Measures Of Poverty In Economic Sense: A Critical Evaluation

1. Using one of the models of co-ordination failure, explain why transportation is a challenge in developing countries. Describe the strategies these developing countries can adopt to overcome problems of co-ordination failure in the transportation sector.

2. Critically evaluate the different measures of poverty and how this might influence the impact of poverty on economic growth and well-being.

3. Discuss with the aid of examples, the constraints to the development of the agricultural sector in developing countries. Suggest some policies that could be applied to overcome some of these constraints.

4. Deforestation, water pollution and the loss of biodiversity are known to be some of the effects of climate change. Explain with the aid of examples and evidence, the extent to which addressing any two of these factors has a successful impact on development.

Concept of Poverty in Economics

Over years, the global economy has undergone considerable changes and experienced huge dynamics, affecting the overall standard of living of the population of the different countries positively as well as negatively (Uribe and Schmitt-Grohé 2017). However, over the years, several issues hav`e remained issues of global concern due to the nature and expanse of the same of which one of the primary issues have been that of poverty.

The concept of poverty in terms of economics, have changed considerably with time owing to the dynamics in the global economy, which in turn has led to varied definition of the same across different regions. However, in general the term “poverty” refers to the state of deprivation from the basic amenities and materialistic facilities of life, which decreases the well-being of people in general (Siteresources.worldbank.org, 2018).

Keeping this into consideration different measures have been developed over the last few decades, in order to comprehensively measure the burden of poverty in the different countries in order to address to the issues of poverty and deprivation of the population of the same. The essay tries to critically evaluate the existing measures of poverty in economic sense, in order to analyze the impacts of the same on the overall economic growth of the countries and well-being of the population.

The word “Poverty”, in the broad sense of the term refers to the situation of deprivation, where the basic needs of sustenance for people, including those of food, shelter and clothing, are not being met by the level of economic resources, which the concerned people have in their hands. In the previous years, the notion of poverty in an economy used to be mainly restricted to the absence of monetary and financial resources in a sector of the population in a country (Fankhauser and Stern 2016). There existed the concept of “Trickle Down” among the economists, according to which, the benefits of economic progress of a country, with time, is expected to trickle down from the wealthy sections to all the socio-economic strata of the country.

However, the Trickle Down Theory was not seen to be considerably credible as with time and progress of the global economy as a whole, the global poverty burden was also observed to be increasing visibly. The concept of poverty also became more inclusive, comprising of not only monetary deprivations, but also of deprivations of other welfare increasing attributes like health care, education, employment and other aspects of human life (Bertrand and Morse 2016).

Measures of Poverty in Economics

As is evident from the above figure, there remained a considerably high share of population in the global framework that remained in extreme poverty, with the share showing an increasing trend till 1980’s, post which the share decreased considerably. However, the share of population experiencing not so extreme poverty remained consistently high, which indicates towards the fact that economic growth does not necessarily solve the problem of poverty and also asserts that trickle down mechanism does not work in real case scenarios (Jolliffe and Prydz 2015).

Measuring the extent and nature of poverty efficiently has always remained one of the primary concerns of the policy makers and economists around the globe.  This is primarily because much of the construction as well as implementation of the poverty alleviation policies as well as their implications on the populations of the concerned countries depends on how poverty is measured in the concerned countries (Dhongde and Minoiu 2013).

The problem of poverty has also been divided into different classifications according to their nature and extent. In broad sense, poverty can be divided into two types- absolute poverty and relative poverty. The measures of poverty also have varied according to these classifications (Corazzini, Esposito and Majorano 2012).

Absolute Poverty- Absolute poverty is measured in terms of a conventional standard, which remains consistent between different countries and over periods. For the measurement of absolute poverty, the concept of “Poverty Line” was first introduced as a standard of measurement of absolute poverty. The poverty line is a conventionally set standard showing the amount of daily income of an individual, which is required for the same to meet the basic needs of life and to sustain himself (MacInnes et al. 2014). Any person with daily income less than that set as the conventional standard is said to live below the poverty line, thereby being considered as poor.

Relative Poverty- The concept of relative poverty defines poverty of an individual with respect to the society in which the same lives. The relative poverty in a country or society is measured in terms of the share of population of the country with income below a fixed proportion of the median income of the residents of the country (Brady and Bostic 2015). There are several measures of poverty, both absolute as well as relative, which are widely used to measure poverty.

The most easily comprehended measure of poverty, widely used in the global framework is the Headcount Index. It is a type of absolute measure of poverty, which measures the share of population in a country, which is poor based on some previously set standard of poverty.

Absolute Poverty

Head count index (P0) = Np/N, where, N is the total number of population and Np is the number of people in the population who are poor.

However, the head count index only takes into account the number of poor people in the country and is not able to measure how poor they are, that is the measure cannot take into account the extent of poverty. Thus, it also becomes inefficient in the aspect of comparing the poverties of different countries as only the number of poor people in the countries is not sufficient to know the burden of poverty (Whelan, Nolan and Maitre 2014).

Another measure is that of the Poverty Gap Index, which tries to measure the extent of poverty in a society. The index adds up the magnitude by which the individuals in a society remain below the poverty line on an average and the measure represents the same as a percentage of the poverty line of the country. It can be expressed as follows:

Poverty Gap (Gi) = (z-yi).I(yi<z)

Where, z is the conventionally set poverty line and yi is the income of the poor individuals who are below the poverty line. Here, only poor individuals are considered and for any one with income above the poverty line the gap is considered zero.

Therefore, Poverty Gap Index (P1) = 1/N. [∑(Gi/z)].

This index is widely used as a measure for the cost of eliminating poverty as a whole in a society. This, however, though sounds easy hypothetically becomes difficult to be implemented in real case scenarios as perfect efficient transfer of lump sum amounts is not plausible (Hall and Patrinos 2012).

Another measure of poverty has also been widely used known as the Squared Poverty Gap Index, which has been designed to measure the inequality among the poor population of the country. The index is the weighted sum of all the poverty gaps, with the weights being proportionate poverty gaps and is expressed as follows:

P2 = 1/N[∑(Gi/z)²]

This measure is used as a measure of severity of poverty. However, the complexity of the measure makes it not easy to comprehend.

All the above-mentioned measures are strictly cardinal and cannot take into account the ordinal aspects of poverty and deprivation. Taking this into consideration, the Human Poverty Index have been developed which again has two sub measures, HPI1 and HPI2, the former being for developing countries and the latter being for high income OECD ones.

Relative Poverty

HPI1= [1/3(P1³+P2³+P3³)]^1/3,

P1= Probability (at birth) of not surviving to 40 years

P2= Rate of adult literacy

P3 = Average of population deprived of access to pure water and underweight children

HPI2 = [1/4(P1³+P2³+P3³+P4³)]^1/3,

P1= Probability (at birth) of not surviving till 60  years

P2= Number of adults without functional literacy skills

P3= Population below the poverty line

P4= Long term unemployment rate

This measure is first of its kind, which tries to take all the aspect of deprivation, in order to measure the real extent of poverty in all sectors of life and with respect to the economic conditions of the country (Alkire, Conconi and Seth 2014). This measure helps the policy makers to observe the poverty in the countries in a more inclusive manner, thereby helping them to design policies targeted for not only increasing the economic but also the overall welfare of the population of the countries.

Conclusion

From the above discussion, it can be asserted that there exist different measures for calculating the extent of poverty, both globally as well as specific to the countries individually. However, it can also be concluded that with time and with the increasingly inclusive definitions of poverty as a social and economic problem, the measures of poverty have also changed significantly, from being single dimensional and income specific to multi dimensional, incorporating different aspects of human life and welfare. These inclusive measures are found to be more effective in measuring the nature and extent of poverty and help the policy makers to make robust policies to address to the situation of poverty in the global scenario.

References

Alkire, S., Conconi, A. and Seth, S., 2014. Multidimensional Poverty Index 2014: Brief methodological note and results.

Bertrand, M. and Morse, A., 2016. Trickle-down consumption. Review of Economics and Statistics, 98(5), pp.863-879.

Brady, D. and Bostic, A., 2015. Paradoxes of social policy: Welfare transfers, relative poverty, and redistribution preferences. American Sociological Review, 80(2), pp.268-298.

Corazzini, L., Esposito, L. and Majorano, F., 2012. Reign in hell or serve in heaven? A cross-country journey into the relative vs absolute perceptions of wellbeing. Journal of Economic Behavior & Organization, 81(3), pp.715-730.

Dhongde, S. and Minoiu, C., 2013. Global poverty estimates: A sensitivity analysis. World Development, 44, pp.1-13.

Fankhauser, S. and Stern, N., 2016. Climate change, development, poverty and economics.

Hall, G.H. and Patrinos, H.A. eds., 2012. Indigenous peoples, poverty, and development. Cambridge University Press.

Jolliffe, D. and Prydz, E.B., 2015. Global poverty goals and prices: how purchasing power parity matters.

MacInnes, T., Bushe, S., Tinson, A., Born, T.B. and Aldridge, H., 2014. Monitoring poverty and social exclusion 2014. York: Joseph Rowntree Foundation.

Ourworldindata.org (2018). Global Extreme Poverty - Our World in Data. [online] Our World in Data. Available at: https://ourworldindata.org/extreme-poverty [Accessed 1 Mar. 2018].

Siteresources.worldbank.org. (2018). Chapter 4. Measures of Poverty. [online] Available at: https://siteresources.worldbank.org/PGLP/Resources/povertymanual_ch4.pdf [Accessed 1 Mar. 2018].

Uribe, M. and Schmitt-Grohé, S., 2017. Open economy macroeconomics. Princeton University Press.

Whelan, C.T., Nolan, B. and Maitre, B., 2014. Multidimensional poverty measurement in Europe: An application of the adjusted headcount approach. Journal of European Social Policy, 24(2), pp.183-197.