The comparative dynamics of locally differentiable feedback Nash equilibria are derived for the ubiquitous class of autonomous and exponentially discounted infinite horizon differential games. The resulting refutable implications are intrinsic to the said class of differential games, and thus...

A new comparative statics formalism using generalized compensated derivatives is presented that, in contrast to existing methodologies, directly yields constraint-free semidefiniteness results for any differentiable, constrained optimization problem. The formalism provides a natural and powerful...

We prove that the symmetric and negative semidefinite modified Slutsky matrix derived by Samuelson and Sato (1984) for the money-goods model of the consumer, is identical to that derived by Pearce (1958) a quarter century before and restated sixteen years later by Berglas and Razin (1974). We...

In a recent paper, Mundlak assumes that the price-taking, risk-neutral and profit-maximizing entrepreneur makes his decisions on the basis of a planning model that maximizes expected profit using expected prices. In the same paper, the author asserts that when there is no sample price variation...

In 1944, Marschak and Andrews published a seminal paper on how to obtain consistent estimates of a production technology. The original formulation of the econometric model regarded the joint estimation of the production function together with the first-order necessary conditions for...

In 1944, Marschak and Andrews published a seminal paper on how to obtain consistent estimates of a production technology. The original formulation of the econometric model regarded the joint estimation of the production function together with the first-order necessary conditions for...

An exhaustive comparative statics analysis of a general rate-of-return regulated, profit-maximizing model of the firm is carried out under a minimal set of assumptions. The resulting intrinsic comparative statics are contained in a positive semi-definite matrix. Each element of this matrix...