Aggregate data in the context of "Areal unit"

A macroeconomic model is an analytical tool designed to describe the operation of the problems of economy of a country or a region. These models are usually designed to examine the comparative statics and dynamics of aggregate quantities such as the total amount of goods and services produced, total income earned, the level of employment of productive resources, and the level of prices.

Macroeconomic models may be logical, mathematical, and/or computational; the different types of macroeconomic models serve different purposes and have different advantages and disadvantages. Macroeconomic models may be used to clarify and illustrate basic theoretical principles; they may be used to test, compare, and quantify different macroeconomic theories; they may be used to produce "what if" scenarios (usually to predict the effects of changes in monetary, fiscal, or other macroeconomic policies); and they may be used to generate economic forecasts. Thus, macroeconomic models are widely used in academia in teaching and research, and are also widely used by international organizations, national governments and larger corporations, as well as by economic consultants and think tanks.

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). Data may also be collected from surveys of for example individuals and firms or aggregated to sectors and industries of a single economy or for the international economy. A collection of such data in table form comprises a data set.

Methodological economic and statistical elements of the subject include measurement, collection, analysis, and publication of data. 'Economic statistics' may also refer to a subtopic of official statistics produced by official organizations (e.g. statistical institutes, intergovernmental organizations such as United Nations, European Union or OECD, central banks, ministries, etc.). Economic data provide an empirical basis for economic research, whether descriptive or econometric. Data archives are also a key input for assessing the replicability of empirical findings and for use in decision making as to economic policy.

Vital statistics is accumulated data gathered on live births, deaths, migration, fetal deaths, marriages and divorces. The most common way of collecting information on these events is through civil registration, an administrative system used by governments to record vital events which occur in their populations. Efforts to improve the quality of vital statistics will therefore be closely related to the development of civil registration systems in countries. Civil registration followed the practice of churches keeping such records since the 19th century.

This article covers mainly the US, UK and Canada, with references to global standards.

The Lucas critique argues that it is naive to try to predict the effects of a change in economic policy entirely on the basis of relationships observed in historical data, especially highly aggregated historical data. More formally, it states that the decision rules of Keynesian models—such as the consumption function—cannot be considered as structural in the sense of being invariant with respect to changes in government policy variables. It was named after American economist Robert Lucas's work on macroeconomic policymaking.

The Lucas critique is significant in the history of economic thought as a representative of the paradigm shift that occurred in macroeconomic theory in the 1970s towards attempts at establishing micro-foundations.

In medical research, epidemiology, social science, and biology, a cross-sectional study (also known as a cross-sectional analysis, transverse study, prevalence study) is a type of observational study that analyzes data from a population, or a representative subset, at a specific point in time—that is, cross-sectional data.

In economics, cross-sectional studies typically involve the use of cross-sectional regression, in order to sort out the existence and magnitude of causal effects of one independent variable upon a dependent variable of interest at a given point in time. They differ from time series analysis, in which the behavior of one or more economic aggregates is traced through time.