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DATA FOR AGRICULTURAL STUDIES

(Item 4 of the Agenda)

Consideration of gender variables in the analysis of food and agriculture sector data

19. Jariah MASUD, Associate Professor, Department of Resource Management and Consumer Studies, University of Putra Malaysia indicated that the final goal of development was to improve the quality of life of the population and said that, although much already had been achieved, gender inequality still persisted. As examples, she cited the prevalence of the feminization of poverty, increased incidence of HIV/AIDS, increased violence against women, human trafficking, all of which reflect gender inequality.

20. She pointed out that in most developing countries the feminization of poverty and agriculture was of concern while women's role in agriculture remained unaccounted for owing to a lack of adequate concepts, methods of measurement, data collection and interpretation. Ms Masud noted that gender disaggregated data were available from censuses and provided trends and an overview of men's and women's roles in the food and agriculture sector. However, she said that not much was known about the roles of women and men in food and agriculture due to lack of gender disaggregated data at community and household levels and that such information could form part of the basis for the development of sustainable food and agriculture sector programmes.

21. Ms Masud pointed out that gender analysis skills could enhance the capability of producers and users of food and agriculture data to identify the information gaps when designing sustainable development programmes to eliminate gender inequality, to empower women and to increase the well-being of both men and women in line with the achievement of the MDGs.

22. Gender-disaggregated data were important, she said, to assess the impact of development on women and men, and girls and boys. Such data were a prerequisite to the integration and mainstreaming of gender concerns in the planning, needs assessment, monitoring and evaluation of food and agriculture programmes.

23. In line with these considerations, the Experts recommended the conduct of time use studies in order to supplement the gender-disaggregated data from censuses used in the analysis of the gender dynamics, relations and connections in communities, but agreed that collection of data on the activities (independent of the time involved) that women do would also be helpful and should be considered as a higher priority than data on time use.

The crop monitoring system of the food security information system

24. Mr Nampoothiry, Economic and Statistical Adviser, Directorate of Economics and Statistics, Ministry of Agriculture, Government of India, spoke about the crop monitoring system of the food security information system. He informed the Experts that crop monitoring was an essential component of the food security information system. The timely supply of reliable agricultural sector statistics to planners and policy-makers assumed vital significance in the context of policies and programmes aimed at increasing production, better distribution and assured food security. Equally important was nutrition security, which implied not just assured food availability, but also the actual food intake with the prescribed minimum dietary energy required for maintaining a healthy and active life.

25. The Experts learned that in India the crop monitoring system consisted of advance estimates, final estimates and fully revised estimates. Advance Estimates (AEs) were based on diverse sources like data furnished by Agriculture Departments and Bureaus of Economics and Statistics from sub-national governments (States and Union Territories), inputs from weekly crop weather watch group meetings, remote sensing and crop directorates located in states. The first AE gives production figures for kharif (crop season coinciding with south-west-monsoon during June - September) cereals, pulses, oilseeds and other commercial crops, viz. cotton, jute, mesta and sugar cane. This estimate was followed by the second AE covering both kharif and rabi (crop season covering the period October to March) crops including wheat (a major rabi crop), pulses and oilseeds. The second AE was released in December/January. The third and fourth AEs covering both kharif and rabi crops were released in March/April and June/July, respectively, of the following year. Since not all data gaps were filled at the time of AEs, they were followed by final and fully revised estimates in December of the first succeeding agricultural year (July - June) and the second succeeding agricultural year, respectively.

26. Major limitations in the current system of crop monitoring, particularly with reference to the food security information system, had been noted. These limitations included delays arising from release of a large number of estimates, variations between estimates, perceived deterioration in quality of area and yield estimates which formed the basis of production estimates and resulting erosion in utility of data for policy formulation and decision-making.

27. The Experts recognized the need to improve the quality of available crop information to promote crop diversification, which could lead to an increase in the value of farmer's production without adversely affecting food and nutrition security. It might even be desirable to put in place a crop monitoring system designed to enable a farmer to obtain timely and reliable facts and figures on agriculture not only of his/her own country but of other countries as well. This information would promote the farmer's global competitiveness.

28. Based on these considerations, the Experts recommended that the existing system of crop monitoring should be improved with a view to enhancing its utility as an effective component of the food security information system. In this respect, the use of additional sources of data, such as farmer appraisal surveys and remote sensing applications, should be explored. In this way, the reliability of advance estimates might be enhanced without corresponding increases in costs through expanded crop cutting surveys for yield estimation and additional staff for area enumeration.


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