 Solution

For fixed $b$, put ${\mathcal{L}}_b(x)=f(x)+\lambda (b{)}^T(b-g(x))$. Feasibility gives ${\mathcal{L}}_b(\bar{x}(b))=f(\bar{x}(b))=\varphi (b)$. The assumed Lagrangian duality representation says this value is the unrestricted supremum of ${\mathcal{L}}_b$, so $\bar{x}(b)$ is also an unconstrained global maximizer of this continuously differentiable function. Its first derivative vanishes:Differentiate the identity $g(\bar{x}(b))=b$ using the assumed smooth dependence of the optimizer:The chain rule now gives the envelope theoremThusEach Lagrange multiplier is the marginal change in optimal value per unit relaxation of its constraint. The proof only uses the resulting stationarity and smooth feasibility identities; it does not require differentiating the maximizer explicitly or differentiating the multiplier.