# Overview Standard Error Correction in Time Series / Panel Literature

In microeconometrics, the time component is usually short (meaning that $$T$$ is fixed in $$t=1,\ldots,T$$). Serial correlation is here usually just seen as a negligible issue affecting the standard errors of a standard linear regression model (and not the point estimates) because it can be easily correct via robust standard error (both adjusting for possible heteroscedasticity and serial correlation, a similar approach as to use the Newey-West correction).

A lot of studies have however apparently calculated biased standard error in the difference-and-difference context as demonstrated by Bertrand, Duflo and Mullainathan (2003). They recommend, among others, to use block bootstrap for such an analyses. Yet, their study focuses mainly on the validity of different correction mechanisms with respect to the number of available groups ($$n=1,\ldots,N$$ in a panel context) but less on the length of the time component $$T$$.

I have some of questions based on my limited understanding:

1. Are there other good overviews I should be aware of?
2. Can you recommend an introduction or a paper about how to assure correct standard error in the time series literature for real-world time series data (not focusing on entirely on theoretical asymptotics but taking into account, for example, time series with multiple seasonalities such as hourly data; or long time series in a slowing but changing world / the effects of a slowly changing data generating process such as climate change). Here is a recent slightly related question which inspired me to raise these questions.
3. Is there a similar overview available differentiating more between shorter and longer panels?
4. Are the Bertrand et al. conclusions still considered as current state of the literature after more than 15 years?

An answer to any of these question is welcome!

1. Baltagi, B. H. (2006). Panel Data Econometrics Theoretical Contributions and Empirical Applications. Emerald Group Publishing Limited.
2. See https://scholar.harvard.edu/files/stock/files/aea_2015_lecture4_har_rev.pdf and the other lectures in the same series (which you can watch online at https://www.aeaweb.org/conference/cont-ed/2019-webcasts (2019 version) or https://www.aeaweb.org/webcasts/2015/continuing-education.php (2015 version); it's a great series).
3. See (1).
4. No, more can be said. See Section 8.2 in https://mycourses.aalto.fi/pluginfile.php/203124/mod_resource/content/1/Angrist%20%20Pischke.pdf. There is no consensus yet regarding these issues.
• @AnonymousGuess: Thanks for the nice references. Is the third one a summary of the book or an addendum to the book ? Dec 14, 2019 at 21:18
• Would you mind providing a link to the videos in 2) if they're available. If I need to join AEA, I'll check that out. Thanks. Dec 14, 2019 at 21:26
• @mlofton The link in item 4 gives the complete book (the published version just has a different design). There is an online version of the book mentioned in item 1. I provided two links for the publicly available videos corresponding to the lectures in the series on time series econometrics by Stock & Watson. Dec 15, 2019 at 8:56
• The Stack and Watson lecture series sounds amazing, I will go through it thanks! Any further ideas about published papers in the vein of Betrand et al. or a JEL/JEP paper? Dec 15, 2019 at 12:49
• AnonymousIGuess: 1) I have the Angrist book. Thanks. 2) I found the full set of Stock and Watson AEA notes and they look great ( and advanced ). Thanks for that too. Dec 15, 2019 at 15:09