Re: st: Looping with the tin() function

[Autria Christensen <autria@yahoo.com>]

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
>> }
>> 
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