UPDATE: Following up on a comment below, I used another data source, ONS JOBS02 for the labor market statistics. I report the findings below.


I read a series of articles related to the goings of the UK housing market, the likely effects of the new Help To Buy scheme, the 10% increase in mean London house price over the last year, and employment statistics. I failed to reproduce some numbers cited in the economist (below). This post talks about this.

It all starts with this blog post on the economist:

http://www.economist.com/blogs/buttonwood/2013/09/house-prices

It talks about many things, amongst which employment and housing completions, and how the UK seems likely to be embarking on another round of debt-fueled growth. I combined house completions and employment in construction and real estate industry into a single plot against time.

In the bottom panel, I find the increase in jobs in the real estate agents sector quite dazzling. In the top panel, you can see completed houses over time, split by who actually built them. I think HA (Housing Associations) and LA (local authorities) can be viewed as "public".




The economist blog has a quote from a report by Fathom Consulting:

The real estate sector accounts for almost of quarter of all the jobs created in the UK over the year to June. The rise in real estate employment in the latest quarter is the strongest on record. Over the past year the number of real estate jobs has risen by 77,000, the number of construction jobs is 1,000 higher, manufacturing is 14,000 lower. The number of real estate jobs is now at a record high – 100,000 more than at the peak of the boom in the summer of 2008. The number of construction jobs is more than 300,000 lower than its peak.
And so, the UK is going from a nation of shopkeepers to one of real estate agents. I had a look at this report of Fathom on the likely impact of Help To Buy (very interesting - no model description, see below), but couldn't find the one on the employment numbers cited above. The economist says it's in a "splendid piece of research last week", I couldn't find anything resembling that. Probably my fault. Or not.

By the way, the same citation appears in the telegraph.

I was unable to reproduce those numbers. My numbers are ONS employment statistics, table JOBS03, UK total. Everything is linked and document in my code.

My R code is in this github repo in a file called UKjobs.r

It would be interesting to know why our numbers are so different. I find an increase of "only" 28.000 real estate agent employees in the last year, as opposed to Fathom's 77.000. Even worse is my figure for change in that sector relative to summer 2008, with Fathom put at 100.000. I find a much more modest 21.000 increase of jobs in estate agents. This graph plots the difference of employment with employment in summer 2008 for both estate agents and construction.


There is no doubt that regardless of the eventual magnitude, this trend is striking. 

I have got to say though that the way the economist and Fathom put those numbers out there is strange. No source, no code, nothing. 
Notice that I'm not trying to say Fathom Consulting juke their numbers or don't do proper work (impossible to tell), most likely they just defined "Real Estate Sector" in a different way (I just took the column headed "Real Estate Sector"), or we used a different data set or whatever. 

But without knowing all of this, how I am to judge those informations? Of course I couldn't read their report (because that is only for paying customers, presumably containing all of those details), but the Economist uses them without any further qualifications. 

I think that in general, it would be very useful to have this metadata in a section on any Consulting's website, particularly if they get cited in the media. I can see that they want to sell their work to customers, but if they want to be participating in the public discussion, which is clearly in their interest, this stuff must be verifiable. 

UPDATE:
I have been told that the difference may arise by using table JOBS02 instead of JOBS03. As far as I can tell, the tables differ in the number of categories they have (JOBS03 has much greater detail). Both are according to SIC 2007 industry classification. JOBS02 is called "Workforce Jobs by Industry (seasonally adjusted)", JOBS03 is called "Employee jobs by industry".

I used ONS table JOBS02 to see whether I could get any closer to the 77.000 increase in real estate agent jobs reported by Fathom over the last year. Here is the data (d.realest is the quarterly difference in real estate jobs)

         date         d.realest       d.construct
1: 2012-03-01         2         -12
2: 2012-06-01         0         -42
3: 2012-09-01        13         -11
4: 2012-12-01         0         -11
5: 2013-03-01        13          11

This is a total of +28.000 over the last year. With regards to changes with respect to summer 2008, the JOBS02 data table produces the following graph, where we see that as of 2013-03-01 we have 39.000 more real estate agents than at 2008-06-01. I'm clueless as to how Fathom could get 100.000 instead of this number.


flo.
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  1. They're using the JOBS02 including self-employed - which makes sense. However, the sector includes all sorts of housing management - so will include the management of rented housing. In particular this includes social landlords trying to get tenants to pay rent when their housing benefit has been cut way below rent levels. The Summer 2008 looks odd - but that is affected by the change to SIC 2007 which affected this group a lot. Fathom may disagree with ONS on that.

    ReplyDelete
    Replies

    1. Hi Paul,
      thanks for your comment. I'm glad you point me to another data source, as this was too far off. Let me see if can produce an update with that other data source.

      Delete

    2. Paul, I've updated this post with data from JOBS02. I'm still 60K estate agents short of Fathom's 100K increase wrt 2008

      Delete

  2. Perhaps the explanation: selling (residential) real estate is a non-salaried, commission-only mode of employment, at least here in the US, and is thus not really "employment" from an earned wages point of view. IOW, yet another way, a real estate sales license is fairly easy to come by, and can be a near last-resort attempt to earn a living. When all else, including the dole, fails. Kind of like signing up to be a Herbalife, or other MTM, "distributor". It's a low barrier to entry, no wage, occupation. Is the UK different with regard to obtaining the chit sell houses?

    As the saying goes, when data and policy are in conflict, policy wins. That's how we in the US crashed to world's economy; the data said, "stop this nonsense!", but the policy said, "get your shekels while the picking is easy."

    ReplyDelete

  3. I think JOBS02 Workforce jobs by industry (seasonally adjusted) is the right table to use but you are not using the most recent data. You've got data up to Q1 2013 but there are Q2 data available and employment in the real estate sector rose by 50k over Q2 2013.

    ReplyDelete

  4. Hey Bobby. I've looked at the most recent data and you are right, the increase in real estate w.r.t the last quarter is 50K. The change wrt summer 2008 is still 90K. That IS closer to 100K reported by fathom. However, one wonders how they came up with that number (which is still too high) **before** the data you point me to were even published? I take it their report must have been written before the economist blog post (september). The data came out october 16.

    ReplyDelete
    Replies

    1. That would mean that they are frighteningly good at forecasting. The 77k increase over the past year matches the data exactly. It must have been that the data were out in September.

      Delete

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UPDATE: Following up on a comment below, I used another data source, ONS JOBS02 for the labor market statistics. I report the findings below.

I read a series of articles related to the goings of the UK housing market, the likely effects of the new Help To Buy scheme, the 10% increase in mean London house price over the last year, and employment statistics. I failed to reproduce some numbers cited in the economist (below). This post talks about this.

It all starts with this blog post on the economist:

http://www.economist.com/blogs/buttonwood/2013/09/house-prices

It talks about many things, amongst which employment and housing completions, and how the UK seems likely to be embarking on another round of debt-fueled growth.
10

For loss of a better place, I'll store my recipe for homemade pizza dough here. This will make dough for 14 people.

2kg strong white flour (no self-raising or other extras) 4 sachets of yeast, 7g each (not the super fast bicarbonate stuff) Salt Sugar Olive Oil Water The main problem is to get the right consistency, i.e. how much water to add. You'll have to do some experiments here.

I've got some questions regarding this issue, maybe someone out there has a clue.

The Austrian contingent was 300 out of 1000 soldiers

source: http://www.guardian.co.uk/world/2013/jun/06/israel-angry-austria-golan-heights.

Inspired by the Institute of Fiscal Studies' "Where do you fit in" application, where people can find out their position in the UK's income distribution, I wanted to find out how the picture in London looks like. Quite different. If you are in a very high percentile nationwide, high incomes of mainly financial sector employees in London make sure that you find yourself a couple of ranks further down.
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I just pushed the most recent version of the PSID panel data builder introduced a little while ago. Got some user feedback and made some improvements. The package is hosted on github.

News:

I added a reproducible example using artificial data which you can run by calling 'example(build.panel)'. This means you can try out the package before bothering to download anything and it provides a simple test of the main function.
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I got intrigued by the numbers presented in this news article talking about the re-trial in the Amanda Knox case. The defendants, accused and initially convicted of murder, were acquitted in the appeal's instance when the judge ruled that the forensic evidence was insufficiently conclusive. The appeals judge ignored the forensic scientist's advice to retest a DNA sample, because

"The sum of the two results, both unreliable… cannot give a reliable result," he wrote.

I just finished reading the extraordinary book tomorrow's table by P. Ronald and Raoul Adamchak. (I linked to Ronald's blog). In this post I wanted to quickly redo a calculation Adamchak does on page 16, where he explains to his students how much energy is required to produce the fertilizer used to grow one acre of corn using conventional agriculture (as opposed to organic methods).

Economists frequently use public datasets. One frequently used dataset is the Panel Study of Income Dynamics, short PSID, maintained by the Institute of Social Research at the University of Michigan.

I'm introducing psidR, which is a small helper package for R here which makes constructing panels from the PSID a bit easier.

One potential difficulty with the PSID is to construct a longitudinal dataset, i.e. one where individuals are followed over several survey waves.
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I was recently asked by a friend whether it's worth to buy a house in the UK. That is, assuming they could put down the money, whether it was worth buying as opposed to renting. Apart from obvious things like the expected length of stay in one place, the interest on mortgages and how prices might develop and so forth, they were interested in particular in the amount of transaction costs they were likely to face: fees, taxes and so forth.

So Paul Krugman laments in his post that policy makers across Europe have blindly signed up to the "Austerity only" ticket. He cites some evidence which I find fairly convincing. I just want to raise the point that what he says cannot be used as a critique against the Monti government.

Basically what he's saying is that Monti was installed as a puppet of European creditor nations to make sure that austerity would be imposed and the country's government debt would be continued to be serviced.
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