In　this　paper,　we　investigate　the　estimation　and　testing　problems　of　unbalanced　two-way　error　component　regression　model　with　errors-in-variables.　The　estimation　of　the　unknown　parameter　is　given　based　on　the　bias-corrected　technique,　and　the　asymptotic　property　of　the　resulting　estimator　is　shown　under　some　regularity　conditions.　For　the　hypothesis　testing　problem　of　restricted　condition,　a　test　statistic　is　constructed　through　the　difference　of　the　corrected　residual　sums　of　squares　under　the　null　and　alternative　hypotheses.　Then　we　develop　an　adjusted　test　statistic,　which　follows　an　asymptotically　standard　Chi-squared　distribution.　Some　simulation　studies　and　a　real　data　analysis　are　carried　out　to　assess　the　performance　of　the　proposed　methods.　(C)　2017　The　Korean　Statistical　Society.　Published　by　Elsevier　B.V.　All　rights　reserved.