Title: Constrained Optimization
1Constrained Optimization
22nd Order Conditions Constrained Optimization
Sufficient conditions in optimization problems
require determining The sign of the second total
differential. The sign of the second Total
differential of a Lagrangian function
Depends on the sign of the determinant of the
bordered Hessian of the Lagrangian function.
3Bordered Hessian for Bivariate Function
The Bordered Hessian for the Lagrangian function
4Determinant Bordered Hessian
52nd Order Conditions for Maximum
- Sufficient Condition for a Maximum in the
Bivariate Case with one Constraint A Lagrangian
function is negative definite at a stationary
point if the determinant of its bordered Hessian
is positive when evaluated at that point. In
this case the stationary point identified by the
Lagrange multiplier method is a maximum.
62nd Order Condition for Minimum
- Sufficient Condition for a minimum in the
Bivariate Case with one Constraint A Lagrangian
function is positive definite at a stationary
point if the determinant of its bordered Hessian
is negative when evaluated at that point. In
this case the stationary point identified by the
Lagrange multiplier method is a minimum.
7Utility Maximization Example
8Utility Max example continued
92nd Order Conditions
102nd Utility Maximization Example
112nd Example Continued
122nd Order Conditions