THE ESTIMATION OF SHORT-RUN DEMAND AND SUPPLY FROM MARKET DATA CONTAINING SEASONAL PATTERNS,
Abstract
The purpose of this paper has been to acquaint economists with the use of spectral analysis as an aid in identifying short-run demand and supply from market data. It has been shown that the seasonal and purely random components of price and quantity series can allow us to distinguish short-run demand from supply providing that at least one of the components results in a cross-spectral representation whose sign is opposite to those of the remaining components' representations. Our short-run schedules are actually linear combinations of independent processes. In this sense, our analysis of demand and supply differs from the traditional approach in which long-run phenomena are removed and the aggregate remainders are used to estimate short-run demand and supply. Disaggregating the price and quantity processes allows us to take advantage of the greater certainties in prediction associated with the regularly recurring seasonal patterns, as compared with the purely random processes whose means are the best estimates to be used in preduction. (Author)
Document Details
- Document Type
- Technical Report
- Publication Date
- Sep 01, 1963
- Accession Number
- AD0420821
Entities
People
- George S. Fishman
Organizations
- RAND Corporation