A Different Approach to Understanding Poverty - Essay Example

Poverty and inequality Poverty is the situation where one has less than others have in the society, or community within which one resides. In poverty analysis, how one perceives his or her wealth determines the social welfare of that person. The use of a relative poverty line in studying the poverty standards of a society enables one to realize the welfare variance between those considered rich and the poor by societal guidelines. In the society today, determining poverty means considering the ability of an individual to meet specific welfare needs. A person’s income directly influences their ability to meet their welfare needs within the society; this is the most common way of measuring poverty in a population. Contemporary scholars of poverty offer a different approach towards understanding poverty. In contemporary view, poverty is multidimensional and it is not dependent on income alone, rather it depends on lack of capabilities, deprivation or lack of resources and other important aspects such as security, rights and freedoms. Most traditional scholars depended on the traditional method of indexing poverty levels but the contemporary view has been helpful in giving clearer methods of dealing with poverty. Multidimensional study of poverty may take on the objective and subjective references in measurement of data. Measurement may also be dependent on the relative and absolute approaches in the references. In this discourse, several indices applying the latter and former methods will be under application in determining poverty and inequality. In order to calculate inequality, however, one has to understand what inequality means in an economic perspective in relation to poverty. In any given population, there is a difference between what people within the population earn. The uneven distribution of income in any given population is income inequality. In order for there to be income, there has to be several sources of income. These sources of income may be combinational or independent per person receiving the income. Income may result from wages, rent, bank account interests, salaries or even profits made in business transactions ( Stiglitz, 2012). In order to understand the complexities of economic inequality, the best specimen to use for the study is a family. In the study, the family’s income is under analysis, and then the family members ranked from the lowest income earner to the highest income earner. After the ranking, the incomes aid in establishing a Lorenz curve that is important in analysis of income. In order for a Lorenz curve to be correct, the incomes of the family members have to be divided into fifths (Lorenz, 1905). A Lorenz curve enables analysis of data by adding the percentage value of the lowest fifth to the next higher fifth, which becomes the first point of the curve. The second point in the curve comes about through adding the first point to the middle fifth of the derived incomes. The process of plotting continues until exhaustion of all cumulative values of member incomes (Lorenz, 1905). For a perfect Lorenz curve, all members in a family would earn the same amount and the Lorenz curve would be a diagonal with the lowest point being the lower left hand corner moving progressively towards the higher right hand corner. This diagonal shows an ideal situation and it is the baseline in determining income inequality. Since not all family members receive an equal income, the Lorenz curve turns out as a curve instead of a diagonal. The area between the curve and the diagonal dictates the measure of inequality from one member of a given family to the next member (Lorenz, 1905). Income inequality is a broad topic with numerous key issues to discuss. In this research, income inequality will be under analysis in relation to poverty. Understanding the several key factors in determining the poverty level and inequality levels using various indices enables one to understand the impact of poverty and inequality in the society. Understanding income inequality is important since it has been a major issue in predicting economic growth and development globally. Income inequality has always been an area of contention between capitalists and communists whether it is good or bad (Pikketty, 2014). Understanding how income inequality affect the society gives one the tools necessary in making an ethical standpoint on whether it is a good thing or vice versa (Pikketty, 2014). Understanding the relationship between poverty and inequality is more important since it offers insights on reducing poverty. Poverty and inequality indices Head count index (FGT0) The head count index involves determining the proportion of people living below the poverty line. It measures the proportion of the population determined as poor by societal norm. Head count index method is the most commonly used method in calculating the poverty index. In the head count index, the poor are usually Po Po=Np/N Np represents the number of poor people in a population while N is the number of the total population in that society. The head count index takes the form shown below for easier calculation. The equation means that I is the indicator that has a value of 1. The value of I is 1 if only the condition in the brackets is true. Yi represents expenditure and if it is less than Z, which is the poverty line, the expression is true hence, the value of I is 1. When the value of I is 1, the equation means that the household falls to a poor household. The headcount index method is easy to understand and carry out, which is its major strength. This indexing method, however, has several setbacks that make it unideal for use in several situations. This indexing method fails to take into account the poverty intensity into account. The head count index principle gives a generalized view of the poverty level. A generalized perception of poverty violates Dalton’s idea of the transfer principle. In 1920, Dalton formulated an idea that if a rich person gave wealth to a poor person, the wealth would enable the poor person become richer by reducing the intensity of the poverty (Dalton, 19200. Even if the wealth given to the poor person did not take him or her above the poverty line, it helped in improving the welfare of the poor. Another limitation of the head count index is that it does not indicate how poor the poor people are, hence there is no change to it despite change in the level of poverty. According to the head count index, there is no change if a person below the poverty line becomes poorer. Static values offer inaccuracy in understanding the level of poverty within a given economy since they do not reflect the dynamics involved in improving economies or reducing incomes. The final limitation associated with the head count index mechanism arises due to the calculation of poverty in groups. The head count index calculates the poverty of a society by determining the percentage of households below the poverty line. The outcome determines the poverty of the society, which is usually inaccurate. Determining poverty should be individualistic so that the number of people in a household, or the number of people living below the poverty line does not bias the rest of the population. Poverty gap index (FGT1) This method is moderately popular, and it adds up the extent to which people fall under the poverty line, it then expresses the extent as a percentage of the poverty line. The poverty gap Gi is the difference between the poverty line Z and the actual income Yi for the poor people. The poverty gap index assumes that the poverty gap for everyone else above the poverty line is zero. Gi = (z − yi ).I ( yi 0) In the equation, Z is the poverty line and α is the measure of sensitivity the index has towards poverty. The poverty gap for an individual in this case is Gi=z-Xi where Xi is the expenditure per capita of the ith person in the household. In that case, when α has a parameter of zero, then Po is the head count index. When the value passed to alpha is 1 the poverty gap index translates to P1 and when alpha is 2 the poverty severity index translates to P2. According to the above formulas, it is clear that some measures of poverty differ due to the intensity of poverty and the poverty gap index. The measures may differ in cases where there are few poor people but the intensity of the poverty lies far from the poverty line. The latter increases the poverty index by a significant margin, without taking into consideration the poverty gap of the people above the poverty line. In other cases, the index measures the intensity of poor people in relation to the poverty line;hence, it differs with a measure that assumes the intensity. This observation gives a clear insight on why some indexing methods are better suited for application in differing circumstances as opposed to others. Different indexing methods give different poverty indexes in the same economy and it is important to determine the target of a given index measurement in order to determine the best indexing method to use. In some cases, all the methods are applicable in order to give a complete perspective of the poverty situation in an economy without bias from specific indexing methods in use(Piketty, 2014). Gini index This is the most commonly used single measure of inequality in the present research field. The Gini coefficient is dependent on the Lorenz curve tackled briefly in the introduction part of this discourse. It is a cumulative frequency curve dependent on the distribution of a specific variable in relation to the uniform distribution representing perfect equality in a population. The Gini coefficient graph translates into a Lorenz curve with the diagonal being the measure of complete equality. If the diagonal translates to zero, there is complete equality in the population but if the value of the curve translates to zero, there is complete in equality. In an equation, the Gini coefficient translates to The Gini coefficient has several limitations that make unsatisfactory in meeting the necessary requirements. In this part, the strengths of the Gini index will be under discussion in order to give a clearer view of the limitations. The coefficient relies heavily on mean independence, which means in a case where the income doubled uniformly in the whole population, the mean of the Gini coefficient would not change. The latter is a good thing in measuring inequality since it shows versatility in the population, and a good index measure should accommodate it as the Gini proves. According to business scholars, if the population to a certain region were to change, the inequality of that population would remain the same. The Gini coefficient satisfies the ceteris paribus principle of population change with, but constant inequality. Satisfying the latter makes the index efficient to use in any population despite the versatility of that population. If there is transfer of wealth from the rich to poor, the Gini index reflects the transfer. The Gini index adheres to the Dalton transfer sensitivity principle that any good equation should be able to meet. The Gini coefficient also observes symmetry within its operation, which means that swapping of salaries would not affect the measure of inequality and the curve would remain the same. The Gini has various limitations that will enable us to understand why some researchers prefer a different method of inequality measurement. Unlike the Watts index and the Square poverty gap index, the Gini index is non-decomposable. Having a non-decomposable index means that the population cannot be under division into groups according to the poverty level, hence there can be no targeted elimination of poverty and inequality. The total societal Gini is not a sum of the Gini indices of the subgroups to that society(Piketty, 2014). The final limitation of the Gini is its inability to check and test for significant changes in the index over a period. Although statistical testability is not a major problem due to bootstrap techniques, a while back it posed a big disadvantage to the Gini index equation. Nowadays analysts settle for incorporation of other techniques in testing the statistical changes over time, but it still discourages other researchers who opt for more error free methods of inequality determination. Watt index In 1968, the first distribution sensitive measure of poverty was under proposal by Watts. Its discrete version is in the form stated above. The population (N) is indexed in ascending order of their income, and the sum of this expenditure is divided by the sum of the income of q individuals whose expenditure (yi) falls below the poverty line. The watts approach towards poverty indexing meets all the theoretical frameworks set forth in poverty indexing, and researchers adopt it more often than any other method when plotting the poverty incidence curve. Due to its theoretical aspect, it lacks the intuitive edge that should make it applicable practically hence, the minimal use in practical field of study(Piketty, 2014). In order to minimize the watts index, anti-poverty resources would fall to the poorest in the economy. This is a rarely applicable feature in any economy, but according to Sen it is the most effective. The watts index measure also meets the transfer sensitivity axiom mentioned in this discourse. The transfer sensitivity axiom enables the watts index to change even with a slight change in wealth for the people below the poverty line. This index is also dynamic since it is decomposable into weighted sum of poverty indices for specific groups, people or regions. When an index allows for a decomposable analysis, it enables division of people into distinct groups that enable policy makers to eradicate poverty in a targeted manner as evident in the squared poverty gap index. MLD (Mean Logged Deviation) This is a general equation for a family of measures of inequality. The family is the generalized entropy measure where the mean logged deviation index of determining inequality lies. Where Y’ is the average income, the value of the equation GE measures the limit between zero and infinity. The zero in the limit represents equal distribution in the population while the higher limit represents the higher level of inequality in the population. The weight given to the distances between incomes at variant income distributions has the value α in the equation and it can take a real value. When the value for α is lower, the GE has a higher sensitivity to the lower parts of the distribution curve and for higher values of α the sensitivity shifts to higher parts of the distribution curve. In the generalized entropy equations, the value of α is usually zero, one or two. If the value is one, then the GE reflects the Theil’s index T. In cases where the value of α=0, then GE(0) takes on another form of the Theil’s index L, also known as the mean log deviation(Piketty, 2014). Mean log deviation comes from the nature of the equation, whereby it gives the standard deviation of the log (Y). Mean logged deviation does not support transfer principle, and it does not reflect decomposable indices. Most analysts avoid it due to its complexity and difficulty in interpretation. It is not intuitive; therefore, it is mostly applicable in a theoretical basis. Findings Using the index measurement values on eight countries from different continents gave a varying output on the poverty level. Argentina According to the statics from the calculations, it is evident that argentine population has an extreme poverty level with over 11% of the population vulnerable to falling below the poverty line. According to this research the poverty line in Argentina is 38 dollars; in 2012 the World Bank estimated that more people would start earning between 4-10 dollars. According to the head count, the latter might not affect the poverty percentage but there will be an effect in the other methods due to the transfer principle. In a country with over 40 million people, the poverty level increasing to 40% as speculated by the World Bank would cause the economy to drop drastically. The only way to prevent the economic drop would be to decrease the inequality level and increase the consumption share. The Gini coefficient would help reflect the necessary changes necessary in making the country a better economic giant in South America. China According to the research and calculations, china has a higher poverty percentage as opposed to Argentina. All the indices used reflect that China is poorer than Argentina thus it has a higher population below the poverty line. Despite the high population living below the poverty line, china’s per capita income has been under progressive increase since the 80’s. Despite the high poverty index, china is better off currently than it was a few years ago. The major problem arises due to china’s inequality levels. The inequality is evident through comparison of living standards between the rural and urban dwellers. The country has a population totaling over 1 billion dollars with over 36.5 living on less than 6 dollars a day. Despite china’s poverty reduction and high economic growth as reflected by the indices, the countries inequality level is nowhere near reduction. Despite the advantages brought about by economic improvement, most households do not have equal opportunities when it comes to social amenities and education. Germany Germany has a good economy with the lowest poverty rates as shown by the indices. The German population is quite scarce and most of it lives above the poverty line. The inequality rate in Germany is also minimal as shown through the Gini coefficient. The policies governing the German population ascertain that almost every citizen has access to welfare services such as medicine and health. The good economic distribution in Germany is due to the high industrial investment within the county. Most citizens have well paying jobs in the industries and those that do not have jobs rely on marketing the industrial produce. Kenya and Nigeria Kenya and Nigeria are good economic countries within the African continent, but their poverty levels compare poorly to other countries in other continents. The issues that lead to high poverty indices are common between the two countries. The countries have poor education levels and high rates of inequality between the poor and the rich. The economic growth happening affects the middle class and the rich without any effects on the poor. The poor endure poor resources and lack access to welfare facilities due to poor governing policies and poor economic decisions. Terror groups within the countries dissuade investors from venturing into the rural areas; therefore the poor have no chance of improving their social status. Mexico The poverty level n Mexico fell by o.6% between 2010 and 2012 leading to around 53.3 million falling below the poverty line. The population below the poverty level is approximately 52.3%. If the poverty level is calculated based on assets or food then the people falling below the poverty level are approximately 38%. Estimates indicate that another 40% are at a risk of falling below this poverty line. This is because of a population growth from 114 million to 117million people. However extreme poverty has declined from 11.3% to 9.8% in 2012. This is mainly due to opportunities, improved healthcare and conditional cash transfer program. Weak economic growth in the country leads to this constant high poverty levels. Russia Although Russia has experienced a rapid economic growth it has unfortunately not led to a decrease in its poverty levels. Approximately 1 in 8 individuals live below the poverty line. this is approximately 18million Russians or 13% in 2011. This number is due to wealth inequality which has led to limited opportunities for the poor to escape their poverty by improving their living standards. Moscow is home to many billionaires in the world. Russia also presents itself like a successful, idle income country and thus prefers the marginalized and poor to remain invisible or silent. however it is important to note that 3/4 of poor individuals only need to increase their income by amounts less than half of their current income to get out of absolute poverty because most people in Russia do not experience extreme poverty. Poverty in Russia is also experienced aim small durations. Approximately 2/3rds poor families only experienced this poverty for 1-2 years. However, more than half the population has experienced poverty and for must it is repetitive. India An income that is below $1.25 purchasing power parity per day per head falls under the bracket of extreme poverty. This estimate of extreme poverty describes approximately 32.7% of Indians. In 2013, the Indian government stated that 21.9% of the population was below the poverty line. The rapid economic growth experienced from 1991 has led to some reduction in poverty but those above the poverty line have a very fragile economic life. The lack of basic essentials like sanitation, health care, clean drinking water, housing and malnutrition impact the population negatively. According to a 2014 World Bank review about 872.3 million fell below the poverty line and 179.6 million of these poor people lived in India. This implies that out of the 17.5% of the total world population, India held a share of 20.6% of the worlds poorest individuals. 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