In Data Buffet, each time series is identified by (named with) a mnemonic. Unlike arbitrary sequence numbers, our mnemonics meaningfully encode many (but not all) attributes of the series (including the statistical theme, measurement unit, adjustment, frequency and country). Systematic mnemonics ensure comparability (that is, grouping) between related series and continuity between successor series.
It is precisely this structure that makes bulk retrieval using basket wild cards possible—but sometimes we face a choice as to which attributes to emphasize. In such situations we assign a principal name, the canonical mnemonic, and one or more auxiliary names, called aliases.
Where do aliases appear in Data Buffet?
In Mnemonic 411, if you open an entry under the canonical mnemonic, any and all aliases will be listed in the "Overview" tab. Conversely, the entry for the alias will not show the canonical mnemonic. For example, compare ET.US versus ET.IUSA.
In the catalog, series are listed by canonical mnemonic, but the "find in catalog" search mode will also locate them via alias.
In basket output, the "Mnemonic" header field will show the mnemonic requested, whether canonical or alias (that is, whatever you entered in the basket editor). It cannot show if you used an alias.
Under what circumstances does Moody's Analytics use aliases?
1. Forward compatibility with new series
As we expand Data Buffet, we encounter new opportunities to either differentiate or group series by their mnemonics. With more dimensions to identify, old naming standards may not suffice, nor prevent "false positive" wild card matches, i.e., similar mnemonics that retrieve unrelated series.
In one such situation, our original standard was to name all series at the national U.S. level using the geo code "US". When we later added international coverage, we created four-letter geo codes like "ICAN" (Canada) and "IJPN" (Japan). To facilitate retrieval of all national (as opposed to subnational) series using the geo wild card "I^^^", U.S. series needed the geo code "IUSA".
For example, U.S. forecast total nonfarm employment is identified by canonical mnemonic FET.US (kept to serve legacy baskets) and by alias FET.IUSA (for harmony with the newer geo code standard).
2. Backwards compatibility when harmonizing series
Long ago, we named interest rate series using the prefix "R·". Later we rededicated "R·" exclusively to our proprietary estimates, and renamed the older series under "IR·" -- but because they were widely used, we applied aliases to preserve legacy retrievals.
For example, the secondary market yield of six-month T-bills (per the daily H.15 report) is now named IRTB6MD.US but preserves its original name RTB6D.US as an alias. (Note: This will change after the great "US/IUSA transition" of July 1, 2017; see related article).
We do this only in select situations. More often, we decide that continued use of the older, non-standard mnemonic is too problematic, so we rename outright with no recourse. If so, continued use will elicit "series not found" error messages, and you will need to edit your basket or other retrieval.
We document these operations either in dedicated "Mnemonic Change" articles on Data Buffet News, or as secondary topics in "New Data" and "Data Change" articles. The articles state whether we have applied aliases or not, and will describe an explicit concordance or a renaming rule. The basket editor provides a "find and replace" tool that can often help.
3. Global concept aliases
For select major indicators, we have identified representative series from individual country catalogs and assigned short aliases. This doesn't guarantee the indicators are strictly comparable (they may differ in frequency, scale and scope) but rather serves to expedite cross-country retrieval. They appear in the top-level catalog called "Global Concept."
For example, total population:
- POP.IFIN = VSQPOPA.IFIN = Thousands of persons, end-of-year, Finland
- POP.IGBR = VSQPOPTA.IGBR_X = Single persons, mid-year, U.K.
- POP.I^^^ = wild card expression to retrieve all available series at the national geo level
4. Brevity
A dataset with numerous dimensions dictates a lengthy mnemonic (we do not necessarily harvest all available detail, but arrange to be forward-compatible). In select cases, we can assign an equivalent mnemonic using a shorter or more general scheme, which is easier to type and to read.
For example, under ESA 1995 sector accounts, gross value added for the total economy for Latvia uses mnemonic NALNPTEBGVATUQ.ILVA, which also encodes the table and direction. This measure happens to be equivalent to GVA under the simpler national accounts output approach, which has a shorter and more familiar mnemonic we assigned as an alias: NALSGVATUQ.ILVA.
5. Source identifiers
When our sources have unique identifiers for their series, we sometimes borrow them to serve Data Buffet clients who are familiar with the nomenclature, and as a form of documentation. (In practice, we modify the source's identifier to suit our database.)
For example, the Statistics Canada "vector" for total merchandise exports from Canada is named V54056200, so we've aliased "V54056200." (note the period) to the series known canonically as TRLXMMTUM.ICAN. (Additionally, its global concept alias is TREG.ICAN.)
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