Here’s a link to a previous post in the series about the book. Before proceeding to the coverage of the textbook, I thought I should mention that I yesterday read another novel by Wodehouse, and started on a third one. His stuff is awesome – if you’re having trouble finding fiction which is fun and enjoyable to read, you should definitely check out Wodehouse if you haven’t already.
Okay, back to the textbook. When I started out writing this post I thought it would be my last post about the book, but in the end I decided that the post would get too long if I covered all the remaining chapters in this post. So I may or may not cover the rest of the book later. The first topic I’ll cover in this post is intimacy. Some observations from the chapter on that topic:
“Individuals can influence the evolution of an emerging relationship by adjusting the breadth (the number of topics disclosed) and the depth of their self-disclosure (the degree of personal relevance). In addition, nonverbal behaviors (e.g., gaze, touch, body orientation) are expressions that can augment and interact with verbal self-disclosures to influence intimacy in a relationship […] Self-disclosure has been found to account for just below half of the variance in ratings of couples’ level of intimacy […] To contribute to the development of intimacy in a relationship, an individual’s responses have to demonstrate concern for the discloser. A response must be sincere and immediate, capture the content of the original communication, and meet the need of the discloser […]. Responsiveness has been found to play an important role in disclosure reciprocity, liking, and closeness in relationships […]. Recently, researchers have conceptualized responsiveness as a process whereby a person communicates understanding, validation, and caring in response to a partner’s self-disclosure […] In personal relationships, receiving validation and acceptance can often take on a self-esteem maintaining or protective function, in that individuals often seek to confirm their self-concept through the responses of others […]. Reis and Shaver (1988) argued that the speaker’s perception and judgment of the listener’s response as understanding, validating, and caring are important factors in the experience of intimacy, above and beyond the listener’s actual responsiveness. […] According to Reis and Shaver (1988), intimacy is an interpersonal, transactional process with two principal components: self-disclosure and partner responsiveness. Intimacy can be initiated when one person communicates personally relevant and revealing information to another person. […] For the intimacy process to continue, the listener must emit emotions, expressions, and behaviors that are both responsive to the specific content of the disclosure and convey acceptance, validation, and caring toward the individual disclosing. For the interaction to be experienced as intimate by the discloser, he or she must perceive both the descriptive qualities (understanding of content) and evaluative qualities (validation and caring) of the response. […] a consistent finding is that individuals with an insecure attachment style are less responsive than more securely attached individuals according to both objective third-party ratings and subjective reports”.
“A notable tenet of existing models of intimacy […] is that intimacy is achieved when Partner A self-discloses and feels validated, cared for, and understood by Partner B’s attempts at responsiveness. Although we agree that this model describes the intimacy process, we believe that in many ways it is decidedly one-sided. Is the experience of intimacy only achieved when one feels that a relationship partner is responding to one’s needs? We argue that an individual may experience intimacy while providing understanding, care, and validation, as well as while receiving it. In other words, Partner B’s feelings of intimacy may match Partner A’s, even though A is the one being validated.” (I should note that I have made a similar argument during conversations with a good friend, and that I share the opinion of the authors that this aspect is important as well).
“Nonverbal cues have been thought to contribute to intimacy in two ways. First, they communicate specific emotional messages, which may stand alone or be considered along with concurrent verbal messages. Second, nonverbal cues may intensify emotions that are experienced during intimate interactions […] nonverbal cues can increase the likelihood of an intimate outcome, whereas others may decrease the possibility. Specifically, smiling, eye contact, and physical proximity tend to engross the listener, especially if the behaviors amplify the speaker’s words […] Observational studies have shown that husbands and wives use different nonverbal behaviors when delivering positive and negative messages” [I’ll again remind people reading along here that ‘observational studies’ in this context means studies where they’ve actually observed people interacting with each other, instead of e.g. relying on self-reports].
“Self-disclosures have been classified into two types: factual–descriptive (e.g., personal information, such as the number of one’s siblings) versus emotional–evaluative (e.g., feelings about those siblings […]). Emotional disclosures have been shown to be more important to intimate interactions […] Research has shown that more emotional information is transmitted nonverbally than verbally […] Nonverbal cues are often better indicators of feelings, emotions, and attitudes than are words […] when there is a discrepancy between verbal and nonverbal messages, people tend to believe the nonverbal ones […] There is evidence that nonverbal communication affects the outcomes of a wide variety of relationships. In married couples nonverbal behavior is more likely than verbal behavior to distinguish between distressed and undistressed pairs […]. Poor nonverbal skills have been shown to be associated with less satisfying relationships for married couples […], romantic partners […], roommates […], children’s peer relationships […], and adults in general […] To create intimacy in an interaction, several nonverbal processes must occur. First, the discloser must display appropriate emotional nonverbal cues. Second, the listener must be able to decode them accurately. Third, the listener must then respond with appropriate nonverbal expressiveness. Finally, the original discloser must perceive these expressive cues accurately. In any interaction, this process is repeated continuously, and thus there is substantial room for error. […] A wealth of literature supports the conclusion that nonverbal skills are essential to relationship outcomes. Few studies, however, have focused on issues related to mechanism: How do nonverbal behaviors and skills affect relationship outcomes and processes?”
The next chapter is about ‘Social Networks and Personal Communities’. A few observations from the chapter:
“Generally, there is a shortage of longitudinal material on what might be termed the routine natural history of personal communities – the ways in which different relationships unremarkably alter over time, some becoming more central in people’s lives and others becoming of lesser consequence. Importantly, too, the studies there have been have tended to be short rather than long term. […] [A few exceptions exist, and what] these studies indicate, not surprisingly, is that social change routinely occurs across the life course, affecting people’s social location and in turn the sets of relationships they sustain. Although based on a shorter term study, Morgan and his colleagues […] made the important point that although the personnel making up an individual’s network may alter over time, the properties of the network itself can be more stable. In this study of widows, a core segment of key relationships remained relatively constant over the course of the research, whereas relationships that were more peripheral waxed and waned. Thus, as Morgan, Neal, et al. (1997) expressed it, “the stability of the aggregate properties in personal networks is much greater than the stability of the membership in these networks” (p. 22).”
The next chapter, on ‘Relationships in home and community environments’, is terrible, so I won’t talk about that here. Instead I’ll end the coverage here with some observations from the chapter about ‘Relationships, Culture, and Social Change’:
“There are several theoretical reasons for studying relationships across cultures. First, there may be variation in the relative magnitude of different relationship phenomena. […] Second, culture can have a moderating impact on the association between individual-level factors (such as personality) and various relationship phenomena. […] Finally, even when there are strong universal relational phenomena consistent across cultures, the ways in which these influence actual behaviors may differ. As we note later, individuals may feel passionately for each other in some cultures, but their passion may have relatively little impact on who they end up with as partners. Instead, pragmatic considerations (family pressures, but also basic economic realities) may have a far more significant role in partner choice.”
“In the last 2 decades a number of major international studies have sought to differentiate cultures empirically on the basis of their scores on key values. The most influential of these has been the dimensions that arose from Hofstede’s (1980) seminal study of IBM employees of 50 nations and more than one hundred thousand respondents. In this study, Hofstede (1980) concluded that cultures vary along four dimensions: power distance (deference to authority), masculinity–femininity (relative emphasis on achievement or interpersonal harmony), uncertainty avoidance (stability and “planning ahead”) and individualism–collectivism (which concerns the relationship between the individual and the group). Individualism–collectivism has been the most widely researched of these dimensions”
“Most research into PR assumes that close relationships partners are chosen rather in the manner of an individual shopping in a supermarket, with individuals free to choose from a wide variety of products, in a multiplicity of shapes and sizes, from a range of different origins. […] In reality, this image is unlikely to be accurate even in the most individualistic of societies. Personal reputation, availability of social networks, and even opportunities to travel and shop around are basic limiters of choice in most cultures. However, in some cultures there is little opportunity to form any kind of romantic relationship outside of the most tightly restricted range. Indeed, we can plot a continuum ranging from those cultures in which partner choice is rarely restricted (usually those cultures where mate selection studies are conducted) to those cultures where partner choice might be prescribed as early as birth […]. Across the world, the majority of marriages are by arrangement, usually with the aid of matchmakers or relatives (Ingoldsby, 1995). [I dislike having to rely on a 20-year old study here, but I would caution people who think that just because it’s 20 years old, it’s probably obsolete and the results worthless. For example the relationship between ‘modernization’ and marriage is, complicated – see e.g. this paper (“No empirical support was found for any of our hypotheses which link the level of modernization to the risk of divorce”).] Marriage in such cultures is not regarded as a union of two individuals but of two families, with the families likely to be similar in terms of values, customs, and norms. […] Arranged relationships can be seen as invaluable in cementing family liaisons, helping build new economic ties, and maintaining the influence of the extended network on the new couple. Because such arrangements are of such significance to the wider family, opportunities for Western-style dating and partner choice outside of those approved as eligible is likely to be highly restricted”.
“Because partner choice is restricted among some cultures and cultural groups, the role of love in the choice of marital partner is also likely to vary across the world. There is strong evidence that Western beliefs in the significance of love for marriage may not be universal […]. In cultures where marriages are arranged, love is often assumed to grow out of marriage, rather than to be a motivator for the formation of a particular relationship […] because of the importance to family honor and economic success of an “appropriate” relationship match, in societies where marriage is arranged love is most likely to be sanctioned between only certain partners.”
“In those societies in which arranged marriages dominate, divorce or even separation are often difficult or impossible […]. Although marital dissatisfaction undoubtedly exists here as elsewhere, it is important not to exaggerate the unhappiness felt in many more traditional cultures. Instead, in such societies, different expectations about marriage may lead to different kinds of expectations as to what is – and is not – to be obtained from a marital relationship. […] One enduring debate has been the extent to which free-choice matches are happier than arranged marriages. This is difficult to assess because expectations for marriage differ, and in those societies in which arranged marriages predominate divorce is often difficult. To address this issue Xiaohe and Whyte (1990) tested a representative probability sample of 586 ever-married women in the Sichuan Province of mainland China. Their data suggested that women in arranged marriages were consistently less satisfied than those that had chosen their own partners. Controlling for a large number of measures (including age at marriage and family income), their study did suggest that freedom of mate choice was the strongest predictor of marital quality.”
“There are significant culture differences not only in network size and sources of support but also in network utilization. In the West, individuals are expected to solicit help from others actively […], whereas in Eastern cultures a greater sensitivity to others’ needs and feelings may make help seeking less necessary […]. In collectivists cultures where social connectedness is high, help is expected to be voluntarily provided, and asking for help may be regarded as socially demeaning”.
“Buss, Shackleford, Kirkpatrick, and Larsen (2001) reviewed partner preferences over a more than 50-year period using the same instrument (1939, 1956, 1967, 1977, 1984, and 1996). Over this time period, they found important generational shifts in mate preferences. Both men and women increasingly valued mutual attraction and love, education and intelligence, sociability and good looks, and decreased their stress on refinement, neatness, and chastity. Men increasingly valued similar educational background and good financial prospects and decreasingly valued a woman being a good cook and housekeeper, whereas women placed less value on ambition and industriousness. Partner preferences across genders became generally similar over this time period, with men’s preferences moving toward those of women.”
“The aim of this article is to integrate empirical research on divorce risks in Europe and to explain the variation of empirical findings between European countries by the different levels of modernization and differences in the strength of marriage norms. We focus on the effects of premarital cohabitation, the presence of children, and the experience with parental divorce on marital stability. More than 260 studies on divorce risks could be identified, and 120 were used for further meta-analytical examinations. We show that there is considerable heterogeneity of divorce risks within as well as between countries. Explaining the variation of effect sizes between European countries, it could be shown that in countries where more rigid marriage norms prevail cohabitation has a stronger effect on marital stability than in countries where marriage norms are weaker. Furthermore, the lower the divorce barriers are, the weaker is the association between the parental divorce and the divorce risk of the offspring.”
Some data and results from the paper (click tables and figures to see them in a higher resolution):
The table shows the estimated effect sizes of premarital cohabitation on the divorce risk in various European countries; a positive effect size indicates a higher likelihood of divorce among couples who lived together before they got married, whereas a negative effect size indicates a smaller divorce risk for couples who did not cohabitate before they got married. They note in the paper that, “The European overall effect indicates a positive relationship between cohabitation and the risk of divorce, that is, cohabiting couples have a 33 per cent higher risk to divorce than couples who do not share a common household before marriage.” However the effecs are highly heterogenous across countries, and more specifically they find that: “In countries in which traditional marriage norms are strongly institutionalized, cohabitation has a stronger effect than in countries in which marriage norms are weaker.” The institutional framework is important. The Q-statistic is a heterogeneity-measure – read the paper if you want the details..
What about children? Here’s a brief summary:
Effect sizes are almost universally negative (children = smaller risk of divorce) and a lot of them are highly significant (more than half of them are significant at the 1% confidence level). As they note, “The presence of children strongly decreases the risk of divorce”. Note that the effect sizes vary but tend to be large; in the Netherlands, the country with the largest effect size, married couples with children are 70% less likely to divorce than are couples without children. The average estimated effect size is 50% so this is a huge effect. However I would be cautious about making a lot of inferences based on this finding without at the very least having a closer look at the studies on which these results are based; for example it’s unclear if they have taken into account that there may be unobserved heterogeneity problems playing a role when comparing married couples with- and without children here; lots of marriages break up early on (using Danish data I have previously estimated that once the marriage has lasted 9 years, half of the total divorce risk the Danish couple confronted ex ante will basically have been accounted for; i.e. the total risk that you’ll divorce your partner during the first 9 years is as big as is the risk that you’ll do it at any point after the 9th year of marriage – see the last figure in this post), and it does not seem unlikely e.g. that sampled marriages involving children may, ceteris paribus, have lasted a longer time on average than have sampled marriages without children (most European couples get married before they have children so the likelihood that a couple will have children is positively correlated with the marriage duration), meaning that these marriages were less likely to get broken up, regardless of the children. If they conditioned on marriage duration when calculating these effects this particular problem is dealt with, but I don’t know if they did that (and I’m not going to go through all those studies in order to find out..) and there may be a lot of other ways in which marriages with and without children differ; differences that may also relate to divorce probability (education, income, labour market status, …). Note that the fact that the studies included in the meta-study are longitudinal studies does not on its own solve the potential ‘duration problem’ (/selection problem); you can easily follow two couples for the same amount of time and still have radically different (ex ante) divorce likelihoods – and comparing unadjusted (group?) hazard rates and making conclusions based on those seems problematic if you have selection issues like these. Researchers aren’t stupid, so the studies here may all have taken care of this particular potential problem. But I’m sure there are problems they haven’t handled. Caution is warranted – part of the estimated ‘children effect’ is likely not to go through the children at all.
How about the parents? How does the fact that your parents got divorced impact your own likelihood of divorce?
“Nearly all the reported effect sizes indicate positive associations between the stability of the parental marriage and the stability of children’s marriage”. There are huge cross-country differences – in Italy an individual whose parents got divorced is almost three times as likely to get divorced him/herself as is an individual whose parents did not divorce, whereas the risk increase in Poland amounts to only (a statistically insignificant) 14%.
Lastly, I’ll note that:
“No empirical support was found for any of our hypotheses which link the level of modernization to the risk of divorce. A least with respect to the divorce risk, we considered the level of socioeconomic development not to be an important macro-variable. Also, we could not find any significant relationships between the strength of divorce barriers and the effect of children on marital stability.”
I would not have expected these results if you’d asked me beforehand. Then again e.g. the differences in socioeconomic development among the countries included here are not that big, so it may just be a power issue.
“The share of one-person households in the U.S. maintained by men ages 15 to 64 rose to 34% in 2012, up from 23% in 1970, according to a Census report on the status of families released Tuesday. For women of the same age, this figure actually dropped slightly, to 30% in 2012 from 31% in 1970.
The findings may reflect, in part, the sharp increase in divorce rates in the U.S. throughout the 1970s, Census said. The dominant living arrangement for children following their parents’ divorce is custody by mothers.”
I would have preferred to read the actual Census report and I did go have a look for it; but when I click the pdf link to the report in question at the census site all I get is an error message (link) – they seem to have put up a corrupt link. Annoying. Here are some related Danish numbers which I blogged a while ago. Although the 2012 report doesn’t seem to be available, there’s a lot of 2009-2011 data on related matters here. I messed around a little with that data – below some stuff from that source:
Naturally there’s a big gender disparity; at the age range of 24-29, 89.1% of males have never married whereas only 80,7% of the females have never married. For people in the 25-29 year age range 64% of males and 50,1% of females have never married. You’d expect the numbers to converge somewhat ‘over time’ (/as people get older) and they do, but not until we reach the age group of 55-64 year olds do the proportion of females who have never married surpass the proportion of males who have not (and these numbers are quite small – less than 9% have never married at that age, both when looking at males and females).
Higher earnings seem to confer an advantage when it comes to minimizing the risk of never getting married, which is of course a big surprise. For example, of the 45-49 year old people with a reported income of $25,000 to $39,999 17,6% of them have never married, whereas the corresponding number for people with an income of $40,000-75,000 is 11,5%. For people with incomes in the $75,000-$100,000 range the number is 5.5%, and incidentally the number of 45-49 year olds with incomes above $100k who’ve never married is also 5,5%. The relationship is not perfectly linear, but it’s clear that people with higher earnings have a higher likelihood of getting married. Incidentally almost a third of people in that age range who reported annual earnings less than $5000 have never married (29.2%).
The numbers above are from the first third of the first document. There’s a lot of data available here if you’re curious.
ii. Global Reality of Type 1 Diabetes Care in 2013. Not much to see here – here’s why I bookmarked it:
“from a global perspective, the most common cause of death for a child with type 1 diabetes is lack of access to insulin (2). Yet, this is not just a problem for low-income countries, with one recent study in the U.S. noting that discontinuation of insulin therapy represents the leading precipitating cause of diabetic ketoacidosis (3). Indeed, lack of insulin explained 68% of such episodes in people living in an inner-city setting, with approximately one-third of people reporting a lack of financial resources to buy insulin and eking out their insulin supplies.”
We’re talking about the United States of America, a very rich country – and in fact the country in the world with the highest health care expenditures. And still you have type 1 diabetics who go into ketoacidosis because they can’t afford their drugs. That’s messed up. Note that low medical subsidies to type 1s may not necessarily be cost saving at a systemic level as hospital admissions are very expensive; based on the average estimates at the link and these length of stay estimates, a back of the envelope estimate of the average cost of a DKA-related hospital admission would be $5.500. This estimate is probably too low as this study (which I may blog in more detail later) estimated non-compliance-related DKA-admissions to cost on average roughly $7.500 (and the non-compliance admissions were actually significantly cheaper than the other admissions on a per-case basis). To put this estimate into perspective, the mean annual cost of intensive diabetes care per diabetic patient in the U.S. is $4,000 (same link).
iii. Related to i., but I figured it deserved to be linked to separately: A theory of marriage, by Gary Becker.
iv. Some maps illustrating racial segregation patterns in the US. Don’t miss the sixth map of Detroit. The one of Saint Louis is also…
v. Vocabulary.com. I haven’t used it much yet, so I don’t really know if it’s any good – but it looks interesting and I’ve missed such a resource. I sometimes feel a bit guilty about not working harder on improving my vocabulary, especially on account of the fact that I’ve basically ended up only speaking two languages – I used to speak French reasonably well, but that’s many years ago and at this point I’d rather spend time improving my English than spend a lot of effort on a third language which most likely will only be of very limited use to me.
“Robots offer new possibilities for investigating animal social behaviour. This method enhances controllability and reproducibility of experimental techniques, and it allows also the experimental separation of the effects of bodily appearance (embodiment) and behaviour. In the present study we examined dogs’ interactive behaviour in a problem solving task (in which the dog has no access to the food) with three different social partners, two of which were robots and the third a human behaving in a robot-like manner. The Mechanical UMO (Unidentified Moving Object) and the Mechanical Human differed only in their embodiment, but showed similar behaviour toward the dog. In contrast, the Social UMO was interactive, showed contingent responsiveness and goal-directed behaviour and moved along varied routes. The dogs showed shorter looking and touching duration, but increased gaze alternation toward the Mechanical Human than to the Mechanical UMO. This suggests that dogs’ interactive behaviour may have been affected by previous experience with typical humans. We found that dogs also looked longer and showed more gaze alternations between the food and the Social UMO compared to the Mechanical UMO. These results suggest that dogs form expectations about an unfamiliar moving object within a short period of time and they recognise some social aspects of UMOs’ behaviour. This is the first evidence that interactive behaviour of a robot is important for evoking dogs’ social responsiveness.”
From the discussion:
“The aim of this study was to investigate whether dogs are able to differentiate agents on the basis of their behaviour and show social behaviours toward an UMO (Unidentified Moving Object) if the agent behaves appropriately in an interactive situation. In order to observe such interaction we modelled an experimental situation in which the dog is faced with inaccessible food. Miklósi et al  showed that in this case dogs increase their looking time at a human helper and show gaze alternation between the inaccessible food and the human. These observations have been replicated by Gaunet  and Horn et al , and the authors implicated that the dogs’ behaviour reflects communicative intentions. The present experiment showed that these behaviour features also emerge in the dogs while they are interacting with an UMO, moreover the onset of these behaviours is facilitated by the social features of the UMO: Dogs look longer and show more gaze alternation if the UMO carries eyes, shows variations in its path of movement, displays goal-directed behaviour and contingent reactivity (reacts to the looking action of the dog by retrieving the inaccessible food item).”
If you’re curious about how they actually did this stuff, don’t miss the neat video towards the end.
I have a paper deadline approaching, so I’ll be unlikely to blog much more this week. Below some links and stuff of interest:
“we surveyed the faculty and trainees at MD Anderson Cancer Center using an anonymous computerized questionnaire; we sought to ascertain the frequency and potential causes of non-reproducible data. We found that ~50% of respondents had experienced at least one episode of the inability to reproduce published data; many who pursued this issue with the original authors were never able to identify the reason for the lack of reproducibility; some were even met with a less than “collegial” interaction. […] These results suggest that the problem of data reproducibility is real. Biomedical science needs to establish processes to decrease the problem and adjudicate discrepancies in findings when they are discovered.”
ii. The development in the number of people killed in traffic accidents in Denmark over the last decade (link):
For people who don’t understand Danish: The x-axis displays the years, the y-axis displays deaths – I dislike it when people manipulate the y-axis (…it should start at 0, not 200…), but this decline is real; the number of Danes killed in traffic accidents has more than halved over the last decade (463 deaths in 2002; 220 deaths in 2011). The number of people sustaining traffic-related injuries dropped from 9254 in 2002 to 4259 in 2011. There’s a direct link to the data set at the link provided above if you want to know more.
iii. Gender identity and relative income within households, by Bertrand, Kamenica & Pan.
“We examine causes and consequences of relative income within households. We establish that gender identity – in particular, an aversion to the wife earning more than the husband – impacts marriage formation, the wife’s labor force participation, the wife’s income conditional on working, marriage satisfaction, likelihood of divorce, and the division of home production. The distribution of the share of household income earned by the wife exhibits a sharp cliff at 0.5, which suggests that a couple is less willing to match if her income exceeds his. Within marriage markets, when a randomly chosen woman becomes more likely to earn more than a randomly chosen man, marriage rates decline. Within couples, if the wife’s potential income (based on her demographics) is likely to exceed the husband’s, the wife is less likely to be in the labor force and earns less than her potential if she does work. Couples where the wife earns more than the husband are less satisfied with their marriage and are more likely to divorce. Finally, based on time use surveys, the gender gap in non-market work is larger if the wife earns more than the husband.” […]
“In our preferred specification […] we find that if the wife earns more than the husband, spouses are 7 percentage points (15%) less likely to report that their marriage is very happy, 8 percentage points (32%) more likely to report marital troubles in the past year, and 6 percentage points (46%) more likely to have discussed separating in the past year.”
These are not trivial effects…
iv. Some Khan Academy videos of interest:
“Relative to developed countries, there are far fewer women than men in India. Estimates suggest that among the stock of women who could potentially be alive today, over 25 million are “missing”. Sex selection at birth and the mistreatment of young girls are widely regarded as key explanations. We provide a decomposition of missing women by age across the states. While we do not dispute the existence of severe gender bias at young ages, our computations yield some striking findings. First, the vast majority of missing women in India are of adult age. Second, there is significant variation in the distribution of missing women by age across different states. Missing girls at birth are most pervasive in some north-western states, but excess female mortality at older ages is relatively low. In contrast, some north-eastern states have the highest excess female mortality in adulthood but the lowest number of missing women at birth. The state-wise variation in the distribution of missing women across the age groups makes it very difficult to draw simple conclusions to explain the missing women phenomenon in India.”
A table from the paper:
“We estimate that a total of more than two million women in India are missing in a given year. Our age decomposition of this total yields some striking findings. First, the majority of missing women, in India die in adulthood. Our estimates demonstrate that roughly 12% of missing women are found at birth, 25% die in childhood, 18% at the reproductive ages, and 45% die at older ages. […] There are just two states in which the majority of missing women are either never born or die in childhood (i e, [sic] before age 15), and these are Haryana and Rajasthan. Moreover, the missing women in these three states add up to well under 15% of the total missing women in India.
For all other states, the majority of missing women die in adulthood. […]
Because there is so much state-wise variation in the distribution of missing women across the age groups, it is difficult to provide a clear explanation for missing women in India. The traditional explanation for missing women, a strong preference for the birth of a son, is most likely driving a significant proportion of missing women in the two states of Punjab and Haryana where the biased sex ratios at birth are undeniable. However, the explanation for excess female deaths after birth is far from clear.”
I’ve now finished the book. I must say that I’m a bit disappointed but thinking about it this is likely mostly due to the huge variation in the quality of the material here; some of it is really great (I’ve tried to cover that stuff here), some of it is downright awful. If you’re interested in this kind of stuff, you may also like this previous post of mine (I liked that book better).
Below I’ve tried to pick out the good stuff from chapters 10-14 (there’s quite a bit of not-very-good-stuff as well). As always, you can click on the figures/tables to see them in a higher resolution:
“Looking at the intrinsic–extrinsic dimension of vocational satisfaction, researchers have found that people with high neuroticism scores are less likely to feel that their jobs are intrinsically rewarding. Perhaps for this reason, neuroticism is negatively related to job satisfaction; by contrast, people high in the traits of conscientiousness and extraversion are more satisfied in their jobs (Furnham, Eracleous, & Chamorro-Premuzic, 2009; Judge, Heller, & Mount, 2002; Seibert & Kraimer, 2001).
The relationship between personality and job satisfaction works both ways. In one longitudinal study of adults in Australia, although personality changes predicted changes in work satisfaction, changes in personality were also found to result from higher job satisfaction. Over time, workers who were more satisfied with their jobs became more extraverted (Scollon & Diener, 2006).
People’s affect can also have an impact on the extent to which they perceive that there is a good fit between their work-related needs and the characteristics of the job. People who tend to have a positive approach to life in general will approach their work in a more positive manner, which in turn will lead to a better person–environment fit (Yu, 2009). […]
The Whitehall II Study, a longitudinal investigation of health in more than 10,300 civil employees in Great Britain, provides compelling data to show the links between workrelated stress and the risk of metabolic syndrome (Chandola, Brunner, & Marmot, 2006). Carried out over five phases from 1985 to 1997, the study included measurements of stress, social class, intake of fruits and vegetables, alcohol consumption, smoking, exercise, and obesity status at the start of the study. Holding all other factors constant and excluding participants who were initially obese, men under high levels of work stress over the course of the study had twice the risk of subsequently developing metabolic syndrome. Women with high levels of stress had over five times the risk of developing this condition.
More recent research suggests that Whitehall II men who reported higher justice at work (such as perceived job fairness) had a far lower risk of metabolic syndrome compared with men who experienced lower work justice (Gimeno et al., 2010). For women, stress encountered at work independently predicted Type 2 diabetes, even after controlling for socioeconomic position and stressors unrelated to work (Heraclides, Chandola, Witte, & Brunner, 2009). […]
When work–family conflict does occur, it takes its toll on the individual’s physical and mental health, causing emotional strain, fatigue, perception of overload, and stress (van Hooff et al., 2005). There are variations in the extent and impact of work–family conflict, however, and not all workers feel the same degree of conflict. Conflict is most likely to occur among mothers of young children, dual-career couples, and those who are highly involved with their jobs.Workers who devote a great deal of time to their jobs at the expense of their families ultimately pay the price in terms of experiencing a lower overall quality of life (Greenhaus, Collins, & Shaw, 2003). There are higher levels of work-family conflict among those employed in the private sector than those employed in the public sector (Dolcos & Daley, 2009).
Age also plays into the work–family conflict equation. Younger workers (under age 45) typically experience more conflict than older workers (46 and older); though when older workers experience conflict the effects seem to be stronger (Matthews, Bulger, & Barnes-Farrell, 2010). […]
Overall, workers over the age of 55 are nearly half as likely to suffer a nonfatal injury as those who are 35 years and younger, and about half as likely to suffer death due to a work-related injury. However, when older workers (55–64) must miss work due to injury or illness, they spend twice as many days away from work (12) per year than do younger workers (25–34) (Bureau of Labor Statistics, 2010c). […]
Few retirees show a ‘‘crisp’’ pattern of leaving the workplace in a single, unreversed, clear-cut exit. Most experience a ‘‘blurred’’ exit in which they exit and reenter the workplace several times. They may have retired from a long-term job to accept bridge employment, such as an insurance agent who retires from the insurance business but works as a crossing guard or server at a fast-food restaurant. Other workers may retire from one job in a company and accept another job performing another role in the same company.
Workers who have a long, continuous history of employment in private sector jobs tend not to seek bridge employment because they typically have sufficient financial resources (Davis, 2003). In general, involvement in bridge employment is strongly related to financial need. […]
about 17% of the 65 and older population are still considered to be in the labor force, meaning that they are either working or actively seeking employment. Virtually all of those 75 years and older (93%) have ended their full-time participation in the nation’s workforce (Bureau of Labor Statistics, 2010b). However, many remain employed on a part-time basis; nearly half of all men and 61% of all women 70 years and older engage in some paid work (He et al., 2005). […]
Retirement is in many ways a 20th-century phenomenon (Sterns & Gray, 1999). Throughout the 1700s andmid-1800s very few people retired, a trend that continued into the 1900s; in 1900 about 70% of all men over 65 years were still in the labor force. […] Attitudes toward retirement were largely negative in the United States until the mid-1960s because lack of employment was associated with poverty. People did not want to retire because their financial security would be placed at risk. However, with increases in earnings and Social Security benefits, retirement began to gain more acceptance. […]
The transition itself from work to retirement seems to take its toll on marital satisfaction when partners have high levels of conflict. The greatest conflict is observed when one partner is working while the other has retired. Eventually, however, these problems seem to subside, and after about 2 years of retirement for both partners, levels of marital satisfaction once again rise (Moen, Kim, & Hofmeister, 2001). [So large spousal age differences would seem to predict higher levels of conflict, US…] […]
Approximately 90% of adults who complete suicide have a diagnosable psychiatric disorder. The most frequent diagnoses of suicidal individuals are major depressive disorder, alcohol abuse or dependence, and schizophrenia. Among suicidal adults of all ages, the rates of psychiatric disorders are very high, ranging from 71% to over 90%.
Each year, approximately 33,000 people in the U.S. population as a whole die of suicide. The majority are ages 25 to 54 (Xu et al., 2010). The age-adjusted suicide rate in the United States of all age, race, and sex groups is highest for all demographic categories among White males aged 85 and older at about 48 suicide deaths per 100,000 in the population (Centers for Disease Control and Prevention, 2010f). […]
Typically, nursing homes are thought of as permanent residences for the older adults who enter them, but about 30% of residents are discharged and able to move back into the community after being treated for the condition that required their admission. About one quarter of people admitted to nursing homes die there, and another 36% move to another facility (Sahyoun, Pratt, Lentzner, Dey, & Robinson, 2001). [I found this to be very surprising and would love to see some Danish numbers…, US] […] As of 2008, there were approximately 15,700 nursing homes in the Unites States with a total of over 1.7million beds, 83% of which were occupied (National Center for Health Statistics, 2009). […]
In 2008 [Medicaid] provided health care assistance amounting to $344.3 billion. Nursing homes received $56.3 billion from Medicaid in 2008. Together Medicare and Medicaid (federal and state) financed $813.5 billion in health care services in 2008, which was 34% of the nation’s total health care bill of $2.3 trillion (private and public funding combined) and 82% of all federal spending on health (Center for Medicare and Medicaid Services, 2010b). […]
deficiencies in nursing homes remain a significant problem, limiting severely the quality of care that many residents receive. Continued reporting of these deficiencies, monitoring by government agencies, and involvement of family members advocating for residents are important safeguards. If you have a relative in a nursing home, it is important for you to be aware of these problems and vigilant for ways to prevent them from affecting your relatives. […] Although there is a relatively small percentage overall of people 65 and older living in nursing homes, the percentage of older adults who are institutionalized increases dramatically with age. As of 2004 (the most recent date available), the percentages rise from 0.9% for persons 65 to 74 years to 3.6% for persons 75 to 84 years and 13.9% for persons 85+ (Federal Interagency Forum on Age-Related Statistics, 2009). […]
Alzheimer’s disease is found in nearly half of all nursing home residents (45% in 2008) […] 56.8% of nursing home residents are chairbound, meaning that they are restricted to a wheelchair. Despite the large number of residents with Alzheimer’s disease, only 5% of nursing homes have special care units devoted specifically to their care (Harrington, Carrillo, & Blank, 2009). […] Nearly two thirds (65.2%) of residents receive psychotropic medications, including antidepressants, antianxiety drugs, sedatives and hypnotics, and antipsychotics (Harrington et al., 2009). […] A study of the daily life of residents conducted in 2002 revealed that, as was the case in the 1960s, residents spend almost two thirds of the time in their room, doing nothing at all (Ice, 2002). Thus, for many residents, there are simply not enough activities in the average nursing home (Martin et al., 2002). […]
In a dying person, the symptoms that death is imminent include being asleep most of the time, being disoriented, breathing irregularly, having visual and auditory hallucinations, being less able to see, producing less urine, and having mottled skin, cool hands and feet, an overly warm trunk, and excessive secretions of bodily fluids (Gavrin & Chapman, 1995). An older adult who is close to death is likely to be unable to walk or eat, recognize family members, in constant pain, and finds breathing to be difficult. A common syndrome observed at the end of life is the anorexia-cachexia syndrome, in which the individual loses appetite (anorexia) and muscle mass (cachexia). The majority of cancer patients experience cachexia, a condition also found commonly in patients who have AIDS and dementia. In addition to the symptoms already mentioned, patients who are dying are likely to experience nausea, difficulty swallowing, bowel problems, dry mouth, and edema, or the accumulation of liquid in the abdomen and extremities that leads to bloating. […]
Marital status and education are two significant predictors of mortality. The age-adjusted death rate for those who never married is substantially higher than for those who were ever married, even taking into account the higher mortality of those who are widowed and divorced. The advantage holds for both men and women across all age groups of adults ages 15 and older (Xu et al., 2010). Educational status is also related to mortality rate. In all age groups, those with a college education or better have lower mortality rates. […] Not only the level of occupation, but also the pattern of jobs people hold throughout adulthood, are related to mortality rates. The risk of mortality is lower in men who move up from manual to professional or managerial-level occupations (House, Kessler, Herzog, & Mero, 1990; Moore & Hayward, 1990). Men who hold a string of unrelated jobs have higher rates of early mortality than those with stable career progressions (Pavalko, Elder, & Clipp, 1993). […]
Across all countries studied by the World Health Organization, the poor are over four times as likely to die between the ages of 15 and 59 as are the nonpoor (World Health Organization, 2009). […]
The majority of patients in SUPPORT [‘Study to Understand Prognoses and Preferences for Outcomes and Risks of Treatments’ – US] stated that they preferred to die at home; nonetheless, most of the deaths occurred in the hospital (Pritchard et al., 1998). Furthermore, the percentage of SUPPORT patients who died in the hospital varied by more than double across the five hospitals in the study (from 29 to 66%). The primary factor accounting for the probability of a patient dying in the hospital rather than at home was the availability of hospital beds. Later studies in countries such as Great Britain, Belgium, and the Netherlands have confirmed that place of death varies according to availability of hospital beds rather than any specific characteristics of patients or wishes of their families (Houttekier et al., 2010). […]
Identity processes may provide a means of maintaining high levels of well-being in the face of less than satisfactory circumstances. Through identity assimilation, people may place a positive interpretation on what might otherwise cause them to feel that they are not accomplishing their desired objectives. The process of the life story, through which people develop a narrative view of the past that emphasizes the positive, is an example of identity assimilation as it alters the way that people interpret events that might otherwise detract from self-esteem (Whitbourne et al., 2002). For instance, older psychiatric patients minimized and in some cases denied the potentially distressing experience of having spent a significant part of their lives within a state mental hospital. Therefore, they were not distressed in thinking back on their lives and past experiences (Whitbourne & Sherry, 1991). People can maintain their sense of subjective well-being and can portray their identity in a positive light, even when their actual experiences would support less favorable interpretations.”
I’ve read chapters 7-9 today so far. Some stuff from those chapters:
“In using written language, older adults may experience deficits in retrieval that can lead to spelling errors for words they once knew (Burke, 1997). […] slower cognitive processes may also have an effect on the complexity of grammatical structures that older adults use. As you form sentences, you must keep one clause in mind while you compose the next one, a process that places demands on your working memory. As we saw in Chapter 6, working memory undergoes significant changes with age. Consequently, compared with young adults, older adults speak in simpler sentences (Kemper, Marquis, & Thompson, 2001). Their writing also becomes simpler, in both the expression of ideas and the use of grammatical complexity (Kemper, Greiner, Marquis, Prenovost, & Mitzner, 2001). Thus, although older adults retain their knowledge of grammatical rules (a form of semantic memory), declines in working memory can cause older adults to lose track of what they mean to say while they are saying it.
On the positive side, their greater experience with language gives older adults the potential to compensate for other cognitive changes that affect their ability to produce and understand speech. Most older adults retain the ability to understand individual words (James & MacKay, 2007). […]
Longitudinal estimates of changes in the PMA [primary mental abilities] scale, shown in Figure 7.6, reveal that there is an overall picture of relatively stability until the 50s or 60s, followed by decline through the oldest age tested. However, caution is required in making conclusions from these findings (Schaie, 1996). For example, although some individuals may show declines in intelligence by the mid-50s, there are not significant losses until the decade of the 70s. […]
Specific theories about aging and personality based on the cognitive perspective place importance on the ways that people interpret their experiences and understand themselves over time. An important principle of the cognitive perspective is the idea that people do not always view themselves realistically. In part, this is because people strive to maintain a sense of themselves as consistent (Baumeister, 1996; 1997). In other words, most people prefer to see themselves as stable and predictable (even if they are not). Another basic tendency is for people to view their abilities and personal qualities in a positive light (Baumeister, Bratslavsky, Finkenauer, & Vohs, 2001). […]
Apart from the original investigation by Levinson and colleagues, little empirical support has been presented for the existence of the midlife crisis as a universal phenomenon (Lachman, 2004). Even before the data were available, however, psychologists in the adult development field expressed considerable skepticism about the concept of the midlife crisis based on what at the time appeared to be extrapolation far beyond the available evidence (Brim, 1976; Whitbourne, 1986). […] As a scientific concept, the midlife crisis simply fails to withstand multiple tests. By now you must surely be wondering why a concept so thoroughly debunked by the data continues to remain alive. Some argue that the idea of a midlife crisis makes a ‘‘good story’’ (Rosenberg, Rosenberg, & Farrell, 1999). […] Similarly, the idea that personality is subject to major upheavals in the middle years may lead to the persistence of this phenomenon in the public mind far longer than warranted by the data. […]
Among all adults 18 and older, over half of Whites (56%) are married. […] Among people 65 and older in the United States, there is a higher percentage of men (72%) than women (42%) married and living with a spouse […] Consequently, women over the age of 65 are about twice as likely (39%) as men (19%) to be living alone (Administration on Aging, 2009). Therefore, older women are at greater risk for some of the disadvantages that come with single status, including fewer financial resources, less access to care, and lower social support. […]
Living in a stable relationship prior to or instead of marrying is referred to as cohabitation. Since the 1960s, there has been a steady increase in the number of couples who choose this lifestyle. In 1960 an estimated 439,000 individuals in the United States reported that they were cohabitating with a person of the opposite sex. By 2009 this number was estimated at about 6.7 million (U.S. Bureau of the Census, 2010f). From 50 to 60% of all marriages are now preceded by cohabitation (Stanley, Amato, Johnson, & Markman, 2006); looking at the data on couples who cohabitate, approximately 28% of women 44 and under who cohabitate eventually marry their partner (National Center for Health Statistics, 2010). […] Along with a rise in the overall number of couples who cohabitate is a parallel increase in the number of cohabitating adults with children under the age of 15. In 1960 this number amounted to 197,000, but by 2009 it was estimated to have increased greatly to the present estimated level of 2.6 million (U.S. Bureau of the Census, 2010d).
Approximately 10% of the adult population in the United States is divorced (U.S. Bureau of the Census, 2010d). Taking into account all marriages that end in divorce, the average length of first marriage prior to divorce is about 8 years (Kreider, 2005). […] Studies on divorced (compared with married) individuals show that they have lower levels of psychological well-being, poorer health, higher mortality rates, more problems with substance abuse and depression, less satisfying sex lives, and more negative life events (Amato, 2000). The negative consequences of divorce are more severe for individuals who have young children, especially women (Williams & Dunne-Bryant, 2006). These effects may persist for many years, particularly for individuals who remain psychologically attached to their ex-partner, experience conflict in coparenting, or who have unusual difficulty in living on their own (Sweeper & Halford, 2006). Divorced or widowed adults who do not remarry are in poorer health (including chronic conditions and depressive symptoms) than those who remarry (Hughes & Waite, 2009). Divorce in older adults has negative effects on health in that newly divorced older adults experience more physical limitations in their daily lives (Bennett, 2006). […]
In the United States, approximately 18% of all marriages are second marriages, and 4% are third marriages. The average duration of a second marriage that ends in divorce is slightly longer than that of a first marriage—8 years for men and 9 years for women (Kreider, 2005). The probability of a second marriage ending in divorce after 10 years is .39, slightly higher than that of the ending of a first marriage, which is .33 (Bramlett & Mosher, 2002). […]
In the United States, currently there are approximately 14.3 million widowed adults ages 18 and older; 77% of these are 65 and older. The majority (81%) of the over-65 widowed adults are women. By the age of 85 and older, the majority of women are widows (76%), about double the rate for men (38%) (U.S. Bureau of the Census, 2010d). The highest rate of widowhood is among Black women 85 and older, among whom the large majority (87.5%) have lost their spouses (He, Sangupta, Velkoff, & DeBarros, 2005). […]
In what is called the widowhood effect, there is a greater probability of death in those who have become widowed compared to those who are married (Manzoli et al., 2007), an effect that is stronger for men (Lee, DeMaris, Bavin, & Sullivan, 2001)
Despite population trends toward more single-parent and cohabitating families, the large majority of households in the United States (77%) consist of people living together as a family. In the United States, the average household size is 2.57 people. Households with married couples constitute 53.6% of all households (U.S. Bureau of the Census, 2010d). […] Approximately 4.3 million women in the United States give birth each year. In the United States in 2006, 75% of all children were born to mothers between the ages of 20 and 34 years old (National Vital Statistics System, 2010). […]
Fatherhood is increasingly being studied as an aspect of identity in adulthood reflecting, in part, the increasing role of fathers in the raising of their children (Marsiglio, Amato, Day, & Lamb, 2002). Becoming a first-time father can significantly influence a man’s patterns of interaction outside the home. A 7-year longitudinal study of nearly 3,100 fathers of children under the age of 18 described the ‘‘transformative’’ process that occurs as new fathers become more involved with their own parents, grandparents, and other relatives. Fathers also become more involved with service-oriented groups and church. These effects occur along with the birth of each child, but are particularly pronounced at the time of the
first child’s birth (Knoester & Eggebeen, 2006).” […]
Stuff you may not want to know:
“Children do undergo developmental changes that alter their relationships with parents, a concept referred to as filial maturity (Blenkner, 1963). During early adulthood, but particularly in the 30s, children begin to relate to their parents in a different way than they did when they were younger. By taking on the responsibilities and status of an adult (employment, parenthood, involvement in the community), the adult child begins to identify with the parent. Over time, the relationship may change as a consequence of this process, and parents and children relate to each other more like equals (Fingerman, 1996). […]
A model incorporating the various dimensions present in the adult child–parent relations is the intergenerational solidarity model (Bengtson & Schrader, 1982; Silverstein & Bengtson, 1997). According to this model (see Figure 9.6), six dimensions characterize the cohesiveness of family relationships: distance apart, frequency of interaction, feelings of emotional closeness, agreement in areas such as values and lifestyles, exchanges of help, and feelings of obligation. […]
Estimates are that there are approximately 56 million grandparents in the United States (Fields, O’Connell, &Downs, 2006); about 11% (6.2 million) live with their under-18-year-old grandchildren. Of grandparents living with grandchildren, 2.5 million are responsible entirely for their basic needs (U.S. Bureau of the Census, 2009b). This situation, referred to as a skip generation family, may occur for a variety of reasons, including substance abuse by parents, child abuse or neglect by parents, teenage pregnancy or failure of parents to handle children, and parental unemployment, divorce, AIDS, or incarceration.
Although only a small percentage (14%) of grandparents in skip generation households are over the age of 60 years, substantial percentages live in poverty (Economist, 2007). Many have a disability. […]
From a life course perspective, the major dimension that underlies close friendships is reciprocity, or a sense of mutuality (Hartup & Stevens, 1997). The fundamental characteristic of reciprocity is that there is give and take within the relationship at a deep, emotional level involving intimacy, support, sharing, and companionship. At the behavioral level, reciprocity is expressed in such actions as exchanging favors, gifts, and advice.
Close friends in adulthood confide in each other, help each other in times of trouble, and attempt to enhance each other’s sense of well-being. Although there may be developmental differences across the life span in the expression of reciprocity, the essence of all friendships remains this sense of deep mutuality. Another important function of friendships is socializing, or helping each other through life transitions in other spheres, such as changes in health, marital relationships, residence, and work.”
From the paper:
“Because we began by putting forward a theoretically derived hypothesis and calling its viability into question on the basis of experimental data, it behooves us to listen carefully to what that data has been trying tell us and to draw together plausibly the various strands of evidence. The most parsimonious inductive explanation for our cumulative findings, we contend, is that automatic attitudes are asymmetrically malleable. That is, like creditcard debt and excess calories, they are easier to acquire than they are to cast aside. Thus, when people construe an object for the first time, their conscious fondness or antipathy for it is swiftly supplemented by an automatic positive or negative reaction. However, once people have acquired an attitude toward the object, attempts to subsequently undo it are differentially successful at different levels of the mind and lead its automatic component to lag behind its conscious one. Thus, Devine’s (1989) key prediction—that automatic attitudes will be generally be [sic] harder to shift that their self-reported counterparts — may be correct after all, not under the boundary conditions that we initially proposed but under a new set of boundary conditions that our data have subsequently suggested. […]
We contend that automatic attitudes operate like rapidly established perceptual defaults: although they can initially be engendered by conscious cognition, they later become relatively resilient to its influence.”
So, there might exist a variety of perhaps even non-overlapping reasons why one might be interested in stuff like this. I’m interested because I believe that some of the automatic attitudes I have implicitly come under the influence of are attitudes which does not make me happy, which is why I feel that I at the very least should try to understand them better. Understanding might make it easier for me to successfully challenge them. Though I’m not optimistic about that. I should specify that the automatic attitudes I have in mind here are perhaps of a somewhat different kind than the ones described in the study; but it doesn’t seem like a lot of stuff is written about how to overcome biological imperatives, and you need to take what you can get.
Human males my age – not only human males my age, but also human males my age – are ‘supposed to’ look for a mate to have children with, and if they can’t find one they are supposed to work towards gathering power and resources so that once someone is there to be found, they can compete more successfully with the other available males in the bidding war that will ensue, and perhaps win the right to have offspring. The male brain has not yet caught on to the fact that contraception has changed everything, in a way that means that power and resources no longer matter all that much when it comes to reproductive success. As Kanazawa put it in this paper; “men’s wealth still translates into their greater reproductive success had it not been for modern contraception, which men’s brain, adapted to the ancestral environment, has difficulty comprehending.”
To the Paleolithic brain, sex = offspring. The whole ‘offspring’-part is why sex feels good. Most (/non-ignorant?) males (/and females) know that the reason why sex feels good is because sex is nature’s (/your genes’) way of tricking you into having offspring. Just as the reason why chocolate cookies taste good is because they contain a lot of fats and sugars, i.e. calories; and calories are good if you want to avoid starving to death, a risk our ancestors spent a lot more time worrying about than we do. But whereas people are quite open about how it’s probably a bad idea to eat too many cookies, because it will make you fat and unhealthy, and thus people do not eat all that many chocolate cookies, there are, to put it bluntly, certainly a lot less people who seem to be open about drawing the conclusion that partnership and children is not worth it and that they ‘refuse to be slaves of their biology’. At least in that area of life…
I have this strange feeling that a lot of male (/and female) behaviour today might look completely crazy to someone who’s not as invested in the underlying ideals of the Paleolithic Era as are (all?) (/fe)males today. For a male, it looks like this: ‘The way to be happy/the good life is to find a fecund-looking female, court her and then have sex with her a lot, have babies and provide for them, die.’ A slightly more elaborate version would also include ‘convince your partner on an ongoing basis that you’re the best male available (by doing all kinds of weird things that signal to the female that you are there for the long haul, even if you’re not – and by golly, the modern economy/-world has certainly increased the number of insane-looking jump-through-the-hoops signals a (self-identified?) high-quality female can demand of her partner..)’, as well as ‘try to cheat on her as often as you can get away with – so that you can have more babies – but try your best to hide the cheating from her so as not to incur significant switching costs.’
The bidding wars these days in the partnership setting relates far more to the quality of the offspring than to the number of offspring. The Paleolithic fecundity markers are more or less completely out of whack with reality today. Today it is mostly preferences – which are to a very large degree driven by socioeconomic factors, religion, culture and societal norms more broadly – and not biological factors (waist-hip ratio etc.) which decide how many children a female is likely to/willing to have. Kanazawa (see above) found that resource access is pretty much irrelevant too. However the lives of most males and females continue to follow the age-old recipe, to some degree. To be happy you need to find a mate and have children. For a male, in order to get the best possible female you need access to resources, you need power. So you need money, which means that you need to work hard, both to obtain access to resources and incidentally also to actually convince the high-quality female that you’re the most suitable partner available. It’s not that these ideals seem completely true to everybody; it’s more that when you defend a different version of the good life, my impression is that you most often will have a hard time making that defense sound credible, even to yourself. People often reject some of the defining characteristics of the traditional partnership equation, like the idea that a partnership necessarily needs to involve children, that it makes sense to look for ‘the one’, that romantic relationships need to involve members of both genders, or perhaps that a monogamous relationship is the best way to deal with the romantic stuff in your life; but how many people openly reject the idea of having a relationship as a major life goal in favour of the alternative in the (‘semi’…, see my remarks below regarding the commitment issues here)-long run, for no other reason than that they think that they will be probably end up happier in the long run if they do? Surely only a person who has no chance in the dating market would do such a thing, right?
I assume the standard narrative will not work for me. It seems like too much hard work that you just know that you’re only undertaking because your Stone Age brain is trying to trick you into undertaking it, just like it’s trying to trick you into eating too many chocolate cookies – and with not too dissimilar consequences. I will probably not be willing to work hard enough to find a long-term partner who would not reject me in favour of someone more suitable, given the amount of competition. And if I do find someone, I will still have major problems trusting her, because I’ll assume that if she follows the standard narrative here, she’ll also follow the Paleolithic recipe later on. Which tells me that she’ll be more likely than not to leave me when I start getting really sick. Yeah, I may not get really sick and a potential she may not leave even if I do, but in expected terms this needs to be taken into account; as does my loss aversion at that point.
So why was I reading the paper again? Because it seems to me at this point that the smartest thing for me to do would be to rewire my brain somehow, to make it like stuff it currently does not like as much as would be optimal, and to dislike stuff it currently seems to enjoy thinking about. To let go of a lot of the counterproductive narratives which were never about people like me in the first place. I’m perfectly well aware that this is all about rationalization, and Paleolithic mind has views about that stuff too. Given what I’ve previously said about the Stoics, naturally I’m not very optimistic about this whole endeavour. But it seems worth trying. Maybe my mind can actually outsmart my Paleolithic mind. In the eyes of most females, I probably won’t be proper partner-material for some time (because of ‘resources, power’) anyway – at least not for the kind of partner my Stone Age brain is trying to convince me I’d like to have. I know about the assortative mating-aspects of the college/university experience, but I also know that that part of the university experience is probably not likely to be relevant for me. Either way, I hope that I can obtain a state of mind such that my period of thinking about dating and similar stuff is over – at least for the time being. The only way not to lose the bidding war is not to play or think about playing.
Incidentally, I ought to at post a few remarks here about how this post relates to my commitment to change: I was writing this and publishing it here at least in part to more efficiently commit myself to this change. I know how strong ‘the opposition’ (‘the Paleolithic mind’ and all its friends and allies…) is, and I might give up on this idea before long. But writing this here can not hurt my chances much, and I’ve been thinking along these lines for a while now. I’ve found that it’s much easier to (knowingly) ‘rationalize’ not looking for a partner than it is to actually be perfectly okay with not doing it. And if it turns out to be impossible to obtain that mind state, it seems suboptimal in most scenarios to not be dating. I’m not trying to commit myself to not dating/finding a girlfriend; I’m trying to commit myself to thinking that I can be perfectly happy even though I don’t. It’s the thoughts in my head, not the behaviour they engender, which are central here. Interestingly enough, if I’m succesful it also probably means that long-run credible commitment to this state of mind is impossible (if preferences such as these can actually be changed over time, such changes can also be reversed later on), which should if anything make commitment in the short run easier, rather than harder, to achieve.
I decided to follow up on this post and have a closer look at the Danish numbers. In the post I’ve used data from Statistics Denmark’s public database (Statistikbanken). First, let’s just have a look at the raw numbers (from: ‘SKI107: Skilsmisser fordelt efter parternes bopæl, alder og ægteskabets varighed’):
The above graph displays the total number of divorces as a function of the length of marriage for the divorces that happened in Denmark during the year 2010. To take an example, 911 couples divorced after 3 years of marriage. Divorce risk as a function of marriage duration is pretty much (though not completely) monotonically decreasing over time (yes, I know it’s problematic to extrapolate from cross-sectional data like this, but let’s just pretend for a moment that this makes sense anyway…) after the first decade of marriage. When looking only at the first 10-15 years the distribution looks a bit bimodal. Actually, I can’t help remarking here more specifically that when it comes to the 7th year, the divorce risk is actually lower than it is for any other marriage duration in the 0-9 year span except for the first two years of marriage – i.e. the 7 year mark is a local minimum. There were 148 divorces at the 25-year mark, but only 93 divorced after 27 years of marriage. This is not to say that the risk of divorce at the 25-year mark is high – it’s almost twice as high for marriages that have lasted exactly 20 years (291) – but the risk doesn’t really tail off there, rather it does it a couple years later (in terms of marriage duration). The total number of divorces in 2010 was 14292, or about 39 each day of the year. I found it interesting that whereas people are much more likely to marry during the summer, there does not seem to be much systematic variation in the divorce rate over the course of the year – but you can judge yourself, here are the data from 2010 (‘BEV3C: Vielser og skilsmisser på måneder’):
[‘2010M01’ = First month of 2010 (and so on)]
Back to the other data set, if we once again assume that the age/duration profile of divorcees/divorces do not change much over time so that we can extrapolate from the data we have, and you then decide to condition on a divorce actually happening during a marriage, what is then the likelihood that a marriage that will fail will end at year X? (To make this absolutely clear: This is not the probability that a marriage that has lasted X years will end in divorce during that year.)
If you instead look at the cumulative distribution function, it looks like this:
I cut it off after 20 years – more than 85% of all divorces are accounted for by then and adding more numbers seemed counterproductive because it made it harder to see what was going on to the left of the graph – where the most important stuff’s going on – in detail. More than half of the marriages that ended in divorce in 2010 were marriages between partners who had been together for 9 years or less. 73% of them were between partners who’d been together for 15 years or less. Almost one fourth of them (24%) had only lasted 4 years or less.
From page 18 of this book, Divorce: causes and consequences. The book also mentions a 2002 CDC report which found that after three years, 12 % of all marriages had ended in divorce or separation; after 5 years, 20 % of all first-marriages had ended, after 10 years; 33 %. After 15 years the number is 43 %. Maybe there’s such a thing as a ‘7-year-itch’, but the divorce likelihood is statistically much higher in the years before that and divorce risk in general is highly front-loaded. If 20 % of all marriages have ended in divorce after 5 years and the likelihood that a marriage will end in divorce after 50 years is 50%, that means that 40 % of all divorces that do happen (…at least within a 50 year time frame) take place during the first 5 years of marriage. In the US, first marriages that end in divorce last about eight years [on average].
US divorce patterns might not be similar to those found other places, so it makes sense to add some data from the UK (same link): “According to [a 2004] survey, husbands engaged in extramarital affairs in 75% of cases; wives in 25%. In cases of family strain, wives’ families were the primary source of strain in 78%, compared to 22% of husbands’ families. Emotional and physical abuse were more evenly split, with wives affected in 60% and husbands in 40% of cases. In 70% of workaholism-related divorces it was husbands who were the cause, and in 30%, wives. The 2004 survey found that 93% of divorce cases were petitioned by wives, very few of which were contested. 53% of divorces were of marriages that had lasted 10 to 15 years, with 40% ending after 5 to 10 years. The first 5 years are relatively divorce-free, and if a marriage survives more than 20 years it is unlikely to end in divorce.”
As should be clear from the above passages, divorce patterns are not the same across countries. In the US, people are more likely to divorce early on, whereas the Brits tend to wait longer before they split up. CDC probably has more US data here if Plamus or Gwern (or others?) are interested in taking a closer look, but I didn’t find what I was looking for and I didn’t want to spend a lot of time searching for that data.
If people marry young, the likelihood of divorce is much higher than if they do not. Here’s another graph from the book (p.36):
This link between age and divorce risk is not controversial, the wikipedia link has more:
“Success in marriage has been associated with higher education and higher age. 81% of college graduates, over 26 years of age, who wed in the 1980s, were still married 20 years later. 65% of college graduates under 26 who married in the 1980s, were still married 20 years later. 49% of high school graduates under 26 years old who married in the 1980s, were still married 20 years later.” […] In 2009, 2.9% of adults 35–39 without a college degree were divorced, compared with 1.6% with a college education.”
The book notes (p.40) that: “Interracial marriages are more likely to disrupt than marriages in which both spouses are the same race and ethnicity. Interracial marriages have a 10 percent higher chance of failure in the first 10 years than same-race marriages (41 percent versus 31 percent).”
Here’s another interesting tidbit from the wikipedia article:
“According to a study published in the American Law and Economics Review, women currently file slightly more than two-thirds of divorce cases in the United States. There is some variation among states, and the numbers have also varied over time, with about 60% of filings by women in most of the 19th century, and over 70% by women in some states just after no-fault divorce was introduced, according to the paper. Evidence is given that among college-educated couples, the percentages of divorces initiated by women is approximately 90%.” [my emphasis – again, from the wikipedia link above. This 90% estimate is comparable to the British estimate above and maybe I should have emphasized that one as well. Anyway, it seems that females are much more likely to file for divorce than are males, and it seems that they are pretty much almost always the ones to file for divorce when both partners have a high education level. There’s needless to say more than one model of marriage dynamics that fits those facts, but in order to get a good model, you probably need to include in such a model the fact that males are on average much more likely to cheat on their partner than are females.]
The figure below (the book, p.32) on household data is somewhat unrelated to the above, but worth posting:
Part iii of this previous post of mine has some related Danish household data. Danish readers might also want to reread this post if they want to know more about some related Danish numbers. Right now I’m considering having a closer look at Statistics Denmark’s data on marriage/divorce-patterns – I know they have data on this stuff – so I might write another post on this subject at a later point in time.
“This article addresses open questions about the nature and meaning of the positive association between marriage and well-being, namely, the extent to which it is causal, shared with cohabitation, and stable over time. We relied on data from the National Survey of Families and Households (N = 2,737) and a modeling approach that controls for fixed differences between individuals by relating union transitions to changes in well-being. This study is unique in examining the persistence of changes in wellbeing as marriages and cohabitations progress (and potentially dissolve) over time. The effects of marriage and cohabitation are found to be similar across a range of measures tapping psychological well-being, health, and social ties. Where there are statistically significant differences, marriage is not always more advantageous. Overall, differences tend to be small and appear to dissipate over time, even when the greater instability of cohabitation is taken into account. […]
Examined across a range of outcomes, we found the similarities between marriage and cohabitation to be more striking than the differences: Entering into any union improved psychological well-being and reduced contact with parents and friends. Direct marriage and marriage preceded by cohabitation were statistically indistinguishable in all outcomes examined, providing no evidence that premarital cohabitation has negative consequences for wellbeing or ties to family and friends. When union dissolutions were excluded from the analysis, there were no statistically significant differences between the married and cohabiting for depression, relationships with parents, contact with parents, or time with friends. […] The married fared better in health than cohabitors, but the opposite was true of happiness and self-esteem. […]
We found no evidence that marriage and cohabitation provide benefits over being single in the realm of social ties; indeed, entering into a union reduced contact with parents and social evenings with friends. In some ways, of course, it is not surprising that forming a coresidential relationship reduces time with others, as partners spend time together that cannot be spent elsewhere. These findings do not, however, support arguments in the literature that marriage expands social circles and does so to a greater extent than cohabitation (e.g., Nock, 1995). Our results are more consistent with Sarkisian and Gerstel’s (2008) assessment of marriage as a ‘‘greedy’’ institution — and suggest the same of cohabitation. […] We found no change over time in the effects of marriage and cohabitation on ties with family and friends, suggesting that these ties do not rebound in the years following marriage or cohabitation.”
With as many as half of all marriages ending in divorce or separation (Goldstein, 1999; Raley & Bumpass, 2003), marriage is as likely to be temporary as it is to be a lifetime relationship.”
Here’s the link.
I decided to start out with this:
…in order to illustrate that you could probably write a not too dissimilar post about other countries as well. Also, it’s a nice image. Image credit: Wikipedia. “Description: Sex ratio total population. Pink = Female higher than male, Green = Equal, Blue = Male higher than female.”
This post will only deal with China. Here’s some related stuff about India.
So anyway, I was skimming a few world bank working papers and I found this one (pdf), which I decided to cover in a bit of detail here. It’s called China’s Marriage Market and Upcoming Challenges for Elderly Men and it’s written by Monica Das Gupta, Avraham Ebenstein & Ethan Jennings Sharygin. Some stuff from the paper:
“The Chinese census in 2005 reflected a staggering sex ratio at birth of 119, implying that each year there are roughly 1 million more boys born than girls.3 For cohorts born between 1985 and 2005, we estimate that there are 27 million more men than women4, implying a large number of men will fail to marry. […]
We demonstrate two key facts regarding the Chinese marriage market using historical census microdata from 1990 and 2000. First, economic status is a crucial predictor of marital probability for men in China. We use years of education as the closest proxy for status, and document that while there is almost universal marriage for highly educated men, lower rates of marriage prevail among men of lower education. By contrast, the marriage market for women cleared: women across the educational distribution enjoy nearly universal marriage, and are able to engage in hypergamy, choosing spouses of higher status and income. Second, since many women migrate for the purpose of marriage, it seems very likely that in the coming decades the collapse of marital prospects for men will occur in poor areas of the country with low educational attainment. […]
The results paint a grim picture for China’s ability to care for these men under the current policy structure of social assistance and social insurance programs that are primarily locally funded (Wang 2006, World Bank 2009). We estimate that in the absence of major redistribution of education and employment opportunities across China, the marriage squeeze will be in China’s poorer regions with large minority populations.7 Thus it will not necessarily be the more prosperous eastern regions of China with the most skewed sex ratio at birth that will experience high marriage failure rates among men. Rather, the poorer provinces ─ with more balanced sex ratios at birth ─ will bear a disproportionate share of the social and economic burden of China’s unmarried and childless men.”
How big is the difference in marriage rates between the successful males and the not quite so successful males, I hear you ask? Well, the paper states that: “over 98% of college graduates successfully marry by age 35 whereas the proportion is under 90% for men with less than a primary education.” One way to look at those numbers is that ‘that’s actually not that big of a difference’ – it’s around 9 out of 10 or more in both cases, right? But who are we actually comparing again? – another way to look at that is that males with less than a primary education are more than 5 times as likely to not succesfully marry by age 35. To me, that sounds like a huge difference, and it’s expected to get even worse over time: “over 10 percent of men with less than primary school education aged 30+ in 2030 are projected never to marry, and this figure increases to almost half in 2050”. Of course one might argue that economic growth increases mobility (so that even poor men might be able to move to find females willing to marry them) and ‘historical data are historical data’ which perhaps shouldn’t be given as much weight, given how much Chinese society has changed over the past decades. But rural China is still very poor and it isn’t growing very much compared to the rest – many of the people who have not left already for the urban provinces are people who can’t afford to, and they can’t really afford to save either so there’s not in my mind any compelling reason to think they will be able to afford to move in the future. Incidentally, it’s not really that hard to set up a model where you have decreased mobility over time even though the poor group has a positive net savings rate. Property prices are functions of local economic conditions, and if an area experiences significant income growth whereas another area does not and the people living in the poorer area are neither able to save enough money over time to at least keep up with the income growth of the richer area nor can afford to move there in the short run, the relative property price differential and the costs of moving will go up over time, even though the poor single guy might have a significant positive net savings rate. A very simplified model illustrating this could go along these lines:
Average income of ‘poor area’ residents: 10.
Average income of ‘rich area’ residents: 100.
Poor area income growth rate: 0%.
Rich area income growth rate: 10%
I shall assume that income growth rates and housing price growth rates are identical. In reality, housing prices are probably growing faster than income for the relevant demographic in the rich area and slower than income in the poor area. Let’s say the poor guy saves 20% of his income/year, i.e. 2 mu (‘monetary units’)/period. Say he invests that money in the rich area, earning 10%/year. After 10 years, he’ll have saved ~35 mu. How much will a house in the rich area that used to cost 100 mu cost after 10 years? 259. At the beginning, the poor guy was 98 mu short of being able to buy a house in the rich area – after ten years he’s now more than 200 mu short, even though he had a very high savings rate given his income and even though he earned a quite nice return on investment during that period. The property price differential was 90 mu to begin with, it’s 249 mu after 10 years. Maybe the effect sizes won’t be as large as assumed in the paper, but some of the dynamics described in the paper will probably play out to some degree.
Some more numbers and stuff related to these remarks from the paper:
“Poverty in China is heavily concentrated in the rural areas. Different measures of poverty all paint the same picture: while nearly 30 percent of the rural population was poor in 2005, this applied to only 5 percent or less of the urban population […] The vast majority of the poor in 2003 lived in rural areas, and poverty is most heavily concentrated in the northwestern and southwestern regions […] Both rural and urban incomes have continued to grow, but the rural-urban gap has continued to widen […]
Significant proportions of urban workers are covered by formal social insurance programs: in 2007, around half of workers had pension coverage, 45 percent had Basic Medical Insurance, and 40 percent had unemployment insurance and work injury insurance […] The rural pension system (funded mainly by personal contributions and collective subsidies) covered only about 10-11% of the rural labor force (World Bank 2009: Table 6.65), and coverage of the farm-based elderly population appeared to be particularly limited. Beneficiaries were highly concentrated in a few (mostly wealthy) provinces. […]
Since men who are not as educated, healthy, and able to earn well tend to fail to attract a bride, they are likely to be heavily represented among those who are unable to save adequately for their old age, or labor heavily into their old age. They are the most vulnerable to income and illness shocks, since they cannot smooth fluctuations in household income by pooling earnings from spouses or children. Unmarried individuals are also more likely to be living without family to serve as caregivers (Table 5). For example, in the 2000 census, 65% of those aged 65-80 who had ever-married were co-residing with younger kin, compared with only 20% of those never-married. Moreover, levels of co-residence have dropped sharply in recent decades (Table 5), and this trend can be expected to continue. The men who fail to marry are among the least likely to be able to save for their old age, to work in their old age, and to have access to old age support from family members.”
Last, a few tables (click to view full size):
Wu Bao, Di Bao and Tekun Hu are various social assistance programs: “The Te Kun program provides cash assistance to very poor and incapacitated residents of less-developed areas, at the discretion of the local officials. The Wu Bao program, dating from the 1950s, sought to ensure that no section of the population remained destitute.11 In 2006, the State Council issued regulations that shift financing responsibility for wubao from village reserves to local fiscal budgets (World Bank 2008:79-80). The Di Bao program, also known as the Minimum Living Standard Scheme, provides subsidies and in-kind transfers to those living below a certain poverty line.”
More than 45 % of the total income of Chinese urban residents above the age of 60 comes from pensions; the number for rural residents in the same age group is about one-tenth of that, 4.6 %. Also take note of the family support numbers.
Can’t let the blog die so I sort of have to at least post something from time to time. So here goes…
1. Global sex ratios:
At birth: 1.07 male(s)/female
Under 15 years: 1.07 male(s)/female
15-64 years: 1.02 male(s)/female
65 years and over: 0.79 male(s)/female
Total population: 1.01 male(s)/female (2011 est.)
Here’s one for the whole population, image credit: Wikipedia (much larger version at the link):
I’ve from time to time read about the Chinese gender ratio problem, I didn’t know there were much going on on that score in India. The clustering of gender ratio frequencies seems in my opinion sufficiently non-random to merit some explanation or other, especially when it comes to the northern provinces (Punjab, Haryana & Kashmir). Here’s a pic dealing with more countries:
2. Gambler’s ruin. I remember having read about this before, but you forget that kind of stuff over time so worth rehashing. I think the version of the idea I’ve seen before is the first of the four in the article; ‘a gambler who raises his bet to a fixed fraction of bankroll when he wins, but does not reduce it when he loses, will eventually go broke, even if he has a positive expected value on each bet.’ I assume all readers of this blog already know about the Gambler’s fallacy but in case one or two of you don’t already do click the link (and go here afterwards, lots of good stuff at that link and I shall quote from it below as well) – that one is likely far more important in terms of ‘useful stuff to know’ because we’re so prone to committing this error; basically the important thing to note there is that random and independent events are actually random and independent.
A couple of statistics quotes from the tvtropes link:
“The Science Of Discworld books have an arguably accurate but somewhat twisted take on statistics: the chances of anything at all happening are so remote that it doesn’t make sense to be surprised at specific unlikely things.”
“There is something fascinating about science. One gets such wholesale returns of conjecture out of such a trifling investment of fact.” (Mark Twain. Maybe it’s more of a science quote really – or perhaps a ‘science’ quote?)
“People (especially TV or movie characters who are against the idea of marriage) often like to cite the “50 percent of marriages end in divorce” statistic as the reason they won’t risk getting hitched. That is actually a misleading statistic as it seems to imply that half of all people who get married will wind up divorced. What it doesn’t take into account is the fact that a single person could be married and divorced more than once in a single lifetime. Thus the number of marriages will exceed the number of people and skew the statistics. The likelihood that any one person chosen at random will be divorced during their lifetime is closer to 35 percent (the rate fluctuates wildly for males, females, educated and uneducated populations). It’s still a huge chunk of people, but not as high a failure rate for marriage for an individual as the oft-cited “50 percent of all marriages” statistic would leave you to believe.” (comment after this: “How can you give that setup and not deliver the punchline. “But the other half end in death!””)
“Black Mage: 2 + 2 = 4
Fighter: You can’t transform numbers into other numbers like that. It’d just go on forever. That’s like Witchcraft! ”
3. Messier 87. Interesting stuff, ‘good article’, lots of links.
4. Substitution cipher. I’d guess most people think of codes and codebreaking within this context:
“In cryptography, a substitution cipher is a method of encryption by which units of plaintext are replaced with ciphertext according to a regular system; the “units” may be single letters (the most common), pairs of letters, triplets of letters, mixtures of the above, and so forth. The receiver deciphers the text by performing an inverse substitution.
Substitution ciphers can be compared with transposition ciphers. In a transposition cipher, the units of the plaintext are rearranged in a different and usually quite complex order, but the units themselves are left unchanged. By contrast, in a substitution cipher, the units of the plaintext are retained in the same sequence in the ciphertext, but the units themselves are altered.
There are a number of different types of substitution cipher. If the cipher operates on single letters, it is termed a simple substitution cipher; a cipher that operates on larger groups of letters is termed polygraphic. A monoalphabetic cipher uses fixed substitution over the entire message, whereas a polyalphabetic cipher uses a number of substitutions at different times in the message, where a unit from the plaintext is mapped to one of several possibilities in the ciphertext and vice-versa.”
The one-time-pad stuff related is quite fascinating; that encryption mechanism is literally proven unbreakable if applied correctly (it has other shortcomings though..).
“there’s only so much a human female pelvis can increase in terms of width before serious functional problems in locomotion make change in that direction unfeasible. […] If the pelvis was prevented from getting any wider due to biomechanics, and a large adult brain was a necessary condition of high fitness value for humans, then one had to accelerate the timing of childbirth so that the neonate exited while the cranium was manageable in circumference.”
6. Random walk. The article actually has some stuff related to the previous remarks on gambler’s ruin.
Some bits from the first chapter of the Phd Thesis by Malene Lamb.
“75% of the males in the sample work full-time, whereas only 54% of the women are employed full-time.”
“Finally, we have information about contributions to both labor market pension schemes and private pension schemes. […] The variables show how much the individual has contributed to the different schemes each year making it a good indicator for how much the individual has put aside to supplement the public retirement schemes. […] Around 95% of the individuals in our sample have made no contributions within a given year to a labor market pension schemes independently of which of the two types we consider. […] For private schemes the picture looks slightly better since ‘only’ 70% have no private capital pension and 75% have no private annuity pension.”
“If the spouse is working full-time it lowers the probability for the individual to enter early retirement. However, this effect only holds for women indicating that women actively participating in the labor market have a lower retirement hazard if their husband works full time. […] A longer spell of illness of the spouse significantly increases the retirement hazard indicating that people may leave the labor market earlier in order to take care of their spouse. Looking at the two sub-samples this effect is only significant for the men. […] In this context it is important to note that free medical care is available to everyone thus not forcing one member of the household to continue working in order to maintain a health insurance.”
“We have […] shown that the husbands’ characteristics do affect the retirement behaviour of their wives differently than the wives’ characteristics affect their husbands. Within all the variable groups (labor market, education, age, occupation, sector, financial indicator, and pension) included in the model we find that spousal differences exists. However we never find opposite significant spousal effects, it is always the case that it is only significant for one of them.
Women’s retirement hazard is affected positively by the husband’s experience, if the husband has a short education compared to basic education, the husband’s high contributions to a labor market capital pension scheme and finally medium or high contributions to a private annuity pension scheme. On the other hand women’s retirement hazard is affected negatively (thus retire later) if the husband works full time, is self-employed or works in construction compared to the public sector. Men’s retirement hazard is affected positively by the wife’s age, labor market pension payments or if she receives sickness benefits. Men retire later if the wife has been unemployed, is high educated, not working as a high-salaried worker, is working in the construction, trade or transport sector compared to the public sector. Overall, we find more significant effects for men indicating that they are more influenced by their spouse in the early retirement decision compared to women. This corresponds to the results found in Gustman and Steinmeier (2000) and Coile (2004).”
Most of this I didn’t know. The sample is based on all Danish workers who were active in the labor market at the age of 50 in 1985 (99.498 individuals) – so many of the results probably don’t hold for the whole population (/entire workforce, all Danes/…). For instance private savings and the level of education are both variables likely to be somewhat higher in the younger cohorts. It seems that a majority in the cohort they looked at didn’t consider it to be necessary to save any money for retirement at all – I was simply flabbergasted when I read those numbers. Though it is worth remembering the role real estate plays in the savings equation (/and of course also the impact of the public pension scheme); in a way it makes more sense for a Dane to implicitly put the savings into the house than it does for an American, as the median Dane will never get into a situation where he or she suddenly needs to raise a lot of money fast to pay for a medical procedure – the liquidity part is much less important.
“Neuroticism is a fundamental personality trait in the study of psychology. It is an enduring tendency to experience negative emotional states. Individuals who score high on neuroticism are more likely than the average to experience such feelings as anxiety, anger, guilt, and depressed mood. They respond more poorly to environmental stress, and are more likely to interpret ordinary situations as threatening, and minor frustrations as hopelessly difficult. They are often self-conscious and shy, and they may have trouble controlling urges and delaying gratification. Neuroticism is associated with low emotional intelligence, which involves emotional regulation, motivation, and interpersonal skills.”
“A robust literature indicates that neuroticism has numerous negative implications for romantic relationships. But are there factors that can protect intimates from such implications? Given that negative affect accounts for part of the association between neuroticism and relationship distress, and given that the positive affect associated with sex may negate that negative affect, the authors predicted that sexual frequency would moderate the association between neuroticism and relationship satisfaction. A total of 72 newlywed couples reported their marital satisfaction and sexual frequency up to seven times over the first 4 years of marriage. Consistent with predictions, a lagged multilevel analysis revealed that although neuroticism was negatively associated with marital satisfaction on average, it was unrelated to marital satisfaction when couples had engaged in relatively frequent sex over the past 6 months. These findings join others in highlighting the importance of attending to the broader context of the relationship to developing a complete understanding of relationships.”
I am so saving that study for when/if I find a girlfriend!
1. The jumping skills of the Rocky Mountain tailed frog suggest that frogs’ ability to land gracefully might have come after they’d learned how to jump far. A very nice video (via Ed Yong) – turn the speakers off/down before playing the video if you’re in a workplace environment, the music is quite loud:
Here’s a video of a drunk squirrel trying to climb a tree. Well, I thought it was funny/cute:
2. Evil Overlord list (TvTropes). Everything you’ve always wanted to know about how to become a successful evil overlord in a fictional world. Well, perhaps not everything, but it’s a good starting point. There are links to several extensions to the list at the end of the article.
3. Kposowa examined the link between suicide and marital status using data on nearly 472,000 men and women included in the National Longitudinal Mortality study. Between 1979 and 1989, 545 of these individuals committed suicide.
“Men were nearly 4.8 times as likely to commit suicide as women,” [she wrote] […] In addition, divorce or marital separation more than doubled the risk of suicide in men, whereas in women, marital status was unrelated to suicide.
Kposowa suspects that this difference is related to the social networks men and women form outside their marriages, which may be stronger or more meaningful in women than in men.
Here’s where I found that piece. Yes, the fact that divorce impacts male suicide risk greatly but does not have any significant impact on female suicide risk is clearly because females are better at communicating. That’s surely the most likely explanation.
In other news, of all the children in Denmark who’ve been involved in a divorce and do not yet live on their own (275.000 children), 7 out of 8 of them live with their mother. From what I’ve gathered, the numbers aren’t equally bad in the US, and they’re getting better. However a majority of cases are cases of joint custody and here it’s worthwhile to compare tables 1 and 2 of this older paper and keep the difference between those in mind every time you read claims about how there isn’t a problem because joint legal custody is now a common way to settle such disputes. On an unrelated note, women currently file slightly more than two-thirds of divorce cases in the US. I wonder if males are more or less likely than females to be denied access to their children? Anyway, of course stats like these are not as important when it comes to explaining the suicide impact of divorce gender disparity as the well-known communication issues of males are. Kposowa isn’t implicitly blaming the victims.
5. Crisis provokes anger at god. The last two responses had me laughing out loud.
If marriage was a manufactured product it would be promptly banned in many countries due to its outrageous failure rate and the damage caused by the failures.
This working paper has taken a closer look.
The abstract reads:
This paper tests whether being convicted of a crime affects marriage market outcomes. While it is relatively well documented that crime hurts in terms of reduced future income, there has been little systematic analysis on the association between crime and marriage market outcomes. This paper exploits a detailed Danish register-based data set to fi ll this gap in the literature. The main fi ndings are that male convicts do not face lower transition rates into partnerships as such, but they face a lower chance of forming partnerships with females from more well-off families. In addition males who are convicted face a signi cantly higher dissolution risk than their law abiding counterparts.