What’s the difference between time-series econometrics and panel data econometrics?

This question may be very naive, but the way I’m taught econometrics I’m very confused if there’s a difference between time-series and panel data method.

Regarding time series, I’ve covered topics such as covariance stationary, AR, MA, etc.
Regarding panel data, I’ve only seen discussions in the form of fixed effect vs random effect (or more generally, hierarchical model), difference-in-differences, etc.

Are these topics related in some ways? Since panel data also has a time dimension, why is there not discussion of AR, MA, etc. as well?

If the answer is that my education on panel methods is simply insufficient, could you point to a book that covers more than just FE/RE, difference-in-differences?


At least in the social sciences you often have panel data that has large N and small T asymptotics, meaning that you observe each entity for a relatively short period of time. This is why applied work with panel data is often somewhat less concerned with the time series component of the data.

Nevertheless time-series elements are still important in the treatment of panel data. For instance, the degree of auto-correlation determines whether fixed effects or first differences is more efficient. In difference in differences proper treatment of the standard errors to account for autocorrelation is important for correct inference (see Bertrand et al., 2004). Dynamic panels using estimators for small N, large T asymptotics are also available, you often find such data in macroeconomics. There you may run into known time-series issues like panel non-stationarity.

An excellent treatment of these topics is provided in Wooldridge (2010) “Econometric Analysis of Cross Section and Panel Data”.

Source : Link , Question Author : Heisenberg , Answer Author : Pavel Fedotov

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