The link between trade and development has been widely established. However, there is mounting evidence that women and men have different opportunities to access and operate in e.g. local markets. Therefore, there is a need to strengthen the empirical- as well as the analytical dimensions in the area of gender and trade. This paper aims to contribute to the understanding of the trading patterns of farming women and men in Ethiopia - a country that relies on agriculture for the mainstay of its economic structure and export and employs the majority of the population. The focus of my analysis is to ascertain whether and how there any variations in the trading patterns of farming women and men (frequency, type, specialization, etc? Are there variations in women and men’s use of resources (social and natural) in their trade? In concluding, I develop typologies of trading identities and analyze the gendered dimensions of these. Finally I relate the findings to the broader issue of rural women and men’s access to rural resources.
I take concrete market places as my point-of-departure. To perform the analysis, empirical data from two formal surveys undertaken in the Ambo Woreda during March-May 2006 are used - one village survey addressing a probability sample of farmers in four villages (n=464), and one market survey undertaken in three markets of differing sizes (n=144) (one village market, one “bigger” market, and the “regional market”). The units of analyses are primarily the categories of “women” and “men” but an intersectional perspective (Lykke 2003; Darvishpour 2006) is taken as well, open to the analysis of locally relevant categories, i.e. household-headship, age and education. To broaden, deepen and blend the analysis, qualitative data gathered in the area over the period 1996-2006 are employed as a complement. The Statistical Package for the Social Sciences (SPSS) software version 14.0 is used to perform the analyses, using primarily descriptive statistics. In those cases where variance between groups have been analysed, one-way ANalyses Of VAriance (ANOVA), post-hoc tested with Fisher’s Least Significant Difference (LSD), are used.