assets, wealth and spousal violence: insights from ecuador and ghana
DESCRIPTION
Assets, Wealth and Spousal Violence: Insights from Ecuador and Ghana. Abena D. Oduro, University of Ghana Carmen Diana Deere, University of Florida Zachary Catanzarite , University of Florida Prepared for the World Bank Workshop on Gender and Assets June 14 2012. Introduction. - PowerPoint PPT PresentationTRANSCRIPT
Assets, Wealth and Spousal Violence: Insights from Ecuador and Ghana
Abena D. Oduro, University of GhanaCarmen Diana Deere, University of FloridaZachary Catanzarite, University of Florida
Prepared for the World Bank Workshop on Gender and Assets
June 14 2012
Introduction
• Numerous studies investigate factors that might increase women’s bargaining power and reduce the risk of abuse.
• Very few have considered the relationship between women’s asset (i.e. land and home)ownership and spousal violence– Women’s homeownership deters physical and psychological
abuse (Panda and Agarwal 2005, Bhattacharrya et al 2011)– Evidence on association of spousal abuse and women’s land
ownership is mixed (Bhattacharyya et al 2011, Ezeh and Gage 2000, Panda and Agarwal, 2005,)
Introduction (contd.)• This study adds to the growing literature on spousal abuse in
two ways:– It considers ownership of a wider range of assets, i.e. agricultural
land, home ownership and ownership of other real estate such as another residence, commercial building and non-agricultural plot.
– It investigates women’s ownership of assets relative to their partners.• Places emphasis on relative value of women’s assets as a measure of
their fall back position• Controls for the fact that different assets may impact bargaining power
differently.• Allow us to determine whether the preventive impact of women’s share
of couple wealth varies along the wealth distribution
Context
Ecuador• Population: 14.7 million• HDI rank: 83• Law Against Domestic
Violence Towards Women and the Family (1995)
Ghana• Population 25 million• HDI rank: 135• Domestic Violence Act
(2007)
Survey Instrument• Designed to be similar in several respects.– Two sections
• Household asset inventory• Individual questionnaire completed by 2 respondents in the household.
• Domestic Violence Module in Individual Questionnaire- Respondents were asked:– How common domestic violence was in their community or
neighbourhood?– Whether they had been abused physically, verbally or
psychologically in the past year– Who the perpetrator(s) of the abuse was
The DataEcuador
• EAFF-Ecuador Household Asset Survey conducted in 2010
• 2,892 Households• Two-stage sampling procedure• Sample size for this study:
1,938 partnered women –married or in a consensual union, resident in the same household with their partner and who both responded to the individual questionnaire
Ghana• GHAS-Ghana Household Asset
Survey conducted in 2010• 2,170 Households• Two-stage sampling procedure• Sample size for this study: 886
partnered women – married or in a consensual union, resident in the same household with their partner and who both responded to the individual questionnaire
Incidence of Spousal Violence During Previous 12 months (Currently partnered women aged
18-49 years)Type of Abuse
Ecuador(2010)
Ecuador(2004)
Ghana(2010)
Ghana(2008)
N= 1,938 N=6,138 N = 886 N=1,039
Physical 3.3% 10.1% 2.1% 17.4%
Emotional 17.7% 14.7% 11.2% 30.3%
Sexual - 3.4% - 5.1%
Any form of abuse
18.1% 17.4% 12.0% 35.1%
Notes: *Categories are not mutually exclusive. Percentages are weighted by the sample expansion factors. Sources: For Ecuador, derived from the data set for ENDEMAIN 2004 available at www.cepar.org.ec/endemain_04/nuev (accessed January 10, 2012). For Ghana, derived from the data set for Ghana Demographic and Health Survey 2008 available on request at www.measuredhs.com/data/dataset/Ghana_Standard-DHS_2008 (accessed March 9, 2012).
The Models
• The Dependent variables:– Physical violence in past 12 months– Emotional violence, i.e. verbal and psychological abuse, in
past 12 months• Variable of Interest- Women’s asset ownership
measured as:– Women’s ownership of any of the following real estate:
agricultural land, place of residence, other real estate . Categorical variable that takes a value of 1 if owner, 0 if not
– Women’s share of couple’s gross value of physical and financial wealth- continuous variable ranging from 0 to 1.
Other Explanatory Variables• Characteristics of the Woman
– Age, education and number of children aged under 13 years• Characteristics of the Couple
– Age difference, difference in years of education, employment status relative to spouse, woman’s report of earnings relative to spouse
• Nature of the Relationship– Type of union (i.e. married or in a consensual union), occurrence of financial
disagreements in past 12 months• Household Context
– Socioeconomic status of household- gross value of assets, crowding, location• Community Context
– Woman’s perception of the frequency of domestic violence in the community
DescriptivesEcuador Ghana
N=1,938 N=886
Woman a Major Asset Owner (Percent) 54.5 21.8
Female share of Couple Wealth (Mean, percent) 46.8 23.2
Woman’s Age (Years) 41.27 39.24
Spousal Age difference (Years) 4.09 7.95
Woman’s Years of Schooling 8.17 4.51
Spousal Schooling Difference (Years) 0.38 1.76
Consensual Union (Percent) 35.4 13.3
Polygamous Marriage (Percent) - 11.2
Financial Disagreements (Percent) 15.1 13.3
Both Employed (Percent) 58.2 85.6
Woman Reports both Earn about the Same (Percent) 18.0 3.8
Sources: EAFF (2010); GHAS (2010)
Methodology• Logistic regression
– Physical abuse– Emotional Abuse
• Baseline model:– Includes all explanatory variables except variable of interest.
• Model I: – Adds woman’s ownership of asset variable to the baseline
• Model II: – Adds woman’s share of couple wealth to the baseline
• Model III:– Adds woman’s share of couple wealth plus interaction of woman’s share
of couple wealth and household wealth categories
Logistic Regression Results for Physical Violence
Ecuador (N=1938) Ghana (N=886)
Model Variables Coefficient (OR) Standard Error Coefficient (OR) Standard Error
I Woman Owns Real Estate -0.177 (.838) 0.295 -0.064(.0.937) 0.847
Likelihood Ratio Chi-Squared (df) 52.971 (18)*** 27.17(16)**
Pseudo-R squared 0.086 0.200
II Share of Couple Wealth -2.766**(0.063) 1.397 -3.91 (.019) 4.282
Share of Couple Wealth Squared 2.210 (9.113) 1.415 5.63 (279.81) 5.26
Likelihood Ratio Chi-Squared (df) 57.096 (19)*** 28.13(17)**
Pseudo-R squared 0.093 0.2075
III Share of Couple Wealth -2.293*** (0.101) 0.932 -7.498(0.0005) 6.692
Share of Wealth*Tertile 2 1.793 (6.009) 1.1868 5.288 (197.97) 7.590
Share of Wealth*Tertile 3 2.957**(19.234) 1.354 10.982 (58864.88) 6.912
Likelihood Ratio Chi-Squared (df) 59.775(20)*** 33.07(18)***
Pseudo-R squared 0.097 0.243
The Odds Ratios of Physical Violence and Women’s Share of Couple Wealth by Tertile, Ecuador and Ghana
Other Significant Explanatory Variables
Ecuador• Financial Disagreements
(+)• Report of Community
Violence(+)• Employment: Man is
employed, she is not (-) (Reference: both are working)
• Ghana• Financial Disagreements
(+)• Age of Woman (-)• Years of education of
woman (- )
Logistic Regression Results for Emotional Violence
Ecuador Ghana
Model Variables Coefficient (OR) Standard Error Coefficient (OR) Standard Error
I Woman Owns Real Estate -0.140 (0.869) 0.1753 -0.687*(0.502) 0.379
Likelihood Ratio Chi-Squared (df) 137.939 (18)*** 104.98 (18)***
Pseudo-R squared 0.095 0.197
II Share of Couple Wealth -0.451(0.637) 0.899 -2.64 (0.071) 1.828
Share of Couple Wealth Squared 1.051(2.862) 0.846 1.969 (7.168) 2.384
Likelihood Ratio Chi-Squared (df) 143.269 (19)*** 105.90(18)***
Pseudo-R squared 0.099 0.198
III Share of Couple Wealth 1.200**(3.321) 0.521 0.859 (2.36) 1.313
Share of Wealth*Tertile 2 -0.580(.560) 0.692 -4.556**(0.01) 1.916
Share of Wealth*Tertile 3 -1.224*(0.294) 0.745 -1.502(0.222) 1.608
Likelihood Ratio Chi-Squared (df) 144.437 (20)*** 111.9(20)***
Pseudo-R squared 0.100 0.210
The Odds Ratio of Emotional Violence and Women’s Share of Couple Wealth by Tertile, Ecuador and Ghana
Other Significant Explanatory Variables
Ecuador• Financial Disagreements
(+)• Perceptions of
community violence (+)• Urban location (+)• Earnings: Woman earns
more than partner (+)
Ghana• Financial Disagreements
(+)• Perceptions of
community violence (+)• Urban location (-)• Polygamous union (-)
Discussion
• Asset variables behave differently across models and between the two countries.– Being an asset owner has a significant and negative
effect in Ghana for emotional abuse– In Ecuador woman’s share of couple wealth has a
significant deterrent effect on physical abuse. – In Ghana woman’s share of couple wealth has a
significant deterrent effect for emotional abuse only. • Context Matters.
Discussion contd.
• The deterrent effect of women’s share of wealth depends on the socioeconomic status of the household. Women in different socio-economic strata face different risks.
• Ecuador:– Woman in lowest third of household wealth with zero share
of couple wealth is predicted to be at risk from physical abuse but is buffered from emotional abuse.
– However, when she increases her share of couple wealth predicted likelihood of physical abuse declines whilst likelihood of emotional abuse rises.
Discussion contd.• Predictors of both types of abuse:– Both countries:
• Financial disagreements• Perception of community violence
• Deterrents: – Ecuador:
• Only male is employed, reduces likelihood of physical abuse• Man’s years of schooling exceeds that of partner reduces likelihood of
emotional abuse– Ghana:
• Age, Years of schooling of woman reduces physical violence• Polygamous marriage reduces emotional violence
Thank you for your attention