Background of question

I am an economics student, currently writing my bachelor thesis, and quite inexperienced with Stata. I would be grateful for any help!

The purpose of my research is to analyse the drivers of export sophistication of Malaysian exports.

The dependent variable is the natural logarithm of the export sophistication index, more specifically the export sophistication of Malaysian exports to 171 countries.

The independent variables are:
  • Foreign Direct Investment (FDI) proxied by the stock and flow of FDI inflow, FDIS and FDIF respectively
  • Research and Development (R&D) proxied by Gross Domestic Expenditure on R&D as a percentage of GDP and Number of researchers per thousand in the labour force, GDE and RES respectively
Control variables are Malaysia’s GDP per capita PPP (current international $) proxying for the level of economic development (GDPc); Malaysia’s total population proxying for the country size (POPc); Malaysia’s gross enrolment ratio of the tertiary education segment proxying for Malaysia’s human capital (HCc); and the rule of law proxying for Malaysia's institutional quality (INSc).

Important here is that the data for the independent and control variables do not vary between the countries (id), only throughout the years since the data is specific to Malaysia.

My question

To check whether I should use a fixed-effects or random-effects model, I did the Hausman test, but the output does not seem right.

The coefficients in the random and fixed effects model are exactly the same. Furthermore, "V_b-V_B is not positive definite" appears.

I also tried by adding "hausman fixed random, sigmamore", but that does not change anything to my results.

What would you recommend me to do? Does that simply mean I will have to stick to the random-effects model? And I should simply ignore the "V_b-V_B is not positive definite" ?


Please find a screenshot of the test attached.

I would highly appreciate if you could help me.
Please let me know if you need further clarification.
Thank you and kind regards,
Julie