By a time series we mean a series of value of a variable, the values of which vary according to the passage of time. In such type of variables, the time factor plays an important role in affecting the variable to a marked extent. The examples of such series may be cited as under:
(i) A series relating to consumption, production, or prices of certain goods.
(ii) A series relating to purchase, sales, profits, or losses of a certain business concern.
(iii) A series relating to agricultural of industrial production, investments, foreign exchange reserves, population, crimes, national income or imports and exports of a company.
(iv) A series relating to bank deposits, bank clearings, prices of shares, or dividend rates of a certain company.
(v) A series relating to temperature, rainfall, or yield of a particular area.
Time series cited as above has been defined variously by various authors. Some important ones among those are quoted as under:
- According to Croxton and Cowden, “A time series consists of data arrayed chronologically”.
- According to Kenny and Keeping, “A set of data depending on the time is called time series”.
- In the words of Ya-Lun-Chou, “A time series may be defined as a collection of readings belonging to different time periods, of some economic variables such as production of steel, per capita income, gross national products, price of tobacco, or index of industrial production.”
From all the above definitions, the essential characteristics of a time series may be derived as under:
(i) It consists of a set of values of a variable with reference to the time of their occurrence. As such, a series to constitute a time series must exhibit the data in two columns at least viz: (i) time columns, and (ii) value column.
(ii) It consists of the data quite for a long period, say, 7,10,20, or 30 periods of years, months, weeks or days which may be reasonable for the problem in issue.
(iii) It consists of equal time gaps between the various values of a variable, viz.: 1999, 2000, 2001, 2002, and 2003 etc. or January, February, March, April etc. This means that the data must have been obtained in equal order of chronology.
(iv) It represents a variable the values of which are affected by the time factor. For example, the price of woolen products goes put during the winter season and come down during the summer season. As such, the gap, if any, in the data must be capable of being interpolated or extrapolated with reference to the effect of the time factor.