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Income Elasticity and What it Can Tell Us About Packaged Food

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How do the sizes of different packaged food categories change in relation to a variation in disposable income? Do all categories benefit equally from a rise in income, or do some categories decline when incomes rise as consumers trade up to more premium products? Knowing how demand for different products responds to income changes can help tackle many similar questions.

Figure 1. Income Volume Elasticity for Selected Packaged Food Categories

Source: Industry Demand Model (based on Packaged Food industry data)

Note: Long- run income volume elasticity (over five years), category averages for all geographies. Elasticity shows how volume consumption would change in response to a 1% increase in income.

Snack bars and baby food the most elastic and bread and pasta the least elastic

Figure 1 ranks packaged food categories by income elasticity. The figure refers to long-run global elasticity (averaged across 80 countries). Long run means that a cumulative five-year effect is
considered. Often, it takes time for people to adjust their purchasing habits as incomes rise, and long-run income elasticity allows for such dynamic effects.

Most categories in packaged food have income elasticity of 0.1 to 0.5, which means that they are inelastic. This is perfectly logical considering that as incomes rise and economies become more affluent, people tend to spend less on food as a proportion of total income.

Among the different packaged food categories, meal replacement and snack bars have the highest income elasticity of 0.67 and 0.51, respectively. This is not unexpected as these categories are generally more costly and are more “nice-to-have” than “need-to-have” products. In addition, snack foods are often purchased spontaneously and impulse products overall do better when consumers are less worried about the economy.

On the other hand, products such as bakery and pasta are the most inelastic. This can be attributed to their necessity nature. In many households bakery and pasta products are staple food items and volume demand does not change significantly depending on economic conditions.

How to read elasticity figures?

Elasticity is a unitless number and it measures how a change in one variable, let’s say consumer income, affects another, such as sales of noodles. Therefore, elasticity can be estimated between any two variables, for example income and market size or population growth and market size.

Income elasticity, which is the focus of this article, reveals how growing purchasing power affects category market sizes in volume terms. For example, Figure 2 illustrates how a 1% increase in income (measured as 1% growth in per capita real GDP) would affect chilled soup and instant noodles, with the volume sales of chilled soup expected to rise by 1.6%, or more than the rise in income, but only 0.2% for instant noodles. In the figure below, elasticity is represented by the slope of the curve.

Figure 2. Income Elasticity for Chilled Soup and Instant Noodles

Source: Euromonitor International

Income elasticity also depends on country – oils and fats example

There are also differences in income elasticity between countries, depending on whether the country is a developed or emerging economy, and reflecting different culinary traditions. Oils and fats is an example of a category with relatively low income elasticity of 0.23. Nevertheless, when we look at country by country, important differences start to emerge (Figure 3).

In oils and fats, for example, there is an apparent negative correlation between the category’s income elasticity and per capita GDP. Emerging economies such as China and Vietnam have moderate income elasticity for oils and fats, whereas in developed countries such as the US or Norway, income elasticity is close to zero. This suggests that in developed economies people already consume as much butter or margarine as they want regardless of the economic conditions as these are not very expensive products. As such, there is little room for volume sales to grow. On the other hand, in emerging economies, the category is still far from saturation level, and rise in income translates into significant growth of oils and fats sales, as people increase the variety and quantity of products of products purchased, also some people move from using home made products to packaged products.

Figure 3. Greece, Spain and Italy Form a High Elasticity Cluster in Oils and Fats

Source: Industry Demand Model (based on Packaged Food industry data)

Note: Circle size represents per capita value sales of oils and fats, 2012.

Moreover, even if the oils and fats category is on average quite inelastic, there are significant elasticity differences at a lower category level. As Figure 4 shows, olive oil is moderately elastic, with
estimated average elasticity of 0.96, while vegetable oil, margarine and cooking fats are very inelastic and drive the average elasticity of oils and fats down.

Figure 4. Olive Oil the Most Elastic of All Oils and Fats

Table 1: Leading Consumers of Olive Oil – Kg Per Capita, Retail Sales, 2012

Euromonitor International - Analysis - 2013-09-19_15.15.51


Source: Euromonitor International (Packaged Food)

Income elasticity can help prepare for a slowdown or improvement in economic conditions

Income elasticity is a useful analytical measure which can answer a broad range of questions. It can tell you a market’s response to fluctuations in GDP, which is especially relevant in a post-global
economic crisis period. In a case of economic slowdown, elastic categories would experience a greater decrease in volume sales while inelastic categories would be less affected and remain a safer option. On the other hand, an economic boom would bring about a greater increase in volume sales in elastic categories.

Moreover, income elasticity can provide insight on market saturation levels, which can help predict consumer behaviour. Products that have low income elasticity are considered necessities and have a threshold of maximum consumption. This implies that an increase in income would not have a strong positive effect on consumption of those products, and hence the market may be considered saturated.

Euromonitor International has been developing econometric product demand models for the packaged food and beauty and personal care markets, which we will begin featuring more often. The models track variables such as growth in income, changes in price and population growth as well as industry-specific variables, looking to what extent each of them can explain historical market dynamics and predict future trends. All of these are based on Passport data.

A second article will delve deeper into price elasticity and how changes in price affect demand in specific categories.

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