Making Choices in Health: WHO Guide to Cost-Effectiveness Analysis

You can buy the book here, though I should note that I’m certain that free versions of the book are also available online. I started reading it yesterday and I completed it today.

The book consists of two parts: Part one deals with “Methods for Generalized Cost-Effectiveness Analysis” and part two consists of “Background Papers and Applications”. If you’re weird, like me, (or if you’re a researcher in the field…) you’ll want to read both parts. They write in the introduction that: “The main objective of this Guide is to provide policy-makers and researchers with a clear understanding of the concepts and benefits of GCEA [generalized cost-effectiveness analysis]. It provides guidance on how to undertake studies using this form of analysis and how to interpret the results.” As mentioned the book has two parts. It’s very clear that part one is written mainly for the politicians and that part two is written for the researchers – and good luck finding a politician who’ll actually read part 2 (/or part 1..?). I like to think that part one can be read and understood by most people, including certainly most readers of this blog, and I do not believe it requires a lot of knowledge about statistics or mathematics; some papers in part 2 on the other hand require math beyond the level I’ve taken for the reader to understand all the steps taken (here are a few wikipedia articles I had a look at while reading this part of the book). They repeat themselves a bit here and there, but it’s not hard to just skim passages containing stuff you’ve already dealt with elsewhere.

It should be noted that although some of it is a bit technical, there’s some good stuff in part 2 as well – for instance I really liked this table (from the fourth study in part 2, Econometric estimation of country-specific hospital costs):

Table 3
Click to view full size. The obvious conclusion to draw here is that costs do not vary much across countries – no, they definitely do not… Actually I was very surprised to learn that there’s a huge amount of variation even within countries – in the same article they note that: “it must be emphasized that there is wide variation in the unit costs estimated from studies within a particular country […] These differences are sometimes of an order of magnitude, and cannot always be attributed to different methods. This implies that analysts cannot simply take the cost estimates from a single study in a country to guide their assessment of the cost-effectiveness of interventions, or the costs of scaling-up. In some cases, they could be wrong by an order of magnitude.”

In the first chapter they state that:

“It appears that the field can develop in two distinct directions, towards increasingly contextualized analyses or towards more generalized assessments. Cost-effectiveness studies and the sectoral application of CEA [cost effectiveness analyses] to a wide range of interventions can become increasingly context specific—at the individual study level by directly incorporating other social concerns such as distributional weights or a priority to treat the sick and at the sectoral level by developing complex resource allocation models that capture the full range of resource, ethical and political constraints facing decision-makers.
We fear that this direction will lead ultimately to less use of costeffectiveness information in the health policy dialogue. Highly contextualized analyses must by definition be undertaken in each context; the cost and time involved as well as the inevitable complexity of the resource allocation models will limit their practical use. The other direction for sectoral cost-effectiveness, the direction that WHO is promoting […] is to focus on the general assessment of the costs and health benefits of different interventions in the absence of various highly variable local decision constraints. A generalized league table of the cost-effectiveness of interventions for a group of populations with comparable health systems and epidemiological profiles can make the most powerful component of CEA readily available to inform health policy debates. Relative judgements on cost-effectiveness—e.g. treating tuberculosis with the DOTS strategy is highly cost-effective and providing liver transplants in cases of alcoholic cirrhosis is highly cost-ineffective—can have wide ranging influence and, as one input to an informed policy debate, can enhance allocative efficiency of many health systems.”

I’m not a health economist so I have no idea which way the field has developed since the book was written. The book isn’t exactly brand new (it’s from 2003) and so I figured one way to probe whether the recommendations have been followed in the years after the book was published was to try to figure out the extent to which one of the big ideas here, the use of Stochastic League Tables in CEAs, has been implemented. So I went to google scholar and searched for the term – and it gave me 7400+ results (and 589 since 2012). It seems to me that the use of these things at least have caught on. I incidentally have no idea to which extent researchers have now moved towards the use of GCEAs and away from the previously (?) widely used ‘incremental approach’ studies when performing these analyses. I posted the long quote above also to caution people unfamiliar with the literature against complaining about CEAs which are ‘not specific enough’ (a complaint I’ve made myself in the past…) – it may make a lot of sense to not make a CEA too specific, in order to make it more potentially useful to decisionmakers. A related point is that the idea of using CEAs in a formulaic way to decide which health interventions ‘pass the bar’ and which do not, and thus base decisions such as which health interventions should receive government support only on the outcome of CEAs, do not have much support in the field – as they put it in Murray, Lauer et al. (study 7 in the second part):

“The results of cost-effectiveness analysis should not be used in a formulaic way—starting with the intervention that has the lowest cost-effectiveness ratio, choosing the next most attractive intervention, and continuing until all resources have been used (10). There is generally too much uncertainty surrounding estimates for this approach; moreover, there are other goals of health policy in addition to improving population health. The tool is most powerful when it is used to classify interventions into broad categories such as those we used. This approach provides decision-makers with information on which interventions are low-cost ways of improving population health and which improve health at a much higher cost. This information enters the policy debate to be weighed against the effect of the interventions on other goals of health policy.”

(They also emphasize this aspect in the first part of the book). I could quote a lot of stuff from the book, but if you’re interested you’ll read it and if you’re not you’d probably not read my quotes either. If you’re interested in cost-effectiveness analyses, I think you should probably read this book – or at least the first part which is relatively easy and does not take that long to read. If you’re not interested in this stuff you should definitely stay away from it. But I think the book is a good starting point if you seek to understand some of the main concepts, issues, and tradeoffs involved when doing and interpreting CEAs.

One last thing I should note, primarily to the people who will not read the book: Many people think of the people doing stuff like cost-effectiveness analyses in this field as the bad guys. That’s because they’re the ones who keep reminding us that we can’t afford everything. When it comes to health care we don’t like to be reminded of this fact, because sometimes when it’s been decided by decisionmakers that public money should not be spent on X it means that someone will die. What I’d like to remind you of is that resource constraints don’t go away just because people prefer to ignore them; rather, when people disregard cost-effectiveness it may just mean that fewer people will be helped and more people will die than if a different course of action, perhaps the one suggested by a CEA, had been taken. CEAs may not provide the complete answer to how we should do these things and they have some limitations, but we should all keep in mind that it matters how we spend our money on this stuff, and that completely ignoring the resource constraint isn’t really a solution to the problems we face when dealing with these matters.

January 30, 2013 Posted by | books, economics, health, health care | Leave a comment

The Great Sea – A Human History of the Mediterranean (II)

Here’s my first post about the book. As mentioned I started reading it last year but I didn’t get very far back then. I’ve had some social obligations over the last few days, but I still managed to read the last 400 pages in between the other stuff. I think I’ve read about ~20 pages/hour or so on average (if you don’t include the sizeable index and the notes in the page-count), meaning that there’s a total of ~32 hours spent here. The book requires less work than what it takes to complete most textbooks but it’s not a book you can just read during an afternoon where you happen to be bored, at least not unless you read much faster than I do.

I knew far more about the prehistoric era of the region and the stuff that took place during the (particularly the first half of the…) first millenium AD than I did about the stuff that happened later on (the Crusades; Venice, Genoa, and Pisa; The Fatimid Caliphate; the rise and fall of the Habsburgs; the Ottoman empire; the Barbary Wars; British domination; the Suez Canal…) and so I’m probably one of the few readers who knew sufficiently little about the stuff covered to actually learn a great deal – at least I like to think so. It must be said that Abulafia at some points may be somewhat unaware of just how much he’s actually assuming the reader already knows; these assumptions sometimes make the book harder to read than it otherwise would have been and had me visit wikipedia a couple of times. At a few points I was sort of missing a ‘box’ or something like that with a list of key events – the inclusion of something like that would have made the book easier to read, and it would certainly have been more helpful than quite a few of the maps included in the book, most of which look pretty much the same only with an occasional new town added here and there. Along the way I was somewhat surprised to learn that he’d apparently decided at no point to include more detailed maps of key areas like e.g. the Aegean Sea, the Tyrrhenian Sea, or the Dardanelles – or just close-ups of some of the islands, like Crete, Cyprus, or Sicily, which he spends so much time telling us about. Some of the amazon reviews touch upon the problem with the maps as well, so it’s not just me – for instance here’s one comment from a 4/5 review from

“the maps are too few, and lack detail. It appears the publisher outsourced the illustrations to a minimalist. It is exactly these kinds of books that appeal to geography students and students of geography. And students of geography love maps. […] Easily 5-star had the maps been up to speed.”

Even so, the book has a lot of good stuff. Had it had some better maps and a few lists/boxes, I’d have had a hard time getting my arms down – though there are a few other things I’m not perfectly happy with (a few places where he lets the notes and references do a bit too much of the work, to take an example, but then again this is almost impossible to avoid in a book covering such a huge amount of stuff) overall it’s a really nice book. There’s a lot of stuff on the economic development that took place, or did not take place, in the regions of interest (what was produced and traded, and with whom), and a great deal of emphasis on how trading patterns changed over time and how trade flows were determined. This of course was closely related to the naval power balances, so naturally there’s also a lot of stuff about the wars and conflicts that have taken place in the region – there were a lot of those – and how and why power balances changed over time. Piracy, and related themes such as slavery, is covered in some detail. Most of the book deals with ‘big-picture stuff’, but there’s also some ‘down to earth stuff’ about e.g. the diet of galley slaves, or travel times of merchants during the Medieval period. Demographic stuff is covered; both ‘traditional stuff’ like migration patterns, but also less traditional stuff like how long it took a town to recover from the plague or how the population exchange between Greece and Turkey in the modern period affected the areas involved. Naturally, given how important that stuff has been, he also talks a lot about the various religious groups in the region and how they interacted with each other (and how that interaction changed over time). He spends much less time on the 20th century than you’d perhaps expect from his thorough treatment of the Medieval period, but I didn’t mind that.

It’s a great read.

January 29, 2013 Posted by | books, Geography, history | Leave a comment

Wikipedia articles of interest

I went to Copenhagen over the weekend and so I didn’t have a lot of time for blogging.

I completed Pamela Regan’s book yesterday, but aside from a few remarks here I won’t post any more about it. Some of the chapters I had not read when I last posted turned out to be disappointing. Not just because of the stuff covered but also because of the stuff not covered. The results of likely deeply flawed studies are reported and a few of the problems with the studies are mentioned – but some places the author basically acts as if you can’t really do any more stuff with the data once you’ve done an OLS regression and had a look at the p-values. This despite the fact that she’s previously talked about the results of psychometric studies using factor analysis and thus should at least be aware that there’s more potential stuff in the statistical toolbox than meets the eye (/her eyes). Despite my previous remarks about the book not being a self-help book, the last part of the book, especially the last chapters, unfortunately does read way too much like a self-help book. And let’s just say that after having read the last chapter I remain wholly unconvinced that a) relationship counseling ‘works’, and b) that I should trust Regan’s opinion on the matter. She spends a total of one sentence on the self-selection problem (i.e. the problem that couples that seek and go through counseling may be different from couples that do not).). All those critical remarks aside, there’s also some good stuff in some of the later chapters and overall I’m glad I’ve read the book as I think I learned some stuff from it.

In related matters, I spent some hours Friday reading David Abulafia’s The Great Sea, A Human History of the Mediterranean, and I also read a bit in it today. I first started reading it in October last year, but back then my studies got in the way and so I never got very far; I only ever finished the first 260 pages or so (out of 650 pages). I expect to finish it tomorrow.

Okay, on to the wikipedia articles:

i. Factor analysis. (Now I’ve already mentioned it in the post and I’m sure some readers don’t know about this stuff…)

ii. Finnish Civil War (featured). The very brief version:

“The Finnish Civil War (Finnish: Suomen sisällissota, kansalaissota; Swedish: Finska inbördeskriget) was a part of the national, political and social turmoil caused by World War I (1914–1918) in Europe. The Civil War concerned control and leadership of the Grand Duchy of Finland after it had become sovereign in 1917. The war was fought from 27 January to 15 May 1918 between the forces of the Social Democrats led by the People’s Deputation of Finland, commonly called the “Reds” (Finnish: punaiset, Swedish: röda), and the forces of the non-socialist, conservative-led Senate, commonly called the “Whites” (Finnish: valkoiset, Swedish: vita). The Reds—dominated by industrial and agrarian workers—were supported by the Russian Soviet Republic. The Whites—dominated by peasants and middle- and upper-class factions, in particular upper-class Swedish speakers—received marked military assistance from the German Empire. The Reds were based in the towns and industrial centres of southern Finland, while the Whites controlled more rural central and northern Finland. The Whites won the war, in which about 37,000 people died out of a population of 3 million.[5]

Following the Diet of Porvoo in 1809, Finland had been ruled as a nominally autonomous part of the Russian Empire, known as the Grand Duchy of Finland. It was gradually developing into what would become the Finnish state, including a marked rise of the Fennoman movement standing for the Finnic majority of the population, with minority Swedish speakers representing the marked Swedish cultural background. By 1917 Finland had experienced rapid population growth, industrialization, improvements in the economy and standard of living, and the rise of a comprehensive labor movement; economic, social, and political divisions were deepening while the Finnish political system was in an unstable phase of democratization and modernization.[6]

The collapse of the Russian Empire following the February and October Revolutions of 1917 spurred the collapse of the Grand Duchy of Finland, and the resultant power vacuum led to bitter conflict between the left-leaning labor movement, led by the Social Democrats, and more conservative non-socialists. A breakdown of power and authority penetrated all levels of society as both sides, aiming to gain supremacy for their own faction, refused to make political compromises. Finland’s declaration of independence on 6 December 1917 – though supported by most Finns and soon recognized by the Russian Bolshevist Council of People’s Commissars – occurred in the context of the worsening power struggle, and therefore failed to either unite or pacify the nation.[7]

With the dissolution of regular police and military forces, both left and right began forming armed groups in the spring of 1917. Two rival paramilitary forces, the White Guards and Red Guards, emerged. An atmosphere of political violence, fear and mistrust reigned over the country. Fighting broke out between the Reds and the Whites in January 1918 and quickly escalated. The fate of the Finns during 1917–1918 was much like that of the peoples of minor nations separating from (disintegrating) large ones.[8]

If you think 37.000 dead people doesn’t sound like a very big deal, here’s a bit more about those deaths:

Lives lost

“Almost 37,000 people perished, 5,900 of whom (16 percent of the total) were between 14 and 20 years old, the youngest victims of the battles and the terror being between 8 and 10 years. Only about 10,000 of these casualties occurred on the battlefields; most of the deaths resulted from the terror campaigns and from the appalling conditions in the prison camps. In addition, the war left about 20,000 children orphaned.”

iii. Anglo–Zulu War.

“The Anglo–Zulu War was fought in 1879 between the British Empire and the Zulu Kingdom. It was thought that similar combined military and political campaigns might succeed with the other African kingdoms, tribal areas and Boer republics in South Africa. In 1874, Sir Henry Bartle Frere was sent to South Africa as High Commissioner for the British Empire to bring such plans into being. Among the obstacles were the presence of the independent states of the South African Republic and the Kingdom of Zululand and its army.[6] Frere, on his own initiative, without the approval of the British government[7][8] and with the intent of instigating a war with the Zulu, had presented an ultimatum on 11 December 1878, to the Zulu king Cetshwayo with which the Zulu king could not comply.[9] Cetshwayo did not comply and Bartle Frere sent Lord Chelmsford to invade Zululand.[10] The war is notable for several particularly bloody battles, including a stunning opening victory by the Zulu at Isandlwana, as well as for being a landmark in the timeline of imperialism in the region. The war eventually resulted in a British victory and the end of the Zulu nation’s independence. […]

This part was pretty wild to think about:

“20,000 Zulu warriors[42] attacked Wood’s 2,068 men in a well-fortified camp at Kambula, apparently without Cetshwayo’s permission. The British held them off in the Battle of Kambula and after five hours of heavy attacks the Zulus withdrew with heavy losses but were pursued by British mounted troops, who killed many more fleeing and wounded warriors. British losses amounted to 83 (28 killed and 55 wounded), while the Zulus lost up to 2,000 killed.[43] The effect of the battle of Kambula on the Zulu army was severe. Their commander Mnyamana tried to get the regiments to return to Ulundi but many demoralised warriors simply went home.[44]

iv. Green sea turtle.

I thought this part was particularly awesome: “Sea turtles spend almost all their lives submerged, but must breathe air for the oxygen needed to meet the demands of vigorous activity. With a single explosive exhalation and rapid inhalation, sea turtles can quickly replace the air in their lungs. The lungs permit a rapid exchange of oxygen and prevent gases from being trapped during deep dives. Sea turtle blood can deliver oxygen efficiently to body tissues even at the pressures encountered during diving. During routine activity, green and loggerhead turtles dive for about four to five minutes, and surface to breathe for one to three seconds.

Turtles can rest or sleep underwater for several hours at a time…”

v. Tenerife airport disaster. This was a really horrible event, but maybe because it happened before I was ever born I’d never heard about it:

“The Tenerife airport disaster occurred on Sunday, March 27, 1977, when two Boeing 747 passenger aircraft collided on the runway of Los Rodeos Airport (now known as Tenerife North Airport) on the Spanish island of Tenerife, one of the Canary Islands. With a total of 583 fatalities, the crash is the deadliest accident in aviation history.

After a bomb exploded at Gran Canaria Airport, many aircraft were diverted to Tenerife. Among them were KLM Flight 4805 and Pan Am Flight 1736 – the two aircraft involved in the accident. The threat of a second bomb forced the authorities to close the airport while a search was conducted, resulting in many airplanes being diverted to the smaller Tenerife airport where air traffic controllers were forced to park many of the airplanes on the taxiway, thereby blocking it. Further complicating the situation, while authorities waited to reopen Gran Canaria, a dense fog developed at Tenerife, greatly reducing visibility. When Gran Canaria reopened, the parked aircraft blocking the taxiway at Tenerife required both of the 747s to taxi on the only runway in order to get in position for takeoff. Due to the fog, neither aircraft could see the other, nor could the controller in the tower see the runway or the two 747s on it. As the airport did not have ground radar, the only means for the controller to identify the location of each airplane was via voice reports over the radio. As a result of several misunderstandings in the ensuing communication, the KLM flight attempted to take off while the Pan Am flight was still on the runway. The resulting collision destroyed both aircraft, killing all 248 aboard the KLM flight and 335 of 396 aboard the Pan Am flight. Sixty-one people aboard the Pan Am flight, including the pilots and flight engineer, survived the disaster.[1]

vi. World’s Columbian Exposition.

“The World’s Columbian Exposition (the official shortened name for the World’s Fair: Columbian Exposition,[1] also known as The Chicago World’s Fair) was a World’s Fair held in Chicago in 1893 to celebrate the 400th anniversary of Christopher Columbus‘s arrival in the New World in 1492. Chicago bested New York City; Washington, D.C.; and St. Louis for the honor of hosting the fair. The fair had a profound effect on architecture, the arts, Chicago’s self-image, and American industrial optimism. The Chicago Columbian Exposition was, in large part, designed by Daniel Burnham and Frederick Law Olmsted. It was the prototype of what Burnham and his colleagues thought a city should be. It was designed to follow Beaux Arts principles of design, namely French neoclassical architecture principles based on symmetry, balance, and splendor.

The exposition covered more than 600 acres (2.4 km2), featuring nearly 200 new (but purposely temporary) buildings of predominantly neoclassical architecture, canals and lagoons, and people and cultures from around the world. More than 27 million people attended the exposition during its six-month run. Its scale and grandeur far exceeded the other world fairs, and it became a symbol of the emerging American Exceptionalism, much in the same way that the Great Exhibition became a symbol of the Victorian era United Kingdom.”

January 28, 2013 Posted by | biology, books, history, statistics, wikipedia | Leave a comment

Close Relationships (II)

I’m now more than half-way through and I’m no longer in doubt this book is great, so I should make that clear right away.

There’s a lot of stuff about variables of interests and qualitative results, but not much stuff on, say, effect sizes, statistical power, or similar stuff. A lot of the studies covering these things involve WEIRD people. But it’s interesting stuff anyway, and the book is great at handling the conceptual stuff and telling you what people in the field find and how they arrive at the findings they do. I may post one more post about it, but I probably won’t; there’s just way too much good stuff to cover it all here and I don’t want to struggle with the question of what to include and what not to include. You should just read the damn book.

Below some stuff from the book that I put into this post before I realized that I really shouldn’t blog this in that much detail:

“many individuals assume that they have adequately conveyed their attraction to a partner when in fact they have not. The signal amplification bias occurs when people believe that their overtures communicate more romantic interest to potential partners than is actually the case; consequently, they fail to realize that the partner may not be aware of their attraction (Vorauer, Cameron, Holmes, & Pearce, 2003). […]

Most relationship scholars now agree that relationships develop gradually over time rather than by passing through a series of discrete stages. Process models suggest that relationship development is fueled by sometimes imperceptible changes in intimacy, self-disclosure, exchange of benefits and costs, and other interpersonal processes that occur between partners. […]

it is not only the depth and the breadth of self-disclosure that propel a relationship along its developmental path but also how responsive each partner is to the other’s disclosures. Intimacy Theory, developed by psychologist Harry Reis and his colleagues (Reis, Clark, & Holmes, 2004; Reis & Patrick, 1996; Reis & Shaver, 1988), posits that attentive, supportive responses that leave the partner feeling validated, understood, cared for, and accepted promote the growth of intimacy and the subsequent development of the relationship. These responses may be of a verbal or a nonverbal nature. In their review of the literature, Karen Prager and Linda Roberts (2004; also see Prager, 2000) observed that an individual who is engaged in an intimate interaction displays a host of behavioral cues that signal attentiveness and responsiveness to the partner as well as positive involvement in the interaction. These include increased eye contact, more forward lean and direct body orientation, more frequent head nods, increased physical proximity, greater facial expressiveness, longer speech duration, more frequent or more intense interruptions, and more intense paralinguistic cues (e.g., speaking rate, tone of voice, pauses, silences, laughter). Recent research reveals that people do, in fact, interpret these behavioral cues as communicating validation, understanding, and caring—in short, responsiveness (see Maisel, Gable, & Strachman, 2008). […] it is not simply the act of disclosing information or making personal revelations that contributes to relationship development. Rather, reciprocal and responsive disclosures that contribute to feelings of intimacy — in other words, verbal and nonverbal behaviors that reflect mutual perceptions of understanding, caring, and validation — are what encourage and sustain the growth of relationships. […]

self-disclosure and intimacy appear to be integrally connected with both relationship satisfaction and stability. Research conducted with romantic partners and with friends generally reveals that people who self-disclose, who perceive their partners as self-disclosing, and who believe that their disclosures and confidences are understood by their partners experience greater satisfaction, closeness, commitment, need fulfillment, and love than people whose relationships contain lower levels of intimacy and disclosure (e.g., Laurenceau, Barrett, & Rovine, 2005; Meeks, Hendrick, & Hendrick, 1998; Morry, 2005; Prager & Buhrmester, 1998; Rosenfeld & Bowen, 1991; Sprecher & Hendrick, 2004). […]

U.S. census data indicate that between the years 1935 and 1939, approximately 66% of men and 83% of women were married by the age of 25. Twenty years later, between 1955 and 1959, 51% of men and 65% of women were married by the time they reached 25 years of age. And two decades after this, between 1975 and 1979, only 37% of 25-year-old men and 50% of 25-year-old women were married (U.S. Census Bureau, 2007a). Currently, approximately one third of the adult U.S. population consists of single men and women who have never married; an additional 10% of adults are divorced and single (U.S. Census Bureau, 2007b, 2007c). […]

recent surveys conducted in Turkey, Jordan, Yemen, Afghanistan, and Pakistan revealed that approximately 20% to 50% of all marriages were between first cousins (e.g., Gunaid, Hummad, & Tamim, 2004; Kir, Gulec, Bakir, Hosgonul, & Tumerdem, 2005; Sueyoshi & Ohtsuka, 2003; Wahab & Ahmad, 2005; Wahab, Ahmad, & Shah, 2006). […]

More than 40 years ago, social scientist William Kephart (1967) asked a sample of young men and women whether they would marry someone with whom they were not in love if that person possessed all of the other qualities they desired in a spouse. More than one third (35%) of the men and three fourths (76%) of the women responded affirmatively—they were willing to marry without love. However, by the mid-1980s there was evidence of a dramatic shift in attitude. When psychologists Jeffrey Simpson, Bruce Campbell, and Ellen Berscheid (1986) asked a group of young adults the very same question, only 14% of the men and 20% of the women indicated that they would marry someone they did not love […] A similar attitude shift is occurring around the world. In the mid-1990s another group of researchers (Levine, Sato, Hashimoto, & Verma, 1995) asked a large sample of adults from 11 countries to answer the question first posed by Kephart […] the percentage of participants who said “no” in response to the question was as follows: United States (86%), England (84%), Mexico (81%), Australia (80%), Philippines (64%), Japan (62%), Pakistan (39%), Thailand (34%), and India (24%). […] sociologist Fumie Kumagai (1995) reported that the ratio of arranged (miai ) to love-based (renai) marriages in Japan shifted dramatically over the last half of the twentieth century. Specifically, during the time of World War II, approximately 70% of new marriages were arranged by parents whereas 30% were love-based or personal choice matches. By 1988, however, only 23% of new marriages were arranged; the rest either were completely love-based (75%) or refl ected a combination of parental arrangement and personal choice (2%). Data collected more recently reveal an even greater decline in the proportion of arranged marriages: among Japanese couples marrying in 2005, only 6.4% reported an arranged marriage (National Institute of Population and Social Security Research, 2005, as cited in Farrer, Tsuchiya, & Bagrowicz, 2008). Similar changes have been documented in other countries (e.g., China, Nepal; Ghimire et al., 2006; Xu & Whyte, 1990). […]


longitudinal research consistently reveals that most newlywed couples (whether in their first or subsequent marriage) begin their married lives with a “honeymoon” period characterized by high amounts of satisfaction and well-being which then progressively decline during the next several years, stabilize for a period of time (often between the fourth and sixth years of marriage), and then continue to decline, assuming the couple stays together. In general, husbands and wives show the same changes in marital happiness. […] A large literature about the impact of parenthood on marital quality exists, with the majority of studies finding that the transition to parenthood is marked by a reduction in marital satisfaction (e.g., Perren et al., 2005; for reviews, see Belsky, 1990, 2009; Sanders, Nicholson, & Floyd, 1997; Twenge, Campbell, & Foster, 2003). […] there is some evidence that spouses’ marital satisfaction levels may increase once their children reach adulthood and leave home (see Gorchoff, John, & Helson, 2008). […]

A vast body of social psychological research reveals that, as people go about their daily lives, they tend to interpret the situations they encounter and the events they experience in a decidedly selfcentered, self-aggrandizing, and self-justifying way (Greenwald, 1980). For example, the majority of men and women possess unrealistically positive self-views—they judge positive traits as overwhelmingly more characteristic of themselves than negative traits; dismiss any unfavorable attributes they may have as inconsequential while at the same time emphasizing the uniqueness and importance of their favorable attributes; recall personal successes more readily than failures; take credit for positive outcomes while steadfastly denying responsibility for negative ones; and generally view themselves as “better” than the average person (and as better than they actually are viewed by others; for reviews, see Mezulis, Abramson, Hyde, & Hankin, 2004; Taylor & Brown, 1988). In addition, people often fall prey to an illusion of control consisting of exaggerated perceptions of their own ability to master and control events and situations that are solely or primarily determined by chance (e.g., Langer, 1975; for reviews, see Taylor & Brown, 1988; Thompson, 1999). Moreover, most individuals are unrealistically optimistic about the future, firmly believing that positive life events are more likely (and negative events are less likely) to happen to them than to others (Weinstein, 1980, 1984). […] These cognitive processes, collectively known as self-serving biases or self-enhancement biases, not only function to protect and enhance people’s self-esteem (see Taylor & Brown, 1988, 1994) but also color perceptions of the events that occur in their closest and most intimate relationships. For example, two early investigations (Ross & Sicoly, 1979; Thompson & Kelley, 1981) demonstrated that married individuals routinely overestimate the extent of their own contributions, relative to their spouses, to a variety of joint marital activities (e.g., planning mutual leisure activities, carrying the conversation, resolving conflict, providing emotional support, initiating discussions about the relationship). Moreover, they more readily call to mind instances of the specific ways in which they (as opposed to their partners) contribute to each activity.
Research also demonstrates that people tend to adopt a self-serving orientation when interpreting and responding to negative relationship events. […] Although self-serving biases may benefit the individual partners by protecting their self-esteem, such cognitions may have additional, less-than-beneficial consequences for their relationship. […]

People not only perceive their own attributes, behaviors, and future outcomes in an overly positive manner, but they also tend to idealize the characteristics of their intimate partners and relationships. Several relationship-enhancement biases have been identified. For example, research reveals a pervasive memory bias for relationship events, such that partners recall more positive experiences, fewer negative experiences, and greater improvement over time in relationship well-being than actually occurred (e.g., Halford, Keefer, & Osgarby, 2002; Karney & Coombs, 2000). […]

Not only do people rewrite the history of their relationships, but they also tend to view those relationships (and their partners) in an overly positive manner (e.g., Barelds & Dijkstra, 2009; Buunk, 2001; Buunk & van der Eijnden, 1997; Murray & Holmes, 1999; Murray, Holmes, & Griffin, 1996a; Neff & Karney, 2002; Van Lange & Rusbult, 1995). A large body of research reveals that most of us:

● perceive our own relationships as superior to the relationships of other people;
● view our current partners more favorably than we view other possible partners;
● view our partners more positively than our partners view themselves;
● minimize any seeming faults that our partners possess by miscasting them as virtues (“Sure, she can seem kind of rude, but that’s because she’s so honest”) or downplaying their significance (“He’s not very communicative, but it’s no big deal. He shows his love for me in many other ways”);
● accentuate our partners’ virtues by emphasizing their overall impact on the relationship (“Because she is so honest, I know I can trust her completely—she will never give me any reason to doubt her love”). […]

Together, these findings suggest that most people “see their partners through the filters provided by their ideals, essentially seeing them . . . as they wish to see them” (Murray et al., 1996a, p. 86).
The idealization effect is not limited to perceptions of romantic partners. Research indicates that parents view their children as possessing more positive qualities than the average child (Cohen & Fowers, 2004; Wenger & Fowers, 2008). Similarly, adults rate their friends more favorably than those friends rate themselves (Toyama, 2002). […] In sum, people appear to see their partners as their partners see themselves—only better. […]
Current evidence suggests that […] Partners are happiest and most satisfied when they are realistically idealistic—that is, when they possess an accurate understanding of each other’s most self-relevant attributes but maintain an exaggeratedly positive view of each other’s overall character and their relationship.”

January 23, 2013 Posted by | books, data, demographics, Psychology | 4 Comments

Close Relationships

By Pamela Regan. I’ve started reading it on account of it being ‘the type of book I should read.’

Although the ‘how-does-all-that-social-stuff-work-anyway’-field is full of self-help books, this isn’t one of them. It’s basically a systematic take on many relevant topics within the field of relationship science (apparently there’s a field called relationship science). From what I’ve been able to tell so far it’s the type of book I’ve been looking for for a long time.

The problem with reading a book like this is that it’ll probably include a lot of stuff most people already ‘sort of know’. When you read stuff where it’s easy to convince yourself that you already know this stuff to some extent, it gets easy to just read the words, nod along a bit, and then forget the stuff two days later. One way for me to try to counteract this tendency will be to stop reading for at least a bit of time everytime I reach a new chapter instead of just reading one page after the other until I get tired/hungry/whatever, which is how I most often tend to read stuff I enjoy reading.

Although it’s natural for a book like this to contain stuff you may already know there’s a difference between ‘rediscovering’ relevant information pertaining to the problem at hand, and then rereading stuff you already know and have no need to ‘rediscover’. I feel fairly certain that people reading along here have no need of reading chapter 2 and will be quite okay if they only skim chapters 1 and 3. I only briefly skimmed the first 3 chapters and my ‘stopping rule’ did not apply to those – I immediately realized that this was not where the interesting stuff’s at; to me the book proper doesn’t really start until chapter 4. That chapter is certainly a big part of what’s currently making me think the book is promising, and that’s even though it also covers some stuff I already knew (I’ve blogged some of these topics here before and I’m familiar with stuff like e.g. the mere-exposure effect).

If the book’s great I’ll probably just tell you it’s great. I’m not sure I’ll blog it in detail in that case because it’s quite likely that there’ll simply be too much great stuff in there to blog for me to want to go into a lot of details here.

Anyway, a little bit of stuff from chapter 4:

“The association between familiarity and interpersonal attraction has been extensively documented and is now one of the most robust findings in the literature (for reviews, see Bornstein, 1989; Zajonc, 2001). However, there is an important caveat: if our initial reaction to someone is negative, repeated exposure to that person is unlikely to produce attraction. In general, familiarity appears to strengthen first responses, such that a person who is initially disliked comes to be disliked even more, and a person who is initially liked comes to be liked even more, with increased exposure (e.g., Perlman & Oskamp, 1971). […]

Not only do people prefer potential partners who possess similar demographic characteristics, personality traits and dispositional tendencies, values and attitudes, and interests and hobbies (Markey & Markey, 2007; Regan et al., 2000; Sprecher & Regan, 2002), but similarity repeatedly has been shown to produce liking in laboratory experiments as well as in “real-life” contexts (e.g., Newcomb, 1961; for reviews, see Fehr, 2008; Montoya, Horton, & Kirchner, 2008). […] The results, across multiple studies with multiple participant samples (and age groups), are uniform and robust—attitude similarity generates attraction. […] responsiveness is another variable that is strongly associated with interpersonal attraction. Research consistently reveals that men and women report greater liking for individuals who are responsive than for those who are not […] Doreen Baringer and James McCroskey (2000) found a strong, positive correlation between student responsiveness and attraction among a sample of teachers. Specifically, teachers expressed higher amounts of positive affect for students who engaged in interpersonal behaviors indicative of responsiveness (such as sitting closer, establishing eye contact, smiling, leaning forward, engaging in positive head nods) than they did for less-responsive students. Similar results were reported more recently by psychologists Edward Lemay and Margaret Clark (2008). […] One of the reasons we pay particular attention to another person’s responsiveness may be because it imparts important information about the likelihood of a future relationship with him or her. People who are unresponsive—who avoid eye contact, refuse to respond (or respond inappropriately) when addressed by others, or remove themselves from social situations—are signaling a clear lack of interest in establishing a connection with us, and it makes sense that we would find them unappealing.
In sum, people tend to be attracted to individuals who possess desirable (and socially or culturally appropriate) characteristics, who resemble them along a number of dimensions, who are familiar, and who appear responsive. […]

In addition to physical or virtual proximity, social proximity — how close potential partners are to each other in the social environment or the extent to which their social networks overlap—also influences affiliation. Relationship scholars Malcolm Parks and Leona Eggert (1991) propose that communicative distance, or the number of people in each individual’s communication network that two persons must “go through” to reach each other for the first time, plays an important role in relationship beginnings. […] It seems that we meet many of our future partners through our current ones. […] our opportunities for interacting with someone are strongly influenced not only by the nature of the physical environment, but also by the closeness of our social connection to that person and the extent to which others in our social network approve of and directly facilitate the initial encounter. […]

fear of rejection is one of the primary reasons people give for their failure to initiate a potential relationship. […] In sum, in open field settings, people tend to approach those who are accessible for interaction and who they believe will be responsive to their initiation attempts.”

January 23, 2013 Posted by | books, Psychology | Leave a comment

A trip to the movies

After completing 3 books in four days, I’ve decided that this evening I’m going to watch The Hobbit in a local movie theater.

When I ordered the ticket online I started thinking back, about when I’ve last been to one of those things. My impression was that it was probably a few years ago, perhaps 3. I’m pretty sure by now that the answer to the question is 2009 – I’m almost certain the last movie I watched in such a venue was Australia, which I watched with my parents not too long after it came out in Denmark. It’s the last movie I remember watching such a place anyway. (Which is not to say that the movie was memorable – it wasn’t).*

I believe people generally have some not-insignificant degree of influence over how unpleasant it is for them to forgo pleasurable activities the costs of which might not be justified given the budget constraint. I’ve basically not given the idea of going to a movie theater and pay quite a bit of money simply to watch a movie a thought for a few years, and when you don’t think about what you’re missing out on it doesn’t hurt nearly as much as if what you’re missing out on is an activity you engage in on a regular basis. Actually it doesn’t really hurt at all.

So I’ve employed a ‘don’t think about it, just forget that this type of thing is even an option’-strategy for some years now regarding these matters. Over the last couple of years I’ve started employing similar strategies when it comes to my eating habits. There are types of food I just don’t consume, and so never really think about anymore. Naturally most of the things I’ve deliberately cut out like that are unhealthy types of food.

Habits are very important both when it comes to which types of behaviour we engage in, and how we feel about how we spend our time and what we do. I believe that engaging in a bit of systematic thinking about optimal ways to impact habit formation every now and then may be time and effort well spent. Implicitly people do engage in this type of ‘selective blindness’ behaviour, where they overlook ways their lives are worse than others, without thinking about it all the time; you can’t really function well if you don’t. Most normal people don’t get annoyed every day by the fact that they don’t have a maid or a cook employed in their private residence, even though some other people do. The point is that if you mentally make an effort of systematically adding more variables to this ‘this is really quite irrelevant stuff I shouldn’t worry about anyway..’-set, you may be less likely to feel deprived (even though maybe you are).

Incidentally I don’t think I’m particularly likely to go to the movies again this year after today – it’s a one-time thing, which is a big part of why it’ll probably (hopefully?) be an enjoyable experience. Also, I’m finding it quite unlikely that I’ll be thinking in the months to come that I’m missing out after having had this experience and being reminded of what it’s like; another established habit of mine is to avoid new movies and books as much as possible, unless there are some quite exceptional circumstances at play which make me believe that I’m highly likely to enjoy the work in question.

*On second thought I now recall that I have watched Watchmen with my big brother, and I’m reasonably certain we went to a movie theater to see it. It also came out in 2009, but later during the year than Australia.

January 22, 2013 Posted by | personal, random stuff | Leave a comment

Adult development and aging: Biopsychosocial Perspectives, 4th edition (IV)

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.”

January 21, 2013 Posted by | books, data, demographics, diabetes, health, marriage, Psychology | Leave a comment

Adult development and aging: Biopsychosocial Perspectives, 4th edition (III)

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.”

January 20, 2013 Posted by | books, data, demographics, marriage, Psychology | Leave a comment

Surely you’re joking Mr. Feynman!

If you watched this and liked it, there’s really no excuse for not reading this book.

The book was a Christmas present and I started reading it just before the exam-period started, though I didn’t get very far back then. Yesterday I read the rest. The book is based on conversations Feynman had with his friend Ralph Leighton, and they talk about a lot of stuff you’d most probably never think would come up in discussions with a Nobel Prize winning physicist: Stuff like his childhood experiments with ants; a late night bar fight; trips to Las Vegas and his interactions with the showgirls there; bongo drum playing; his experiences with safe-cracking; his experience as an artist trying to sell his work to local brothels; how he was deferred from the draft for psychiatric reasons; why he gave up learning Japanese and how he almost decided to learn Portuguese instead of Spanish because of a terrific-looking blonde girl; his first night as a professor at Cornell, where he almost ended up sleeping in a pile of leaves under a street light (no alcohol was involved).

There’s also, naturally, stuff included in the book which you’d sort of expect to be there: Stuff about Feynman’s interactions with other brilliant physicists; his college years; his experiences at Los Alamos; teaching and lecturing experiences he’d had, both in the US and abroad; and a little bit of stuff about the work he did. He was a very interesting man. It’s a quite funny and very interesting book.

January 20, 2013 Posted by | books, Physics | Leave a comment

Unseen Academicals

Exams are over for now (so blogging should be back to normal – no more reposts..) and I spent yesterday reading a Discworld novel. It was able to take my mind off exams and exam-related stuff completely for most of a day. That said, I don’t think it’s one of his best novels. A central theme of the book is the age-old one about an individual’s struggle to break out of the role created for him (/her) by the expectations of others. It’s also about foot-the-ball. I laughed out loud several times so it wasn’t too disappointing, but on the other hand it’s a quite long book (540 pages) so in a way I would have been very surprised if I hadn’t, considering the fact that it’s a Pratchett novel. A few quotes from the book:

i. “Regrettably, when he’d gone to check on things with the previous Master of The Traditions, who, everyone agreed, had not been seen around and about lately, he’d found that the man had been dead for two hundred years. This wasn’t a wholly unusual circumstance. Ponder, after years at Unseen, still didn’t know the full size of the faculty. […]
‘Er, I would have been happier had my predecessor paid a little more attention to some of the traditions,’ said Ponder, who believed in drip-feeding bad news.
‘Well, he was dead.’
‘Yes, of course. Perhaps, sir, we should, ahem, start a tradition of checking on the health of the Master of The Traditions?’
‘Oh, he was quite healthy,’ said the Archchancellor. ‘Just dead. Quite healthy for a dead man.’
‘He was a pile of dust, Archchancellor!’
‘That’s not the same as being ill, exactly,’ said Ridcully, who believed in never giving in. ‘Broadly speaking, it’s stable.'”

ii. “It is said that the onlooker sees most of the game. But the Librarian could smell as well, and the game, seen from outside, was humanity. Not a day went past without his thanking the magical accident that had moved him a few little genes away from it. Apes had it worked out. No ape would philosophize, ‘The mountain is, and is not.’ They would think, ‘The banana is. I will eat the banana. There is no banana. I want another banana.'”

iii. “The laws of favours are amongst the most fundamental in the multiverse. The first law is: nobody asks for just one favour; the second request (after the granting of the first favour), prefaced by ‘and can I be really cheeky …?’ is the asking of the second favour. If the aforesaid second request is not granted, the second law ensures that the need for any gratitude for the first favour is nullified, and in accordance with the third law the favour giver has not done any favours at all, and the favour field collapses.”

iv. “By his own admission, he would rather run ten miles, leap a five-bar gate and climb a big hill than engage in any athletic activity. […] he didn’t like people much, an affliction that affects many who have to deal with the general public over a long perid…”

v. “Ponder’s office always puzzled Mustrum Ridcully. The man used filing cabinets for heavens’ sake. Ridcully worked on the basis that anything you couldn’t remember wasn’t important and had developed the floor-heap method of document storage to a fine art.”

vi. “‘Drumknott, if you saw a ball lying invitingly on the ground, would you kick it?’
The secretary’s forehead wrinkled. ‘How would the invitation be couched, sir?’
‘I’m sorry?’
‘Would it be, for example, a written note attached to the ball by person or persons unknown?”I was rather inclining to the idea that you might perhaps feel simply that the whole world was silently willing you to give said ball a hearty kick?’
‘No, sir. There are too many variables. Possibly an enemy or japester might have assumed that I would take some action of the kind and made the ball out of concrete or similar material, in the hope I might do myself a serious or humorous injury. So, I would check first.’
‘And then, if all was in order, you would kick the ball?’
‘To what purpose or profit, sir?’
‘Interesting question. I suppose for the joy of seeing it fly.’
Drumknott seemed to consider this for a while, and then shook his head. ‘I am sorry, sir, but you have lost me at this point.'”

vii. “Glenda reached down inside her west and pulled out a burgundy-coloured booklet with the seal of Ankh-Morpork on it.
‘What’s that?’ said Juliet.
‘Your bank book. Your money’s safe in the bank and you can take it out any time you want.’
Juliet turned the bank book over and over in her hands. ‘I don’t fink anyone in my family’s ever been in a bank except for Uncle Geoffrey and they caught up with ‘im even before he got home.'”

viii. “‘Anyway, pies are so yesterday,’ said Dibbler dismissively. ‘I am on the ground floor of football memorabilityness.’
‘What’s that, then?’
‘Like genuine autographed team jerseys and that sort of thing. I mean, look here.’ Dibbler produced from the large tray around his neck a smaller version of what one of the new gloing! gloing! footballs would be if it were about a half of the size and had been badly carved out of wood. ‘See those white patches? That’s so they can be signed by the team.’
‘You’re going to get them signed, are you?’
‘Well, no, I think people would like to get that done themselves. The personal touch, you know what I mean?’
‘So they’re actually just painted balls of wood and nothin’ else?’ said Trev.
‘But authentic!’ said Dibbler.”

ix. “‘There were no assasinations,’ said her ladyship. She turned her eyes upwards. ‘There was, however, a terrible mining accident and a rather unusual rock slide.'”

x. “Football owned the day. Nothing was happening that wasn’t about football. There were certainly no lectures. Of course, there never were, but at least today they weren’t being attended because of the excitement about the upcoming match rather than not being attended because no one wanted to go to them.”

January 19, 2013 Posted by | books, Terry Pratchett | 6 Comments

Repost: Data on Danish immigrants (1)

The post below, which I first published in late 2011, is one of the most popular ones on the blog in terms of the reader ratings, though that may also be related to the remarks at the end of the post. I never got around to combining the posts on the topic into one big post covering everything, but you can read the other posts on the topic here: Part 2, part 3, part 4. If you know this stuff, you know more than perhaps even a significant majority of the Danes who like to spend time arguing about immigration policy (which is yet another reason why I don’t do political discussions anymore). I incidentally never did a post on the crime stuff – I may get back to that, but I’m not really sure it’s worth it because I’m unlikely to learn much from working on that stuff; I have looked at that type of data before and these things don’t change that much from one year to the next. Anyway, the post:

The central Danish statistical office, Statistics Denmark, has just published a report with a lot of data on Danish immigrants, Immigrants in Denmark, 2011. I thought some of the non-Danes reading along might appreciate a post in English on this subject.

At the site, they’ve given no indications that they’re planning to translate this, so I don’t think an English version of this material is coming up anytime soon. My translation of the stuff is better than what you’d get from google translate, but do remember that I’m not exactly a professional translator. I’ve decided to page-source every bit of data for this reason, so that it’s easier to go have a look for yourself if you’re in doubt. It was most convenient for me to page-source the pdf version pages, not the official page numbers at the top of each page in the report. Don’t think of the statements below as direct quotations from the report – I’ve frequently had to reformulate the expressions used in the report. If something’s unclear, please ask away. Anyway, let’s start:

*10,1 % of the Danish population are immigrants or descendants of immigrants. (p.13)
*Immigrants make up 7,7% and descendants make up 2,4%. (p.13) [A small note here: The report only explicitly mentions the 10,1% and the 7,7%, not the 2,4% – but I think it’s safe to assume that this is a simple subtraction problem and that it makes good sense to post that number as well just for completeness.]
*60,2% of all immigrants are from non-Western countries. (p.13)
*66% of all immigrants and descendants are from non-Western countries. (p.25)
*The number of non-Western immigrants has almost sextupled since 1980. (p.14)
*From 1980 to 2011, the number of non-Western descendants has increased from 7.653 to 115.597. (p.15)
*The number of descendants of Western immigrants grew by 70% from 1980 to 2011. (p.15)

*The immigrants living in Denmark come from more than 200 countries. (p.15)
*The distribution is asymmetric. Immigrants from the top 12 countries (in terms of number of immigrants living in Denmark) make up 50% of all immigrants. (p.15)
*Turkey is at the top of the list with 32 479 immigrants living in Denmark. (p.15)
*5 out of the top 12 countries are Western countries (Germany, Poland, Norway, Sweden, GB). 7 are Non-western countries (Turkey, Iraq, Bosnia and Herzegovina, Iran, Lebanon, Pakistan, ex-Jugoslavia). (p.16)
*There’s significant variation in the age distribution of immigrants from different countries. When looking at the top twelve, 20% of the Western immigrants in that group are 60 years old or older, whereas only 10% of the non-Western immigrants in the top-twelve are 60 years old or older. (p.16)
*As to the Poles, they’re an interesting case because they’re quite different from the rest of the Western immigrants. They’re the third largest immigrant population (26 580) in Denmark – the number of Polish born people living in Denmark is higher than the number of immigrants from Sweden and Great Britain combined – and more than half of the Poles (53%) are between 20 and 40. 68% of the Polish immigrants are between 20 and 49 years old. 10 % of them are 60 years or older. (p.16)

*When looking at the descendant populations living in Denmark, 11 out of the top 12 countries are non-Western countries. More than one in five (21%) of all descendants living in Denmark are descendants of Turkish immigrants. Lebanon and Pakistan are next on the list, with 9% and 7% respectively. (p.17)
*Most descendants are quite young. 41% of them are below the age of 10, and only 10% have reached the age of 30.

[I used to comment on this fact back when I did political discussions, because it is often overlooked or simply ignored in discussions about what might be termed the demographic potential of descendant populations. We have no idea how many children descendants will end up having, and it makes no sense to try to draw strong conclusions out of sample from the data sets that are available now. Please have this in mind when we get to the forecasts later on. Putting the above numbers in context, the average age of women having their first child in Denmark was 29,1 years in 2010 (Statistikbanken, FOD11). I also urge people to remember here that the growth rate of population segment X in a population doesn’t just depend on the total fertility rate differential, but also on age of birth differentials. If women from population segment X get children at the age of 30 and women from population segment Y get children at the age of 20, population segment Y will grow faster than population segment X, even if every single woman in the two population segments have the same amount of children. This remark is relevant because non-Western immigrants as a rule get children at a lower age than ethnic Danes. Females of Danish origin get on average 0,21 children during the period of their lives where they are 20-24 years old. For all non-Western female immigrants, the corresponding average number is 0,35. For Lebanese women, the number is 0,72. (pp. 27-28)]

*Western descendants are much older than non-Western descendants, on average. [worsening the data problems mentioned above. Especially if you mix up the Westerns and non-Westerns – does it make sense to extrapolate birth rates of Turkish descendants in 2015 from the historical birth rates of descendants of Norwegian women?] One third of the descendants of Western immigrants are above the age of 30, whereas only 6% of the descendants of non-Western immigrants are that old. (p.18)
*Descendants from Turkey, Pakistan, Jugoslavia or Morocco make up 77% of all 30+ year old descendants from non-Western countries. (p.18)
*The total fertility rate of Somali immigrants in Denmark is 3,937. (p.26)
*In the period 2006-2010, there were an average of 64.056 living births pr. year. In the same period, there were an average of 5.860 (9,1%) children born every year of non-Western immigrants and an average of 2.310 (3,6%) children every year born of Western immigrants. The average annual number of children of descendants over the time period was just 961. (p.26)

*The report has some stats on family patterns and the degree of observed endogamy. When it comes to male immigrants from Western countries who are classified as being in a relationship, in 59% of the cases the partner is of Danish origin and in 37% of the cases the partner is an immigrant from a Western country. When it comes to the female immigrants from a Western country, 63% of the partners are of Danish origin and in one-third of the cases it’s a Western immigrant. The pattern is different when it comes to immigrants from non-Western countries. For male immigrants from non-Western countries, 13% have partners of Danish origin and 80% have partners from a non-Western country. For female immigrants from non-Western countries, 28% have partners of Danish origin and 68% have partners of non-Western origin. Interestingly, when it comes to descendants Western immigrants are more likely to have a partner of Danish origin than are first generation immigrants (83% and 85% for males and females respectively), whereas this pattern is actually reversed for females from non-Western countries, where descendants are less likely to have a Danish partner than are first generation immigrants (19% of females who are descendants of immigrants from non-Western countries with a partner have a partner of Danish origin, whereas the corresponding number for the first generation non-Western female immigrants is 28%.) 3 out of 5 non-Western descendants who are in a relationship are in a relationship with a non-Western immigrant and 18% of them have a partner who’s also a descendant of immigrants from a non-Western country. (all numbers above from Tabel 1.9, p.32)
*When it comes to the non-Western females who find Danish male partners, few of these women come from the major immigrant countries. Of the 19.981 female non-Western immigrants with a partner of Danish origin, females from Thailand, Philippines, Russia, China, Brazil and Ukraine make up 11.644 of them – 58%. (p.33)
*Females from Thailand and Philippines alone make up 39% of the non-Western females who have partners of Danish origin. (p.34)
*When it comes to females from Turkey, Pakistan and Iraq, only 2% of them have a partner of Danish origin. (p.34)
*97% of female Turkish immigrants with a partner have a partner of Turkish origin. 94% of Pakistani females in a relationship have a partner of Pakistani origin. (p.35)
*88% of Turkish descendants in a relationship have a partner of Turkish origin. (p.37)

*Today the country from which Denmark receives the largest number of immigrants is Poland. Denmark received 3850 Polish immigrants in 2010. (p.38)
*(not direct citation but paraphrasing…)’Immigrants from Western countries like USA, Spain and Italy rarely come to Denmark to live here permanently and a large share of them leave Denmark again.’ – ‘This is not the case for non-Western immigrants.’ (p.40) Some data: 77% of the Poles who came to Denmark in 2002 had left the country by January 1st, 2011. 88% of the immigrants from the US who came in 2002 had left Denmark by 2011. On the other hand, only 9 percent of Iraqis who came in 2002 had left by 2011. 24% of the Turks who arrived in 2002 had left by 2011. (all numbers from table, p.39) [the 9% number is interesting also because during that time period, Denmark actually had various policies (Danish links) in place where Iraqis who decided to leave Denmark could get a one-time cash prize for doing so.]

This post dealt with roughly the first 40 pages of the report. The report has 153 pages. So there’s a lot of stuff to cover – there’s also data on education, crime, employment, ect. I might write another post or two on this subject if people liked this one.

Major related hint: If you’d like me to write another post on this, tell me, either by using the rating system or by commenting. If I don’t get positive feedback, I probably won’t do any more work on this – it adds a not insignificant time component to not being able to just quote directly from the report because the stuff needs to be translated as well.

January 15, 2013 Posted by | Reposts | 2 Comments

A repost: Some data

I first posted this one and a half years ago – here’s a link to the original post with comments.

From Pew:

From the report: “Nearly a decade after September 11, 2001, skepticism about the events of that day persists among Muslim publics. When asked whether they think groups of Arabs carried out the 9/11 attacks on the U.S., most Muslims in the nations surveyed say they do not believe this.

There is no Muslim public in which even 30% accept that Arabs conducted the attacks.”

“Muslims continue to believe there is widespread hostility toward them in the West. More than seven-in-ten think most or many Americans are hostile toward Muslims in the Palestinian territories, Turkey, and Pakistan, and solid majorities feel this way in Egypt and Jordan.

Moreover, perceptions of American hostility have increased since 2006 in four of the five countries where trends are available”

“On balance, respondents in the non-Muslim nations surveyed believe Muslims in their countries want to be distinct from the larger society. Majorities or pluralities hold this view in Western Europe, the U.S., Israel and Russia. This opinion is particularly widespread in Germany (72%), Spain (69%), and Russia (66%).”

“Among the Muslim publics surveyed, those in Lebanon offer the most positive ratings of Christians; 96% express a favorable opinion of the religious group, which makes up about 40% of the Lebanese population. Majorities of Muslims in Jordan (57%) and Indonesia (52%) also rate Christians favorably; Egyptian Muslims are nearly evenly divided, with 48% offering positive views and 47% saying they have an unfavorable opinion.

In contrast, Muslims in Turkey and Pakistan offer overwhelmingly negative views of Christians. In Turkey, just 6% of Muslims have a favorable view and 82% offer negative opinions of Christians; among Pakistani Muslims, 16% have positive opinions and 66% offer unfavorable views.” [my emphasis]

“Ratings of Jews are dismal in the seven predominantly Muslim nations surveyed. About one-in-ten (9%) Muslims in Indonesia, and even fewer in Turkey (4%), the Palestinian territories (4%), Lebanon (3%), Jordan (2%), Egypt (2%) and Pakistan (2%) express favorable opinions of Jews.”

“In the Arab countries surveyed, large majorities of Muslims who say some religions are more prone to violence consider Judaism to be the most violent religion; 97% in Jordan, 93% in Egypt, 88% in the Palestinian territories and 77% in Lebanon share this view.”

“On balance, Muslims in the predominantly Muslim countries surveyed are more likely to associate negative characteristics with Westerners than non-Muslims are to associate them with Muslims. For example, nearly nine-in-ten (89%) Jordanian Muslims use at least three of the six negative adjectives tested to describe people in Western countries, as do majorities in Egypt (81%), Turkey (73%), the Palestinian territories (71%), Pakistan (67%) and Indonesia (63%); only in Lebanon is this not the case.

In contrast, Spain is the only Western country surveyed where a majority (60%) of non-Muslims associate three or more negative characteristics with Muslims. At least three-in-ten non-Muslims in Britain (39%), the U.S. (35%) and France (30%) do not attribute any of the six negative characteristics tested to Muslims.”

The link has more.

January 13, 2013 Posted by | Reposts | Leave a comment


Right now I’m listening to Beethoven’s second symphony on my computer. There are probably about 100 people who contributed to that recording, thinking just in terms of the people sitting there with their instruments. Then there’s the person who recorded the piece. Of course there’s also the composer, but he died a long time ago. And there are the people who made the code that enables my computer to translate the zeros and ones into music. Then there are the people who made my computer, and my earphones, and the people who keep my internet connection up and running. The people who manage the power grid and make sure I have electricity so that I can play the piece without my computer shutting down because of power failure (in case the battery in it, which someone also made, needed to be recharged). I’m sitting in a room that is brightly lit. I don’t know who made the two lamps I have turned on right now, nor do I know who made sure the lamps were transported to a place close to me so that I could buy them, but I’m grateful that they did all that work.

I’m not in need of food at the moment – I had dinner a few hours ago, and I’m sure more people were involved in getting the stuff I ate from a) to b) than I’d like to think about; for one thing, people don’t grow bananas in Denmark in January. I would have gotten sick from eating the banana if I hadn’t been able to take medicine to help my body process the carbohydrates; I’m sure a lot of people were involved both in developing the medicine, producing it, and transporting it to a pharmacy close to where I live, so that I have access to it and am able to use it to keep my illness from killing me. If they didn’t do that work I’d die, so of course I’m grateful.

It’s not cold in my appartment – it’s a pleasant temperature, and it’s not really because of anything I did. Oh yes, there’s a thermostat I can adjust, true, but that wouldn’t really be worth a lot if the people who currently work on making sure that heat is produced and moved around stopped doing what they do. Part of why I’m not cold is that I’m wearing clothes. My t-shirt was made on a different continent thousands of kilometres away. The place where I currently live is not exactly new, and I didn’t build it. Other people did, in the past. I think there were a lot of people involved, because it’s a big building and they’ve used a lot of different materials once you start to have a closer look. Someone made a big window so that even though I’m inside, I can look out and see what’s going on outside. Or I can decide not to, by closing the curtains someone made at some point and had other people transport to a shop near where I live, where I was able to buy them. I say ‘near’ where I live, but it’s not really – if I had to walk on my own two feet, it would have taken me more than an hour to get to the shop. I don’t recall which mode of transportation I used instead, which is in itself rather interesting – there are so many different ones (parents’ car, bicycle, bus?) that it’s hard to keep track of how you’ve gotten around.

I’m sitting down on a chair, which is nice. It’s much better than standing up or sitting down on the floor. I wonder how many people were involved in the process of producing the chair, transporting it, selling it… The same questions could be asked about the table the computer is standing on.

The hot food I got before I ate the banana wasn’t always hot. Some of it used to be very cold, it was taken from the freezer. You know, the thing most people own and that they use to put stuff in to keep it cold, even though it’s actually quite cold outside, so that the food can stay fresh much longer and won’t spoil – the thing that was made on some factory far away, much farther away than I could have travelled in a week if I had to walk there. Of course I didn’t heat up the food by starting a fire in my kitchen – for one thing, someone has made a smoke alarm which is set up quite close to my kitchen so that would not have worked very well. No, I used a stove which someone somewhere has made so that people like me can heat up the food I take out of my other machine keeping it cold until it needs to be heated up. And I didn’t eat the food with my hands – well, in a way I did, but I also used a knife, which is probably made in some other country, and a fork – which is also likely made in some other country.

I’m not worried about being unable to locate a source of potable water in case I get thirsty soon. This is because from where I sit I have less than 10 metres to a sink and a faucet, out of which I can make water come out – almost as if by magic. I don’t know the people who make sure that the pipes are clean and that the water is not contaminated with bugs I wouldn’t even be able to see if they were in the water, or perhaps toxins and/or heavy metals which could also easily make me sick; I sort of take it for granted that water comes out of the faucet when I want it to and that I’ll not get sick from drinking it. Not only that – I take it for granted that I have control over the temperature of the water.

I think people radically underestimate how much their continued existence, to speak nothing of ‘the kind of life they lead at this point’, depends upon people whom they have never even met.

On a related note I generally feel like crap this time of year – the exam periods really have included many of the worst times of my life. But there’s stuff to be grateful for. Stuff to keep remembering. Thoughts like these make it a bit harder for me to feel sorry for myself. I don’t want to feel sorry for myself – in my experience it only if anything tends to make things worse.

January 11, 2013 Posted by | personal, random stuff | 1 Comment

A repost: Some stuff on lotteries

I’ve reconsidered my decision not to update the blog over the next days. But as I don’t have time to actually do blogging-worthy stuff I’ve decided to repost some material from the archives that I’m not too ashamed of having posted here (the posts I’m reposting should incidentally in no way be construed as an argument for going through my archives – there’s a lot of crappy stuff hidden away there and it’s just not worth it…). The original post is from May 2011 and the only change I’ve made to the post is to remove the last part requesting feedback from readers (I probably would not consider writing such an addendum if I were to write a similar post today). Anyway, here goes:

Let’s say you have a population of n (ex ante) identical individuals each making an income of w. Say you now decide to set up a simple voluntary tax-transfer type scheme, where all individuals who choose to participate are required to pay an amount (/tax), t. The contribution/tax t is used to finance a transfer T, which is equal to n*t (the sum of all contributions, i.e. there’s no administration or anything like that to start with). Each individual has a 1/n probability of receiving the transfer T, so that the expected payoff of this scheme is equal to the probability of receiving the transfer times the size of the transfer minus the contribution, or 1/n*(n*t)-t. Which is equal to 0 and independent of both t and n. The expected income of an agent participating in the scheme is w + EP = w.

A risk averse individual will always choose not to participate. A risk neutral is indifferent between participating and not participating given that the reservation utility is 0. Note that even if the expected payoff of the scheme is ‘mathematically’ zero, the way most people think about a scheme like this (..out of context at least, when talking pure math) is that you’re most likely to lose if you participate, especially if n is sufficiently high. If a million people participate and there’s one transfer each month, then the likelihood that you’ll have gotten your money from the contributions back after a year is not very big.

It’s probably even lower than you realize, if you’re not familiar with statistics. To illustrate why this is, let’s get a little more technical. There’s one transfer T each timeperiod. There are n people who participate in the scheme. Now assume that your likelihood of getting a transfer next period does not depend on who got it last period. You can think of it as an assumption stating that an individual can receive several transfers if he or she is very lucky. This assumption is important, but I also think it’s justified in the empirical framework I’m attempting to apply this to – it would be completely justified if the scheme was mandatory, but regarding lotteries we know that a) at least some lottery winners play on after they’ve won anyway and, far more important, b) that the number of participants in real world lotteries is pretty much independent of the behaviour of the winners ex post (1 marginal lottery winner does not translate to one less lottery participant in general) [where ‘behaviour’ here relates only to the decision as to whether to participate in future lotteries or not]. If you don’t like to think of it as an assumption about past winners playing along after they’ve won, you can think of it as new people entering the scheme after past winners decide to exit, keeping the probability of winning constant over time.

Now perhaps a not uncommon way to misunderstand how this works is for people who don’t know statistics to think/assume that if you have 52 participants and 52 weeks of contributions/transfers, then the probability that you receive a transfer is equal to 1 after one year. It’s not, it’s lower than that, because some lucky guy might win 2 times and get the transfer instead of you. The only case where you can be certain to have won after a year is in the case where nobody can win more than once. In that case, the conditional probability of winning is increasing over time – the chance of winning the first lottery is 1/52, if you don’t win the first lottery you have a 1 in 51 chance of winning the next lottery, ect. I’d like to instead look only at the case where the conditional probability of winning is constant over time.

The probability that an individual i will receive a transfer before period k, where k is equal to 1,2,3…, follows in that case what is called a geometric distribution, which is itself a negative binomial distribution (I know I’ve linked to that one not long ago here on the blog) with r = 1. The cumulative distribution function, which in this specific case can be thought of as a function telling us how likely we are to have gotten a transfer by the time we reach period k, is equal to 1 – (1 – p)^k. To make this a bit easier, think of throws with a die. After one attempt, the likelihood of rolling a 6 is 1 – (1 – 1/6)^1 = 1 – 5/6 = 1/6 (we knew that!). The likelihood of rolling a 6 after exactly two attempts is equal to: 1 – (1 – 1/6)^2 = 1 – (5/6)^2 = 1 – 25/36 = 11/36. Note that this is smaller than 1/3 (or 12/36) for reasons already mentioned; when outcomes are independent, you can’t just add the probabilities to get your estimate. Also note that the probability of getting that damn 6 is of course increasing in the number of attempts. Now what’s the probability that you will not have rolled a 6 after 10 throws? Probably higher than most people think: 1 – [1 – (1 – 1/6)^10] = 0,1615, which is a tiny bit lower than the probability of rolling a 6 in the first attempt. Note that here I take advantage of the fact that there are only two outcomes [roll 6 or don’t roll 6] and that the probability of not rolling 6 in a sequence is equal to 1 minus the probability of doing it (mutually exclusive & collective exhaustive and all that..).

Now if we have a lottery with 1 million people participating (p = 1/1.000.000) and one transfer handed out each week, what’s the probability that you’ve not gotten a transfer after 10 years of participation (k=520, 52 weeks in one year…)? Putting in the numbers we get 1 – {1 – (1 – 1/1.000.000)^520} = 0,99948 = 99,948%. The funny thing here is also that the transfer is uncertain but the contributions are not, so if you assume weekly contributions of value $5 over the 10 year period, the certain costs are $5 * 520 weeks = $2.600. So if you play along in this lottery, you pay $2,600 and get nothing with 99,9% certainty. The expected payout from the lottery is of course the same as the amount you pay, as the transfer is $5.000.000 and and the probability of getting the transfer each period is one in a million, so that expected payout is 520/1.000.000*5.000.000= 520*5 = 2600 and the expected total payoff is 0.

Now here’s a twist some of the people who participate in schemes such as these probably don’t fully understand: Assume you try to buy two lottery tickets instead of one to increase your chances of winning. How does that affect the expected payoff? We already know. By assumption it doesn’t, because EP = 0 in our model (see the beginning and above). It also doesn’t matter how many times (weeks) you play, you can’t increase your chances in expected terms by playing for a longer period. Another thing is that in the real world the expected payoff of participating in a lottery is of course always negative – because it takes work and effort to make lotteries work, the contributions need to cover the costs of selling the lottery tickets, tv ads, tax compliance and administration, ect. In the real world, when you buy another lottery ticket, your expected payoff goes down. So to return to our model, if you think it would be mad to participate in a lottery where you pay $2,600 ove a decade and end up with nothing with 99,9% certainty, you should be aware of the fact that these odds are better than the ones offered by real-world lotteries. In the real world, the deal offered is even worse.

People who claim to be in favour of income distribution from rich to poor who also participate in lotteries are kind of funny. They say they want one thing from the political system, then they voluntarily decide to participate in a redistribution mechanism which will always have the exact opposite result. When you have a lottery where the winner takes all or most of the money, you redistribute from everybody to one (/soon to be) very rich guy. I know that lotteries hand out both large transfers and small, but on net most of the small transfers probably cancel out because that’s part of what keep people playing.

January 10, 2013 Posted by | Reposts | Leave a comment


Sorry for the lack of updates – I have explained the reasons for my inactivity here, and it will have to last a bit longer.

I had an exam today – I passed, and it went quite well.

I plan on studying ~10 hours/day over the next week and so I will not have much time for blogging. You can expect me to get ‘back to normal’ in the last part of January (in another 10 days or so).

January 9, 2013 Posted by | blogging, personal | Leave a comment


I have exams coming up and so I won’t post much during the next couple of weeks.

I’d like to point out to new readers in particular that I posted more than 200 posts last year. Even though posting frequency will be low for a little while, this is hardly an inactive blog in general.

January 3, 2013 Posted by | blogging | Leave a comment

Poor modelling

A few recent examples:

i. I played Citadels with my little brother this Christmas. I spotted two obvious instances of poor modelling which happened during the game.

The game is complex and I won’t go over all the rules here – it should be noted that the game complexity is probably part of why these errors to be described below were made in the first place. But anyway, we were in a situation where my brother had picked a specific card. Having picked that specific card he had to try to guess which card I had on my hand – if he guessed correctly, I’d lose my turn and the income that turn would generate (which would benefit him and harm me, making him more likely to win the game). There were two obvious candidates; one card generating a potential income of 2 and another other card generating a potential income of 5. He knew I’d taken one of these cards but not which of them I’d picked – if I randomized my draw completely there’d thus be a 50% chance for him to pick the right card. The situation took place during one ’round’ (subgame) of the game, and both of us knew that this would not be the last round in the game. But we did not know how many more rounds were to be played – a conservative estimate would be at least 4 or 5. Whether it would make sense to consider the round to be one round of several in a semi-‘pure’ repeated game or not, and which type of repeated game we’re talking about, depended to some extent on which cards would be picked in future rounds (as I mentioned, the game is complicated – the fundamentals of the stage game can change during gameplay, e.g. I might end up in my brother’s position, i.e. as the player who should guess which card the other player had taken, in a future round); but it would make little sense to consider it a single-shot game.

Now the first thing to note here is that if you consider it a repeated game, it probably doesn’t make a lot of sense not to at least consider to mix strategies. You could probably make an even stronger argument: Consider that if I play ‘2’ (the card giving me an income of 2) with a probability of 100 % my brother would probably pick up on that relatively fast and pick that card every round, and I’d end up with an income of zero – and if I always played ‘5’, he’d always pick 5. So the second person, the one picking the card to be guessed, has to consider adding some uncertainty to the table or he’s probably going to be in trouble. Now let’s think about how one might best mix strategies in this situation. An important theoretical aspect here is that while it’s certainly a finite game, the lenght of the game is still unknown, or at least uncertain, to the players (they do have some idea how long it’ll take to finish the game). This uncertainty adds complexity, and even though only relatively few rounds of the game is left, the game is still much too complex to be solvable by backwards induction by the players while they play the game even if such a solution might exist. Incidentally in the specific game in question when playing that specific subgame I evaluated the costs of reversing the roles of the players (so that I’d get to be the one guessing, which would be a permissible change to the stage game given a specific subgame strategy constellation) to be too high to implement – but my brother didn’t know that.

The first modelling error here was done by me when I was deciding which card to pick. I did pure randomization when I picked my card – basically I shuffled the cards and picked one of the two cards at random. Basically this was just me being stupid, because this is obviously not the best mixed strategy (it’s only optimal in the case where the expected income derived from the two cards are equal). One way to think about this is that a 50% likelihood of picking either card gives you an expected income of 0,5 x 2 + 0,5 x 5 = 3,5 if your opponent also mixes 50/50 – and foolishly I’d considered only that strategic response to my mixing strategy. The problem is that of course the opponent needn’t mix at all! A mixing strategy on his part is obviously dominated by the pure strategy of always picking ‘5’ – if he always picks ‘5’, I end up with an average income of only 1 (I get an income of 2 every second round). I realized this 5 seconds after I’d picked my card..

This is where we get to the second modelling error. My little brother said after that specific round had been played – where he’d picked 5 and I’d gotten lucky and randomly picked 2 (so the inferior strategy did not cost me anything in this specific case) that ‘of course he’d picked 5, it was the dominant strategy’. I thought that this was obviously true in the specific case of a mixing strategy on my part with 50/50 mixing, but that it would not be an optimal response to other mixing strategies with a low probability of playing ‘5’ (nor would it be an optimal response to the pure strategy of 2). I assumed we’d play at least four more rounds, and in that case it would probably be optimal to go with a mixing strategy with a ~30/70% likelihood or something along those lines (i.e. one ‘5’ and 3 ‘2’s in the rounds to come) – I figured that 5 is 2,5 as much as 2, so I should play ‘2’ 2,5 times as often as ‘5’ in equilibrium; i.e. 2,5 ‘2’s for every 1 ‘5’, meaning I should play ‘2’ in 2,5 out of 3,5 rounds, which would be about 70% of the time. I assumed my little brother would mix as well in the rounds to come when I would no longer obviously mix 50/50 and that he’d reach a similar conclusion – that he should pick 5 more often than 2 to minimize my potential income and end up near the (assumed) long-run equilibrium. After the game my little brother made it clear to me that he had not mixed but had played 5 every time, and he stated that he’d picked that strategy because it was ‘the dominant strategy’ and because it would be his best response to any strategy I could come up with. Which it clearly wasn’t.

ii. I went shopping yesterday. I got to the store and it was full of people. I generally dislike shopping when there’s a lot of people around, and I generally avoid this by strategically shopping at times during the day where I know not very many people go shopping. I have previously arrived to a store, decided it was too full of people and postponed my shopping to a later point in time because of that, but yesterday I decided instead to just get it over with fast. When I came back home I remembered that it’s been mentioned in the papers that a lot of people are sick with influenza in Aarhus, and so I realized that I’d just exposed myself to a huge health risk considering how many people were in the store. If asked about this type of stuff before I left my home, I’d have said that such a risk would be completely unacceptable to me, because I have exams before long and thus it would be very inconvenient for me to get sick at this point. If I’d included that health risk in my model, I would not have gone shopping yesterday.

I will often avoid taking public transportation when it’s possible for me to do so due to similar health-related reasons – diseases are easily transmitted in such environments. People often do not remember to include risks like these in their mental models. That’s poor modelling.

Even (reasonably) simple card games and everyday decisions about stuff like when and where to go grocery shopping can include models too complex for humans to handle well; our cognitive limitations are easy to ignore if we don’t think about them, but they’re there just the same. Social dynamics are usually a lot more complex to model than the stuff in the post. Sometimes it seems almost unbelievable to me that people somehow make all this stuff work – taking all those decisions they do on an average day, interacting with all those other people along the way… Given how complex the world is and how even very simple things like a card game can cause us all kinds of problems when we start thinking about them, I find this pretty amazing to think about.

January 1, 2013 Posted by | Game theory, rambling nonsense, random stuff | 3 Comments