We have a dataset of around 20k observations. The dependent variable is the change (i.e. delta) on the amount of a common resource (e.g. land) of individual households in a year, so:
- It has negative and positive values (some increased their land, while others decreased it)
- Around 70-80% of observations are 0s (most of them did not exchange land)
- It's a common and static resource (the sum of the dependent variable for the whole dataset is 0)
- The independent variables are continuous or categorical
We tried multiple transformations but it doesn't really work. I was reading about the zero-inflated approaches, but most of them are non-negative count variables. We're trying quantile regression, but not yet sure if that would be the best approach.
Would you have any suggestions?