Capabilities: Circularity Analysis in Sen’s Development...

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.

9

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


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* -







Husband relative young - -0.0065329 -


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*


Constant -0.2489496* 0.6143744* 0.349417*


.252* - 0.224*

Social capital residual (Simultaneity test) -0.567* 1.21* -


- 1.09* -0.37*

P-value < 0.01 *, P-value <0.05 **, P-value<0.1 **


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


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 -







12

Husband relative young - 0.0014401 -


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*


Constant 0.0904726* 0.9782796* 0.3266332*


0.217* - 0.180*

Social capital residual (Simultaneity test) .13* 1.33* -


- 1.30* -0.39*

P-value < 0.01 *, P-value <0.05 **, P-value<0.1 ***


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.

References

Agarwal, B., & Panda, P. (2007). Toward Freedom from Domestic Violence: the Neglected Obvious.

Journal of Human Development, 8(3), 359-388.

Anand, P., Hunter, G., & Smith, R. (2005). Capabilities and Well-being: Evidence Based on the Sen–

17

Nussbaum Approach to Welfare. Social Indicators Research, 74(1), 9-55.

Anand, S., & Sen, A. (1997). Concepts or Human Development and Poverty! A Multidimensional

Perspective. United Nations Development Programme, Poverty and Human Development: Human

Development Papers, 1-20.

Becker, G. S. (1985). Human Capital, Effort, and the Sexual Division of Labor. Journal of Labor

Economics, 3(1, Part 2), S33-S58.

Bhattacharya, H. (2015). Spousal Violence and Women's Employment in India. Feminist Economics,

21(2), 30-52.

Binder, M., & Coad, A. (2011). Disentangling the Circularity in Sen’s Capability Approach: An analysis

of the Co-evolution of Functioning Achievement and Resources. Social Indicators Research,

103(3), 327-355.

Burazeri, G., Roshi, E., Jewkes, R., Jordan, S., Bjegovic, V., & Laaser, U. (2005). Factors Associated

with Spousal Physical Violence in Albania: Cross Sectional Study. British Medical Journal,

331(7510), 197-201.

Chowdhury, S., & Squire, L. (2006). Setting Weights for Aggregate Indices: An application to the

Commitment to Development Index and Human Development Index. Journal of Development

Studies, 42(5), 761–771.

Decancq, K., & Lugo, M. A. (2012). Weights in Multidimensional Indices of Wellbeing: An Overview.

Econometric Reviews, 32(1), 7–34.

Feng, X., Girosi, F., & McRae, I. S. (2014). People with Multiple Unhealthy Lifestyles are less likely to

Consult Primary Healthcare. BMC Family Practice, 15(1), 126.

Ford, M., & Lyons, L. (Eds.). (2012). Men and Masculinities in Southeast Asia (Vol. 41). Routledge.

Gibson‐Davis, C. M., Magnuson, K., Gennetian, L. A., & Duncan, G. J. (2005). Employment and the

Risk of Domestic Abuse among Low‐Income Women. Journal of Marriage and Family, 67(5),

1149-1168.

Grabe, S. (2012). An Empirical Examination of Women's Empowerment and Transformative Change

in the Context of International Development. American Journal of Community

Psychology, 49(1-2), 233-245.

Greco, G. (2016). Setting the Weights: The Women’s Capabilities Index for Malawi. Social Indicators

Research, 1-22.

Hill, E. (2010). Worker Identity, Agency and Economic Development: Women's Empowerment in

the Indian Informal Economy (Vol. 15). Taylor & Francis.

18

Kaur, R., & Garg, S. (2008). Addressing Domestic Violence against Women: An Unfinished agenda.

Indian Journal of Community Medicine, 33(2), 73.

Lenze, J., & Klasen, S. (2016). Does Women’s Labor Force Participation Reduce Domestic Violence?

Evidence from Jordan. Feminist Economics, 1-29.

Lin, N. (2002). Social Capital: A theory of Social Structure and Action (Vol. 19). Cambridge University

Press.

Meulemann, H. (2008). Social Capital in Europe: Similarity of Countries and Diversity of People?

Multi-level Analyses of the European Social Survey 2002. Brill.

Moser, C. O. (1989). Gender planning in the Third World: Meeting Practical and Strategic Gender

Needs. World Development, 17(11), 1799-1825.

Muffels, R., & Headey, B. (2013). Capabilities and Choices: Do they Make Sen’se for Understanding

Objective and Subjective Well-being? An Empirical Test of Sen’s Capability Framework on

German and British Panel Data. Social Indicators Research, 110(3), 1159-1185.

Nussbaum, M. C. (2005). Women's Bodies: Violence, Security, Capabilities. Journal of Human

Development, 6(2), 167-183.

Robeyns, I. (2005). Selecting Capabilities for Quality of Life Measurement. Social Indicators Research,

74(1), 191-215.

Schmidt-Traub, G., & Shah, A. (2015). Investment Needs to Achieve the Sustainable Development

Goals. Paris and New York: Sustainable Development Solutions Network.

Semahegn, A., & Mengistie, B. (2015). Domestic Violence against Women and Associated Factors in

Ethiopia; Systematic Review. Reproductive Health, 12(1), 78.

Sen, A. (1982). Choice, Welfare and Measurement. Cambridge, MA: Harvar University Press.

Sen, A. (1983). "Poor, Relatively Speaking." Oxford Economic Papers 35(2): pp. 153 - 169.

Sen, A. (1985). Commodities and Capabilities. Oxford: Oxford University Press.

Sen, A. (1999). Development as Freedom. New York: Alfred A. Knopf.

Sen, A. K. (1985a). Commodities and Capabilities. Amsterdam: North.

Sen, A. K. (1985b). Well-being, Agency and Freedom: The Dewey Lectures 1984. The Journal of

Philosophy, 82(4), 169-221.

Sen, A. K. (1992). Inequality Reexamined. Oxford: Clarendon

Sen, G., & Grown, C. (1988). Development, Crises and Alternative Visions: Third World Women's Perspectives.

Earthscan.

Stiglitz, J. E., Sen, A. et al. (2009). Report by the Commission on the Measurement of Economic

19

Performance and Social Progress, Commission on the Measurement of Economic

Performance and Social Progress

World Health Organization (2013). Global and Regional Estimates of Violence against Women:

Prevalence and Health Effects of Intimate Partner Violence and Non-partner Sexual Violence.

World Health Organization.

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


=1 if jointly 1634 50.95


Person who took decision about household purchases


=1 jointly 1782 55.57


Person who took decision about spending of women earning

=0 if husband does not earn 409 12.75


=2 if jointly 1278 39.85


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


=3 if daily 68 2.12

Frequency of watching television

=0 if not at all

1023 31.9

=1 f occasionally 599 18.68


=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 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



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


_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


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




Social capital 3,207 11 0.1485593 0.2632 1874.83 0


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


Inlaws violence -0.0202545 0.0075725 -2.67 0.007 -0.0350964 -0.0054127

Woman occupation



Children -0.0007883 0.0007245 -1.09 0.277 -0.0022083 0.0006316

Relative earning




_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 occupation



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



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


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



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



skilled occupation, Children ,Sons , less relative earning, More relative earning, Years of marriage, Husband unskilled occupation, Husband skilled occupation,



3. PCA weighted index model




Social capital 3,207 11 0.1446695 0.1223 1904.72 0


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



Children -0.0022608 0.0009263 -2.44 0.015 -0.0040762 -

0.0004454

Relative earning



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 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



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


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


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



skilled occupation, Children ,Sons , Less relative earning, More relative earning, Years of marriage, Husband unskilled occupation, Husband skilled occupation,



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


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


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.

Date post:	27-Jun-2020
Category:	Documents
Upload:	others
View:	0 times
Download:	0 times

Capabilities: Circularity Analysis in Sen’s Development...

Documents