The Role of Qualitative Approaches in Formulating Long-Term Low GHG Emissions Development Strategies
The Paris Agreement on climate change presents an invitation for countries to communicate midcentury long-term low greenhouse gas (GHG) emissions development strategies (hereafter, long-term strategies), which will contribute to limiting warming to well below 2°C compared to preindustrial levels. Such strategies highlight both the near-term investment decisions and the larger-scale transformation of economies and societies that will be required.
The drive for global action to mitigate GHGs that has evolved largely over the past three to four decades has resulted in the development of tools and approaches to provide policymakers and planners with the information required to direct their efforts. Many of these focus on generating quantitative information about how global, national, and subnational emissions may evolve in the future based on a projection from the current context, under different development scenarios and levels of implementation of mitigation policies and measures. This quantitative information plays an important role in prioritizing action and provides a common basis for engagement by decision- and policymakers with the relative and absolute magnitude of emission reduction possible in different sectors.
Significant confidence is often placed in quantitative models to provide a realistic view of how emissions trajectories may evolve over time. However, less consideration is given to the fact that the systems being modeled are complex and unlikely to follow the often-linear path predicted by the models. Quantitative models may thus be less effective at systematically capturing the impact on emissions trajectories of considerations such as lock-in to technologies, the impact of disruptive innovation, the influence of social factors, and the fact that implementation may not happen in line with what is assumed in traditional policy approaches.
While some attempt is made to address some of these limitations in quantitative models through uncertainty and scenario analysis, it is argued that qualitative approaches to generating, analyzing, and presenting information have an important complementary role to play in providing information to support long-term strategy development that isn’t yet fully realized. This is particularly true when looking toward the long term, where uncertainty grows exponentially.
What Are Qualitative Approaches?
In the context of developing long-term strategies, qualitative approaches are defined as a broad range of methodologies and approaches used to gather, analyze, and present information that can support decision-making and planning in a way not as readily made explicit in quantitative models. Examples of available qualitative approaches are presented in Figure 1.
Figure 1: Examples of Qualitative Approaches Potentially Applicable in Developing Long-Term Strategies
The Potential Value of Qualitative Approaches
Qualitative approaches can add value to the development of long-term strategies in a number of ways.
Various information gathering and analysis approaches allow for engagement with the potential impact of human values, behavior, and preferences on implementation of proposed strategies, and allow alternative strategies to be identified. For example, a policymaker might consider a policy option that drives replacement of wood with gas as a cooking fuel, whereas taste and cultural preference factors might result in continued use of traditional fuels, or alternatively communities may reject gas, as electricity is considered a more “affluent” energy carrier. A second example is rollout of public transport, which may be perceived as an inferior option to the aspiration of private car ownership, even though it provides more energy-efficient and lower-carbon transport services. Through providing feedback on the potential rate and extent of uptake of policy options, not only can alternative strategies be developed but education, engagement, and rollout programs can be designed and implemented to help support adoption of preferred policy options.
Scenario planning and visioning exercises are particularly useful in providing “out of the box” options, including those related to potential step changes to the current structure of the economy and society, which can be used to develop alternative long-term strategies. They are also helpful in identifying more flexible options that can be adapted in the light of uncertain future events, and can signal which of a number of alternative futures are unfolding, particularly over the longer term.
In the context of developing countries, the relative importance placed on climate action compared to other development priorities can be highlighted through various qualitative information-gathering and analysis approaches. A higher emissions alternative may be preferred if it is perceived to create more jobs than a lower emissions alternative, or if short-term financial gain outweighs long-term savings and/or financial benefit. At the institutional level, different government departments have different mandates that might lead them to give low emissions development lower priority in decision-making. Understanding individuals’ and institutions’ priorities can help inform design of coordinated action. Furthermore, identifying options with multiple benefits allows for the development of least-regret strategies.
Power dynamics play a significant, and often underestimated, role in determining how effectively a long-term strategy can be implemented. Entrenched vested financial interests, ownership structures and political agendas are examples of power dynamics. The entrenchment of ideological frames for how policy priorities such as unemployment, inequality and development are best addressed is another type of power dynamic. Qualitative information-gathering approaches can aid in understanding how these dynamics manifest in systems, information which help to assess the ability to implement proposed strategies.
Qualitative approaches enable identification and assessment of the cobenefits of implementing long-term strategies that may not have a readily quantified measurement scale or for which data may not be available to quantify the impacts. These may relate to factors such as improving quality of life, reducing local air pollution, increasing local health benefits (for example those relating to water availability or quality), and stimulating economic growth. Assessing and presenting the cobenefits associated with many long-term strategy options can help support the case for long-term strategy adoption and implementation.
Gathering information from experts responsible for generating quantitative data can increase understanding of how values impact the way the experts do their work. This includes considerations such as which models and analytical approaches are used, what system components get prioritized in the modeling, which input data are used, and how results are interpreted and presented. Even though such biases and perspectives are, in most cases, not conscious, explicitly understanding them helps policy and decision-makers better contextualize inputs obtained from the experts.
Finally, although ideally qualitative and quantitative approaches should be used in a complementary fashion in long-term strategy development, where limited capacity is available in countries to generate quantitative data, qualitative approaches can play a role in identifying and prioritizing opportunities.
Limitations of Qualitative Approaches
Despite the potential value such approaches can offer, a number of limitations contribute to their finding less widespread application in these and other contexts. First, the information gathered through qualitative approaches can be highly subjective. Factors impacting the outcomes of information-gathering exercises include which qualitative approaches are used, the way questions are framed, the choice of participants, participants’ mood on a particular day, and even the presence of other individuals in a focus group or workshop. Information-gathering processes need to be carefully planned to ensure that information gathered is fit-for-purpose. Failure to conduct effective planning can produce information that does not fulfil the desired need, or that is biased by the process itself. Typically, one does not get a second chance to collect missing information.
Qualitative approaches can be time- and resource-intensive to implement, and can suffer from stakeholder fatigue if they continue for too long. Finally, qualitative information is often more difficult to replicate and hence, from a classical science perspective, may be perceived as less defensible than quantitative information—even when taking into account some of the limitations of quantitative approaches presented in the introduction to this essay.
The Role of Decision Support Tools
A wide range of decision support tools is available to help structure decision-making and planning processes. Multi-criteria decision analysis (MCDA) refers to a suite of tools developed to structure processes that have multiple role players, each with different preferences, and require evaluations against multiple criteria. MCDA techniques are well suited to concurrently handling qualitative and quantitative information in a structured manner, and also provide the tools and approaches to analyze trade-offs based on stakeholder preferences and values (Belton and Stewart 2002). The latter may be conducted by assigning weights to different criteria.
The use of MCDA tools in decision making and planning has a strong precedent in discrete decisions and evaluation of policy options, although it has been less widely applied to long-term scenario planning. Some examples do, however, exist in application areas such as renewable energy planning (Abu Taha and Daim 2013) and development of climate adaptation strategies (Ramm et al. 2017). Scriecu et al. (2014) proposed a framework for application of MCDA in development-compatible climate policy planning, demonstrating the application of their framework with a selection of case studies. Cohen et al. (2018) discusses the use of MCDA in long-term climate mitigation policy and planning, highlighting some observations from their own work. Streimikiene and Balezentis (2013) discuss the use of multiobjective approaches to rank climate policies.
Despite limited experience with application in this context, the tools that fall under MCDA have the potential to provide valuable information that can be used to guide design and prioritization of policy options. They do, however, need to be applied with care and extensive planning to ensure that the information generated is transparent, robust, and useable.
Certain components in the MCDA toolbox can be readily applied and can add immediate value to any planning process. One worth mentioning in this context is the use of constructed scales to score performance of policy options on criteria for which a quantitative scale is not available. A frequently used approach to assessing a qualitative metric is that of asking stakeholders to rank policy alternatives on a scale of 1 to 5 or 1 to 10. If no context is provided for the scale, stakeholders can very quickly experience difficulty trying to score a number of different policy options. A constructed scale provides a context for the scoring, as illustrated in Figure 2, which shows a hypothetical constructed scale for ranking the impact of energy-sector policy options on the socioeconomic circumstances of a country’s population.
Figure 2: Example of a Constructed Scale Used in an Energy Policy Evaluation
This essay has identified a range of approaches to generation, analysis, and presentation of qualitative information that planners and policy makers responsible for development of long-term strategies can use to provide a richer, more ambitious, and more creative process than one that relies primarily on quantitative information. A wider range of perspectives can be taken onboard, factors that are not readily quantified can be included, and potential for step changes to the economy and society can be identified and understood.
Qualitative techniques are not widely used in long-term climate mitigation planning, with much of the focus remaining on refining quantitative models. There is value in exploring what complementary value qualitative approaches have to offer, particularly in the context of the long-range planning horizons required to develop long-term strategies.
Abu Taha, R., and T. Daim. 2013. “Multi-criteria Applications in Renewable Energy Analysis: A Literature Review. “ In Research and Technology Management in the Electricity Industry, edited by T. Daim, T. Oliver, and J. Kim, 17–30. London: Springer.
Belton, V., and T. Stewart. 2002. Multiple Criteria Decision Analysis: An Integrated Approach. Boston: Springer Science and Business Media.
Cohen, B., H. Blanco, N.K. Dubash, S. Dukkipati, R. Khosla, S. Scrieciu, T. Stewart, and M. Torres-Gunfaus. 2018. “Multi-criteria Decision Analysis in Policy-Making for Climate Mitigation and Development.” Climate and Development, doi: 10.1080/17565529.2018.1445612.
Ramm, T.D., C.J. White, A. Hin Cheong Chan, and C.S. Watson. 2017. “A Review of Methodologies Applied in Australian Practice to Evaluate Long-Term Coastal Adaptation Options.” Climate Risk Management 17: 35–51.
Scriecu, S., V. Belton, Z. Chalabi, R. Mechler, and D. Puig. 2014. “Advancing Methodological Thinking and Practice for Development-Compatible Climate Policy Planning.” Mitigation and Adaptation Strategies for Global Change 19(3): 261–88.
Streimikiene, D., and T. Balezentis. 2013. “Multi-objective Ranking of Climate Change Mitigation Policies and Measures in Lithuania.” Renewable and Sustainable Energy Reviews 18: 144–53.