Foundations & Databeginner

Types of Economic Data

Applied work uses four data structures. A cross section samples many units at one point in time. A time series follows one unit across many periods. A pooled cross section stacks separate cross sections from different years. A panel, or longitudinal, dataset follows the same units over time. The structure dictates the assumptions and the method, so naming it correctly is the first step of any analysis.

Why it matters

Picture a spreadsheet. One snapshot of 1,000 different workers this year is a cross section. One country watched every quarter for 40 years is a time series. Two separate surveys, one from 2005 and one from 2015 with different people, pooled together is a pooled cross section. The same 200 firms tracked every year is a panel. The shape of that spreadsheet decides what you can estimate and how.

Formulas

Panel observation index

y_{it}, \quad i = 1,\dots,N, \;\; t = 1,\dots,T

A panel carries two subscripts:

i

for the unit and

t

for time. A pure cross section has only

i

; a pure time series has only

t

Worked examples

Scenario

You want to study how a 2014 minimum-wage increase affected employment. What data structure helps most?

Solution

A panel of the same restaurants observed before and after the change lets you difference out fixed, unit-specific traits. A repeated survey of different restaurants each year would instead be a pooled cross section, which still allows before-versus-after comparisons but cannot follow the same establishment.

Scenario

Classify each: (a) GDP for the US, quarterly 1960 to 2020; (b) test scores for 4,000 students in one year; (c) wages of the same 500 workers over five years.

Solution

(a) is a time series (one unit, many periods). (b) is a cross section (many units, one period). (c) is a panel (same units across periods). In Stata you would set the panel with `xtset id year` before using panel commands.

Common mistakes

✗Pooled cross sections and panels are the same thing. A pooled cross section draws new units each period, while a panel follows the same units, which is what allows fixed-unit effects to be removed.
✗Time-series data can be analyzed exactly like cross-section data. Time-series observations are usually correlated over time and may trend, so the classical independence assumptions need to be replaced.
✗A cross section always has more observations than a time series. Sample size is unrelated to the data type; a long daily time series can dwarf a small survey.

Revision bullets

•Cross section: many units, one time period
•Time series: one unit, many periods
•Pooled cross section: separate cross sections stacked across years
•Panel/longitudinal: the same units followed over time
•Data structure dictates assumptions and method

Quick check

Tracking the same 300 firms every year from 2010 to 2020 gives which data structure?

Which best describes a pooled cross section?

Connected topics

Econometrics Population Model Research Process Stata Workflow

Sources

Wooldridge (2019), Ch. 1
Wooldridge, J. M. Introductory Econometrics: A Modern Approach. 7th ed. Cengage, 2019. ISBN 978-1-337-55886-0.
Introduces cross-sectional, time-series, pooled cross-sectional, and panel data structures.

How to cite this page

Dr. Phil's Quant Lab. (2026). Types of Economic Data. Derivatives Atlas. https://phucnguyenvan.com/concept/efm-data-types

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