On Grasses, Transects and Statistics or Science Is a Mess

As an environmental economist, I in a sense build my work upon the work of others. So, its foundations are provided mainly by ecology and related (sub-)disciplines such as conservation biology. However, while diving into some aspects of these disciplines and interacting with biologists who actually work in the field, I have realised that in many cases, reality is much more messy than a superficial look into the respective literature might suggest.

Advertisement

The Economic Value of a Statistical Life

A human life is worth $4 million to $9 million. At least according to an authoritative meta-analysis of economic studies that estimate the so-called “value of a statistical life”. This is one of the most controversial issues in modern economics, which has met with vast criticism. Particularly, it has been argued that one cannot attach a price-tag to the life of a human being. In what follows, I would like to argue that a) this criticism is largely based on a misconception of the estimates; b) economists can only blame themselves that the misconception actually arised; and c) the calculation of the value of a statistical life is not sensible, albeit for reasons different from the ethical ones that are commonly used to argue against it.

Resource Economics’s Most Problematic Assumption

Every theory or, to use the term famously coined by Thomas Kuhn, paradigm is based on a set of assumptions. Some assumptions are more, others less important for the overall theoretical system that is built upon them. This has to do with the ease with which they can (or cannot) be relaxed if shown not valid. It is, however, a truism that every model, theory or paradigm must be based on simplifying assumptions and that “closeness to reality” is seldom a relevant criterion for their evaluation (this latter statement must be, of course, qualified, which I will do below). Resource economics, i.e., the branch of economic theory that deals with the exploration, extraction and markets for (non-renewable) resources is no exception from this rule. One of my professors at the university used to present empirical findings regarding important assumptions of economic theory (such as the interest rate parity) by stating: “This is one of the few economic assumptions that stand up to reality.” The so-called Hotelling’s rule, one of the crucial models and assumptions of resource economics, is not one of those few.

3 Reasons Why a Post-Growth Society Is Not Within Reach

For reasons explained elsewhere (see, e.g., this post and that one), I am among those dreaming of a post-growth society. Of course, it is not entirely clear what a post-growth society would look like, and even less is known about the road there. Still, many people around the world–for instance those coming to Leipzig in September for the 4th International Degrowth Conference–agree that one of the greatest problems of the current societal-economic model is that it is heavily dependent on economic growth. And that at least the first steps towards it should be done soon, for the longer we wait the more we put our civilisation at danger of collapse of one kind or another. Nevertheless, there are numerous obstacles that hinder the urgently needed transition. In what follows, I would like to present three reasons why a post-growth society is not within reach, which are related to three aspects of human psychology: laziness, narratives and conservative inertia.

Historical Dynamics of Growth Critique

Since the beginning of modern economic theory’s history, which set off in the second half of the 18^th century, economic growth was one of the most central themes, creating controversies over and over again. The emergence of modern economics, identified oftentimes with the publication of An Inquiry Into the Nature and Causes of the Wealth of Nations by Adam Smith, coincided with the onset of an exceptional process in human history: until the late 18^th and early 19^th century, economic growth had been a temporary intermezzo at best, not a general pattern of socio-economic development of human societies. Then, around the time when Smith wrote his book, a new pattern gained momentum, economic growth becoming a matter of course. However, the perception of growth and its limits has evolved over time

Is Geo-Engineering a Viable Solution to Climate Change?

In a few months the Rio +20 conference will be held. This means that 20 years have gone since world leaders agreed on an unprecedentedly ambitious programme for global sustainability – including the first attempt to lay foundation for a global fight against climate change. During these 20 years, much has changed – unfortunately, mainly to the worse. We still find ourselves on the business-as-usual emissions trajectory – in other words, on collision course. Understandingly, this feeds calls for alternative approaches and solutions. One of them that gains ever more prominence is: geo-engineering.

What Is Uncertain in Climate Economics?

One of the central problems of a majority of economic integrated assessment models of climate change is that they mostly ignore or at best underplay all the uncertainty around the problem they try to analyse. Meanwhile, these models are mostly presented in calibrated form, i.e. including concrete values for different variables – just what a cost-benefit analysis is expected to do. Even if there are some confidence intervals specified, they are mostly rather crude and are a kind of sherry-picking of “meaningful” uncertainties. However, the dynamics of the climate itself and the consequences of his changing are profoundly uncertain and full of feedback mechanisms. In the following I would like to present and discuss some major sources of uncertainty in economic climate modelling, arguing that it is even deeper than in “just” climate modelling and that the consequences for standard approaches are profound.

Connecting Climate Science and Economics, Part 3

In this post I am going to give a summary of the third part of Climate Economics: The State of the Art by Frank Ackerman and Elizabeth Stanton of the Stockholm Environment Institute, concerning recent research in the economics of mitigation and adaptation. Part 1, with a discussion of newest results from the climate science, can be found here. Part 2, summarizing the report’s findings about the economics of climate change, here.

Connecting Climate Science and Economics, Part 2

In this post I am going to give a summary of the second part of Climate Economics: The State of the Art by Frank Ackerman and Elizabeth Stanton of the Stockholm Environment Institute, which deals with recent advances in the economics of climate change. Part 1, with a discussion of newest results from the climate science, can be found here. A summary of the above report’s overview of research in the economics of mitigation and adaptation will follow.

Connecting Climate Science and Economics, Part 1

2007 and 2006 marked two important milestones in the climate science and the economics of climate change, respectively. The former was the highly authoritative 4th Assessment Report (AR4) of the Intergovernmental Panel on Climate Change (IPCC), the latter the more controversial Stern Review. Since then, a lot changed in both fields, as the understanding of the climate dynamics improved, and, on the other hand, the debate triggered by the Stern Review brought a number of new, innovative approaches to the economics of climate change. An important issue was to restore the connection between climate science and economics that appears to have been lost some time in the late 90’s (on which I commented here). Now, a comprehensive review of the improvements in both fields has been prepared by Frank Ackerman and Elizabeth Stanton of the Stockholm Environment Institute (Climate Economics: The State of the Art). In the following I am going to summarize the report’s most important and interesting findings in the area of climate science. Overviews of advances in climate economics in general, and in the economics of mitigation and adaptation will follow.

GM Food: Another Case for the Economics of Uncertainty

Here you can find my updated standpoint toward genetically engineered crops.

The discussion about the use of genetically modified organisms in agriculture is one of the most heated environmental debates of the present. While some claim that Europe’s opposition to GM crops is “arrogant hypocrisy” and dooms Africa to hunger, others answer that the so-called green biotechnology only promotes superweeds, food insecurity and pesticides. It is indeed a very complicated subject where the treatment of uncertain hazards plays a significant role – similar to the nuclear power or climate change debates. I already once wrote a piece about the socio-economic aspects of GMO, but it was, admittedly, rather superficial. After having discussed uncertainty aspects more broadly and in the field of climate change in more recent entries, today I am going to try to give a broader, more balanced look on GMO with the focus on decision-making under uncertainty.

Climate Change and Uncertainty

Probably the main reason why we cannot agree on what to do about anthropogenic climate change is that we seem not to understand the inherent, deep uncertainty of the problem. A few days ago I wrote a more general post about the importance of uncertainty in decision-making, so I won’t repeat the argumentation here. I just would like to focus on the specific problem of uncertainty in climate policy, and present a possible approach.

Uncertainty and Decision-Making

How long can an ecosystem endure pressures without collapsing? How high is the climate sensitivity? What are the long-term consequences of growing and consuming GMO? How much renewable energy is feasible? How many species can get extinct without destabilizing an ecosystem? What is the (future expected) value of biodiversity? How long will oil, coal and uranium last? How large are the dangers from nuclear power? These are a few important questions that are highly uncertain. We probably cannot answer them exactly – at least not ex ante. So, how to deal with uncertainty when it comes to decision-making?