Urban poverty and governance: the case of Multan City.

Chaudhry, Imran Sharif ; Malik, Shahnawaz ; Imran, Asma 等

I. INTRODUCTION

The issue of poverty is as old as economic development. A significant quantitative research on poverty has been undertaken for many decades all over the world in general and in developing countries in particular. However the issue of urban poverty has not been addressed effectively. Nevertheless urban poverty has until recently, been low on the agenda of development policy not only in the developing world but also in Pakistan because of dominant perception of urban bias and the need to counter this with a focus on rural development policy.

The analysis of urban poverty is as necessary as the overall level of poverty in the country. There are many causes and determinants of urban poverty (1) but distribution and management of economic and social resources in poverty reduction cannot be ignored. It is internationally recognised that poverty reduction and governance both are interrelated. Bad governance has made poverty reduction efforts ineffective [Blaxall (2000), Eid (2000) and Gupta, et al. (1998)], while poverty reduction projects provide fertile ground for corruption. (2) The consensus emerges from this line of thinking is that good governance is necessary and effective for poverty alleviation efforts.

A large number of studies in Pakistan agree that urban poverty fluctuated around 40 percent level during the sixties, remained close to 20 percent during the eighties and persisted around 30 percent since the nineties. The persistence of lower level of urban poverty is regarded due to the strong growth rate, rise in per capita income, large inflow of remittances, and better economic and social policies of the present government. However there is a need to examine the situation of urban poverty and governance at the city level. Multan is one of the largest cities of Pakistan with an estimated population of over 1.2 million. It accounts for 2.8 percent of the urban population of the country, and 6 percent of the urban population of Punjab province [District Census Report of Multan (1998)]. Multan has grown at a very rapid rate and becomes a major urbanised area in Punjab. It is the industrial, commercial, financial, and service centre of the country. In recent years, the urban infrastructure has become overburdened and the city has been subjected to considerable urban strife.

The above observations, roughly, provide an agenda for the present study. The major objective of the study is to highlight the determinants of urban poverty with a special focus on governance at the city level. This paper consists of five parts. Section II describes the conceptual framework of urban poverty and governance, and also presents the review of the literature. Section III describes the methodology and data issues. Empirical results and discussion is given in Section IV. Finally, policy recommendations based on the findings are given in Section V.

II. URBAN POVERTY AND GOVERNANCE

Urban poverty and governance are the contemporary issues of economic development particularly in developing countries like Pakistan. Numerous studies have found that corruption reduces public revenue and increases public spending. As a result, it also contributes to larger fiscal deficits, making it more difficult for governments to run a sound fiscal policy. Studies also find that corruption is likely to increase income inequality and poverty [Qureshi (1999)]. Nevertheless, the issue of good governance has not been discussed earlier in terms of the management of urban infrastructural facilities and urban poverty in Pakistan.

(a) Conceptual Framework

Some authors doubt the distinction between urban and rural poverty because of the fear that such distinction would remove one from considering the main determinants of poverty [Wratten (1995)]. There are however, some distinguishing features of urban poverty that need to be recognised and to be understood. The incidence, economics, demography, politics and governance of poverty differ between urban and rural areas. Moreover, a city poverty assessment is a tool for acquiring up-to-date information on a city's poverty and social development. Constructing a poverty profile at the city level will provide a snapshot showing who is poor, where they live in the city, their access to services, their living standards and so forth, thereby contributing to the targeting of poverty measures.

There is no consensus on a definition of urban poverty in the literature but two broad complementary approaches are prevalent: economic and anthropological interpretations. Conventional economic definitions are currently still the most widely used proxies for evaluating human welfare. By comparing income, or consumption, against a set of basic needs it is argued that it is possible to compare the depth and extent of poverty between different groups even within a large city or for the same group at different points in time [Wratten (1995)]. Moreover, the minimum level of income necessary to meet the defined set of need is so-called 'poverty line'.

The economic definition of poverty has so far proved easy to measure and has provided a useful tool for understanding the general patterns of deprivation and causes of urban poverty. So, we use income-based approach to urban poverty in the present study because it is the most frequently used proxy for poverty. The measurement and analysis of urban poverty is an important tool for monitoring the progress towards target urban poverty alleviation goals and objectives.

The term "governance" or "good governance" is being used extensively in the development literature. Bad governance is being considered as one of the root cause of poverty particularly in urban areas. Now-a-days, major donors and international financial institutions are increasingly basing their aid and loans to developing countries on the condition that reforms that ensure 'good governance' are undertaken.

The concept of 'governance' is not new; it is as old as human civilisation. Simply governance means the process of decision-making and its implementation. The concept of governance can be used in several contents such as corporate governance, international governance, national governance and local governance. Governance refers to the manner in which power is exercised in the management of a country's economic and social resources. Good governance requires checks and balances in a country's institutional infrastructure, such that politicians and bureaucrats have the flexibility to pursue the common good, while restraining arbitrary action and corruption [Hussain (1999)].

The World Bank (1992) defines good governance as a public service that is efficient, a judicial system that is reliable, and an administration that is accountable to its public. Moreover, the World Bank (1992) defines three different dimensions of governance. First, type of political regime (Parliamentary or Presidential, Military or Civilian and authoritarian or democratic). Second, the process by which authority is exercised in the management of a country's economic and social resources. Third, the capacity of the government to design, formulate, and implement policies, and in general, to discharge functions. The United Nations Development Programme [UNDP (1997)] defines governance as:

 The exercise of economic, political and administrative authority to
 manage a country's affairs at all levels. It comprises of the
 mechanisms, processes and institutions through which citizens and
 groups articulate their interests, exercise their legal rights,
 meet their obligations, and mediate their differences.

The World Bank economists Daniel Kaufmann, Aart Kraay, and Pablo Zoido-Lobation (1999) define governance as:

 .....the traditions and institutions by which authority in a
 country is exercised, including (1) the process by which
 governments are selected, monitored and replaced; (2) the capacity
 of the government to effectively formulate and implement sound
 policies; and (3) the respect of citizens and the state for the
 institutions that govern economic and social interaction among
 them.

Governance is a multidimensional concept that consists of political, economic socio-cultural-variables and management of infrastructural facilities that determine whether public policy designed by the government can achieve its intended goals and improve welfare of its people. Nevertheless present study is concerned with the local governance particularly in terms of the management of drinking water, sanitation, sewerage and road facilities in Multan city.

(b) Literature Review

Since governance is an old concept that originates from early democratic political theory, which discusses the relationship between the rulers and the people, they rule, it has gained significant attention in the developing world recently. This was motivated by a concern that bilateral and multilateral assistance from the developed world to developing countries had failed to reach its goals (i.e. to reduce poverty and promote sustainable economic growth) and result was the wide spread corruption in the management of the urban facilities to households.

With these brief background concepts of governance and urban poverty in mind we come to the experience of Pakistan. Urban poverty and governance have, until recently, been low not only on the agenda of development policy but also at the level of enquiry or research in Pakistan. According to the most recent evidence, despite rapid economic growth rate of 8.6 percent in 2004-05 and 6.6 percent in 2005-06, urban poverty declined by relatively less rate as compared to the rural poverty in Pakistan. (3) This necessitates the need to address the issue of urban poverty in relation to governance at city level in Pakistan.

A fair number of studies on poverty are available for a period up to recent times in Pakistan. These studies include, Naseem (1973, 1977), Alauddin (1975), Wasay (1977), Mujahid (1978), Ercelawn (1988, 1990), Akhter (1988), Abroad (1993), Altaf, et al. (1993), Amjad and Kamal (1997), Zingel (1998), Ali and Tahir (1999), Jafri (1999), Qureshi and Arif (2001), Arif, et al. (2001), FBS (2002) and Malik and Chaudhry (2005). Most of these studies used data from the household income and expenditure surveys (HIES) and estimated overall, rural and urban poverty figures. However, two major studies, first by Wasey (1977) and second by Altal, et al. (1993) have been undertaken exclusively on urban poverty. Both were detailed studies relating to urban poverty in Rawalpindi and Karachi cities respectively.

The concept of governance has gained significant attention in the international policy making arena and recently in Pakistan. There are few studies on governance in Pakistan. These are Hijazi (1999), Husain (1999), Qureshi (1999), Shafqat (1999), Shah (1999), Streeten (1999), and Tahir (1999). Hijazi (1999) analysed the relationship between motivation theories and role of the government servants. He concluded that the working system in government is administrative and not management, and good governance can be achieved by considering the motivation of the key role occupant.

Hussain (1999) has undertaken a detailed study on governance and institutions with particular reference to Pakistan. He elaborated the concepts of governance and institutions, their definitions and relationships. He divided public sector functions into three categories, namely, policy-making, service delivery, and oversight and accountability, and focused on the last. Moreover, he also presented the pillars of good governance.

Qureshi (1999) also emphasised on good governance based on appropriate institutional reforms and broad-based sustained economic growth policies. Shafqat (1999) focused on the role and assessment of bureaucracy with some changing socioeconomic profile and corresponding attitudinal changes and provided guidelines for possible reforms in Pakistan. He concluded that a piece-meal but holistic reform of the existing bureaucratic institutions is really needed. Shah (1999) also contributed with three complementary themes in bringing about responsive and accountable public governance namely globalisation, localisation and a results oriented management and evaluation.

These analyses have focused on the different issues related with good governance at a macro level. However, the present study attempts to analyse urban poverty in Multan city and how it can be alleviated with good governance among other factors.

III. DATA AND METHODOLOGY

The analysis of poverty in Multan city is significantly based on primary source of data collected from the enumeration blocks of Multan city as identified by the Federal Bureau of Statistics (FBS) using simple and systematic random sampling techniques. The urban household survey was conducted and information was recorded from sampled 200 households.

The next step in poverty analysis is the identification of an urban poverty line that distinguishes the poor from non-poor. Instead of calculating a new poverty line to be used in this study we decided to follow the poverty line estimated by FBS (2002). The FBS estimated a poverty line (Rs 650.00) based on 2150 calories per day per adult for the period 1998-99. Then we inflated it using the consumer price index (CPI) of annual changes in prices (Pakistan Economic Survey, 2004-05). The resultant urban poverty line is Rs. 865.52.

In this study, three different formulations have been employed for empirical analyses namely descriptive analysis, bi-variate analysis and multi-variate analysis. In order to estimate the incidence, depth and severity of poverty, Foster, Greer and Thorbecke (FGT) index (1984) is used. Moreover, we also use Logit Model for multivariate analysis in order to explain the determinants of urban poverty. In Logit Model the endogenous variable is a dichotomous or dummy variable, with (1) if the urban household is poor, and (0) if the urban household is not poor under the hypothesis of logistic distribution. The list of the variables for Logit model is given in Table 1.

IV. EMPIRICAL RESULTS AND DISCUSSION

Urban poverty is multidimensional and involves several issues related to employment, income, labour market, health and education, shelter, infrastructure and particularly governance relating to all socio-economic and demographic variables. A comprehensive view of these dimensions is necessary to get a good understanding of the determinants of urban poverty at city level.

(a) Descriptive Analysis

Before discussing the structure and profile of urban poverty status, it is necessary to present the descriptive analysis of the facts and poverty related issues that have been observed during the conduct of household survey. Urban household survey was conducted during the months of March to April 2006 of the same 200 households as taken in 2003 by the same authors. The urban household survey data indicates that surveyed households are mostly Sariki speaking followed by Punjabi and then Urdu speaking.

The urban poor in Multan city live in a crowded, with very poor or non-existing sanitation facilities and undesirable environment particularly around the railway line, slums and in the areas of old city. Poor people are facing the problem of sanitation facilities, sewerage, poor conditions of roads, solid waste management and polluted environment. Water and sewerage services are the responsibility of Water and Sewerage Authority (WASA) in Multan city. The old sewerage system is inefficient and does not fulfill the needs of the people. The city government has started many schemes of sewerage and sanitation but poor areas have not been benefited so tar. Solid waste management in the city is the municipality function, which is carried out by the Tehsil Municipal Administration (TMA) of four towns. Solid waste collection in the city of Multan is in a state of deplorable condition. Heaps of garbage is the common feature all over the poor areas. According to statistics of city government, 35 tones solid waste is created by the habitants daily but only 14 tones is being collected and managed. This unhygienic condition is also creating health problem of the poor households.

According to the findings of urban household survey data, the urban 200 households have 1476 members with 51 percent male and 49 percent female population. Male literate persons are 64.18 percent while female 59.46 percent. Average household size is 7.4 persons per household. Dependency ratio per household is 0.79 while child and old dependency ratios are 0.67 and 0.12 respectively. Participation rate per household is 52 percent and literate household heads are 82 percent while 18 percent are illiterate. Average age of the household head is 52.63 years. Persons per room per household are 3.58. About 45 percent households have the location and housing problems. Households take 25.2 minutes on average to reach the nearest health center, bus stop, bank and post office. About 93 percent households have the facility of gas and electricity.

In sum, good governance based on proper management and provision of infrastructural facilities on equity basis to all households in the city, can minimise the level of poverty and problems of poor households. City government should make their efforts to alleviate urban poverty, not just through an increase in income level, but also through good infrastructural management for the poor.

(b) Bivariate Analysis

The urban poverty profile is a bi-variate analysis that compares the poverty status. The important and most common method of presenting urban poverty data is to apply poverty measures for various household groups. Three different poverty indices have been estimated: the headcount, the poverty gap and the severity of poverty. Descriptive Index of Governance is used as a proxy variable for the empirical analysis. Index of governance consists of the management of sewerage system, sanitation conditions, drinking water, and roads. The area where all mentioned facilities are in a worse situation and not being managed accordingly is called the area of bad governance and vice versa. The results are given in Table 2.

The results of Table 2 show that enumeration block-I has the highest incidence, depth and severity of poverty than enumeration block-III. Similarly the index of governance shows that the area where it is very low has highest level of poverty. As governance in terms of variables improves, urban poverty reduces. Thus there is trade off between good governance and poverty alleviation in urban areas. Overall 24.50 percent households are poor in Multan city. The other two indicators, poverty gap and severity of poverty are aggregate measures of scatterness of the poor below the poverty line. A lower value indicates that most of the poor are bunched around the poverty line. In line with the improvement in headcount, both the poverty gap and severity of poverty has also declined substantially with the improvement in infrastructural governance in Multan city.

Bi-variate analysis is also conducted to compare the number of poor people between years 2003 and 2006 at city level. It also reveals the indication of good governance. The results are given in Table 3.

On average, an incidence of poverty dropped from 36 percent to 24.50 percent due to better management and improvement in basic infrastructure, socio-economic and demographic variables. This decline in poverty of Multan city indicates the improvement in good governance through better management by the local bodies. However substantial struggle is needed to be done for good governance at city level.

(e) Multivariate Analysis

To strengthen the results of bi-variate analysis given above, a multi-variate approach is also exercised. The analysis of the determinants of urban poverty is a multivariate analysis that extends urban poverty profile by attempting to infer the causality of specific household characteristics and proxy dummy variable for governance. The Logit estimates of the factors affecting urban poverty are given in Table 4.

The empirical results show that all the variables have correct signs. The regression results confirm the indications of bi-variate analysis that good governance affects urban poverty. Household size (HSIZE), female-male ratio (FMRA), dependency ratio (DEPR), age of household head (AGEH), female household head (FEMALE), casual and informal worker (INFOR) and persons per room (PROOM) have the odds ratios more than one, which confirm the positive relation with the probability of being poor. On the contrary, variables like participation ratio (PART), female participation (FPART), literate household head (HLITE), value of assets (ASSETS), governance (GOVER) and owned house (OWNH) have odd ratio less than one, which means that these variables are inversely correlated with the probability of being poor.

The coefficients of HSIZE, FEMALE, OWNH and FMRA are not statistically significant and rather inconclusive. This implies that there is no significant effect of these variables on the probability of being poor. The coefficient of dependency ratio (DEPR) has the positive significant effect on the urban poverty. The coefficient of (HLITE) has the negative significant effect on the urban poverty. It implies that the more literate heads have more potential to exploit the resources and technology and avoid urban poverty. The coefficient of (ASSETS) has the negative significant effect on urban poverty. It implies that the households having better assets will lead to escape urban poverty.

Participation and female participation rates are the main components of employment of urban households. Both variables have the correct signs and have negative effects on urban poverty. The coefficient of (PART) has the negative significant effect on being urban poor. It reveals that more earnings of a household will increase the income level and this tendency directly alleviates urban poverty. Similarly the role of female participation cannot be ignored to alleviate urban poverty. The coefficients of (AGEH) and (OWNH) are the insignificant variables. Empirically, it is proved that female household heads (FEMALE) are positively correlated with the probability to be an urban poor. The coefficients of (INFOR) and (PROOM) have positive and significant effect on urban poverty. The overall model of total households is also empirically significant at all levels.

The proxy variable of governance is also found statistically significant that affects the probability of being urban poor with inverse relation. As governance improves in the urban areas, poverty reduces. Moreover, dependency ratio can be minimised through sound employment and better population policies. It is also concluded that good governance in education sector also affects the poverty profile by many ways.

V. CONCLUSIONS AND POLICY RECOMMENDATIONS

Generally, it is believed that bad governance is considered as one of the root causes of all evil. The problem of governance was apparent in Pakistan, but it is ignored. Pakistan has been ranked highly on the list of most corrupt countries in the world for a long time. At present, evidence suggests that reduction in poverty at all levels is due to the significant improvements in governance in Pakistan.

The analysis suggests that poor people who are in the weakest position and who are most powerless in influencing decisions that affect their lives, become most vulnerable in the face of bad governance. It is also evident from the descriptive analysis of the present study. It is concluded that urban poverty can be alleviated through good governance in infrastructure, socio-economic and demographic variables at the city level.

Keeping in view the above discussion, we offer some policy recommendations to alleviate urban poverty through good governance in Pakistan in general and in Multan city in particular.

(i) Waste disposal, sanitation, drainage, sewerage, and environmental health services remain totally inadequate and flawed. There is an ardent need to address these through city level governance. Consequently, urban poverty will also reduce. City government should give more attention to improve infrastructure and services particularly in low-income areas of Multan city.

(ii) The coordination between different development institutions is necessary so that costs can be minimised. The condition of roads and streets should be improved in the areas of slums and around the railway line in Multan city.

(iii) City government should manage and create human capital in the shape of better technical education that will increase the productivity of the urban poor.

(iv) Female labour force participation helps in overall growth and development of the country. Efforts should be made to provide the financial help through different financial schemes to females to start home based income-generating activities like cottage industry (Embroidery, garments, etc.) in Multan.

(v) It is also empirically proved that majority of urban poor household is engaged in casual and informal sector work. Steps should be taken to improve the informal sector for better earnings. Improving physical access to jobs and markets can be facilitated through better and more affordable transport facilities to low-income settlements particularly near the railway line in Multan city.

(vi) The process of decentralisation in Pakistan remains incomplete. The central government should give more sovereignty and accountability to the city level governments and institutions.

To summarise, steps should be taken by the city governments to improve economic and social infrastructure in urban areas to alleviate urban poverty. However, further studies are needed to explain the relationship between urban poverty and governance in Pakistan at macro level.

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Imran Sharif Chaudhry <imrancbaudhry@bzu.edu.pk> is Associate Professor of Economics and Shahnawaz Malik <shahnawazmalik@bzu.edu.pk> is Professor of Economics, Bahauddin Zakariya University, Multan. Asma Imran <asmamajeedsh@yahoo.com> is Lecturer in Economics at Multan Postgraduate College, Multan.

Authors' Note: We are grateful to Dr Aqdas Ali Kazmi for his valuable and useful comments on an earlier draft of this paper.

(1) See Malik and Chaudhry (2005).

(2) See for example Woodhouse (2001).

(3) See Pakistan Economic Survey, 2005-06. pp.55 and 1.

(4) Federal Bureau of Statistics (FBS) has used the concept of enumeration blocks in sampling.

Table 1

List of Variables for Logit Model Estimates of the Factors
Affecting Urban Poverty

Variables Variable's Description

 Dependent Variable

POV = 1 If the urban household is poor
 = 0 If the urban household is non-poor

 Explanatory Variables

HSIZE Size of the urban household
FMRA Female-male ratio
DEPR Dependency ratio
PART Participation rate
FPART Female participation rate
AGEH Age of the household head (years)
FEMALE = 1, If household head is female, and
 = 0, If male
HLITE = l, If household head is literate, and
 = 0, if illiterate
ASSET = 1, If household head has physical assets, and
 = 0, If otherwise
INFOR = 1, If household head is casual and informal sector
 worker, and
 = 0, If otherwise
OWNH = I, If household head has own house, and
 = 0, If otherwise
PROOM Persons per room in a household
GOVER = 1, If urban household locates in the area where,
 sufficient facilities of drinking water, sanitation,
 sewerage and roads are available and properly
 managed/maintained by the city government.
 = 0, Otherwise

Table 2 Urban Povertv Estimates and Governance

 Poverty Poverty
Enumeration Blocks (4) Incidence Depth

Enumeration Block-I 19.11 6.30
Enumeration Block-II 5.39 2.05
Enumeration Block-III 00.00 00.00
Total Sample 24.50 8.35

 Severity Index
Enumeration Blocks (4) of Poverty of Governance

Enumeration Block-I 2.04 Very lowest index
Enumeration Block-II 0.92 Lowest index
Enumeration Block-III 00.00 Highest index
Total Sample 2.96

Source: Calculated from the Urban Household Survey Data, 2006.

Table 3 Urban Poverty Reduction between 2003 and 2006 in Multan City

Indicators of Poverty 2003 2006

Incidence of Poverty 36.00 24.50
Poverty Gap 14.10 8.35
Severity of Poverty 6.60 2.96

Source: The figures of 2006 are calculated using data collected in
2006 and for 2003 figures, sec Imran (2004).

Table 4 Logit Estimates of the Factors Affecting Urban Poverty

Explanatory
Variables Coefficient Z-Statistic Odd Ratio

HSIZE 0.02 0.65 1.05
FMRA 0.28 0.48 1.48
DEPR 1.93 * 3.45 6.82
PART -6.38 *** 1.83 0.09
HART -6.76 ** -1.96 0.18
AGE11 0.04 0.85 1.09
FEMALE 1.68 1.04 2.82
ALITE -3.20 ** 2.30 0.15
ASSETS -8.49 * 2.96 0.04
INFOR 3.45 * 3.60 18.42
OWNH -1.08 1.08 0.16
PROOM 1.49 * 2.86 1.75
GOVER -8.30 * -3.02 0.01
Constant -10.74 1.39 --

 Log-likelihood = -34.92
 Joint significance = 10.51, DF = 12, p = 0.000,
 n = 200

Source: Estimated from the Urban Household Survey Data, 2006.

Note: * Indicates that the coefficients are significant at 1 percent
level.

** Indicates that the coefficients are significant at 5 percent
level.

*** Indicates that the coefficients are significant at 10 percent
level.