|Unit||Mil. Ch. 2012 USD|
|Exports of Goods||2020 Q1||7,822,144||10,103,219||USD, NSA||Quarterly|
|Exports of Goods and Services||2019||1,375||1,165||Mil. USD||Annual|
|Imports of Goods and Services||2019||3,567||3,256||Mil. USD||Annual|
|Net Exports||2019||-2,192||-2,091||Mil. USD||Annual|
|Real Exports of Goods and Services||2019||1,316||1,143||Mil. Ch. 2012 USD||Annual|
|Real Imports of Goods and Services||2019||3,482||3,186||Mil. Ch. 2012 USD||Annual|
|Real Net Exports||2019||-2,166||-2,043||Mil. Ch. 2012 USD||Annual|
|Imports of Goods||Jan 2019||34,132,835||USD, NSA||Monthly|
For the U.S. insular territory of Guam, estimates of gross domestic product, GDP by industry and compensation by industry. These estimates were developed by the Statistical Improvement Program funded by the Office of Insular Affairs (OIA) of the U.S. Department of the Interior. For statistical purposes, Data Buffet considers Guam a country-type area.
The source writes:
The Bureau of Economic Analysis (BEA) released its first set of estimates of gross domestic product (GDP) for American Samoa, the Commonwealth of the Northern Mariana Islands (CNMI), Guam, and the U.S. Virgin Islands (USVI).
Objectively gauging changes in economic activity is difficult in the absence of comprehensive economic metrics, such as GDP. Until now, a framework did not exist to estimate the GDP of these four U.S. territories. The Statistical Improvement Program, funded by the Office of Insular Affairs (OIA) of the U.S. Department of the Interior, has made it possible for BEA to develop formal methodologies for measuring the GDP of the territories.
In constructing the estimates for the territories, BEA used methodologies consistent with the methods used to estimate U.S. GDP. Information from the Economic Census of Island Areas was used to establish levels of GDP for each territory for the years 2002 and 2007. Annual series were then developed and used to estimate GDP for the intervening years. Because the territories are not included in most of the major surveys used by BEA to estimate U.S. GDP, the support of government leaders in the territories and the assistance provided by the territorial statistical offices were critical to the successful production of these estimates.
In May, June, and July, BEA will be releasing additional detail on the major components of GDP at press events in each of the territories. Moving forward, the agreement between OIA and BEA will extend and improve the estimates of GDP.
For most NIPA components, the current-dollar estimates are derived from source data that are “value data,” where value = price x quantity. Frequently,BEA—which does not collect much of its own data—must adjust the data that are collected by others, primarily government agencies, trade associations, and international organizations. Most source data are collected for purposes other than the estimation of the NIPAs, and therefore use definitions, population parameters, or time periods that differ from NIPA concepts. Much of the data must be adjusted by filling gaps in coverage or by using available data as proxies for the desired NIPA measure.
For periods for which data are not available, NIPA estimates may be derived using existing estimates. For example, when annual data are available and the quarterly are not, the quarterly data are often estimated by interpolation. For the periods beyond those covered by annual estimates (such as the most recent quarter), the quarterly estimates are derived by extrapolation. These interpolations and extrapolations are often based on “indicators”—related data that are used to approximate movements in the NIPA measures.
Quantity and price estimates
Changes over time in the current-dollar measures provided in the NIPAs may reflect a change in quantity, a change in price, or a combination of both. For some analyses, it is important to know these separate effects—for instance, to know how much of the change in GDP is due to changes in the quantities of goods and services without the influence of price changes.
Therefore, the NIPAs provide separate estimates of changes in quantities and prices, derived as indexes that provide information on the change from some reference period. BEA describes estimates of quantities as “real” expenditures—for example “real GDP” or “real PCE.” Note that the level of an index in any single period is not in itself meaningful. Instead, it is the relation of that index level to the index level in another period—that is, it is the change in the index over time—that is important. Indeed, the change in real GDP over time is the featured measure of economic activity. In addition, BEA provides measures of the contributions of various components (such as personal consumption expenditures or investment) to GDP growth.
BEA also provides quantity measures in value terms—called chained dollars—by scaling the index. Specifically, the index in the reference year is set equal to the current-dollar level in the same year, and the change in the index in successive and previous periods is multiplied by the current-dollar level to form a time series in monetary terms.
To facilitate the analysis of the drivers of change in the real estimates, BEA provides measures of the contributions of real components to the percent change in real aggregates. These are provided because the chained-dollar measures of components are not additive,and therefore, accurate measures of a component’s contribution to change cannot be derived from the chained-dollar measures.
The source writes:
The BEA's first set of estimates of gross domestic product (GDP) for American Samoa, the Commonwealth of the Northern Mariana Islands (CNMI), Guam, and the U.S. Virgin Islands (USVI) are based on limited source data and are subject to revision.
In 2014, the BEA conducted their first comprehensive revision of the territorial econmic accounts. Revised estimates of GDP, GDP by industry, and compensation by industry are presented, extending back to 2002...
With the comprehensive revision, estimates for 2002 to 2013 have been revised in order to incorporate improvements to source data, including: