Steel Price Index

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A price index (plural: "price indices" or "price indexes") is a normalized average (typically a weighted average) of price relatives for a given class of goods or services in a given region, during a given interval of time. It is a statistic designed to help to compare how these price relatives, taken as a whole, differ between time periods or geographical locations.

Price indices have several potential uses. For particularly broad indices, the index can be said to measure the economy's general price level or a cost of living. More narrow price indices can help producers with business plans and pricing. Sometimes, they can be useful in helping to guide investment.

Some notable price indices include:

• Consumer price index
• Producer price index
• Employment cost index
• Export price index
• Import price index
• GDP deflator

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History of early price indices

No clear consensus has emerged on who created the first price index. The earliest reported research in this area came from Welshman Rice Vaughan, who examined price level change in his 1675 book A Discourse of Coin and Coinage. Vaughan wanted to separate the inflationary impact of the influx of precious metals brought by Spain from the New World from the effect due to currency debasement. Vaughan compared labor statutes from his own time to similar statutes dating back to Edward III. These statutes set wages for certain tasks and provided a good record of the change in wage levels. Vaughan reasoned that the market for basic labor did not fluctuate much with time and that a basic laborer's salary would probably buy the same amount of goods in different time periods, so that a laborer's salary acted as a basket of goods. Vaughan's analysis indicated that price levels in England had risen six- to eight-fold over the preceding century.

While Vaughan can be considered a forerunner of price index research, his analysis did not actually involve calculating an index. In 1707, Englishman William Fleetwood created perhaps the first true price index. An Oxford student asked Fleetwood to help show how prices had changed. The student stood to lose his fellowship since a 15th-century stipulation barred students with annual incomes over five pounds from receiving a fellowship. Fleetwood, who already had an interest in price change, had collected a large amount of price data going back hundreds of years. Fleetwood proposed an index consisting of averaged price relatives and used his methods to show that the value of five pounds had changed greatly over the course of 260 years. He argued on behalf of the Oxford students and published his findings anonymously in a volume entitled Chronicon Preciosum.

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Formal calculation

Given a set ${\displaystyle C}$ of goods and services, the total market value of transactions in ${\displaystyle C}$ in some period ${\displaystyle t}$ would be

where

If, across two periods ${\displaystyle t_{0}}$ and ${\displaystyle t_{n}}$, the same quantities of each good or service were sold, but under different prices, then

and

would be a reasonable measure of the price of the set in one period relative to that in the other, and would provide an index measuring relative prices overall, weighted by quantities sold.

Of course, for any practical purpose, quantities purchased are rarely if ever identical across any two periods. As such, this is not a very practical index formula.

One might be tempted to modify the formula slightly to

This new index, however, does not do anything to distinguish growth or reduction in quantities sold from price changes. To see that this is so, consider what happens if all the prices double between ${\displaystyle t_{0}}$ and ${\displaystyle t_{n}}$, while quantities stay the same: ${\displaystyle P}$ will double. Now consider what happens if all the quantities double between ${\displaystyle t_{0}}$ and ${\displaystyle t_{n}}$ while all the prices stay the same: ${\displaystyle P}$ will double. In either case, the change in ${\displaystyle P}$ is identical. As such, ${\displaystyle P}$ is as much a quantity index as it is a price index.

Various indices have been constructed in an attempt to compensate for this difficulty.

Paasche and Laspeyres price indices

The two most basic formulae used to calculate price indices are the Paasche index (after the economist Hermann Paasche ['pa:??]) and the Laspeyres index (after the economist Etienne Laspeyres [las'pejres]).

The Paasche index is computed as

while the Laspeyres index is computed as

where ${\displaystyle P}$ is the relative index of the price levels in two periods, ${\displaystyle t_{0}}$ is the base period (usually the first year), and ${\displaystyle t_{n}}$ the period for which the index is computed.

Note that the only difference in the formulas is that the former uses period n quantities, whereas the latter uses base period (period 0) quantities.

When applied to bundles of individual consumers, a Laspeyres index of 1 would state that an agent in the current period can afford to buy the same bundle as she consumed in the previous period, given that income has not changed; a Paasche index of 1 would state that an agent could have consumed the same bundle in the base period as she is consuming in the current period, given that income has not changed.

Hence, one may think of the Paasche index as one where the numeraire is the bundle of goods using current year prices and current year quantities. Similarly, the Laspeyres index can be thought of as a price index taking the bundle of goods using current prices and base period quantities as the numeraire.

The Laspeyres index tends to overstate inflation (in a cost of living framework), while the Paasche index tends to understate it, because the indices do not account for the fact that consumers typically react to price changes by changing the quantities that they buy. For example, if prices go up for good ${\displaystyle c}$ then, ceteris paribus, quantities of that good should go down.

Lowe indices

Many price indices are calculated with the Lowe index procedure which is sometimes referred to as a "modified Laspeyres" index. "A Lowe price index is distinguished from [a] Laspeyres index by the separation of the weight reference (or expenditure base) period and price reference (or link) period." Lowe indexes are named for economist Joseph Lowe. Most CPIs and employment cost indices from Statistics Canada, the U.S. Bureau of Labor Statistics, and many other national statistics offices are Lowe indices.

Fisher index and Marshall-Edgeworth index

A third index, the Marshall-Edgeworth index (named for economists Alfred Marshall and Francis Ysidro Edgeworth), tries to overcome these problems of under- and overstatement by using the arithmetic means of the quantities:

A fourth, the Fisher index (after the American economist Irving Fisher), also known as ideal index, is calculated as the geometric mean of ${\displaystyle P_{P}}$ and ${\displaystyle P_{L}}$:

However, no guarantee exists with either the Marshall-Edgeworth index or the Fisher index that the overstatement and understatement will exactly cancel the other.

While these indices were introduced to provide overall measurement of relative prices, ultimately no method measures the imperfections of any of these indices (Paasche, Laspeyres, Fisher, or Marshall-Edgeworth) against reality.

Practical measurement considerations

Normalizing index numbers

Price indices are represented as index numbers, number values that indicate relative change but not absolute values (i.e. one price index value can be compared to another or a base, but the number alone has no meaning). Price indices generally select a base year and make that index value equal to 100. You then express every other year as a percentage of that base year. In our example above, let's take 2000 as our base year. The value of our index will be 100. The price

• 2000: original index value was $2.50; $2.50/$2.50 = 100%, so our new index value is 100
• 2001: original index value was $2.60; $2.60/$2.50 = 104%, so our new index value is 104
• 2002: original index value was $2.70; $2.70/$2.50 = 108%, so our new index value is 108
• 2003: original index value was $2.80; $2.80/$2.50 = 112%, so our new index value is 112

When an index has been normalized in this manner, the meaning of the number 112, for instance, is that the total cost for the basket of goods is 4% more in 2001, 8% more in 2002, and 12% more in 2003 than in the base year (in this case, year 2000).

Relative ease of calculating the Laspeyres index

As can be seen from the definitions above, if one already has price and quantity data (or, alternatively, price and expenditure data) for the base period, then calculating the Laspeyres index for a new period requires only new price data. In contrast, calculating many other indices (e.g., the Paasche index) for a new period requires both new price data and new quantity data (or alternatively, both new price data and new expenditure data) for each new period. Collecting only new price data is often easier than collecting both new price data and new quantity data, so calculating the Laspeyres index for a new period tends to require less time and effort than calculating these other indices for a new period.

In practice, price indices regularly compiled and released by national statistical agencies are of the Laspeyres type, due to the above-mentioned difficulties in obtaining current-period quantity or expenditure data.

Calculating indices from expenditure data

Sometimes, especially for aggregate data, expenditure data are more readily available than quantity data. For these cases, the indices can be formulated in terms of relative prices and base year expenditures, rather than quantities.

Here is a reformulation for the Laspeyres index:

Let ${\displaystyle E_{c,t_{0}}}$ be the total expenditure on good c in the base period, then (by definition) we have ${\displaystyle E_{c,t_{0}}=p_{c,t_{0}}\cdot q_{c,t_{0}}}$ and therefore also ${\displaystyle {\frac {E_{c,t_{0}}}{p_{c,t_{0}}}}=q_{c,t_{0}}}$. We can substitute these values into our Laspeyres formula as follows:

A similar transformation can be made for any index.

Chained vs unchained calculations

The above price indices were calculated relative to a fixed base period. An alternative is to take the base period for each time period to be the immediately preceding time period. This can be done with any of the above indices. Here is an example with the Laspeyres index, where ${\displaystyle t_{n}}$ is the period for which we wish to calculate the index and ${\displaystyle t_{0}}$ is a reference period that anchors the value of the series:

Each term

answers the question "by what factor have prices increased between period ${\displaystyle t_{n-1}}$ and period ${\displaystyle t_{n}}$". These are multiplied together to answer the question "by what factor have prices increased since period ${\displaystyle t_{0}}$". The index is then the result of these multiplications, and gives the price relative to period ${\displaystyle t_{0}}$ prices.

Chaining is defined for a quantity index just as it is for a price index.

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Index number theory

Price index formulas can be evaluated based on their relation to economic concepts (like cost of living) or on their mathematical properties. Several different tests of such properties have been proposed in index number theory literature. W.E. Diewert summarized past research in a list of nine such tests for a price index ${\displaystyle I(P_{t_{0}},P_{t_{m}},Q_{t_{0}},Q_{t_{m}})}$, where ${\displaystyle P_{t_{0}}}$ and ${\displaystyle P_{t_{m}}}$ are vectors giving prices for a base period and a reference period while ${\displaystyle Q_{t_{0}}}$ and ${\displaystyle Q_{t_{m}}}$ give quantities for these periods.

1. Identity test:
2. Proportionality test:
3. Invariance to changes in scale test:
4. Commensurability test:
5. Symmetric treatment of time (or, in parity measures, symmetric treatment of place):
6. Symmetric treatment of commodities:
7. Monotonicity test:
8. Mean value test:
9. Circularity test:

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Quality change

Price indices often capture changes in price and quantities for goods and services, but they often fail to account for variation in the quality of goods and services. This could be overcome if the principal method for relating price and quality, namely hedonic regression, could be reversed. Then quality change could be calculated from price. Instead, statistical agencies generally use matched-model price indices, where one model of a particular good is priced at the same store at regular time intervals. The matched-model method becomes problematic when statistical agencies try to use this method on goods and services with rapid turnover in quality features. For instance, computers rapidly improve and a specific model may quickly become obsolete. Statisticians constructing matched-model price indices must decide how to compare the price of the obsolete item originally used in the index with the new and improved item that replaces it. Statistical agencies use several different methods to make such price comparisons.

The problem discussed above can be represented as attempting to bridge the gap between the price for the old item at time t, ${\displaystyle P(M)_{t}}$, with the price of the new item at the later time period, ${\displaystyle P(N)_{t+1}}$.

• The overlap method uses prices collected for both items in both time periods, t and t+1. The price relative ${\displaystyle {P(N)_{t+1}}}$/${\displaystyle {P(N)_{t}}}$ is used.
• The direct comparison method assumes that the difference in the price of the two items is not due to quality change, so the entire price difference is used in the index. ${\displaystyle P(N)_{t+1}}$/${\displaystyle P(M)_{t}}$ is used as the price relative.
• The link-to-show-no-change assumes the opposite of the direct comparison method; it assumes that the entire difference between the two items is due to the change in quality. The price relative based on link-to-show-no-change is 1.
• The deletion method simply leaves the price relative for the changing item out of the price index. This is equivalent to using the average of other price relatives in the index as the price relative for the changing item. Similarly, class mean imputation uses the average price relative for items with similar characteristics (physical, geographic, economic, etc.) to M and N.

Source of the article : Wikipedia