No surprises to see some people questioning the HS2 decision in light of the West Coast Mainline franchising fiasco.
My personal position remains unchanged: I'm not convinced by the case for HS2 even on the basis of the existing growth numbers. That said, the WCML fiasco did reinforce my prejudice for the need to present simple headline figures for passenger numbers etc alongside more complex cost-benefit calculations. I say 'reinforced' because my experience on the HS2 Analytical Challenge Panel had already convinced me that only a small number of people are really on top of the modelling work that is being done for these very complex schemes. [Indeed, one of the factors behind my recent decision to resign from the ACP was that I no longer felt sufficiently on top of the details of the economic model to be able to fulfil the challenge role.]
Unfortunately, HS2 (and, I assume, DfT) don't seem to share the same prejudice. So, for example, the economic case for HS2 (updated) predicts that 148,000 passengers will use HS2 each day between Birmingham and Old Oak Common. To my mind, the most helpful way to think about that number is to compare it to current figures. Sadly, this is not a comparison that you'll be able to make easily on the basis of information provided in the economic case. Likewise, I'd find it helpful to see user numbers by station compared to current user numbers. Again, not information that you'll find provided in a simple format anywhere in the report. Without these figures I find the more complex calculations even harder to assess.
In short: Simple descriptive statistics help provide context and allow ballpark assessment of more complex analysis. If nothing else, let's hope that DfT and HS2 ltd learn that particular lesson from the WCML fiasco.
CEP Urban and Spatial Programme Blog (formerly SERC)
Tuesday, 9 October 2012
Thursday, 4 October 2012
More conference housing plans
I was pretty critical of Nick Clegg's recent announcement on allowing parents to use their pension pots to help their kids buy housing. Ed Ball's plans announced earlier this week fair marginally better.
I haven't seen much persuasive analysis that the previous stamp duty holiday had much impact, so it's unclear why a new one should make much difference (a much better move would be a wholesale reform of property tax).
Setting aside the question of the overall fiscal position, using the windfall from 4G to help fund affordable homes makes more sense than Clegg's proposal because it boosts supply rather than demand. The crucial question, of course, is whether it will make any meaningful difference to affordability? The answer, I'm afraid, is almost certainly not. Making the very generous assumption that all of these government funded houses are truly additional (i.e. wouldn't have been built anyhow) the plan delivers at most 100,000 affordable houses over two years. If Balls has 'got his sums wrong' as some claim that figure might be closer to the 60,000 mark. 30,000 to 50,000 additional housing units per annum roughly takes annual house building back to where it was in the mid 2000's.
Unfortunately, even in a downturn, building houses is expensive. Ball's scheme makes some sense, but truly dealing with the problem of affordability requires a market led response in the areas of highest demand. This in turn, requires the planning system to allow a proper supply response. Labour only woke up to this problem very late in their last administration and, arguably, did too little too late. Addressing long term affordability isn't a matter of short term stimulus. Instead, it requires a private sector response when the market finally (hopefully) picks up. Developing a planning system that allows that to happen is the real challenge for the next administration.
I haven't seen much persuasive analysis that the previous stamp duty holiday had much impact, so it's unclear why a new one should make much difference (a much better move would be a wholesale reform of property tax).
Setting aside the question of the overall fiscal position, using the windfall from 4G to help fund affordable homes makes more sense than Clegg's proposal because it boosts supply rather than demand. The crucial question, of course, is whether it will make any meaningful difference to affordability? The answer, I'm afraid, is almost certainly not. Making the very generous assumption that all of these government funded houses are truly additional (i.e. wouldn't have been built anyhow) the plan delivers at most 100,000 affordable houses over two years. If Balls has 'got his sums wrong' as some claim that figure might be closer to the 60,000 mark. 30,000 to 50,000 additional housing units per annum roughly takes annual house building back to where it was in the mid 2000's.
Unfortunately, even in a downturn, building houses is expensive. Ball's scheme makes some sense, but truly dealing with the problem of affordability requires a market led response in the areas of highest demand. This in turn, requires the planning system to allow a proper supply response. Labour only woke up to this problem very late in their last administration and, arguably, did too little too late. Addressing long term affordability isn't a matter of short term stimulus. Instead, it requires a private sector response when the market finally (hopefully) picks up. Developing a planning system that allows that to happen is the real challenge for the next administration.
Tuesday, 25 September 2012
The soft power Games
Posted by Dr Max Nathan, SERC and
LSE Cities
The Economist Intelligence Unit has published Legacy 2012, a collection of essays on the economic effects of the London Olympics. You can download it here. I’ve got the lead piece, written pre-Games, which (post-Games) now seems a bit grumpy. Here are the headlines, and some reflections with the benefit of hindsight:
First, the direct economic benefits of 2012 to London are pretty small. This is the overwhelming message from the economic evidence, and the experience of past Games. Predictions of a hit to local retail and tourism also turned out to be correct.
Second, the major hard gain is the physical regeneration of the Olympic site. We can argue about whether winning the Games ‘created’ this, or just accelerated it. But some Londoners (homeowners, certainly) got more out of it than others. It’s telling that the Centre for Cities suggests a ‘separate’ employment and skills strategy is needed for East London – so what positive effect did the Games have on local people’s employment chances?
Third, the indirect economic effects on the UK may be pretty big – as they have been for Korea, China and Spain. Hosting the Olympics is a massively powerful policy signal, and the Games are a platform from which to tell a story about the UK’s place in the world. Work by Rose and Spiegel, published in the Economic Journal, suggests that on average, Olympic host countries get a whopping 20% trade boost. (Amazingly, even losing bidders pick up some positive trade effect.) The host city stands in for the nation at Games time, so that London effectively was the UK for foreign viewers. Boris clearly understood this before David Cameron.
More prescient than he knew, Tony Blair is fumbling for the political economy argument in this Vanity Fair interview (thanks to Will Davies for the spot):
For a country like Britain, it’s a great thing for us to have the Olympics here. We can afford to do the Olympics. We’re Britain. We’re not some Third World country.
For countries like Korea and China the message is ‘we’re arrived’. For Britain, perhaps – ‘we’ve still got it’?
So perhaps we’ve been looking for legacy in the wrong place. If it's all about messaging, the biggest economic impacts of 2012 may be the long term boost to British soft power.
The other takeaway is that economists vastly under-estimated the intangible benefits from the Games. Pre-Games analysis suggested the ‘willingness to pay’ was dwarfed by the £9.3bn budget, but our medal hauls in both Games have clearly changed the calculus. Perhaps we should have spotted this coming – Goldman Sachs suggest that host countries typically win 54% more medals than usual. That sporting success doesn’t come for free, as Will points out here. But Team GB’s glorious performances are likely worth several billions in – fleeting? – goodwill.
This post originally appeared on the squareglasses blog.
The Economist Intelligence Unit has published Legacy 2012, a collection of essays on the economic effects of the London Olympics. You can download it here. I’ve got the lead piece, written pre-Games, which (post-Games) now seems a bit grumpy. Here are the headlines, and some reflections with the benefit of hindsight:
First, the direct economic benefits of 2012 to London are pretty small. This is the overwhelming message from the economic evidence, and the experience of past Games. Predictions of a hit to local retail and tourism also turned out to be correct.
Second, the major hard gain is the physical regeneration of the Olympic site. We can argue about whether winning the Games ‘created’ this, or just accelerated it. But some Londoners (homeowners, certainly) got more out of it than others. It’s telling that the Centre for Cities suggests a ‘separate’ employment and skills strategy is needed for East London – so what positive effect did the Games have on local people’s employment chances?
Third, the indirect economic effects on the UK may be pretty big – as they have been for Korea, China and Spain. Hosting the Olympics is a massively powerful policy signal, and the Games are a platform from which to tell a story about the UK’s place in the world. Work by Rose and Spiegel, published in the Economic Journal, suggests that on average, Olympic host countries get a whopping 20% trade boost. (Amazingly, even losing bidders pick up some positive trade effect.) The host city stands in for the nation at Games time, so that London effectively was the UK for foreign viewers. Boris clearly understood this before David Cameron.
More prescient than he knew, Tony Blair is fumbling for the political economy argument in this Vanity Fair interview (thanks to Will Davies for the spot):
For a country like Britain, it’s a great thing for us to have the Olympics here. We can afford to do the Olympics. We’re Britain. We’re not some Third World country.
For countries like Korea and China the message is ‘we’re arrived’. For Britain, perhaps – ‘we’ve still got it’?
So perhaps we’ve been looking for legacy in the wrong place. If it's all about messaging, the biggest economic impacts of 2012 may be the long term boost to British soft power.
The other takeaway is that economists vastly under-estimated the intangible benefits from the Games. Pre-Games analysis suggested the ‘willingness to pay’ was dwarfed by the £9.3bn budget, but our medal hauls in both Games have clearly changed the calculus. Perhaps we should have spotted this coming – Goldman Sachs suggest that host countries typically win 54% more medals than usual. That sporting success doesn’t come for free, as Will points out here. But Team GB’s glorious performances are likely worth several billions in – fleeting? – goodwill.
This post originally appeared on the squareglasses blog.
Helping young people buy more housing
What is it about politicians and the housing market? Sure, understanding housing markets is sometimes tricky (I still struggle) but why is it that so many announcements in this area don't stand up to even the most basic scrutiny? The most recent example comes with Nick Clegg's suggestion that parents should be allowed to use their pension to help younger people buy property.
Here's my two step assessment (which can, of course, be applied to many other housing policy initiatives)
1. How many people are likely to be affected? This can be tricky to work out precisely, but often easy to ball-park. For Nick Clegg's announcement - as with a number of recent schemes - the conclusion seems to be 'not many'.
2. If the policy affects relatively large numbers of people, what's the likely impact on the housing market? This step is slightly, but not much, trickier because it involves applying some basic insights from supply and demand. There are essentially two ways to help young people in the housing market. First, increase the supply of (suitable) housing. Second, redistribute some of the existing housing stock from older people to younger people. Nick Clegg's proposal does neither of these things so even if it 'works' it won't 'help'.
Here's my two step assessment (which can, of course, be applied to many other housing policy initiatives)
1. How many people are likely to be affected? This can be tricky to work out precisely, but often easy to ball-park. For Nick Clegg's announcement - as with a number of recent schemes - the conclusion seems to be 'not many'.
2. If the policy affects relatively large numbers of people, what's the likely impact on the housing market? This step is slightly, but not much, trickier because it involves applying some basic insights from supply and demand. There are essentially two ways to help young people in the housing market. First, increase the supply of (suitable) housing. Second, redistribute some of the existing housing stock from older people to younger people. Nick Clegg's proposal does neither of these things so even if it 'works' it won't 'help'.
Monday, 24 September 2012
Evaluation and self-report additionality.
As I have written before, I like the idea of making information about policy interventions more freely available. Partly because I think it's an important principle of open government but also because it allows for better policy evaluation.
I have been reminded of this in the past couple of months because, together with colleagues, I've been looking through quite a lot of government evaluation reports. One thing that has struck me as I have read through those reports is the willingness of people to rely on self-reported 'guesstimates' of additionality (i.e. what 'extra' happened as a result of the policy intervention). These are usually provided either by recipients of the money or by people directly involved in handing out the money.
Like many economists, I tend to take these with a pinch of salt. Partly this is because I have the economists natural distrust about asking people to evaluate the counterfactual - i.e. what would have happened in the absence of the grant. This is a very difficult thought experiment at the best of times and one that is surely made more difficult with policy evaluation because the people being asked are often receiving money (or some kind of benefit in kind) from the operation of the policy.
I get even more worried, however, when these self-reported additionality figures are used as the basis for comparisons across different policy areas or different types of recipients. Why should we expect a young unemployed worker assessing the additionality of a training scheme to give us numbers that can meaningfully be compared to those from a scheme supporting R&D? More subtly, even within schemes, why should we expect the answers to such questions to be the same across, say, small and large firms? Of course, one reason why the answers might differ is because the policy actually differs in terms of additionality for the different types of interventions etc. But more worrying is that the answers might differ depending on characteristics of the policy that have nothing to do with whether the policy has any impact on behaviour.
There doesn't seem to be a big literature unpacking this problem. I have a vague recollection of one paper (possibly by Heckman) which suggested that self-reported additionality tended to be positively correlated with things that were, somewhat worrying, negatively correlated with econometrically estimated additionality (based on what people do, not on what they say). But I don't know of many other references (and would be happy to receive some pointers).
In light of these concerns, it is a little depressing that such self-reported additionality appears to remain remarkably popular with many in the policy making community.
I have been reminded of this in the past couple of months because, together with colleagues, I've been looking through quite a lot of government evaluation reports. One thing that has struck me as I have read through those reports is the willingness of people to rely on self-reported 'guesstimates' of additionality (i.e. what 'extra' happened as a result of the policy intervention). These are usually provided either by recipients of the money or by people directly involved in handing out the money.
Like many economists, I tend to take these with a pinch of salt. Partly this is because I have the economists natural distrust about asking people to evaluate the counterfactual - i.e. what would have happened in the absence of the grant. This is a very difficult thought experiment at the best of times and one that is surely made more difficult with policy evaluation because the people being asked are often receiving money (or some kind of benefit in kind) from the operation of the policy.
I get even more worried, however, when these self-reported additionality figures are used as the basis for comparisons across different policy areas or different types of recipients. Why should we expect a young unemployed worker assessing the additionality of a training scheme to give us numbers that can meaningfully be compared to those from a scheme supporting R&D? More subtly, even within schemes, why should we expect the answers to such questions to be the same across, say, small and large firms? Of course, one reason why the answers might differ is because the policy actually differs in terms of additionality for the different types of interventions etc. But more worrying is that the answers might differ depending on characteristics of the policy that have nothing to do with whether the policy has any impact on behaviour.
There doesn't seem to be a big literature unpacking this problem. I have a vague recollection of one paper (possibly by Heckman) which suggested that self-reported additionality tended to be positively correlated with things that were, somewhat worrying, negatively correlated with econometrically estimated additionality (based on what people do, not on what they say). But I don't know of many other references (and would be happy to receive some pointers).
In light of these concerns, it is a little depressing that such self-reported additionality appears to remain remarkably popular with many in the policy making community.
Friday, 14 September 2012
Talking about Building on the Greenbelt
A couple of week's ago, I was writing about CPRE's report highlighting a renewed 'threat' to the greenbelt.
The report identifies projects "amounting to the development of a new town greater than the size of Slough over the next twenty years". At the time, I commented on the fact that this seemed an odd unit of measurement.
One might argue that it's a simple way of communicating the threat. However, Daniel Kahneman's Thinking, Fast and Slow provides an alternative explanation - that CEPR are suffering from 'denominator neglect' (or attempting to make use of it). Denominator neglect in this cases means that your attention is drawn to the new development, but you ignore all of the greenbelt land left untouched. Denominator neglect is the effect that causes people to over-weight low probability events.
A number of other biases are at work when it comes to assessing statements about the greenbelt. I'm not sure that I completely understand all of these, but I think I've understood enough to know that I will henceforth discuss proposals for the greenbelt as follows: 'Over the next twenty years we plan to build 1 million more homes, helping address housing affordability for our poorest families; our plans safeguard the countryside ensuring that 99.5% of our currently undeveloped land will remain undeveloped.'
When I get a moment, I'll do the exact maths in terms of 1 million houses and the amount of land left undeveloped - but I'm hoping the re-framing might help regardless.
The report identifies projects "amounting to the development of a new town greater than the size of Slough over the next twenty years". At the time, I commented on the fact that this seemed an odd unit of measurement.
One might argue that it's a simple way of communicating the threat. However, Daniel Kahneman's Thinking, Fast and Slow provides an alternative explanation - that CEPR are suffering from 'denominator neglect' (or attempting to make use of it). Denominator neglect in this cases means that your attention is drawn to the new development, but you ignore all of the greenbelt land left untouched. Denominator neglect is the effect that causes people to over-weight low probability events.
A number of other biases are at work when it comes to assessing statements about the greenbelt. I'm not sure that I completely understand all of these, but I think I've understood enough to know that I will henceforth discuss proposals for the greenbelt as follows: 'Over the next twenty years we plan to build 1 million more homes, helping address housing affordability for our poorest families; our plans safeguard the countryside ensuring that 99.5% of our currently undeveloped land will remain undeveloped.'
When I get a moment, I'll do the exact maths in terms of 1 million houses and the amount of land left undeveloped - but I'm hoping the re-framing might help regardless.
Wednesday, 12 September 2012
Knowledge exchange
I am all for academics engaging with popular debate (or 'knowledge exchange' according to our funders). Indeed, it's one of the main reasons why I write posts for this blog.
One of the things less enthusiastic colleagues struggle with is that often your research ends up getting misinterpreted. I've experienced this on many occasions - most recently when my research on the effect of public sector employment on private sector employment was interpreted by some as saying something about the impact of a move to local pay. Generally speaking, I think academics need to be fairly relaxed about this. After all, reaching broader conclusions from rather specific research findings is something a lot of us do when faced with big issues where the underlying research is indicative at best.
That said, I am surprised when people use my research to reach a conclusion that goes specifically against the findings of the research in question. Today's FT provides a nice example. Talking about the findings of our research on the impact of Regional Selective Assistance the article says "research by the LSE shows grants to small UK businesses help increase productivity." In fact, our research shows the exact opposite, as you can read for yourself in the abstract of the paper (kindly linked to by the FT article): "we find that the program has had a positive effect on both employment and investment [...]. There is no statistically significant effect on total factor productivity."
Still, it's good to know that people out there read your research (even if you might wish they read it a little more carefully).
One of the things less enthusiastic colleagues struggle with is that often your research ends up getting misinterpreted. I've experienced this on many occasions - most recently when my research on the effect of public sector employment on private sector employment was interpreted by some as saying something about the impact of a move to local pay. Generally speaking, I think academics need to be fairly relaxed about this. After all, reaching broader conclusions from rather specific research findings is something a lot of us do when faced with big issues where the underlying research is indicative at best.
That said, I am surprised when people use my research to reach a conclusion that goes specifically against the findings of the research in question. Today's FT provides a nice example. Talking about the findings of our research on the impact of Regional Selective Assistance the article says "research by the LSE shows grants to small UK businesses help increase productivity." In fact, our research shows the exact opposite, as you can read for yourself in the abstract of the paper (kindly linked to by the FT article): "we find that the program has had a positive effect on both employment and investment [...]. There is no statistically significant effect on total factor productivity."
Still, it's good to know that people out there read your research (even if you might wish they read it a little more carefully).
Subscribe to:
Posts (Atom)