# 16.2) Panel Data Flashcards

1
Q

What makes a panel data set?

A

It has both time-series and cross-sectional dimensions.

2
Q

Panel data include observations on…

A

the same variables from the same cross sectional sample from two or more different time periods.

3
Q

When does data that combines time-series and cross-sectional data not meet the panel data set definition?

A

For example, if different variables are observed in the different time periods or if the data are drawn from different samples in the different time periods, then the data are not considered to be panel data.

4
Q

Why use panel data?

A
1. ) Panel data will certainly increase sample sizes
2. ) To provide insight into analytical questions that can’t be answered using time-series or cross-sectional data alone.
3. ) Panel data often allow researchers to avoid omitted variable problems that otherwise would cause bias in cross-sectional studies.
5
Q

There are four different kinds of variables that we encounter when we use panel data.

A
1. ) We have variables that can differ between individuals but don’t change over time (gender, ethnicity)
2. ) Variables that change over time but are the same for all individuals (retail price index)
3. ) Variables that vary both over time and between individuals (income marital status)
4. ) Trend variables that vary in predictable ways (age)
6
Q

To estimate an equation using panel data…

A

it’s crucial to ensure that the data are in the right order.

7
Q

In a panel data set, variables will have both …

A

a cross-sectional and a time series component there will subscripts for both components.

8
Q

The fixed effects model is…

A

a method of estimating panel data equations that works by allowing each cross-sectional unit to have a different intercept.

9
Q

One major advantage of the fixed effects model is that…

A

it avoids bias due to omitted variables that don’t change over time (like race or gender). Such time invariant variables are referred to as unobserved heterogeneity or a fixed effect.

10
Q

The fixed effects model has some drawbacks.

A
1. ) Degrees of freedom for the fixed-effects model tend to be low because we lose one degree of freedom per cross-sectional observation because of time demeaning.
2. ) Any substantive explanatory variables that do not vary across time in each unit will be perfectly collinear with the fixed effects, so we can’t include them in the model or estimate their coefficients.
11
Q

The author’s recommend that..

A

readers of this text should tend to use fixed effects model whenever they estimate panel data.