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From |
Autria Christensen <autria@yahoo.com> |

To |
"statalist@hsphsun2.harvard.edu" <statalist@hsphsun2.harvard.edu> |

Subject |
Re: st: Looping with the tin() function |

Date |
Mon, 2 Jul 2012 09:16:48 -0700 |

Inrange works!!! Thank you Nick and Steve!!! (I will make note of Nick's general comments for future postings). Have a great week everyone!!! Autria On Jul 1, 2012, at 2:23 AM, Nick Cox <njcoxstata@gmail.com> wrote: > Points of general note include: > > 1. References on Statalist are like references everywhere else. > Journal title, volume number, page numbers do no harm and their > absence is lack of information. > > 2. We can't access your data on your c: drive; it is much better to > replicate a problem with a mutually accessible dataset. > > 3. You give specific code (good) but don't say what the specific > problem with that code is. We can't comment easily on other problems > that occur with other code that you don't give us. > > 4. If you want the minimum or the mean, don't use -egen- to put the > constant result in a variable. Use the results from -summarize-. (This > is a style point.) > > su AIC, meanonly > gen opt_lag_aic = lag if AIC == r(min) > su opt_lag_aic, meanonly > scalar aic_lag = r(mean) > > 5. You should explain where user-written programs you refer to come > from. (-eststo-, -esttab-). > > I don't follow your general aim -- I rarely do time series forecasting > --- but if all else fails, you can evaluate scalars on the fly (as you > did for your -forvalues- loop, so that -tin()- sees their values, not > their names, and you can use -inrange()- as an alternative to -tin()-. > > . set obs 10 > . gen t = _n > . tsset t > . scalar foo1 = 4 > . scalar foo2 = 7 > > . l if tin(`= foo1', `=foo2') > > +---+ > | t | > |---| > 4. | 4 | > 5. | 5 | > 6. | 6 | > 7. | 7 | > +---+ > > . gen t1 = 4 > > . gen t2 = 7 > > . l if inrange(t, t1, t2) > > +-------------+ > | t t1 t2 | > |-------------| > 4. | 4 4 7 | > 5. | 5 4 7 | > 6. | 6 4 7 | > 7. | 7 4 7 | > +-------------+ > > Nick > > On Fri, Jun 29, 2012 at 10:08 PM, Autria Mazda <autria@yahoo.com> wrote: > >> I'm a first-timer and this is a re-post of a previously poorly explained problem I'm having, my apologies. >> (I'm trying to replicate Stock and Watson 2007, "Why Has Inflation Become Harder to Forecast" in case anyone is familiar with the paper). >> >> >> Data: I have a quarterly time series of gdp deflator data from 1960-2010. >> >> Objective: Ultimately, I'm trying to run a pseudo-out-of-sample forecast. >> >> What I'm currently doing: >> 1) Obtain the optimal lag length (based on AIC) over an initial sub-sample (e.g. 1960q1-1970q1) using varsoc. >> 2) Once I obtain the optimal lag length, I feed that into an AR(n) model. (Technically, n can change every quarter based on the varsoc results.) >> 3) I am able to do the above steps successfully but not efficiently with the code below. (Right now I'm just deleting the observations that are >> outside the sub-sample period before I run varsoc.) >> >> Problem: >> I need to run the regression over the sub-sample (1960-1970q1) use those parameters and model specification to forecast for the next quarter (1970q2). >> Then I need to store the forecast in a variable (e.g. f_cast_gdp_def) as the observation for 1970q2. >> Next I need to repeat steps 1 and 2 above and re-run the regression (this time over the sample period 1960q1-1970q2). >> Then forecast for 1970q3 and save that as observation 2 in variable f_cast_gdp_def, and so on and so forth for every quarter until the end of the sample. >> >> I looked into trying the rolling reg command but from my understanding of the documentation I don't think I can keep changing the model specification at each iteration. >> I think if I can figure out how to have tin() accept a variable, scalar or my loop var (t), then I can get what I need. My code is below. >> >> I've tried many syntax variants and either I get an error message: invalid syntax or stata just ignores the tin() function altogether and uses the entire sample. >> >> >> Any tips or advice would be greatly appreciated. Thanks again!!! >> >> Autria Christensen >> autria@yahoo.com >> >> >> use "C:\Stata Files\Thesis\Data\SW_Econ_Activity_Vars_Tab1-3.dta", clear >> forvalues t = `=tq(1970q1)'/`=tq(2010q4)' { >> preserve >> >> *set date range for optimal lag length selection >> drop if date < tq(1960q1) >> drop if date > `t' >> set more off >> varsoc gdpc96_yoy, maxlag(20) >> >> *Select optimal lag length and save as new scalar AIC_LAG >> matrix D = r(stats) >> svmat D, name(col) >> egen min_aic = min(AIC) >> gen opt_lag_aic = lag if min_aic == AIC >> egen store_a = mean(opt_lag_aic) >> scalar aic_lag = store_a >> disp "OPTIMAL LAG (BASED ON AIC) = " aic_lag >> >> *Run regression and store/output parameter estimates >> eststo one: arima gdpc96_yoy L(0/`=aic_lag').gdpc96_yoy, robust >> esttab one using "C:\Stata Files\Thesis\Data\Stats\test_`=end_date'.csv", cells("b se z p ci") stats(N ll chi2) nomtitle nonumber replace wide plain >> >> *Now I need to forecast for the period t+1 using parameter estimates and lags from period t >> gen fcast_date = `t' + 1 >> scalar f_date = fcast_date >> >> *I've tried using fcast_date and f_date but neither work the "predict" code below which doesn't really work >> predict static_yhat_AR if tin(`t', `t') >> predict dynamic_yhat_AR if tin(1970q2,2010q2), dyn(tq(1970q1)) >> >> est clear >> restore >> } >> > * > * For searches and help try: > * http://www.stata.com/help.cgi?search > * http://www.stata.com/support/statalist/faq > * http://www.ats.ucla.edu/stat/stata/ * * For searches and help try: * http://www.stata.com/help.cgi?search * http://www.stata.com/support/statalist/faq * http://www.ats.ucla.edu/stat/stata/

**References**:**Re: st: Looping with the tin() function***From:*Nick Cox <njcoxstata@gmail.com>

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