Importance of Statistics in Economics

Introduction

Statistics refers to the practice of data quantification. It is related to gathering and representing data of interest. It’s not simply a collection of data but deals with classification, presentation, and tabulation. In economics, statistics are utilised to prove theories or models. Economics is incomplete without numbers, and statistics are all about numbers and interpreting them. It has played a pivotal role in making economics a vast study area and concrete science. 

Importance of statistics in economics: Advantages and limitations

Quantifies economic problems 

In economics, we often speak about how a particular problem will affect the economy. Similarly, a specific event can also help the economy in certain ways. Without statistics, it would be impossible to quantify economic events and problems. 

Deducing theories 

Economics usually means establishing a general or complex theory using various economic entities. However, providing evidence is essential to developing economic theories and models. Statistics does the job of providing numerical evidence to these statements/theories. 

Forecasting and identifying patterns 

Economists try to figure out the pattern from the underlying data. It helps in predicting future economic trends, including opportunities and challenges. The statistical tools help them study the data and use it for future planning. 

Making policies 

Economists do the job of analysing national data to suggest policies to the governments. It would be impossible to analyse and interpret such diverse and enormous chunks of data without statistical tools. Therefore, statistics are essential for the general welfare of the public. 

Market Equilibrium 

Economics is everything about studying the various market forces. The market equilibrium is balanced through demand and supply, i.e., products/services and customers. A statistical study is essential to identify whether the market is favourable for producers and consumers. 

Inter-sectoral and inter-temporal comparisons 

In economics, studying various sectors is essential to establish relationships or interdependencies between them. Similarly, learning different periods is crucial in identifying trends and patterns. The comparison of multiple sectors is inter-sectoral, whereas the comparison of different periods is intertemporal. Both these comparisons cannot be made without the help of statistical tools. 

From the above points, we can say that the biggest economies in the world rely on statistics for making policies and planning for the future. Though the importance of statistics in economics cannot be denied, it also has some limitations. Here are some significant limitations faced by economists while leveraging statistical tools:

Qualitative analysis 

Being a quantitative study, statistics fail to measure qualitative entities like health, intelligence, loyalty, etc. Therefore, we can say that the biggest advantage of statistics is also one of its significant drawbacks. 

Aggregate study 

As statistics deals with bulk quantities, data needs to be aggregated into various types. Therefore, it is impossible to study a single entity or economic factor with statistical tools. 

Homogenous Data 

We cannot compare data unless it is homogenous and of uniform type. Statistics is all about obtaining data through comparison, which is impossible if the data is heterogeneous. As a result, statistics fail to analyse and interpret heterogeneous data. 

Knowledge-based 

Statistical tools can only be used by statisticians, economists, and anyone who has acquired knowledge and understands statistical methods. However, as the commoners don’t understand these methods, it becomes difficult for economists to explain statistical models or data in the public domain. 

For example, the government fails to explain the benefits of their policies to the public properly because common people don’t have access to data. Neither can understand how to use statistical tools to understand the data available in the public domain. 

Misuse and lacks common sense at times 

Anyone who has a fair bit of knowledge about statistics can misuse it to provide a wrong picture. It can be harmful as miscreants can create panic or give false analyses regarding economic matters. Also, statistics do not always mean the right people hing. In simple terms, we can say that it lacks common sense on several occasions. For example, if the average waist size of the family is 32, it does not mean that jeans of 32 waist size will fit everyone. 

Just a reference point 

The importance of statistics in economics is majorly from a reference point of view. It is because huge chunks of data are analysed to draw a conclusion that may lack common sense, as we have seen in the above point. Therefore, trusting statistical methods blindly will often lead to bad or no results. Analysing the conditions on which the conclusions are made is essential. 

For instance, a company that earned a profit of Rs. 1500, Rs. 500, and Rs. 400 in three consecutive months will show an average profit of Rs. 800. Similarly, a company that earned a profit of Rs. 500, Rs. 900 and Rs. 1000 will also show the same average profit. 

However, if we observe the data closely, we can notice that the profit of the first company is dropping while the other company’s profit is increasing. Now, if you are planning to purchase shares of either of these companies, you should not only see that both the companies are showing the same average profit. Instead, you should be able to identify and relate to the pattern. 

Economies of scale 

To understand the economies of scale meaning, the students have to think from the context of a manufacturing firm. It refers to the reduced average cost for manufacturing units when a company increases its manufacturing scale or magnitude. 

However, when the average cost for manufacturing units increases after a certain increase point, this phenomenon is called diseconomies of scale. 

There are two types of economies of scale: internal economies of scale and external economies of scale. 

Internal Economies of Scale: When a company uses economies that are not available to those outside it, it is known as internal economies of scale. 

For instance, if a company uses a patented manufacturing unit that reduces its average production cost, it falls under its internal economies of scale. 

External Economies of Scale: Some economies can be utilised by everyone in the industry, and they are known as external economies of scale. For example, if the price of manufacturing steel reduces due to a specific decision, everyone in the steel industry can benefit from it. 

Conclusion 

The importance of statistics in economics and its limitations are related concepts highlighted in the above sections.