Recession and recovery–hard times or smoke and mirrors? Savoy Place, 27 October

Looks like a recession all right!

Andrew Dilnot opened the Annual Conference of the Royal Statistical Society’s User Forum by saying that ONS in Titchfield were the most beautiful and important people in the world.

Charlie Bean (Bank of England) said that in dealing with the ‘Great Contraction’ of 2008/09, the MPC had used three sources of information:  official statistics, regular business surveys and a network of regional agents with 8000 business contacts between them.  They had got nowhere near predicting the 6% fall for 2008/09.  Financial innovation had left risk concentrated in the banking sector.

While the media liked to talk of ‘two or more consecutive quarters of falling,output’, economists saw a recession as meaning unused resources.  The potential output was difficult to measure.  If one assumed that in general potential output evolved smoothly through time, then output was at present 10% below potential.  Previous banking crises had led to a 10% decline in output as against trend, lasting for 10 years.

Going forward, one would need more flexible financial data collection for macroprudential policies to be used successfully.  These presentation slides can be found here.

Not such a bad hit on employment this time round

 

Speaking on the media perspective, Michael Blastland said that it was marked by Aggregation (“It’s all debts innit?”) and Confirmation bias, whereby events were fitted to a default narrative based on folk memory of previous recessions.  So you had various Winters, also Springs, Summers and Autumns, Of Discontent.

Wage restraint, for instance, could be storing up trouble or an example of employer/employee cooperation, but in the media bleakness would be applied to everything.  There was great use of expressions like ‘it was last this bad X years ago’, which could of course just mean there had been X years of uninterrupted growth.

There was also the implausible conditional:  if all the banks are allowed to fail…we’ll be reduced to foraging for berries [but there would be some policy response to stop themn failing of course].

As for the banks, the narrative was like:  the money has gone–it’s irrecoverable–the debts must be cleared in full–we haven’t gained any assets.  Stephanie Flanders had correctly noted that the ‘toxic assets’ weren’t made of plutonium, they just didn’t have a market-clearingf price at present.

In essence, there were only two narratives allowed:

Sustained growth/Boom–‘The New Paradigm’

Recession–‘The Same Old Catastrophe’.

Ian Diamond (Aberdeen) spoke to ‘Recessions and their impact on society’, and said that it was very difficult, especially as you couldn’t do a RCT.  The increase in unemployment had been less than might be expected.  Those who were unemployed at 16-18 showed wage scarring at 23, recovery by 33, as small scar by age 43.  The effect was less for the high-skilled.

Lifelong learning improved wages and employment chances.  Many companies had increased training as part of their ‘job hoarding’ activity.

Poor economic conditions and low education were associated with crime.  Wages at the bottom of the distribution were inversely related to crime.  But it was more difficult to establish a direct crime-unemployment relationship.

As for health, poorer health for the unemployed was well-known, but was this causation and anyway one had to remember the ‘healthy worker’ effect, whereby some of the unemployed were unemployed because they were sick.  If one used Swedish data and worked very hard and controlled for confounding factors, one could show a relationship between unemployment and overall mortality and also suicide, but not mortality from CVD.

In summary, there was evidence of effects due to the recession, many of them mediated by unemployment or other forms of income reduction.  One needed the ability to construct large and complex datasets from multiple separate datasets.  For the future, one would desire a cadre of methodologists, a community of analysts, and a quantitatively-literate population.

On the role of Official Statistics, Stephen Penneck (ONS) said that gaps had been identified, for instance in liabilities to be included in the National Accounts.

An analysis of labour market flows showed that during the recession the rate of people entering jobs from unemployment had remained steady; it was an increase in the rate of leaving employment that had led to the rise in unemployment.  Now the rate of entering jobs was increasing.

He felt that in the first UK recession for 20 years the ONS had responded well; but the jury was still out, and there was room for improvement.

After lunch, in the parallel session on labour market statistics, Jamie Jenkins (ONS) said that GDP had gone down by 6% and employment by 4% this time.  Total employment had been held up by an increase in part-time employment,  which was entirely due to those who would like to work full time.

The last 3 recessions had been rather different.  In the 1980s the oil price shock and tight monetary policy had pushed down incomes.  In the 1990s interest rates had been used to control inflation and there had been the ERM debacle and an impact on the housing market.  In the last recession, demand had fallen sharply while inflation and interest rates remained low.  Perhaps this time we had been spared a wage-price spiral and consequent damage to employment.

Alastair Hatchett (IDS) said that in 2009  there had been a pay freeze in 1/3 of private companies and no freeze in 2/3;  it was more like 20% with a freeze in 2010.  The negatives had largely been concentrated in bonuses.  Freezes had been concentrated in certain areas (for instance, cars and components, media)–this explained why one heard so much about them in the media.

The median pay increase was 2% this year.  Pay cuts were very rare.

It made little sense to compare the public and private sectors directly–the public sector had a higher skill profile, 2/3 of public employees were women.  The gender pay gap had narrowed during the recession, but would increase as public sector pay was constrained.

From this talk, one got the impression that the problem with unemployment had been rather inflated in the media, and if you had some skills you had little to worry about.  But there was a lot of underemployment about, and one reason that unemployment had been contained was that people had been very frightened after the Lehman Brothers collapse and prepared to take anything.

Danny Dorling (Sheffield) then showed many maps (or rather cartograms) to illustrate the geographical extent of the recession.  Or rather, how things had been running up to the recession, since it was very difficult to get data that was both disaggregated and up-to-date.  He said that London was young, so you weren’t going to get insolvencies there, and people were desperate, so they weren’t going to go on strike.

The segregation index of Tory voters was at its highest since 1918.  This was a problem for them because they were piling up votes in constituencies they already held, and soon enough demons would arrive and carry them off to hell.  Geographically speaking, the difference between the elections of 1929 and 2010 was that London had gone Labour.

Equal areas~equal populations

Adults said that their well-being was highest in the home counties, while children seemed to have the best emotional health in the North, but Eric Pickles had just scrapped the corresponding survey.  Many things depended upon exactly what questions you asked–volunteering was low in London, while civic engagement (which included things like going to a meeting and complaining) was high.

John Fisher (Local Futures) then spoke about much the same kind of thing, but with less whizzy maps and frequent reference to Middlesbrough.  He was keen on promoting Output Area Classification as a free, open and transparent geographic data system.  He felt it was important to liberate and share locally sourced data.  Stoke was going backwards fast, while there was a cluster of growth in Central England but he wasn’t going to say where.

Carl Emmerson (IFS) wasn’t going to state the size of the hole in the public finances.  There was extra structural borrowing of 5.8% of GDP or £ 86 bn.

Better modelling and timely data would help.  Treasury forecasts were overly pessimistic when the economy was improving and overly optimistic when the economy was deteriorating.

At the end, Andrew Dilnot said that it was important really to find out what was going on, and really to understand it.  People who came to meetings like this were felt to be peculiar, not special, but in reality they were both.

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