In Econometrics and Finance analysis of large sets of data is required in order to identify the various financial indices.
In this article, we will cover the various types of data used in the field of econometrics including Cross-sectional data, time-series data, and pooled data. In this way, you will gain a better understanding of each one of them and where these can be used.
There are three types of data on which the econometric analysis are done:
1. Cross-sectional data – observations on one or several variables at a single point in time
Obesity levels in a population at a single point in time, Surveys and government records are some common sources of cross-sectional data. The datasets record observations of multiple variables at a particular point in time. Financial Analysts may, for example, want to compare the financial position of two companies at a specific point in time.
2. Time Series data – observations on one or several variables over time
Stock prices, money supply, GDP, sales figures
3. Panel data(or Longitudinal data) – multi-dimensional data involving measurements over time. It’s a combination of time series and cross-sectional data.
panel data is multi-dimensional data of an observation that is measured repeatedly over time.
property 1: the same objects/individuals are observed repeatedly
property 2: multiple variables are measured of those same individuals/objects
property 3: the observations take place at multiple points in time
International trade tables, world socioeconomic tables, currency exchange rate tables. Public health insurance data, disease survival rate data, child development, and well-being data.
Two advantages of longitudinal surveys are the following:
• It is possible to actually measure individual change (not just averages).
• Such surveys do not depend on people’s memories about what they did some time ago.
