THEORETICAL BASIS 3.1 Introduction
3.2 Discussion of various theoretical foundations for this research
3.2.1 Economic schools of thought
‘Economic equilibrium’ is reached when supply and demand is matched (Wing, 2004;
Barzilai, 2016). Economic equilibrium models are simulation exercises that intertwine principles of equilibrium with empirical data to determine when demand and supply reaches equilibrium (Konnov, 2015; Wing, 2004). Wing (2004) further adds that economic equilibrium models are intended to analyse aggregate impacts of interventions. Key characteristics of traditional economic modelling include: being built from the top-down and is based on the foundation of fixed rules, homogenous components and market equilibrium (Tesfatsion, 2002). A key shortcoming of general equilibrium theory is the assumption that all agents make completely rational decisions (Wolpert and Tumer, 1999; Whittle et al., 2014). In addition, the equilibrium approach is made tractable to allow the analysis of its structure and implications (Arthur, 2006). Arthur (2006) further adds that the tractability arises out of many assumptions, such as components being homogenous and utilise all available information. The implication of imposing such limitation, according to LeBaron and Tesfatsion (2008), is that critical empirical factors are not intertwined. As a result, some of the robustness that actually takes place in reality is overlooked and not incorporated into the development of a comprehensive understanding of the aspect that is being researched.
Marchant and Snell (1997, pg. 3) states that microeconomics is “The branch of economics that deals with the behaviour of the individual producer and consumer, particularly as decisions are made with respect to the allocation of limited resources”. In essence, microeconomics is concerned with behavioural nuances of individuals and organisations use of resources (Dominique, 2017; Manuel, 2006).
According to Black et al. (1997), some of the key concepts of microeconomics include: opportunity cost which is the cost associated with a waivered substitute, demand function states that the demand of a good or service will increase as the price of the item decreases, supply function states that the quantity of a good supplied and its price is positively related to demand and equilibrium brings together the supply
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and demand functions and results in so-called optimum state when supply equals demand.
“Macroeconomic policy is primarily aimed at addressing the problems of unemployment, inflation and cyclical instability. Its overall aim is to create a business environment that is conducive to achieving and sustaining economic growth under conditions of certainty” (Black et al., 1997, pg. 289). This is broadly supported by Dacheux and Goujon (2011) and Mankiw (2010).
Microeconomics and macroeconomics address two very different aspects of an economy, with microeconomic activity giving rise to macroeconomic phenomenon.
The various branches of economics that could potentially be utilised as an underpinning theory for this research will now be discussed.
This research requires a theoretical underpinning that does not simplify a system, the economy, to better understand it and that does not inherently claim to be able to predict the future. The rationale of requiring a theoretical foundation that can deal with the complexity of a system is critical for bringing about an understanding of a system that is new, or in its early development stages and will also allow leverage points in the system to emerge, be identified or observed. The identification of these leverage points would be the first step in further developing and stimulating the system. Predictability in the chosen system is not important, given the path dependence characteristic of complex systems. It will be extremely onerous to even begin to try and predict what a likely outcome can be, however probable outcomes and scenarios might be possible. Levin (1998, pg. 433) defines path dependence as
“… a consequence of nonlinearity, which refers simply to the fact that the local rules of interaction change as the system evolves and develops”. In addition, the identified theory should be able to incorporate a plethora of aspects, not just economic agents, such as the actual environment and GHG emissions, impacts from climate change, such as flooding, drought and international practices and trends. Most importantly, all of the above needs to be able to be aggregated into an established theory that revolves around agents’ micro-interactions, which will give rise to emergent properties. The ability of a theory to lend itself to computer simulation, or be developed around computer simulation, is also vitally important even though this research intended to only develop a framework.
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Ecological economics assimilates aspects from natural and social science to solve environmental challenges while ensuring that sustainable development is achieved and viewing the economy as a part of a larger eco-system (Van den Bergh, 2001;
Sutton et al., 2016). A definition is provided by Spash and Schandl (2009, pg. 4)
“Ecological economics is concerned with environmental degradation, loss of species, damage to ecosystems structure and functioning, the basic limits on economic activity imposed by physical laws, the role of money in perverting environmental values and the means by which human society can operate in harmony with Nature”. Faber (2008) points out that ecological economics is still in its infancy and not yet well established, however this leaves a lot of scope for blue-sky thinking. The inability of economics, according to Faber (2008), to conceptualise nature and justice has given rise to ecological economics. Gerber and Gerber (2017) states that ecological economists are ardent supporters of commodification, when the opposite is likely the best possibility. Ecological economics is premised around quantifying the financial value of ecological services (Ricketts et al., 2004; McCauley, 2006; Costanza et al., 1997). The methodology of calculating the worth of ecological services has been strongly rebuked and the validity of calculated figures is questionable (Spangenberg and Settele, 2010; Norgaard, 2010). It is for this reason that ecological economics is not considered as an underpinning theory for this research.
The next possible theoretical underpinning is environmental economics, which is a field that focuses on the relationship between the physical environment and the economy while giving attention to the potential to utilise the physical environment for economic development and giving due consideration to impacts on the environmental by economic activity (Folmer and Johansson-Stenman, 2011; Sandmo, 2015;
Andersen, 2007). Beder (2011, pg. 145) highlights a structural problem with environmental economics, “Rather than being an interdisciplinary expansion of the discipline of economics, environmental economics has adopted the theory, assumptions and paradigms of neoclassical economics and applied them to incorporate environmental problems into economics analysis”. Spash (1999) supports this and states that environmental economics endeavours to make issues tractable to fit within the developed models. Amongst the differences between ecological economics and environmental economics, the latter ‘externalises’ the environmental problems to core economic interaction between people. This is different to ecological
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economics that sees the economic system as a sub-system with a larger environment.
Another key difference is that environmental economics takes an optimisation approach (Van den Bergh, 2001). Environmental economics is not appropriate for this research as it utilises equilibrium models and does not take into account the inherent complexity of which economies operate according to.
Diacon et al. (2013, pg. 28) describes behavioural economics as that which “… aims to join together and to adapt the basic principles of neoclassical economics with the realities imposed by the complex human nature”. In other words, behavioural economics seeks to study the individual nuances of financial decisions and the implications for the economy (Lunn, 2013; Whittle et al., 2014). A key tenet of behavioural economics is ‘bounded rationality’, which means decisions are limited because of imperfect information and time constraints, which is totally at odds with the ‘completely logical’ decisions in neo-classical economics (Whittle et al., 2014;
Never, 2014). Adam Smith did not subscribe to purely rational utility decision making but rather to a realistic conception of the fallibility of Homo sapiens (Ashraf et al., 2005; Viera, 2017). Behavioural economics does closely align with most of the prerequisites for the selection of a theoretical underpinning for this research, however it is not explicitly developed around the issues of complexity and dynamism and there are better suited theoretical options.
The fundamental tenets of evolutionary economics, unlike most other economic theories, cannot be agreed on by academics (Witt, 2008). However, according to Lambooy and Boschma (2001), “… evolutionary economics has two faces. The first one focuses on the longer term growth-paths, or trajectories, and the second one has an emphasis on human strategies in the struggle to survive, sometimes in adverse environments. This latter one emphasises the ways to improving the properties of the structure, or the conditions or production, in order to raise the productivity of the actors, by influencing the selection environment by well devised strategies of innovation. In general, evolutionary economics does not consider individual decision- making as such”. Evolutionary economics take into account the inherent heterogeneous characteristics and behaviour of economic agents (Santos, 2017;
Robert and Yoguel, 2016). The fundamentals of evolutionary economics is very consistent with what is required for this research, however there are other theoretical
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approaches that can better incorporate complexity and dynamic elements as its central pillars and as a result acts as a more appropriate choice.
Undoubtedly, the above mentioned economic schools of thought are rooted in a vast array of reputable theory, such as Diacon et al. (2013); Sutton et al. (2016) and Sandmo (2015). The contention of this research is that the highlighted schools of thought have been developed during simpler times, without the inherent dynamism and complexity that we are currently rooted in. This research also acknowledges that theories and schools of thought evolve over time, with new research. However, the inherent fundamentals of most established economic schools of thought are limited and made tractable to simplify reality (LeBaron and Tesfatsion, 2008). Currently, the world is experiencing multiple unprecedented challenges, all seeming to converge at the same time, this includes climate change and growing nationalist movements (World Economy Forum, 2017). When analysing a current economy, particularly a local green economy, that is made up of economic, environmental and social elements – it is vitally important that theoretical foundations that can incorporate an unprecedented level of data, complexity, dynamism and feedback loops are adopted (Dolores Sánchez-Fernández et al., 2014; Armiger, 2015).