UNDP has taken an initiative to publish SOUTH ASIA POVERTY MONITOR periodically to assess the poverty situation at national grassroots level through the existing national expertise in South Asia. As part of this initiative a country report will be prepared for Bangladesh as well. The Bangladesh country report will be prepared through both quantitative and qualitative approach. Unnayan Shamannay is proposing to conduct the qualitative part of the study.
Statistical data do help very little in understanding what the variation means. Qualitative data, on the other hand, “illustrate the value of detailed, descriptive data in deepening our understanding of individual variation….They give rise synergistically to insights and solutions that would not come about without them” (Palton 1990:15-17)
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Qualitative approach “can provide a depth of understanding of the issues associated with poverty that the more formal and statistically valid approaches may not. This class of studies includes the increasingly popular techniques of rapid and participatory rural appraisal and beneficiary assessment” (WB 1992: 8-4).
The objectives of this study are as follows:
The scope of this qualitative study will be to:
Poverty profile and poverty indicators are some of the important components of poverty assessment. Poverty assessment will be carried out in participatory manner. Broad topics on the extent of poverty, identification of sub-groups, nature of poverty, characteristics of the poor and risk management have been included in the proposed research agenda. Moreover, poverty monitoring will also be conducted periodically and it will act as a barometer to measure the changes in various socio-economic and welfare indicators relating to the lives of the poorest households.
All major qualitative research methods will be used in the study. Interview will be extensively used in the study including its key variants, namely participatory group discussion, focus group discussion, standardised open-ended interview and case study. In addition to interview, other methods of qualitative inquiry, namely observation and document analysis will also be made use of in the study.
Qualitative exercises will be conducted in both urban and rural settings of the country. To cover the greater diversity in socio-economic environments, three different regional configurations of northern, central and southern parts of the country would be accommodated in the study. A total of six villages including two from each part would be covered under the study. In urban area, at least three slum areas would be covered to facilitate the comparison and triangulation of data and information.
However, for monitoring of poverty in the selected six villages and three urban slums, certain number of the poorest households will be selected from each of the study sites. Out of six villages, three will be selected in such a manner where at least anti-poverty intervention by government is in operation. These three villages will serve as programme villages and they will be drawn from the three parts of the country including one from each. Besides, other three villages will also be selected nearby where there is no poverty focused government intervention. These three will serve as control villages in the three parts of the country.
Most of the topics would be addressed at the community level and no specific number of participants are needed to be ascertained beforehand. For poverty monitoring, a total of 120 poorest households will be selected ¾ 90 from six villages and 30 from three urban slums. The poorest households will be selected through consultation with the respective community members.
In selecting tools desirable characteristics namely ‘easy’, ‘simple’, ‘visual’, ‘non-verbal’ etc., must be taken into accounts. As PRA tools are recognized to have all these desirable characteristics, most of the tools will be drawn from its repertoire. Important PRA tools that will be extensively used in the poverty assessment include ‘scoring and ranking’, ‘matrix ranking’, ‘wealth/well-being ranking’, ‘time line’, ‘social mapping’, ‘pie chart’ and so forth.
Although the qualitative data are essentially based on the perception, opinion and judgement of the participants, the quality of data would be, nevertheless, refined through of the triangulation principle underlying the research design of this study. A combination of multiple sources, researchers/facilitators and on-the-spot cross-checking of data through discussion, debate and deliberation among the community participants would minimise the degree of error and bias of data to the minimum. Besides, the field observation by the researchers would in addition , act as a guard against any major inconsistency and biasness of data.
For conducting the study a number of activities will be undertaken.
The activities include:
Now-a-days wide ranging literature on poverty is available. Different facets of poverty have been discussed in those literature. The indicators, measurement process, sampling frame etc. also differ. For a qualitative study for monitoring poverty, the volume of the problem further increases. The approach is not only different but gives a deeper insight. To make it complement the qualitative approach the literature on poverty needs a review. For this purpose all available literature on poverty will be reviewed.
Before finalising the indicators for assessment of poverty there is a need for analysing the presently used indicators. This will provide a rational basis for the use of the indicators in the qualitative study.
The indicators and tools to be used in the study will be pre-tested in the field. This will help understand the effectiveness of tools.
Before starting field work a primary field visit is needed to get acquainted with the actual field condition.
The field/research officers who will be engaged in this study are competent and experienced. Even then the field/research officers need training/orientation for doing such work. With this purpose they will be imparted in-house and field training.
The data/information processing in qualitative study is not similar to that of quantitative one. The information generated through qualitative approach is processed in a different manner. Different factors and aspects of reality are considered while classifying these information.
The field activities to be undertaken in this study will require two types of work: a. in rural area and b. in urban area.
Significant insights can be found through document analysis. Even discrepancies between reality and pronounced goals can be identified.
Problems facing the poor were identified by the poor themselves, and a list of ‘felt needs’ were the outcome of the participatory discussion, debates and consensus among themselves. Two sets of problems and needs were assessed in a participatory manner each for the urban and rural areas.
To the urban slum poor, homelessness and eviction from slums are the topmost problems. Other serious problems identified by the poor include lack of good health and water facilities, employment opportunities, security, education, latrine, gas, etc. (Exhibit 38).
Regarding the needs assessment, the urban poor listed and prioritized their felt needs. Some of the most important are, latrine, shelter, drinking water, electricity, gas, security, rationing, employment and so on (Exhibit 39).
Agricultural inputs, irrigation and culverts are considered to be the topmost problems by the rural poor. Apart from these, some other most serious problems mentioned by them are related to health, electricity, unemployment, flood, drinking water, industrialisation, veterinary facilities, silting up of rivers etc. (Exhibit 40).
According to the needs assessment and prioritization by the rural poor, some of the most important needs as articulated by themselves are industries for employment, agricultural inputs at a fair price, rural roads, irrigation, electricity, school and madrasa, medical facilities etc. (Exhibit 41).
The primary objective of monitoring of impact of public expenditure on poverty in this chapter is to understand the living condition of the poor. This is more of an illustrative exercise rather than a whole sector monitoring of poverty. The issue of representativeness has to be, therefore, viewed in this context. One of the stated objectives of the development strategy of both present and previous governments is to reduce poverty. A growing share of public expenditure is claimed to have been allocated to the development activities ostensibly aiming at poverty reduction in the recent past, and this is likely to be continued in the future.
Against this background of increasing the public expenditure allocation to poverty alleviating projects, it is needed to know the effects and impacts of these expenditure on poverty alleviation. In this section a number of key questions have been addressed: Does the benefit of the public expenditure reach those lying at the bottom of the income scale ? Is there any sign of improvement in the condition of the poorest of the poor ? How do the selected poverty indicators behave? Do they improve, deteriorate or oscillate ? In case of improvement, at what pace do they improve ? Based on the findings from these questions, an attempt will be made to assess the quality of public expenditure in terms of a set of selected indicators. To understand the trend of the impact of public expenditure on poverty, we started monitoring the behaviour of some selected indicators of poverty in both the urban and rural areas since 1993 as the base year. The qualitative and quantitative data generated through the participatory tools have been used for this poverty monitoring. This is the first round of the periodic monitoring of poverty in a participatory manner.
The poverty assessment carried out under this study has two components. The community members actively participated in the assessment of their well-being by listing and categorizing of all the households by themselves in several groups based on their own criteria. This is, in fact, a subjective assessment. Secondly, after categorization, all households were arranged in descending order on the basis of well-being scores of each of the households resulting in the identification of the poorest of the poor in the respective communities lying at the bottom of the scale with quantitative precision which was again vetted by the community members/participants. The poverty of some of the poorest households in the community has been monitored on the selected indicators. As this monitoring is based on hard data, it, therefore, gives us an objective assessment of the living standard of the poorest. (Figure 9.1) The poverty sitution in the urban and rural areas has been assessed in a participatory manner. Instead of applying any pre-conceived ideas, standards, measures or categories by the researchers to measure poverty as is done conventionally, the criteria used in this study has been developed by the people at the community level. The basic question relating to poverty measurement or assessment is who is poor and how to identify him/her.
Unlike a single standard or formula as applied in the conventional methodology, the community-members consider it appropriate to use a set of socio-economic criteria to assess the economic and social status of a household. For this purpose, the researchers and facilitators involved in the study initiated a series of group-level discussions and community-level validations. The community people developed their own criteria (Box 9.1) to assess the status of their own members and also to categorize them into a set of social classes.
The more important criteria developed by the rural people in the selected villages are, among others, the amount of land owned and cultivated, the number of earning members, cash in hand, the housing condition, the amount of fixed assets, the family size, other sources of income, whether a household is female or male headed, etc.
Based on the above criteria, the community people identified the poor (‘moderate’ poor) and the poorest (‘extreme’ or ‘hardcore’ poor) households in their own community. As poverty was assessed at the household level, the status of all the households in the community was assessed and categorized into four classes, namely well-off, medium, poor and poorest.
In the urban slums, 72 percent of the households were found poor (moderate: 51, hardcore: 21) and 28 percent non-poor (middle: 19, well-off:9). The incidence of poverty was, however, found to be widely different in different slums. In one sample slum there were no well-off households in 1996 although there were many in another sample.
In the rural area, 75 percent of the households were classified as poor (moderate: 20 and hardcore: 55) whereas 25 percent were classified as non-poor (middle:14 and well-off: 11). Regionally, the incidence of poverty was more acute (moderate: 17, hardcore: 60) in the central part compared to that (moderate: 25, hardcore:47) in the northern part.
The findings generated by the PRA exercise were further validated by the people in the respective community. So the scope of subjective bias, if any, was greatly reduced.
Being a value loaded term, poverty as such cannot be measured quantitatively/objectively. The debate on the issue abounds in the literature. But the symptoms and aspects of poverty can be measured and monitored by means of a series of socio-economic indicators that proxy the level of well-being of people. That is why, an attempt has been made in this section to measure and monitor poverty through a number of indicators/variables in two different years i.e., 1993 and 1996. Most of the indicators used for monitoring were suggested by the community members (Box 9.1.). The number of indicators used here are meant to have satisfied the desirable criteria, namely, unambiguity, consistency, specificity, sensitivity and ease of collection (Carvalho and White, 1994).
The population of the poorest households and their average family size grew by 5 percent over the monitoring period 1993-96. However, the populatioin growth rate is found to have been higher at 7.2 percent for the urban poor compared to 4.4 percent in the rural area over the same period. The family size of the poorest households in the rural area is, however, found to be higher at 4.2 in 1993 and increased further to 4.4 in 1996. The family size of the urban poor was lower at 3.5 in 1993, and it grew to 3.7 in 1996.
In the rural area, the family size of the FFE-households is found to be much higher at 6.0 on an average in both the central and northern parts compared to those for the non-FFE households in both programme and control villages in 1996.
Another important demographic characteristic of the poorest households is their family composition. In 1996, the FFE households are found to have a male majority ¾ 61 percent compared to 49 percent and 41 percent for the non-FFE households in the programme and control villages respectively. The family composition is, however, found reverse for the poorest families in the urban slums. The poorest households had a female majority at 62 percent in 1996.
The above findings pose some questions challenging the appropriateness of the main thrust of the development strategy being pursued by the government in the country. The much-publicized motto “two children are enough” seems to have been irrelevant so far as the poorest people are concerned in both the urban and rural areas. The increasing growth rates in populatioin and family size suggest that under the existing socio-economic conditions, their economic and social securities lie not in smaller family but in larger one.
The poorest households and their different groups are found to have peculiar characterstics in the composition of their earning members. Overall, close to half of the earning members are men, and one-fourth are women and boys each in 1996.
Against this general distribution of the earning members, the poorest families in the urban and rural areas are found to have different compositions of earning members by age and gender. In the urban slums, female earning members accounted for 43 percent (women: 36% and girls: 7%) among all the earners compared to 24 percent (women:23% & girls:1%) in the rural area. Female children are not found to have been as active in income earning activities previously as they are found to be in 1996. The preponderance of male income earners is found to be more prominent among the poorest households in the rural area. At the disaggregate level, the difference is more revealing in the rural areas. The participation of girls in income earning activities is found to be very minimal throughout the rural areas. Among the FFE-households, women’s participation in income earning activities is very small (3%), but it is widely observed (33%-36%) among the non-FFE households.
Among the FFE households, the preponderance of male child labour is observed, and this remained unchanged throughout the monitoring period despite the programme intervention in the rural areas. The incidence of child labour among the earning members of the FFE households is found to be 40 and 41 percent in the central and northern parts respectively of the country, and this remained unchanged in both the areas during the period 1993-1996. The poor impact of the FFE programme on the incidence of child labour at large in the rural areas is also revealed sharply if we focus on the trend in the incidence of child labour. Overall, 25 percent of the boys of all ages were involved in income earning activities in 1993, and this remained almost at the same level (24%) in 1996. As the boys, the incidence of female child labour among the earning members is found to be at a much lower level (1.2%) in 1993 and this remained at that level 1996 as well.
The above findings raise an important question to the fore: why is the FFE programme found to be ineffective in reducing the incidence of child labour? The answer to this question should be searched not in the programme itself but in the economics. For the poorest households, the opportunity cost of sparing a boy from education is around Tk. 14 a day (wage rate) in 1996. The financial benefit gained from the FFE programme by a rural poor household is found not so significant at Tk. 4.85 (Tk. 0.81 per capita per day) a day for a boy. The participatioin of a poor family in the FFE programme causes a substantial income loss to that family. As the benefit under the programme cannot offset the income loss that an extremely poor family has to incur, the appeal of the programme to a precariously income-poor family is found to be weak. This finding is found consistent with that of other studies (Ahmed and Billah,1995).
One of the important demographic features of the poorest households is that close to one-third of them were female-headed during the reference period. More than half of the sample households (55%) are found to be female-headed in the urban slums compared to 23% in the rural households during the same period.
Another important demographic feature of the three groups of the poorest households is that only 5 percent of the FFE households have been female headed compared to 25 percent and 40 percent for the non-FFE households respectively in the programme and control villages in 1993. This composition remained unchanged even in 1996.
The above findings suggest that the FFE households are found to be relatively stable not only in respect of assets (details later) but also demographically. The preponderance of female-headed households among the non-FFE household groups imply that these households are not only income-poor but also subject to a higher degree of vulnerability and defencelessness both economically and socially.
In the urban slums, a significant portion of the poorest households happened to be female-headed during the monitoring period The gender focus of poverty is found more pronounced among the poorest segment of the slum-dwellers compared to those in the rural area. More than half (55%) of the sample households have been female-headed compared to that (23%) among the rural counterparts during the same period.
Altogether, 6% of the poorest households are found engaged in begging. In the urban slums, none of the poorest households is found in this category and all begging households under our sample belong to the rural area. Besides, all these households are found among the non-FFE groups. These households are more vulnerable and extremely poverty-ridden mainly due to some unfavourable demographic factors. The households engaged in begging are relatively small (3.8) in family size compared to the sample average (4.2) in 1996. Moreover, the dependancy ratio for the begging households is lower (2.7) compared to that for the sample households (3.0) in 1996.The predominance of women among the earning members points to the poor income level of these households. As the dependency ratio is very low, it implies that most of the family members are forced to go for earning activities due to their poverty.
The poorest households have limited sources of income. The urban poor are usually engaged in unskilled manual labour. Similar is the case with the rural poor as well. Sale of labour has been the main source of the rural poor accounting for 82% of their total income in 1993. This has marginally increased to 84 in 1996. Agriculture is the second most important source of income making up only 12% of the total income of the rural poor in 1993 and 10% in 1996. Only 1% of the income of the rural poor has been derived from livestock, a new source of income, in 1996.
In the rural area, the income of the poorest households has been found to be miserably low during the monitoring period. The per capita daily income of these households was Tk. 6.9 in 1993. This increased to Tk. 7.4 in 1996 showing an 7% growth. Their per household daily income grew by 12% from Tk. 29 in 1993 to Tk 33 in 1996. The higher growth rate of nominal income is mainly due to a positive growth of the nominal wage rate (12%) alongwith a growth of the number of earning members (5%) of the poorest households. The low per capita income is partly due to the large family size and its growth over the monitoring period. The low income of the poorest households is the result of a number of socio-economic factors, e.g., low wage rate, poor asset base, poor human capability due to illiteracy, low access to economic opportunities, etc.
The impact of the FFE programme does not seem to have been appreciable on the level of income of the programme households. Although the programme has had some positive impact on the growth of income (15% in per capita and 18% in per households terms during 1993-1996), its contribution to the growth is difficult to ascertain. However, other findings indicate that the contribution of the programme to the income of the programme households is insignificant (Tk. 0.81 per capita/daily, Tk. 4.85 per household/daily, 15% of the average household income).
The per capita nominal income of the poorest households in the urban slums was Tk. 12 a day in 1993 and increased to Tk. 19 a day in 1996 representing a 31 percent growth. The per household daily income of the urban poor increased by a higher rate of 40 percent from Tk. 41 a day to Tk. 58 during the same period.
The income of the urban poor increased by a much higher rate than that of the rural poor in both per capita and per household terms because of the higher growth rates of wage (29%) and of earners per household (17%), lower family size (3.7), etc. Moreover, gainful economic opportunities are greater in the urban area relative to the rural area.
The income of the poorest households in real terms (in kilogram of coarse rice) is found to have declined across the board during the monitoring period. In the rural area, the per capita real income of the poorest households declined by 22% on an average from 0.9 in 1993 to 0.7 kilograms of coarse rice in 1996. Barring the FFE households, the per household real income has registered a sharp decline during the same period irrespective of differences in regional diversity. Due to the income support under the FFE programme, the FFE households could avoid the sharp fall of income. The per capita real income for the FFE households has declined by 13% against a 20 to 25 percent decline for the non-FFE households over the same peiod. Overall, despite an 7% increase in per capita income in nominal terms on an average during 1993-96, the corresponding real income took an appreciably higher downward trend (22%) caused by a 24 to 43 percent price hike of coarse rice in the rural areas during the same peirod.
The per capita real income of the urban poor remained unchanged, whereas, the per household real income marked an upward trend (5%) during the monitoring period. The per capita real income of the urban poor is almost double at 1.4 kg a day of that of the rural poor in 1993 which remained almost unchanged during the same period. The per household real income of the poorest households stood in urban slums at 4.7 kg and 5.0 kg a day in 1993 and 1996 respectively recording a 5% growth. The poorest households in the urban slums are relatively better off than their rural counterparts in respect of per household real income which declined by 16% for the latter during the same period.
The unskilled wage rate is considered to be an important indicator for monitoring poverty. The wage rate of all categories of unskilled wage labourers is found to have increased in both the rural and urban areas. In the rural area, the daily nominal wage rate increased by 11.7% from Tk. 17.2 in 1993 to Tk. 19.2 in 1996. The wage rate is found to be much higher for the urban slum-dwellers, and it grew by 29% from the level of Tk. 35.8 in 1993 to Tk. 46.1 in 1996.
Although the wage rate for unskilled labourers increased during the monitoring period, the purchasing power of the poor labourers did not rise due to a higher rate of price increase in the case of coarse rice. The average wage rate for unskilled wage labourers, in fact, declined across the board in real terms during the monitoring period. However, the poor in the northern part had to sustain a much higher rate of fall (22%) in real wage rate compared to 14% for those in the central part during this period.
The consumption of rice and wheat ¾ the staple food items of the poorest households ¾ is found to have recorded opposite trends among these households in the urban and rural areas. In the urban slums, the per capita daily consumption of food (rice and wheat) was 442 grams in 1993 and it rose to 514 grams in 1996 representing a 16 per cent growth. The increase in the consumption level of food in terms of both per adult equivalent unit and per household units has also been substantial, 18 and 25 percent respectively during the monitoring period. These findings, however, conceal the substantially low level of food intake observed in one of the slums where poverty is found to be more acute.
In the rural area, the trend in food consumption is, however, found to have consistantly sunk during the monitoring period in per capita and per adult equivalent and per household terms. The per capita daily consumption of rice and wheat declined from the level of 585 grams in 1993 to 566 in 1996 showing a 3 percent decrease. The food consumption per adult equivalent unit is found to have been at a much higher level ¾ 797 grams in 1993 and 786 grams a day in 1996 – recording a relatively small fall during the period. Per household consumption, likewise declined during the same period. The declining trend in food intake is true of both the programme and non-programme households during the same period. The consistent fall in the level of consumption of food is largely due to the fall in real income and expansion of the average family size of the poorest households during the monitoring period.
In order to assess the poverty status of sample households, the heads of the households were asked to make self-assessments in respect of poverty. Their self-assessed status may be categorized as follows:
The distribution of sample households by poverty status. It appears from the table that most of the sample households are characterized as year round or occasional deficit households and very few are surplus households. About 26% among the urban and 65% among the rural household heads have said that they had chronic food deficit in the previous year as against only 10% in the urban and 1% in the rural area who have assessed themselves as surplus households. The proportion of occasional deficit households is about 37% in the urban and 30% in the rural areas. The break-even households comprise about 27% in the urban and 4% in the rural areas. The situation of the poor in respect of food availability seems to be more deplorable in the rural areas than in the urban areas.
In the rural area, some consumers of the poorest households seem to have switched over to wheat from rice and have increasingly consumed wheat, a close inferior substitute for rice during the reference period. It is found that wheat accounted for 8 percent of total cereal food (rice and wheat) in 1996 compared to only 3 percent in 1993. The shift from rice to wheat in the composition of the food basket has been more pronounced in the central part compared to the northern part of the country. The change in composition of cereal food seems to be largely due to poverty and the availability of wheat under the FFE programme.The shift took place in the cases of FFE and non-FFE households alike. There is a likelihood that a part of this wheat provided to the beneficiaries of the programme might leak to other non-FFE households through sale or other channels. This might contribute to the process even for the non-FFE households. The urban poor are not found to consume wheat and no shift from rice to wheat took place during the reporting period.
The consumption of protein-rich non-cereal food like fish, beef, chicken, egg, milk, etc., by the hardcore poor in the rural areas declined alarmingly during the monitoring period. The consumption of these nutritious food items is, however, found to have been unchanged in the urban slums. On an average, the poorest households eat fish less than 6 times a month, meat twice a year, chicken less than once a year, milk less than once a month and so on, showing the extremely poor level of consumption of such nutritionally rich food items. More alarmingly, the consumption level of these important food items have tended to fall further since the base period. Although the rural poor do consume fish, chicken, egg and milk more frequently within certain time bands, the frequency of consuming these items has gone down in 1996 in comparison with the base period 1993. The urban poor have eaten beef and vegetables more frequently during the monitoring period.
At a more disaggregate level, the consumption of these protein-rich food by the poorest households is much worse in the central part compared to the northern part of the country. A similar difference is observed among the urban slums as well. Although the consumption of these nutritious food items by the FFE-households group recorded downward trend with respect to almost all the above items except egg, chicken and milk they ate more frequently compared to the two non-FFE household groups during the same time because of their higher level of income and resource base.
In the rural area, the housing condition of the poorest households improved marginally during the monitoring period. In 1993, 87 percent of the poorest households had completely thatched (F-type) houses, the figure decreasing to 80 percent in 1996. On the other hand, 13 percent of their houses were thatched with corrogated iron-roof in 1993,the figure improving to 20 percent in 1996. Whatever improvement took place during the monitoring period, it was in the northern part which accounted for the larger part of it compared to the central part. Similarly, most of the benefit resulting from the improvement in the housing structure accrued to the poorest households under the FFE programme compared to the other control groups. This suggests that the FFE progamme may have contributed to improvement in the living standards of the poorest albeit minimally, the causality, however, is difficult to prove.
In the urban slums, the houses of the poorest households were completely thatched ones and no improvement took place in any manner during the monitoring period.
It is not only the structure of the houses that the poorest people lived in were the worst but the space of these houses had was also very limited in both the urban and rural areas. In the urban slums, 95 percent of the houses that the poorest lived in were single-roomed and only 5 percent were double-roomed in 1993. The housing condition of the urban poor with respect to living space did not improve in any respect during the monitoring period.
In the rural area, the housing problem facing the poorest is found to have been a bit less acute. Single-, double- and tripple -roomed houses of the hardcore poor accounted for 88, 8 and 3 percent respectively in 1993 and this improved marginally to 85, 10 and 5 percent respectively in 1996. As in the case of the structure of the houses, the housing condition of the poorest households in terms of living space also shows some sign of improvement though not significant, in the rural area during the monitoring period.
It must be mentioned that the benefit by the way of improvement in the housing condition in terms of both the structure and living space, is found to have gone to the FFE-households only. The non-FFE households could not improve their housing condition during the period from 1993 to 1996.
The shortage of availability of living space for the household members can be better appreciated in terms of average number of member per room. In the rural area, the state of overcrowding is showing no sign of improvement. The condition for the urban poor has aggravated during the monitoring period. The finding that the households under the FFE programme have had improvement in the housing condition during the reference period is also supported by another finding in this regard. Although the FFE-households had the worse state of overcrowding due to their higher family sizes (5.3 in 1993 and 5.6 in 1996), the overcrowding problems faced by these households eased marginally from 4.4 persons/room in 1993 to 4.1 in 1996.
The overcrowding problem has become worse for the non-programme households because of their more precarious economic condition.
Regionally, the overcrowding problem facing the poorest households is found more acute in the central part compared to the northern part during the monitoring period. In the central part, the burden of overcrowding increased irrespective of the programme and non-programme households. However, in the northern part, the FFE-househods had some improvement in respect of this problems during this period, although no improvement accrued to the non-FFE households.
In the rural area, the poorest households mostly used dry leaves (98% of the huoseholds), fire wood (10%) and cow dung (33%) as fuel for cooking. The urban poor, on the other hand, commonly used fire wood (50%) and rag (piece cloth) (50%) for cooking purposes during this period. Although, as a whole cowdung was found to be the second largest source of fuel for cooking, households in the northern part are mostly dependent (60%) on it compared to that (7%) in the central part. This is probably due to the better asset position (livestock) of the poorest households in the northern part. There has been no change in the type of fuels used during the monitoring period in both the urban and rural areas.
The poorest households in both the areas are found to be completely dependent on a single type of lighting, namely uncovered kerosene lamp. They did not have any access to electricity in both the areas in the monitoring period.
The poorest households in the rural area are found to be extremely land-poor in terms of both cultivable land and area of homestead. Only 17 percent of them are found owning cultivable land. The average size of landholding cultivated by them is found to have been 68 decimals in 1993 which subsequently shrank to 64 decimals in 1996. However, the average size of cultivable land per household is found to be insignificant 11.4 decimals in 1993, falling further to 10.6 decimals in 1996.
Although most of the poorest households in the rural area owned homesteads, the size of homestead is found to be very small. Eighty two percent of the poorest households owned homesteads built on 7 decimals of land on an average, and this remained unchanged throughout the monitoring period. However, the average size of land for homestead per sample households amounts to 6 decimals in 1996.
There has been differences in the landholding pattern in the rural areas. The average holding size of cultivable land was much larger (93 decimals) in the central part compared to that (57 decimals) in the northern part, although the per household cultivable land was strikingly much lower in the central part than that in the northern part. This indicates the existence of the skewed patterns of landholding (10% of hhs owned cultivable land) among the poorest households in the central part compared to that (23%) in the northern part.
The poorest households under the FFE programme have much more land compared to those outside the programme. The FFE-households have on an average 23.6 decimals of cultivable land compared to 3.1-5.3 decimals for the non-FFE households in 1996. With respect to the area of homestead, the FFE households are also found in a comparatively better position relative to the other groups. The average size of homestead is found to be 13 decimals for the FFE households in comparison with 5 and 2 decimals for the non-FFE households in the experimental and control villages respectively. The better resource endowments of the FFE households relative to the non-FFE households seems to be the real cause of the better performance by the FFE households in respect of some of the indicators mentioned elsewhere.
The poorest households in the urban slums are found to be completely detached from land. They have neither cultivable land nor homestead of their own. This shows that the asset base of the urban poor is more weak compared to their counterparts in the rural area.
In the rural area, livestock is an important asset of the rural people. But the poorest households are found to be bereft of this asset. It is strange to observe that on an average 7-8 percent of the poorest household have had less than two cows and goats, on an average, 8 percent have had 2 ducks and 22 percent have had less than 2 chicken in 1996. The livestock size of the poorest households has improved at a very slow pace during the monitoring period.
The resource base of the poorest households in the central part is terribly low not only in terms of cultivable land but in terms of livestock too. Only 3 percent households had cow and goat in the central part compared to 10-13 percent in the northern part.
In the urban slums, the poorest households are found to be completely bereft of livestock in the monitoring period.
Regarding consumer goods, the only asset that the poorest households purchased during the monitoring period are utensils. In the rural area, 35 percent of the poorest households bought utensils whereas 3 percent of them sold the same in 1996. So far as producer goods are concerned, namely rickshaw, rickshaw van, bicycle and cow, 5 and 10 percent of the poorest household bought and sold each of these items during the monitoring period. No systematic pattern of buying and selling of goods is found among the FFE and non-FFE household groups during the reference period.
In the urban slums, a considerable number of the poorest households bought both consumer and producer goods during the monitoring period. Forty percent and 20 percent of these households bought consumer and producer goods respectively in 1996. The urban poor could not, however, buy any kind of producer goods whatsoever in the base year.
The poor’s access to credit improved considerably in terms of both the number of borrowers and the volume of credit in both the urban and rural areas during 1993-96. In terms of the volume of credit, their access to credit grew by 457 percent in the rural area and by 135 percent in the urban slums during this period. Their access to credit in terms of the number of borrowers (net) registered 63 percent and 233 percent growth in the rural and urban areas respectively.
The volume of credit per poorest borrower increased markedly from Tk 1,156 to Tk. 3,963 in the rural area but declined from Tk. 4,500 to Tk. 3,170 in the urban area during the same period. The average volume of credit per poorest household is found to have been very low at Tk. 400 in 1993, and it soared to Tk. 1,684 in 1996. The main financiers of credit to the poorest households are moneylenders, friends and NGOs. In 1993, moneylenders and friends had been the main sources of their credit. As new window for credit NGOs started lending to the poorest households in the study areas in 1996.
Moneylenders have been the top-ranking financiers of the poorest households both in the rural and urban areas. The credit from this source although escalated in absolute terms, it declined proportionately during the monitoring period. Despite that, moneylenders are found not only as the largest deliverer of credit but also meet the credit needs of the largest number of poorest borrowers. NGOs have emerged as a new and potential source of credit to the poorest in both the urban and rural areas. As the poorest households in both the areas have been deprived of institutional credit NGOs are marginally filling the gap as an alternative source of institutional credit for them. NGOs are coming forward to meet the credit need of the poorest households albeit at a lower pace. Although NGOs have emerged as an important source of credit for the poor in the study areas in 1996, the access of the poorest households to NGO credit in terms of coverage (10% of poorest hhs) is still at a much lower level. The poorest households are found to have borrowed for a variety of purposes, namely consumption, repairing of houses, to finance agricultural activities, purchase of rickshaw/push cart, repayment of loans and medical treatment. In the urban area, the poorest households used 63 percent of their credit for health in 1993 compared to 61 percent for buying rickshaw in 1996. Credit used for consumption purpose declined during this period. In the rural area the credit used for consumption although decreased, health recorded increasing pattern during the same period. The percentage shares of total credit used for consumption, health and agriculture has been to the extent of 76, 0 and 22 percent in 1993 compared to 40, 28 and 24 percent respectively in 1996. In the face of high incidence of diseases, the rural poor had to borrow credit for meeting medical expenses in 1996.
Majority of the respondents (72%) replied affirmatively to the question whether they had taken credit from any source. It appears from the same table that households that took credit during the year preceding the enumeration were 60% of the total respondents in the urban and 83% in the rural areas. Distribution of respondents by source of credit. It is interesting to note that interest rate of credit taken from usurer and relatives is found to be exorbitantly high and it varies from 102.8% in urban to 153.6% in rural for credit from usurers, while the interest rate of credit taken from relatives varies from 103.2% in urban and 110% in rural areas.
Credits from institutional sources like commercial banks were about 8% for the chronic deficit households in the rural areas, 2% for the occasional deficit households, and 17% for the break-even households. On the other hand credit from NGOs were about 15% for chronic deficit, 39% for the break-even and 30% for the surplus households in the urban areas and 19%, 30%, 33% and 50% respectively in the rural areas. Of the traditional credit sources, money-lenders, relatives and shopkeepers were prominent particularly among the chronic deficit households both in the urban and rural areas. Among the 130 chronic deficit households, money-lenders provided credit to as many as 52 households (43%) with average interest rates ranging from 103% in the urban and 154% in the rural areas. On the other hand, 30% of the surplus households received credits from the urban areas from NGOs with the interest rate of 17% per annum and only one household out of two surplus households in the rural areas received credit from NGOs sources. NGOs as a credit source, were available more to the break-even and surplus households. On the other hand, the money-lender was reportedly the main source of credit for chronic deficit and occasionally deficit households. Similar results were reported by the BBS in its poverty monitoring survey report on 2,235 rural households.
In the rural area, the poorest households are found to have increasingly utilized credit for directly income yielding activities like agriculture, purchase of rickshaw, etc., instead of consumption and other purposes. This is why credit used for consumption declined appreciably from 76 percent in 1993 to 40 perent in 1996 in the rural area, although it increased in absolute terms during the same period. As regards the urban poor, credit for consumption is found to have reduced from 38 percent in 1993 to 12 percent in the terminal year of the monitoring period. Credit utilized for directly productive activities, on the other hand, escalated during the same period. The change in credit utiliztion took place mainly due to the impact of the new source of credit, namely NGOs who are providing credit to the poor for income yielding pruposes.
Savings by the poorest households have been insignificant during 1993-96. Not only the volume of their savings has been low, but the number of saving households is also very small.
In 1993 there had been no saving-households. However, the number of households participating in the savings programmes increased to 22 percent of the poorest households in the rural area. In the urban slums, no poorest household is found to have saved during this period. In the rural areas, the poorest households who participated in the savings programme could save only Tk. 21 on an average in 1996. However, the average savings per household had been much lower at Tk. 7 and Tk. 3 to 4 for the programme and non-programme households respectively in 1996. The poorest households in the northern part regardless of groups could save nothing during the monitoring period.
The difference in the amount of savings of the three groups of the poorest households is found to have been unchanged, because their saving is largely determined by the differences in the resource bases of these households. The FFE households could save more than the non-FFE households because their resource base is better than those of the non-FFE households.
The poverty monitoring carried out under this study has the following limitations.
The pauperization process in Bangladesh, particularly in the rural area, is in full motion. Poverty is degenerating into indigence and pauperism. In the rural area, 75 percent of the households are poor in 1996 including 55 percent in extreme poverty. The comparable figures for the urban slums are 72 percent and 21 percent respectively. This is one aspect of poverty. The prevalence of poverty as such cannot reveal the “intensity” and “severity” of poverty. The base and impact data under this study confirm that the living standard of the poorest is deteriorating as a part of declining trends of the economy particularly in the rural area where the majority of them live.
To counteract the gradual alienation from land and decline in real labour wages, the poorest households are reducing the consumption of those food items which are badly needed for the maintenance of the physiological existence. They are trying to offset the declining trend in real income by increasing family size and the number of earning members. To them, a larger family size means more earning members and more income for the family. Total income of a household is increasing but per capita income in real terms is declining. The pace of development taking place in the rural areas is so slow that the poorest have to bear the brunt of the stagnation. They are trying to cope with their socio-economic uncertainities and insecurity by resorting to demographic solutions. Some of them are felling back on humiliating activities like begging. The income-earning capacity of the poorest households remained at the lowest level due to lack of gainful opportnities in the rural area. Although NGOs have recently entered the field in the study areas with their credit package, the access of the poorest household to NGO credit is at a lower level. The poorest households are found outside the network of institutional credit. Public policies including budgetary policies are totally ineffective in transfering the benefits to them through traditional channels. Only targeted programmes are found effective in transfering benefits despite leakages and wrong targeting.
The findings from the study provide some empirical ground to raise questions about the rationale of public expenditure in the two important social sectors, namely health and education. From the perspective of poverty, the benefit of the huge public expenditure for the health sector does not reach the poorest in either the urban or the rural areas. The same is the case with the education sector. Although targeted programmes are providing some benefits to the poorest, they fail to ensure the sustainability of such benefits as to link human capability with economic opportunities.
Public policies and public expenditure have failed to satisfy the basic principles of social justice. The pauperization process is pushing hard the hardcore poor to migrate to urban cities for sheer survival. The failure of the public policies in this regard is not only pointing to the inapplicability of the current strands of economic policies but also raises question about the legitimacy of the political and economic governance because of forced displacement and evacuation from their paternal homesteads caused to the poorest by the stagnant rural economy.
The qualitative survey complements most of the above findings. This survey also confirms that the quality of primary education is very poor. While the access of students from the poor households has been improving due to the Food For Education programme in recent years, this did not make a substantial impact on the quality of education. The delivery system introduced by the programme has a number of loopholes which encourage corruption and waste of the teacher-student contact period.
The qualitative assessment of performance of the primary health sector is not encouraging either. The delivery system of the health sector at the grassroots level is inefficient, unequal and often biased towards infrastructure building rather than toward improving the quality of service. The rural poor get maximum health services from pharmacists and existing indigenous providers like herbalists (Kaviraj).
When a set of qualitative tools for monitoring public expenditures were applied to find out their impacts on poverty a number of interesting findings were noted:
A number of food aided programmes for poverty alleviation are in operation (e.g. FFW, TR, VGD, and FFE).
Most of these programmes are intended mainly for transfer of income rather than for capacity building of the beneficiaries. In real sense, these are not poverty alleviating programmes. They are at best survival programmes. But they are quite important in terms of coping vulnerabilities.
However, neither the income nor the employment effect of the food aided programmes has been significant over the past few years.
The targeted rural development projects like RD-5, RD-9, RD-12, even though have contributed to some extent towards increase in income of the poor in absolute terms (however, their number has not been significantly high), the impact of these programmes on social and demographic indicators of poverty has not been satisfactory. Neither, these projects have been very cost-effective.
The targeted public expenditure for women’s development as per cent of ADP increased insignificantly from 0.29% to 0.31% during the last five year despite greater incidence of poverty amongst the female headed households and lagged participation of women folk in labour force.
The Food For Education Programme (FFE), however, is new and has been making some positive impact on both primary education and nutritional status of the poor households.
Increased allocations for educational sector, particularly the targeted FFE programme has reduced dropout ratio in the targeted school areas (at some cost of the non-FFE school areas). However, there are serious concerns about the falling quality of education, the large teacher-student ratios, the reduced contact hours and mismanagement of wheat distribution. Nearly 13% of the wheat disappears in the distribution system.
Some progress has been made in terms of girls’ education. However, early marriage is still a serious constraint to female education.
The adult literacy is still quite low (33%) in the country. The contribution of targeted poverty alleviation projects will remain unpredictable as long as these will be dependent on food aid. If so, the multi-dimensional indicators of poverty can not be adequately addressed by these programmes.
Despite some improvement in the number of institutional channels (both NGOs, GOs and quasi-NGOs), the role of traditional sources of credit (e.g. moneylenders, relatives, shop keepers) is still important among the chronic deficit households both in the urban and rural areas. Our survey reveals that money lenders still provide 43% of the sample chronic deficit households with loans at an average yearly interest rate ranging between 102%-141%. The occasionally deficit households too depend to a large extent on moneylenders for credit.
The credit facilities provided by the institutional sources, (e.g. NGOs, banks and special RD projects) can hardly reach the hard-core poor. They can at best reach the moderate poor. As yet majority of the poor remain outside the institutional credit network.
The poor, both urban and rural, can not understand budget. Many of them did not even heard of it. Those who were aware of it they equated budget with price hike. They observed that budget benefited the well-off, not the poor. They, however, expected that their needs like food, shelter, stable price level, employment, drinking water, agriculture, industry, education, communication, fishery, drinking water get priority in budgetary allocation.
The national budget in Bangladesh by and large has been benefiting the well-off bypassing both the rural and urban poor in the society.
The poor have recorded their own prioritization pattern of allocation. Poor’s prioritization of sectoral allocation significantly differs from that of the government budgets in the recent past. Out of 15 sectors, in total, agriculture has been identified to be the leading sector receiving the topmost priority by the rural and urban poor. Transport and communication – the topmost prioritized sector in the government budget – has been reprioritized next to agriculture in the poor’s budget. Industry is the next important sector in poor’s budget. Education and religion – the second most prioritized sector in government budget — has been ranked fourth in the poor’s budget.
The poor’s budget has clearly shown its own allocation pattern laying added emphasis on five sectors – agriculture, industry, rural development, water resources and subsidy. On the other hand, five other sectors including defence, administration, transport and communication, education and religion and debt service have been relatively de-emphasized in the desired budget compared to the actual expenditures on the same sectors in government budget.
The largest chunk (14%) of total public expenditure has been allocated to agriculture in the poor’s budget compared to the largest share (17%) in total expenditure accounted for by transport and communication in government budget. Standard deviation of sectoral public expenditures have been found higher at in government budget compared to in the poor’s budget. It implies that the poor’s budget is more balanced compared to the government budget so far as sectoral expenditure/allocation is concerned.
An analysis of the expenditure pattern shows that all the sectors except health, population and family planning have been subjected to reallocation in the poor’s budget. Out of the four broad sectoral categories – infrastructures, directly productive sectors, social sectors and miscellaneous sectors – the government budget provides for higher allocations for infrastructures, social sectors and miscellaneous sectors and lower for directly productive sectors compared to the poor’s one. Infrastructure has been given the topmost budgetary allocation in the recent past in the government budgets).
On the other hand the poor’s budget has laid topmost stress on the directly productive sectors which include agriculture, industry and subsidy and has reduced the budgetary allocation for all other sectors under the three sectoral groups, namely infrastructures, social sectors and miscellaneous sectors.
The poor’s budget demands large cutback on the budgetary allocation to non-economic sectors, namely defence, administration and debt service.
The budget reviews reveal that nearly a fourth of the public spending goes into two important social sectors, namely health and education. Below, we look into the quality of these services as perceived by the poor.
In rural areas, despite many weaknesses, the poor have to visit government health complex/centre at Thana/union level, because the skill of doctors are perceived to be good by them compared to others available in the locality. But in reality they are very unhappy with the quality of service they get from them.
In urban areas, government health assistants, NGOs/PVOs, homeopathic, herbalists, diarrhoeal hospital have been the main providers of health service for the urban poor and poorest. Other health service providers found in Dhaka city have been in service of both the well-off and middle.
The key public policies pursued so far exclusively served the well-off. The other social classes, namely middle, poor and poorest were deprived of the benefit from the key public policies under eight broad categories of policies regarding trade, industry, agriculture, manpower, fiscal, food, participation and decentralization. These policies have been selected for assessment by the poor. As perceived by the poor, all these policies benefited the well-off bypassing the poor at large.
The urban poor assessed their own socio-economic development during the last three years in terms of thirteen indicators. On the four-grade scale from ‘very happy’ to ‘very unhappy’ the poor by and large were not found very happy in no cases. They are ‘happy’ with their development in respect of wage rate, credit, development of market place, education and institutional development.
They have been ‘unhappy’ during the last three years with their development in respect of construction/repairing of road, employment opportunities, electric connection, poverty/ crisis and standard of living. The urban poor were found ‘very unhappy’ regarding the law and order and out-migration for job.
The rural poor expressed their perception on their socio-economic development in respect of fifteen indicators on the same scale. By and large, the poor in rural areas are ‘very happy’ with law and order situation and ‘happy’ with wage rate, and education. On the other hand, they are ‘unhappy’ with their development in respect of out-migration for job, credit/banking, living standard and health. The rural poor are found ‘very unhappy’ with the development in construction/ repairing of road, electric connection, irrigation system, institutional development, poverty/crisis, employment opportunities, supply of agricultural inputs and development of market place during the last three years.
The whole budgetary process needs to be overhauled to ensure transparency, simplicity, efficiency, equity and people’s participation.
The budgetary process should be triangular encompassing government, people and think-tank – where the gravitational points of society like government need not yield to any pressure groups. People need to be accommodated in the budgetary process and allowed scope to participate not only in preparatory phase but also in implementing, monitoring and evaluation phases. At this stage people and poor need to be interpreted synonymously and liberally.
The national budget must not be the prerogative of bureaucracy and pressure groups by passing the poor.
The need of the poor must be assessed through participatory process and the poor’s participation in the budgetary process has to be operationalized and sustained. There are now effective tools to make such assessment. These tools should be utilised in preparing national and local budgets.
High allocation of public expenditure to any sector itself can not ensure the desired result.
Formation of an independent development watchdog is a must for ensuring transparency, accountability, implementation, participation and checking corruption.
As the poverty situation in both urban and rural areas is acute and there is no sign of perceptible reduction in the near future the investment strategy and allocation pattern should be modified and geared to directly productive activities to achieve poverty free national self-reliance and autarchy in the long run.
Determining expenditure priorities in the context of limited resources is one of the basic challenges facing all governments. Priorities, in fact, represent interests and concerns of certain specific economic classes or social categories of the society. Theoretically, the class character, interests and concerns of the ruling class are reflected in their priorities. Against the background of the emerging realization and consensus on the part of the elites that their interests would continue to remain unsustainable and under constant risk and threat from the other “half” of the society (Toye and Jackson 1996), and as the realization of the interests of the poor is ostensibly declared to be the sacred task of the non-poor (WB 1992), the need to know the poor’s perception and priorities with regard to sectoral allocation of public expenditure is increasingly being felt by the policy makers, donors and other concerned sections of the society.
The present budgetary process is altogether archaic, non-transparent and mechanical. There is neither the scope for reflecting the people’s perspectives in the budgetary process nor is there any need felt by the ‘public servants’ to ascertain the people’s priorities let alone the poor’s. There is a strong reason to believe that the present budget reflects the preferences of those who are in charge of preparing it. The existing budgetary process is poised to reflect “elite perception”, not the poor’s perception.
What are the public expenditure priorities from the perspectives of the poor? This core question has been addressed in this phase of the study. Besides, some other questions have also been addressed in the study which include: which sectors should be given more priority and which ones less? How to quantify their priorities? To what extent the poor’s perspectives are different from those of a typical recent budget? Are the priorities articulated by the urban poor different from those by the rural poor? How do the poor reflect on the importance of the various economic sectors and give relative weights to them ? These are the questions that have been asked in trying to obtain the poor’s perspectives in the following paragraphs.
The poor, in both the urban and rural areas, do not understand the budget. Many of them have not even heard of it. Those who were aware of it could equate the budget with price hike. They observed that the budget benefited the well-off, not the poor. Even that the budget is perceived as an instrument to put the poor into trouble. They, however, expected that their needs like food, shelter, stable price level, employment, drinking water, latrine, clothing, agriculture, industry, education, communication, fishery, etc., should get priority in the budgetary allocation (Exhibits 30 & 31).
The present budget is viewed by the poor to be highly inequitable with respect to its distributional impacts. Through public expenditure, the national budget in Bangladesh by and large has been benefiting the non-poor to the exclusion of both the urban and rural poor (Exhibit 32). The desired budgetary allocations as prioritized by the poor is expected to have fair distributional impacts on them in the long run. It is, however, true that mere reprioritization of sectoral allocation is no guarantee of a fair distribution of resources; but it is expected that this might benefit them in the long run.
The poor have revealed their prioritization pattern for sectoral allocation of the national budget when they sat in PRA sessions with us (Box 8.1). The poor’s prioritization significantly differs from that of the government budgets in recent times (Exhibits 33 & 34).
Out of 15 sectors, agriculture has been identified to be the most important sector receiving the topmost priority by both the rural and urban poor. The transport and communication sector ¾ the topmost priority sector in the government budget ¾ has been reprioritized next to agriculture in the poor’s budget. Industry has been posted to the third important position in the budget desired by the poor. The education and religion sector ¾ the second most prioritized sector in the government budget ¾ has been ranked fourth on the poor’s desired budget.
Problems facing the poor were identified by the poor themselves, and a list of ‘felt needs’ were the outcome of the participatory discussion, debates and consensus among themselves. Two sets of problems and needs were assessed in a participatory manner each for the urban and rural areas.
To the urban slum poor, homelessness and eviction from slums are the topmost problems. Other serious problems identified by the poor include lack of good health and water facilities, employment opportunities, security, education, latrine, gas, etc. (Exhibit 35).
Regarding the needs assessment, the urban poor listed and prioritized their felt needs. Some of the most important are latrine, shelter, drinking water, electricity, gas, security, rationing, employment and so on (Exhibit 36).
Agricultural inputs, irrigation and culverts are considered to be the topmost problems by the rural poor. Apart from these, some other most serious problems mentioned by them are related to health, electricity, unemployment, flood, drinking water, industrialisation, veterinary facilities, silting up of rivers, etc. (Exhibit 37).
According to the needs assessment and prioritization by the rural poor, some of the most important needs as articulated by themselves are industries for employment, agricultural inputs at a fair price, rural roads, irrigation, electricity, school and madrasa, medical facilities, etc. (Exhibit 38).
The budget charted by the poor has clearly shown their own allocation pattern laying added emphasis on five sectors ¾ agriculture, industry, rural development, water resources and subsidy (Exhibit 39). On the other hand, five other sectors including defence, administration, transport and communication, education and religion, and debt service have been relatively de-emphasized in the desired budget compared to the actual expenditures on the same sectors in the government budget.
The largest chunk (14%) of total public expenditure has been allocated to agriculture in the poor’s budget compared to the largest share (17%) in total expenditure accounted for by transport and communication in the government budget. The standard deviation of sectoral public expenditure have been found higher in the government budget compared to that in the poor’s budget. This indicates that the budget prepared by the poor is more balanced compared to the government budget so far as sectoral expenditure/allocation is concerned.
An analysis of the expenditure pattern shows that all the sectors except health, population and family planning have been subjected to reallocation in the case of the poor’s budget. Out of the four broad sectoral categories ¾ infrastructures, directly productive sectors, social sectors and miscellaneous sectors ¾ the government budget provides for higher allocation for infrastructures, social sectors and miscellaneous sectors and lower for directly productive sectors compared to those for the poor’s one. The infrastructure sector has been given the topmost budgetary allocation in the recent past in the government’s budgets (Exhibits 40 & 41). On the other hand, the poor’s budget has laid topmost emphasis on the directly productive sectors which include agriculture, industry and subsidy. The poor are in favour of a reduction of budgetary allocation for all other sectors under the three sectoral groups, namely infrastructures, social sectors and miscellaneous sectors.
The prominent feature of the poor’s budget is that it demands a large cutback on the budgetary allocation to non-economic sectors, namely defence, administration and debt service.
The perception of the poor on the budgetary process has also been captured by a quantitative knowledge attitude and perception (KAP) survey. The findings of this survey are given below:
It has already been emphasized that information on KAP of the poor people regarding the budget is essential for planners and policy makers in their efforts toward meeting people’s aspirations through the five-year and perspective plans and the annual budgets. In order to know KAP of the poor, an opinion survey was conducted both in the urban and rural areas. Households in the slum areas in Dhaka city were considered as poor and taken as final sampling units for conducting KAP survey on the public budget. Households having land less than 0.50 acres were considered as rural poor and were selected for interviews in the rural areas. In all, 139 households in the urban and 150 households in the rural areas were selected and interviewed to know their KAP regarding the government budget. The sample size was, however, constrained by time and finance.
Based on the opinion survey data, the selected households have been classified according to two criteria and arranged in a rectangular array. This is done to ascertain whether there is any association between the two mutually exclusive classifications. For instance, we may classify respondents according to their knowledge about the public budget and the place of residence (urban and rural) of the respondents or use some other criteria of classification.
To examine the statistical relationship between the classifications, joint frequency distribution of the respondents in accordance with the place of residence and knowledge regarding the budget has been formed. Significance test is then made by using Chi-Square (c2) statistic for the joint classification tables to test whether the classifications are statistically independent, that is, to test whether the data are in accord with the desired null hypothesis (Ho) of association between the two criteria.
The respondents were asked to answer whether they had any knowledge regarding the budget, and their answers were arranged by the level of knowledge (e.g., “Yes”, “No”) and residence (urban and rural).
It appears from the table that about 55% of the respondents in the urban areas have not heard about the budget, while this figure for rural areas is about 81%. The estimated value of c2 is 21.36 indicates that the association between the two criteria of classifications is significant at 0.0001% level. The null hypothesis is, therefore, rejected which means that the level of knowledge is dependent on the location of the sample respondents. A higher percentage of respondents in the urban areas have some knowledge about the national budget than their rural counterpart. When the opinions (“Yes” and “No”) of the respondents are classified according to their respective educational levels (illiterate, literate), the estimated value of c2 indicates that variations in opinion about the budget depend on the variations of the education level of the respondents. Similar results are also obtained when the respondents are distributed according to their opinion (“Yes” and “No”) and income level (Taka 1000, 1000-2500 and 2500+).
The respondents who expressed their opinion that they had some knowledge about the budget were also asked whether they had discussed the budget with others after hearing of it. In response, about 95% in the urban areas and about 76% in the rural areas said “Yes”. It appears from the joint frequency distribution and estimated value of c2 = 7.52 indicates that the null hypothesis is to be rejected, i.e., variation in knowledge depends on the variations in the location of residence of the respondents. But when this table is classified according to the level of opinion and the level of education (illiterate and literate), we do not find any association between the two criteria of classification. Actually, the level of education among the poor in the sample area is very low so that the impact of education on the attitude of the respondents is not found to be significant. As a result, in most of the cases we do not find any significant variation in the answer with the variation of the educational level.
It seems from the findings that there is no difference in the topics of discussion on budget among the poor, irrespective of level of literacy. Overwhelming majority of the respondents mainly discuss the issue of price hike.
The respondents were asked to indicate whether the problems of their day-to-day life can be solved through the budget. The answer is given in Table 8.7 which illustrates the distribution of respondents by level of answer (“Yes”, “No” and “Do not know”) and residence (urban and rural).
It is seen from the table that about 55% of the respondents in the urban and 81% in the rural areas said “do not know”, while about 42% in the urban and 16% in the rural areas said “yes”, and the rest said “no”. The value of c2 = 23.60 indicates that there is a strong association between the criteria of classifications, which implies that there is variation in the level of reply due to variation in the level of residence.
A section of the respondents thought that the national budget, if properly designed and prioritised can help solve the problems identified by them. The order of intervention, according to this group, should be employment creation, infrastructure and environmental protection.
The classification of the respondents according to their answers on the usefulness of the budget (“useful”, “not useful” and “do not know”) and their residence (urban and rural).
It is seen from the table that about 55% of the respondents in the urban and 81% in the rural areas have expressed the views that they actually do not know about the usefulness of the budget. On the contrary, about 40% of the respondents in the urban and 16% in the rural areas opined that the national budget does not serve their interests. However, the value of c2 = 21.88 indicates that the level of usefulness and the category of residence of the respondents are not independent.
Next, they were asked where from they received information about the budget. A majority (80% in urban and 73% in rural areas) of the respondents have said that they have come to know of the budget through radio and different persons. The variation in the level of opinion regarding whether they hear or read the budget speech depends on variations in both education and income levels. The estimated value of c2 supports this statement. Regarding the understanding of the budget speech, about 59% of the respondents in the urban and 69% in the rural areas have said that they do not understand the budget speech. They have also reasoned their inability to understand the budget speech. The main reason for not understanding the budget speech appears to be the illiteracy of the respondents. And 50% respondents in the urban and 11% in the rural areas said that the budget is not easily understandable.
The respondents according to the level of reasons for not listening to the budget speech (lack of radio/TV, illiterate and do not understand/busy with work) and residence (urban and rural). The main reason for not listening to the budget speech appears to be the difficulties in understanding and lack of time. About 61% of the respondents in the urban and 73% in the rural areas said that they do not understand the budget speech and so they do not listen. Seven percent of the respondents do not listen to the budget speech for not having access to radio/TV and 24% for not having education. The estimated test statistic c2 = 5.71 is significant at the 5% level which implies that the level of reasons is dependent on the level of residence of the sample respondents.
Among the respondents, about 65% in the urban and 91% in the rural areas do not seem to react to the budget. However, about 35% of the respondents in the urban areas have expressed their reaction to the budget. The estimated c2 = 28.43 rejects the null hypothesis that there is no association between the level of reaction and the level of residence. Ignorance about the budget is found to be the main reason for not reacting to it.
When asked to identify the immediate impact of the declaration of the national budget about 65% of the respondents in the urban and 91% in the rural areas have said that they do not observe any impact following the budget speech. The rest have expressed their views that they do observe some impacts in the form of rise of the market price of commodities.
The implication of the inadequacy of the knowledge and understanding of the poor about the national budget is serious and worthy of deep reflection. This implies that the poor can hardly act as an organized pressure group to influence the budget decisions in favour of their upliftment, to exert any demand for radical changes in the budget process, despite the fact that the budget is the single conduit for public resources to be diverted to the underprivileged and distressed masses.
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