Reaching conclusions: government and the green transition

If only? Technocracy International was a social movement formed in the 1930s to promote
a technocratic vision for North America (Burris 1993)

Even the most neoclassical economic textbooks recognise that environmental damage cannot be solved by market mechanisms alone. The consensus, however, ends there with different economic and political philosophies disagreeing about how governments can and should address environmental problems. Throughout this blog I've engaged with some of these debates by asking how national governments can promote a green transition and so in this final post, I'm going to draw my thoughts together.

While the EKC hypothesis suggests that governments should just go for growth to improve the environment, the theory’s shaky foundations undermine its conclusions. I believe that to reduce the environmental intensity of economic activity it’s necessary for environmental considerations to be integrated into every area of economic policy. Alongside evidence that shows governments can spur innovation and even lead a new green industrial revolution, policies also have the capacity to address corporate short-termism and thereby promote private sector green investment. Furthermore, social policies are essential in order to increase the resilience of economic systems and mitigate the social consequences of seemingly unavoidable climate change, particularly in developing countries where large poor rural populations are particularly vulnerable.

Governments are clearly integral to the process of green transition and therefore the tools and methods that are used to inform policy formulation are of significant importance. Because environmental economists and their rhetoric of ‘ecosystem services’ are particularly salient within environmental policy-making, this blog has examined some key concepts and developments within environmental economics to examine whether they are conducive to progressive policy developments. In the previous two posts I concluded that, while environmental valuation seems to be more hassle than it's worth, the development of environment-economy models is promising.  Aside from this, however, I’m skeptical that governments are willing to act on the scale demanded by the potential magnitude of future climate change. As the energy price debate has highlighted, politicians operating on 5-year election cycles seem prone to short-termism and more inclined to offer piecemeal populist policy changes than the radical overhaul that a green transition would require.

It’s pretty easy to criticise political myopia, but thinking of ways to address the problem is a lot trickier. Replacing democratic government with a technocratic dictatorship would potentially work but, I must admit, it isn’t the most appealing or feasible of solutions. A more pragmatic approach would be to promote cross-parliamentary agreements, such as current carbon budgets, that tie all parties to certain environmental policy commitments or targets. However, I fear that the sclerosis of Whitehall means this approach would just result in a sort of political constipation where an awful lot of effort generates distinctly underwhelming results. Furthermore, pledges are a considerable political liability (just ask Nick Clegg), and so I doubt that cross-party agreements with ambitious targets would be able to achieve sufficient parliamentary support. 

If governments could overcome their chronic shortsightedness, I believe it would be possible to significantly reduce the environmental impact of economic activity. If not, however, I worry that the current socio-economic system – already creaking under the strain of inequality and environmental degradation – will become untenable. 

And on that cheery note, I'm going to say goodbye and leave you with a bit of Marvin Gaye. I've really enjoyed exploring a range of subjects through this blog – I just hope its been an interesting read! 

                                           

Reaching conclusions: meritorious modelling

A physicist, a chemist and an economist are stranded on an island, with nothing to eat. A can of soup washes ashore. The physicist says, 'Let's smash the can open with a rock.' The chemist says, 'Let's build a fire and heat the can first.' The economist says, 'Let's assume we have a can-opener'.  

George Goodman (1981)

As the joke above parodies, economists have a tendency to simplify the problems they face by making assumptions and early in this blog I explained how the assumptions made during the construction of conventional economic models has led to a systematic neglect of environmental variables within economics. The recent development of environment-economy models, however, is addressing this significant oversight and throughout the course of this blog I've looked at the insights that such models can (and can’t), offer.

From delineating the impact of trade on endangered species to improving land-use decisions to estimating the cost of climate change, it’s clear that environment-economy models can be used to investigate a wide range of subjects. Despite the variety of these hybrid models, however, I want to conclude with two general pieces of advice.

1.   Always remain skeptical – environment-economy models, like all models, rely on a set of simplifying assumptions and, as exemplified by integrated assessment models, these assumptions can be highly problematic. Because of this, if you ever come across a report that uses env-econ models to generate estimates or projections, I would encourage you to flick straight to the technical appendix. Although the inevitable discussion of Cobb-Douglas production functions might not be particularly stimulating, this is where all the assumptions are hidden and so it’s a good way to check the integrity of any models that are used.

2.   Models are never enough –  Because models rely on simplification and abstraction, they are inherently fallible. This means that it’s always necessary to check the accuracy of a model’s results using real-world analysis. If used correctly, I believe that environment-economy models can be informative but it’s essential that modelling is used to complement, rather than replace, more ad hoc sources of evidence.

Although researchers should be more explicit about the assumptions that models are founded on, I think that environment-economy models can make valuable contributions. In particular, environmental-extended input-output models (like the one I discussed here) are important, as they show how production and consumption within a particular country has environmental impacts that extend globally. So overall, my outlook on environment-economy modelling is pretty positive – I just hope this esoteric sub-discipline gets the attention it deserves!

Reaching conclusions: the value of valuation

The maths might look pretty but does environmental valuation risk doing more harm than good?

Happy New Year everyone!

As 2014 gets underway, the beginning of second term is drawing closer and, as this is my final year, I’m afraid that means the end for this blog… at least for a while. Over the last few months I’ve touched on a wide range of issues and so I think a few concluding posts are necessary to draw things together.

One of the issues that I’ve examined during the course of this blog is environmental valuation. Although I initially defended valuation as a way of emphasising that environmental policy can achieve economic – as well as environmental – gains, I’ve become increasingly skeptical about its validity and utility. It is clear that some critical ecosystem characteristics – such as environmental resilience – are simply too complex to value and, therefore, environmental valuation will inevitably be a partial exercise. Furthermore, if individual preferences vary, rather than being intrinsic as is assumed in conventional economics, then environmental values that are derived using preferences are also liable to change.

Despite these problems with environmental valuation, an obvious counter-argument is that imperfect numbers are better than no numbers: even if the methods used to derive environmental values are flawed, the fact that the value of the environment is being recognised can only be a good thing. I’m not convinced by this. As long as methodological issues remain unresolved, it’s too easy for politicians to just dismiss environmental values as imprecise. But even if valuation methods could be improved, I find the rationale behind monetisation problematic.

Monetisation, is a way of standardising the magnitude of various changes in terms of a single unit (e.g. £s or $s), in order to facilitate ‘rational’ decision making. Obviously decisions need to be based on some sort of information but why is it necessary to present everything in terms of a single monetary unit? The only reason I can think of is political. Deciding between a series of qualitative scenarios would require politicians to make value judgments that would then have to be justified to the wider public. Allocating each scenario a quantitative value, however, avoids this by turning a subjective decision into an objective one: the best policy is simple that which results in the biggest positive number. This seems problematic because, as I have argued, the numbers that are ascribed to various impacts are far less objective than they may seem.

What is clear is that climate change will have complex impacts and therefore environmental policy decisions will inevitably involve trade-offs. Should renewable energy generation be promoted even if this increases energy prices?  Should carbon emission mitigation or infrastructure adaptation be prioritised? Should the problems of environmental change take precedence over other social issues such as the public health burden of an ageing population? Such tradeoffs will inevitably require politicians to make hard decisions and I believe that, rather than aiming for quantitative objectivity, politicians should be expected to explain and justify the value judgments underpinning their policy choices.

Because environmental valuation encourages political empiricism, I fear it risks turning environmental decision-makers into quants thereby undermining more deliberative approaches that, in my opinion, are far more suited to addressing the challenges posed by climate change.

Insights from a rare self-reflective economist

I find economics an annoyingly smug discipline. Despite the contestable nature of much core economic theory, any critical analysis is quickly dismissed as heterodox and filed away under an appropriate sub discipline by the Serious economists. Because of this, whenever an academic economist takes a jibe at economics as a discipline, chances are their research is going to be pretty interesting.

This is what drew my attention to ecological economist John Gowdy, who begins this short talk on preferences and valuation by admitting that many of the most exciting developments in contemporary economics – such as the recognition that humans are part of social systems – are rather obvious to non-economists. 

If you have a spare 15 minutes I can recommend watching the video but, if not, here’s a quick summary.

Following his initial statement, Gowdy looks at these recent developments in a bit more detail explaining that research in behavioural economics is challenging some of the fundamental assumptions of textbook microeconomics. Microeconomics is the study of decision making at the individual or firm level and, therefore, these assumptions are often referred to collectively as the model of ‘economic man’: an individual who is purely selfish, perfectly rational and makes decisions based on a set of intrinsic preferences. Gowdy highlights research that contradicts the last of these assumptions by arguing that preferences are not constant or based on what is ‘best’ for an individual, but are influenced by a range of factors such as the opinions of respected figures.

Because individual preferences are not, therefore, innate Gowdy argues that conventional environmental valuation techniques that rely on the model of economic man are too simplistic. It may be possible to use individual preferences to derive monetary values for unpriced goods and services, but if these preferences are liable to change there is no guarantee that the calculated value is consistent with the most socially desirable outcomes.

Observing collective decision-making in rural Nigeria, he suggests that a more appropriate approach to environmental valuation would involve deliberation rather than algebra. While I agree in principle, I’m skeptical about the practicality of such deliberative valuation. Extended discussion to reach consensus may be an appropriate way to solve problems in a small rural community, but it’s not clear to me how such an approach would work when trying to establish values that are used to guide national-level decision-making.

Throughout the course of this blog I’ve noticed that this tradeoff between accuracy and practicality is a frequent problem in environmental economics. As I wrote earlier, I agree that environmental valuation is desirable in principle, as a way to highlight the social and economic importance of the environment to policy makers. However, in light of the practical issues I’ve examined I now find myself questioning the use of environmental valuation and wondering whether it threatens to do more harm than good. I’m still mulling this over so make sure you check back sometime in 2014 for my concluding thoughts. 

Until then, hope you’re all enjoying the Christmas break and Happy New Year!

Thresholds: better safe than valued

The US Dust Bowl in the 1930s – recorded so evocatively by the music of Woody Guthrie – is another instance where 

 the erosion of natural resilience by human activity had catastrophic consequences. 

Avid readers may remember this earlier post in which I introduced the concept of environmental wealth and described the collapse of southern Mesopotamian civilisation to show the severe consequences that result when environmental resilience is not adequately valued. However, if resilience is to be incorporated into comprehensive wealth accounting, simply stating that environmental resilience is ‘valuable’ is not enough as accounting frameworks require that all inputs are allocated an exact monetary value. This interesting paper by Walker et al (2010) attempts to address this considerable practical challenge, estimating a monetary value of agricultural resilience in the Goulburn-Broken Catchment to variation in the water table.

Walker et al define ecological resilience using Holling’s (1973) seminal interpretation that conceptualises resilience as the capacity of a system to remain in a particular state or ‘regime' despite temporary shocks. Holling argued that ecological systems move into alternate ‘regimes’ when a critical point is crossed and therefore resilience is primarily determined by the proximity of a given system to such a threshold. Anderies et al’s analysis of the Goulburn-Broken Catchment in South East Australia (Anderies et al 2006) found that when the region’s water table rose to 2m below the surface, natural processes drew saline groundwater upwards resulting in land salinisation and, therefore, Walker et al take this 2m level as a natural threshold.

By examining historical data on rainfall variability in the basin, Walker et al are able to estimate the probability that the 2m threshold will be exceeded, given any level of the water table in the previous period. This allows the authors to establish the level of resilience for a particular groundwater depth. The authors then use agricultural land value figures from Whish-Wilson and Shafron (1997) to attach a monetary value to the saline and non-saline states that, in turn, allows monetary values to be calculated for each resilience level. Applying their methodology, Walker et al find that between 1991 and 2001 unusually dry climate conditions caused the water table to fall from 3m to 3.5m achieving an increase in resilience worth roughly $23 million, which is equivalent to about 7% of the region’s conventional wealth.

This may seem a bit technical and abstract, but Walker et al’s experimental research is important. It’s all very well saying that environmental services should be included in national accounts but for this to be possible, methods of valuing these services need to be developed. However, I think that Walker et al’s paper also highlights a fundamental problem with resilience valuation.

The author’s entire valuation exercise relies on the knowledge of a precise environmental threshold – in this case the 2m water table level – and therefore application of their valuation methodology in other contexts is only possible if significant environmental thresholds can be identified. Environmental complexity means many different types of interdependent environmental resilience exist at a range of scales. For example, the population resilience of freshwater species influences the resilience of a freshwater body to nutrient enrichment and vice versa. This means that natural thresholds are numerous and extremely hard to determine, suggesting that the perfect knowledge required for resilience valuation is highly unrealistic. 

Because the resilience of ecosystems is such a complex and contingent phenomenon, I believe that resilience valuation is unfeasible, rendering the concept of environmental resilience incompatible with comprehensive wealth accounting. Rather than using wealth indicators to inform policy intervention, an alternative way of avoiding critical thresholds would be to establish ‘safe minimum standard’ policy targets for a series of environmental parameters. Although this doesn’t overcome the problem of threshold identification entirely – as determining a ‘safe minimum standard’ inevitably requires some knowledge of what is ‘unsafe’ – exact knowledge of thresholds isn’t necessary.

Attaching monetary values to environmental resilience may offer the empirical precision so beloved by contemporary economists, but the complexities of the real world make such an approach impractical. When it comes to incorporating environmental resilience into policy decisions, therefore, I reckon it’s better to be safe than valued.

Looking glass modelling

'Mitigation tomorrow and mitigation yesterday - but never mitigation today'
Alice and the White Queen, John Tenniel, 1865.

Utility maximization, perfect competition, consumer rationality – when reading economic modelling literature, it doesn’t take long to come across some pretty absurd statements. Because of the complexity of real-world economic processes, simplification is recognised to be a fundamental tenet of economic modelling that is necessary in order to establish and examine specific economic relationships. Such simplification is achieved by making various assumptions when constructing the model and it is here that the absurdities start cropping up. It’s important to recognise that economic models shouldn’t be automatically dismissed because of these outlandish assumptions. In particular, I believe that abstract models are useful for producing benchmark results that can be compared with the real world. For example, examining model predictions that don’t hold in reality and asking why different outcomes are observed can highlight particularly important aspects of economic systems. However, economic models aren’t used solely for academic purposes and often inform policy decisions, which is when extreme assumptions start to be problematic.

Integrated assessment models (IAMs) are a particular type of environment-economy model that are often used when assessing the economic costs of climate change and mitigation policies[1]. Although specific models vary, the general framework combines an economic model of production with a simple general circulation model. Production is assumed to have a positive effect on ‘utility’ or wellbeing, as it enables consumption, but also incurs economic costs or damages by generating greenhouse gas emissions that cause atmospheric temperature increases. Mitigation is incorporated by assuming that decision makers can invest in either production or abatement technology, which has the effect of reducing the level of emissions per unit of output. Policy makers, therefore, face an inter-temporal problem: investing in abatement today is beneficial, as it causes future climate change costs to be avoided, but also undesirable, as it reduces present-day consumption and hence wellbeing. 

From this, it’s pretty clear that IAMs are gross simplifications of reality, but are these simplifications problematic? This excellent paper by Ackerman et al (2009) argues they are, outlining three issues with the IAM framework related to the practice of discounting, speculative valuation methods and the modelling of mitigation. Although the first two of these points are significant, I’m going to focus here on the third, as discounting and valuation are already highly debated topics and I believe Ackerman et al’s critique of mitigation modelling relates to topics I have discussed previously.

A popular use of IAMs is to determine an ‘optimal’ path of mitigation that achieves particular emission reduction targets while minimising the adverse wellbeing impacts of abatement investment and Ackerman et al observe that such modelling exercises often conclude the ‘optimal’ policy involves backloading investment. This observation is supported by a review of IAMs that found ‘perhaps the most surprising result is the consensus that… modest controls are generally optimal’ (Kelly and Kolstad 1999, pg 19), which directly contradicts statements made by the scientific community that argue immediate action against climate change is imperative.

Ackerman et al argue that this result occurs because the way technological change is modeled in IAMs is inadequate and causes the costs of mitigation to be overstated. While IAMs acknowledge that abatement technology will become increasingly efficient over time (meaning that a given amount of investment in abatement will achieve a greater reduction in emissions), this technological change is assumed to occur at a constant rate that can be determined from past data. As the authors state, this awesome simplification makes the optimality of backloading unsurprising:

‘Because climate change is a long term crisis, and predictable, inexorable technological change will make it easier and cheaper to reduce emissions in the future, it seems better to wait before addressing the problem of climate change’, (Ackerman et al 2009, pg 308).

Such a blithe treatment of efficiency overlooks a significant and rich literature on innovation that emphasises technological change is often path dependent and, as I have written about before, can be positively influenced by public policy. If politicians are presented with the result that the ‘optimal’ policy is to do nothing – or very little – now, the potential benefits of targeted public investment are unlikely to be realised.

Although there have been recent attempts to ‘endogenise’ technological progress, which means efficiency is no longer taken as a constant but is determined within the model, these progressive developments haven’t been applied to all IAMs. Furthermore, it is often very hard to establish what assumptions are being made in any particular model as these are often buried in technical annexes rather than explicitly stated in the main body of reports and research papers. As long as economists continue to use IAMs that treat technological change as given and discuss underlying assumptions evasively, I worry that climate policy will remain an unfulfilled promise reminiscent of the White Queen’s policy of ‘jam tomorrow’ that Alice found so frustrating in her adventures through the looking glass…

"The rule is, jam to-morrow and jam yesterday – but never jam to-day." 
"It must come sometimes to 'jam to-day'," Alice objected."No, it can't," said the Queen. "It's jam every other day: to-day isn't any other day, you know."  (Carroll 1897).

---

[1] Just to give you an idea of their significance, the whole Stern Review was based on the PAGE2002 IAM (Hope 2006, Dietz et al 2007)

Hungry for social policy

At the beginning of this blog I explained the concept of a ‘green transition’ referred to two distinct changes: reducing the environmental intensity of economic activity and improving the resilience of socio-economic systems to changes in climate. My previous posts have all addressed the former topic and so today I’m going to focus on the latter and examine how experiences of past climate change can inform present efforts to increase such societal resilience.

Records of the Great Famine that spread across Northern Europe during 1315-17 exemplify the severe social effects that changes in climate can cause. While historians have been aware of the catastrophic event for centuries, thanks to the harrowing accounts recorded by medieval chroniclers, more recent analyses have reconstructed climatic conditions during the period in order to examine the causes of the crisis. The tree-ring and GISP2 ice core analyses (undertaken by Lyons in Crawford (ed) 1989 (Ch. 2) and Dawson et al 2007 respectively), conclude that Northern Europe experienced significant increases in rainfall during 1315-16 that occurred alongside an increase in Northern Atlantic sea surface temperature. This supports numerous accounts recorded during the famine period that describe prolonged downpours from 1314-1316 that decimated crops and caused severe flooding (Jordan 1996). Although the rains subsided in 1317, the agricultural crisis persisted as widespread outbreaks of livestock murrain, caused by inundated pastures, continued to disrupt agricultural markets. Jordan argues that this caused the crisis period to continue for a further 5 years with food prices returning to pre-1315 levels only after 1322.

While the climatic cause of the famine is uncontested there is evidence that the severity of the crisis was increased by socio-economic factors. Crop failures caused substantial increases in agricultural market prices causing food to become unaffordable for large sectors of the population. Within this group it was the landless poor who experienced the most prolonged and severe impacts as, unable to undertake subsistence agriculture, they were dependent on agricultural markets and therefore endured food scarcity over the entire 1315-1322 period.

By analysing historical records, Kershaw (1973) has identified two factors that caused increases in this particularly vulnerable group during the famine period:

1. Increases in the unemployed landless – Outbreaks of livestock murrain and increased pressures on manorial finances caused large landowners to considerably reduce the number of people they employed resulting an increase in unemployment among landless individuals and, hence, an increase in the landless poor.

2. Reduction in peasant population – Peasants (individuals who undertook subsistence agriculture on small plots of land they owned) were vulnerable to climate variations as they didn’t maintain stores of produce. Following the initial crop failures, these individuals were forced to sell their smallholdings to wealthier households securing a temporary increase in income but removing their capacity to cultivate subsistence crops when the torrential rains ended in 1317. 

The factors highlighted by Kershaw indicate that economic responses can exacerbate the social effects of climate change implying that resilience to future climate change could be increased by policies that inhibit the repeat of these responses:

1. Improving climate-resilience of smallholders – It is clear that measures designed to increase the resilience of agricultural production to climate change are critical to the improvement of broader social resilience.  In particular, policies that seek to ensure that smallholder subsistence agriculturalists are prepared to withstand future climate change and climate variability could minimise a recurrence of the most severe social impacts observed during 1315-22. Reports such as CGIAR (2012) have identified which crops are most suited to increasing food security in poorer countries while also enhancing resilience to future climate and therefore policies that attempt to increase uptake of these crops among smallholders, such as seed subsidies, could be valuable methods of increasing social resilience.

2. Rural employment guarantees – The Great Famine also shows that resilience to climate variations could be improved by reducing the sensitivity of employment to climate change. In the present context, rural workforces dependent on agriculture are most vulnerable to climate variations and therefore, policies to guarantee rural employment could mitigate the social impact of harvest failure. Economist Jean Dreze is a prominent advocate of such policies and in this interview he explains his position and defends India’s rural employment guarantee scheme.

Although it’s necessary to treat precedents from the past with some caution, as their relevance is inevitably constrained by their historical context, an understanding of the factors that have increased vulnerability to climate in the past can be insightful. The experience of the Great Famine exemplifies how economic responses can exacerbate the social impacts of climate events and emphasises that economic policies will be essential in mitigating the severe social consequences threatened by a changing and increasingly variable climate.