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In usinfl. Louis FRED database. I generate recursive forecasts for these models beginning in q2. This implies an initial window size of observations from q1 to q1. The choice of the window size for computing forecasts in applied research is arbitrary.
See Rossi and Inoue for tests of predictive accuracy that is robust to the choice of window size. Line 1 defines the name of the command and declares it to be rclass so that I can return my results in r after executing the command. Line 2 defines the syntax for the command. I specify an if qualifier in the syntax so that my command can identify the correct observations when used with the rolling prefix.
Lines 4—6 store the time variable and the beginning time index in my dataset as local macros timevar and first , respectively. Lines 8—9 use regress to fit an AR 2 model and summarize the time variable in the sample used for estimation. Line 11 stores the last time index in the local macro last.
Lines 12—14 store the forecast in a local macro fcast. Lines 16—19 return the forecasted value, actual value, and the squared error in local macros fcast , actual , and sqerror , respectively. Line 20 specifies the end of the command. The structure of this command is similar to the AR 2 I described earlier. Lines 13—19 store the one-step-ahead forecast in local macro fcast. I specify a window size of and store the estimates in the dataset ar2. With a window size of , I have 55 usable observations that are one-step-ahead forecasts.
I merge the two datasets containing the forecasts and label the actual and forecast variables. I plot the actual versus the forecasts of dinflation obtained from an AR 2 and a VAR 2 model respectively. Both models produce forecasts that track the actual change in inflation.
However, the performance of one forecast from the other is indistinguishable from the figure above. A popular statistic used to compare out-of-sample forecasts is the MSFE. I use the mean command to compute this. This comparison, however, is based on a single sample and does not reflect the predictive performance in the population. McCracken provides test statistics to test the predictive accuracy of forecasts generated by a pair of nested parametric models.
Under the null hypothesis, the expected loss of the pair of forecasts is the same. Under the alternative, the expected loss of the bigger model is less than that of the one it nests. The limiting distribution of both test statistics is nonstandard. I compute the OOS-F statistic below:. Under the null hypothesis, forecasts from model 1 encompass that from model 2; thus forecasts from the latter model contain no additional information. Under the alternative hypothesis, forecast from model 2 contain more information than that from model 1.
I compute the ENC-New statistic below:. In other words, unemployment rate is useful for forecasting inflation rate. In this post, I used the rolling prefix command to generate out-of-sample recursive forecasts from an AR 2 of changes in inflation and a VAR 2 model of changes in inflation and unemployment rate. Login or Register Log in with. Forums FAQ. Search in titles only. Posts Latest Activity. Page of 2. Filtered by:. Sebastian Eiblmeier.
Calculations within columns 25 Mar , Hello, I'm relatively new to Stata, so this might be a dumb question. However, via google search I couldn't find anything helpful. What I want to do is to do calculations within columns. For a start I have the following table: I'd like stata to multiply the values of those rows where indicator! Lateron I'll have more complicated within column calcuations coming up. Is there any smooth way to do this? Tags: None. Nick Cox. Columns is spreadsheet jargon for what Stata calls variables.
Screenshots don't work well here and are not easy for people to use in replies. A data example posted with dataex would make a detailed reply easier and indeed more likely. Comment Post Cancel. Carlo Lazzaro. Sebastian: as Nick said, screenshots can only delay helpful replies.
That said, for calculations implying variables as well as observations , you may wantb to take a look at -help egen-. Sebastian Geiger. Sebastian, I'd say your dataset is not probably organized for what you're trying to do and for the use of Stata in general. In a panel like your, the indicators should generally be the titles of the "columns" and the years should be in the the "rows". There may be applications where your data structure is appropriate, but for your calculation it is not.
Difference of means in stata forex | Perhaps you want something like Code:. Rossi, B. Search in titles only. That's my favourite. A popular statistic for forecast comparison is the mean squared forecast error MSFEa smaller value of which implies a better forecast. Out-of-sample forecast tests robust to the choice of window size. Columns is spreadsheet jargon for what Stata calls variables. |
Difference of means in stata forex | 72 |
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This goes for all data and counties. I repeat tat I work on a macro panel that contains 55 countries for a time length of about 20 years and need the first difference of a number of variables. Thanks abc.. RedOwl New Member Dec 20, I don't see anything wrong with Maarten's solution, but I don't have your data to allow me to do any diagnosis.
Last edited: Dec 21, Here is a toy example of Maarten's approach. Note that tsset can only accept numeric variables, so you need a numeric variable for country. RedOwl said:. Now I am very worried. You should never have to do something like x - L. If that "solves" your problem, i. If you tried RedOwl's example as is and added your "solution" at the bottom you will see that it to leads to missing values at the first observation of each country, as it should: how can you compute a difference with a previous value, if you are the first and by definition no such previous value exists?
You must log in or register to reply here. It is important to note that we have to list all variables which we want to report as omitting any variable from the list will cause asdoc to omit that variable from the output table. Let us use the auto dataset from the system folder and estimate two regressions. As with any other Stata command, we need to add asdoc to the beginning of the command line.
We shall nest these regressions in one table, hence we need to use the option nest. Also, we shall use option replace in the first regression to replace any existing output file in the current directory. Therefore, the variables are listed in this order inside the keep option. The code and output file are shown below. Option keep is also used for reporting only needed variables, for example, we might not be interested in reporting coefficients of year or industry dummies.
In such cases, we shall list the desired variable names inside the brackets of the keep option. Again, the variables will be listed in the order in which they are listed inside the keep option. Two queries 1. To identify the overall significance of model. Both asdoc and outreg do not report it in table. If you can guide please. Can we add t-test or any other test for mean difference with in same regression table. For example, if we regress 5 portfolios and at last we are interested in testing mean difference of Port-1 and Port Fa: For your first query, I would refer you to the help file of asdoc, Section 4.
Regressions, subsection 4. You can use option stat for reporting any statistic from the e macro. These statistics are usually revealed by typing. The macro for F-statistic is e F. So if you wish to report it with asdoc, you can use option stat F.
For your second query, I would refer you again to the help file of asdoc, Section 4, subsection 4. You can use option add to add up to three lines of additional text and statistics. This option adds text legends to the bottom cells of the nested regression table. The text legends should be added in pairs of two, each one separated by a comma.
So to add mean of a variable to the regression table, see how I use this option. First, I create the mean with sum command, write it to a local named as mean1 , and then add additional text and the local in the add option. Right now this option needs some additional tweaks as it deletes decimal points, therefore, I have written the above macro with zero decimal points. I shall work on it sometime in future. Dear Mr.
This is a great addition and I used it successfully many times. However, there seems to be a problem with asdoc when using a mixed model for analyzing panel data. For some reason, it gives me an error message. Befristetwithin is part of my analyses, which im trying to estimate as a random effect. I think there could be an issue with the highlighted part of my regression.
It would be great and i really appreciate it, if you could give me any advice on how to solve this issue. Thanks for the feedback. I have changed asdoc and uploaded a new version to SSC. Please install it by. In-text citation Tables were created using asdoc, a Stata program written by Shah Bibliography Shah, A.
Can w replace tstat instead of standard errors while reporting our results in Stata? Farah Zamir The option rep t can be used for reporting t-statistics when making a nested regression table. Thank you for your dedicated introduction of asdoc. Its user friendlyness and concise helpfiles make it a great addition to Stata. I have a question regarding the significance stars. I think that this is because the regression coefficients are exponentiated while the standard errors are not; hence the stars are reported over the wrong franction — but this is just a guess.
Dear Bram Hogendoorn Thanks for your kinds words and pointing out this bug. The problem occurs in cloglog regression when using option eform and nest together. I shall rectify the error soon.