Written by Dan Brockington
A move to a green economy requires changes in the way we make things, move, allocate resources, produce energy and consume stuff. It requires changes to our planning of cities, trade policy and budget allocations. It requires governments to do things differently and promote policies that encourage citizens, businesses and civil society to behave differently and have different aspirations. And that, these days, also entails some sort of measurements to tell whether or not the new policies are having the desired effects and creating the sort of change that a green economy requires.
There is currently a great deal of attention paid to the measures by which we know about our societies and global change. This is partly because the 169 targets set for the 17 Sustainable Development Goals (SDGs) all have an agreed set of (230) indicators for which governments now have to collect data to monitor their progress towards achieving those goals. It is partly because there is renewed criticism and interest in the accuracy and reliability of many of the measures currently used to assess the state of the world (not least GDP).
In this context, my contribution to the greenmentality project takes on two tasks:
First, I will examine the construction, robustness and meanings of indicators used to evaluate performance of those aspects of the SDGs which are relevant to assessing progress towards a ‘Green Economy’. I will do this by exploring the construction of national level statistics. This will entail interviews with the government officials who work on these statistics.
Second, I will explore what changes have been taking place in different parts of rural Tanzania. We know that there have been dramatic changes in the country in the last 20-30 years. It is less clear to what extent the changes, which have happened would be compatible with moves towards a ‘green economy’ and to what extent the proposed indicators might be able to capture them.
The SDG indicators and the green economy are not identical but they are related. In the first place some proponents of a green economy hold that their vision is part of the ‘pathways towards the sustainable development goals’ (according to UNEP). In the second there are organisations promoting green growth, which assemble readily available indicators as part of their endeavours in irrigation activity to plot progress towards a green economy. Finally, some of the indicators are plainly relevant to the condition and state of any green economy. These include measures of CO2 production, use of fresh water, management of forests, and presence of forest cover and so on. This means that, as countries try to strengthen their statistical apparatus and surveillance capabilities, so they will be producing official ways of knowing about measures which will be taken as indicative of the strength (weakness) and presence (absence) of the green economy.
We know, however, that these measures can be flawed. Sometimes the indicators chosen are inappropriate (expanding protected areas for example can be inimical to local development). Extent of forest cover is not good for measuring the health of grassland systems. Alternatively, the problem can lie in the systems of state surveillance and monitoring, which are used to determine the condition of society and environment. The data used are sometimes inaccurate, flawed or misleading. It is an interesting and important exercise to consider what those weaknesses are, what misunderstandings they lead to and how well-known these problems are.
The purpose of the first part of this project therefore is to examine, through a study of the construction of SDG indicators, what view of the world is perpetrated by these statistics, and what errors can arise from them. This entails working with the people who produce and compile these statistics and with those who work in quality control and evaluation and those who use them. It entails exploring internal contradictions and complementaries within the data themselves. Outcomes may be that we shed doubt upon the value of these numbers, or, alternatively, that we need to move on from past criticisms about the invalidity of these statistics and recognize their fundamental reliability in core areas. This part of the project could entail some interesting collaborations with government officers who have been tasked with constructing strong and reliable statistical measures.
If the first part of the project is about accuracy, the second is about sensitivity. This element of the research project will build on current work in Tanzania, which is identifying places, which have seen transformations in their local economy (which may or may not have led to changes in local prosperity). This phase of the project explores in more detail the nature of and drivers of these changes and asks to what extent they are captured, and could be captured by current indicators of movement towards a green economy.
This will entail village level fieldwork interviewing key people whose lives and livelihoods have transformed or are meant to have been transformed by green economic measures. It will entail examining the reasons for and agents of change (networks, media, NGOs, government officers, companies selling new seeds etc.). It will entail exploring the local consequences of these transformations (inclusive growth, class formation etc.). It will entail considering on the basis of these data how ‘green’ these transformations have been. This part of the project will build on research projects, which are now completing and which have explored transformations in irrigation activity and in livelihood change and asset ownership in Tanzania.
Finally, having gleaned some understanding of the greenness of changes involved in place, which we know have been subject to forces of change, we can ask how sensitive current indicators of a green economy are to the changes we have observed. This part of the project could entail some interesting engagements with villagers’ own conceptions of the changes and transformations of their lives and what the consequences have been for them.