tag:blogger.com,1999:blog-7905515.post2643778032897907687..comments2024-07-03T02:33:39.550-05:00Comments on Falkenblog: Do Global Climate Models Contain Keynesian Macro Models?Eric Falkensteinhttp://www.blogger.com/profile/07243687157322033496noreply@blogger.comBlogger7125tag:blogger.com,1999:blog-7905515.post-55620922496902700572009-04-16T20:24:00.000-05:002009-04-16T20:24:00.000-05:00GT,
very thoughtful. My experience circa 1987-90...GT,<br /><br />very thoughtful. My experience circa 1987-90 was that no one was doing better than a VAR with GDP and Fed Fund difference lags. I do a lot of out of sample testing currently, but not of complex interactive systems like economies or climates. <br /><br />Maybe you can get them to work better. Great luck with that (seriously). <br /><br />EEric Falkensteinhttps://www.blogger.com/profile/07243687157322033496noreply@blogger.comtag:blogger.com,1999:blog-7905515.post-18335022945396279072009-04-16T19:27:00.000-05:002009-04-16T19:27:00.000-05:00The primary problem with macro models from the 197...The primary problem with macro models from the 1970s is that nobody paid attention to the requirement for the model to have a sensible 'steady state' - there was admixture of variables of different orders of integration. <br />A 'steady state' has 'sensible' characteristics which stem explicitly from theory - if left untouched the economy will eventually wind up on a path where all real variables will grow at the same rate, all nominal variables will grow at the same rate, with growth rates given by rates of technical progress and population growth. Relative prices in a steady state are constant. <br /><br />This results in a set of stylised facts that were not satisfied by 1970s macro models - for example 'money neutrality' (that a 1% increase in the money supply will not change long-run real outcomes... it will result in a 1% increase in all prices).<br /><br />A second problem is that right up until the 1990s most behavioural equations were estimated outside of their simultaneous context - variables which were endogenous to the system as a whole were treated as being exogenous during estimation. <br /><br />When I re-estimated a 'modern' macro model using 3SNLS, there were significant changes in the parameter vector - as one would expect - and the forecasting capability of the model was improved (assuming that the forecaster made perfect guesses at the exogenous variables) that is, running the model forward from the estimation dataset, and giving the model actual values for the exovars, resulted in paths for endovars that were a decent for to actual values for the endovars.<br /><br />Furthermore, 1970s models assumed better-than-unity stimulus from government spending, and had no intertemporal budget constraint - that is, government debt could increase without bound (and people would not be 'fooled', either).<br /><br />Simply attacking the modelling paradigm because a bunch of people didn't do it very well 30 years ago, is simply stupid - it is like saying that supersonic flight is impossible based on analysis of a Sopwith Camel.<br /><br />To the guy who worked on an IO model - congrats for contributing to a 1920's (Leontief) technology. You might not be aware that Leontief's grad student from the 1970s (Peter Dixon, who was my PhD supervisor) revised and extended IO modelling to incorporate technical/preference change and intertemporality... and is currently building a CGE model for the US State department.<br /><br />As to the idea that a macro model is 'underidentified' because it has more parameters than datapoints: well, that just means the model you're looking at is badly designed. The model I worked on - TRYM - had 13 behavioural equations, a dozen or so reaction functions and 80 identities (things which MUST hold - the components of GDP must add to GDP, for example). It was identified - by design. VAR models - the tools of frustrated mathematicians - are helped inordinately by the fact that steady-state type ideas are sensible - since the VAR model is really just a bare-bones reduced-form expression designed for people who think economics is glorified mathematics.<br /><br />Your statement about out-of-sample performance also belies some ignorance about how modelling is done. <br /><br />As a very first step: assuming you have a modern, properly identified model with a stable steady state, and you want to perform a forecast. <br /><br />How do you close the model (i.e., how do you choose your exogenous variables? (i.e., variables over which the agents in the model do not have any control)? <br /><br /><br />Then, how do you <B>forecast</B> the EXOGENOUS variables?<br /> <br />In reality, there ARE some things that are determined outside any model: until recently the modelling fraternity simply used the estimatio nclosure as its forecasting closure (not necessarily sensible) and then came up with a 'point forecast' of the matrix of endogenous variables required to close the model.<br /><br />Part of my (unfinished) PhD was to think a bit about the silliness of point-forecasting exovars: it makes no sense to use the mean if the distribution of the exovars might be skewed. Do you use the mode, perhaps? Not so fast - the mode of an asymmetric multivariate distribution is not necessarily the vector of the modes of the individual variables.<br /><br />My solution was to perform STOCHASTIC SIMULATION - but based on a set of realistic scenarios (which most US economists, being frustrated mathematicians first and foremost, don't think hard enough about).<br /><br />Then you do a gazillion simulations, and you get a distribution for the endovars - and you can then run a 'Bayesian ruler' over them to see if they make sense.<br /><br />When I did that (in 1998, with the press being all a-twitter about the Asian currency crisism the Russian default and and LTCM), I constructed what I thought were sensible scenarios for the Australian economy, estimated some distributions for those scecnarios, and ran the thing a bazillion times. The result was that the best guess for GDP for the Australian economy over the next 10 years was annualised growth of 4.1%, there was less than a 5% chance of recession and all of the probability mass said that unemployment was likely to FALL.<br /><br />Beginner's luck, perhaps. Let's just say that when I presented it at a grad seminar, I got lots of raised eyebrows, basedon the idea that the crisis would 'cause a depression in Asia'. <br /><br />ALL THAT being said, I absolutely agree that climate models are garbage - for the simple reason that a lot of the 'data' used to generate parameters is itself generated by a ethod that has a MAPE that any sensible modeller would find unacceptable - and the degree of simultaneity in the system is MUCH greater (nobody can agree on the causality chain between temperature and CO2 concentration for example: in the economic context it is like not knowing whether or not government spending in 1940 affects GDP in 1920).<br /><br />Cheerio<br /><br /><br />GTKratoklasteshttps://www.blogger.com/profile/08656600074436057305noreply@blogger.comtag:blogger.com,1999:blog-7905515.post-43214233398892150522009-04-15T21:28:00.000-05:002009-04-15T21:28:00.000-05:00Great minds. . . . I wrote a piece on my Streetwis...Great minds. . . . <A HREF="http://streetwiseprofessor.com/?p=44" REL="nofollow">I wrote a piece on my Streetwise Professor blog in December '06</A> pointing out the similarities between climate models and the big macro models. I was initially very interested in macro models when I started grad school at Chicago, but soon became very disillusioned with them. Unfortunately, it seems that climate scientists are more enamored with their models than economists were of theirs, as economists pretty much ditched the big models in a decade or so, whereas climate scientists just keep making theirs bigger without realizing that (as Lucas pointed out about macro models) the models have intrinsic flaws that can't be fixed by adding equations and parameters.Craig Pirronghttp://www.streetwiseprofessor.comnoreply@blogger.comtag:blogger.com,1999:blog-7905515.post-72546125021425216712009-04-15T09:43:00.000-05:002009-04-15T09:43:00.000-05:00高尚的普通話，您想要什麼？高尚的普通話，您想要什麼？Jhttps://www.blogger.com/profile/05676167615981895061noreply@blogger.comtag:blogger.com,1999:blog-7905515.post-10377456443678824472009-04-15T07:47:00.000-05:002009-04-15T07:47:00.000-05:00More degrees of freedom --> bigger data sets . ...More degrees of freedom --> bigger data sets . . .lancenoreply@blogger.comtag:blogger.com,1999:blog-7905515.post-72646627798285168952009-04-15T03:38:00.000-05:002009-04-15T03:38:00.000-05:00I was a FORTRAN programmer back in the early 70s a...I was a FORTRAN programmer back in the early 70s and was involved with several projects while in grad school.<br /><br />One was doing the programming for an 'input/output' model of the Iranian economy that a team in our Econ Dept was building at the request of the Shah's govt.<br /><br />The other was programming an equally complicated model a professor in the Physiscs Department was building to forecast 'monsoons' on the Indian subcontinent.<br /> <br />Superficially, both models were pretty much the same -- took thousands of historical data observations put them through some mathematical model and output some forecasts.<br /><br />Neither, as it turned out, was sucesfully able to predict. <br /><br />However,scientists the results from the monsoon model provided much input which factors could be ignored and which additional factors needed to be considred. It took them another ten years, but the ability to predict the monsoon greatly improved. <br /><br />Yes, it is pure outright socialism to work on complicated models in physics or economics.Anonymousnoreply@blogger.comtag:blogger.com,1999:blog-7905515.post-52565831705410678052009-04-15T00:31:00.000-05:002009-04-15T00:31:00.000-05:00Much money and effort was invested in the building...Much money and effort was invested in the building of the World Model by the Club of Rome in the seventies. Among other prophetic things, it showed that we would have run out of oil before 1992. The World Bank assumed it was going to be so, hunger will hunt the land. World modelling is an eternal illusion in the category of socialism, and each generation has to discover that it does not work, as you are doing now.Jhttps://www.blogger.com/profile/05676167615981895061noreply@blogger.com