This interesting article (with minor editing) was published in Business Line, Hindu Group of Papers (India), on Jun 11, 2002 by G. Ramachandran
MEAN income is a popular statistical measure used by experts and common folk to measure and to describe the prosperity of nations. Per capita incomes and mean household incomes are widely used by economists and policy-makers in government and by analysts and marketers to make important inferences and decisions. The widespread acceptance of mean is due to the simplicity with which it can be calculated. It is used widely as a result of the ease with which it can be visualised by those interested in measurement and comparison. Mean is the expected value of a random variable. But it has important limitations in its ability to convey critical and defining characteristics vis-à-vis the other statistical measure, MODE.
A neighbourhood where nine households earn $1,000 each and one household earns $6,000 has the same mean household income as another where nine households earn $500 each and one household earns $10,500. Their mean household income is $1,500. However, the modal, or most frequently observed, income of the first neighbourhood is $1,000 while it is only $500 in the second. The limitation of averages has a larger and deeper impact on economic and business policies that are derived from mean incomes. The neighbourhood with the lower modal income is unlikely to be a promising market for some goods that have a high sticker price. The neighbourhood with the higher modal income is unlikely to be interested in some goods that have a low sticker price. If both neighbourhoods are in the same economy and if households compete for jobs, it is very likely that wage competition would be intense in the neighbourhood with a modal income of $500.
It is easy to see why and how modal income influences wage aspirations and the willingness of households to invest in new skills. It is also easy to see how modal income influences the supply of human resources, and thereby aggregate demand and the size of markets. From such a perspective, the neighbourhood with the modal income of $500 might respond more vigorously to stimulus aimed at growth. When households break out of the lower modal income, they would push the mean household income beyond $1,500. It is easy to see why and how modal incomes and the principal factors that give rise to modal incomes are more important than mean incomes.
The Indian economy resembles the second neighbourhood. The per capita annual income is about $460, higher than that of 41 countries. But there are more poor households in India than in all of Africa, Asia and Central America. Why? The modal or most frequently observed income is less than $100, which makes most Indian households poorer than those in Angola, Burundi and Congo. Therefore, the analysis of modal incomes in the Indian economy could provide a new thrust to the generation of new income-producing opportunities in India and to aggregate growth.
Income Analysis:
Income analysis has an overwhelming influence over the inferences and recommendations of development institutions such as the World Bank. Their methodologies have influenced the formulation of poverty-alleviation policies by many governments. Comparative analyses of mean incomes are an important component of these methodologies. Time-series analysis involves comparisons of mean incomes of the same country or region but at different times. Cross-sectional analysis involves comparisons of mean incomes at a point in time of two or more countries or regions.
The purpose of cross-sectional analysis is to enable the formulation and implementation of policies that could lead to better incomes. But if the analysis is confined to mean incomes, there may be little to learn and emulate. Dr Branko Milanovic, a leading economist and researcher, has found that inequality in world income is very high more because of differences between mean country incomes than because of inequality within countries. Development economists may infer that domestic inequality in mean incomes is not as critical an issue as global inequality in mean incomes. They may argue for a better and more equitable world order, but this article would disappoint them by arguing for a better and more proactive domestic economy.
Neighbourhood Effect:
The rich seek privileges, while the poor are concerned about inequality. Privileges too are the outcomes of inequality. However, inequality is more poignant to the poor than to the rich. Hence, inequality is starker when 20 per cent of a population is poor and 80 per cent is rich than when 20 per cent is rich and 80 per cent is poor. Income inequality is a critical social issue in the OECD economies rather than in India. When many households in a locale have meagre incomes, only a few households feel poor. Remember Winston Churchill’s famous saying “beggars do not envy millionaires, though of course they will envy other beggars”. When neighbourhoods operate in isolation, there is relative satiation that modifies the effort expended by households towards earning higher incomes. This explains why households around the world tend to choose `comfortable neighbourhoods' in their domestic economies where they do not feel too unequal, but have better bargaining power than their neighbours.
However, in the long run, the neighbourhood modifies the effort expended by all households towards earning higher incomes. Dr Milanovic's research results are not surprising. Poor countries continue to remain poor for many reasons, but their low modal incomes and their neighbourhoods that operate in isolation are perhaps the most fundamental reasons. India should, therefore, focus on the modal incomes of households in every neighbourhood and on the mobility of human resources.
Income Expectations:
Households are exposed primarily to the incomes and purchasing power of other households in their immediate neighbourhood. Their exposure to the incomes and purchasing power of households in a distant neighbourhood is secondary. Hence, local incomes and purchasing power are the fundamental determinants of local prosperity. It is unlikely that a skin specialist would choose to practise in a locale where the modal income is low. Low modal income would adversely affect the specialist's income. The specialist's decision to ignore a neighbourhood would, in turn, adversely affect its mean income.
Every neighbourhood is a unique ecosystem with particular marginal costs and revenues, and particular opportunity costs and revenues. The costs and income expectations are driven by the neighbourhood's modal income. This is particularly important when services are produced by human effort but cannot be stored or transported. Such services constitute more than 30 per cent of India's economy. E-enabled services and remote servicing of customers could favourably alter the determinants of prosperity someday. But it could take long. In the meanwhile, smart governments could work on costs and income expectations by improving the terms of trade in their locales. The income of a skin specialist is determined by the number of customers and their individual capability to spend than by the mean income of customers. If households from several neighbourhoods could access the skin specialist, the specialist may choose to practise in a neighbourhood though its modal income is low. The mode of access -say, a system of roads - would make up for the low modal income. Roads and reliable transport overcome the inherent limitations of low modal incomes of neighbourhoods.
Empirical Evidence:
Many analysts assume that prosperity in the US is driven by urban, non-agrarian activities in the metropolises. Empirical evidence shows that 52 of the 250 richest counties are not metropolitan counties. The 52 counties derive their incomes from an interesting mix of income-producing activities, though they are agrarian at the core. They have generated new income-producing opportunities as a response to local modal incomes and local demand. Political will and administrative conscientiousness have made a difference to states such as Iowa. Linn and Polk counties in Iowa are in the midst of agrarian activities related to corn, soybean and hogs. Are they non-metropolitan? They are among the 198 richest metropolitan counties in the US. They have overcome the inherent limitations of low modal incomes imposed by agrarian activities.
By contrast, counties that have not overcome the inherent limitations of low modal incomes imposed by agrarian activities have lagged; 240 of the 250 poorest counties are not metropolitan counties. They are driven by agrarian activities. Kings County in California is among the 250 poorest counties, though California has a much higher mean income than Iowa. However, no county from Iowa is among the 250 poorest. Agriculture is not a hurdle to prosperity. Wichita and Haskell counties in Kansas continue to be agrarian and non-metropolitan but are among the 250 richest counties because they have found complementary sources of income. Empirical analysis of the 3,110 counties in the US shows that political will, administrative conscientiousness and the effectiveness of local governance make a vital difference to the domestic economy. These could be emulated in India.
States that are committed to improving the incomes of households could focus on the factors that affect modal incomes. An objective analysis of income-producing opportunities would show that most people earn their livelihoods in their neighbourhoods because of the purchasing power of their neighbours. That is the mode! The same analysis would show that most people who earn meagre incomes have failed to connect adequately with the purchasing power of their neighbours. Governments could, therefore, ask how they could make more people connect with more purchasing power in a bigger neighbourhood. Efforts in this direction would lead to the generation of new income-producing opportunities and to higher modal incomes and higher mean incomes.
MEAN income is a popular statistical measure used by experts and common folk to measure and to describe the prosperity of nations. Per capita incomes and mean household incomes are widely used by economists and policy-makers in government and by analysts and marketers to make important inferences and decisions. The widespread acceptance of mean is due to the simplicity with which it can be calculated. It is used widely as a result of the ease with which it can be visualised by those interested in measurement and comparison. Mean is the expected value of a random variable. But it has important limitations in its ability to convey critical and defining characteristics vis-à-vis the other statistical measure, MODE.
A neighbourhood where nine households earn $1,000 each and one household earns $6,000 has the same mean household income as another where nine households earn $500 each and one household earns $10,500. Their mean household income is $1,500. However, the modal, or most frequently observed, income of the first neighbourhood is $1,000 while it is only $500 in the second. The limitation of averages has a larger and deeper impact on economic and business policies that are derived from mean incomes. The neighbourhood with the lower modal income is unlikely to be a promising market for some goods that have a high sticker price. The neighbourhood with the higher modal income is unlikely to be interested in some goods that have a low sticker price. If both neighbourhoods are in the same economy and if households compete for jobs, it is very likely that wage competition would be intense in the neighbourhood with a modal income of $500.
It is easy to see why and how modal income influences wage aspirations and the willingness of households to invest in new skills. It is also easy to see how modal income influences the supply of human resources, and thereby aggregate demand and the size of markets. From such a perspective, the neighbourhood with the modal income of $500 might respond more vigorously to stimulus aimed at growth. When households break out of the lower modal income, they would push the mean household income beyond $1,500. It is easy to see why and how modal incomes and the principal factors that give rise to modal incomes are more important than mean incomes.
The Indian economy resembles the second neighbourhood. The per capita annual income is about $460, higher than that of 41 countries. But there are more poor households in India than in all of Africa, Asia and Central America. Why? The modal or most frequently observed income is less than $100, which makes most Indian households poorer than those in Angola, Burundi and Congo. Therefore, the analysis of modal incomes in the Indian economy could provide a new thrust to the generation of new income-producing opportunities in India and to aggregate growth.
Income Analysis:
Income analysis has an overwhelming influence over the inferences and recommendations of development institutions such as the World Bank. Their methodologies have influenced the formulation of poverty-alleviation policies by many governments. Comparative analyses of mean incomes are an important component of these methodologies. Time-series analysis involves comparisons of mean incomes of the same country or region but at different times. Cross-sectional analysis involves comparisons of mean incomes at a point in time of two or more countries or regions.
The purpose of cross-sectional analysis is to enable the formulation and implementation of policies that could lead to better incomes. But if the analysis is confined to mean incomes, there may be little to learn and emulate. Dr Branko Milanovic, a leading economist and researcher, has found that inequality in world income is very high more because of differences between mean country incomes than because of inequality within countries. Development economists may infer that domestic inequality in mean incomes is not as critical an issue as global inequality in mean incomes. They may argue for a better and more equitable world order, but this article would disappoint them by arguing for a better and more proactive domestic economy.
Neighbourhood Effect:
The rich seek privileges, while the poor are concerned about inequality. Privileges too are the outcomes of inequality. However, inequality is more poignant to the poor than to the rich. Hence, inequality is starker when 20 per cent of a population is poor and 80 per cent is rich than when 20 per cent is rich and 80 per cent is poor. Income inequality is a critical social issue in the OECD economies rather than in India. When many households in a locale have meagre incomes, only a few households feel poor. Remember Winston Churchill’s famous saying “beggars do not envy millionaires, though of course they will envy other beggars”. When neighbourhoods operate in isolation, there is relative satiation that modifies the effort expended by households towards earning higher incomes. This explains why households around the world tend to choose `comfortable neighbourhoods' in their domestic economies where they do not feel too unequal, but have better bargaining power than their neighbours.
However, in the long run, the neighbourhood modifies the effort expended by all households towards earning higher incomes. Dr Milanovic's research results are not surprising. Poor countries continue to remain poor for many reasons, but their low modal incomes and their neighbourhoods that operate in isolation are perhaps the most fundamental reasons. India should, therefore, focus on the modal incomes of households in every neighbourhood and on the mobility of human resources.
Income Expectations:
Households are exposed primarily to the incomes and purchasing power of other households in their immediate neighbourhood. Their exposure to the incomes and purchasing power of households in a distant neighbourhood is secondary. Hence, local incomes and purchasing power are the fundamental determinants of local prosperity. It is unlikely that a skin specialist would choose to practise in a locale where the modal income is low. Low modal income would adversely affect the specialist's income. The specialist's decision to ignore a neighbourhood would, in turn, adversely affect its mean income.
Every neighbourhood is a unique ecosystem with particular marginal costs and revenues, and particular opportunity costs and revenues. The costs and income expectations are driven by the neighbourhood's modal income. This is particularly important when services are produced by human effort but cannot be stored or transported. Such services constitute more than 30 per cent of India's economy. E-enabled services and remote servicing of customers could favourably alter the determinants of prosperity someday. But it could take long. In the meanwhile, smart governments could work on costs and income expectations by improving the terms of trade in their locales. The income of a skin specialist is determined by the number of customers and their individual capability to spend than by the mean income of customers. If households from several neighbourhoods could access the skin specialist, the specialist may choose to practise in a neighbourhood though its modal income is low. The mode of access -say, a system of roads - would make up for the low modal income. Roads and reliable transport overcome the inherent limitations of low modal incomes of neighbourhoods.
Empirical Evidence:
Many analysts assume that prosperity in the US is driven by urban, non-agrarian activities in the metropolises. Empirical evidence shows that 52 of the 250 richest counties are not metropolitan counties. The 52 counties derive their incomes from an interesting mix of income-producing activities, though they are agrarian at the core. They have generated new income-producing opportunities as a response to local modal incomes and local demand. Political will and administrative conscientiousness have made a difference to states such as Iowa. Linn and Polk counties in Iowa are in the midst of agrarian activities related to corn, soybean and hogs. Are they non-metropolitan? They are among the 198 richest metropolitan counties in the US. They have overcome the inherent limitations of low modal incomes imposed by agrarian activities.
By contrast, counties that have not overcome the inherent limitations of low modal incomes imposed by agrarian activities have lagged; 240 of the 250 poorest counties are not metropolitan counties. They are driven by agrarian activities. Kings County in California is among the 250 poorest counties, though California has a much higher mean income than Iowa. However, no county from Iowa is among the 250 poorest. Agriculture is not a hurdle to prosperity. Wichita and Haskell counties in Kansas continue to be agrarian and non-metropolitan but are among the 250 richest counties because they have found complementary sources of income. Empirical analysis of the 3,110 counties in the US shows that political will, administrative conscientiousness and the effectiveness of local governance make a vital difference to the domestic economy. These could be emulated in India.
States that are committed to improving the incomes of households could focus on the factors that affect modal incomes. An objective analysis of income-producing opportunities would show that most people earn their livelihoods in their neighbourhoods because of the purchasing power of their neighbours. That is the mode! The same analysis would show that most people who earn meagre incomes have failed to connect adequately with the purchasing power of their neighbours. Governments could, therefore, ask how they could make more people connect with more purchasing power in a bigger neighbourhood. Efforts in this direction would lead to the generation of new income-producing opportunities and to higher modal incomes and higher mean incomes.
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