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used only because of calculational efficiency. It may be better to vary with the correlation dimension to maximize the power of the test.
In small samples or in series that have unusual distributions, the distribution of the BDS test statistic can be quite different from the asymptotic normal distribution. To compensate for this, EViews offers you the option of calculating bootstrapped p-values for the test statistic. To request bootstrapped p-values, simply check the Use bootstrap box, then specify the number of repetitions in the field below. A greater number of repetitions will provide a more accurate estimate of the p-values, but the procedure will take longer to perform.
When bootstrapped p-values are requested, EViews first calculates the test statistic for the data in the order in which it appears in the sample. EViews then carries out a set of repetitions where for each repetition a set of observations is randomly drawn without replacement from the original data. Also note that the set of observations will be of the same size as the original data. For each repetition, EViews recalculates the BDS test statistic for the randomly drawn data, then compares the statistic to that obtained from the original data. When all the repetitions are complete, EViews forms the final estimate of the bootstrapped p-value by dividing the lesser of the number of repetitions above or below the original statistic by the total number of repetitions, then multiplying by two (to account for the two tails).
As an example of a series where the BDS statistic will reject independence, consider a series generated by the non-linear moving average model:
yt = ut + 8ut − 1ut − 2 |
(11.29) |
where ut is a normal random variable. On simulated data, the correlogram of this series shows no statistically significant correlations, yet the BDS test strongly rejects the hypothesis that the observations of the series are independent (note that the Q-statistics on the squared levels of the series also reject independence).
Properties
Selecting View/Properties... provides access to the dialog controlling various series properties. Selecting this entry is equivalent to clicking on the Properties button on the series toolbar.
There are several tabs in the dialog. The first tab, labeled Display, allows you to set the default display characteristics for the series (see “Changing the Spreadsheet Display” on page 88). The Values tab may be used to define or modify a formula, turning the series into an auto-updating series, or to freeze the series values at their current levels (see “Defining an Auto-Updating Series” on page 150). The last Value Map tab should be used to assign value maps to the series (see “Value Maps” on page 163).
Label—333
In dated workfiles, the Freq Conversion tab will also be displayed. You may use this tab to set the default frequency conversion settings for the series. Recall that when you fetch a series from an EViews database or when you copy a series to a workfile or workfile page with a different frequency, the series will automatically be converted to the frequency of the destination workfile. The conversion options view allows you to set the method that will be used to perform these conversions (see “Frequency Conversion” on page 115).
Each series has a default up and down frequency conversion method. By default, the series will take its settings from the EViews global options (see “Dates & Frequency Conversion” on page 939) in Appendix A, “Global Options”, on page 937. This default series setting is labeled EViews default. You may, of course, override these settings for a given series.
Here, instead of using the global defaults, the high to low conversion method is set to Sum observations without propagating NAs.
Label
This view displays a description of the series object.
You can edit any of the field cells in the series label, except the Last Update cell which displays the date/ time the series was last modified. Each field contains a single line, except for the Remarks and History fields which can contain up to 20 comment lines. Note that if you insert a line, the last (of the 20) line of these fields will be deleted.
The Name is the series name as it appears in the workfile; you can rename your series by editing this cell. If you fill in the Display Name field, this name may be used in tables and graphs in place of the standard object name. Unlike ordinary object names, Display Names may contain spaces and preserve capitalization (upper and lower case letters).
See Chapter 10, “EViews Databases”, on page 261 for further discussion of label fields and their use in Database searches.
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Series Procs Overview
Series procedures may be used to generate new series that are based upon the data in the original series.
When working with numeric series, you may use series procs to resample from the original series, to perform seasonal adjustment or exponential smoothing, or to filter the series using the HodrickPrescott or band-pass filters.
For alpha series you may, use a series proc to make a valmapped numeric series. EViews will create a new numeric series and valmap
so that which each value in the numeric series is mapped to the original alpha series value.
Generate by Equation
This is a general procedure that allows you to create new series by using expressions to transform the values in the existing series. The rules governing the generation of series are explained in detail in “Series Expressions” on page 131.
It is equivalent to using the genr command.
Resample
The series resampling procedure selects from the observations in a series to create a new series (the resampled series). You may draw your new sample with replacement (allow a given observation to be drawn multiple times) or without replacement. When you select Proc/Resample... from the series window, you will be prompted to specify various options.
Input Sample
Describes the sample from which observations are to be drawn. The default is the current workfile sample.
If you select the Draw without replacement option, each row will be drawn at most once. This option requires the input sample to be at least as large as the output sample. If you do not select this option, each row will be drawn with replacement.
Resample—335
Output Sample
Specifies the sample into which the resampled series will be saved. Any value outside the output sample will not be changed. The default output sample is the current workfile sample. If you select the Draw without replacement option, the output sample cannot be larger than the input sample.
NA Handling
The default Include NAs in draws instructs EViews to draw from every observation in the input sample, including those that contain missing values. Alternatively, you may select the Exclude NAs from draws option so that you draw only from observations in the input sample that do not contain any missing values. Finally, the Exclude NAs from draws but copy NA rows to output option first copies matching observations in the input sample that contain missing values to the output sample. The remaining rows of the output sample are then filled by drawing from observations in the input sample that do not contain any missing values. This option keeps observations with missing values fixed and resamples those that do not contain any missing values.
Series Name
The new series will be named using the specified series name. You may provide a series name or a wildcard expression. If you use a wildcard expression, EViews will substitute the existing series name in place of the wildcard. For example, if you are sampling from the series X and specify “*_SMP” as the output series, EViews will save the results in the series X_SMP. You may not specify a destination series that is the same as the original series.
If another series with the specified name exists in the workfile, the values in the output sample will be overwritten with the resampled values. Any values outside the output sample will remain unchanged. If there is a non-series object with the specified name, EViews will return an error message.
Because of these naming conventions, your original series cannot be an auto-series. For example, if the original series is X(-1) or LOG(X), EViews will issue an error. You will have to generate a new series, say by setting XLAG = X(-1) or LOGX = LOG(X), and then resample from the newly generated series.
Weighting
By default, the procedure draws from each row in the input sample with equal probabilities. If you want to attach different probabilities to the rows (importance sampling), you can specify a name of an existing series that contains weights that are proportional to the desired probabilities in each row. The weight series must have non-missing non-negative values in the input sample, but the weights need not add up to 1 since EViews will normalize the weights.