The National Trust have outlined their alternative vision for the planning system. As a reminder, at the heart of the government's reform proposal lies the idea of the local plan (drawn up subject to incentives via New Homes Bonus etc) and a 'presumption in favour of development' providing it is consistent with the plan. No up-to-date plan? Then the presumption in favour of development takes over.
The National Trust suggests several adjustments. First, local communities should be able to have more say in drawing up local plans and specifically to reduce the amount of development that is planned locally. This suggestion causes problems for the government precisely because the proposed reforms do appear asymmetric on the extent to which neighbourhoods have power to affect local development. Specifically, they can decide to allow more development, but not less. If the government had confidence in the power of its financial incentives to affect local community attitudes to development, this restriction would be unnecessary. The problem is, of course, that the incentives are at the local authority, not the local level, we don't know whether they will be large enough and, regardless, it's hard to see exactly how the financial benefits to allowing development will filter down to local neighbourhoods affected. In short, there is a potential conflict between the principle of localism and what the government wants to achieve.
I have less sympathy with the other proposals in the NT manifesto. For example, if the lack of a local plan removes the need to say yes to development, then how does NT suggest that we make sure that LAs have up-to-date local plans? With no local plan in place, we are back to decision-by-decision planning which is worse than the system we currently have (which most people, including the NT, agree doesn't work).
Much more seriously, is the presumption in favour of 'brownfield land first' that NT want imposed. Again, this would maintain the status quo, so it might be useful to remind ourselves of the fundamental problem here: we need more housing. There are alternatives to trying to achieve this by building more homes on greenfield land. For example, let's all agree it would be good to make more use of long term vacant properties (especially if neglected). Let's agree to disagree on second homes. But let's acknowledge that even if we tackled both these issues it wouldn't do much to tackle the overall problem (even if we knew how). Debates around the sale of council homes are another red herring because those homes still constitute part of the supply. There is, of course, a debate to be had about how much new housing the government (or local councils) should directly provide. However, I haven't seen any serious suggests as to how a large government home building programme would be funded if it was necessary.
And all of these alternatives still leave open the question of where these homes would be built. By opposing reforms because of the impact on the environment, NT are continuing to champion brownfield land policies. But these policies haven't delivered the kind of homes people want, in the place they want them, in the kind of numbers needed. The same profound problem applies to commercial land. In short, the problem with the NT manifesto is that they provide no concrete proposals for dealing with the fundamental problem that the government's reforms are trying to address!
CEP Urban and Spatial Programme Blog (formerly SERC)
Friday, 30 September 2011
Wednesday, 28 September 2011
Rewarding Good Firms
Ed Miliband tells us he wants to reward good families and firms. Where there are details, they raise as many questions as answers. Allocating housing on the basis of criteria other than needs throws up big questions. It's not clear to me why we want people to do apprenticeships in firms that have government contracts, etc. Stepping back from the details, Ed Milliband says that what they will do is change the regulatory and tax framework to carefully reward good firms. Fine in principle, but in practice I worry that this sort of thing vastly overestimates the ability of government to intervene in a way that actually achieves it's objectives. Two analogies spring to mind - one concerns the role of the Basel regulations on capital requirements that sought to ensure good behaviour but ended up encouraging banks to hold mortgage backed assets (and derivatives of those assets). The second is a little more in line with my expertise and concerns what policy might do to 'reward innovative firms located in clusters'. For those of you that want the headline message - it turns out to be incredibly difficult to know what we should do (if anything) to reward innovative clusters of firms. For those of you that like the details, read on for a more careful analysis (based on my contribution to the Manchester Independent Economic Review)
There is an extensive policy literature on clusters that uses the existence of agglomeration economies to justify a whole range of policy interventions. Such an approach could be used to develop policy options for encouraging innovative clusters of firms. Policy makers like this approach because it argues for a strong role for active policy and usually involves the introduction of a range of ‘innovative’ policy measures. A significant number of academics like it too, for similar reasons. In contrast, most mainstream economists, and a number of leading economic geographers, are sceptical, if not hostile, to this approach and thus cautious about the policy conclusions that this literature reaches.
The first, well documented problem, is one of definition. Just what is meant by a cluster? The literature provides a large number of rather vague answers to this question. Even if this objection could be met by tightening the definition, much more significant problems remain. As noted by Gilles Duranton, “the [main] problem with the cluster policy literature is one of a lack of well-articulated theory: what is the ‘problem’ that cluster initiatives are trying to fix?” This problem lies at the heart of economist’s objections to this approach.
A common answer to the question about the role of cluster policy is that it aims to improve local “competitiveness” or productivity. The problem with this answer is that it does not clearly set out the source of any possible inefficiencies (or inequities) and thus cannot explain how to correct for them. Porter’s famous diamond attempts to map out the underlying sources of competitiveness. The resulting model appears to be complex with many different elements all feeding in to one another. But this complexity is actually rather superficial as all of the different elements feedback positively to other elements. A complex policy mix is called for, but fortunately, in Porter’s model, all policy actions on any component of the diamond will help strengthen the cluster.
Of course, in reality this will not be the case because of the presence of negative feedback. For example, in many cases, reducing barriers to entry in a sector which is already reasonably competitive, may hamper the development of new products (because firms offset the cost of innovating against the profits that they make once they innovate; entry drives down these profits and reduces incentives to innovate all else equal). Yet clusters policies often advocate increasing both entry and new product development as mutually reinforcing elements in strengthening a cluster. It would be possible to identify many other examples where carefully specified economic models and available empirical evidence actually point to a negative feedback between different elements of the diamond.
The second problem with the diamond model is that, despite its apparent complexity, it pays no attention to some fundamental drivers. For example, what is being assumed about labour mobility? If firms are mobile, but workers are not, how can one be sure that encouraging larger clusters in a particular place is a good idea? Similarly, what is being assumed about the functioning of the land market? It is quite possible that any surplus generated by increasing the size of the cluster just translates in to higher rents for owners of land. Models of urban economics show that the answers to such questions are fundamentally important in understanding the functioning of the spatial economy and in assessing the role, if any, for policy. Yet the diamond model is silent on these issues. This is particularly important in the UK context, where planning for housing and commercial land use is one of the key policy levers available at the sub-national level.
Finally, even if there is positive feedback between the different elements of the diamond model, this does not actually provide a justification for policy intervention. Such a justification needs to be based on carefully identifying reasons why the market ignores these positive feedbacks and produces an inefficient outcome. That is, we need to look for market failures and construct policy to address them accordingly. Unfortunately for the clusters policy approach, simple models that do this, suggest that market failures can lead to clusters being too big as well as too small. In other words, effective clusters policy might actually call for a reduction in the size of clusters.
The simplest way to think about the benefits of clustering is to assume that, because of the existence of agglomeration economies, the productivity of firms and thus the wages that they pay are increasing with cluster size. Offsetting this are rising costs (e.g. increased land prices) as the cluster increases in size. At small cluster sizes, we might expect increased benefits to outweigh increased costs as the size of the cluster increases. That is, the “competitiveness” of the cluster (as measured by the wages that its firms can pay to workers) is increasing in cluster size. At some size, however, the rate at which costs increase will begin to outweigh the rate at which benefits increase. That is, there is likely to be an optimal cluster size at which the wages that firms can pay are maximized. Encouraging expansion beyond this size will lead firms and workers to be worse off.
In the absence of government intervention would we expect cluster sizes to be above or below this optimal size? The answer depends on the mobility of workers and firms. If firms are reasonably mobile (which is likely to be the case) then clusters tend to be too large. This is because when firms enter the cluster they take account of the benefit to them (of being able to pay a higher wage as a result of agglomeration economies), but they ignore the increased costs to all the other firms. This is an example of a coordination failure. One way to solve this coordination problem is to have some large agent come along and help firms recognise the additional costs that they impose on other firms or else restrict the size of clusters. In other words, in this simple world, government should be working to decrease the size of clusters, not increase them.
Of course, this explanation is too simple, because there are externalities on both the benefit and cost side of cluster formation. Firms ignore both types of externalities when making their decisions. Cluster advocates focus on the unexploited benefits to argue that clusters will be smaller than optimal. In reality, there are cost externalities as well as agglomeration externalities which may make the social optimum for the cluster bigger or smaller than the private optimum. However, even if the social optimum is bigger than the private optimum this doesn’t necessarily mean government policy needs to expand the size of the cluster because private decisions may have already led to the cluster being too big relative to the private optimum.
In short, as is so often the case, the existence of several un-priced externalities make it very difficult to know what policy should be seeking to do in practice. Cluster advocates essentially only think about one of the three types of externalities present here (agglomeration externalities) while ignoring the other two (cost externalities and coordination failures). Oddly, when it comes to the overall size of our cities, advocates of strong land use controls do the opposite. They focus only on cost externalities and coordination failures, generally ignoring agglomeration benefits, to reach the conclusion that larger cities are too big relative to some optimum. As should be clear by now, both of these approaches only represent a very partial view of even the simplest models of cluster and city size formation. We would argue strongly that this is not a good basis for policy.
Of course, these conceptual issues might not matter at all if cluster advocates could point to a large number of cases where carefully designed public policies have had significant effect on both the size of clusters and their competitiveness. Unfortunately, a recent meta-survey of more than 750 clusters finds evidence that government policy does not do this. For example, van der Linde (2003, p.144) finds that “Random events or government influence […] are the least important determinants in competitive clusters, while they play a much more important role in uncompetitive clusters”. Cluster creation policies perform even worse. For the over 750 clusters that van der Linde (2003) studies, only one competitive cluster has been established as a result of a specific government policy to attract it. In short, even if we wanted to, simplistic implementation of cluster policies appears to do essentially nothing to create or increase the competitiveness of clusters.
As I said at the very beginning, Ed Milliband's idea may sound good in theory but it will certainly be very difficult to implement in practice.
There is an extensive policy literature on clusters that uses the existence of agglomeration economies to justify a whole range of policy interventions. Such an approach could be used to develop policy options for encouraging innovative clusters of firms. Policy makers like this approach because it argues for a strong role for active policy and usually involves the introduction of a range of ‘innovative’ policy measures. A significant number of academics like it too, for similar reasons. In contrast, most mainstream economists, and a number of leading economic geographers, are sceptical, if not hostile, to this approach and thus cautious about the policy conclusions that this literature reaches.
The first, well documented problem, is one of definition. Just what is meant by a cluster? The literature provides a large number of rather vague answers to this question. Even if this objection could be met by tightening the definition, much more significant problems remain. As noted by Gilles Duranton, “the [main] problem with the cluster policy literature is one of a lack of well-articulated theory: what is the ‘problem’ that cluster initiatives are trying to fix?” This problem lies at the heart of economist’s objections to this approach.
A common answer to the question about the role of cluster policy is that it aims to improve local “competitiveness” or productivity. The problem with this answer is that it does not clearly set out the source of any possible inefficiencies (or inequities) and thus cannot explain how to correct for them. Porter’s famous diamond attempts to map out the underlying sources of competitiveness. The resulting model appears to be complex with many different elements all feeding in to one another. But this complexity is actually rather superficial as all of the different elements feedback positively to other elements. A complex policy mix is called for, but fortunately, in Porter’s model, all policy actions on any component of the diamond will help strengthen the cluster.
Of course, in reality this will not be the case because of the presence of negative feedback. For example, in many cases, reducing barriers to entry in a sector which is already reasonably competitive, may hamper the development of new products (because firms offset the cost of innovating against the profits that they make once they innovate; entry drives down these profits and reduces incentives to innovate all else equal). Yet clusters policies often advocate increasing both entry and new product development as mutually reinforcing elements in strengthening a cluster. It would be possible to identify many other examples where carefully specified economic models and available empirical evidence actually point to a negative feedback between different elements of the diamond.
The second problem with the diamond model is that, despite its apparent complexity, it pays no attention to some fundamental drivers. For example, what is being assumed about labour mobility? If firms are mobile, but workers are not, how can one be sure that encouraging larger clusters in a particular place is a good idea? Similarly, what is being assumed about the functioning of the land market? It is quite possible that any surplus generated by increasing the size of the cluster just translates in to higher rents for owners of land. Models of urban economics show that the answers to such questions are fundamentally important in understanding the functioning of the spatial economy and in assessing the role, if any, for policy. Yet the diamond model is silent on these issues. This is particularly important in the UK context, where planning for housing and commercial land use is one of the key policy levers available at the sub-national level.
Finally, even if there is positive feedback between the different elements of the diamond model, this does not actually provide a justification for policy intervention. Such a justification needs to be based on carefully identifying reasons why the market ignores these positive feedbacks and produces an inefficient outcome. That is, we need to look for market failures and construct policy to address them accordingly. Unfortunately for the clusters policy approach, simple models that do this, suggest that market failures can lead to clusters being too big as well as too small. In other words, effective clusters policy might actually call for a reduction in the size of clusters.
The simplest way to think about the benefits of clustering is to assume that, because of the existence of agglomeration economies, the productivity of firms and thus the wages that they pay are increasing with cluster size. Offsetting this are rising costs (e.g. increased land prices) as the cluster increases in size. At small cluster sizes, we might expect increased benefits to outweigh increased costs as the size of the cluster increases. That is, the “competitiveness” of the cluster (as measured by the wages that its firms can pay to workers) is increasing in cluster size. At some size, however, the rate at which costs increase will begin to outweigh the rate at which benefits increase. That is, there is likely to be an optimal cluster size at which the wages that firms can pay are maximized. Encouraging expansion beyond this size will lead firms and workers to be worse off.
In the absence of government intervention would we expect cluster sizes to be above or below this optimal size? The answer depends on the mobility of workers and firms. If firms are reasonably mobile (which is likely to be the case) then clusters tend to be too large. This is because when firms enter the cluster they take account of the benefit to them (of being able to pay a higher wage as a result of agglomeration economies), but they ignore the increased costs to all the other firms. This is an example of a coordination failure. One way to solve this coordination problem is to have some large agent come along and help firms recognise the additional costs that they impose on other firms or else restrict the size of clusters. In other words, in this simple world, government should be working to decrease the size of clusters, not increase them.
Of course, this explanation is too simple, because there are externalities on both the benefit and cost side of cluster formation. Firms ignore both types of externalities when making their decisions. Cluster advocates focus on the unexploited benefits to argue that clusters will be smaller than optimal. In reality, there are cost externalities as well as agglomeration externalities which may make the social optimum for the cluster bigger or smaller than the private optimum. However, even if the social optimum is bigger than the private optimum this doesn’t necessarily mean government policy needs to expand the size of the cluster because private decisions may have already led to the cluster being too big relative to the private optimum.
In short, as is so often the case, the existence of several un-priced externalities make it very difficult to know what policy should be seeking to do in practice. Cluster advocates essentially only think about one of the three types of externalities present here (agglomeration externalities) while ignoring the other two (cost externalities and coordination failures). Oddly, when it comes to the overall size of our cities, advocates of strong land use controls do the opposite. They focus only on cost externalities and coordination failures, generally ignoring agglomeration benefits, to reach the conclusion that larger cities are too big relative to some optimum. As should be clear by now, both of these approaches only represent a very partial view of even the simplest models of cluster and city size formation. We would argue strongly that this is not a good basis for policy.
Of course, these conceptual issues might not matter at all if cluster advocates could point to a large number of cases where carefully designed public policies have had significant effect on both the size of clusters and their competitiveness. Unfortunately, a recent meta-survey of more than 750 clusters finds evidence that government policy does not do this. For example, van der Linde (2003, p.144) finds that “Random events or government influence […] are the least important determinants in competitive clusters, while they play a much more important role in uncompetitive clusters”. Cluster creation policies perform even worse. For the over 750 clusters that van der Linde (2003) studies, only one competitive cluster has been established as a result of a specific government policy to attract it. In short, even if we wanted to, simplistic implementation of cluster policies appears to do essentially nothing to create or increase the competitiveness of clusters.
As I said at the very beginning, Ed Milliband's idea may sound good in theory but it will certainly be very difficult to implement in practice.
Monday, 26 September 2011
Family Friendly Hotspots
Lots of coverage in the UK press for a report claiming that Winkleigh in Devon is the 'best place [in England and Wales] to bring up children'. As I have explained before, in the context of similar city rankings, I find these kind of exercises fairly uninformative. To allow you to reach your own opinion let me repeat some of the issues.
Economists think of households as facing an earnings, cost of living, amenity tradeoff when they think about where to locate. In recent SERC research, we address this question, by considering the extent to which higher post-tax earnings are offset by higher housing costs. Across Britain, our research shows increased living costs (particularly of housing) tend to completely offset increased wages for the average household. In the lowest wage areas, which are mostly rural, differences in amenities drive the cost-of-living versus wage tradeoff. In (mostly urban) higher wage areas, differences in firm productivity drive the results.
Rankings of places based on one or two characteristics make for interesting stories, but they don't tell us much about the more complex tradeoffs facing households and firms. This report doesn't suffer from that problem, because it considers many different characteristics of places. But multivariate indices (that consider many characteristics) try to get round this by applying arbitrary weights to those different characteristics which likely makes the index not useful for anyone (except those who just happen to have the same weighting as used in the report).
In contrast, urban economists start from observed difference in wages and costs of living, assume that people are pretty mobile across space and then try to figure out from actual behaviour what amenities people appear to value. This approach doesn't always make for such nice stories, but it does make for a more consistent way of evaluating the wage-cost-amenity tradeoff that firms and households face when choosing their city. To this way of thinking if a place is 'best' on some dimensions that will then be offset by other factors.
In short, I have a conceptual problem with picking some place as being somehow 'best' for families. Even if, for some reason, Winkleigh currently held this honour - I wouldn't expect that to last for long because as families flood to move there house prices should change so that property is no longer affordable. The fact that they haven't yet makes me wonder about the validity of the claim. Perhaps the locals are very good at keeping secrets (unusual, in my experience) so this adjustment hasn't yet happened. More realistically, perhaps the houses are small (making them look cheap) or its full of highly skilled people who could earn similar salaries in some other place with much cheaper housing. Or perhaps there are amenities there that make this a bad place to live for parents (or for teenagers so that families have to move as their children get older).
Whatever the reason, while I am sure that Winkleigh is a nice place to live, I (along with many other families) will not be rushing to move there.
Economists think of households as facing an earnings, cost of living, amenity tradeoff when they think about where to locate. In recent SERC research, we address this question, by considering the extent to which higher post-tax earnings are offset by higher housing costs. Across Britain, our research shows increased living costs (particularly of housing) tend to completely offset increased wages for the average household. In the lowest wage areas, which are mostly rural, differences in amenities drive the cost-of-living versus wage tradeoff. In (mostly urban) higher wage areas, differences in firm productivity drive the results.
Rankings of places based on one or two characteristics make for interesting stories, but they don't tell us much about the more complex tradeoffs facing households and firms. This report doesn't suffer from that problem, because it considers many different characteristics of places. But multivariate indices (that consider many characteristics) try to get round this by applying arbitrary weights to those different characteristics which likely makes the index not useful for anyone (except those who just happen to have the same weighting as used in the report).
In contrast, urban economists start from observed difference in wages and costs of living, assume that people are pretty mobile across space and then try to figure out from actual behaviour what amenities people appear to value. This approach doesn't always make for such nice stories, but it does make for a more consistent way of evaluating the wage-cost-amenity tradeoff that firms and households face when choosing their city. To this way of thinking if a place is 'best' on some dimensions that will then be offset by other factors.
In short, I have a conceptual problem with picking some place as being somehow 'best' for families. Even if, for some reason, Winkleigh currently held this honour - I wouldn't expect that to last for long because as families flood to move there house prices should change so that property is no longer affordable. The fact that they haven't yet makes me wonder about the validity of the claim. Perhaps the locals are very good at keeping secrets (unusual, in my experience) so this adjustment hasn't yet happened. More realistically, perhaps the houses are small (making them look cheap) or its full of highly skilled people who could earn similar salaries in some other place with much cheaper housing. Or perhaps there are amenities there that make this a bad place to live for parents (or for teenagers so that families have to move as their children get older).
Whatever the reason, while I am sure that Winkleigh is a nice place to live, I (along with many other families) will not be rushing to move there.
Friday, 23 September 2011
Higher local taxes a threat to jobs
Writing about the UK government’s consultation on Local Government Finance reform a couple of months ago, SERC affiliate Teemu Lyytikäinen talked about the fact that government had no intention of allowing councils to set their own business tax rates. He argued that the problem was partly political, but that the bigger issue is that it’s not clear what the effects of full localisation would be. There are several main fears. One is a race to the bottom – local authorities undercutting their competitors and undermining tax basis. The other fears relate to the opposite scenario, a `race to the top'. Would some councils set very high tax rates and waste the revenues on useless programmes and bureaucracy? Would these very high tax rates bring more pain to firms already struggling in the face of the recession? Some of my recent research, published in the Economic Journal this week, provides evidence that this fear is to some extent justified.
This issue has been the focus of an extensive theoretical literature and our study is not the first one to consider these issues empirically. Evidence from the 1960s and 1970s suggested that there was no effect of taxes on firm location decisions. Work focusing on the 1980s suggested a negative relationship and a number of subsequent papers have confirmed that finding.
The existing literature, however, has failed to resolve a central problem when assessing this impact. Specifically, there are many things about firms and local authorities that we do not observe, so any correlation between taxes and firm growth needs to be interpreted cautiously because some third factor (e.g. the remoteness of the location) might explain both. In addition, tax setting may be driven by firm choices, rather than vice-versa. That is taxes may be high because employment is low.
Our methodology solves these problems by using firm level data and comparing changes over time for firms located on either side of local authority boundaries. Comparing sites close to local authority borders eliminates major differences (because we assume closely located sites are similar). Comparing firms over time allows us to identify ‘good’ and ‘bad’ firms and so eliminate the problems due to sorting of firms. That is, these techniques help eliminate things about local authorities and firms that we do not observe that may be responsible for the correlation between taxes and firm growth. Finally, we use the electoral make up of the local authority to predict local taxes (some parties consistently set higher taxes) so we can adjust our results to allow for the possibility that taxes might be high because employment is low.
We use our methodology to study the impact of the UK business rates between 1984 and 1989. We find a negative (statistically significant) relationship between employment and taxes. Higher local authority taxes lower employment in existing firms. In contrast, we find that local taxation has no effect on the entry of new establishments, probably because landlords have to lower rents in high tax local authorities to continue to attract tenants. In contrast, because existing firms are less likely to move away, landlords don’t necessarily change their rents, hence the negative effect on employment in existing firms.
Our methodology is applicable more widely, but results for the UK suggest that the government may be right to worry that local taxation can negatively affect local employment. One important caveat, however – our results can’t tell us whether local authorities would actually set such high taxes. They only provide a warning about the negative employment effects of doing so.
(If you are not in an academic institution and would like to see the full paper, please get in touch with my colleague Max Nathan: m dot a dot nathan [at] lse dot ac dot uk.)
Wednesday, 21 September 2011
Adapting to climate change
Professor Matt Kahn (UCLA) talked at LSE yesterday on how cities adapt to climate change. It was a great talk, so if you missed it here's a broad outline of what he had to say. The text is from Matt's blog (which comes highly recommended if you are interested in environmental and urban economics). If you want more details, you should read his new book, Climatopolis.
---
There's several different ways to approach the broad question of how will Europe adapt to climate change.
1. You can focus on geography and compare likely scenarios for northern versus southern nations and coastal versus inland nations and nations who have built up along rivers.
2. You can contrast likely outcomes for the richest nations in Europe versus poorer nations in Europe. You can also discuss across income groups the issue of how the rich will cope versus how the poor will cope.
3. You can contrast how urbanites will cope versus how agricultural interests will adapt.
4. You can discuss how the EU and its emphasis on free trade within the zone will help nations to adapt to changing conditions.
5. You can discuss which nations have the best institutions to allow them to be flexible to adapt to changing circumstances.
I see an important role for geographers here. There is a real need for specificity and in particular for detailed maps to be made concerning the geography of different European nations. Which of their cities are at greatest risk of flooding? Are their citizens aware of these evolving risks? What "insurance" have these nations purchased through where they locate housing and industry and what types of materials they build with?
A recent example of such specificity is a new paper about California's coastline and climate change adaptation. I will blog about that paper in the future.
As readers of this exciting blog know, I am an optimist. Human ingenuity is a key asset in helping us to cope with change. If we know that we face increased threats of extreme heat and cold and floods and other challenges, this "heads up" is a first step to making investments now that will reduce the damage caused by these events when they happen. My Climatopolis book was meant to start a discussion about how economists view investment under uncertainty. A surprising number of environmentalists view men and women as helpless doomed individuals who will be knocked out by Mother Nature. I don't believe that. We have many strategies available to us to adapt to the very real challenge of climate change and we have the right incentives to do so.
---
[This outline originally posted on Matt Kahn's Environmental and Urban Economics blog on Thursday 16th September. Thanks to Matt for permission to reproduce it.]
---
There's several different ways to approach the broad question of how will Europe adapt to climate change.
1. You can focus on geography and compare likely scenarios for northern versus southern nations and coastal versus inland nations and nations who have built up along rivers.
2. You can contrast likely outcomes for the richest nations in Europe versus poorer nations in Europe. You can also discuss across income groups the issue of how the rich will cope versus how the poor will cope.
3. You can contrast how urbanites will cope versus how agricultural interests will adapt.
4. You can discuss how the EU and its emphasis on free trade within the zone will help nations to adapt to changing conditions.
5. You can discuss which nations have the best institutions to allow them to be flexible to adapt to changing circumstances.
I see an important role for geographers here. There is a real need for specificity and in particular for detailed maps to be made concerning the geography of different European nations. Which of their cities are at greatest risk of flooding? Are their citizens aware of these evolving risks? What "insurance" have these nations purchased through where they locate housing and industry and what types of materials they build with?
A recent example of such specificity is a new paper about California's coastline and climate change adaptation. I will blog about that paper in the future.
As readers of this exciting blog know, I am an optimist. Human ingenuity is a key asset in helping us to cope with change. If we know that we face increased threats of extreme heat and cold and floods and other challenges, this "heads up" is a first step to making investments now that will reduce the damage caused by these events when they happen. My Climatopolis book was meant to start a discussion about how economists view investment under uncertainty. A surprising number of environmentalists view men and women as helpless doomed individuals who will be knocked out by Mother Nature. I don't believe that. We have many strategies available to us to adapt to the very real challenge of climate change and we have the right incentives to do so.
---
[This outline originally posted on Matt Kahn's Environmental and Urban Economics blog on Thursday 16th September. Thanks to Matt for permission to reproduce it.]
Monday, 19 September 2011
Evidence on planning
A group of leading businessmen have written to the Times supporting government reforms to the planning system.
The National Trust respond with their concerns about concrete, but the Council for the Protection of Rural England focus on the economic arguments. According to the Times, the CPRE claim there is no evidence planning undermines productivity and no evidence that planning system’s default answer was “No” because the vast majority of planning applications are approved. One of these statements is wrong, the other is misleading.
Evidence that planning reduces productivity.
On the first of these (productivity) CPRE is simply wrong. In a recent SERC report we provided evidence that planning reduced productivity in a leading supermarket chain by 20%.
Evidence that planning could hurt investment.
In a paper published in the Economic Journal in 2008, my colleagues Paul Cheshire and Christian Hilber carefully document how planning restrictions in England impose a 'tax' on office developments that varies from around 250% (of development costs) in Birmingham, to 400-800% in London. New York imposes a 'tax' of around 0-50%, central Paris around 300%.
Approval rates are misleading
As I have explained in more detail before: approval rates tell us nothing about whether planning holds back development because the rules affect both the submission and approval rates. If planning rules are so draconian that no one applies to build houses, approval rates would run at 100%. Would that mean planning was not a problem?
Planning increases house prices (substantially)
OK, CPRE don't mention house prices, but planning matters there too. SERC research suggests that an area moving from have an average level of restrictiveness to having the lowest level of housing restrictiveness would see house prices fall by around 30%. This is an underestimate because it ignores the effect on UK house prices overall, as well as any effects on the composition of housing (i.e. houses are smaller).
Planning may increase house price volatility
At least until this last recession, average volatility in the UK housing market was higher than volatility in the most volatile market in the US (LA). When house prices fall, supply is fixed in both the UK and US (unless you destroy houses). However when, as in the UK, housing supply is very unresponsive to increased demand, booms drive up prices rather than leading to more building. That means the UK sees more volatility on the up-side of the market and leads to move volatility overall.
The costs of planning
So, there is evidence that the planning system:
The National Trust respond with their concerns about concrete, but the Council for the Protection of Rural England focus on the economic arguments. According to the Times, the CPRE claim there is no evidence planning undermines productivity and no evidence that planning system’s default answer was “No” because the vast majority of planning applications are approved. One of these statements is wrong, the other is misleading.
Evidence that planning reduces productivity.
On the first of these (productivity) CPRE is simply wrong. In a recent SERC report we provided evidence that planning reduced productivity in a leading supermarket chain by 20%.
Evidence that planning could hurt investment.
In a paper published in the Economic Journal in 2008, my colleagues Paul Cheshire and Christian Hilber carefully document how planning restrictions in England impose a 'tax' on office developments that varies from around 250% (of development costs) in Birmingham, to 400-800% in London. New York imposes a 'tax' of around 0-50%, central Paris around 300%.
Approval rates are misleading
As I have explained in more detail before: approval rates tell us nothing about whether planning holds back development because the rules affect both the submission and approval rates. If planning rules are so draconian that no one applies to build houses, approval rates would run at 100%. Would that mean planning was not a problem?
Planning increases house prices (substantially)
OK, CPRE don't mention house prices, but planning matters there too. SERC research suggests that an area moving from have an average level of restrictiveness to having the lowest level of housing restrictiveness would see house prices fall by around 30%. This is an underestimate because it ignores the effect on UK house prices overall, as well as any effects on the composition of housing (i.e. houses are smaller).
Planning may increase house price volatility
At least until this last recession, average volatility in the UK housing market was higher than volatility in the most volatile market in the US (LA). When house prices fall, supply is fixed in both the UK and US (unless you destroy houses). However when, as in the UK, housing supply is very unresponsive to increased demand, booms drive up prices rather than leading to more building. That means the UK sees more volatility on the up-side of the market and leads to move volatility overall.
The costs of planning
So, there is evidence that the planning system:
- Lowers retail productivity
- Increases office rents
- Increases house prices and housing market volatility
Friday, 16 September 2011
Urban schools: more money, better outcomes?
Posted by Steve Gibbons, SERC and LSE
The new school year has started, but with all the noise about Free Schools it's easy to lose sight of the bigger issue: how well pupils actually do.
Back in the spring, English schools with the poorest pupils received a small boost to their budgets through the coalition's flagship 'pupil premium' policy (£430 for each pupil registered for free school meals). It's still too early to say whether the extra money has had an effect on standards, but new research I've done with colleagues from CEE provides some grounds for optimism. It shows that urban primary schools in England that received more money performed better in subsequent years.
You might wonder why this is an interesting finding. Isn't it obvious that spending more produces better results? Look at richly-resourced private schools, compared to cash-strapped state schools, for example.
Surprisingly, however, a lot of evidence suggests that moderate resource disparities actually don't make much difference to children's achievement. And unlike private schools, state schools can't cherry-pick pupils. For some city schools, teaching is a lot tougher as a result. Simply injecting cash may not help.
In practice it's rare to see schools that teach similar children, but get dissimilar funding. It is, therefore, difficult to measure whether more money really makes a difference. But there are some situations in England where one school can get quite a lot more money than its neighbour: when two schools are on opposite sides of Local Authority boundaries.
Some odd geographical anomalies in the way central government pays money to Local Authorities ('Area Cost Adjustments', or ACAs) mean some councils end up with more money to spend per pupil than their neighbours. These differences filter down to neighbouring schools, even when these schools have similar pupils, and face similar teacher pay scales and prices for other resources.
These arrangements have raised a lot of local objections (for example, the Lib Dem 'Fair Deal for Haringay' campaign). These objections are understandable, since our data shows that differences in the order of £1000 per pupil are not uncommon. We should question the logic and equity of these quirks in funding formulae.
Fairness aside, ACAs do provide a nice experiment for studying the local effects of investing in schools. As it turns out, children in city primary schools that received an additional £1000 per pupil per year did much better (on average) in their Key Stage 2 tests at age 11. The estimated effect is equivalent to moving 19% of students currently achieving Level 4 in Maths (the target grade) to Level 5 (the top grade) and 31% of students currently at Level 3 maths to Level 4.
We can't answer the question of how the extra money is best spent (teachers, books, computers?), and that question is probably best left to those who actually teach. But importantly, our research confirms that those running city schools can significantly raise standards - when they have additional resources to work with.
The new school year has started, but with all the noise about Free Schools it's easy to lose sight of the bigger issue: how well pupils actually do.
Back in the spring, English schools with the poorest pupils received a small boost to their budgets through the coalition's flagship 'pupil premium' policy (£430 for each pupil registered for free school meals). It's still too early to say whether the extra money has had an effect on standards, but new research I've done with colleagues from CEE provides some grounds for optimism. It shows that urban primary schools in England that received more money performed better in subsequent years.
You might wonder why this is an interesting finding. Isn't it obvious that spending more produces better results? Look at richly-resourced private schools, compared to cash-strapped state schools, for example.
Surprisingly, however, a lot of evidence suggests that moderate resource disparities actually don't make much difference to children's achievement. And unlike private schools, state schools can't cherry-pick pupils. For some city schools, teaching is a lot tougher as a result. Simply injecting cash may not help.
In practice it's rare to see schools that teach similar children, but get dissimilar funding. It is, therefore, difficult to measure whether more money really makes a difference. But there are some situations in England where one school can get quite a lot more money than its neighbour: when two schools are on opposite sides of Local Authority boundaries.
Some odd geographical anomalies in the way central government pays money to Local Authorities ('Area Cost Adjustments', or ACAs) mean some councils end up with more money to spend per pupil than their neighbours. These differences filter down to neighbouring schools, even when these schools have similar pupils, and face similar teacher pay scales and prices for other resources.
These arrangements have raised a lot of local objections (for example, the Lib Dem 'Fair Deal for Haringay' campaign). These objections are understandable, since our data shows that differences in the order of £1000 per pupil are not uncommon. We should question the logic and equity of these quirks in funding formulae.
Fairness aside, ACAs do provide a nice experiment for studying the local effects of investing in schools. As it turns out, children in city primary schools that received an additional £1000 per pupil per year did much better (on average) in their Key Stage 2 tests at age 11. The estimated effect is equivalent to moving 19% of students currently achieving Level 4 in Maths (the target grade) to Level 5 (the top grade) and 31% of students currently at Level 3 maths to Level 4.
We can't answer the question of how the extra money is best spent (teachers, books, computers?), and that question is probably best left to those who actually teach. But importantly, our research confirms that those running city schools can significantly raise standards - when they have additional resources to work with.
Subscribe to:
Posts (Atom)