Economics is concerned with the study of the production and distribution of wealth. It is natural that the study of large amounts of data on wealth and production leads to applications of statistical methods.
Statistics is important in economics for the following reasons:
- It allows us to give a quantitative description of the economy.
- It is helpful in economic planning and formulation of policies by the government.
- It allows us to construct mathematical models which are useful for economic forecasting.
- It allows for the formulation of economic laws.
- It has applications in the area of demand analysis, business, banking, and public finance.
1) Quantitative Description of the Economy:
Statistical averages such as GDP and GNP allow us to understand the purchasing power and standard of living of people in a particular country.
Consumption statistics studies reveal the pattern of consumption of various commodities by various sections of society and also give us an idea of their purchasing power and standard of living.
Production statistics studies allow us to describe the relationship between supply and demand. Income and wealth statistics are primarily useful in understanding income disparities.
2) Economic Planning and Formulation of Policies:
It is important to have correct and accurate data when the government is trying to solve difficult problems such as poverty and unemployment.
For example, if the government collects data showing that the rate of rural unemployment is much greater than the rate of urban unemployment, it can formulate policies in such as way that more rural jobs are created.
Another example is the formulation of pension plans for government servants. The government designs a suitable pension plan for retired government servants on the basis of various statistical quantities such as the rate of inflation, predicted growth rate of the country, expected tax collections, etc.
3) Forecasting:
Regression analysis and time series analysis are useful methods that are applied in predicting future trends in the economy. The forecasting methods are based on the technique of curve fitting by the principle of least squares. Time series analyses are based on the method of moving averages.
Regression Models can be used to predict the future prices of a commodity, the degree of consumption of a particular commodity, sales in a departmental store, etc.
Time series analysis can be used to understand the causes that affect the dependent variable. By isolating and understanding each of the causes/independent variables we can hope to predict future values.
4) Allows for Formulation of Economic Laws:
The Law of supply and demand is well known. This law can only be accurately stated in mathematical terms.
Engels’s famous law of consumption about the consumption habits of the population of a country was formulated on the basis of statistical data analysis. Ernst Engel discovered a correlation between household food expenditure and household income using data from several households.
5) Wide Applications in Finance:
Financial statistics are basic in the field of banking. For example, the central bank may decide the interest rate on the basis of factors such as consumption rate, inflation, etc.
Exchange statistics tell us about the economic development of a nation and tell us about the money in circulation and the volume of business being done in the country.
A business can decide what price to charge to get maximum profits on the basis of demand analysis. A study of the demand and consumption patterns requires statistical methods.
