Fish Imports, Tariffs and Conservation

A recent paper proposes that, post-Brexit, the UK should lower tariffs on imported fish to benefit consumers.  That may be a good idea, but the effect on fish stocks in the regions of origin should also be considered.

The Institute of Economic Affairs has published Plan A+: Creating a prosperous post-Brexit U.K. by Singham and Tylecote (1).  The paper is wide-ranging, but of particular interest from an environmental perspective is a short section on fish and fisheries (2).  It includes a proposal that tariffs on certain imported fish should be lowered once Brexit allows the UK to do so (3).  That set me thinking. Generally I favour free trade so that countries can gain from specialising in industries in which they have a comparative advantage, but sometimes short-term gains from trade must be weighed against long-term costs. When the traded good has been harvested from a renewable natural resource such as fish, there clearly is a possible long-term cost in that the quantity of fish imported could contribute to over-exploitation and depletion of the resource.

A little background.   Currently, fish imported into the UK from outside the EU are subject to the EU’s common customs tariff.  Imports of Pacific bluefin tuna, for example, carry a tariff of 22% (4).  Once the UK leaves the EU, and subject to the terms of any Brexit agreement, it will be free to set a lower tariff, or none at all.  Arguments regarding import tariffs typically focus on the protection they offer to domestic producers and the costs they impose on domestic consumers.  The UK fishing industry contributes £1.4 billion annually to the UK economy and employs some 24,000 people (5).  But tuna in recent years has been rare in UK waters (6).  Commercial fishing of tuna by UK fishers is virtually non-existent, and the same goes for some other fish types.

Singham and Tylecote’s proposal to lower tariffs on imported fish relates specifically to those types of fish that are consumed but rarely caught in the UK.  Reduced tariffs, they state, would benefit consumers but have little effect on the UK fishing industry.

Let’s examine these claims.  For any fish type, UK demand is only a small proportion of world demand.  Whether or not the UK levies a tariff therefore has only a small effect on the world price (7).  If a tariff is levied, then it raises the price to UK consumers by most of the amount of the tariff.  Conversely, starting from the UK’s current position, lowering the tariff will reduce prices by most of the amount of the tariff reduction.  That’s a clear benefit to UK consumers.

The claim that there would be little effect on the UK fishing industry is more problematic.  Singham and Tylecote’s point is that the fish types mainly caught by UK fishers – cod, haddock, mackerel, etc – are not those on which they advocate a lowering of tariffs.   But the relevance of this depends on consumer behaviour  in respect of fish purchases, which can usefully be described in terms of the cross-elasticity of demand, a measure of how a change in the price of one good affects demand for another.

Suppose cod and tuna can be taken as representative respectively of UK-caught and imported fish.  If the cross-elasticity of demand between cod and tuna were close to zero – that is, a change in the price of one would have very little effect on demand for the other – then Singham and Tylecote’s argument would be valid.  But it would fail if there were a large positive cross-elasticity of demand, implying that consumers regard cod and tuna as good substitutes. The reality is probably somewhere in between, a situation sometimes described by saying that the goods are weak substitutes. Cod is a white fish while tuna is an oily fish, an important distinction for consumers in terms of both taste and nutrition.  So far, then, Singham and Tylecote’s claim that there would be little effect on the UK fishing industry seems to have a degree of validity.

However, about one third by value of the UK catch consists of oily fish such as mackerel (8). The cross-elasticity of demand between tuna and mackerel seems likely to be fairly high.  If so it would further weaken Singham and Tylecote’s claim.

It might also have been suggested that the interests of millions of fish consumers should take precedence over those of the relatively small number of people employed in the UK fishing industry, but that is not an argument used by Singham and Tylecote.

The above analysis is entirely within a comparative static framework, which is fine so far as it goes.  When considering the economics of a natural resource at risk of depletion, however, it can never give the full picture.  It has no regard to the importance of conservation of fish stocks so as to ensure continuing catches for the benefit of future consumers. This prompts me to pose the following question:

If country A imports fish caught by country B within B’s waters (eg its Exclusive Economic Zone (EEZ)), should A’s policy on fish imports have regard to the conservation of B’s fish stocks?

Admittedly the scenario posited by the question is only one of several possibilities: imported fish might be caught (under agreed arrangements) in a third country’s EEZ, or in international waters.  It does I believe present the issue I want to consider in its simplest form.  Here are some arguments that might be adduced.

The sovereignty argument: No
Management of the fish stocks within B’s waters is entirely a matter for B.  Whether it chooses to conserve or to over-exploit is its own decision.  It is no business of A’s to interfere, and to do so could infringe B’s rights under the UN Convention on the Law of the Sea (9).

The laissez-faire argument: No
The fact that there is, and will probably continue to be, a market for exports of fish caught in B’s waters provides B with an incentive to conserve its fish stocks.  Although A has an interest in continuing to have the opportunity to import fish from B, there is no need for it to take any particular steps to that end.

The second-best argument: Yes
B may not be managing its fish stock in a sustainable manner, as evidenced by declining fish populations in its waters.  By limiting its fish imports from B, A can help to limit demand for B’s fish.  Other things being equal, reduced demand will reduce the quantity of fish that B’s fishers can profitably catch in its waters and so contribute to conservation of its fish stock for the benefit of future consumers, including those in country A.

The public choice argument: Yes
B’s government may understand the long-term benefits of conservation, but find it politically impracticable to override a fishing industry lobby defending its short-term interests.  A’s government, however, may find it relatively easy to limit its fish imports, imposing a small cost on each of a very large number of consumers.

All these arguments could have a degree of validity, subject to the detailed circumstances. But the applicability of the sovereignty argument is I suggest very limited indeed.  The UN Convention on Law of the Sea does indeed assign sovereign rights to a coastal country within its 200 nautical mile EEZ.  Those rights, however, are not the equivalent of the sovereignty a country exercises over its land territory: they do not amount to the right to do almost anything it likes. Article 56 specifies that, within its EEZ, a country has:

“sovereign rights  for the purpose of exploring and exploiting, conserving and managing the natural resources, whether living or non-living, of the waters …” (9)

Article 61 explictly forbids over-exploitation of living resources:

“The coastal state, taking into account the best scientific evidence available to it, shall ensure through proper conservation and management measures that the maintenance of the living resources in the exclusive economic zone is not endangered by over-exploitation.” (10)

If B – like most countries (11) – has ratified the Convention, then for A in its policy on fish imports to have regard to the conservation of B’s fish stocks could hardly be described as interference.  It would be helping B to fulfil its treaty obligations.  Even if B were not a party to the treaty, no one would suggest that for A to adopt a trade policy such as an import tariff would in itself amount to interference or an infringement of sovereignty. Any such claim would have to refer to the intentions underlying A’s policy.  There is a subtle difference between a country adopting a trade policy to advance its own interests, without particular regard to its effects on another country, and adopting perhaps the same policy with the intention of affecting another country in a specific way.  Trade sanctions would be an extreme case of the latter.  A policy intended to help conserve another country’s fish stocks would be, at worst, a very mild form of interference.

The laissez-faire argument would be a good one in circumstances in which B is effectively managing its fish stock in a sustainable manner, with regard to its long-term commercial interests.  However,  there are many fisheries for which this is not the case.  The FAO estimated that in 2013 31% of the world’s marine fish stocks were fished at a biologically unsustainable rate (12).

Where, for whatever reason, B is not managing its fish stock sustainably, the second-best argument becomes relevant.  For country A through its trade policy to try to contribute to conserving B’s fish stock is an inferior approach to effective management by B itself, but it may be better than nothing, especially if A’s policy can be coordinated with that of other importing countries.  A coordinated tariff could ensure a significant lowering of the world price of the fish, resulting in a worthwhile reduction in the quantity demanded and so make a material contribution to conservation of B’s fish stock.  It could also avoid the objection that a tariff adopted by one country alone would impose a cost on its consumers but do little towards conservation and therefore little to safeguard continuing imports of the fish for its consumers in future.

Where the reason B is not managing its fish stock sustainably relates to the lobbying power of its fish industry, the second-best argument may be complemented by the public choice argument.  What is envisaged here is far from the situation in which a powerful producer lobby achieving gains for itself at the expense of many dispersed consumers.  In the right circumstances, perhaps via coordination with other importing countries as above, the cost to consumers would be in return for a benefit to future consumers via conservation of B’s fish stock and continuing imports.

In conclusion, my main concern about Singham and Tylecote’s proposal to lower tariffs on certain imported fish is that it is presented without any consideration of the possible effects on fish stocks in the marine regions of origin.  Whether detailed information on the state of those fish stocks and the way in which they are managed would strengthen or weaken the case for their proposal is beyond the scope of this post.  But it would be unwise – an application of the precautionary principle – to lower tariffs without a careful examination of what the full effects might be.

Notes and references

  1. Singham S & Tylecote R (2018) Plan A+: Creating a prosperous post-Brexit U.K. , IEA Discussion Paper 95 https://iea.org.uk/publications/plan-a-creating-a-prosperous-post-brexit-uk/
  2. Singham & Tylecote, as 1 above, pp 64-67.
  3. Singham & Tylecote, as 1 above, p 66.
  4. European Commission Market Access Database http://madb.europa.eu/madb/euTariffs.htm?productCode=03023599&country=US
  5. Ares E, Rhodes C & Ward M (2017) The UK Fishing Industry House of Commons Library Debate Pack 2017/256
  6. Although it is beginning to become slightly more common. See https://phys.org/news/2018-04-experts-team-bluefin-tuna-uk.html
  7. Suranovic, S M International Trade Theory and Policy Trade 90-5 http://internationalecon.com/Trade/Tch90/T90-5.php
  8. UK National Statistics (2017) UK sea fisheries annual statistics report 2016 https://www.gov.uk/government/statistics/uk-sea-fisheries-annual-statistics-report-2016 See Chapter 3 Table 3.2.
  9. UN United Nations Convention on the Law of the Sea http://www.un.org/depts/los/convention_agreements/texts/unclos/unclos_e.pdf  p 40
  10. UN, as above, p 46
  11. Wikipedia UN Convention on the Law of the Sea – Parties https://en.wikipedia.org/wiki/United_Nations_Convention_on_the_Law_of_the_Sea#Parties
  12. FAO (Food and Agriculture Organisation of the United Nations) The State of World Fisheries and Aquaculture 2016  http://www.fao.org/3/a-i5555e.pdf  p 38.
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Housing, Countryside and Economic Welfare

If we can value ecosystem services, then the “housing v countryside” debate can be treated as an optimisation problem.

Cities often expand laterally to provide housing for an increasing population. This usually involves a loss of surrounding farmland, woodland, wetlands or other countryside, and consequent loss of the ecosystem services they used to provide.  Opinions on housing and the countryside often tend towards one of two extreme positions.  There is the view that land must always be made available to meet some conception of “housing need”, regardless of the resulting destruction of the countryside.  At the other extreme is the view that countryside around cities (Green Belt as some is designated in the UK) should be inviolable, implying that “urban sprawl” should always be prevented.

An Economic Model of Land Use In and Around a City

Economic analysis offers a way to articulate a third view.  To anyone with a little economic training the following formulation may seem quite natural, a straightforward application of the equimarginal principle of optimisation to the case of different land uses:

Overall welfare is maximised if housing extends up to, but not beyond, the point at which the marginal value of housing per unit of land equals the marginal value of an undeveloped unit of land.

This is represented in Diagram 1 below.  Line MVH shows the marginal value of housing, falling as housing area is increased. Line MVU shows the marginal value of undeveloped land, rising as housing area is increased and therefore less undeveloped land remains.  In the case shown, the area occupied by housing is H0, the red area represents the total economic value of housing, and the green area the total economic value of undeveloped land within the relevant area.  However, overall welfare is maximised where the respective marginal values are equal, that is, at the intersection of the marginal value lines, with housing area H*, and declines with distance from H* on either side.  With housing occupying area H0, therefore, welfare is less than it might have been by the amount represented by the blue triangle (though more than it would have been if H0 had been even further to the left of H*).

Welfare Effect of Urban-Rural Boundary

Now I do indeed think that this is a useful model to have in mind when considering policy towards housing development. Nevertheless, the assumptions on which it relies are considerable.  Awareness of those assumptions can help to ensure that we do not misapply the model.

I begin with some general remarks about assumptions in relation to economic models.  Some assumptions are just convenient simplifications, useful for presenting a model but readily replaced by more realistic descriptions in empirical work that pretends to any degree of accuracy.  Others are more essential to the model, indicating limitations in scope beyond which it would not work or be fundamentally altered. In the present case, the assumption of  linearity of the marginal value lines is just a convenient simplification.  The fact that these lines are monotonic (downward sloping in one case and upward sloping in the other) is more essential: if instead the lines were complex curves with both downward and upward sloping regions, then there could be multiple local optima at which the marginal values were equal, and welfare would not always be lower if H0 were further from the global optimum.

The spatial and temporal frameworks of the model require comment.  The assumption that all relevant land is either undeveloped or used for housing ignores other urban land uses (businesses, roads and railways, urban parks, etc) but is a convenient simplification.  The same can be said of the assumption that there exists a fixed area of “relevant land” in and around a city. What matters for the model is that it considers the respective marginal values over the range of areas of land relevant to a particular question. In terms of the diagram, moving A a little to the left or right will not change either the position of H* or the area of the blue triangle.  Similarly, it could be acceptable to truncate the diagram at the left, setting the origin at, say, 500 hectares rather than at zero area. This would change the position of H* only in the trivial sense that it would be closer to the new origin.  Its true position relative to the area indicated by the horizontal scale would be unaffected.

A measure of welfare should relate to a defined period.  It is convenient to take the period to be short (one year at most), since then in most circumstances we can ignore additions to the housing stock during the period.  This is a reasonable assumption because additions to housing in any period are usually only a very small proportion of total stock. Policy on housing development relates to the model in that the housing stock reflects policies in many past periods, which may or may not have changed the quantity or character of housing development from that which would have been delivered in a free market.  Thus the model relates welfare in a period to the outcome of policy and market forces in many previous periods.  What the model does not do, and it is a significant limitation, is draw out the full consequences of policy at any time for welfare extending over many periods.

Nor is the model designed to show the welfare effects of possible additional housing development.  That would require consideration of housing construction costs, which do not feature in the model (the assumption of no additions implies that all construction costs were incurred in past periods and are therefore sunk costs, irrelevant to welfare in the period of interest).  Any welfare comparisons inferred from the model are not comparisons before and after new development.  They are comparisons involving one or two hypothetical alternatives to the actual situation in the period, based on counterfactual assumptions about the quantities of housing development in past periods.

The Value of Land with Housing

Consider now the marginal value of housing line.  Because the horizontal axis measures land area, the line must be taken to mean the marginal value of housing per unit of land area.  A simple interpretation of the line starts from assumptions of uniform housing density and uniform utility to residents per home.  Given these assumptions, residents have no reason to prefer one home to another.  Ignoring externalities (which we will consider below), the marginal value of housing line would therefore be a pure price-quantity relation, its downward slope reflecting the greater quantity demanded of housing of uniform utility when the price of housing is lower.

Suppose that, with a view to greater realism, we drop the uniform utility assumption and take it instead that, although housing is of uniform density, homes differ in attributes such as quality and location which determine their utility to residents.  Then we must expect the price of housing in a particular location per unit of land to depend upon both its attributes and the total quantity of housing.  But if homes are not equivalent, on which land shall we take the marginal unit of housing to be?  For the purposes of economic welfare analysis, we should ignore geographical considerations, such as distance from the city centre, and take units of land in descending order of utility of their housing.  Thus the marginal unit of land with housing is that at which the homes offer the least utility.

Table 1 below shows how this would work for a very simple case with just three land units, identified in descending order of utility as L1, L2 and L3.  H is the number of units occupied by housing and, given uniform housing density, also measures the quantity of housing.  The locations have demand functions with the same downward slopes with respect to housing quantity, but different choke prices reflecting their different utility.  In the demand columns, an entry of “na” against an area indicates that it would have no housing at the relevant value of H.

Derivation of MV of Housing

The entries in red trace the marginal value of housing line: if for example H = 2, then the marginal unit is L2 for which demand is 11.  Note that, unlike in the case of uniform utility, this line is not a pure price-quantity relation.  Of the fall in marginal value of 7 from H = 2 to H = 3, for example, 2 is due to the higher quantity of housing and 5 to the lesser utility of L3 than L2.

Thus we can derive a downward-sloping marginal value of housing line without assuming uniform utility, at least within the area of existing housing.  To extend the line into the area of undeveloped land, we would need to make an assumption about the quality of the homes that might be built on that land.

Even within the area of existing housing there are further issues with the concept of the marginal value of housing line.  We have noted that location is an attribute that can affect the utility offered by a home.  Some characteristics associated with location, such as risk of subsidence or flooding, may be permanent.  Within a city, however, most of the utility associated with a home location relates to ease of access to and quality of shops, schools, transport links, employment opportunities, business and social networks, parks, and so on.  Importantly in this context, differences in housing quantity at the margin can be associated with differences in the locational attributes of intra-marginal homes.  In other words there can be positive or negative externalities associated with particular homes, that is, social benefits or costs not accruing to or borne by residents of those homes.  Comparing situations with larger and smaller numbers of residents, the former may for example have more or better shops, different social mixes in schools, more congestion on roads and public transport, and more networking opportunities. Such externalities imply that the utility of any one home is not fixed but may depend upon the quantity and location of other homes.  Consequently, an ordering of land units defined in terms of housing utility may itself not be fixed.

In most cities the density of housing is far from uniform (with the inevitable consequence that there is no simple relation between housing area and quantity of housing (whether measured as number of homes or as floor space).  One way to handle this within the model is to treat density as another characteristic of location.  Thus demand for housing on a unit of land on which there is a tower block containing many flats will be the sum of the demands for the individual flats.  Subject to quality, that housing will have a much higher value per unit of land than land with low-rise homes, and so feature earlier in the ordering of land units.

Another approach starts from the observation that, in some cities, most high-rise housing developments are towards the centre.  For such cities, it may be a reasonably good approximation to reality to treat the outer suburbs as being of uniform density.  One might then exploit the possibility noted above of truncating the model at an area chosen so as to exclude most high-rise developments.

Unfortunately these approaches, though consistent with our model, are unsuited to addressing the important practical issue of selecting the appropriate density for new housing developments.  As many have pointed out, building housing at fairly high densities, either on undeveloped land or by redevelopment of urban sites, can limit the extent to which cities impinge on their surrounding countryside.  In this context, we really need a more complex model which considers how welfare can be maximised when both the area of land used for housing and the density of housing on that land are considered variable.  That is beyond the scope of this post.

A further issue concerning the marginal value of housing line is the definition of the underlying concepts of demand and price.  Since the model relates to a period, demand must be taken to mean demand for the use of housing for the period by both tenants and owner-occupiers, sometimes termed demand for housing services. Tenant demand can be equated with willingness to pay a period’s rent for a home.  Owner-occupier demand for a period’s use of housing is a theoretical construct that would have to be inferred from market data, with suitable adjustments to exclude the effect of any speculative element in market values.  That has its complications, but without such a concept of housing demand it is hard to see how economic welfare analysis can be applied to housing.

The Value of Undeveloped Land

The economic value of the undeveloped land is the total value of the various ecosystem services it provides over the period.  It includes the market value of the agricultural products of farmland less the costs of inputs other than land.  Often more important, however, are the values of non-market services including water purification, drainage, support for biodiversity, carbon sequestration, and opportunities for outdoor recreation. These values would have to be estimated using suitable non-market environmental valuation techniques (1). Some of these techniques are contentious, and none can be expected to yield more than very approximate value estimates.

If we assume that the ecosystem services are uniform across the land, then we can interpret the marginal value of undeveloped land line as a pure value-quantity relation.  Whether such a line would be upward-sloping would depend on the type of land use.  If the undeveloped land were all used for agriculture and were all of similar quality for that use, then its value might be roughly proportional to its area. Agricultural products from farmland may be sold on markets supplied by many regions, and the small changes in total market supply that would result from changes in the amount of farmland around one city would not significantly affect prices.  Proportionality would also probably apply to woodland if its main value elements were timber sold on markets supplied by many sources, and carbon sequestration contributing through atmospheric mixing to mitigation of the global increase in atmospheric greenhouse gases.  The model will work with a horizontal marginal value line for undeveloped land, provided that the marginal value of housing line slopes down so that the lines meet only at one point.

For some other land uses, the marginal value will be greater if there is less undeveloped land.  This applies especially to recreation.  If there is much open-access countryside within easy reach of a city’s inhabitants, then a little more or less would be unlikely to be of much consequence, but if only a little remains, then its marginal value would probably be considerable.  Recreational land much further from the city could not be considered an adequate substitute, given the greater travel costs city residents would have to incur to enjoy it (2).  It could also apply to aspects of biodiversity.  An animal species usually needs to forage or hunt for food, and this may be impossible if the remaining area of otherwise suitable habitat is too small, leading to loss of the species from the locality.   For such land uses, the marginal value of undeveloped line might be expected to slope upwards with increasing use of land for housing.

In most circumstances, however, the mix of ecosystem services provided by a unit of land will differ between units.  Provisioning services such as food crops and timber may relate to clearly delineated subsets of the total undeveloped area.  The rate of carbon sequestration is likely to be highest in areas of woodland, lower in areas with fewer trees, and close to zero in some other areas.  Support for biodiversity, which embraces many different plants and animals requiring different habitats, will vary according to the characteristics of different locations, and in some cases (eg where agricultural pests are present) could include negative value elements.  The effectiveness of water purification and drainage services will vary with geological and soil characteristics.

This leads to a problem analogous to that encountered above in respect of housing.  Where units of undeveloped land differ in ecosystem services and therefore in value, which piece of land should be taken to be the marginal unit?  Again, the economic approach is to take units of undeveloped land in descending order of value, reading in this case from right to left in our diagram.  As with housing land, the slope of the marginal line may then reflect a combination of differences in ecosystem services between land units and quantity effects.

Does the Model Identify the Welfare Optimum?

Let’s now bring together our analyses of the two marginal value lines.  Given the ordering approach to the construction of the two marginal curves, we can identify the marginal unit of undeveloped land and, in terms of the housing land ordering, the first extra-marginal unit of undeveloped land suitable for housing.  Suppose, to keep things simple, that the undeveloped land in Diagram 1 has been divided into just three units, X, Y and Z (and take the sloping marginal value lines as approximate representations of the step functions which such large units would require).  We might then identify X as being both the marginal unit of undeveloped land and the first extra-marginal unit of undeveloped land suitable for housing.  Since the marginal value of unit X as land for housing is greater than its marginal value as undeveloped land, we might infer (as suggested by the blue triangle) that welfare would be higher if X had been developed for housing.

But this is a fallacy.  Our orderings for housing and for undeveloped land are based on different principles. To make even partial sense of our diagram in circumstances of non-uniformity, we must specify that units of land with housing (to the left of H0) have been ordered according to value as housing, while units of undeveloped land (to the right of H0) have been ordered according to value as undeveloped land.  We cannot assume that the units of undeveloped land have the same ordering according to value as housing.  Table 2 below shows two (of several) possible ways in which the respective orderings of the undeveloped land might relate to each other.  Note that both possibilities have the same three values in the “Value as housing” column: only the orders differ.

Possible Relations between MV Lines

Possibility 1 is the interpretation which Diagram 1 invites, with unit X having a higher value as housing.  But Possibility 2 is entirely plausible.  For example, unit Z might be attractive green space close to the edge of the city and have the highest value as undeveloped land because it receives many recreational visitors, but also because of its closeness to the city  have the highest value as housing.

Conclusion

The model clearly has many limitations.  I would justify the claim that it is nevertheless useful in the following ways.  Firstly, it offers a principled intermediate position on housing and the countryside as an alternative to the two extreme views outlined at the start of this post.  Even if it is challenging to estimate the marginal value lines for a particular city, the idea that welfare is maximised when the marginal values are equal is an important one whose recognition could raise the level of public debate on proposed housing development.  Secondly, the possibility of truncating the scope of the model – applying it to a relatively small area of land at the urban-rural fringe rather than to a whole city and a large area of surrounding countryside – could in some circumstances enable it to be applied in a relatively simple form because assumptions of uniformity would approximate to reality fairly well within that limited area.  Thirdly, it may be found that for some cities the difference in estimates of the marginal value of housing and undeveloped land is so large that – notwithstanding limitations of the model and the approximate nature of such estimates – a conclusion that welfare is far from being maximised would be hard to dispute.  That would not lead directly to a policy conclusion – whether or not to permit housing development on undeveloped land – but it would give a strong pointer suggesting a need for more detailed studies of particular sites near the urban-rural boundary.

Notes and References

  1. For an overview of such methods see Joint Nature Conservation Committee – Ecosystem Services Valuation http://jncc.defra.gov.uk/default.aspx?page=6383.   I have discussed some of these methods in previous posts: see especially here re the travel cost method and here re contingent valuation.
  2. Re the value of recreational land near to urban centres see Bateman I et al (2013) Bringing Ecosystem Services into Economic Decision-Making: Land Use in the United Kingdom Science Vol 341 Issue 6141 pp 45-50 (section headed National-Scale Implications)  http://science.sciencemag.org/content/341/6141/45
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Behavioural Economics and Environmental Valuation

The behaviour on which revealed preference valuation methods are based almost inevitably results from thought processes involving bounded rationality.  What does that imply for such methods?

The insights of behavioural economics have been applied to many sub-fields of economics, and environmental economics is quite properly no exception.  If actual human behaviour is often found to differ from that of homo economicus due to bounded rationality, cognitive biases, and pro-social behaviour, then it is hardly to be expected that such differences will not be encountered in human decision-making relating to the environment.  Indeed, the complexity of issues such as climate change and sustainability may suggest that  environmental decision-making is a habitat in which homo economicus is especially unlikely to be found.

Academic surveys of what has been termed ‘behavioural-environmental economics’ include Shogren & Taylor (2008) (1) and Croson & Treich (2014) (2).  There has also been considerable interest by the UK authorities including publications by DEFRA (3) and the Forestry Commission (4).  All of these consider, among other topics, the application of behavioural economics to the valuation of non-market environmental goods.  I am struck, however, by the fact that in each case their focus is primarily on stated preference valuation methods such as contingent valuation.  This is not to deny the relevance of behavioural economics to stated preference methods: issues concerning the cognitive biases of survey respondents and their implications for the framing of questions are an obvious link.  Here, however, I will explore the possible relevance of behavioural economics to two revealed preference valuation methods, the travel cost and the hedonic pricing methods.

The travel cost method estimates the direct use value of recreational sites such as parks from the travel costs incurred by their visitors.  Travel cost is generally taken to be the sum of out-of-pocket expenses such as petrol and the opportunity cost of the time taken.

Decisions on whether to visit a park are unlikely to be made in the manner of homo economicus.  There are likely to be many alternative ways in which a potential visitor might spend their time: visiting other parks at different distances and with different characteristics; enjoying various other leisure activities or entertainments; doing housework, gardening, DIY  or even paid work.  Depending upon the location of the park and of alternative activities, a potential visitor might have a choice of modes of travel and routes.  They might regard some journeys as contributing positively to their whole experience, and others simply as sources of disutility.  Factors they might consider include the weather forecast, the likely appearance and condition of the park at the time of year, and what is known of air quality in the park and elsewhere. Then there are considerations about journeys, such as the likelihood of traffic jams, and the reliability of public transport.  And all that is before the additional complexity arising when a trip has more than one purpose, or when it is a compromise between the differing preferences of group members travelling together.

Note also that the decision whether to visit a park is in most cases not worth thinking about in too much detail.  The worst that can happen, unless something very unfortunate happens, is that a limited time will be spent somewhat less enjoyably or productively than it might have been.

Almost inevitably, the decision whether or not to visit the park will involve bounded rationality.  Even a person who is quite capable of acting as homo economicus for a big decision such as accepting a job offer will be unlikely to take that trouble in deciding how to spend a little of their leisure time.  What most people will do is apply heuristics (mental short cuts) in reaching their decision.  That does not mean making an instant, thoughtless decision.  What it will often mean is focusing on some but not all of the relevant factors.  For example, a person might have regard to the weather but not consider possible travel difficulties; and might consider only a very few possible alternative activities.  And even for the factors they do consider, their thinking is unlikely to go very deep. If they consider the cost of travel by car, for example, they may well roughly estimate the cost of fuel, but have no regard to vehicle wear and tear and the effect of mileage on depreciation (5).

The hedonic pricing method is used to estimate the value of an environmental characteristic of a locality from the prices of its homes relative to those in other localities.  It involves analysing the relation between home prices and the many factors which influence them so as to isolate the effect of the characteristic of interest.

Suppose the method is used to estimate the (negative) value of air pollution in a neighbourhood due to industrial emissions, using house price data from the neighbourhood and from other neighbourhoods in which air pollution is insignificant.  Ideally for the method, the neighbourhoods would be the same in all respects other than the air pollution, but in practice this will never be the case.  Both within and between neighbourhoods, homes will differ in number and size of rooms, quality, size of garden and availability of parking.  Accessibility of  shops, schools and places of work, and characteristics of such key facilities, will differ.  Home locations will also differ in other environmental characteristics such as traffic noise, views, proximity to parks, other forms of pollution, and risks of extreme weather events or earthquakes.

A person deciding whether to buy a particular home therefore has many factors to consider.  Now it is true that buying a home is a big decision which most people will consider quite carefully.  Even so, the complexity of the decision is such that the rationality people bring to bear will probably still be bounded.  One reason is the time and effort that would be needed to  obtain all relevant information.  Take schools, a key issue for many families.  An online search may quickly yield information about a school’s examination results.  But it may be much harder to assess whether good results reflect the school’s teaching or the standards of its pupil intake, or the likelihood that a particular child will be able to obtain a place at that school.  And that information may be needed for numerous schools near different homes under consideration.  Then there are home characteristics.  Perhaps the homes under consideration differ in their heating systems and extent of insulation.  A lot of information might be needed to assess the consequences for comfort and running costs.  As for the air pollution itself, it may be difficult to extract reliable information on pollution levels from competing claims by interested parties quoting different measurements and statistics, and to assess the associated health risks.

Another reason for complexity is that moving home is a decision with long-term consequences.  The health risks from the pollution may accumulate with exposure over many years.  Most fundamentally, because moving home is costly, both financially and in terms of disruption to normal life, people will be extremely reluctant to move on a ‘trial’ basis, that is, with the thought that if the home or its neighbourhood proves unsatisfactory they can simply move again.  Most people buying a new home will expect to live in it for a number of years, and therefore have an interest not only in what the neighbourhood is now like, but also in how it may change in future.  But prediction is difficult: past trends may not continue, and promised improvements may not come to fruition.  And even if the future could be perfectly foreseen, there is the issue of discounting to obtain the net present value of the stream of future benefits and costs from a proposed move.

Given all this complexity, it is hardly to be expected that home buyers will take account of every piece of information relevant to their choice.  Even for those whose inclination is to do as much research as possible, the discrete nature of the housing market and consequent risk that properties on offer will be snapped up by others tends to force buyers who know roughly what they want to make quick decisions.

In summary, therefore, the behaviour from which the travel cost and hedonic methods draws conclusions about environmental values will almost always result from thought processes involving bounded rationality.  That conclusion seems solidly based.  But what it implies for revealed preference valuation is much less clear. The remainder of this post is accordingly much more tentative.

Where rationality is bounded, various cognitive biases may come into play.  It is not difficult, in discussions of behavioural economics, to find lists of such biases.  Sometimes, however, the argument does not go beyond the broad generalisation that, where such biases are present, conclusions based on an assumption of rational behaviour will be unreliable.  That I submit is an oversimplification.

Consider for example confirmation bias.  Suppose a couple are considering buying a home in a neighbourhood which some claim to suffer from significant air pollution.  She, we suppose, really likes the home, and dismisses the air pollution as a minor issue.  He, on the other hand, is less keen on the home, and regards the air pollution as a serious problem.  Looking at it from a neutral standpoint, we may suspect that their thoughts have both been affected by  confirmation bias.  But as this example illustrates, confirmation bias can bias different people in different ways.   There is no obvious reason why the result of a valuation should be biased just because some of the underlying behaviour was influenced by confirmation bias.  It is plausible that the effects of such bias on individual behaviour will tend to cancel out when a valuation is based on large sample data.

Are there, then, types of cognitive bias which can be expected to affect the results of revealed preference valuations because they are likely to influence the behaviour of many individuals in the same way, so that their effects will not cancel out in large samples.  I offer the following suggestions:

Publicity Bias: People considering alternative activities may be unduly influenced by advertising and publicity.  Since the attractions of non-market goods tend to be less publicised than commercial goods (because there is less incentive for their owners or providers to do so), people may visit free parks less and go to paid entertainments more than they would if they chose their activities fully rationally.

Loss Aversion: Most parks are permanent facilities, whereas many alternative activities such as shows and concerts are only available for a limited period.  People may decide to go to such activities rather than visit a park because they would perceive not doing so as a loss in the form of a missed opportunity, whereas they know that they can visit a park at any time.  The same could apply where a more permanent activity offers a discount for a fixed period, an option not available for facilities that are free anyway.

Visibility Bias: People assessing air pollution may be unduly influenced by what they can or cannot see.  Consequently they may underestimate the seriousness of invisible pollution in the form of small particulates.

Name Bias: People considering visiting a park which they do not know may be unduly influenced by whether it has an attractive-sounding name.  Among London parks and open spaces, for example, they might be more inclined to visit St James’s Park, Kensington Gardens or Primrose Hill than Wanstead Flats, Figges Marsh or Wormwood Scrubs.  For home-buyers, this form of bias could be prompted by names of neighbourhoods.

Salience Bias: For people considering buying a home in a neighbourhood without significant air pollution, the presence or absence of such pollution may not be salient.  They may therefore make no allowance in their thinking for the benefits of clean air.

Present Bias: People may underestimate long-term risks relative to present benefits.  They might for example be attracted to a coastal home offering fine views and nearby beaches, but give little weight to evidence of gradually increasing risk from coastal erosion or rising sea-level, or to the likelihood that such physical risks will affect the future sale value of the home long before they result in actual damage.

Probability Neglect: People may ignore real but low risks such as an earthquake in the vicinity of a possible new home or a murder in a park.  They may also greatly overestimate such risks if similar events have featured prominently in recent news, even if the events are far away.  At any one time, either of these effects may predominate.

Taking these forms of bias together, it seems quite possible that the result of a revealed preference valuation could be significantly different from what it would have been if all the behaviour on which it was based had been fully rational (I pass over the pertinent but difficult issue of how the latter might be estimated).

This leads to a fundamental question:

Suppose a revealed preference method estimates the value of an environmental good (or bad), based on actual behaviour, as V, but would have estimated the value,  had all the relevant behaviour been fully rational, as V*.  Should we say that:

1. A revealed preference value estimate based on behaviour that is not fully rational but influenced in a consistent manner by cognitive biases must itself be biased. The true value is V*.  If V* cannot be estimated directly, then an attempt should at least be made to adjust V for the most obvious forms of bias relevant to the circumstances.   OR

2. Value as estimated by a revealed preference method is value to actual people. It isn’t relevant how those people decide on their behaviour.  Consumer sovereignty should apply in valuing non-market goods, just as (in a market economy) it applies to market goods.  The true value is V.

I don’t have a clear answer to this question.  But it is clearly important.  If the answer is 1, then any revealed preference valuation study needs to include a consideration of the effects of cognitive biases such as those listed above, and estimated adjustments for any significant effects.  If the answer is 2, however, we can ignore such cognitive biases even when we know them to be present, and simply conduct revealed preference studies in the way in which they have always been done.

What can be said is that the question is one illustration of a broader debate in welfare economics as to how welfare should be defined and measured in situations where there are indications that people’s behaviour may not be fully rational.  I use the word indications advisedly as there is a line of argument that, notwithstanding appearances to the contrary, all behaviour is fully rational or at least can plausibly be rationalised, albeit sometimes the implied preferences (utility functions) are unusual.  To me that seems unconvincing, for the reasons set out at length above.

Some have drawn a distinction between decision utility, the preferences that would be implied by an assumption of rationality, and true utility, the preferences that really would maximise a person’s well-being (6).  On that basis one can define alternative concepts of welfare or value.  It could then be argued that answers 1 and 2 above simply reflect those two different value concepts.  But such definition-making does not address what is clearly a substantive issue.  If for example a revealed preference value estimate is needed to determine the value at which a non-market environmental good should be included in a cost-benefit analysis of a proposed project, it will not do just to offer two numbers reflecting two different value concepts.  We need to know which is the appropriate one to use.

There is surely much more to be said on this topic?

 

Notes and References

  1. Shogren J F & Taylor L O (2008) On Behavioral-Environmental Economics Review of Environmental Economics and Policy 2(1) pp 26-44
  2. Croson R & Treich N (2014) Behavioral Environmental Economics: Promises and Challenges http://www2.toulouse.inra.fr/lerna/treich/BEE.pdf
  3. Department for Environment, Food & Rural Affairs (DEFRA) (2013) Behavioural Economics in DEFRA: Applying Theory to Policy https://www.gov.uk/government/uploads/system/uploads/attachment_data/file/223835/pb13986-behavioural-economics-defra.pdf
  4. Moseley D & Valatin G (2013) Insights from Behavioural Economics for Ecosystem Services Valuation and Sustainability Forestry Commission  https://www.forestry.gov.uk/PDF/FCRP022.pdf/$FILE/FCRP022.pdf
  5. Re the effect of mileage on depreciation see this AA site: http://www.theaa.com/car-buying/depreciation
  6. See for example Bernheim B D & Rangel A (2009) Beyond Revealed Preference: Choice-Theoretic Foundations for Behavioral Welfare Economics Quarterly Journal of Economics Feb 2009 p 52
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Explaining Environmental Policy Failure

A proposed new approach to environmental policy fails to convince.

Why Environmental Policies Fail by Jan Laitos is a curious book (1). Its subject is certainly important, and it’s hard to disagree strongly with the bleak picture it presents of risks to the environmental conditions needed for humans to live safely  (pp 59-76).  It contains interesting discussions of particular situations and policy failures.  What makes it curious is the abstract framework within which its proposals are presented, based on what it describes as “fundamental laws of nature” (p 171).

The author is a professor of environmental and natural resources law, and it’s interesting  to see how he pigeonholes what economists regard as two key policies to address environmental issues: Pigovian taxes and marketable permits.  Grouped within the heading of economic policies, these form just one of ten items on his list of current environmental policy strategies (pp 139-140 & 145).  Among the others are some which are commonly discussed by economists as alternatives to market-based instruments, eg regulations (command and control), and adjustments to property rights.  Some others are new to me: legal rights for nature (pp 153-9) and human-nature linkages (pp 160-3).

Laitos’ comments on all these policy strategies are generally critical.  In the case of economic policies, his main criticism is that they are based on assumptions that human behaviour is deliberate, rational and utility-optimising. He refers to evidence that people often behave quite differently (pp 32-3, 145-8). But a crucial question, which he does not consider, is how much difference this makes.  Consider a case where emissions of pollutant are initially at a rate of 100 units per day.  Suppose that, applied to relevant data, conventional economic analysis predicts that a proposed tax would reduce the rate to 50 per day.  Given a more realistic view of behaviour, we would not expect the outcome of the tax to be exactly 50 per day.  But will it be, for example, 55 per day or 90 per day?  The former would suggest that the theory works fairly well in this situation (perhaps because departures from rationality largely offset each other in aggregate); the latter that it does not.

Environmental Policy Failure – an Orthodox Account

Laitos’ overall assessment, as the book’s title suggests, is that environmental policies to date have been unsuccessful.  His argument is essentially that severe environmental degradation has occurred despite the presence of many environmental policies (p 61).  I will not dwell on the objection that some policies, for example the Montreal Protocol on Substances that Deplete the Ozone Layer, have been fairly successful (2).  Of more importance here is that he shows little interest in distinguishing types of failure.  The following is I suggest a useful classification:

Type 1 Failure: Environmental policies which fail to achieve their objectives.

Type 2 Failure: Environmental policies which produce undesirable environmental side-effects.

Type 3 Failure: Environmental policies for which the objectives might be considered insufficiently ambitious.

All three types occur (some policies may exhibit failure of more than one type).  As examples I offer the following:

Example of Type 1 Failure:  The US Lead and Copper Rule, intended to minimise lead and copper levels in drinking water (3), which did not prevent lead contamination in Flint, Michigan (4).

Example of Type 2 Failure:  Germany closed eight of its seventeen nuclear reactors in 2011 following the Fukushima disaster in Japan (5).  This significantly reduced its exposure to the environmental and safety risks of nuclear power.  But to ensure adequate electricity supply, Germany has since increased production of brown coal which is an even worse source of air pollution and greenhouse gas emissions than ordinary coal (6).

Example of Type 3 Failure: Australia’s greenhouse gas emissions target for the Kyoto Protocol’s first commitment period was an increase of no more than 8% on its baseline level (7).

The reasons for these different types of failure are likely to be quite different.  Type 1 failures are often due to poor technical advice to policy-makers and/or ineffective administration and enforcement (including regulatory capture by rent-seeking groups).  Type 3 failures tend to result from political compromises between differing interest groups, or between short and long term interests.  Type 2 failures may occur for either of these reasons, or because a particular environmental problem happens to be especially salient when a policy is adopted.  We have, therefore, the outline of an orthodox answer to the question implicit in the book’s title.

Environmental Policy Failure – Laitos’ Account

Laitos, however, largely neglects these sorts of explanation. Instead, he presents a framework of thought, the key elements of which can be summarised as follows (8):

Nature as a Complex Adaptive System, not necessarily in equilibrium, characterised by co-evolution of living organisms and their abiotic surroundings, and often achieving resilience between stability and instability in the state sometimes termed ‘the edge of chaos’ (pp 95-100).  This leads to the idea that environmental policy should not aim to conserve or restore a state of nature, because there never was such a stable baseline state (p 100).

The Requirement of Symmetry as fundamental to the laws of nature, in physics and in biology (p 174).  The following three consequences of symmetry are of particular relevance to environmental policy.

The Law of Conservation according to which certain quantities cannot be created or destroyed, an example being the First Law of Thermodynamics  (p 177).  This leads to the conclusion that, because the natural environment is a complex adaptive system, environmental policy should be simple, and complex policies are likely to fail (p 179).

The Equivalence Principle according to which seemingly different concepts are actually the same, an example being the equivalence of gravity and acceleration in Einstein’s general theory of relativity (p 180).  This leads to a rejection of the ideas that humans are morally superior to their environment, and have the ability to manage and master it.  Instead, environmental policy should treat humans and their environment as equivalent parts of a social-ecological system (p 181).

The Unification Principle according to which apparently opposite concepts are actually the same (pp 181-2.  Again, there are examples from physics.  The conclusion drawn is that environmental policy should address not simply the environment but the whole social-ecological system (p 183).

According to Laitos, therefore, environmental policies do not work well for four main reasons: they are based on an inaccurate model of nature; they often presuppose human superiority; they are inconsistent with the law of symmetry; and sometimes they are based on a false model of how humans behave (p 184).

The most persuasive part of this is the view of nature as a complex adaptive system.  We know for example that there are complex interdepencies between the biotic and abiotic elements of the environment, via processes such as photosynthesis and carbon sequestration.  We also know that such natural processes have not always been in equilibrium.  The oxygen content of the atmosphere, 21% at present, has during the last billion years been as low as 3% and as high as 35% (9).  Even within the much more recent past, there have been dramatic changes such as the retreat of glaciers at the end of the last ice age about 12,000 years ago (10), and a period about 10,000 years ago when much of what is now the Sahara desert received sufficient rainfall to support a savanna-like environment (11).  Certainly, therefore, environmental policies should be developed with awareness of the complexity of natural processes and the possibility that the past may not be a good guide to the future.

On the other hand I am not persuaded by the ‘no natural baseline’ argument. Consider how it might apply to the issue of waste plastic polluting the oceans with adverse consequences for wildlife and indirectly (via food chains) for humans.  The argument would presumably be that the former plastic-free ocean was just one state which had persisted over a certain period and which, given the complexity of nature, might have come to an end without human intervention.  Hence to regard plastic-free oceans as a baseline to be restored if possible would be misguided.  Now that argument seems to me mistaken: it ignores both the implausibility of plastic being produced by natural processes, and the fact that, for thousands of years, fish caught from plastic-free oceans have been an important component of human diets.  What’s more, it illustrates a general shortcoming of Laitos’ approach.  His criticism of actual environmental policies contains many examples of particular policies in particular situations.  But in his presentation of his own policy ideas, I can find little indication that he has tested his abstract principles by considering what they would imply for specific situations.

So far as the requirement of symmetry is concerned, I will not comment on its application to theoretical physics, which is not my specialism.  But I have to say that I find the drawing out of consequences for environmental policy not just unconvincing but in places positively bizarre.  Nevertheless, let us consider the three conclusions on their merits, ignoring their provenance.

Simplicity can indeed be a virtue of environmental policy.  The five pence charge for single-use plastic bags introduced in England in 2015 is an example of a fairly simple policy (12).  It’s easy to think of ways in which the policy might with apparent justification have been made more complex, such as different charges for different bag sizes or exemptions for those on low incomes.  Nevertheless, the policy seems to have been widely accepted.  One likely reason is that the charge is too small to affect anyone’s vital interests.  Another is that it seems obvious that the administrative costs of the sort of complications listed above would greatly outweigh the benefits.

On the other hand, consider the case of international negotiations on reducing greenhouse gas emissions so as to mitigate climate change.  Here vital interests are at stake, along with different understandings of what the scientific evidence shows and different views of fairness in apportioning reductions.  A requirement that any agreement be simple, such as a uniform percentage reduction in emissions, would be fairly certain to ensure failure via a collapse in negotiations. Acceptance that an agreement will need to be complex keeps open the possibility of a partial success – an agreement that if implemented would lead to a reduction in emissions, albeit not as large a reduction as many consider necessary.

Laitos’ rejection of human superiority might suggest that he is an advocate of animal rights.  In fact, the concept of animal rights receives only one brief mention (p 156).  Nor does he ascribe value to nature generally, except in so far as the degradation of nature affects humans (p 38).  The superiority that Laitos rejects is the idea that humans have the ability to manage the environment (pp 29 & 181).  This highlights another weakness of his approach.  Perhaps as a consequence of his high level of abstraction, he tends to make statements that are too absolute and do not allow for matters of degree.  If he had just said that, when trying to manage their environment, humans often fail due to lack of ability, or make mistakes due to lack of knowledge or cognitive errors, then it would have been easy to agree.  But to deny outright  that humans have the ability to manage the environment is too strong.  Human actions do affect the environment, and humans do have the ability to choose among different actions that have different consequences.

If however one really did consider that humans cannot manage their environment, then the natural conclusion would be that any environmental policy is doomed to failure.  It is hard to see how such a belief could be a basis for choosing one policy rather than another.  Yet as we shall see, Laitos does advocate a particular type of environmental policy.

Laitos’ third conclusion – that environmental policy should address the whole social-ecological system – could be taken as just a way of saying that policy formulation should have regard to political feasibility (the social part of the system) as well as to its effect on the environment (the ecological part).  If so it would be entirely acceptable.  But what he actually means by this seems implicit in his rights-based approach to environmental policy, to which I now turn.

Laitos’ Proposed Environmental Policy: A Rights-Based Approach

Laitos proposes that environmental policies consistent with his framework would confer a certain type of right and impose a corresponding duty (p 36).  The right would be:

Positive, that is, a right entitling the holder to the help of others (as opposed to a negative right which merely requires others not to take certain actions) (pp 38-9 & 185-6).

Held by the social-ecological system, that is, by both humans and the environment. Thus it would be quite different from a specifically human right such as a right to clean water (p 185).

To environmental conditions in which humans can live safely (p 185). Thus although the right is held by humans and the environment, its purpose is solely to meet a human requirement, not to save or protect the natural environment (p 187).

Inclusive of the power to alter the right (pp 191).  Thus any legal right granted to the social-ecological system should be capable of being amended (p 192).

Laitos’ account of this right leaves unaddressed the key question of who would grant it.  The answer, at his abstract level, must be humans.  But that leads back to issues of political authority and international negotiation.  For he consistently identifies the right-holder as the social-ecological system. He is not talking about local ecosystems and their human inhabitants, on which one might envisage rights being conferred by local or national governments, but about one system consisting of the global environment and the whole of humanity.

That the right should be capable of being amended seems to amount to saying that there should be flexibility to adjust environmental policies in the light of circumstances (p 192).  As such it seems entirely acceptable.  But again it raises issues of authority which Laitos does not address.  How far should administrators have delegated authority to adjust policies (with risks of uncertainty for those affected and even outright abuse), and how far should changes be a matter reserved for law-makers?

So far as enforcement of the right is concerned, this is best considered after introducing the corresponding duty.  This duty is:

Imposed on humans only, not on the whole social-ecological system (p 185).

Affirmative, that is, a duty to provide something, not merely to refrain from harm (p 197).

To create public environmental goods and positive externalities (p 197).  In this case Laitos does give an example: a person planting a tree which will sequester carbon and so contribute to mitigation of climate change.

Laitos supports the affirmative nature of the duty with the argument that, as a matter of psychology, people respond better to being told what to do than what not do.  This seems problematic.  For one thing, the difference is often just a matter of polite wording, which is important in everyday intercourse (compare “Could you close the door” and “Could you not leave the door open”) but should not be a key consideration in framing laws.  For another, being told what to do can be far more restrictive of individual liberty than being told what not to do (compare requiring a car-owner to travel by public transport, or not to exceed speed limits).  Most fundamentally, the natural wording of some essential environmental policies is negative.  Consider safety policy for nuclear power stations. One might try to formulate a safety policy in terms of ‘preserving a radiation-free environment’, but the more obvious formulation is ‘avoiding radiation leakage’, and any idea that companies would respond better to the former than the latter is rather implausible.

The content of the duty is not specified in any detail. But let’s explore the tree-planting example. Suppose policy required every adult to plant at least one tree a year. That could help in mitigating climate change (though it is pertinent to ask how much else would be required to maintain the habitability of the planet).  But it could waste resources to little effect in places where the climate or soil is unsuitable for tree growth.  It could also do harm where tree-planting conflicts with other important land uses, or where the uptake of water by trees within a river basin would lead to reduced water flows with adverse downstream effects on agriculture or wetlands.  So a sensible policy focused on tree-planting would have to be more complicated, perhaps permitting people in places unsuitable for trees to enter into offsetting arrangements with those in more suitable places.

One way to give content to the duty while addressing such issues would be a policy telling each person in what way they should contribute to public environmental goods and positive externalities, but with the contributions tailored to people’s local circumstances: tree-planting in region A; rainwater harvesting in B; fish restocking in C; and so on.  At the other extreme, another would be to allow people discretion as to the nature of their contributions, but to require each person to submit an annual statement of their contribution for review by the authorities.  Intermediate arrangements would probably be more workable, for example, a list of acceptable contributions from which people could choose any one, or a system of points for contributions with an annual points target for each person.

What emerges from this is that giving practical form to a duty to create public goods and positive externalities would not meet Laitos’ requirement that policy should be simple.  Any apparent simplicity is entirely due to Laitos’ abstract presentation of his ideas.  Putting it into practice would raise the same sorts of issues as existing environmental policies, such as whether policy-makers have adequate technical advice, conflicts between different environmental objectives, and political feasibility.

Then there is the issue of enforcement.  Laitos states that environmental policy needs a “stick” instead of “carrots”, contrasting the “carrots” of subsidies with the “stick” of his positive duty (p 200).  This is an odd comparison for two reasons.  Firstly, subsidies are only one of many instruments used by existing environmental policies, and as a means of incentivising firms to reduce pollution are generally considered by economists to be inferior to taxes (because subsidies can also encourage new firms to enter polluting industries).  Secondly, a duty is not itself a “stick”. A “stick” would be a penalty that an authority could impose for failing to fulfil a duty.  One might have expected here a discussion of the process for imposition: how evidence might be gathered; whether the process would be administrative or judicial; types of penalty; and so on.  As throughout the positive parts of his book, however, Laitos seems uninterested in such details.

In summary, therefore, although Laitos is right to highlight the failure of many existing environmental policies, the alternative he offers owes whatever plausibility it may have almost entirely to its abstract formulation.  As soon as one attempts to flesh it out with practical detail, it becomes apparent that it would encounter much the same complexities and difficulties as existing policies.

Notes and References

  1. Laitos J, with Okulski J (2017) Why Environmental Policies Fail  Cambridge University Press.  All page references above are to this book.
  2. Wikipedia: Montreal Protocol – Effect https://en.wikipedia.org/wiki/Montreal_Protocol#Effect
  3. US Environmental Protection Agency: Lead and Copper Rule – A Quick Reference Guide https://nepis.epa.gov/Exe/ZyPDF.cgi?Dockey=60001N8P.txt
  4. Wikipedia: Flint Water Crisis https://en.wikipedia.org/wiki/Flint_water_crisis
  5. Wikipedia: Nuclear Power in Germany – Closures and Phase-Out https://en.wikipedia.org/wiki/Nuclear_power_in_Germany#Closures_and_phase-out
  6. Der Spiegel (22/11/2017) Can Germany Break its Lignite Habit? http://www.spiegel.de/international/business/energy-transition-blocked-by-brown-coal-a-1179537.html
  7. UN Framework Convention on Climate Change – Kyoto Protocol – Targets for the first Commitment Period http://unfccc.int/kyoto_protocol/items/3145.php
  8. My policy in this blog when setting out the views of others is normally to paraphrase and rarely to quote. This is partly because a paraphrase highlighting key points can be more concise than a quotation, and partly for copyright reasons. I hope that my paraphrases are fair and, as ever, would appreciate advice of any misrepresentation.
  9. Wikipedia: Atmosphere of Earth – Evolution of Earth’s Atmosphere https://en.wikipedia.org/wiki/Atmosphere_of_Earth#Evolution_of_Earth.27s_atmosphere
  10. Wikipedia: Last Glacial Period https://en.wikipedia.org/wiki/Last_glacial_period
  11. Carey B, Live Science (20/7/2006) Sahara Desert was Once Lush and Populated https://www.livescience.com/4180-sahara-desert-lush-populated.html
  12. The government regulations on the 5p charge are at http://www.legislation.gov.uk/uksi/2015/776/contents/made
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