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The Retail Price Index

The Retail Price Index (RPI) is the most familiar measurement of inflation. It measures the change over a period of time usually month to month in the prices of goods purchased in households. The spending pattern on which the index is based is changed from year to year and it depends from country to country. It uses information from the Expenditure and Index Survey. It excludes the pensioners and the high society households. It represents a variety of goods and overall around 650 different types of goods and services. The index considers more than 100000 different price quotations and they are used each month in compiling the index which is published the following month. It is usually used for private contracts for upgrading of contracts of maintenance payments and housing rents. It is also used for wage bargaining. It has started since June 1947 and the base was shifted to 100 in Jan 1987.

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Like any price index the RPI is constructed in the following manner:

A base year or a starting point is chosen. This basically becomes the standard against which the price changes will be measured.

Then lists of items are selected that an average household would buy. This item is collected from a survey that is conducted.

Set of weights are calculated showing the importance of items it carries on average in the family budget, the greater the share of the bill the greater is the weight of the item.

The price of each item is then multiplied by its subsequent weight, thus adjusting the items size proportion to its importance.

The price for each item must be found in both the base year and the year of comparison.

There are different versions of RPI along to the main figure:

RPIX- this does not include mortgage interest payment.

RPIY- this excludes mortgage repayments and indirect taxes (VAT, council tax, excise duty, vehicle duty, etc.)

Tax and Price Index.

The Consumer Price Index is also known as the RPI. It measures the price of a constant basket of goods from the market and it does this from one period to another and it is from the same locality and area. This index basically is for the typical kind of consumers and the market goods typically purchased by different households. It is very helpful for estimating inflation. It is also used to measure the effect of inflation on the value of real money, the mediums of exchanges, wages, and salaries. It is a very important tool of the national economic statistics in the United Kingdom.

The major groups that are covered in the calculation on RPI are:


Alcohol drinks (off sales) and Tobacco

Clothing and Footwear

Housing, Fuel and Light.

Housing Goods and Domestic Services

Personal Goods and Services (health related)

Motoring Expenditure, fares and other travel costs.

Leisure goods and services

Catering and alcohol drinks (on sales)

It is important to note that although the RPI and the CPI are calculated using the same underlying price data they use different classification systems. To be more precise the CPI is based on the international classification system COICOP (classification of individual consumption by purpose). These are then added to the different groups of RPI.


An increase in the price of fruits and vegetables to less healthy foods could reduce consumers' incentives to purchase fruits and vegetables and result in less healthy diets. Whether such a change in relative prices and incentives has occurred is difficult to prove because of substantial quality improvements in many fresh fruits and vegetables. For the commonly consumed fresh fruits and vegetables for which quality has remained fairly constant, analysis of price trends reveal a price decline similar to that of dessert and snack foods.

In theory, it should be easy to compare food prices from decades ago to current prices and demonstrate whether relative prices of healthy and non healthy foods have changed. In practice, an increase in the relative prices of fresh fruits and vegetables is difficult to prove. Standard price comparisons using RPI numbers suggest that price that price of fresh fruits and vegetables have increased relatives to prices of other products. However, these numbers have been shown to overstate the rate of price increase for many types of foods, especially for fresh fruits and vegetables. The main reason for computing the price change is the change in quality of the goods, availability and packaging. Thus we shall see whether the prices have actually changed over a period of time by holding the quality constant.

Index adjusted price trends for these largely unchanged fruits and vegetables show patterns similar to those of the less healthy foods. Prices for healthy and unhealthy foods declined at the same rate as compared to other foods.

Specifically from 1980 to 2006, the index adjusted prices of chocolate chip cookies, cola, ice cream, and potato chips fell by 0.5-1.7% each year. During the same period the index adjusted prices of apples, bananas, and iceberg lettuce and dry beans fell by an average of 0.8-1.6% each year. The prices of cabbage, carrots, celery, cucumbers and peppers fell by an average of 0.5 to 1.5% each year.

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Rising price trends were noticed for broccoli and field grown tomatoes. These trends are non-counter examples but reveal the selection process was not exclusive enough to screen out all foods that have undergone quality change. The price trend evidence is specific to the foods examined and also suggests that the price of a healthy diet has not changed relatively to the price of an unhealthy diet, although a healthy diet might not include all kinds of fresh fruits and vegetables.

Many innovative fresh fruits and vegetable products have been introduced in recent years. These newer products account for a growing share of produce sold by retailers. The growing availability of such products suggests that many consumers value these innovations. A remaining question is whether low-income households also share in the benefits provided by foods that are more convenient and more readily available.

Many newer and fresh fruits have grown in popularity and now account for a significant portion on what households spend on produce. Due to this there is change in price as there are fluctuations in demand thus causing significant change in supply.


We will now forecast the price of fresh vegetables by using the RPI.

We assume a whole basket of vegetables that are used in a household and we assume the price of the same for few of the months.

Line of Best Fit = b

b= (n∑xy-∑x∑y)



b= (14*42962.46-200*3000)











e.g. 1) if we assume that for the month of March 2010 the price of the whole basket of vegetables is 21 which will be denoted by x in the above formulae then RPI which is denoted by y will be





(Rounded to 1 decimal point.)

In the 1st example we can see that if we price of the basket of vegetables increases the RPI also increases thus making the slope point in an upward direction. By this we can say that the RPI is directly related to the prices of goods and any change in the prices of goods causes the RPI to change in the same direction.

e.g. 2) if we assume for the month of March 2010 the RPI which is denoted by y is 218 then the price of the basket of vegetables which is denoted by x will be







(Rounded to 1 decimal point.)

In the above example we can see that if the RPI falls there if a fall in the prices of the basket of vegetables also. By this it is proved that the prices of vegetables are directly related to RPI.

This means that if inflation goes up, RPI also increases and the prices of vegetables also go up. The major assumption in the whole process is of linearity which means all other conditions and circumstances remain constant.

The Consumer Price Index may not defiantly answer how vegetable prices trended over the past several decades. The CPI overstates the rate of price of inflation as compared with what a true cost-of-living index would have reported. (The objective of CPI is to approximate a cost-of-living index. For example, if we compare the cost of living this year against that of the past year, the CPI should measure how much more {or less} households need to spend in order to achieve the same level of utility as they did in the previous year.)

We will now forecast the cost of ice creams.

Cost of the month of March 2010 = (80 * 1000) + 4%


Cost of the month of March 2010 = 888.89 + 4%

Cost of the month of March 2010 = 892.89

We are assuming in this that all other situation and prices remain constant and the price fluctuations are only and only due to the change in the Retail Price Index. This means that if we would want to produce 90 units in the month of Aug 2009 for e.g. then we would should just add the % change between Aug 2009 and Jan 2009 to the price of Jan 2009 as we have taken the base month as Jan 2009. In real life this is not possible as loads of other factors have to be considered before forecasting the price and thus the amount would differ from that of our calculation.

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The actual amount of any month would differ from that of what we have calculated but as the Retail Price Index has increased, meaning there is growth in inflation the price would me more than our forecast unless and until the factors that are considered in our forecast of Jan 2009 and the situation and prices of the other factors remain the same.

The main factors that are not considered in linearity is the fluctuation in demand and supply, and other factors such as technological, economical, geographical, political, climatic, etc. Thus in RPI the concept of linearity doesn't fit in well as it considers everything constant as that of the base year or month.

We also need to remember that forecast is always based on historical data and in order to forecast prices of the future it is very important to see how much of past data do we take into consideration. In some cases we need to take data of past few years while in many few months is sufficient.

For goods like ice creams we need to take into consideration historical data of particular months as that product is a seasonal product and the maximum sales happen in summer. Thus we need to take mainly into consideration the figures of summer. In that also we have to consider many years as just 1 year data is not sufficient for any proper forecasting.

The more data we have the better it is to forecast future figures. If we see the profit margins for a product like ice cream for the month of December for e.g. and decide to dissolve the organization it is not correct as the sales are not as they are in the month of May. To compare the sales of the month of May of just 2 years is also not sufficient as that is very less compare to that of 5 years. With the data of around 5 years it is very much sufficient to come to a conclusion of whether the organization is making any kind of profit or loss.

The reason for this also is that the first few years is the introduction phase of the product so the cost increases compared to that of the sales. Although the Retail Price Index is included in the cost of making of the product the returns aren't as much as they should be.

For product like vegetables the Retail Price Index calculation doesn't take into consideration the amount of rainfall. So even if the rate of inflation is low but due to lack of rainfall in the country the prices of vegetables can be very high and/ or increase in comparison to that of the previous month or year. If in a particular country vegetables are only imported then the RPI does matter as the price of vegetables would fluctuate in equal proportion with that of inflation in most of the cases.

The main reason for the change in Retail Price Index to that of the change in price is also the amount actually spent behind the goods. Each goods and services have been assigned particular weightings and this gives them the relative importance to other goods and services in the basket of goods. For e.g. 5 % increase in the cost of food items is more important to that of telephone as food products are used more and are more vital than telephone charges. Similarly if in a particular household certain goods are used more than compared to other goods or to other household and if the prices of those goods fluctuate in the upward direction in a massive way the personal expenditure and the personal price index would be larger to the index to the average consumers.

RPI is the base of forecasting any goods and services. If RPI would not be present our forecasting would not be correct as the % of inflation along with its change over the decades would not be available. By keeping this in mind we should also note that there would not be any kind of control on the prices of goods and services by corporate and individuals. E.g. If RPI would not be present we could probably end up paying £ 10 for 6 pints of milk or £ 1 for 6 pints of milk as retailers would only calculate certain costs and not other indirect expenses and direct expenses, which are considered for the calculation of inflation as well as the Retail Price Index.


Thus to conclude we can say that different households have demand of different goods and the Retail Price Index for each household varies, but the RPI of the country takes all households together and also the most commonly bought goods and services. Many of these goods are not even purchase by many houses.

The concept of linearity doesn't quiet fit into the calculation of RPI. Each product has its own weighting in the basket and thus holds that much amount of importance as compared to the other products. RPI differs from country to country and the method of calculation is also different and so are the goods and services. In agricultural countries the importance of RPI on the prices of vegetables is very different to those countries that are more on the industrial side and import vegetables.

RPI not only controls but also brings stability in the prices of goods and services that are commonly used by households. With RPI there isn't a vast difference in a price of a particular good between two or more retailers.


Economic Research Service - United States Department of Agriculture

Economic Research Report No. 55 (March 2008) - United States Department of Agriculture


National Statistics -

Wikipedia -

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