argued to be negative. Seldon and Song (1994) argues that population growth has a negative relation to environmental degradation in the sense that increased awareness, due to expansion over the landscape, leads to more pressure on environmental regulations. The suggested explanation for the positive implications of a growing population is based on findings that urbanization, by increased technological progress, will decrease the amount of emissions. This finding suggests population density as an additional variable and it is presented in more detail in the next section. Population is however expected to have a positive relationship to CO₂ in this study. An increase in population is anticipated to significantly increase the emissions and the relationship is furthermore expected to be approximately proportional.

Urbanization

As mentioned before, the original technology factor represented a residual of all other factors with environmental impact, other than population and affluence. However, attempts have been made in recent studies to incorporate the factor in the model. Suggested variables range from industry structure, climate and urbanization. The latter is discussed in this section as an additional variable affecting the CO₂ emissions in Swedish regions.
In addition to the increased level of population, urban migration is another demographic change with an observed accelerating trend worldwide and with a possible negative impact on CO₂ emissions. The original IPAT identity assumes identical contribution of the whole population regardless of their locations. It is however argued that population living in rural areas, with agriculture as the major economic activity, is less fuel intensive and emits a low quantity of CO₂. Whereas the population working in the industry sector in urban areas is argued to emit a much higher amount of carbon dioxide, due to a more fossil fuel intensive production (Auffhammer et al, 2004).
Although it is a rather recent approach, a number of studies have incorporated a variable representing urbanization, to determine the level of environmental degradation Auffhammer et al (2004), York et al (2003) and Martinez-Zarzoso (2008). It is in some studies represented in terms of population density but also percentage of urban population is a commonly used measurement. In addition, Cole and Neumayer (2004) investigate if the emissions are differing across age groups, due to different consumption patterns. Furthermore, Martinez-Zarzosa (2008) studies the relation between CO₂ emissions and urbanization by investigating the percentage of urban population in countries with different income levels. In this thesis urbanization is represented by population density. However, due to the small number of studies, specifically investigating the CO₂ emissions, as the environmental indicator, and population density as the measurement of urbanization, expectations and explanations is interpreted in the frame of urbanization in general

1 Introduction
2 The economic nature of environmental problems
2.1 Carbon dioxide emissions and the Swedish regions
3 The foundation of the STIRPAT model
4 Core driving forces of CO₂ emissions
4.1 Economic growth
4.2 Population
4.3 Urbanization
4.4 Economic structure
5 Empirical study
5.1 Methodology
5.2 Data and variable specification
5.3 Model specification
6 Empirical results and analysis
6.1 Descriptive statistics
6.2 Regression results
6.2.1 Regression results, CO₂ per capita
6.2.2 Regression results, EKC
6.3 Validity and limitations
6.4 Policy implications
7 Conclusion
8 References
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