tag:blogger.com,1999:blog-3621026.post3495653592004938272..comments2021-06-09T15:25:30.961+02:00Comments on Robert's Stochastic thoughts: Roberthttp://www.blogger.com/profile/14455788499385673507noreply@blogger.comBlogger4125tag:blogger.com,1999:blog-3621026.post-76868728109832697902012-04-13T18:52:54.923+02:002012-04-13T18:52:54.923+02:00thanks for response.
You know, I hadn't real...thanks for response. <br /><br />You know, I hadn't really thought before about the assumption embedded in these models that policy (monetary, fiscal) has no long-run impact on important real variables like say unemployment or the distribution of real wages. I had previously thought, if I thought about it at all, that was okay because they are supposed to be models of the short-run, used for thinking about how to respond to shocks, not models used for thinking about the long-run and how policy shapes the economy, and haven't thought about what effect policies inspired by these models are having ... I was intrigued by interfluidity's argument that inflation target has held down wage growth ... I would like to see research in that area, maybe it already exists I don't know.Luis Enriquehttps://www.blogger.com/profile/09373244720653497312noreply@blogger.comtag:blogger.com,1999:blog-3621026.post-30847042532011745682012-04-13T01:22:59.908+02:002012-04-13T01:22:59.908+02:00Uh I should know that too. But I don't. I do...Uh I should know that too. But I don't. I don't do any work with time series. I do the sort of macro theory I denounce. I do simle cross country regressions. I do some regressions with micro data. I analyse data on professional forecasters. I never ever forecast.<br /><br />I will try to answer your question, but be warned that I don't know what I am talking about. <br /><br />I agree with your hypothesis about what actual macro econometricians do. It isn't very hard if you only allow as many different kinds of shock ( technology, aggregate demand, money supply etc) as you have time series (GDP, total hours worked, price level, wage level, interest rate). Then you can solve for the shocks. <br /><br />It is harder if you have many dimensions of shocks as in adding measurement error for each of the varibles. Then the same change in time series can be due to many different combinations of shocks. Fortunately, a probability distribution of shocks is assumed, so you can get a posterior distribution conditional on the data so far. Then to forecast you integrate.<br /><br />But really really very often the model which confronts the data is a linear approximation to the theoretical model near The steady state. This often means that the model used to forecast is a vector autoregression (just regress current values of the variables on a few lags of that variable and all the other variables). The role of all the fancy theory is often just to get restrictions on these regressions. Forecasting is just the fitted value of the regressions. The role of theory is, say, changes in expected inflation must be innovations (unpredictable) given the rational expectations assumption. Or say the long run effect of monetary policy on output must be zero, so some sum of products of coefficients must add up to zero.<br /><br />Note that the policy advice is based on the assumption made for convenience that there is only one possible steady state (why I capitalized The) and the untested imposed assumption that the effects of monetary policy on real variables don't last.<br /><br />The bottom line advice is focus on fighting inflation, because nothing else lasts, as we assumed for convenience and convention.Roberthttps://www.blogger.com/profile/14455788499385673507noreply@blogger.comtag:blogger.com,1999:blog-3621026.post-40331152268700999462012-04-12T14:58:07.930+02:002012-04-12T14:58:07.930+02:00oh, I think I figured it out - you just say GDP (o...oh, I think I figured it out - you just say GDP (or whatever) fell x% from date 1 to date 2, and work out what kind of shock would be needed in the model to replicate that, and then that's your shock. <br /><br />am I right in thinking there's sort of room for double-the-error here that it must be hard to disentangle? first to the extent that the model is wrong you will impute the wrong magnitude of shock, second to the extent that the model is wrong you will predict the wrong response. <br /><br />I'm still confused though - because if GDP falls again from date 2 to date 3, more than the model predicts, what stops you from saying aha another shock must have hit (or the shock must have persisted)?Luis Enriquehttps://www.blogger.com/profile/09373244720653497312noreply@blogger.comtag:blogger.com,1999:blog-3621026.post-83021506947138547432012-04-12T12:24:10.408+02:002012-04-12T12:24:10.408+02:00There's something very fundamental I don't...There's something very fundamental I don't understand about testing the predictive power of DSGE and similar models, which I ought to understand and would be grateful if you could explain. Please try to ignore that as a so-called economist myself I should know this already.<br /><br />These models start by presuming shock processes that drive everything. These models were inherently incapable of predicting the financial crisis, unless by predict you mean "assume a shock process with the occasional very large negative shock." Then you can say, our models says there's going to be a crisis! Not sure when. <br /><br />Once the shock has hit, the predictions of these models hinge on how large a shock you assume has hit the system, its persistence, and any subsequent shocks etc. How do the people who "test" these models first decide what sort of shock the system has been hit with, before they can then evaluate the consequent predictions?Luis Enriquehttps://www.blogger.com/profile/09373244720653497312noreply@blogger.com