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«Title of Document: SOCIETY AND INFRASTRUCTURE: GEOGRAPHICAL ACCESSIBILITY AND ITS EFFECTS ON SCHOOL ENROLMENT IN NEPAL Shyam KC, Doctor of ...»

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ABSTRACT

Title of Document: SOCIETY AND INFRASTRUCTURE:

GEOGRAPHICAL ACCESSIBILITY AND ITS

EFFECTS ON SCHOOL ENROLMENT IN

NEPAL

Shyam KC, Doctor of Philosophy, 2007

Directed By: Professor Reeve D. Vanneman Department of Sociology This research examines the effects of geographical isolation on school enrolment in Nepal using mainly the Nepal Living Standards Survey-II (2003-2004). Nepal, a country with severe road accessibility problems, presents an especially suitable population for this research. Geographical access is measured as the time required by the household to reach the nearest motorable (dirt or paved) road. The accessibility profile that emerges reflects three forms of imbalance in the state-society relations in Nepal. The first imbalance is regional. The second imbalance is socio-economic reflected mainly in higher concentrations of poverty and illiteracy in inaccessible areas. The third imbalance is the state’s inability to cater essential services for the people there.

Stepwise regressions of the NLSS-II cross sectional data show that isolated children are less likely to be enrolled in part because they are poorer, have less educated parents and are from disadvantaged caste/ethnic groups. Another important part of the reason is isolated children are served by distant and low quality schools and also lack basic services such as electricity. Among secondary aged children, isolation continues to have an independent effect even after taking into account all other determinants of enrolment. This suggests that isolation operates beyond the socio-economic, familial and institutional disadvantages the children face in getting enrolled in school. Adolescent (but not pre-adolescent) girls are more likely to be impacted by inaccessibility than boys.

There is no evidence that inaccessibility operates differentially amongst the poor and the non-poor in sending children to school.

Analyses of the NLSS panel data reveals that improvements in accessibility improves the chance of the children to continue being enrolled in school, but the remoteness they lived through in their childhood also affects such chances in later years.

‘Physical’ networks in the form of roads have the potential to enhance social networks and the political voice of isolated households, which in turn enables them to value and demand education for their children. Sociology of roads is a field that needs to be expanded to get a better insight on the social changes that are associated with the building of roads.

SOCIETY AND INFRASTRUCTURE: GEOGRAPHICAL ACCESSIBILITY AND

ITS EFFECTS ON SCHOOL ENROLMENT IN NEPAL

–  –  –

Advisory Committee:

Professor Reeve Vanneman, Chair Professor Sonalde Desai John Leslie Hine Professor Roberto Patricio Korzeniewicz Professor Michael Paolisso © Copyright by Shyam KC To my parents, Shrimati Pabitra Khatri and Shri Dol Bahadur Khatri

–  –  –

I am grateful to my advisor Professor Reeve Vanneman for his mentoring and guidance throughout my PhD program, including for this research. His teaching has increased immensely my ability to do a better sociology. I thank Professors Sonalde Desai, Roberto Patricio Korzeniewicz and Michael Paolisso for their comments on the proposal and for the support they provided at various stages of my PhD program.

My work with the Transport Results Initiative of the World Bank led by Peter Roberts helped materialize this dissertation greatly. I have benefited from insightful comments by him, John Hine and Dr. Douglas Barnes at the World Bank. I express my sincere thanks to them. I am thankful to Dr. Saurav Bhatta and Dilip Parajuli for their suggestions regarding the use of NLSS-II data.

I presented parts of this research in the Department of Sociology at Maryland, at the World Bank, Washington, DC and in the IUSSP/BIDS workshop on Gender and Access in Dhaka. I am grateful to all participants of these meetings. I express my gratitude to my colleagues who helped me with my field visit, in accessing resources and discussing the research with me in Nepal. Also, I am thankful to all my friends in the sociology department for their friendship and support.

At this moment, I am flooded with memories of my family members, old friends and well-wishers who have, in one way or the other encouraged and supported me in this endeavor of mine. I would like to thank you all for being with me all these times.

Finally, this effort of mine would not have been complete without the faith and love I have received from my Mother, Father, my wife Shashi, and our boy Shashwot. Thank you for living through the process and for your unconditional support.

–  –  –

vi

5.12 Logistic regression of school enrolment on dirt road accessibility (all 194 children age 6-12)

5.13 Logistic regression of school enrolment on dirt road accessibility (all 197 children age 13-19)

5.14 Logistic regression of school enrolment on dirt road accessibility (rural 200 children age 6-12)

5.15 Logistic regression of school enrolment on dirt road accessibility (rural 204 children age 13-19) 5.16 5.16. Ideal types of secondary age children and estimated probabilities of 206 enrolment





5.17 Logistic regression of school enrolment on dirt road accessibility (all 207 children age 6-12), using log functional from

5.18 Logistic regression of school enrolment on dirt road accessibility (all 210 children age 13-19), using log functional from of accessibility

5.19 Logistic regression of school enrolment on dirt road accessibility (all 213 children age 6-12), 4 categories of accessibility

5.20 Logistic regression of school enrolment on dirt road accessibility (all 217 children age 13-19), using 4 categories of accessibility

5.21 Logistic Regression: Comparison of dirt road accessibility coefficients 221 using different functional forms

5.22 Logistic regression of school enrolment on dirt road accessibility, 222 comparing with results for clustering at the household level

5.23 Logistic regression of school enrolment on dirt road accessibility, 227 comparing results with results for clustering at the household level

5.24 Logistic regression of school enrolment on paved road accessibility (all 228 children age 6-12)

5.25 Logistic regression of school enrolment on paved road accessibility (all 231 children age 13-19)

5.26 Logistic Regression: Comparison of dirt road and paved road accessibility 233 coefficients

5.27 Logistic regression of school enrolment on geographical accessibility (all 235 children age 6-12) using both dirt and paved road measures

5.28 Logistic regression of school enrolment on geographical accessibility (all 238 children age 13-19) using both dirt and paved road measures

6.1 Time to closest dirt road vs. school enrolment by gender 262

6.2 Logistic regression of school enrolment on accessibility and interaction 263 between gender and accessibility (all children age 6-12)

6.3 Logistic regression of school enrolment on accessibility and interaction 266 between gender and accessibility (all children age 13-19)

6.4 Logistic regression of school enrolment accessibility and interaction 269 between gender and accessibility (rural children age 13-19)

6.5 Logistic regression of school enrolment accessibility and interaction 272 between gender and accessibility (rural children age 6-12)

6.6 Logistic regression of school enrolment on accessibility by gender 275

7.1 Time to closest dirt road vs. school enrolment by poor/non-poor 288 vii

7.2 Logistic regression of school enrolment on accessibility and interaction 289 between poverty and accessibility (all children age 6-12)

7.3 Logistic regression of school enrolment on accessibility and interaction 292 between poverty and accessibility (all children age 13-19)

7.4 Logistic regression of school enrolment accessibility and interaction 295 between poverty and accessibility (rural children age 6-12)

7.5 Logistic regression of school enrolment accessibility and interaction 298 between poverty and accessibility (rural children age 13-19) 8.1 % households by one way time to nearest road from households in 324 1995/1996 and 2003/2004 8.2 % households in different accessibility zones (1995/1996 and 2003/2004) 325 8.3 8.3. Change in accessibility level between 1995/1996 to 2003/2004 326

8.4 Number of PSUs by one way median PSU time to nearest road in 327 1995/1996 and 2003/2004

8.5 Change in various development indicators between 1995/1996 and 328 2003/2004

8.6 Regression of log odds of PSU school enrolment on road accessibility 329

8.7 Difference in PSU enrolment by change in PSU accessibility level 330

8.8 Village level fixed effect regression on change in log odds of enrolment 331 on dirt road accessibility

8.9 Logistic regression of school enrolment on road accessibility, 1995/1996 332 and 2003/2004 separately for Age 6-12 and Age 13-19

8.10 Difference in enrolment by change in accessibility level 333

8.11 Logistic regression of 2003-2004 school enrolment of children 6-12 334 enrolled in 1995-1996 on change in accessibility

8.12 Logistic regression of 2003-2004 school enrolment of children 6-12 336 enrolled in 1995-1996 on change in accessibility

–  –  –

Geographical inaccessibility has often been cited, and rightly so, as a major hurdle for the rural poor in developing countries to embark on a path to better lives. Just as inaccessibility prevents them from reaching facilities for getting basic services, such as education and medical care, it also restricts movement of external actors who are trying to reach them. In this research, I explore the effect of geographical accessibility/isolation, as measured by access to motorable roads, on school enrolment in Nepal using mainly the Nepal Living Standard Survey-II (2003-2004), and also drawing from the insights from a field level study that I carried out in July 2006 in Nepal. Nepal, a country with severe accessibility problems and low level of school enrolment presents an especially suitable population for this research. About 56% of the rural population lives at least an hour’s walking distance from the paved roads, and about 28% do so even from the dirt roads. About three fifths of the rural population 6 years or older has never attended school (Central Bureau of Statistics 2004a).

Many studies have examined the relationship between geographical accessibility and development. However, most of the research focuses around improved accessibility through roads as a factor of economic growth. A focus on economic outcomes corresponds well with methods that evaluate road projects based on monetary costs and benefits. Although measuring social outcomes of investments on roads such as increase in school participation has generally remained peripheral in roads evaluation, recently a renewed emphasis in the development community has examined how and whether roads can help achieve social development. The social evaluation has been triggered, in part, by the realization that it is extremely difficult to achieve several millennium development goals, most of which are social in nature, requires first improving people’s accessibility.

This emphasis on the “social” is bringing about, or at least has the potential to bring about some major shifts in the way planners are devising interventions to improve accessibility level of households. First and foremost, it helps answer whether roads help attain social development such as accessing schools and health centers. Second, it lets us probe who benefits more from roads—girls or boys, poor or rich, high caste or untouchables, etc. Third, bringing the “social” in is also coincides with shift in the way outputs of transport interventions are being measured, such as from measuring some aspect of network size (for example, kilometers of roads per square kilometer of land) to the actual time it requires households to reach roads (Roberts, KC and Rastogi 2006).

Apart from the lack of roads that reflects the geographical dimension of inaccessibility, households also lack institutions that provide services within reasonable walking distances. Further, these geographical and institutional barriers to access operate together with several socio-economic barriers—such as gender, caste, ethnicity or religion based discrimination, poverty and low level of education. Figure 1.1 shows how the three kinds of accessibility barriers can overlap in relation to development outcomes.

Conceptually thus, the households and individuals which face the triple accessibility barriers are the most marginalized group when it comes to benefiting from development.

This dissertation develops this conceptual model as a framework for analyzing the impact of accessibility on school participation and applies it to the case of Nepal. Our analysis of the NLSS-II data shows that improved geographical accessibility—derived through both dirt and paved roads—has statistically significant and direct effect on the chances of children enrolling in school.

–  –  –

Should roads, a field that has generally been handled by economists, engineers and politicians interest sociologists? Economists ensure that the roads have enough economic returns so that investors are willing to invest. Engineers design and supervise the making of roads. Politicians are interested because the politics of bringing in road projects—at the international, national and regional levels—entails the possibility of exerting influence on the electorate. Is there any sociology of roads? To the least, is there any scope for such sociology? Do sociologists have any role in road making beyond the marginal role they are assigned in carrying out conventional socio-economic and environmental impact assessments?

The most obvious answer why there is room for sociology of roads is that roads have huge social returns, not only economic. The second answer is that no matter what length, what type, or for what purpose, when a road is built, social change is inevitable.



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