Julie Babinard , World Bank Kinnon Scott, World Bank

1. What Can Existing Household Surveys Tell Us about Gender and Transportation in Developing Countries? Julie Babinard, World Bank Kinnon Scott, World Bank

2. Transport, Development and Women • Access to affordable, reliable and safe transport is critical element for economic growth and poverty reduction • Transport planning typically not addressing differences in men and women travel needs • Social and economic roles of women: • Earnings opportunities (jobs, markets ) • Household and domestic work (Child-rearing; resources & food) • Access to social and health services

3. Women’s travel patterns and mobility constraints • Access to fewer transport choices • (Venter et al. 2007; Odufuwa 2007; Srinivasan 2002) • Spend more on transport • (Kamuhanda and Schmidt 2009; Srinavasan 2002) • Complex travel patterns • (Anand and Tiwari 2006; Odufuwa 2005; Abidemi 2002; Rosenbloom 1995; Malmberg-Calvo 1994; Hanson and Hanson 1980;) • Quality and security concerns • (Okoko 2007)

4. Knowledge and data gapsin gender and transport • Access to transport by women • Affordability • Journey length and reasons for travel • Quality of transport • How to fill in the gaps?

5. Data sources • “Stand alone” surveys of transport users or households • Costly to carry out • Often one-off (not part of any system of data collection in a country) • Urban • National household surveys • Many countries carry out a range of surveys • Comparable across time, or across countries • Can existing household surveys in developing countries inform transportation policy?

6. National Household Surveys • Variety of surveys are carried out • Selection criteria: • Frequency of implementation (across countries and across time) • Data collected at the individual level • Our assessment, a priori, of potential usefulness

7. National Household Surveys • Living Standards Measurement Study Surveys (LSMS) • Income and Expenditure /Household Budget Surveys (IES/HBS) • Demographic and Health Surveys (DHS) • Multiple Indicator Cluster Surveys (MICS

8. Living Standards Measurement Study Surveys (LSMS) • Goal  new, better quality data for public policy research on household behavior, household-policy interactions • Focus on welfare- (multi-topic) --causes • Data on individuals and households • Complementary data on community, prices, facilities

9. National Household Surveys • Living Standards Measurement Study Surveys (LSMS) • Income and Expenditure /Household Budget Surveys (IES/HBS) • Demographic and Health Surveys (DHS) • Multiple Indicator Cluster Surveys (MICS

10. Income and Expenditure/ Household Budget Surveys (IES/HBS) • Goal household expenditures, weights for consumer price indices, inputs for national accounts • Some demographics, education and employment data • Data are always collected at the household level • Some contain individual expenditure diaries. • Frequent: annually in Eastern Europe, every five years in other parts Latin America, for ex.

11. National Household Surveys • Living Standards Measurement Study Surveys (LSMS) • Income and Expenditure /Household Budget Surveys (IES/HBS) • Demographic and Health Surveys (DHS) • Multiple Indicator Cluster Surveys (MICS

12. Demographic and Health Surveys (DHS) • Goal data for policy on health, primarily maternal and infant health, fertility, family planning, nutrition, assets, education • Data at individual level and household level • Implemented systematically in many developing countries, multiple rounds • Comparable across countries and time

13. National Household Surveys • Living Standards Measurement Study Surveys (LSMS) • Income and Expenditure /Household Budget Surveys (IES/HBS) • Demographic and Health Surveys (DHS) • Multiple Indicator Cluster Surveys (MICS)

14. Multiple Indicator Cluster Surveys (MICS) • Goal monitor progress on the goals adopted at the 1990 World Summit for Children, look at children and their welfare, indicators • Includes topics such as nutrition, child health and mortality, literacy, child protection, etc. • Major international effort- over 100 countries, multiple rounds • Comparability across countries and some add-ons allowed

15. (1) Transport access and use • LSMS: community level data to paved and unpaved roads; existence of bus service • Caveat: not on individual preference or expenditure  Overall use or demand for individual transport cannot be determined • HBS/IES: individual expenditures on modes of transport; by rural and urban areas • Caveat: may have no disaggregation per trip type or number of trips taken • Inability to assess mode shares and individual demand as (a) costs related to mode use are aggregated ; (b) movements with no immediate expenditures not recorded (walking; bicycle) and (c) expenditures not equal to trips (private vehicles)

16. (2) Transport affordability • HSB/IES: Individual expenditure data by male and female on transport; type of mode used; number of trips • Caveat: Specific data on number of trips is not always available unless collected in specific individual diaries/’open’ questionnaires  No conclusion can be drawn on whether one form of transport is more or less expensive for men or women

17. (3) Journey length and reasons for travel • LSMS: Individual data on mode of transport, trip purposes and costs for access to education and health facilities, labor-related activities (but not necessarily across countries)  individual data allows disaggregation of data according to gender and provides reasons for not using health care (distance; lack of transport as options) • DHS: individual data on reasons for not using health care (distance; lack of transport as options) opportunities for geo-referencing with national surveys • MICS: Types of transport and mode owned and used for accessing social and economic activities (education; domestic and household chores – water & food) • Caveat: mainly household data available • Opportunity for custom-questionnaire and questions on reasons for not attending school; not registering children’s birth (distance and travel time as options)

18. Conclusions • The four survey types provide some information on transport access, affordability, trip purposes • No information on quality or safety • Benefits of the four survey types • National level data sets • Ability to link transport use with welfare status, human capital • Ability to track changes over time for specific groups • Not a substitute for transport specific surveys

19. Recommendations • Incorporate additional questions to surveys with focus on gender and transport • Systematize questions as much as possible (International Household Survey Network) • Seek IES/HBS data that is disaggregated by expenditure • Investigate existing data sources before designing full transport survey

20. Additional resources • LSMS http://www.worldbank.org/lsms/ • IES/HBS http://www.measuredhs.com • MICS http://www.unicef.org/statistics/index_24302.html http://www.childinfo.org/mics3_surveys.html

21. Brazil: Type of expenditure by women and men, Brazil (% of men and women that made each type of expenditure per week) Source: POF 2002/2003, calculations by authors

22. Mode of Transport to School: Panama 2003 Source: Encuesta de Niveles de Vida,calculations by authors