On none of our measures of severe poverty do we find any evidence of a significant rise in severe poverty ‘hiding’ behind the relatively small changes seen in headline measures of income poverty since 2010–11. Material deprivation rates (using both more and less severe thresholds) have clearly declined over the period, and the frequency with which people report being unable to afford those items most indicative of more severe poverty – such as keeping the home warm or keeping up with bills and debt repayments – has fallen by about as much as the frequencies for other items. Income and expenditure measures of severe poverty suggest little change, however. This discrepancy is not due to material deprivation falling only among those families not in poverty, because we see declines across the income distribution. It may be partly explained by the basic items, access to which is tracked by material deprivation measures, becoming cheaper (relative to other goods and services), though this evidence is only suggestive. Looking over a longer period, the modest declines in headline income poverty that have been seen since the mid 1990s do not appear to be reflected in more severe forms of poverty, with income- and expenditure-based measures suggesting a small increase over the period. However, some of this increase is driven by those with very low incomes who in fact on average have higher livingstandards; more generally, the unreliability of low incomes in survey data and the long-run fall in the coverage of spending in the LCF mean that we should be cautious in putting too much weight on these results.
important limitations. For example, it is a ‘snapshot’ measure – reflecting actual, or in some cases ‘usual’, income at around the time of the Family Resources Survey (FRS) interview. Measuring income in this way means the HBAI income statistics capture both temporary and permanent variation in income between individuals, but the latter would generally be regarded as a better measure of their relative welfare. For example, having a temporarily low income is unlikely to have severe consequences for current material livingstandards if individuals are able to draw on previously accumulated wealth. Statistics based upon current incomes will attribute the same level of welfare to people with the same income, regardless of how much savings or other assets they have, or how much they spend. Consumption would arguably make a better measure of material well-being, but reliable data can be harder and more expensive to collect. Using consumption as the measure of well-being can change our interpretation of who is ‘poor’ and how rates of poverty have changed over time. 137
According to the 2018-19 Nigeria LivingStandards Survey (NLSS) conducted by the National Bureau of Statistics (NBS) in collaboration with the World Bank, absolute poverty headcount ratio stood at 40.1% in 2019. This implies that the incidence of poverty is such that 4 out of 10 individuals are said to be poor. The current poverty rate ultimately translates to 83 million individuals that live below the poverty line, thus, are considered poor. This segment of the country’s total population failed to meet the minimum consumption expenditure threshold (or national poverty line) estimated at N137,430 ($449.3) per annum or N376.52 ($1.23) per day 1 . A further breakdown of the poverty statistics showed that poverty is prevalent
Definitions of poverty are much debated. Some of the debates tend to revolve around whether to use measures of absolute or relative poverty and whether to focus on material resources or to include broader measures of what allows for acceptable livingstandards and social inclusion. In recent years, the government in England has proposed a radical departure from either approach, with its proposals to uncouple any link with income. This is out of line with the vast majority of organisations working in this field and other countries, most of whom incorporate approaches to income measurement which have a relational component. Currently, for example, the Child Poverty Action Group uses the definition advanced by one of its founders, Peter Townsend, in 1979:
Measurement of inequality in household livingstandards tends to focus on differences in income. However, income may not be the best guide to a household’s standard of living as some families have high or low incomes only temporarily. A practical problem is the difficulty of collecting accurate data, particularly at the bottom end of the income distribution, as households may under-report their income. An alternative is to assess livingstandards based on household expenditure. Households experiencing a temporary drop in income may sustain their previous expenditure patterns to some degree by drawing on savings or taking on debt (in the expectation that their income is soon to increase again). Under- reporting also appears to be less of a problem when measuring expenditure than when measuring income: surveys find that households with the lowest reported incomes are not the lowest spenders. To expenditure we can also add benefits derived from goods bought previously that are still being ‘consumed’ (for example, housing or cars). This gives a more positive picture of livingstandards for households who may be on low incomes but own their own home.
During the 1990s, Vietnam’s economy was transformed through a series of economic, social and political reforms, resulting in an average growth rate over the decade in excess of 6% per annum. This strong growth performance was accompanied by a dramatic fall in the incidence of consumption per capita poverty. This paper examines the changes in poverty and poverty dynamics over the 1990s using a nationally representative panel of households surveyed in 1992-93 and 1997-98. We analyse how robust the reduction in poverty is to the methods used to measure poverty. We find that regardless of where the poverty line is drawn, consumption poverty fell between 1992-93 and 1997-98, but that the extent of this fall is sensitive to the choice of poverty line. We also examine changes in the distribution of livingstandards over time, finding that the fall in poverty was accompanied by a rise in inequality, with some sub- groups of the population failing to share equally in the strong growth of the country. Finally, we examine rural poverty dynamics, presenting transition matrices of movements in and out of poverty over time and estimating a model of consumption change. We find that regional differences are important, as are access to key institutions and infrastructure, and education. We also find that shifts in employment and production patterns, especially of rice, which we argue to be induced by the economic reform process, are strongly related to changes in livingstandards over time.
Whether global economic integration continues to be an equalizing force will depend on the extent to which poor locations participate in this integration, and that in turn will depend on both their own policies and the policies of the rich world. True integration requires not just trade liberalization, but also wide-ranging reforms of institutions and policies. If we look at some of the countries that are not participating very strongly in globalization, many of them have serious problems with the overall investment climate: Kenya, Pakistan, Burma, and Nigeria would all be examples. Some of these countries also have restrictive policies toward trade, but even if they liberalize trade not much is likely to happen without other measures. It is not easy to predict the reform paths of these countries. (If you think about some of the relative successes that I have cited – China, India, Uganda, Vietnam – in each case their reform was a startling surprise.) As long as there are locations with weak institutions and policies, people living there are going to fall further and further behind the rest of the world in terms of livingstandards.
where Y i denotes a welfare indicator for person i , z is the poverty line, n is the number of people in the sample, q is the total number of poor people, and α is a measure of inequality aversion. Different values of α provide different indices. When α = 0 , the index measures the proportion of people who live under the poverty line (headcount index); when α = 1 , the index represents the depth of poverty (poverty gap index); and when α = 2 , the index characterizes square poverty gap (poverty severity index). Following the literature, we employ per capita expenditure as a proxy for welfare (Razavi (1998); Van den Berg and Cuong (2011); Bui, Dungey, Nguyen and Pham (2014))
There are a number of other approaches adopted elsewhere that are less simple but are better able to take into account the multifaceted nature of livingstandards. One approach is to consider a range of different indicators. For example, the Department for Work and Pensions (formerly the Department of Social Security) publishes a number of different indicators, such as income, housing, health, employment and literacy, in its annual audit of poverty, Opportunity for All (most recently, Department for Work and Pensions (2002a)). Another approach is to combine a number of different measures into a single index which can then be compared across countries and across time. A good example of this approach is the United Nations Development Programme’s human development index, published each year in the Human Development Report (most recently, United Nations Development Programme (2002)). This index combines statistics on life expectancy, literacy, incomes and unemployment to derive a single measure of ‘human development’, although constructing indices such as these is not without problems too.
In earlier work (Dirven, Fouarge, Muffels, 1998) a classification of poverty definitions is used based on two dimensions. The first dimension starts from the distinction between direct and indirect definitions of poverty which was developed by Ringen some ten years ago (Ringen, 1988). Before him, Sen (1979) already made a distinction between the direct method and the income method and Atkinson (1987) between the right to a minimum level of resources and the attainment of a minimum standard of living. In all these approaches income -or resources- definitions are distinguished from definitions in terms of consumption patterns and standard of living. The so-called indirect method has been used by Ringen to refer to income definitions, and the term direct to consumption, deprivation or budget definitions (see also Muffels, 1993). Both types of definitions may also be distinguished according to their mono- or multidimensional (inclusive) character. The indirect method considers poverty as a state of low welfare or insufficient income while the second sees poverty as a multifaceted or multidimensional deprivation concept where material wellbeing is part of an inclusive list of resources and amenities. In this paper we limit ourselves to the indirect method using income as a yardstick for welfare instead of consumption or deprivation. Another possibility would be to pay attention to the direct method and, in particular, the comparison of the income and consumption or deprivation method. For an extensive treatment of this issue compare Callan, Nolan & Whelan (1996).
Just like the poverty dominance tests, the number of dominant relationships varies de- pending on the living standard indicator employed. There are 3 dominant pairs for consumption, 3 for health, and 2 for education. In terms of consumption inequality, the dominance results indicate that Muslims and members of indigenous religious dominate Catholics at order 2 but no dominant relationship exists between Muslims and mem- bers of indigenous religious. This …nding implies that Muslims and indigenous religions are more equal with respect to consumption for all inequality measures one can use. A comparison between the poverty and inequality dominance test results with respect to consumption shows some di¤erences. For instance, poverty dominance tests show that Catholics have lower levels of consumption poverty compared to Muslims and members of indigenous religions, while an opposite relationship holds in terms of consumption in- equality. This is interesting as it suggests that even though Catholics have lower levels of consumption poverty, the variance of consumption among Muslims and members of indigenous religions is lower.
In addition to measuring poverty in the three dimensions, we also measure economic, health, and education inequalities. There are two approaches to measuring inequality in non income or consumption dimensions such as health and education where the di- mensions are looked at separately. The …rst, the gradient approach, makes comparisons in health or education outcomes across populations with di¤erent social economic char- acteristics (see for example Filmer & Pritchett (2001) and Wagsta¤ et al. (1991) for applications of this approach). The second, the univariate approach, focuses on the dis- persion of the health or education outcome without regard to how they are correlated with social economic characteristics (see for example Sahn & Stifel (2003) and Sahn & Younger (2006) for applications of this approach). We use the univariate approach in this paper for two reasons. First, it better handles inequality in multiple dimensions in the sense that unlike the gradient approach it does not tie a health or education outcome to a social economic characteristic say income. Second, conventionally consumption inequal- ity is measured by using the dispersion of consumption, and thus the univariate approach ensures health and education inequality measures which are comparable to consumption inequality.
Housing security and quality are also an important part of how people feel about their standard of living. Owning one’s own home is a widespread aspiration and can create a sense of belonging to a local area. While the late 20s may now be considered relatively early for home ownership, two-in-five baby boomers from the 1961-65 cohort owned their home when they were in their late 20s. 
The objective of this paper was to assess the inequalities of poverty in Cameroon, we used the capabilities approach and a Sub-group decomposition, and we construct a multidimensional poverty indicator (MPI). Poverty and inequality decomposition execute from socio- demographic characteristics of households head, generally reveals some new insights about the poverty situation in the country, which contrasts with the results available from traditional poverty analysis. The results used to estimate membership functions, depicting the deprivation levels for the various categories of deprivation, show a composite deprivation degree of 0.4631 for the whole country, which is different than the one obtained from the head count index of 0.39524. Considering the various deprivation characteristics, the results show high deprivation degrees for essential household items such as instruction (0.0942), housing (0.0809) and employment (0.0677). This suggests that the Cameroonian lifestyle is geared toward fulfilling basic necessities of life.
Our dependent variables, GDP, poverty rates and Theil indices of inequality, both urban and rural, are measured only in 1980, 1991 and 2000. However the ten year gap between measurements is not as unfortunate as it may at first seem; poverty and inequality tend to be slow moving variables whose year-‐on-‐year changes likely contain considerable noise (if they were measured). Furthermore, the spread of soy into the Amazon is a relatively recent (post 1991) phenomenon. The advantage to us of using the 2006 Agricultural Census data is that, prior to its release, agricultural census data was available only until 1995. The addition of the new data ensures that, assuming constant annual growth rates, we can interpolate values for 2000 from the 1995 and 2006 data. In turn, we interpolate 1991 agricultural variables from the 1995 and 1985 census. Note that this necessary interpolation could potentially generate econometric problems if the 1995 data is incorrectly measured in a way that is correlated with underlying variables of interest. Due to changes in the time of year the data were collected it is highly likely that the 1985, 1995, and 2006 data suffer a number of differences (see Helfand and Brunstein, 2001 for an excellent discussion of this), but it remains unknown whether these are correlated in a way that would do more than introduce additional noise into the analysis.
Several years ago, the fight against poverty has become a constitutive element of development policy. A set of countries in the international community has been devoted entirely to the fight against poverty in its monetary dimension, educational and equity. Their main objective "Millennium Development Goal" is based on the reduction by half between 1990 and 2015 the proportion of people whose income is less than one dollar per day.
The World Bank has a major influence on the policy environment in developing countries. The Bank’s stance on distributional issues over the last three decades has changed notably. As with national governments, the changes have not always been in one direction. Jolly (2005) cites Kapur, Lewis, and Webb (1997) as recording Robert McNamara’s persistent highlighting of income and wealth disparities in the early 1970s when he was World Bank President – and the Bank’s subsequent shift in emphasis away from concern with inequality towards a concern for absolute poverty. The World Development Report 1990: Poverty marked the Bank’s commitment to the goal of poverty reduction. But, perhaps inevitably, this in turn has led in time to more interest in inequality as one driver of poverty. As a result, the World Development Report 2006: Equity and Development is another landmark. The emphasis is on equality of opportunity (starting at birth) rather than on inequalities in outcomes in terms of income or consumption. 3 The former is viewed as unambigously bad (or at least something to be reduced), in contrast to the latter. That emphasis, with its concern for education, health, gender, race and other determinants of economic outcomes, reflects in part the issues discussed under our next heading.
Carlen’s (1988) study of imprisoned women, showed that the women she spoke to made rational choices based on the options they had available and their economic situation. The attractions of crime for these women were an alternative to the indignities, humiliations, delays and frustrations of claiming welfare. Others have argued that female crime rates are less driven by poverty than a desire to engage in consumer society. The inability of poorer groups to legitimately attain consumer items considered desirable, and therefore use illegal methods of attaining them, is nevertheless still about being poor in a society where the attainment of certain goods is the norm (Box and Hale, 1984). For Carlen’s (1998) women, committing crimes to make ends meet and live what was considered a ‘normal’ life, was mixed up with sudden, unexpected events that impoverished them – even having children – and sent them into a spiral of decline, which crime became a desperate measure. More generally, Box’s (1987:43) review of fifty North American and British studies of
Nur, estimated that for both food and non-food items, anyone who spends/receives less than this estimated poverty line at the February 1996 prices is Ls 27,000 is identified as poor. Then, it remains to determine the level of existence and magnitude of poverty among the middle class. A minimum cost of living, therefore, is a mere subsistence level that should be achieved for survival. For instance, those who are identified as poor, on the basis of the welfare distribution, are those who fall in the categories below the level of Ls. 27,000/month. This means that 60.8% and 41.5% of our middle class are poor on the basis of income (aggregate) and expenditure respectively. These results have been obtained by employing a poverty indicator represented by a poverty line that is fixed over the welfare frequency so as to distinguish the poor from the non-poor.
When a country becomes richer (prosperous), it tends to revise its poverty line higher, with the exception of the United States, which is that the poverty line has remained essentially unchanged for almost four decades. For example, the European Union generally defines poor people as those who have per capita income below 50 percent of the median (average) income. As the median / average income increases, the relative poverty line also increases. In terms of identifying and targeting poor people, the poverty line is relatively sufficient to be used, and needs to be adjusted to the level of overall development of the country.