I am writing a paper using a panel dataset in which my depepent variable has an large percentage amount of zero values observations. Those zero values are real zeros, I mean they are not missing data or whatsoever. I have taken a look on the literature and there are many models that can be applied in this case. I am awared of the following: Tobit (Tobin, 1958), Two-Stage Model (Heckman, 1979), Two-Parts Model (Duan et al.,1984), PPML (Silva & Tenreyro, 2006) and Double-Hurdle models (Dong & Kaiser, 2008). Which one should I use and how to justify the adoption?
Related Posts with Handling large percentage of zero-valued observations in the dependent variable in a panel dataset
Matrix of matricesDears I would like to create a matrix containing the results of other matrices generated after the …
Stata Codes for Post-estimation TestsGood day everyone, I am currently working on the focus - Working Capital Management and Performance …
Ignoring missing value in egen maxDear all, I have a panel data and would like to create a dummy variable using the following: bys bv…
-zipuse- unable to recognize .dta files inside zip foldersDear All, I am trying to use -zipuse- to use and append a number of files that are inside some zip …
RDD graph helpHello everyone, I am currently writing my thesis and doing an RDD. It is very intersting but I am n…
Subscribe to:
Post Comments (Atom)
0 Response to Handling large percentage of zero-valued observations in the dependent variable in a panel dataset
Post a Comment