What the data hides and shows

Source: The post is based on the article “Madan Sabnavis writes: What the data hides and shows” published in The Indian express on 2nd August 2023.

Syllabus: GS3- Indian Economy and issues relating to planning.

News: In this article author discusses the reliability of economic indicators in India. The Purchasing Managers Indices (PMI) and other data often suggest strong economic health, but actual growth rates can be different. Issues arise from limited sample sizes, unaccounted informal sectors, and biases in monthly figures. While data availability has improved, its accuracy for policymaking remains questionable.

How high-frequency economic data add value to economic understanding?

Timely Insights: High-frequency data like PMI is available on the first of every month, offering quick snapshots of the economy compared to other data released with a 40–45-day lag.

Sectoral Performance: PMI informs about the state of industry and services monthly, providing sector-specific insights.

International Comparisons: PMI and similar indices are available for many countries, allowing for international economic comparisons and understanding global trends.

GST Collections: They give insights into tax compliance and the extent of formalization in the economy.

Indication of Demand: While they might have limitations, high-frequency data can still hint at consumption trends and sectoral demand, aiding in economic analysis.

Why do high-frequency economic data tend to be misleading in India?

Limited Sample Sizes: One problem is the limited sample sizes in surveys. For instance, the Purchasing Managers’ Index (PMI) is based on only 400 businesses. Such a small number doesn’t represent India’s diverse and massive economy well. So, while PMI might show strong growth, the real GDP growth can be much lower, as seen last year.

Unaccounted Informal Sector: India’s economy has a big informal sector. However, many economic indicators do not account for this. For example, the National Statistical Office’s data, released 40-45 days later, mainly covers the organized sector, leaving out a large portion of the economy. This omission can lead to inflated growth rates.

Biases in Monthly Figures: Monthly data like export numbers, industrial production, or GST collections can be affected by temporary factors such as commodity prices, compliance changes, or logistical issues. They may not reflect long-term trends, leading to erroneous conclusions if extrapolated.

Over-reliance on Announcements: Investment announcements by companies and Memoranda of Understanding (MoUs) signed at summits often don’t materialise. Despite this, they’re taken as positive economic indicators, which can be misleading.

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