The provided research proposal will serve as a blueprint for my final dissertation. Existing and readily available literature, will be thoroughly reviewed as well as an in-depth description of my methods and the statistics produced thereof. This study will also require the use of an econometric and game-approach to examine the underlying relationship between changes in unemployment and domestic violence with a global focus, and brief highlight on this topic, focusing on a case set in Papua New Guinea. My results will be delivered along with my dissertation findings and conclude with a result that either is consistent or inconsistent with my hypotheses.
Background of the research question
My desired terminal objective of this research is to accurately adumbrate that unemployment and domestic violence are robustly correlated. According to the NHS, domestic violence can be defined as: “Any incident of controlling, coercive, threatening behaviour, violence or abuse between those aged 16 or over who are or have been intimate partners or family members regardless of gender or sexuality. The abuse can encompass, but is not limited to: psychological, physical, sexual, financial, emotional coercion.” (NHS, 2018). Many developing economies, such as that of Papua New Guinea, battle the problem of job allocation where majority of the employable and able-bodied population are unemployed. Furthermore, and equally of great concern, these economies have high numbers of domestic violence cases. Similarly, in more economically developed societies there is a suspected link between domestic violence and unemployment rates, even in the United Kingdom. In an instance in 1993, the British daily newspaper The Independent cited a constable talk about the rise in domestic violence:
“With the problems in the country and unemployment being as high as it is and the associated financial problems, the pressures within family life are far greater. That must exacerbate the problems and, sadly, the police service is now picking up the pieces of that increase.” (Andrew May, Assistant Chief Constable South Wales, The Independent, 9 March 1993).
In a 2008 interview for The Guardian, the Attorney General for England and Wales argued that domestic violence will spread as the recession deepens: “When families go through difficulties, if someone loses their job, or they have financial problems, it can escalate stress, and lead to alcohol or drug abuse. Quite often violence can flow from that.” (Baroness Scotland of Asthal, The Guardian, 20 December 2008).
These instances are all cemented on the idea and advocates that immense unemployment may contribute to the occurrence of violence in a home. Nonetheless, from an experimental point of view it is somewhat ambiguous as to whether unemployment is a key determinant of domestic violence. There has been distinct philosophical work that has fully investigated this topic, any evidence or research on this link has been null or incomplete. My Thesis will seek to solve this problem.
Literature& Structural review : Unemployment and Domestic Violence
To begin with we have to adopt a model with the use of game theory to uncover how domestic violence can be affected by the changes in Unemployment. It assumes that the higher the level of unemployment the more the distinctive to the labor-income risk an agent becomes.
The major speculative outcome of this model is that if the risk of unemployment in men rises there will be a reduction in the occurrence of violence with intimate partners. We also want to give a reason for our perception of the effects of unemployment on male and females are really different.
If a man has tendencies to be violent and faces a risk of unemployment, he pretends as if he is not violent because he knows he faces a situation where his female partner leaves him because of his violent nature. Resultantly, high levels of male unemployment is related with a smaller risk of violence. Contrarily when a woman is fazed with a high level of unemployment risk she has little or no incentive to leave her male partner even if he has violent tendencies.
Therefore, when there is high level of women prone to unemployment risks they become very susceptible to violence from their intimate partner.
To buttress my empirical method from the theoretical prognosis which states that women are more susceptible to domestic violence, banks on gender-definitive risks of unemployment . To support this in my dissertation I will be making use of some statistics and readily available data of occurrences of domestic violence amongst intimate partners in both the United kingdom and in Papua new Guinea.
Structure
This paper will be shared into three different section of studies. To begin with it study the links between the susceptibility of women to domestic violence and their economic status. For this particular study we will review already existing literature on this category and finds favour in Aizer’s (2010) study which is of the idea that the gender wage gap has a significant role in the case of domestic violence against women by an intimate partner.
The succeeding brand of study examines the consequence of Public Policies on intimate partner violence. Whether or not these policies are effective in reducing domestic violence again women, for this we review studies from Aizer(2009) and Iyen gar(2009) Iyen concludes that compulsory rules concerning arrests of culprits involved in these violent acts can increase intimate partner homicides.
The final category of study examines the rationales behind violent practises amongst males. JoAnna Elmquist(2014) conclude that the most frequently endorsed motives for intimate partner violence are self defence , communication difficulties and expression of negative emotions. Their hypothesis was tested using the data of a demographic questioner which gathered each participants age, ethnicity, relationship status, ethnicity, and number of violent intervention sessions attended. The questioner contained an RVS( reason for violence scale) that was used to examine reasons for inflicting physical assault against an intimate partner. Subjects were given 29 possible motives, and were required to determine the percentage of violent instances in which each motive was a influenced their resolution to execute intimate partner violence. The mark for an individual component could be between 0% and 100%, which signals the number of instances each motive was the root of a violent incident.
The rest of the dissertation will be will have 4 departments. The first department deduces a theoretical framework as a driver for explaining the empirical results. the Second Department will explain our data and statistics deployed. The third department will draft the methodology we utilise to examine the fundamental notions behind the model and displays the results. The Fourth Department will give a well detailed conclusion of the dissertation.
Method
I am deploying two methods for my Thesis . (i) A game theoretical framework model and (ii)
The game theoretical model will be established on the assumption that marriage is a non-market institution that can provide a certain level of insurance against income risk it is also a Signalling model for forward looking males. A dynamic game of partial information associated with two intimate partners: Male partner(x) and female partner(h). Below is explicit timing of the game:
A certain type of male partner is picked from a set of two feasible types δ∈{P,Q}. Type P has a tendency to be violent, on the other hand type Q has a distaste for violence. The probability that δ=Q is denoted φ ∈(0,1).
The male partner studies his type δ and adopts a way to behave from a paired set, ζ∈(0,1), which together with his type, actuates the probability that future disputes with his spouse can lead to domestic violence. A probability of occurrence of violence will be denoted in my thesis as well as the costs incurred and also an empirical example.
The female partner studies her male partners actions ζ (but does not study his type δ) and amends her notions about his type φ ̂ (ζ). Based on her amended notions she is left with a choice of either continuing the marriage with her partner or getting a divorce, this choice is denoted by Κ={f,j} . A stigma cost μ_b≥0 is incurred by both the male and female partner b if the female partner decides to end the marriage.
The Employment results are determined by Nature. Each partner b (b = y, u) is employed or unemployed with a probability α_(b )if employed and 1 – α_(b )if unemployed. Partner b has makes an income y_b=ϑ_b. Whereas if unemployed each person has an income of y_b= L which can also be known as a perk of being unemployed. I’ll assume that L <〖 ϑ〗_b for each partner b. If they remain married, both spouses enjoy consumption from having some level of publicness in the household. The consumption function of partner b can be expressed as
p_b^m = p(y_b y_c )≡y_b+λy_c, (1)
where λ ∈(0,1] specifies the level of publicness of household consumption where y_c is the income level of the spouse. In the case of a divorce both partner’s consumption is basically his or her income, p_b^d = y_c. Partner b acquires a utility u( p_b) from consumption, whereby u(⋅) is increasing and strictly concave.
If the partners remain married , they both are faced with a conflict situation (i.e severe argument)
Which becomes a violent situation with probability π(δ, ζ). The female partner endures additive disutility σ_h > 0 if violence occurs. The male partner’s disutility from violence depends on his type, σ_P>0 for a husband of type P and σ_Q = 0 for a male partner of type Q.
I will solve this model for a Pure strategy Bayesian equilibrium. All through, (ζ^',ζ'') denotes that a male partner of type Q chooses ζ^' and a male partner of type P chooses ζ^''. Likewise , (K’,K’’) indicates picks K’ following ζ=0 and K’’ following ζ'' = 1 .
This equilibrium will be solved in the dissertation to arrive at an empirical prediction that men with a violent tendencies may tactically imitate the behaviour of non-violent men, in order to cover up their real type when faced with risk of unemployment. Contrary to that, men who have strong earning prospects and little or no risk of unemployment are less likely to cover up any violent traits they may have.
Econometric model
I intent to follow the econometric model which will be further describe main analysis that links a female victim’s struggle with domestic violence to the unemployment rates within the United states by also examining the change in male and female unemployment and change in the occurrence of intimate partner violence across Law enforcement Area’s (LEA) in the United States. Each period variable obtained from our labour market data will be denoted as t, where are particular period. The basic model below represents the inherent tendency to for abuse against a person p in LEA k in period t and within age group of g is given by:
y_pktg^*= 〖βX〗_pktg+δ^f 〖UNEMPL〗_ktg^f+〖δ^m UNEMPL〗_ktg^m+ μ_t+ρ_k+ε_pktg
where X_pktg includes demographic controls at the individual level, 〖UNEMPL〗_ktg^f and 〖UNEMPL〗_ktg^m are the rates of unemployment for both male and female and p is the individuals age group in law enforcement area k during period t ,and ε_pktg is a normally distributed error term. Parameters μ_t and ρ_k are fixed effects for both time-periods and Law enforcement areas and therefore controls for the total trend in the outcome variables and for factors affecting violence that vary across but are fixed over time.
Hence our basic identifies the impact of gender-specific unemployment on domestic abuse from variation in trends across PFA.
Data and Sources
The data used will be from the United States National intimate partner and sexual violence survey provided by the (CDC)Centre for disease and control prevention(domestic abuse data) and also (Labour market data) labour market from the United states bureau of Statistics .
TABLE 1 . CDC categories of domestic violence (Source: USA national intimate partner violence survey 2015)
WEIGHTED% 95% CL Estimated Number of victims
Physical Aggression or any 36.4 (34.8, 38.0) 43,546,000
Expressive aggression- Insulted, humiliated , made fun of in front of others 25.7 (24.3,27.2) 30,770,000
Any coercive control 30.6 (29.1,32.2) 36,654,000
Kept you from having your own money 9.6 (8.7,10.6) 11,501,000
Tried to keep you from seeing your own friends and family 16.4 (15.2,17.6) 19,622,000
Kept track of by demanding to know where you were and what you were doing 23.5 (2.2,25.0) 28,185,000
Made threats to harm physically 19.7 (18.4,21.0) 23,546,000
Abbreviation: CI = confidence interval.
*Rounded to the nearest thousand* This 1this Represents a subset of the psychological aggression items that were included in previous administrations of the NISVS survey.
The NISV is a regular cell phone survey on intimate partner violence in the united states. The approximations and statistics delivered by these reports are based 10,081 interviews conducted between April and September 2015. The main method adopted by the survey was making use of a two part sampling approach for cell numbers, in this method an activity code was attached to each individuals telephone number after the cell had been sampled to detect whether the individuals phone line was active or inactive. Any phone number that had been discovered to be active was dialled at 100%, but other phone number were dialled at a rate were by statistical and cost efficiency would be achieved.
My final thesis will give Outline the several strengths this CDC data has over other forms of data relating to domestic and intimate partner violence.
Labor Market Data Frome the United States Current Population Survey
The final thesis will combine individual-level Data from the NISV and Labour market data from the United States current Population Survey (USCPS). Monthly data sets are provided, with each set containing data of 12 months.
TABLE 2 . Summary statistics for US unemployment rates generated by stata with data from USCPS from January 2008- December 2017 with 120 observations for each Category.
Variable Mean Standard Deviation Min Max
Total Unemployment 6.981667 1.884487 4.1 10
Unemployment by Gender
Male 6.72 2.122786 4 9.8
Female 6.089167 1.552661 3.966667 8.033334
Unemployment by Age group
Aged 16-19 20.65 4.182569 14.1 25.9
Aged 25-34 7.253333 2.00281 4.3 10.6
Aged 35-44 5.66 1.712357 3 9
Aged 45-54 5.266667 1.652314 2.7 8.1
Conclusion
My Dissertation will extend our analysis on my empirical approach in which intimate partnership and domestic violence are immensely related. An equilibrium in the theoretical model is expected to be arrived at in which increased in unemployment rate of males lowers the occurrence of domestic violence while a rising risk of unemployment rate of females increases the rate of domestic violence.