# How Strong is the Blanchard, Cerutti and Summers Evidence for Hysteresis ?

A comment on

Olivier Blanchard, Eugenio Cerutti, and Lawrence Summers: Inflation and Activity–Two Explorations and their Monetary Policy Implications:

update: Anne in comments said it was impossible to understand what, if anything, I concluded. My conclusion ~~is ~~ was that Blanchard, Cerutti and Summers have found striking evidence of hysteresis. They reject the null hypothesis that GDP is a stationary AR(2) around a quadratic trend. It is true that I came up with the null (they don’t do formal hypothesis testing) based on what I guessed they had in mind. In any case, I personally am reassured that they are on to something.

end update:

Major update: I have been playing with the program. I find that the proportion of simulated recessions followed by lower output (as defined by BCS) is very sensitive to assumptions about trends and persistence of shocks. I no longer draw any particular conclusion from my effort.

end update:

While I really like the non-parametric approach of ” we look at 122 recessions over the past 50 years in 23 countries. We find that a high proportion of them have been followed by lower

output or even lower growth. ” I worry that this might happen even without hysteresis.BCS do not consider the distribution of their statistic under the no hysteresis null. This isn’t hard to do — just simulate data with a trend stationary process and do the calculations.

update 5

This also isn’t very useful. Without details, it is possible to make a large fraction of recessions be followed by lower output as defined by BCS by playing with assumptions about the trend stationary process. I am deleting my first effort to do this (there was a bug in the program) and just reporting that (as usual) if one makes arbitrary assumptions, one can get arbitrary results.

[deleted stuff]

I don’t think this worries BCS, because they know ~~that GDP is very far from a trend stationary AR(1) with coefficient 0.5.~~ how common the pattern is given standard models with standard parameters.

I did a more serious effort to check the distribution of their statistic under their null. I model log GDP as an AR(2) around a quadratic trend. Coefficients estimated with US data

AR coeffs rho1 = 1.328043 ; rho2 = -0.3781878; trend tr=.0105446 per quarter ;

-0.000009077 per (quarter -1947) squared. SE of disturbance to get roughly the right number of recessions.

update 3: new simulations here too

update 6: newer simulations.

27,700 pseudo recessions of which 15,172 = 54.8 % are followed by low output. For the reasonable null hypothesis with parameters based on data, the fraction with low output as defined by BCS is ~~about~~ very roughly what they would hope (to be cautious they round down their estimated trends by one standard deviation).

the Gauss file which I used for the simulations [was] after the jump (yes I still use Gauss)

update 4: jmg points out that the Gauss code was messed up. It seems that wordpress assumed it was html code and rendered it. I won’t try to post the Gauss code.

Gosh, I would like to understand this essay but the writer provides no summary statement and so I am completely lost.

anne:

I am sure Robert will come back to you. I would like to hear the explanation also.

I think there are some faulty do while and if conditions in your Gauss code.

For example:

“do while iii iii =iii+1;”

“if (ii>25)*(ii0.5 ;”

“if (y[ii] recessions =recessions|(ii-2);”

“do while jj jj=jj+1;”

“if yf nlow=nlow+1; “

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Is it a settled issue that the optimum governmental funding model, if you want a progressive civilized society, requires income taxes?

Is it not possible the slower growth we are now seeing worldwide, with the notable exception of China, is a function of an obsolete funding model?

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Avraam Jack Dectis:

Welcome to AB. First comments always require approvals. You are free to post as you wish.

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And, ( I should have added since it is what made me comment ) , has anyone modeled such alternatives?

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