Dear all, I have been testing the hypotheses for my master thesis and I have run into a problem. For hypotheses 1-3, Stata tells me to use the fixed effects model. However for hypotheses 4 , I get the following error "Error - saved RE estimates are degenerate (sigma_u=0) and equivalent to pooled OLS r(198)". Why is that and what does it mean? So I use the fixed effects model for hypotheses 1-3 and the pooled OLS for hypotheses 4?

Please find my code below:

Code:
**Hypothesis 1: 

* Pooled OLS
reg CAR ESG_score Firm_size Firm_performance Firm_leverage RD_intensity i.Layoff_Reason_New i.Industry i.Year, vce(robust) 

* Fixed effects 
xtreg CAR ESG_score Firm_size Firm_performance Firm_leverage RD_intensity i.Layoff_Reason_New i.Industry i.Year, fe vce(robust) 

* Random effects
xtreg CAR ESG_score Firm_size Firm_performance Firm_leverage RD_intensity Layoff_reason1-Layoff_reason7 Industry1-Industry8 Year2002-Year2020, re vce(robust) 

xtoverid // o. operator not allowed -> remove omitted variables from model

xtreg CAR ESG_score Firm_size Firm_performance Firm_leverage RD_intensity Layoff_reason1-Layoff_reason6 Industry1-Industry3 Industry5 Industry7-Industry8 Year2002-Year2019, re vce(robust)

xtoverid // Rejection of null-hypothesis -> fixed effects 

**Hypothesis 2: 

* Pooled OLS
reg CAR ESG_score c.ESG_score##industry_wave_dummy Firm_size Firm_performance Firm_leverage RD_intensity i.Layoff_Reason_New i.Industry i.Year, vce(robust) 

* Fixed effects 
xtreg CAR ESG_score c.ESG_score##industry_wave_dummy Firm_size Firm_performance Firm_leverage RD_intensity i.Layoff_Reason_New i.Industry i.Year, fe vce(robust) 

* Random effects
xtreg CAR ESG_score industry_wave_dummy moderation1 Firm_size Firm_performance Firm_leverage RD_intensity Layoff_reason1-Layoff_reason7 Industry1-Industry8 Year2002-Year2020, re vce(robust) 

xtoverid // o. operator not allowed -> remove omitted variables from model

xtreg CAR ESG_score industry_wave_dummy moderation1 Firm_size Firm_performance Firm_leverage RD_intensity Layoff_reason1-Layoff_reason6 Industry1-Industry3 Industry5 Industry7-Industry8 Year2002-Year2019, re vce(robust)

xtoverid // Rejection of null-hypothesis -> fixed effects 

**Hypothesis 3:

* Pooled OLS
reg CAR ESG_score c.ESG_score##c.Layoff_Size_in_Percent Firm_size Firm_performance Firm_leverage RD_intensity i.Layoff_Reason_New i.Industry i.Year, vce(robust) 

* Fixed effects 
xtreg CAR ESG_score c.ESG_score##c.Layoff_Size_in_Percent Firm_size Firm_performance Firm_leverage RD_intensity i.Layoff_Reason_New i.Industry i.Year, fe vce(robust) 

* Random effects
xtreg CAR ESG_score Layoff_Size_in_Percent moderation2 Firm_size Firm_performance Firm_leverage RD_intensity Layoff_reason1-Layoff_reason7 Industry1-Industry8 Year2002-Year2020, re vce(robust) 

xtoverid // o. operator not allowed -> remove omitted variables from model

xtreg CAR ESG_score Layoff_Size_in_Percent moderation2 Firm_size Firm_performance Firm_leverage RD_intensity Layoff_reason1-Layoff_reason6 Industry1-Industry3 Industry5 Industry7-Industry8 Year2002-Year2019, re vce(robust)

xtoverid // Rejection of null-hypothesis -> fixed effects 

** Hypothesis 4:

* Pooled OLS
reg CAR ESG_score c.ESG_score##c.ESG_disclosure_score Firm_size Firm_performance Firm_leverage RD_intensity i.Layoff_Reason_New i.Industry i.Year, vce(robust) 

* Fixed effects 
xtreg CAR ESG_score c.ESG_score##c.ESG_disclosure_score Firm_size Firm_performance Firm_leverage RD_intensity i.Layoff_Reason_New i.Industry i.Year, fe vce(robust) 

* Random effects
xtreg CAR ESG_score ESG_disclosure_score moderation3 Firm_size Firm_performance Firm_leverage RD_intensity Layoff_reason1-Layoff_reason7 Industry1-Industry8 Year2002-Year2020, re vce(robust) 

xtoverid // o. operator not allowed -> remove omitted variables from model

xtreg CAR ESG_score ESG_disclosure_score moderation3 Firm_size Firm_performance Firm_leverage RD_intensity Layoff_reason1-Layoff_reason6 Industry1-Industry2 Industry5 Industry7-Industry8 Year2005-Year2019, re vce(robust)

xtoverid // -> error?
Thank you very much in advance!