HOW DOES INFLATION AFFECT CONSUMERS PART VII

REMEMBER THAT FREQUENCY OF THE DATA COLLECTED CAN BE OF VARIOUS PERIODS SUCH AS FOR A MONTH, HALF A YEAR OR A YEAR OR SO, BUT THE REGULARITY OF THE FREQUENCY IS IMPORTANT AND IT SHOULD BE MAINTAINED, FOR EXAMPLE IF THE DATA COLLECTED IS FOR EVERY OTHER YEAR OR SO IT IS BEST TO KEEP ON COLLECTING THE DATA YEAR WISE AND NOT TO SHIP ANY YEAR. STEP 3 SELECTION OF THE DEMAND FUNCTION AFTER SETTING THE VARIABLES AND THE COLLECTION OF PAST DATA, THE NEXT STEP BEFORE FINALLY COMPILING EVERYTHING IS TO DETERMINE THE COMPLETE DEMAND FUNCTION.

WHICH IS THE DEPENDENT OR THE VARIABLE THAT IS TO BE PREDICTED. THE FACTORS THAT EFFECT THIS ARE THE VARIABLES THAT WERE DEFINED IN THE FIRST STEP. THE DEMAND FUNCTION CAN BE OF LINEAR IN LOGARITHMIC FORM, BOTH OF THEM ARE DISCUSSED INDIVIDUALLY BELOW. LINEAR INVOLVES FINDING THE LINE OF BEST FITS BETWEEN TWO OR MORE VARIABLES, THUS BY INPUTTING ONE OR MULTIPLE VARIABLES OTHER VARIABLE CAN BE PREDICTED, USING A LINEAR EQUATION.

NOW CONSIDERING THE FUNCTION FORMED ABOVE IN STEP 1 AND DETERMINING ITS DEMAND FUNCTION IN THE LINEAR EQUATION FOR BELOW, ZDR = M0+M1PZ+M2Y+M3A+M4PS+M5PC WHERE, M1, M2, M3, M4 AND M5 ARE THE REGRESSION COEFFICIENTS. THESE COEFFICIENTS REPRESENT THE ELASTICITY OF DEMAND ALSO INCLUDES PRICE ELASTICITY, INCOME ELASTICITY, PROMOTIONAL ELASTICITY AND CROSS ELASTICITY OF DEMAND.

THESE COEFFICIENTS ARE RESPONSIBLE FOR THE AMOUNT OF CHANGE AS WELL AS THE NATURE OF THE CHANGE (POSITIVE OR NEGATIVE) FOR EXAMPLE IN THE ABOVE EQUATION EFFECT OF INCOME, ADVERTISEMENT AND SUBSTITUTE WILL HAVE A POSITIVE EFFECT ON THE DEMAND, WHEREAS THE PRICE OF COMMODITY A MIGHT HAVE A NEGATIVE EFFECT ON THE FUTURE DEMAND OF IT, THEN COME THE POLYNOMIAL FORMS IN WHICH THE RELATIONSHIP IS NOT A STRAIGHT LINE, NEVER THE LESS THEY CAN BE CONVERTED INTO STRAIGHT LINE BY TRANSFORMING THE VARIABLES USING LOGARITHMS INTO A STRAIGHT LINE FOR SIMPLICITY, IT IS MOST COMMONLY USED IN META MODELS FOR MECHANICAL SYSTEMS.

STEP 4 FUNCTION ESTIMATION THIS IS THE MOST IMPORTANT STEP IN WHICH THE COEFFICIENT VALUES ARE FOUND, THESE COEFFICIENTS EACH REPRESENTS THE MEAN CHANGE IN THE RESPONSE VARIABLE FOR ONE UNIT OF CHANGE WHILE KEEPING THE OTHER VARIABLES CONSTANT. THESE CAN BE EASILY DETERMINED USING THE SOFTWARE USED FOR PLOTTING THE REGRESSION ANALYSES GRAPH OR MANUALLY STANDARDIZING EACH VALUES. IT IS ESSENTIAL TO REMEMBER THAT THE VALUES OF THESE COEFFICIENTS CANNOT BE MORE THAN ONE, ALWAYS <1. 

STEP 5 FORECAST DERIVATIONS THE LAST AND THE FINAL STEP IS DERIVING THE FORECAST USING YOUR PREDICTED VALUES FOR THE COEFFICIENTS AND YOUR FUNCTION. IN THIS STEP YOU CAN ESTIMATE THE VALUES OF INCOME, PRICES, PRICES OF RELATED SUBSTITUTES, PROMOTIONAL EXPENDITURES FOR THE UPCOMING TIME USING THIS REGRESSION METHOD.

AND USING THESE VALUES AS A BAS ONE CAN ESTIMATE THE FUTURE DEMAND/SALE FOR A CERTAIN PRODUCT. REAL LIFE USES AND APPLICATIONS REGRESSION ANALYSIS HAS VERY HIGH IMPORTANCE IN VARIOUS DISCIPLINES SUCH AS BUSINESS, ECONOMICS, ENGINEERING, AND BIOLOGICAL SCIENCES FOR PREDICTING VARIOUS OUTCOMES AS A RESULT OF INFLATION.