Dynamics of Marriage Decisions

How Marriage is Define in our Community?

Marriage is an altogether human-built idea, and there are many components that go into a marriage choice. These variables have been as of late interpreted as small scale level suppositions that can be utilized to clarify large scale level marriage designs. Actually, specialist based displaying has been viewed as an advantageous approach to demonstrate these suspicions keeping in mind the end goal to inspect watched designs (Billari et al., 2007). In this paper, we will propose one such specialist based model ("the model") that takes a gander at two choice variables: social weight and similitude (between the chief and a potential accomplice). We begin with the supposition that both these components affect the marriage choice, and after that inspect coming about examples that come about because of changing the heaviness of each.

Various past reviews have inspected social weight as a consider marriage choices. One such review was directed by Gudmund Hernes; Hernes looks at the contention between expanding social weight to wed against the declining marriageability consider with age (1972). He expect that the impact of social weight on the likelihood of marriage is predictable over the whole populace, and is a component of three elements: the extent of the populace effectively wedded, the extent of the populace not wedded, and a change consider. This factual model will play into the marriage choice lead demonstrated later on. Hernes contrasted his scientific model with exact research and found the "fit" was great, demonstrating that the first suspicions (that social weight expands the likelihood of marriage, however time dissolves at individual marriageability) hold water.

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Others have taken a gander at social weight particularly as the central calculate marriage choices. Billari et al. built a specialist based model (called the "Wedding band," which this model is approximately based off of) to analyze how informal communities play into marriage choices (2007). The "Wedding band" demonstrate goes past just marriage, and incorporates flow of populace development and marriage length. Nonetheless, on the off chance that we disconnect the marriage choice, then the essential consider the choice run is basically pom, the "extent of married."Billari et al. can exhibit the noteworthiness of social weight by demonstrating how the peril rate of marriage tops around more youthful ages, parallel to crests in social weight. (This model likewise considers age, potential accomplices, and so forth… as elements in deciding social weight notwithstanding pom.)

Notwithstanding social weight, homogeneity elements have been broadly considered in connection to marriage choices. Kalmijn takes a gander at hypotheses of endogamy and homogamy (marriage between people who are racially comparable and socially comparative individually) (1998). There are two classifications of speculations about homogeneous relational unions: characteristic inclinations for marriage applicants, and the obstruction of outsiders. Inclinations for marriage competitors are influenced by financial and social assets, and in addition eccentric inclinations. Outsiders can influence relational unions through social weight, yet have more unpretentious impacts too. For instance, essentially the way a kid was raised can, and no doubt will, influence his or her propensity for socially comparative accomplices. Information gathered has demonstrated that most gatherings (ethnically and financially) have a tendency to wed inside their gathering essentially more than we would anticipate from irregular testing (Kalmijn, 1998). This is a pointer that homogeneity is a consider marriage choices, and capacities as support for the model.

Further, despite the fact that interracial is turning out to be increasingly basic, regardless we see patterns of homogeneity in these relational unions. As per Qian, interracial marriage has a tendency to be instructively homogeneous, showing that people still look for some feeling of likeness in an accomplice (1997). This could, obviously, be ascribed to any number of elements. It is likely that instruction is related with a surreptitiously term that is influencing marriage choices. Be that as it may, for the reasons for this model, we are less intrigued by causation and more keen on connection.

Many reviews have taken a gander at both social weight and intermarriage broadly, and the two have risen as probably the most noticeable and generally examined elements influencing marriage choices. Nonetheless, the two are once in a while examined together in such an unequivocal way, and that is the thing that this model would like to finish. The point is to take two noteworthy figures a marriage choice (closeness and social weight) and analyze their relative impacts on marriage choices. The rest of this paper will inspect the model itself and the marriage choice govern, before going ahead to talk about some preparatory discoveries and conceivable augmentations.


The model's motivation is to model marriage basic leadership utilizing two variables: social weight and likeness. Social weight is displayed by the proportion of wedded people to all people in an associate gathering. Likeness is spoken to by financial contrast (noted as "class distinction"), demonstrated by distinction in pay. For demonstrating purposes, other homogeneity components were excluded (i.e. race) however they are a conceivable (and beneficial) augmentation of the model.

The whole populace is isolated into men and ladies equally. Every individual starts with two qualities: salary and group estimate. Wage is arbitrarily browsed an ordinary dissemination (mean $50,000, standard deviation $10,000), which will decide their class distinction. Group size is predictable over all people and decides the extent of every individual's associate gathering. This will play into social weight. The model likewise starts with an estimation of β social pressure which can differ anywhere in the range of 0 to 1 and is utilized as a part of the marriage-choice ("proposition") underneath.

With every tick of the model, men are requested that "date." This comprises of picking a potential accomplice (any single lady in their associate gathering) and choosing on the off chance that he needs to wed her. There are two calculates that go this choice:

(note that Social Pressure is modeled after Hernes’ mathematical model of social pressure – two factors are used to compute an initial measure of social pressure, which is then weighed with a conversion factor in the equation below)

These two factors are weighted to generate:

If this value (proposal) is greater than a randomly generated number between 0 and 1, then the man “proposes” to the woman and the two marry.

Both class-diff and social-pressure are values between 0 and 1, with higher values corresponding to either more similarity or more social pressure. These two inputs are then taken to a value between 0 and 1 (“proposal”), with higher values of proposal corresponding to more similarity, more social pressure, or both. The logic behind this equation is that both social pressure and similarity are positively correlated with the probability of marriage, and that increasing either will increase the likelihood of getting married.

We begin with a basic experiment to determine the relative effects of class difference and social pressure on marriage likelihood. β(social pressure) is variedfrom 0 to 1 in increments of 0.1 (representing a range from social pressure having no effect on marriage decisions to being the only factor in marriage decisions). Population was kept constant at 1000 total individuals and community size was kept constant at 10 individuals. 50 runs were conducted of each parameter setting to achieve repetition and consistency, and minimize extreme results. Three reporters were measured: the number of married individuals (denoted as “Married Individuals” or “Married Turtles”), average social pressure across all individuals (denoted as “Average Social Pressure”), and the total number of ticks (denoted as “Total Ticks”)[ The model includes two stop conditions: the model either stops when all individuals are married or when ticks=104].A results summary can be found in Appendix B.

II.Results &Analysis

Three determinants were used as independent variables: (i) the final number of married individuals (measured at the end of each run, and averaged over parameters, grouped by beta social pressure); (ii) the average social pressure over all individuals, measured by the ratio of married individuals to all individuals, and then averaged over all ticks each run; (iii) the total number of ticks, measured by the max{104,t*} where t* represents the number of ticks for every individual to get married.

Three different regression models were run for each independent variable, with betasp as the dependent variable in each case –a linear regression, a quadratic regression, and a logarithmic regression. Of the three regressions, the quadratic was the most statistically significant for each dependent variable, yielding the highest F-stat and R2. Full statistical output can be found in Appendix C, but for analysis purposes, the quadratic models have been reproduced below:

For three indicators of marriage, betasp is a statistically significant explanatory variable. More importantly, each indicate the same trend between betasp and marriage. To see this, notice that married individuals directly corresponds to average social pressure – the more married individuals there are, the higher social pressure will be. Additionally, a higher average social pressure (the reporter tracked here) is related to a lower number of total ticks. Since social pressure is averaged over total ticks, the fewer ticks there are, the faster individuals marry, and so the higher social pressure per tick will be. For example, say two runs produced the same total number of married individuals, but Run A completed in half as many ticks than Run B. Then, each individual tick within Run A would have to produce, on average, twice as many married turtles as each tick in Run B. This, averaged over all ticks, would produce a higher average social pressure in Run A relative to Run B.


What the information appears to propose is that marriage rates are most elevated when both elements, similitude and social weight, are weighted similarly. To see this, notice betasp = 1 – betasimilar. Betasp speaks to the weight given to social weight in the marriage choice model, and betasimilar speaks to the weight given to similitude in the marriage choice model (here spoke to by monetary comparability). At the point when betasp is extraordinary, near 0 or 1, the greater part of the marriage choice is impacted by only one variable (similitude when betasp is near 0, social weight when betasp is near 1). At these qualities we can see that the marriage rate is most reduced (as spoken to by a lower number of wedded people, a more drawn out time period for marriage, and less social weight). Prominently, every capacity is amplified (or minimized, on account of aggregate ticks) when betasp ~ 0.5. This demonstrates the marriage rate is most noteworthy when closeness and social weight are weighted similarly.

Promote, it appears to be conceivable that comparability and social weight have a sort of synergistic impact with each other. Come back to the first condition for proposition (repeated underneath for accommodation). Our choice manage is a direct model, so a straight diminishing in one part can be similarly offset by a relating increment in the other segment. Saysimilarity and social weight were totally autonomous of each other yet had a similar relative impact on proposition. If we somehow happened to hold classdiff and socialpressure consistent, changing betasp would not influence proposition. In any case, we rather see a critical increment in marriage rate when similitude and social weight are weighted similarly. We can then place that the two are related, and that maybe there is a concealed collaboration term that is emphatically corresponded with proposition when comparability and social weight are both considered similarly in marriage-basic leadership. The cooperation between homogeneity variables and social weight components is an unexpected outcome that is worth further research to figure out whether it holds any exact weight.

These outcomes could have various ramifications for marriage models. Since an essential analysis indicates noteworthy contrasts in results, a further tweaking of the parameters could produce various conceivable marriage circumstances. The fundamental model can be stretched out by including social, religious, and so on variables to comparability to expand the power of the similitude parameter. Group size can differ crosswise over people and crosswise over time, to all the more precisely model genuine people with changing sizes of associate gatherings. Significantly, exact research can be found on these presumptions – the circulation of financial and social contrasts, the extent of minority to greater part populaces, the changing size of associate gatherings as an individual ages, and so on… This information can be contribution to the model so that the underlying suppositions are as sensible as could reasonably be expected. In the event that trials keep on showing such variety in marriage rate as per betasp, then we can gather a genuine choice run people utilize when choosing whether or not to propose or acknowledge a proposition.

Another pattern to notice, that was not talked about here, is the rate of marriage inside a run. Notwithstanding parameter settings, the quantity of wedded people spikes pointedly comfortable start of the run, when people are still "youthful," and levels off rapidly after that. This fundamental pattern was found in all keeps running, over all betasp values. This demonstrates marriage-basic leadership in the whole populace takes after a similar example paying little heed to parameter settings; singular basic leadership may shift all the more definitely as per parameter settings (bringing about higher or lower general marriage rates), yet the general pattern remains reliable. Charts and further detail can be found in Appendix D.

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In this paper, I have talked about an essential marriage demonstrate that consolidates two elements into basic leadership: comparability and social weight. Past research has demonstrated that both comparability and social weight are huge factors in marriage choices, and this model inspected the relative impacts of each on marriage choices, and the subsequent marriage designs that rise up out of shifting weights of every (similitude and social weight).

The information recommends that marriage rate is most noteworthy when comparability and social weight are weighted similarly. This appears to propose that both have fundamentally the same as impacts on marriage rates. Be that as it may, it likewise proposes that similitude and social weight communicate in a way that their individual impacts are increased when both are considered at the same time. Additionally research is required to figure out whether these outcomes can be imitated with regards to observational information, and if the developing examples from the model can be found in any large scale level marriage designs in "this present reality." in general, however, this model gives a fundamental structure to examining different parts in marriage-basic leadership. The model can without much of a stretch be reached out to incorporate more marriage components, and further research could bring about a marriage-choice run with experimental and hypothetical weight.


A model that demonstrates the factors in deciding who and when people marry. Two factors are considered: social pressure and similarity. We vary the weight on each in the decision rule to determine the impact each has on marriage decisions.


The model begins by creating a population of both men and women (an even 50/50 split). Each agent has a peer group, based off a slider community size. This will play into the social pressure factor. Each agent is also given an income, randomly chosen from a normal distribution (mean $50,000 and standard deviation $10,000). This plays into the similarity factor, and is used to represent overall social class and standard of living.

Men are then asked to “date.” We choose men to carry out this action for modeling purposes; we could have easily asked women to carry out this action to achieve the same results. To date, men choose a single woman from their peer group to be his girlfriend and calculate a value, proposal. Proposal is based off of two factors - class difference and social pressure. Both class difference and social pressure are a value from 0 to 1, with higher values indicating either greater similarity or more social pressure (making the man more likely to want to marry the woman). Class difference and social pressure are weighted differently to produce the final value of proposal (also ranging from 0 to 1).

To determine marriage, this value, proposal, is compared to a random number between 0 and 1. If proposal is greater than, marriage occurs. Otherwise, both the man and woman stay single.

If the agent is still single after dating occurs, they move to a new peer group to try and find another partner that is more suitable for marriage.


To begin with, the user must set all the sliders on the Interface:

  • P stands for population, and indicates the total number of turtles in the model (half of p will be men, half will be women).
  • Community indicates how large of a peer group each turtle will have. The larger the community, the more turtles each agent will have to interact with (more potential partners to choose from, but potentially more social pressure as well)
  • Betasocialpressure indicates how much social pressure will be weighted (1 - betasocialpressure is the weight on similarity).
  • There is one graph on the interface that tracks married-turtles in the model. Using this, you can see a general trend in marriage and the points where marriage levels off and most turtles get married. The plot corresponds to two monitors, married-turtles and single-turtles. These track the exact number of turtles that are married and single at each tick in the model.


The user should try varying the three sliders on the Interface. Varying community has many possible implications - a larger community could make it easier for each turtle to find a potential partner, but a larger community will increase the denominator of social pressure and most likely increase the numerator of social pressure. The overall effect on social pressure is ambiguous, and a larger community could either increase or decrease it.

Varying betasocialpressure will change the weight given to social pressure relative to similarity. This could be used to model the effects of social pressure on marriage, and how people actually think through marriage. If varying betasocialpressure produces vastly different results for larger and smaller values, the results can be compared to historical data on marriage to determine a model for how people actually think through marriage decisions (and how much they weigh external vs. internal factors, with social pressure representing external factors and similarity representing internal factors).


This model has many possible complications.

Changing the decision rule:

  • Adding more factors to similarity i.e. racial difference
  • Adding more factors to the proposal decision rule i.e. innate propensity for marriage
  • Changing the probability of getting married for everyone in the model i.e. “proposal” must exceed a random number between 0.5 and 1, instead of 0 and 1

Changing the agents:

  • Adding a “make-money” feature i.e. each tick, turtles with incomes over $50,000 make $10,000 and turtles with income less than $50,000 lose $10,000 (“the rich get richer and the poor get poorer”).
  • Changing the ratio of men to women - if there are more men than women, it’s not possible for every man to find a partner
  • Varying community size across individuals, and/or changing community size as the agents age. This would affect individual social pressure, and may be more accurate in a real-life context.

If the data is available, it may be fruitful to import actual data about income distribution. This would make the model more accurate regarding class differences.

These, along with many more possibilities, are indicative of the power of this model and its ability to handle multiple extensions.

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This model is loosely based off of the “Wedding Ring,” by Billari et al. I have extended their model by adding a similarity factor and varying the weight given to social pressure and similarity. I based the theoretical work off of previous models studying social pressure and its effect on marriage decisions, and the significance of homogeneity in marriage decisions.


  • Billari, Francesco, Alexia Prskawetz, Belinda Aparicio Diaz, and Thomas Fent. “The ”Wedding-Ring"" Demographic Research 17 (2007): 59-82. Print.
  • Hernes, Gudmund. "The Process of Entry Into First Marriage."American Sociological Review37.2 (1972): 173-82. Print.
  • Kalmijn, Matthijs. "Intermarriage and Homogamy: Causes, Patterns, Trends."Annual Review of Sociology24.1 (1998): 395-421. Print.
  • Qian, Zhenchao. "Breaking the Racial Barriers: Variations in Interracial Marriage Between 1980 and 1990."Demography34.2 (1997): 263-76. Print.
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