Dear Researchers,
I am trying to regress GDP, population, irrigation, rainfall, temperature, the area under non-agricultural use, credit institutions, the area under small and marginal farms, and average land size on agricultural land use at the district level using secondary panel data which has been taken from agricultural census data of four time periods of 2000,2005,2010 and 2015. It has 4 time periods and 27 districts( cross-sections). The Hausman test shows that RE model is the appropriate model. But when I regress without adding one of the independent variables i.e.the Non-agricultural area, the chosen model is the FE model by the Hausman test. Should I choose the RE model or the FE model? Should I do more tests before concluding the results? I was wondering if you can suggest which model will be appropriate in this case which would be very much helpful and I would like to appreciate the same. Thank you.
I am trying to regress GDP, population, irrigation, rainfall, temperature, the area under non-agricultural use, credit institutions, the area under small and marginal farms, and average land size on agricultural land use at the district level using secondary panel data which has been taken from agricultural census data of four time periods of 2000,2005,2010 and 2015. It has 4 time periods and 27 districts( cross-sections). The Hausman test shows that RE model is the appropriate model. But when I regress without adding one of the independent variables i.e.the Non-agricultural area, the chosen model is the FE model by the Hausman test. Should I choose the RE model or the FE model? Should I do more tests before concluding the results? I was wondering if you can suggest which model will be appropriate in this case which would be very much helpful and I would like to appreciate the same. Thank you.
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