Global Journal of Human Social Science, E: Economics, Volume 22 Issue 7

According to Alkire-Foster (2007), the percentage of disempowered respondents ( ) H should be adjusted by the respondent’s average number of achievements. By implication, ck is defined as the disempowered censored vector so that if ( ) i c k < then ( ) 0 i c k = and if i c k ≥ then ( ) i i c k c = . Per the k p dual cutoff method, ( ) c k number of categories will always represent one of the disempowered respondents. If this assumption holds, respondents experience within the shared dimensions will be ( ) i c k d and ( ) A c k qd ′ = will be the average disempowered shared dimensions across the respondents. If we put emphasis on the disempowered, the final head count ratio which satisfies the properties of decomposability can be captured as 0 M HA = . Where 0 ( ; ) M y z is the adjusted head count ratio and it satisfies dimensional monotonicity. This is because with any additional dimension, A increases when a rural respondent is disempowered. iv. Computation of Women Empowerment Index (WEI) The WEI computation was done by following Alkire et al., (2013). WEI is a composite index used to measure the progress of women empowerment in a multidimensional context (The Hunger Project, 2014); and it compares women achievement as a factor of men’s achievement. WEI comprises of five key domains (5DE): Agency, Income, Leadership, Resources, and Time. WEI has two major components: Gender Parity Ratio (GPR) and Women Achievement Ratio (WAR). The GPR is a measure that compares women’s achievements to men within the same community while WAR measures women’s achievements based on some defined goals and targets (Alkire et al., 2013). As indicated earlier, scoring is major challenge in comparing women empowerment across different communities and countries. With WEI, the score is computed at the aggregate level to assess the overall level of women empowerment. The five domains (5DE) used in the computation is assigned equal weights. Each domain is assess by using two to three data points. Table 1 below present contextualized five domains and borrowed scoring from Alkire et al., (2013). Table 1: Five domains of women empowerment and their weights # Domains Indicators Weights 1 Agency • Decision making to hospital by women was used as a proxy against men. • Decision making on large household purchases by women was used as proxy against men. • Perception of violence against women 7 7 6 2 Income • With ownership over business/occupation, women’s personal business, works for family and other people was used as indicators. • Financial control was assessed by using control over earnings/income. 10 10 3 Leadership • Women membership in community discussion/groups was assessed by using ownership of house since such women will be members of landlord associations. • Confidence of being comfortable speaking in public was assessed with women’s ability discuss family planning with health workers. 10 10 4 Resources • Minimum number of prenatal care visits • Literacy rate 10 10 5 Time/Workload • Time spent to access to water (source of water) • For workload, type of cooking fuel was used as an indicator as well as division of household chores. 10 10 Source: Author’s Own Construct (July 2020) with adaptation of weights from Alkire et al., (2013) According to the Hunger Project (2014), the overall WEI can be computed as: 11 1 [(0.6 0.4 ) ] i i i i WEI WAR GPR weight = = × + × × ∑ However, this study adopted Alkire and Sabina et al (2012) methodology in estimating the overall WEI. Per their method, the WEI is estimated as: © 2022 Global Journals Volume XXII Issue VII Version I 3 ( ) Global Journal of Human Social Science - Year 2022 E Assessment of the Key Indicators and Dimensions of Women Empowerment in Rural Zambia