# What is the difference between pooled cross sectional data and panel data?

They seem so similar. Are they the same thing but just referred to as different names?

When I see panel data, I think longitudinal data, so observations collected on the same individuals at multiple times, on the same topics. Repeated cross sections should be the same topics, but you get different samples of individuals at each observation. I'd welcome other descriptions.

The answer here is pretty straight forward: Both pooled cross sectional data and pure panel data collect data over time (this can range from 2 time periods to any large number). The key difference between the two is the "units" we follow. I am defining units as households, countries, or whatever we are collecting data on.

In pooled cross section, we will take random samples in different time periods, of different units, i.e. each sample we take, will be populated by different individuals. This is often used to see the impact of policy or programmes. For example we will take household income data on households X, Y and Z, in 1990. And then we will take the same income data on households G, F and A in 1995. Although we are interested in the same data, we are taking different samples (using different households) in different time periods.

In pure panel data, we are following the same units i.e. the same households or individuals over time. For example we will follow the same set of households X, Y and Z, for each time period we collect data i.e. in 1990 and we will also interview the same households in 1995.

Therefore the fundamental difference, is simply the units we observe the data for.

Hope this helps.

Cross-sectional data, or a cross section of a study population, in statistics and econometrics is a type of one- dimensional data set. Cross-sectional data refers to data collected by observing many subjects (such as individuals, firms or countries/regions) at the same point of time, or without regard to differences in time. Analysis of cross-sectional data usually consists of comparing the differences among the subjects. For example, we want to measure current obesity levels in a population. We could draw a sample of 1,000 people randomly from that population (also known as a cross section of that population), measure their weight and height, and calculate what percentage of that sample is categorized as obese. For example, 30% of our sample were categorized as obese. This cross- sectional sample provides us with a snapshot of that population, at that one point in time. Note that we do not know based on one cross-sectional sample if obesity is increasing or decreasing; we can only describe the current proportion. Cross-sectional data differs from time series data also known as longitudinal data, which follows one subject's changes over the course of time. Another variant, panel data (or time- series cross-sectional (TSCS) data), combines both and looks at multiple subjects and how they change over the course of time. Panel analysis uses panel data to examine changes in variables over time and differences in variables between subjects. In a rolling cross-section, both the presence of an individual in the sample and the time at which the individual is included in the sample are determined randomly. For example, a political poll may decide to interview 100,000 individuals. It first selects these individuals randomly from the entire population. It then assigns a random date to each individual. This is the random date on which that individual will be interviewed, and thus included in the survey.

Based on the definition of Corey, we have following methodology to estimate the model with the pooled cross-sectional data and panel data.

Pooled cross section: one way fixed effects or random effects (only time) or just pooled OLS.

Panel data: two (or one) way fixed effects/random effects (either time or individual or both) or pooled OLS.

• This doesn't answer the question Nov 1, 2022 at 19:46

This is from "Basic Econometrics" by Gujarati (4th Edition, P28):

Panel, Longitudinal, or Micropanel Data This is a special type of pooled data in which the same cross-sectional unit (say, a family or a firm) is surveyed over time. For example, the U.S. Department of Commerce carries out a census of housing at periodic intervals. At each periodic survey the same household (or the people living at the same address) is interviewed to find out if there has been any change in the housing and financial conditions of that household since the last survey. By interviewing the same household periodically, the panel data provides very useful information on the dynamics of household behavior.

4.Suppose you were interested in household food consumption and its relation to income in Harar City for the year 2022. Design a survey that could be used for obtaining data that could be used for estimation and hypothesis testing. If you obtain this information over the various income groups, what type of data is it? What type of data will it be if you repeat the survey quarterly in 2023? ?

• What do you mean by this? To answer the question an example of either type of data would help, e.g. panel data follows the same units over time (like a household survey such as the panel study of income dynamics) whereas pooled data is data over different years but from different cross sections (such as the current population study).
– Andy
Apr 14, 2015 at 15:48
• Because this appears to contradict other answers here, it would be helpful to see some elaboration of what you mean by "pooled" and "panel" data.
– whuber
Apr 14, 2015 at 15:48
• I approved your edit but it's still not enough (probably will be rejected by others), and basically turns your answer into a question. Please check How do I write a good answer?. If you have a question, post it separately using Ask Question Jun 19, 2023 at 4:54