Grrrrrrrrrr

by Jerome a Paris
Thu Jul 2nd, 2009 at 08:12:53 AM EST

“Current market disruption in financial markets and the more heavily regulated environment that is likely to follow can also be expected to have a permanent negative effect on potential growth, e.g. through reduced availability of capital for R&D and innovation activities.”

This is from a new European Commission study quoted by the FT but which I have been unable to find so far on the EU website and it makes for depressing reading - not because it warns of yet more Europe.Is.Doomed economic conditions, but because it still considers that unregulated high growth followed by massive crash is somehow better than a slower, steadier version and because it blames the worsened economic conditions of today on the cleanup of the financial mess, and not on the mess itself. It's truly depressing.


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Public Finances in EMU - 2009

which is 300 pages long...

With a brief summary here. Came out last week.

When locusts move on, they leave nothing behind

by afew (afew(a in a circle)eurotrib_dot_com) on Thu Jul 2nd, 2009 at 09:06:16 AM EST
Are you sure? I can't find the quote.

There's no such thing as original sin - Elvis Costello
by dvx (dvx.clt ät gmail dotcom) on Thu Jul 2nd, 2009 at 09:14:47 AM EST
[ Parent ]
Nor can I. Grrr.

Yet it's the same subject matter, and a major recent EC study.

When locusts move on, they leave nothing behind

by afew (afew(a in a circle)eurotrib_dot_com) on Thu Jul 2nd, 2009 at 09:17:16 AM EST
[ Parent ]
Google only turns up the FT as a source for those quotes. So the FT gets an exclusive peek?

When locusts move on, they leave nothing behind
by afew (afew(a in a circle)eurotrib_dot_com) on Thu Jul 2nd, 2009 at 09:55:54 AM EST
[ Parent ]
Or this could be 'creative' journalism.
by ThatBritGuy (thatbritguy (at) googlemail.com) on Thu Jul 2nd, 2009 at 10:09:42 AM EST
[ Parent ]
aka lying?

No-o-o-o...

When locusts move on, they leave nothing behind

by afew (afew(a in a circle)eurotrib_dot_com) on Thu Jul 2nd, 2009 at 10:16:41 AM EST
[ Parent ]
Certainly not! All those words you cite appear at least once somewhere in the report.

The FT is merely engaging in a bit of editing to improve reader understanding.

There's no such thing as original sin - Elvis Costello

by dvx (dvx.clt ät gmail dotcom) on Thu Jul 2nd, 2009 at 12:43:23 PM EST
[ Parent ]
European Tribune - Grrrrrrrrrr
it still considers that unregulated high growth followed by massive crash is somehow better than a slower, steadier version
Well, it is obvious why that is true.

Suppose you're doing econometrics and you want to estimate the "average rate of growth". As everyone knows since their school days, one of the first things you do to a data set is remove the outliers. And it so happens that, to an economist, the crisis is an outlier...

You do outlier removal on a series of 5,000 business days, taking away 0.2% of the sample and what do you get? A 50% larger average rate of growth.

A man of words and not of deeds is like a garden full of weeds; a man of deeds and not of words is like a garden full of turds — Anonymous

by Migeru (migeru at eurotrib dot com) on Thu Jul 2nd, 2009 at 09:33:21 AM EST
But... but... that's not how you average a time series...

- Jake

Tory Bliar for president prison!

by JakeS (JangoSierra 'at' gmail 'dot' com) on Thu Jul 2nd, 2009 at 10:08:28 AM EST
[ Parent ]
How do you average a time series?

A man of words and not of deeds is like a garden full of weeds; a man of deeds and not of words is like a garden full of turds — Anonymous
by Migeru (migeru at eurotrib dot com) on Thu Jul 2nd, 2009 at 10:09:17 AM EST
[ Parent ]
I would use a linear fit, excluding outliers, to get the average rate of growth. What you suggest that economists do is to take the average of the first derivative of the series, excluding outliers in that set. But an outlier in the first derivative only corresponds to an outlier in the second derivative if there is a corresponding first derivative outlier in the opposite direction within a very short span of points.

Thinking about it, it occurs to me that you shouldn't do it to an ensemble either... In fact, you shouldn't do it at all.

If you can get your hands on lower-order data, you fit to that. Partly because of the foregoing, and partly because higher-order data is always more noisy. Subtracting two large numbers from each other (which you have to do to obtain the higher-order data) gives a very high relative uncertainty on the result.

- Jake

Tory Bliar for president prison!

by JakeS (JangoSierra 'at' gmail 'dot' com) on Thu Jul 2nd, 2009 at 10:20:03 AM EST
[ Parent ]
people are not too interested in linear fits if it doesn't generate the same amount of money.
by Nomad on Thu Jul 2nd, 2009 at 12:35:43 PM EST
[ Parent ]
I would use a linear fit, excluding outliers, to get the average rate of growth.

A linear fit of what? There is only one variable here, assuming a stationary model, and that is the return of the index. If you remove the outliers to do the fit you get the same effect Taleb and Mandelbrot are illustrating.

A man of words and not of deeds is like a garden full of weeds; a man of deeds and not of words is like a garden full of turds — Anonymous

by Migeru (migeru at eurotrib dot com) on Thu Jul 2nd, 2009 at 03:40:19 PM EST
[ Parent ]
A linear fit of GDP (or of log(GDP) if you labour under the delusion that GDP must grow exponentially).

What your figure illustrates is what happens when you take the difference in GDP between any two measurements, subtract it, remove all outliers in that data set, and then average. If you remove all outliers in the GDP data set, and then run a linear fit you remove fewer points, and get less noisy data on your fit. What's not to like?

To illustrate: Suppose you have GDP numbers for twenty years, indexed to year 1 (indexing is merely a matter of units of measurement - it does not affect the behaviour of the data).

01    100   
02    099    -1
03    101    2
04    102    1
05    103    1
06    104    1
07    103    -1
08    102    -1
09    103    1
10    102    -1
11    104    2
12    100    -4
13    102    2
14    102    0
15    104    2
16    105    1
17    107    2
18    108    1
19    109    1
20    109    0

I want to fit the second column to the first column, after removing any outliers (there are none in this case). Your sarcastic suggestion is that economists might want to average the third column, after removing the -4 (because it is "obviously" an outlier).

- Jake

Tory Bliar for president prison!

by JakeS (JangoSierra 'at' gmail 'dot' com) on Thu Jul 2nd, 2009 at 05:55:47 PM EST
[ Parent ]
You can't do a linear fit of the observed variable to the time. Among other things because the successive values of the observed variable are not uncorrelated.

To a first approximation you can assume the succesive differences are uncorrelated, and then you could try to do a linear fit. Which in this case means an average of the 3rd column. And then you remove the outlier because it has a large Mahalanobis distance.

What you should try to do is filter (e.g., taking successive differences is a filter) the original series untill you get something that presumably is stationary and then fit some sort of ad-hoc model. ARIMA models are ways to reduce the model to some linear regression or other, and you always have the issue of outlier rejection.

A man of words and not of deeds is like a garden full of weeds; a man of deeds and not of words is like a garden full of turds — Anonymous

by Migeru (migeru at eurotrib dot com) on Fri Jul 3rd, 2009 at 06:02:51 AM EST
[ Parent ]
You're right, of course.

But then again, GDP growth isn't uncorrelated either...

- Jake

Tory Bliar for president prison!

by JakeS (JangoSierra 'at' gmail 'dot' com) on Fri Jul 3rd, 2009 at 12:26:16 PM EST
[ Parent ]
Migeru:
As everyone knows since their school days, one of the first things you do to a data set is remove the outliers.
Just in case it's not clear, I am being ironic.

It is true that outlier detection and rejection is taught in elementary statistics courses.

It is also true it is an outrageously bad idea to simply reject outliers.

And it is still a bad idea to reject outliers with justification because there is a strong risk of bias and of fitting an explanation to the data just to get rid of inconvenient points.

In fact, it is possible that outlier rejection and detection shouldn't be taught at all in elementary statistics.

A man of words and not of deeds is like a garden full of weeds; a man of deeds and not of words is like a garden full of turds — Anonymous

by Migeru (migeru at eurotrib dot com) on Thu Jul 2nd, 2009 at 11:18:33 AM EST
[ Parent ]
European Tribune - Grrrrrrrrrr
it blames the worsened economic conditions of today on the cleanup of the financial mess, and not on the mess itself
I think it blames the future worsened economic conditions on the cleanup of the mess, but that is actually correct, the cleanup has been botched. And it has been botched because of the mental capture of the cleaners by the messers.

A man of words and not of deeds is like a garden full of weeds; a man of deeds and not of words is like a garden full of turds — Anonymous
by Migeru (migeru at eurotrib dot com) on Thu Jul 2nd, 2009 at 10:08:40 AM EST
Whoever you hold responsible, economic recessions is going to affect every one, the developed and the developing.
by domitay on Fri Jul 3rd, 2009 at 05:39:20 AM EST


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