Search results
Results from the WOW.Com Content Network
Nancy Stokey, Robert Lucas Jr. and Edward Prescott describe stochastic and non-stochastic dynamic programming in considerable detail, giving many examples of how to employ dynamic programming to solve problems in economic theory. [4] This book led to dynamic programming being employed to solve a wide range of theoretical problems in economics ...
Econophysics is a non-orthodox (in economics) interdisciplinary research field, applying theories and methods originally developed by physicists in order to solve problems in economics, usually those including uncertainty or stochastic processes and nonlinear dynamics.
This book led to dynamic programming being employed to solve a wide range of theoretical problems in economics, including optimal economic growth, resource extraction, principal–agent problems, public finance, business investment, asset pricing, factor supply, and industrial organization.
Computational economics is an interdisciplinary research discipline that combines methods in computational science and economics to solve complex economic problems. [1] This subject encompasses computational modeling of economic systems .
Transformation problem: The transformation problem is the problem specific to Marxist economics, and not to economics in general, of finding a general rule by which to transform the values of commodities based on socially necessary labour time into the competitive prices of the marketplace. The essential difficulty is how to reconcile profit in ...
The tax experts at Jackson Hewitt analyzed data from the annually published IRS Data Book and determined that there are six main tax problems that Americans face. More: Medical Expenses You Can ...
Dynamic stochastic general equilibrium modeling (abbreviated as DSGE, or DGE, or sometimes SDGE) is a macroeconomic method which is often employed by monetary and fiscal authorities for policy analysis, explaining historical time-series data, as well as future forecasting purposes. [1]
There are generally two approaches to solving optimal stopping problems. [4] When the underlying process (or the gain process) is described by its unconditional finite-dimensional distributions , the appropriate solution technique is the martingale approach, so called because it uses martingale theory, the most important concept being the Snell ...