- author = "John R. Koza",
- title = "A genetic approach to econometric modeling",
- booktitle = "Economics and Cognitive Science",
- publisher = "Pergamon Press",
- year = "1991",
- editor = "Paul Bourgine and Bernard Walliser",
- address = "Oxford, UK",
- pages = "57--75",
- keywords = "genetic algorithms, genetic programming",
- ISBN = "0-08-041050-2",
-
URL = "
http://www.genetic-programming.com/jkpdf/ecs1991cecoia1990.pdf",
-
URL = "
https://www.amazon.co.uk/s?k=9781483294896",
-
abstract = "An important problem in economics is finding the
mathematical relationship between the empirically
observed variables measuring a system. In many
conventional modeling techniques, one necessarily
begins by selecting the size and shape of the model.
After making this choice, one usually then tries to
find the values of certain coefficients required by the
particular model so as to achieve the best fit between
the observed data and the model. But, in many cases,
the most important issue is the size and shape of the
model itself.
Finding the functional form of the model can be viewed as searching a space of possible computer programs for the particular computer program which produces the desired output for given inputs. This most fit computer program can be found via a recently developed genetic programming paradigm originally developed for solving artificial intelligence problems. This new genetic programming paradigm genetically breeds populations of computer programs in a Darwinian competition using genetic operations, such as crossover (sexual recombination). In this paper, we illustrate the process of discovering a model by rediscovering the well-known multiplicative (non-linear) {"}exchange equation{"} P=F(MV,Q) relating the money supply, price level, gross national product, and velocity of money in an economy.",
- notes = "'This paper was submitted in 1989 to the CECOIA-1990 conference held in Paris in 1990. http://www.genetic-programming.com/jkpdf/cecoia1990.pdf '",
