capabilities: circularity analysis in sen’s development...
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S3H Working Paper Series
Number 05: 2017
Domestic Violence and Woman’s Functional
Capabilities: Circularity Analysis in Sen’s
Development Framework
Mahnoor Ibad
Saeeda Batool
November 2017
School of Social Sciences and Humanities (S3H) National University of Sciences and Technology (NUST)
Sector H-12, Islamabad, Pakistan
S3H Working Paper Series
Faculty Editorial Committee
Dr. Zafar Mahmood (Head)
Dr. Najma Sadiq
Dr. Sehar Un Nisa Hassan
Dr. Samina Naveed
Ms. Nazia Malik
S3H Working Paper Series Number 05: 2017
Domestic Violence and Woman’s Functional
Capabilities: Circularity Analysis in Sen’s
Development Framework
Mahnoor Ibad
Graduate, School of Social Sciences and Humanities, NUST Email: [email protected]
Saeeda Batool Assistant Professor, School of Social Sciences and Humanities, NUST
Email: [email protected]
November 2017
School of Social Sciences and Humanities (S3H) National University of Sciences and Technology (NUST)
Sector H-12, Islamabad, Pakistan
iii
Contents
Abstract v
1. Introduction
1.1 Objectives of the Study
1
2
2. Literature Review
2.1 Literature Gap
3
4
3. Analytical Framework
3.1 Theoretical Framework
3.2 Empirical Model
4
5
6
4. Data and Description of Variables
4.1 Assigning Weights to the Capabilities
7
8
5. Results, Estimation Technique and Discussion
5.1 Simultaneous Equation Model and Estimation Technique
5.2 Results
5.3 Interpretations
9
9
9
12
6. Conclusion and Policy Implications
6.1 Conclusion
6.2 Policy Implications
15
15
16
7. References 16
8. Appendix 29
v
Abstract
This research investigates circularity/simultaneity between domestic violence and women capabilities based upon Sen’s
theory of capabilities approach. Multidimensional indexes of women functional capabilities are formed by using
normative, equal and data-driven weighting schemes. Purpose to construct different weighting indexes is to analyze
consistency of circularity analysis. Current study uses recent most data from Pakistan Demographic and Health Survey
for time period 2012-13.The results of three stage simultaneous equations models showed that circularity does exist
between domestic violence and women socio-economic capabilities in all weighting schemes. However results obtained from
data-driven approach is not much consistent with theory and other weighting schemes. Thus weights assigned to the
capabilities must be theoretically proved.
Key Words: Sen’s capabilities approach, domestic violence, women capabilities, circularity, multidimensional indexes.
1
Introduction
Women empowerment is the key component of economic growth and development. Formal
appearance of the terminology “empowerment” occurs after feminist movement at Global South [Sen
& Grown, 1988].Feminist researchers believed that men and women play different role in third world
countries and each have dissimilar wellbeing needs, thus highlighted the importance of women in
economic development [Moser, 1989]. From past few decades international organizations have been
focusing on women empowerment [Grabe, 2012]. United Nation’s developmental goals are based
upon gender equality and women empowerment (MDG’s goal 3 and SDG’s goal 5).There are many
monetary and non-monetary constraints which are making these developmental goals difficult to
achieve. Mostly focus is paid on monetary impediment factors for example budget deficit and lack of
investment [Schmidt-Traub & Shah, 2015]. However non-monetary constraints to women related
developmental goals are also important to study especially in developing countries.
Domestic violence is a non-monetary constraint and is considered to be the major obstacle in
achieving these goals [Semahegn & Mengistie, 2015]. In Pakistan “thirty-two percent of ever-married
women age 15-49 have experienced physical violence at least once” [PDHS 2012-13].
Interrelationships between women capabilities (economic and social) and domestic violence can be
studied in context of Sen’s theory of capabilities approach1. Capabilities are defined as set of valuable
functionings and freedom to achieve them, which depends upon individual factors, social and
environmental conditions [Sen 1984, 1985a, b, 1992].
Since capability is defined as freedom to function, domestic violence damages this freedom
and can be seen as an important conversion factor i.e. social influence [Agarwal & Panda, 2007; Kaur
& Garg, 2008].
There is an open debate in Sen’s capabilities approach regarding capabilities measurement
[Sen, 1985]. Nussbaum [2005] followed Sen’s approach of capabilities and provided a list of important
capabilities that is essential for every human to achieve. Robeyns [2005] opposed Nassubum’s list of
capabilities and called them too common for analysis, he himself postulate the criteria for capabilities
selection. Muffel & Heady [2013] measured capabilities by taking individual’s stocks of economic,
social and psychological capital. Capability is a multidimensional concept that can’t be studied by
observing a single indicator thus there is a need to develop multidimensional indexes constructed
through data-driven, equal and normative weighting schemes [Greco, 2016].
1 Women empowerment is measured by taking women economic capital, social capital and her justification of domestic violence thus interrelationships cannot be studied.
2
Previous studies tried to capture relationship between domestic violence and capabilities by
selecting a particular functioning mainly women employment. Literature shows simultaneous
relationship between domestic violence and women capabilities. One direction of relationship, namely,
the impact of domestic violence on women functioning of employment2 [Bhattacharya, 2015]. Other
direction of relationship is influence of women capabilities on her incidence of domestic violence.
Household bargaining theory suggests that capabilities give bargaining power to women that helps
them to combat domestic violence [Gibson-Davis et al., 2005]. Male backlash theory proposes that
male perceives women increasing capabilities as a threat to their supremacy which they retaliate by
committing violence [Lenze & Klasen, 2016]. Binder & Coad (2011) called this simultaneity a
“circularity problem” in Sen’s capabilities approach because there is entanglement between set of
functionings (capabilities) and social conversion factor3 (domestic violence).
Existing studies address domestic violence and Sen’s capability approach by selecting any
specific functioning. The concept of circularity in Sen’s capabilities approach is never been studied
empirically for Pakistan, this study will fill this literature gap. Research aims to adopt the model of
Amrtya Sen’s capability approach and use it precisely for Pakistan. The data will be taken from latest
Pakistan Demographic and Health Survey (2012-13). To form women capabilities a composite index
will be formed using normative, equal and data-driven approach of weighting schemes. Our study will
incorporate a set of women functional capabilities and then compare them with domestic violence
along with other factors to examine the circularity in Sen’s capabilities approach.
1.1 Objectives of the study
Following are the objectives of our study:
To construct functional capabilities index of women by assigning different kinds of weights
(equal, normative and PCA).
To empirically investigate circularity in Sen’s capabilities approach using domestic violence
and women capabilities.
To empirically examine how change in weighting schemes change the circularity empirics.
2 Most of the researchers have taken a single functioning, mainly employment or decision making abilities to study this relationship. 3 Individual achieve functionings through conversion of resources that are constrained upon social, individual and environment conversion factors (Sen, 1985). Domestic violence is a social conversion factor because society’s cultural practices sets precedence to withstand it (Kaur & Garg, 2008).
3
2. Literature Review
In this section a brief literature related to the study is discussed along with the literature gap.
Anand et al. (2005) empirically tested Sen’s capabilities approach for British using secondary
data for year 2000. Instrumental variable technique and Generalized Moment of Method estimators
were used to empirically test the findings. Study concluded that capabilities do matter for human
well-being, some are more important while some are less. However circular relationships were found
between resources, capabilities and conversion factors. Functioning at one period of time may be
treated as conversion factor at another time period e.g. health.
Gibson-Davis et al. (2005) studied the effect of employment on domestic violence in USA
using 2-stage least square method. Study discusses two types of welfare programs that can decrease
domestic violence through poverty alleviation and increase in labor force participation. Study
concluded that increase in employment of single mothers is one way to decrease domestic violence.
Moreover results were consistent to exchange theory of psychology and bargaining theory of
economics.
Binder and Coad (2011) empirically examine the co-evolution between functionings, resources
and conversion factors using VAR estimation technique for Great Britain from the period of 1991 to
2006. According to them there is a circularity problem between functionings, resources and
conversion factors in Sen’s capability approach i.e. a resource of one period could be a functioning in
other period. They use time leads and lags of functionings, resources and conversion factors and find
coevolution that separate interplay between them. Conclusion of their study shows that income is an
important resource to function but also an important functioning that is “being happy”.
Muffels and Headey (2013) empirically tested “capabilities choice events” impact on long term
objective and subjective wellbeing measured by life satisfaction, relative income and employment for
German and British. The study covers the data of 25 years (1984-2008) for German and 18 years for
British (1991-2008) and uses GLS panel regression. Capabilities were measured by taking individual’s
stock of economic, cultural, social and psychological capital. Study shows a significant support for
functionings and capabilities approach. People’s income and employment security results into long-
term wellbeing. People with more capabilities will be much satisfied from their lives and these
capabilities are reflected by their socio-economic, psychological and culture capital which eventually
result into their capabilities to maintain income and employment security.
4
Bhattacharya (2015) studies the impact of domestic violence on women employment for India,
using instrumental variable technique for the year 2005-06. Study concluded that women experiencing
domestic violence are more likely to be employed because victim women favors to spend much lesser
time with their husbands. Moreover women experiencing spousal violence have less control over their
earnings which indicates financial exploitation of women from employment.
Greco (2016) measured capabilities of Malawi women using Sen’s capabilities approach. The
multidimensional index of capabilities were formed by using four weighting schemes; data-driven,
hybrid method, equal and normative approach. Result shows that equal and normative weights are
highly correlated, while data-driven is most different from equal weighted system. All capabilities are
equally important however results obtained from normative weighted criteria is better because it allows
value judgments of people.
Lenze and Klasen (2016) analyzed the impact of women work participation on domestic
violence. Instrumental variable technique was used to empirically test the findings for Jordan for the
period of 2007. Study concluded that without taking endogeneity in to account, increase in women
employment status has a significant positive impact on domestic violence, supporting male backlash
theory. However relationship appears to be insignificant after taking endogeneity into account.
2.1 Literature Gap
After literature review we come up to the point that different researchers explain different
application of capabilities approach and use different methods to measure the capabilities. Moreover
other part of the literature review tries to capture the relationship between domestic violence and
women employment which is an important capability. Circularity between domestic violence and
women functioning (employment mainly) does exists as both can be treated as dependent variable.
None of the study tries to measure women functional capabilities using different weighting
schemes and empirically found its circular relationship with domestic violence especially for Pakistan.
Therefore, a major contribution of our study is to fulfill this gap in the framework of Sen’s capabilities
approach and to analyze whether different weighting schemes change the circular relationship or not?
3. Analytical framework
In this section theoretical and empirical framework of Sen’s capabilities approach will be
discussed in detail.
5
3.1 Theoretical framework
This study adopted theoretical model of Amrtya Sen’s capabilities approach. Capabilities are
defined as set of valuable functionings that are different “beings” and “doing” of a person. Freedom
to achieve these functionings in the presence of social, environmental and individual constraints
depicts person’s well-being and development. In equation form set of functionings can be written as:
𝒃𝒊 = 𝒇𝒊 {𝒄(𝒙𝒊)|𝒛𝒊, 𝒛𝒆, 𝒛𝒔} 𝒙𝝐𝑿
where,
X = vector of commodities out of set of all probable commodities
𝑥𝑖 = individual i’s vector of commodities.
C (.) = Function that converts 𝑥𝑖 (commodities) into vector of characteristics whereas c=c (𝑥).
𝑓𝑖 = Function that converts vector of characteristics into functionings.
Z’s = possible conversion factors.
An individual faces such non-monetary constraints through these conversion factors.
𝑧𝑖 = individual conversion factor.
𝑧𝑒 = environmental conversion factor.
𝑧𝑠 = social conversion factor.
Since capabilities are set of functionings, thus above model can be written as:
𝑸𝒊(𝑿𝒊) = {𝒃𝒊|𝒃𝒊 = 𝒇𝒊(𝒄(𝒙𝒊)|𝒛𝒊, 𝒛𝒆, 𝒛𝒔)∀ 𝒇𝒊 ∈ 𝑭𝒊 𝜦 ∀ 𝒙𝒊 ∈ 𝑿𝒊 }
𝑸 = {𝒇(𝒄(𝒙)}
Commodities can be apprehended as characteristics which is similar for all individuals.
Individuals are different in terms of capabilities because each have different conversion function 𝑓𝑖
which converts commodity’s characteristics into functionings. This conversion depends upon
individual, environment and social factors.
In our analysis we are concerned about women capabilities that is her set of functionings.
Variables used are depicting one’s functionings e.g. “being employed”, “being educated”, thus focus
is paid only upon the functionings, not on how commodities gets converted into characteristics. The
major social constraint used in our analysis is domestic violence, rest constraints will be included in
individuals, household and husband’s set of control variables.
Binder & Coad (2011) explored circularity problem in Sen’s capabilities approach because of
the entanglement of conversion factors and set of functionings (capabilities). As discussed above that
6
conversion factor like domestic violence has an impact on capabilities and on other hand capabilities
do influence incidences of domestic violence. Hence theoretically endogeneity between the concepts
has been authenticated, empirically this will be tested by applying econometric techniques and models.
3.2 Empirical model
Following Sen (1983, 1984, 1985a, b, 1992, 1999), this study also incorporates capability set
and conversion factors. In order to analyze the circular relationship between conversion factor
(domestic violence) and capabilities (set of economic functionings and social functionings) we will add
some new variables in our model as well, which shows relationship with capabilities. The capability
set of theoretical model will be replaced by women capability index which we will calculate by
incorporating economic social and capital separately in our capability set [Muffel & Heady, 2013].
Individual conversion factor will be included in the set of control variables of woman,
domestic violence is treated as social conversion factor and environmental conversion factors will be
included in the set of household control variables. Husband related control variables will also be
included in the model. Other related variables according to the study will be included in different sets
of control variables.
In order to check circularity between domestic violence and women capabilities in light of
Sen’s capabilities approach a three equation system simultaneous equation model is formed. The
empirical equation can be written as:
E𝑐𝑜𝑛𝑜𝑚𝑖𝑐 𝑐𝑎𝑝𝑖𝑡𝑎𝑙𝑖 = 𝛼10 + 𝛼12 𝐷𝑜𝑚𝑒𝑠𝑡𝑖𝑐 𝑣𝑖𝑜𝑙𝑒𝑛𝑐𝑒𝑖 + 𝛼13𝑆𝑜𝑐𝑖𝑎𝑙 𝑐𝑎𝑝𝑖𝑡𝑎𝑙𝑖 + 𝛽11𝑊𝑜𝑚𝑎𝑛 𝑎𝑔𝑒𝑖 +
𝛽12𝑊𝑜𝑚𝑎𝑛 𝑜𝑐𝑐𝑢𝑝𝑎𝑡𝑖𝑜𝑛𝑖 + 𝛽13𝐻𝑢𝑠𝑏𝑎𝑛𝑑 𝑒𝑑𝑢𝑐𝑎𝑡𝑖𝑜𝑛𝑖 + 𝛽14𝑅𝑒𝑙𝑎𝑡𝑖𝑣𝑒 𝑒𝑎𝑟𝑛𝑖𝑛𝑔 𝑡𝑜 ℎ𝑢𝑠𝑏𝑎𝑛𝑑′𝑠𝑖 +
𝛽15𝐼𝑛 − 𝑙𝑎𝑤𝑠 𝑣𝑖𝑜𝑙𝑒𝑛𝑐𝑒𝑖 + 𝛽16𝑌𝑒𝑎𝑟𝑠 𝑜𝑓 𝑚𝑎𝑟𝑟𝑖𝑎𝑔𝑒𝑖 + 𝛽17𝑊𝑜𝑚𝑎𝑛 𝑤𝑜𝑟𝑘𝑒𝑑 𝑏𝑒𝑓𝑜𝑟𝑒 𝑚𝑎𝑟𝑟𝑖𝑎𝑔𝑒𝑖 +
𝛽18𝐶ℎ𝑖𝑙𝑑𝑟𝑒𝑛𝑖 + 𝜀𝑖
D𝑜𝑚𝑒𝑠𝑡𝑖𝑐 𝑣𝑖𝑜𝑙𝑒𝑛𝑐𝑒𝑖 = 𝛼20 + 𝛼21𝐸𝑐𝑜𝑛𝑜𝑚𝑖𝑐 𝑐𝑎𝑝𝑖𝑡𝑎𝑙𝑖 + 𝛼23𝑆𝑜𝑐𝑖𝑎𝑙 𝑐𝑎𝑝𝑖𝑡𝑎𝑙𝑖 +
𝛽21𝐻𝑢𝑠𝑏𝑎𝑛𝑑 𝑑𝑟𝑖𝑛𝑘 𝑎𝑙𝑐𝑜ℎ𝑎𝑙𝑖 + 𝛽22 𝑅𝑒𝑎𝑙𝑎𝑡𝑖𝑣𝑒 𝑎𝑔𝑒𝑖 + 𝛽23𝐻𝑢𝑠𝑏𝑎𝑛𝑑 𝑒𝑑𝑢𝑐𝑎𝑡𝑖𝑜𝑛𝑖 +
𝛽24𝑅𝑒𝑙𝑎𝑡𝑖𝑣𝑒 𝑒𝑎𝑟𝑛𝑖𝑛𝑔 𝑡𝑜 ℎ𝑢𝑠𝑏𝑎𝑛𝑑′𝑠𝑖 + 𝛽25𝐼𝑛 − 𝑙𝑎𝑤𝑠 𝑣𝑖𝑜𝑙𝑒𝑛𝑐𝑒𝑖 + 𝛽26 𝑊𝑒𝑎𝑙𝑡ℎ 𝑖𝑛𝑑𝑒𝑥𝑖 +
𝛽27𝑅𝑒𝑠𝑖𝑑𝑒𝑛𝑐𝑒 𝑡𝑦𝑝𝑒𝑖 + 𝛽28𝑆𝑜𝑛𝑠𝑖+𝛽29𝐻𝑢𝑠𝑏𝑎𝑛𝑑 𝑜𝑐𝑐𝑢𝑝𝑎𝑡𝑖𝑜𝑛𝑖 + 𝛽20𝑌𝑒𝑎𝑟𝑠 𝑜𝑓 𝑚𝑎𝑟𝑟𝑖𝑎𝑔𝑒𝑖 + 𝜀𝑖
S𝑜𝑐𝑖𝑎𝑙 𝑐𝑎𝑝𝑖𝑡𝑎𝑙𝑖 = 𝛼30 + 𝛼31𝐸𝑐𝑜𝑛𝑜𝑚𝑖𝑐 𝑐𝑎𝑝𝑖𝑡𝑎𝑙𝑖 + 𝛼32𝐷𝑜𝑚𝑒𝑠𝑡𝑖𝑐 𝑣𝑖𝑜𝑙𝑒𝑛𝑐𝑒 + 𝛽31𝑊𝑜𝑚𝑎𝑛 𝑎𝑔𝑒𝑖 +
𝛽32𝑊𝑜𝑚𝑎𝑛 𝑜𝑐𝑐𝑢𝑝𝑎𝑡𝑖𝑜𝑛𝑖 + 𝛽33𝑊𝑜𝑚𝑎𝑛 𝑎𝑔𝑒 𝑎𝑡 𝑚𝑎𝑟𝑟𝑖𝑎𝑔𝑒𝑖 + 𝛽34𝐸𝑙𝑒𝑐𝑡𝑟𝑖𝑐𝑖𝑡𝑦𝑖 +
𝛽35𝐻𝑜𝑢𝑠𝑒ℎ𝑜𝑙𝑑 𝑚𝑒𝑚𝑏𝑒𝑟𝑠𝑖 + 𝛽36 𝑊𝑒𝑎𝑙𝑡ℎ 𝑖𝑛𝑑𝑒𝑥i + 𝛽37 𝑅𝑒𝑠𝑖𝑑𝑒𝑛𝑐𝑒 𝑡𝑦𝑝𝑒𝑖 + 𝜀𝑖
7
4. Data and Description of Variables
Micro level data for this research have been taken from Pakistan Demographic and Health
Survey (PDHS-2012-13) survey published by National Institute of Population Studies in compliance
with Pakistan Bureau of Statistics. This is the third and current most survey held so far in Pakistan.
Data captures the sample of currently married women and single women from each observed
household is selected for this analysis which constitutes the number of observed women up to 3207.
Agency and capabilities are the essential notions of Sen’s capabilities approach, here capability
is set of functionings and the freedom to achieve them reflects agency (Sen, 1992). Agency depicts
individual’s role in society i.e. one’s ability to take part in political and socio-economic actions. By
looking at the data limitations we will take variables of both agency, i.e., socio-economic roles of
decision making and functionings in our capabilities index.
As discussed above capabilities are stocks of economic and social capital (Muffel & Heady,
2013). Human capital (health, education and employment), wealth and economic decision making
roles constitutes individual’s economic capital (Becker 1985). Three proxies for health functioning are
taken, these are visit to health care facility, body mass index and healthy life style. Physical inactivity
are related with deprived health and usually people with poor health status pay visit to doctors and
hospitals (Feng et al., 2014). Body mass index captures current nutritional status and amount of energy
stored in the body. Both obese and under-weight damages the functioning of being “well-nourished”.
Women healthy life style is captured by looking at her non-usage of intoxicants (cigarettes, smokes,
pipes) (Muffel & Heady, 2013). In sense of capabilities approach, wealth shows one’s ability to hold
property (land or house) and agency is individual’s role in society, i.e., the ability to take part in socio-
economic and political decision making (Anand, et al, 2005; Hill, 2010, p.129).
Social capital is defined as extra pool of resources set in by social networkings. Social capital
is measured by taking one’s access of social networking/capital and media (Lin, 2002, p.25;
Meulemann, 2008, p.163).
Control variables of women, husband, and household along with in-laws and own parent’s
domestic violence are used as independent variables, whereas in accordance with the theory husband’s
domestic violence4, social and economic capital index are treated as endogenous variables.
4 Only husband domestic violence will be treated as endogenous and focal variable for domestic violence because out of the total observed sample of 3207 women, 39.54% faced husband’s domestic violence and only 2.9% and 6.95% women faced in-laws and parent’s domestic violence.
8
Description of categorical variables and summary statistics of used variables are described in the appendix.
4.1 Assigning weights to the capabilities
Theory of Sen’s capability approach states that wellbeing and development is a
multidimensional notion which covers all essential factors that are vital to make life worth living
[Stiglitz et al., 2009]. Multidimensional concept of development can be understood only through
composite indexes because particular indicator cannot infer the complex concepts. Selection of
assigning weights to diverse capabilities is an open debate in Sen’s framework of capability approach.
In order to devise multidimensional index of woman capabilities based upon Sen’s theory of
capabilities approach we will use three types of weighting systems that are classified by Oxford Poverty
and Human Development Initiative (OPHI) [Greco, 2016]. These are equal, normative and data
driven approach, each are based upon different theoretical assumptions [Decancq & Lugo, 2012].
The simplest approach is equal index, human development index and human poverty index
are formed by using this approach [Anand & Sen, 1997]. Due to lack of value judgments some
researchers believe that it is not rational to assign identical weights to each capability [Chowdhury &
Squire, 2006, p.762].
Another index of capabilities based upon value judgments is known to be normative index.
Weights can be assigned either by policy makers or by means of participatory method [Chowdhury &
Squire, 2006]. Since our data source is not primary we will assign weights by looking at the goals of
SDG’s and MDG’s because they too are set to be international policy makers [UNDP].
In economic capabilities index highest weight is assigned to “human capital” which is followed
by “women decision making” and “wealth” variables. Many of the SDG’s and vision 2025 goals are
based upon human capital. Goal 3, 4 and 5 deals with the betterment of people health, education and
employment. Goal 5 of SDG have many targets related to decision making autonomy’s e.g. increasing
women control over her earnings and increasing their participation in decision making. SDG’s also
put focus on women holds over ownership of lands and property, which depicts wealth in our case.
The highest weight is assigned to “access to social capital” in women social capabilities index which is
then followed by “access to media”. Goal 17 of SDG is based upon global partnership and
connectivity’s. Importance is also given to access to media, SDG put special focus on target of
enhancing access to interne by 2020.
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The last way of formulating capabilities is through principal component analysis which is a
data-driven approach. It facilitates the analysis of multi-dimensional approaches because it reduces the
complexities of variables by reducing its number and is applicable in raw data set.
Summary statistics of the capabilities indexes are mentioned in appendix.
5. Results, estimation technique and Discussion
5.1 Simultaneous equation model and estimation technique
Circularity theory has proven endogeneity of domestic violence, economic capital and social
capital in the model. Simultaneous equation model with three system of equations are formed.
Domestic violence, economic capital and social capital have been taken as dependent variables
separately in each equation. Since we construct economic and social capital indexes of women by using
three weighting schemes thus three simultaneous equations models will be run to analyze circularity
in Sen’s capabilities approach. Three stage least square estimation technique will be applied in our
simultaneous equations models.
Significance of predicted residual values of endogenous variables and Haussmann test
confirms simultaneity in the model. Identified system of equations fulfills both rank and order
conditions. Instruments used are “women father beaten her mother”, “women experiencing parental
violence”, “women employed for self or for others” and “women justifying behavior of domestic
violence”. “Women afraid of husband” instrument will be used in place of “women working for self
or for others” only in PCA weighted index model. Basmann and Sargan chi2 over identification test
assures instruments validity since null hypothesis of instruments validity got accepted. Instruments
strength has been checked by first stage F-values which is greater than 10.
5.2 Results
3SLS regression is done three times because women economic and social capabilities index is
constricted by using three weighting schemes (equal, normative and PCA). Results obtained from
equal and normative weighted capabilities indexes models are almost similar in terms of significance
except for the variable sons however the magnitude of coefficients differs for all three types of models.
The estimation results will be presented in a following way:
1. Regression analysis using equal weighted indexes of economic capital and social capital.
2. Regression analysis using normative weighted indexes of economic capital and social capital.
3. Regression analysis using PCA weighted indexes of economic capital and social capital
10
Model: 1 Economic capital and social capital constructed from equal weighted index:
Table 5.2a: Three stage least square results obtained from equal weighted economic and social capabilities index Variable Economic capital Domestic Violence Social capital
Economic capital - -1.410241* 0.7469967*
Domestic Violence -0.1115107* - -0.0916426*
Social capital 0.8239313* -0.6114065** -
Woman Age 0.0051676** - -0.0025186
Woman Age ^2 -0.0000395 - 0.0000431
Woman work before marriage 0.0001411 - -
Husband education 0.0031049* 0.0148291* -
Inlaws violence -0.0196842* -0.100394* -
Children -0.00061 - -
Years of marriage -0.0033683* -0.0024708* -
Woman unskilled occupation 0.0340758* - -0.037054*
Woman skilled occupation 0.050105* - -0.05281*
Less relative earning 0.0354303* 0.171416* -
More relative earning 0.0541335* 0.2611686* -
Husband unskilled occupation - -0.029366 -
husband skilled occupation - -0.0133872 -
Husband relative young - -0.0049033 -
Husband relative old - 0.0025346 -
Husband drink alcohol - 0.041114* -
Sons - -0.0045394*** -
Wealth Index - 0.1082853* 0.0236036*
Residence type - 0.0423315* 0.010251*
House hold members - - 0.0001734
Age at marriage - - -0.0030338*
Electricity - - 0.0025609
Constant -0.182212* 0.624395* 0.3193568*
Domestic violence residual(Simultaneity test)
0.24* - 0.224*
Social capital residual (Simultaneity test)
-0.545* 1.19* -
Economic capital residual(Simultaneity test)
- 1.145* -.392*
[P-value < 0.01 *, P-value <0.05 **, P-value<0.1 ***]
Hausman Statistic: 671.27* Test of overidentification: .0235112
Instruments: Woman justify beating, Woman parent’s violence, Woman working for self, Woman history of domestic violence.
Model: 2 Economic capital and social capital constructed from normative weighted index
Table 5.2b: Three stage least square results obtained from normative weighted economic and social capabilities index
Variable Economic capital Domestic Violence Social capital
Economic capital - -0.8227557* 0.7234657*
Domestic Violence -0.0615553*** - -0.134305*
Social capital 0.9152488* -0.7197529* -
Woman Age 0.0060282** - -0.0023599
Woman Age ^2 -0.0000455 - 0.0000434
11
Woman work before marriage 0.0005281 - -
Husband education 0.002761* 0.0096328* -
In-laws violence -0.0202545* -0.1110188* -
Children -0.0007883 - -
Years of marriage -0.0039118* -0.0014999* -
Woman unskilled occupation 0.0372629* - -0.0369182*
Woman skilled occupation 0.0570103* - -0.0522993*
Less relative earning 0.0297197* 0.1173769* -
More relative earning 0.0471317* 0.18406868* -
Husband unskilled occupation - -0.028749 -
husband skilled occupation - -0.0115702 -
Husband relative young - -0.0065329 -
Husband relative old - 0.0046651 -
Husband drink alcohol - 0.062595* -
Sons - -0.0031377 -
Wealth Index - 0.0829848* 0.0189842*
Residence type - 0.026892** 0.0076685**
House hold members - - 0.000012
Age at marriage - - -0.0031957*
Electricity - - 0.0025067
Constant -0.2489496* 0.6143744* 0.349417*
Domestic violence residual(Simultaneity test)
.252* - 0.224*
Social capital residual (Simultaneity test) -0.567* 1.21* -
Economic capital residual(Simultaneity test)
- 1.09* -0.37*
P-value < 0.01 *, P-value <0.05 **, P-value<0.1 **
Hausman Statistic: 802.77* Test of overidentification: .0326891
Instruments: Woman justify beating, Woman parent’s violence, Woman working for self, Woman history of domestic violence.
Model: 3 Economic capital and social capital constructed from PCA weighted index:
Table 5.2c: Three stage least square results obtained from PCA weighted economic and social capabilities index
Variable Economic capital Domestic Violence Social capital
Economic capital - -0.5524745* 0.3525293*
Domestic Violence -0.0631448* - -0.3432122*
Social capital 0.1302514* -2.312049* -
Woman Age 0.00196 - -0.0031261**
Woman Age ^2 -0.000035 - 0.0000182
Woman work before marriage -0.0017607 - -
Husband education -0.0006311 -0.0004511 -
Inlaws violence -0.008321 -0.0254576 -
Children -0.0022608* - -
Years of marriage 0.003515* -.0005471 -
Woman unskilled occupation 0.1183007* - -0.0679708*
Woman skilled occupation 0.1219112* - -0.0674485*
Less relative earning 0.132525* 0.1939295* -
More relative earning 0.1514704* 0.224355* -
Husband unskilled occupation - -0.0059983 -
husband skilled occupation - -0.0022005 -
12
Husband relative young - 0.0014401 -
Husband relative old - 0.0024835 -
Husband drink alcohal - 0.0139871 -
Sons - -.0029769 -
Wealth Index - 0.1479179* 0.0596919*
Residence type - 0.0498549* 0.0208193*
House hold members - - -0.0000979
Age at marriage - - 0.0022767*
Electricity - - 0.0020411
Constant 0.0904726* 0.9782796* 0.3266332*
Domestic violence residual(Simultaneity test)
0.217* - 0.180*
Social capital residual (Simultaneity test) .13* 1.33* -
Economic capital residual(Simultaneity test)
- 1.30* -0.39*
P-value < 0.01 *, P-value <0.05 **, P-value<0.1 ***
Hausman Statistic: 147.49* Test of overidentification: .356619
Instruments: Woman justify beating, Woman parent’s violence, Woman afraid of husband, Woman history of domestic violence.
5.3 Interpretations of Results
5.3a Dependent variable: Economic capability
Increase in social capability of women significantly increases their economic capabilities
however coefficient magnitude is greater for normative weighted index i.e. 0.91 points and lowest for
PCA weighted index model, i.e., 0.13 points. 1 point increase in intensity of domestic violence
significantly decreases women economic capability by 0.061, 0.11 and 0.06 points in normative, equal,
and PCA weighted indexes respectively. 1 year increase in women age significantly increases women
economic capability, its magnitude is highest for normative weighted index i.e. 0.006 points and
insignificantly lowest for PCA weighted index, i.e., 0.0019 points. Women who work before marriage
have insignificantly 0.00052 points and 0.00014 points more economic capabilities in normative and
equal weighted indexes than women who do not work before marriage. However, PCA weighted index
insignificantly decreases by 0.0017 points. Women who are employed in less skilled professions have
significantly more economic capabilities as compared to women who are not employed however the
magnitude is similar for equal and normative weighted indexes, i.e., 0.03 points. Women who are
employed in skilled professions have significantly more economic capabilities as compared to women
who are not employed, however its magnitude is highest for PCA weighted index, i.e., 0.12 points and
0.05 points for other two weighted indexes models. 1 year increase in husband’s education leads to
increase in women economic capability by 0.002 and 0.003 points in normative and equal weighted
index. Results are statistically significant. However in PCA weighted criteria 1 year increase in
13
husband’s education will insignificantly decrease women economic capabilities by 0.0006 points. 1
additional child decreases women economic capability by 0.0007, 0.0006 and 0.002 points in
normative, equal and PCA weighted indexes; however results are significant only in PCA. Women
earning less or same as their husbands have significantly more economic capabilities than women who
are unemployed. The coefficient’s magnitude is greater for equal weighted index model followed by
normative and PCA weighted indexes, i.e., 0.035, 0.029 And 0.13 points. Women earning more than
their husband have significantly more economic capabilities than women who are unemployed. The
coefficient’s magnitude is greater for PCA, i.e., 0.15 points and lowest for normative weighted index,
i.e., 0.04 points. As compared to the women facing in laws violence, women who do not face in laws
violence have 0.02, 0.019 and 0.008 points less economic capability in normative, equal and PCA
weighted criteria. However, results are insignificant for PCA weighted index.1 year increase in the
duration of marriage significantly decrease women economic capabilities by 0.003 points in normative
weighted and equal weighted criteria. But economic capabilities significantly increases by 0.003 points
in PCA.
5.3b Dependent variable: social capability
Increase in economic capability of women will significantly increase her social capability, its
magnitude is similar and greater for normative and equal weighted indexes respectively, i.e., 0.7 points
and less for PCA, i.e., 0.35 points. Increase in intensity of domestic violence will significantly decrease
social capability of women, 1 point increase in intensity of domestic violence will significantly decrease
social capability of women by 0.13, 0.09 and 0.34 points in normative, equal and PCA weighted indexes
respectively. 1 year increase in women’s age decrease their social capability by 0.0023, 0.0025 and 0.003
points in normative, equal and PCA weighted indexes respectively whereas results are significant only
in PCA weighted criteria. 1 year increase in age at marriage will significantly decrease women’s
normative and equal weighted social capital by 0.003 points respectively. However it significantly
increases for PCA weighted index model by 0.0022 points. Women who have facility of electricity at
home possess more social capability than those who do not have, the magnitude is similar for all three
weighting scheme models, i.e., 0.002 points. However, the results are statistically insignificant.
Women employed in less skilled occupation have significantly less social capability as
compared to those who are unemployed. However in terms of magnitude PCA weighted index shows
lowest figure which is negative 0.06 points followed by negative 0.03 points of other two weighted
indexes. Women employed in skilled occupation have significantly less social capability as compared
14
to those who are unemployed. However in terms of magnitude PCA weighted index shows lowest
figure which is negative 0.06 points followed by negative 0.05 points of other two weighted indexes.
Women who belong to rich class have significantly 0.018, 0.02 and 0.05 points more
normative, equal and PCA weighted social capabilities index respectively. Women living in urban areas
have significantly 0.007, 0.01 and 0.02 points more normative, equal and PCA weighted social
capabilities index. Increase in household members increase women’s social capability by 0.000012 and
0.0007 points in normative and equal weighted capabilities indexes models. However PCA weighted
index decreases by 0.00009 points. The results are insignificant for all three types of indexes.
5.3c Dependent variable: Domestic violence
Increase in economic capability of women significantly decreases incidence of domestic
violence.1 point increase in normative, equal and PCA weighted economic capability significantly
decreases domestic violence by 0.82,1.41 and 0.55 points. Increase in social capability of women
significantly decreases incidence of domestic violence 1 point increase in normative, equal and PCA
weighted social capability significantly decrease domestic capital violence by 0.719,0.61 and 2.31
points. Women who do not face domestic violence from their in-laws, face 0.11, 0.10 and 0.02 points
less violence from their husbands as compared to women who do face in-laws violence in the model
of normative, equal and PCA weighted social and economic capabilities indexes. However, the result
is insignificant for the model of PCA weighted capabilities indexes. 1 year increase in husband’s
education will significantly increase domestic violence by 0.009 and 0.01 points, in the model of
normative and equal weighted social and economic capabilities indexes. However, for PCA weighted
capabilities model it insignificantly decreases by 0.0004 points. Husbands who consume alcohol
commits more violence and the magnitude is greatest for normative weighted indexes model i.e. 0.06
points. However, the result is insignificant for the model of PCA weighted capabilities indexes.
Husbands who are employed in less skilled professions are 0.028, 0.029 and 0.005 points less abusive
to their wives in the model of normative, equal and PCA weighted capabilities indexes, as compared
to those who are unemployed. The results are statistically insignificant.
Husbands who are employed in skilled professions are 0.011, 0.013 and 0.002 points less
abusive than husbands who are unemployed in the model of normative, equal and PCA weighted
capabilities indexes. The results are statistically insignificant. Women who belong to rich families will
significantly face more husband’s domestic violence, the coefficient’s magnitude is largest for PCA
weighted capabilities model i.e. 0.14 points and smallest for normative weighted capabilities model,
15
i.e., 0.08 points. 1 additional son will decrease husband’s violence by 0.003, 0.004 and 0.002 points in
the model of normative, equal and PCA weighted capabilities indexes. However, the result is
significant only in the model of equal weighted capabilities indexes. Women living in urban areas
significantly faces more domestic violence than those living in rural areas, the coefficient’s magnitude
is similar and greater for equal and PCA weighted capabilities indexes models. Women earning less or
same as their husbands significantly face more domestic violence than women who are not employed,
the magnitude is largest for the model of PCA weighted capabilities indexes, i.e., 0.19 points and
lowest for normative weighted indexes model, 0.11 points.
Women earning more than husbands significantly face more domestic violence than women
who are not employed, the magnitude is largest for the model of equal weighted capabilities indexes,
i.e., 0.26 points and lowest for normative weighted indexes model, 0.18 points. As compared to the
same age groups, husbands who are younger than their wives are 0.006 and 0.004 points less abusive
in the model of normative and equal weighted capabilities indexes. However, for the model of PCA
weighted capabilities indexes younger husbands are 0.001 points more abusive. The results are
insignificant. As compared to the same age groups, husbands who are older are 0.004, 0.002 and 0.0024
points more abusive to their wives in the model of normative, equal and PCA weighted capabilities
indexes. The results are insignificant. 1 year increase in the duration of marriage significantly decrease
domestic violence by 0.0014, 0.002 and 0.0005 points in the model of normative, equal and PCA
weighted social and economic capabilities indexes. However, the results are insignificant for the model
of PCA weighted capabilities indexes.
6. Conclusion and Policy Implications
6.1. Conclusion
Occurrence of domestic violence is common in traditional patriarchal societies like Pakistan.
It is one of the major non-monetary impediment factor of international developmental goals related
to women development. Since the foundation of these goals are laid upon Sen’s theory that’s why his
theoretical model of capabilities approach is used for this study. The concept of circularity amongst
different capabilities and domestic violence is empirically estimated in this study. Circular associations
between conversion factor, social capital and economic capital in Sen’s capabilities approach are
important to address because otherwise this would make estimations spurious. In this paper
simultaneous equation model is used to test the findings because of the endogeneity of domestic
violence, social capital and economic capital.
16
Three forms of capabilities indexes are formed to measure women capabilities based upon
Sen’s capability theory. Different weighting schemes, i.e., equal, normative and data-driven are applied
to form three types of indexes, each scheme have different theoretical background. The purpose of
formulating different kinds of indexes was to check the consistency of circularity analysis and to
analyze which weighting scheme is showing results proximate to the theory.
Three stage least square estimation technique is used in this study. Results shows that
husband’s domestic violence has a significant and negative impact on wife’s economic and social
capabilities. Increase in woman social capital and economic capital will significantly decrease domestic
violence. Also capabilities are interdependent, increase in economic capital significantly increase social
capital similarly increase in social capital significantly increase economic capital.
All three kinds of indexes proves circularity in Sen’s capabilities approach. However the results
of equal and normative weighted indexes are close to the theory and are consistent with each other.
The possible reason is that PCA weighted indexes are formed on the basis of data, it has no theoretical
background. Thus weights to the capabilities should be given on the basis of theoretical backgrounds.
6.2 Policy Implications
After drawing major conclusions from our study we are able to make authentic policy
recommendations in order to improve Pakistani women’s well-being and development. Social and
economic capabilities are important for development and it also act as important protective factor
against domestic violence. Such policies should be applied which increases women capabilities, our
study shows that increasing one of the important capability will automatically reinforce other. Thus
women education should be enhanced by making access to affordable and good quality education
achievable for all. Promote women employment by making working areas policies feasible for women
also health facilities should be provided to them. These capabilities can be seen as important tools to
combat the incidences of domestic violence because it increases women bargaining power. Similarly
such actions should be avoided which negatively hurts women capabilities because it too will decrease
other capabilities. This will make situation worse and a person can get stuck into vicious cycle which
is harmful for a nation in long run.
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Appendix
Table A1: Description of Economic and Social capabilities index
Variable Category Frequency Percent 1. Economic capital
Person who took decision about spending of women earning
=0 if women does not earn 2577 80.36
=1 if husband alone 88 2.74
=2 if jointly 241 7.51
=3 if women alone 301 9.39
Person who took decision about women healthcare
=0 if husband alone 1169 36.45
=1 if jointly 1634 50.95
=2 if women alone 404 12.6
Person who took decision about household purchases
=0 if husband alone 1145 35.7
=1 jointly 1782 55.57
=2 if women alone 280 8.73
Person who took decision about spending of women earning
=0 if husband does not earn 409 12.75
=1 if husband alone 1247 38.88
=2 if jointly 1278 39.85
=3 if women alone 273 8.51
Autonomy to sell house own =0 if no 3160 98.53
=1 if yes 47 1.47
Autonomy to sell land own =0 if no 3158 98.47
=1 if yes 49 1.53
Own house =0 if does not own 2703 84.28
=1 if own jointly 426 13.28
=2 if own alone 78 2.43
Own land =0 if does not own 2980 92.92
=1 if own jointly 160 4.99
=2 if own alone 67 2.09
Visit healthcare facility in 1 year
=0 if yes 2412 75.21
=1 if no 795 24.79
Use of cigarettes or related intoxicants
=0 if yes 244 7.61
=1 if no 2963 92.39
Currently working =0 if no 2499 77.92
=1 if yes 708 22.08
Body Mass Index =0 if obese or underweight 855 26.66
=1 if normal weight 2352 73.34
Highest level of education =0 if no education 1796 56
=1 if primary education 469 14.62
=2 if secondary education 557 17.37
20
=3 if tertiary education 385 12
2. Social capital
Husband allowing wife to meet family
=0 f no 257 8.01
=1 if yes 2950 91.99
Husband allowing wife to meet friends
=0 f no 300 9.35
=1 if yes 2907 90.65
Frequency of reading newspaper
=0 if not at all
2388 74.46
=1 f occasionally 641 19.99
=2 if once a week 59 1.84
=3 if daily 119 3.71
Frequency of listening radio =0 if not at all
2623 81.79
=1 f occasionally 481 15
=2 if once a week 35 1.09
=3 if daily 68 2.12
Frequency of watching television
=0 if not at all
1023 31.9
=1 f occasionally 599 18.68
=2 if once a week 67 2.09
=3 if daily 1618 47.33
Table A2: Summary statistics of normalized endogenous variables
Variable Mean Standard deviation
Minimum Maximum
Domestic violence (sum of all forms of violence’s)
.14 .22 0 .875
Economic capabilities index
Equal weighted index .24 .16 0.00 1
Normative weighted index .24 .17 0.00 1
PCA weighted index .23 .13 0.00 1
Social capabilities index
Equal weighted index .41 .17 0.00 1
Normative weighted index .43 .17 0.00 1
PCA weighted index .38 .15 0.00 1
Table A3: Description of Categorical control/independent/exogenous variables
Variable Category Frequency Percent
Woman worked before marriage
=0 f no 2533 78.98
=1 if yes 674 21.02
In-laws violence =0 if yes 93 2.9
=1 if no 3114 97.1
Wife relative earning to husband
=0 if not employed (base category) 2577 80.36
=1 if less relative earning 490 15.28
=2 if more relative earning 140 4.37
Husband relative age to wife =0 if same age ( base category) 159 4.96
21
=1 if husband relative younger than wife 197 6.14
=2 if husband relative older than wife 2851 88.9
Husband drinks alcohol =0 f no 3021 94.2
=1 if yes 186 5.8
Husband occupation =0 if not employed (base category) 104 3.24
=1 if employed in unskilled occupation 1368 42.66
=2 if employed in skilled occupation 1735 54.10
Women occupation =0 if not employed (base category) 2440 76.08
=1 if employed in unskilled occupation 394 12.29
=2 if employed in skilled occupation 373 11.63
Wealth index =0 if poor 1216 37.92
=1 if middle 583 18.18
=2 if rich 1408 43.9
Residence type =0 if rural 1691 52.73
=1 if urban 1516 47.27
Electricity at home =0 if no 227 7.08
=1 if yes 2980 92.92
Table A4: Summary statistics of continuous exogenous/control/independent variables
Variable Mean Standard deviation
Minimum Maximum
Women age 34.02 7.98 16 49
Women age ^2 1221.65 552.34 256 2401
Husband education in years 6.73 5.42 0 16
Children 3.88 2.16 0 14
Years of marriage(proxy by age at 1st child birth)
13.24 8.19 0 35
Age at marriage 20.78 4.08 12 39
Sons 1.97 1.38 0 8
Household members 7.61 3.69s 2 48
Three stage least square results:
1. Equal weighted index model
Equation Obs Parms RMSE R-sq chi2 P
Economic capital 3,207 13 0.1501408 0.2097 2214.15 0
Domestic violence 3,207 15 0.2911752 -0.6775 366.38 0
Social capital 3,207 11 0.1487759 0.2783 1930.07 0
Coef. Std. Err. z P>z [95% Conf. Interval]
Economic capital
Social capital 0.8239313 0.0296239 27.81 0 0.7658695 0.8819932
Domestic violence -0.1115107 0.0231774 -4.81 0 -0.1569375 -0.0660838
Woman Age 0.0051676 0.0026069 1.98 0.047 0.0000582 0.0102769
22
Woman Age ^2 -0.0000395 0.0000376 -1.05 0.294 -0.0001132 0.0000342
Woman work before marriage 0.0001411 0.002093 0.07 0.946 -0.0039611 0.0042432
Husband education 0.0031049 0.0004171 7.44 0 0.0022875 0.0039224
Inlaws violence -0.0196842 0.0072519 -2.71 0.007 -0.0338976 -0.0054708
Woman occupation
Woman unskilled occupation 0.0340758 0.0086068 3.96 0 0.0172068 0.0509448
Woman skilled occupation 0.050105 0.0091396 5.48 0 0.0321917 0.0680184
Children -0.00061 0.000594 -1.03 0.304 -0.0017743 0.0005542
Relative earning
Less relative earning 0.0354303 0.0054601 6.49 0 0.0247288 0.0461319
More relative earning 0.0541335 0.007843 6.9 0 0.0387616 0.0695055
Years of marriage -0.0033683 0.0006557 -5.14 0 -0.0046534 -0.0020832
_cons -0.182212 0.0452102 -4.03 0 -0.2708223 -0.0936017
Domestic violence
Economic capital -1.410241 0.2508749 -5.62 0 -1.901947 -0.9185356
Social capital -0.6114065 0.267762 -2.28 0.022 -1.13621 -0.0866027
Inlaws violence -0.100394 0.0290613 -3.45 0.001 -0.1573532 -0.0434349
Husband education 0.0148291 0.0017916 8.28 0 0.0113177 0.0183405
Husband occupation
Husband unskilled occupation -0.029366 0.0189154 -1.55 0.121 -0.0664395 0.0077074
husband skilled occupation -0.0133872 0.0177571 -0.75 0.451 -0.0481904 0.0214161
Husband drink alcohal 0.041114 0.0130023 3.16 0.002 0.01563 0.0665981
Wealth Index 0.1082853 0.0118697 9.12 0 0.0850211 0.1315495
Residence type 0.0423315 0.0127912 3.31 0.001 0.0172611 0.0674018
Relative earning
Less relative earning 0.171416 0.0237672 7.21 0 0.1248331 0.2179988
More relative earning 0.2611686 0.0350938 7.44 0 0.192386 0.3299513
Sons -0.0045394 0.0026853 -1.69 0.091 -0.0098024 0.0007236
Relative age
Husband relative young -0.0049033 0.0161138 -0.3 0.761 -0.0364856 0.0266791
23
Husband relative old 0.0025346 0.0133107 0.19 0.849 -0.023554 0.0286232
Years of marriage -0.0024708 0.0007059 -3.5 0 -0.0038544 -0.0010872
_cons 0.624395 0.0562814 11.09 0 0.5140856 0.7347044
Social capital
Economic capital 0.7469967 0.0363279 20.56 0 0.6757954 0.818198
Domestic violence -0.0916426 0.0241276 -3.8 0 -0.1389319 -0.0443533
Woman Age -0.0025186 0.0026212 -0.96 0.337 -0.0076562 0.0026189
Woman Age ^2 0.0000431 0.0000378 1.14 0.255 -0.000031 0.0001171
Age at marriage -0.0030338 0.0006858 -4.42 0 -0.004378 -0.0016897
Electricity 0.0025609 0.0031857 0.8 0.421 -0.003683 0.0088048
Woman occupation
Woman unskilled occupation -0.037054 0.0080421 -4.61 0 -0.0528163 -0.0212917
Woman skilled occupation -0.05281 0.0088298 -5.98 0 -0.0701161 -0.0355039
Wealth Index 0.0236036 0.002991 7.89 0 0.0177413 0.0294658
Residence type 0.010251 0.0031354 3.27 0.001 0.0041057 0.0163963
House hold members 0.0001734 0.0002916 0.59 0.552 -0.0003982 0.0007449
_cons 0.3193568 0.0439547 7.27 0 0.2332072 0.4055063
Endogenous Variables: Social capital, economic capital and domestic violence.
Exogenous Variables: Woman Age, Woman Age ̂ 2, Woman work before marriage, Husband education, In-laws violence, Woman unskilled occupation, Woman
skilled occupation, Children ,Sons , Less relative earning, More relative earning, Years of marriage, Husband unskilled occupation, Husband skilled occupation,
Sons, Husband drinks alcohol, Wealth index, Residence type, Husband relative young, Husband relative old, Electricity, Age at marriage, House hold members,
Woman justify beating, Woman parent’s violence, Woman working for self, Woman history of domestic violence.
2. Normative weighted index model
Equation Obs Parms RMSE R-sq chi2 P
Economic capital 3,207 13 0.1576339 0.1711 2185.29 0
Domestic violence 3,207 15 0.2554453 -0.291 334.17 0
Social capital 3,207 11 0.1485593 0.2632 1874.83 0
Coef. Std. Err. z P>z [95% Conf. Interval]
Economic capital
Social capital 0.9152488 0.0331769 27.59 0 0.8502232 0.9802744
Domestic violence -0.0615553 0.0329122 -1.87 0.061 -0.126062 0.0029515
Woman Age 0.0060282 0.0027545 2.19 0.029 0.0006294 0.0114269
Woman Age ^2 -0.0000455 0.0000398 -1.14 0.253 -0.0001235 0.0000325
24
Woman work before marriage 0.0005281 0.0026429 0.2 0.842 -0.0046518 0.005708
Husband education 0.002761 0.0004417 6.25 0 0.0018954 0.0036266
Inlaws violence -0.0202545 0.0075725 -2.67 0.007 -0.0350964 -0.0054127
Woman occupation
Woman unskilled occupation 0.0372629 0.0094777 3.93 0 0.018687 0.0558388
Woman skilled occupation 0.0570103 0.0100383 5.68 0 0.0373356 0.0766851
Children -0.0007883 0.0007245 -1.09 0.277 -0.0022083 0.0006316
Relative earning
Less relative earning 0.0297197 0.0062259 4.77 0 0.0175173 0.0419222
More relative earning 0.0471317 0.0085703 5.5 0 0.0303342 0.0639291
Years of marriage -0.0039118 0.0006899 -5.67 0 -0.0052639 -0.0025597
_cons -0.2489496 0.0484501 -5.14 0 -0.3439101 -0.1539891
Domestic violence
Economic capital -0.8227557 0.2209463 -3.72 0 -1.255802 -0.389709
Social capital -0.7197529 0.246403 -2.92 0.003 -1.202694 -0.236812
Inlaws violence -0.1110188 0.0249143 -4.46 0 -0.1598501 -0.0621876
Husband education 0.0096328 0.0016168 5.96 0 0.0064639 0.0128016
Husband occupation
Husband unskilled occupation -0.028749 0.0191081 -1.5 0.132 -0.0662003 0.0087022
husband skilled occupation -0.0115702 0.0182938 -0.63 0.527 -0.0474255 0.0242851
Husband drink alcohal 0.062595 0.0141132 4.44 0 0.0349337 0.0902563
Wealth Index 0.0829848 0.0108107 7.68 0 0.0617962 0.1041734
Residence type 0.026892 0.0113757 2.36 0.018 0.0045961 0.049188
Relative earning
Less relative earning 0.1173769 0.0210919 5.57 0 0.0760375 0.1587162
More relative earning 0.1840686 0.0310959 5.92 0 0.1231218 0.2450154
Sons -0.0031377 0.0027918 -1.12 0.261 -0.0086096 0.0023341
Relative age
Husband relative young -0.0065329 0.0173226 -0.38 0.706 -0.0404845 0.0274188
25
Husband relative old 0.0046651 0.0141955 0.33 0.742 -0.0231575 0.0324878
Years of marriage -0.0014999 0.000645 -2.33 0.02 -0.0027641 -0.0002356
_cons 0.6143744 0.0563512 10.9 0 0.5039281 0.7248207
Social capital
Economic capital 0.7234657 0.0363071 19.93 0 0.6523051 0.7946263
Domestic violence -0.134305 0.0313249 -4.29 0 -0.1957006 -0.0729093
Woman Age -0.0023599 0.0025413 -0.93 0.353 -0.0073408 0.002621
Woman Age ^2 0.0000434 0.0000366 1.19 0.236 -0.0000284 0.0001152
Age at marriage -0.0031957 0.0006742 -4.74 0 -0.0045172 -0.0018742
Electricity 0.0025067 0.0035676 0.7 0.482 -0.0044857 0.0094992
Woman occupation
Woman unskilled occupation -0.0369182 0.0079602 -4.64 0 -0.0525199 -0.0213166
Woman skilled occupation -0.0522993 0.0087005 -6.01 0 -0.0693521 -0.0352466
Wealth Index 0.0189842 0.0030377 6.25 0 0.0130304 0.0249379
Residence type 0.0076685 0.0030726 2.5 0.013 0.0016464 0.0136906
House hold members 0.000012 0.0003126 0.04 0.969 -0.0006006 0.0006247
_cons 0.349417 0.0427853 8.17 0 0.2655593 0.4332746
Endogenous Variables: Social capital, economic capital and domestic violence.
Exogenous Variables: Woman Age, Woman Age ̂ 2, Woman work before marriage, Husband education, In-laws violence, Woman unskilled occupation, Woman
skilled occupation, Children ,Sons , less relative earning, More relative earning, Years of marriage, Husband unskilled occupation, Husband skilled occupation,
Sons, Husband drinks alcohol, Wealth index, Residence type, Husband relative young, Husband relative old, Electricity, Age at marriage, House hold members,
Woman justify beating, Woman parent’s violence, Woman working for self, Woman history of domestic violence.
3. PCA weighted index model
Equation Obs Parms RMSE R-sq chi2 P
Economic capital 3,207 13 0.0915034 0.563 4282.77 0
Domestic violence 3,207 15 0.3556086 -1.502 1080.96 0
Social capital 3,207 11 0.1446695 0.1223 1904.72 0
Coef. Std. Err. z P>z [95% Conf. Interval]
Economic capital
Social capital 0.1302514 0.0321736 4.05 0 0.0671923 0.1933105
Domestic violence -0.0631448 0.0161715 -3.9 0 -0.0948404 -
0.0314492
Woman Age 0.0019604 0.0017404 1.13 0.26 -0.0014507 0.0053715
Woman Age ^2 -0.000035 0.0000252 -1.39 0.166 -0.0000844 0.0000145
Woman work before marriage -0.0017607 0.0037195 -0.47 0.636 -0.0090508 0.0055293
26
Husband education -0.0006311 0.0004311 -1.46 0.143 -0.001476 0.0002138
Inlaws violence -0.008321 0.0095822 -0.87 0.385 -0.0271018 0.0104599
Woman occupation
Woman unskilled occupation 0.1183007 0.0085357 13.86 0 0.101571 0.1350305
Woman skilled occupation 0.1219112 0.0099839 12.21 0 0.1023431 0.1414793
Children -0.0022608 0.0009263 -2.44 0.015 -0.0040762 -
0.0004454
Relative earning
Less relative earning 0.132525 0.0092762 14.29 0 0.114344 0.150706
More relative earning 0.1514704 0.0114015 13.29 0 0.1291239 0.1738169
Years of marriage 0.003515 0.000459 7.66 0 0.0026153 0.0044146
_cons 0.0904726 0.0319152 2.83 0.005 0.02792 0.1530251
Domestic violence
Economic capital -0.5524745 0.205765 -2.68 0.007 -0.9557665 -
0.1491826
Social capital -2.312049 0.1381546 -16.74 0 -2.582828 -2.041271
Inlaws violence -0.0254576 0.0182687 -1.39 0.163 -0.0612636 0.0103484
Husband education -0.0004511 0.0011547 -0.39 0.696 -0.0027143 0.001812
Husband occupation
Husband unskilled occupation -0.0059983 0.013821 -0.43 0.664 -0.033087 0.0210904
husband skilled occupation -0.0022005 0.0136479 -0.16 0.872 -0.0289498 0.0245489
Husband drink alcohal 0.0139871 0.0114058 1.23 0.22 -0.0083679 0.036342
Wealth Index 0.1479179 0.0104172 14.2 0 0.1275006 0.1683351
Residence type 0.0498549 0.0142541 3.5 0 0.0219174 0.0777924
Relative earning
Less relative earning 0.1939295 0.0501887 3.86 0 0.0955616 0.2922975
More relative earning 0.224355 0.0552514 4.06 0 0.1160643 0.3326458
Sons -0.0029769 0.0021793 -1.37 0.172 -0.0072482 0.0012944
Relative age
Husband relative young 0.0014401 0.0138776 0.1 0.917 -0.0257594 0.0286397
Husband relative old 0.0024835 0.0113133 0.22 0.826 -0.0196901 0.0246572
Years of marriage -0.0005471 0.0009525 -0.57 0.566 -0.0024139 0.0013198
27
_cons 0.9782796 0.0459189 21.3 0 0.8882802 1.068279
Social capital
Economic capital 0.3525293 0.0790308 4.46 0 0.1976318 0.5074268
Domestic violence -0.3432122 0.015611 -21.99 0 -0.3738092 -
0.3126152
Woman Age -0.0031261 0.0014461 -2.16 0.031 -0.0059604 -
0.0002917
Woman Age ^2 0.0000182 0.0000197 0.93 0.355 -0.0000204 0.0000568
Age at marriage 0.0022767 0.0004951 4.6 0 0.0013063 0.0032472
Electricity 0.0020411 0.0037322 0.55 0.584 -0.0052739 0.0093561
Woman occupation
Woman unskilled occupation -0.0679708 0.0183531 -3.7 0 -0.1039421 -
0.0319994
Woman skilled occupation -0.0674485 0.0198072 -3.41 0.001 -0.10627 -0.028627
Wealth Index 0.0596919 0.0031641 18.87 0 0.0534905 0.0658934
Residence type 0.0208193 0.0054253 3.84 0 0.0101858 0.0314527
House hold members -0.0000979 0.0003908 -0.25 0.802 -0.0008639 0.0006681
_cons 0.3266332 0.0247328 13.21 0 0.2781579 0.3751085
Endogenous Variables: Social capital, economic capital and domestic violence.
Exogenous Variables: Woman Age, Woman Age ̂ 2, Woman work before marriage, Husband education, In-laws violence, Woman unskilled occupation, Woman
skilled occupation, Children ,Sons , Less relative earning, More relative earning, Years of marriage, Husband unskilled occupation, Husband skilled occupation,
Sons, Husband drinks alcohol, Wealth index, Residence type, Husband relative young, Husband relative old, Electricity, Age at marriage, House hold members,
Woman justify beating, Woman parent’s violence, Woman working for self, Woman history of domestic violence.
S3H Working Paper
01: 2014 Exploring New Pathways to Gender Equality in Education: Does ICT Matter? by
Ayesha Qaisrani and Ather Maqsood Ahmed (2014), 35 pp.
02: 2014 an Investigation into the Export Supply Determinants of Selected South Asian
Economies by Aleena Sajjad and Zafar Mahmood (2014), 33 pp.
03: 2014 Cultural Goods Trade as a Transformative Force in the Global Economy: A Case of
Pakistan by Saba Salim and Zafar Mahmood (2014), 32 pp.
04: 2014 Explaining Trends and Factors Affecting Export Diversification in ASEAN and
SAARC Regions: An Empirical Analysis by Shabana Noureen and Zafar Mahmood
(2014), 29 pp.
05: 2014 In Search of Exchange Rate Undershooting in Pakistan by Wajiha Haq and Iftikhar
Hussain Adil (2014), 20 pp.
01: 2015 A Time Series Analysis of Aggregate Consumption Function for Pakistan by Zakia
Zafar and Tanweer Ul Islam (2015), 13 pp.
02: 2015 Impact of Human Capital Investment on the Exports of Goods and Services: An
Analysis of Selected Outsourcing Countries by Samina Siddique and Zafar Mahmood
(2015), 31 pp.
03: 2015 Energy Demand Elasticity in Pakistan: An Inter-temporal Analysis from Household
Survey Data of PIHS 2001-02 and PSLM 2010-11 by Ashfaque H. Khan, Umer Khalid
and Lubna Shahnaz (2015), 34 pp.
04: 2015 The Size of Trade Misinvoicing in Pakistan by Tehseen Ahmed Qureshi and Zafar
Mahmood (2015), 31 pp.
05: 2015 Services Sector Liberalization and Its Impact on Services GDP Growth in Pakistan by
Maryam Mahfooz and Zafar Mahmood (2015), 30 pp.
06: 2015 Alternative to Kibor for Islamic Banking: A Case Study of Pakistan by Asaad Ismail
Ali and Zahid Siddique (2015), 25 pp.
07: 2015 Impact of Climatic Shocks on Child Human Capital: Evidence from Ethiopia, India,
Peru and Vietnam by Mina Zamand and Asma Hyder (2015), 27 pp.
08: 2015 Energy Related Carbon Dioxide Emissions in Pakistan: A Decomposition Analysis
Using LMDI by Arslan Khan and Faisal Jamil (2015), 20 pp.
09: 2015 Decomposition Analysis of Energy Consumption Growth in Pakistan during 1990-
2013 by Arbab Muhammad Shahzad and Faisal Jamil (2015), 24 pp.
10: 2015 Economic Rationality and Early Age Work-Education Choice: Rethinking the Links
by Zahid Sidique, Faisal Jamil and Ayesha Nazuk (2015), 22pp.
11: 2015 Trade Costs of Pakistan with its Major Trading Partners: Measurement and its
Determinants by Saba Altaf and Zafar Mahmood (2015), 32 pp.
01: 2016 The Statistical Value of Injury Risk in Construction and Manufacturing Sector of
Pakistan by Ahmad Mujtaba Khan and Asma Hyder (2016), 15 pp.
02: 2016 Socio-economic Determinants of Maternal Healthcare Behavior: Evidence from
Pakistan by Sadaf Munir Ahmad and Asma Hyder (2016), 19 pp.
03: 2016 Rising Debt: A Serious Threat to the National Security by Ashfaque H. Khan (2016),
31 pp.
04: 2016 Long-run Pricing Performance of Initial Public Offerings (IPOs) in Pakistan by
Muhammad Zubair Mumtaz and Ather Maqsood Ahmed (2016), 38 pp.
05: 2016 When Enough is Not Enough: An Exploratory Analysis of Corruption Behavior in
Select Urban Populations by Kh. Ayaz Ahmed and Ather Maqsood Ahmed (2016), 43
pp.
06: 2016 Determinants of Income Inequality among the Earners in Pakistan by Saira Naseer
and Ather Maqsood Ahmed (2016), 38 pp.
07: 2016 Natural Resource Dependence and Human Capital Accumulation – An Analysis for
the Selected SAARC, ASEAN and OPEC Countries by Rabia Qaiser and Zafar
Mahmood (2016), 31 pp.
08: 2016 Horizontal and Vertical Spillover Effects of Foreign Direct Investment on Sectoral
Productivity in Selected SAARC Countries by Noreen Kasi and Zafar Mahmood
(2016), 34 pp.
09: 2016 Technology Transfer, Development, Deployment, and Productivity Performance in
Pakistan by Irfan Ali and Zafar Mahmood (2016), 35 pp.
10: 2016 Welfare Impact of Electricity Subsidy Reforms: A Micro Model Study by Syed Adnan
Khalid and Verda Salman (2016), 31 pp.
11: 2016 Public Debt and Economic Growth Incorporating Endogeneity & Non-linearity by
Saira Saeed and Tanweer Ul Islam (2016), 13 pp.
01: 2017 What Explains the Success and Failure of the World Bank Projects? A Cross Country
Analysis by Rabbia Tariq and Abdul Jalil (2017), 32 pp.
02: 2017 A Dynamic Stochastic General Equilibrium Model of Pakistan’s Economy by Gulzar
Khan and Ather Maqsood Ahmed (2017), 32 pp.
03: 2017 Trade Creation Versus Trade Diversion and General Equilibrium Effect in Regional
and Bilateral Free Trade Agreements of Pakistan by Hina Ishaque Khan and Zafar
Mahmood (2017), 31 pp.
04: 2017 The Relative Effectiveness of Public versus Private Social Safety Nets in Mitigating
the Impact of Shocks in Rural Pakistan by Ayesha Imran Malik, Iqra Shahid and
Samina Naveed (2017), 29 pp.
Chinese Studies:
CS-01: 2016 China’s Development Experience by Syed Hasan Javed (2016), 15 pp.
Development Studies:
DS-01: 2016 Rehabilitation of 2010 Flood Affected People in Pakistan: Role of Development
Partners by Sheeba Farooq (2016), 39 pp.