Difficulties in Constructing Index Numbers, and Their Importance in Economics

Difficulties in constructing index numbers.

1. Choice of the base year. The base year should be a "normal" year, free of abnormal events (war, famine, a sudden boom/slump) — a genuinely normal year is not always easy to identify, and a base year that was itself unusual distorts every later comparison built on it.
2. Choice of commodities. No index can include every commodity in the economy; a genuinely REPRESENTATIVE, manageable sample must be selected, and consumption patterns/tastes keep changing, so a sample that was representative once may stop being so over the years.
3. Choice of weights. Deciding what weight each commodity or group deserves is itself a judgement call, and different reasonable weighting schemes can give visibly different index values for the identical price data (Sections 4 and 6 show exactly this — Laspeyres and Paasche differ precisely because they weight differently).
4. Choice of the formula/method. As already seen, the simple aggregative, simple average of relatives, Laspeyres, Paasche and Fisher methods are all valid but give different numbers on the same raw data; choosing among them is a genuine methodological decision, not a purely mechanical one.
5. Data collection problems. Retail prices vary by region, season, shop, and quality/grade of the same nominal commodity — collecting a single "the" price for each item already involves approximation.
6. Index numbers only measure AVERAGE, relative change — they can never show how a price change actually affected any ONE particular household, whose own consumption basket may differ sharply from the assumed "representative" basket.

Importance of index numbers in economics.

1. They provide a standard measure of inflation/deflation in the general price level.
2. They form the basis for wage and dearness-allowance revisions, tying pay to the actual cost of living.
3. They allow money values to be deflated into real values (real GDP, real wages), which is essential for comparing economic welfare across years, not just nominal rupee amounts.
4. They assist government policy-making — monetary policy, subsidy targeting, and social-security indexation all draw on price and CPI data.
5. They enable business forecasting and planning, since firms track wholesale and consumer price indices to anticipate cost and demand movements. …