This　paper　proposes　a　variable　selection　method　for　a　semiparametric　varying　coefficient　spatial　autoregressive　panel　model　with　fixed　effects　based　on　a　penalized　profile　quasi-likelihood　method,　which　can　simultaneously　select　significant　variables　in　parametric　components　and　nonparametric　components　without　estimating　fixed　effects.　With　an　appropriate　selection　of　the　tuning　parameters　and　some　mild　assumptions,　the　consistency　of　this　procedure　and　the　oracle　property　of　the　obtained　estimators　are　established.　Then,　we　conduct　some　Monte　Carlo　simulations　to　assess　the　finite　sample　performance　of　the　proposed　variable　selection　method,　and　finally,　we　analyze　a　real　dataset　for　further　illustration.