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Aggregate data is high-level data which is acquired by combining individual-level data. For instance, the output of an industry is an aggregate of the firms’ individual outputs within that industry. [1] Aggregate data are applied in statistics, data warehouses, and in economics. There is a distinction between aggregate data and individual data.
In input-output analysis, disaggregated data on gross and net outputs of different economic sectors and sub-sectors is used to study the transactions between them. Thus, for example, a sector purchases inputs from several other sectors and sells outputs to several other sectors.
Economic data are data describing an actual economy, past or present. These are typically found in time-series form, that is, covering more than one time period (say the monthly unemployment rate for the last five years) or in cross-sectional data in one time period (say for consumption and income levels for sample households).
Aggregators who agree with information providers to extract data without using an OFX standard may reach a lower level of consensual relationship; therefore, "screen scraping" may be used to obtain account data, but for business or other reasons, the aggregator may decide to obtain prior consent and negotiate the terms on which customer data is ...
The aggregation problem is the difficult problem of finding a valid way to treat an empirical or theoretical aggregate as if it reacted like a less-aggregated measure, say, about behavior of an individual agent as described in general microeconomic theory [1] (see representative agent and heterogeneity in economics). The second meaning of ...
The data of concern to economic statistics may include those of an economy within a region, country, or group of countries. Economic statistics may also refer to a subtopic of official statistics for data produced by official organizations (e.g. national statistical services, intergovernmental organizations such as United Nations, European Union or OECD, central banks, and ministries).
Data reduction is the transformation of numerical or alphabetical digital information derived empirically or experimentally into a corrected, ordered, and simplified form. . The purpose of data reduction can be two-fold: reduce the number of data records by eliminating invalid data or produce summary data and statistics at different aggregation levels for various applications
Seasonal adjustment or deseasonalization is a statistical method for removing the seasonal component of a time series.It is usually done when wanting to analyse the trend, and cyclical deviations from trend, of a time series independently of the seasonal components.