Econometric models

Principles on which Econometric models rest

1. Sale of product depends on several variables.
2. While sale is the dependent variable, the causal factors are the independent variables.
3. Constant interaction is taking place between sales and each of the causal / independent variables.
4. There is also constant interaction among the independent variables themselves.
5. The independent variables consist of two sets – exogenous variables constituted by non-economic forces such as nature, or politics, and endogenous variables constituted by economic forces such as income, employment price etc.
6. The interrelationships between sales and independent variables can be estimated by statistical analysis of past data.

Economic models constitute yet another analytical method of sales forecasting. Econometrics basically attempts to express economic theories in mathematical terms so they can be verified by statistical methods and used to measure the impact of one economic variable upon another for predicting future events. The econometric forecasting models vividly portray real world situations and the multiple variables involved in sales of any product.

The econometric model is constituted by a set of interdependent equations that describe and stimulate the total sales situation. The forecast is derived through this set of equations. Stated in simple terms, in this method, consumption figures for the past few years are taken as the basic data; the relationship for analyzing the time series of consumption figures is provided by the model; the best trend is selected by adopting appropriate statistical tests for the goodness of fit; and based on the analysis of the time series of consumption figures, the forecast for the specified future period is derived.

Econometric models are quite complex and expensive to develop. But they predict the turning points more accurately. Econometric models are used more in forecasting the demand of durable goods – industrial as well as consumer durables, where replacement demand is a significant factor to be projected. Likewise, they are used more for forecasting industry level demand than company level sales.

Market Survey Method: Market survey is yet another method available for demand/sales forecasting. The terms market survey is sometimes used as synonymous with market research or market analysis. This is incorrect. Market survey is just one of the several techniques which market research or market analysis employs. Its purpose is collecting, specific data concerning the market that cannot be had from the company’s internal records or from eternal published sources of data. When a market survey is used for generating relevant market information and such information forms the basis of the sales forecasts, the forecasting method is referred to as the market survey method of sales forecasting.

When primary data becomes essential for forecasting market survey assumes importance. When primary data becomes essential for forecasting, market survey assumes importance. Normally when a company wants to introduce a new product or an improved product, it resorts to a market survey to assess the likely demand. Likewise, a company that is entering a new business, resort to the market survey method for forecasting its demand/sales. This is quite natural. The firm does not have any data of past sales or past demand as patterns to fall back upon. It has to gather the information from the market / consumer and take decisions. Usually, the firm conducts a survey among a sample of consumers and gauges their attitudes, likely purchases and purchase habits. Sometimes, a survey is conducted among the channel members – wholesalers, and/or retailers – to elicit information on their attitudes, likely purchase etc.

The merit of the market survey method lies in the fact that it facilitates gathering of original or primary data that is specific to the problem on hand. The main demerit is that it is time consuming and expensive. Moreover the reliability of the information generated is dependent on the statistical accuracy of the survey procedures.