What mountainous nation in the Himalayas bucks conventional, Washington Consensus wisdom to use Gross National Happiness to define the well-being of its citizens?
How can forming a Hessian Matrix assist in classifying the critical points of a function?
Without matrices, the first step in classifying the critical points of a function, f(x), is to locate the critical points, i.e. where f'(x) = 0. Then, you would need to check the sign of the second derivative evaluated at the point to classify the point. Forming and then classifying the Hessian matrix by calculating the determinant can provide a useful organizing mechanism for this cumbersome process. The Hessian matrix is the matrix formed by the second-order partial derivatives. If the Hessian is positive semidefinite, the critical point is a local minimum. If the Hessian is negative semidefinite, the critical point is a local maximum. Otherwise the Hessian Second Order Derivative Test is inconclusive.
How does recent behavioral and neuroeconomic research affect the neoclassical economic assumption of the individual as rational and utility-maximizing?
In the typical neoclassical economics framework, individuals are assumed to be perfectly rational, utility-maximizing beings who fully understand their options, preferences, constraints, and what will bring them satisfaction. As cross-disciplinary research emerges in fields like behavioral economics and neuroeconomics, economists are beginning to build more complex models of reality by challenging the rationality and utility-maximizing assumption. In mainstream circles, Richard Thaler and Daniel Kahneman are well known for popularizing how rational decision-making consistently breaks down because of biases and fallacies in the way humans process information.