How can I tell if a Data Buffet time series contains nominal or real data? That is, are the values adjusted for inflation?
Many datasets are reported with multiple analytic variants (absolute vs. percent change vs. index, seasonal adjustment, etc.). For Data Buffet, particularly with national accounts presentations in our historical and forecast databases, the most significant variation is inflation adjustment. These come in pairs that are variously called:
- Nominal, current-dollar (*), current-price
- Real, constant-price, chained (**), inflation-adjusted
Which is which? There are three signatures to look for:
- In the unit-descriptor
- For U.S. series, a "$" specifier in the concept code
- For international series, the third letter in the concept code
1. Most importantly, examine the series description metadata. All descriptions have a parenthesized units-descriptor at the end. Real series show a currency reference year and/or the symbol "Ch." or "Chained," but nominal series don't. For example:
| GDPQ.IUSA |
Nominal |
Gross domestic product, (Bil. USD, SAAR) |
| GDP$Q.IUSA |
Real |
Gross domestic product, (Bil. Ch. 2009 USD, SAAR) |
| FCLQ.ICAN |
Nominal |
Private consumption for Canada, (Bil. CAD, SAAR) |
| FCL$Q.ICAN |
Real |
Private consumption for Canada, (Bil. 2007 CAD, SAAR) |
Similar symbology applies to derivative measures, such as percent changes and indexes. Series descriptions appear in Mnemonic 411, View mode, and Basket output. Basket headers can be configured to your liking, but we strongly recommend you always include the description and source.
2. For U.S. series, concept codes that contain the "$" character. Typically, a real-valued series has a "$" character near the end, before the adjustment and frequency characters (if any), but the corresponding nominal series doesn't. For example:
| Nominal | Real | Description |
|---|
| GDPQ.IUSA |
GDP$Q.IUSA |
U.S. gross domestic product (BEA NIPA) |
| EXSQ.IUSA |
EXS$Q.IUSA |
U.S. exports of services |
| FGDPQ.PA |
FGDP$Q.PA |
Gross state product for Pennsylvania (Moody's Analytics forecast) |
| FCLQ.ICAN |
FCL$Q.ICAN |
Private consumption for Canada |
| |
FGDP?$Q.^^ |
All real GSP series for all state forecasts (wild expression) |
Caveat 1: For legacy reasons, concept codes for U.S. datasets and forecasts are less consistent than concept codes for international historical datasets. That is, the same notion may be represented by different symbols or may not be marked at all. Please examine the description metadata; if that is unclear, please contact us.
3. For international series, the third letter denotes the broad type of measurement. The pair L/C indicates that the series is currency-valued, in the local currency, in nominal vs. real terms. Some countries use a secondary reporting currency, in which cases N/R and E/F denote nominal vs. real with U.S. dollars vs. euros. Hypothetically, you could see such pairs as:
| Nominal | Real | Description |
|---|
| NALEGDPUQ.IARG |
NACEGDPUQ.IARG |
GDP for Argentina in local currency |
| NANEGDPUA.IBIH |
NAREGDPUA.IBIH |
GDP for Bosnia and Herzegovina in USD (secondary reporting currency) |
| NAEEGNIUA.ISRB |
NAFEGNIUA.ISRB |
GNI for Serbia in EUR (secondary reporting currency) |
Caveat 2: We are progressively applying this symbology to U.S. series as party of regular dataset maintenance. Caveat 3: For certain legacy international series, the "$" specifier means "U.S. dollars (as contrasted to another currency)" or "U.S. dollar currency level (as contrasted to percentage)." This usage is being phased out as part of ongoing dataset maintenance. To be sure, always check the unit-descriptor.
Note
(*) Some sources use the generic terms "current-dollar" and "constant-dollar," even if the economy being discussed doesn't use a "dollar" currency.
(**) Strictly speaking, "constant-price" vs. "chained-price" are two different methods of inflation adjustment. A source will usually report only one method, but our symbology allows us to differentiate if a triplet -- current, constant, chained -- is reported. If a source changes its inflation methodology, we will post a "data change" article.
See also