New experimental evidence of the effect of language on economic decisions

This is a guest post by Cole Robertson.

Readers of this blog are likely to be familiar with controversy surrounding Keith Chen’s (2013) findings suggesting that the way a language deals with the future tense affects speakers’ economic decisions. A new study by a group of Austrian and German economists has recently added experimental evidence to the growing body of research on the issue.

The study focuses on German and Italian. As with English, Italian requires a speaker to mark the future tense, e.g. “it will rain tomorrow” not simply “it rains tomorrow.” German, on the other hand, requires no such marking—speakers are free to say the equivalent of “it rains tomorrow.”

Chen hypothesized that speaking about future event using the present tense, as in languages like German, could make the future seem more immediate. He suggested this might cause speakers to value future events more highly than speakers of languages like Italian. Indeed, using large-scale statistical methods, Chen found that speakers of languages like German (with no separate future tense) tend to smoke less, be less obese, engage in safer sex practices, retire with more money, and save more per year.

His findings have been criticized on various grounds, from potential inconsistencies in the data, to small number bias in the original dataset, to the fact that the hypothesis could easily have been formulated the other way around, to the fact that Chen’s classification of how languages refer to the future may be overly simplistic.

However, most criticism has centred around the potential spuriousness of the correlation between future tense marking and future orientated behaviour. Commentators have been quick to point out that since cultural traits tend to be inherited in packages, it’s likely that future orientation and future tense reference are causally unrelated. In fact, Roberts, Winters and Chen (2015) found that the correlation dropped below significance when controlling for cultural relatedness (for some if not all their statistical tests). As such, the jury may yet be hung until experimental evidence confirms (or doesn’t) Chen’s findings.

The new study attempts to do exactly this. Though not yet peer reviewed, it was recently opened to comments and criticism as a discussion paper, as apparently is common in the discipline of economics.  You can read it here.

Meran / Merano / Maran

The paper takes advantage of bilingualism in the city of Meran in the autonomous province of South Tyrol in Northern Italy, where roughly 50% of the population speaks German and the other 50% speaks Italian. Hoping to mitigate the cultural confounds that plagued Chen’s (2013) findings, the authors argue that since the German- and Italian-speaking citizens of Meran share a home city, they also share a similar enough cultural milieu that experimenting on them can isolate the effects of their language on how they value future events.

The experiment worked like this: children were presented with three choices. In each of the choices they could either accept two tokens at the time of the test or opt instead to receive a greater number of tokens four weeks in the future (the ‘patient’ choice). The future rewards were three, four, or five tokens. So in other words, children had to choose three times, between: 1) two tokens now and three tokens in four weeks, 2) two tokens now and four tokens in four weeks, and 3) two tokens now and five tokens in four weeks.

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One of these choices was randomly selected for their actual pay-out, and they could then trade the tokens for a selection of small toys and items the experimenters had on offer. As control variables, they also measured IQ relative to cohort, the income and education of the parents, the children’s risk-taking propensity, average housing prices in the area of the school, and whether the children had friends who spoke another language.

In presenting their results they begin with a sample of just those students both of whose parents speak either German or Italian (n=860). They then progressively add students from different linguistic groups to their sample. They start with (n=203) students from bilingual German-Italian households, then add (n=261) students from household where both parents speak a language which has a future tense (like Italian) but which is not Italian. They then treat these delineations as categorical variables and use both regressions and non-parametric tests to see whether a child’s language category affects their tendency to wait for future rewards.

Their results suggest that it does. In the first sample, the German-speaking children were more likely to wait for the future reward than the Italian-speaking children, across all age groups and when including the host of control variables. Moreover, when they added the German-Italian bilingual group to the sample, their tendency to wait for future rewards was intermediate between the all-Italian and all-German children. Finally, they find that the (n=261) student who speak a language which marks the future tense, but which is not Italian, are significantly less likely to wait for future rewards compared to German speaking children, but are not significantly different from the Italian cohort.

They also separately analyse (n=91) students one of whose parents speak German or Italian and the other of whose parents (except for 5 cases) speaks a language which, like Italian, mandates marking of the future tense. They find that children with one German-speaking parent and one future-tense-marking parent are more likely to wait for future rewards than children with one Italian-speaking parent and another future-tense-marking parent.

Should these results be trusted? There are some strange statistics in the paper; throughout, they use multiple Mann-Whitney U Tests when comparing more than two groups, but never report any kind of post-hoc correction for multiple comparisons. With some p-values reported at the < .05 level, this could be problematic for some of their findings. Whilst their regressions would not be affected, I have to assume they present non-parametric tests because at least some of their data violate normality assumptions.

However, their results are corroborated by a second experiment which uses a slightly different discounting task and which only has two groups (all German and all Italian) and is therefore not affected by any apparent failure to correct for multiple comparisons.

They also include several other robustness tests. They make sure risk attitudes (which they find predict propensity to wait for future pay outs) are not correlated with language group (they aren’t). Although, whether this reveals anything more than their multiple regressions is unclear, since they already revealed a result whilst controlling for any correlation between the two variables. Additionally, they survey (n=177) Meraners to check whether there are any differences between the Italian and German populations in terms of their attitudes towards the importance of “thrift” and “patience.” Finding no such differences, they argue that this supports the conclusions that there are no cultural differences confounding their findings.

However, can we really trust self-reported estimations of the importance of thrift and patience? Most people know that they should say these are important, so is it really possible to rule out implicit demand characteristics that might undermine actual differences between the two language groups?

In fact, even according to the authors themselves, the German- and Italian-speaking populations in Meran remain linguistically and culturally “fairly segregated, with different media (like newspapers or TV channels) and leisure activities (like different football clubs)” (Sutter et al, 2015 p. 5). Schools are evidently also segregated by language, teaching either in Italian or German, and no schools to-date have an equal number of Italian and German students.

Indeed, relations between the Italian- and German-speaking people in South Tyrol may not be as copasetic as they are portrayed to be by the authors. In fact, there is evidence that tensions have been simmering since Mussolini attempted to “Italianise” the area in the 1930s by mass relocating Southern Italians northwards.  Activism in the 1960s (including violent conflict) eventually lead to a bilingual language accord, and significant autonomy from Rome in 1972. Today, German speakers accuse Italian authorities of racism and “linguistic imperialism”, whilst Italians accuse Germans of receiving preferential treatment. There have even been arguments over the language of signage on alpine hiking routes , which eventually sparked a felt-tipped graffiti war that quickly degenerated into racial profanity.  As such, is it really possible to rule out cultural confounds? As a Canadian who has lived in Montreal, the epicentre of Canadian French-English bilingual conflict, I can personally attest to the fact that geography and culture are not the same thing.

Moreover, the experiment does not actually manipulate children’s responses; it merely applies the same test to children from different language groups. What is strange is that there may actually be an unreported manipulation in the experiment. Since the authors only state that the test prompts were given in the child’s “mother tongue”, I would assume that some of the (n=203) bilingual children were tested in Italian and some in German. This means that the researchers hopefully have (or might be able to get) data on whether the language of the test prompt affected the children’s propensity to wait for future rewards.

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Until they include these results in the analysis, their findings seem to be subject to the same criticisms levelled against Chen (2013). In other words, they may be picking up on a spurious correlation resulting from the fact that thriftiness and tense structure, whilst causally unrelated, could have been co-inherited from antecedent cultural groups.

If the Italian and German populations in South Tyrol are as alienated and segregated as they seem to be, it’s entirely possible that the German-speakers inherited increased thriftiness as well as a language without a future tense, whilst the Italian-speakers inherited decreased thriftiness as well as a language with a future tense. They need not be causally related, and the speakers’ geographical proximity may not have been enough to override these packages of traits. Until we see a language-based manipulation of future-orientated behaviour, the issue of whether tense affects how we value future events will remain unresolved.

References

Chen, M. K. (2013). “The Effect of Language on Economic Behavior: Evidence from Savings Rates, Health Behaviors, and Retirement Assets.” American Economic Review 103(2): 690-731.

Roberts, S. G., Winters, J. & Chen, M. K. (2015). “Future Tense and Economic Decisions: Controlling for Cultural Evolution.” PLoS One 10(7): e0132145.

Sutter, M., et al. (2015). “The Effect of Language on Economic Behavior: Experimental Evidence from Children’s Intertemporal Choices.” IZA Discussion Paper Series 9383.

cole faceshotCole Robertson lives and works in Oxford, where he is completing a PhD focusing on inter-linguistic tense differences and future-orientated behavior, but he’s generally interested in how language interfaces with other cognitive, perceptual, and behavioural systems, as well as language revitalization and language evolution. He’s an avid rock climber and mountaineer and once spent two days eating nothing but sausages cooked over a candle whilst waiting out a storm. He grew up in Vancouver, Canada.

CreaStoria: Experimenting with collaborative stories

This is a guest post by Christine Cuskley

TL;DR: Please and thank you play this thing for science.

Insofar as the field of language evolution has even had time to spill a lot of ink about anything – if you take Pinker & Bloom’s seminal 1990 paper as the starting point, the field is only just a carefree twenty-something – the focus of the field has primarily been about the finer points of language: syntax, the lexicon, the physiology of speech production, etc. But one’s mid-twenties are a time for exploration, so, with my colleagues at the Social Dynamics Unit, we’re looking towards something relatively unexplored in language evolution: stories.

It’s almost impossible to imagine telling a story without language – how would you even begin? (Even Emoji Dick had to be translated from the original, and might not even be successful, and emojis arguably are language…but I digress…) So the questions emerge: why and how do we tell stories? Do stories simply take advantage of our ability to speak about things that are not present and/or are not concrete (or even real), or are they a key part in how language evolved the ability to do this? How do stories evolve over time and respond to cultural pressures? What kinds of features of stories survive and replicate, and what features peter off and die? What selection pressures underlie this?

This is, of course a whole host of questions, none of which we can expect to find definitive answers to anytime soon – a feature shared by a lot of work in language evolution (and an exciting one, in my opinion). And of course, we’re not jumping into a void: already there is work that focuses on the phylogeny of stories, the potential evolutionary function of stories, and also a fair bit of work on evolution in literature more generally, some of it featured right here on Replicated Typo. But we’re taking a new experimental approach: we’re crowd sourcing collaborative stories. We hope this will contribute to answering the last two questions in particular: how do stories evolve over time and respond to different constraints, and what features survive and replicate?

We’re doing this using an experimental game called CreaStoria – and the more players we have, the better! So please play! The game is a hybrid of choose your own adventure, Twitter, and a creative writing workshop. It works like this: we start with a bunch of single-sentence “story prompts” created in collaboration with Piano Piano Book Bakery in Rome, and these stories become the “root” for collaborative story trees. At each turn, a player is presented with three potential stories and has to choose which one to continue with their own short story, creating an element of preferential selection. After you’ve played, or between bouts of play (I hear it’s great for procrastination, so feel free to come and go as you need it), you can look at the growing story tree and vote on stories you like (or don’t).

The inner workings are a bit more complicated than this, of course – I could tell you, but I’d have to “know your IP address and exclude any stories you write from our data” (if you know what I mean). We’ve had the opportunity to exhibit the game at a couple of live events in Italy, so the tree of Italian stories is pretty well populated – but we would really like more English data (and having a lot of both could lead to some interesting contrasts), so play now and tell your friends! If you’re curious as to how the data pans out, like the game on Facebook or follow @creastoria on Twitter to get updates.

Happy writing!

Christine Cuskley is a linguist/psychologist/nerd type who currently researches the evolution of language and communication in the Social Dynamics Unit at the Institute for Scientific Interchange in Turin, Italy, and will take up a position as a British Academy Postdoctoral Fellow at the University of Edinburgh from January 2016. She mostly retweets at @nerdpro.

Universal Principles in the Repair of Communication Problems

Yesterday, my colleagues and I published a paper on Universal Principles in the Repair of Communication Problems.

People are constantly having problems with communication, like these two people:

In this paper, a team of linguists looked at over 2000 cases of problems with communication in 12 languages.  On average, people have a problem with understanding every 90 seconds! The team coded each instance and found that the same 3 basic tools were used in each language:

  • Open Request: Signalling a problem with the whole utterance (Huh?)
  • Restricted Request: Asking for clarification of a part (Go where?)
  • Restricted Offer: Asking for confirmation of what was heard (Go between them?)

Each tool is increasingly specific about the source of the problem, but takes longer on average to produce.  This means that the amount of work to repair the problem is shared between the speakers.  We can see this in the following graph:  The more I contribute to repair in initiation, the less you have to contribute in response:

journal.pone.0136100.g005

We also found that, on average, a problem takes about as long to repair as it did to produce, regardless of type.

What this suggests is that people have a pro-social bias.  In principle, any problem can be fixed with the easy-to-produce huh?  So if people were being selfish, they might just produce this all the time.  However,  each langauge uses each type, which suggests that listeners try to help out as much as they can:  speakers treat conversation as a joint activity and try to work together to fix problems.

We found some variation between languages in the proportion of repair types used.  However, we also found that the same factors which cause problems (e.g. noise, parallel activities) affected which tool was chosen in the same way across all languages.   That is, the repair system works in the same way for all languages.

This was tested using a mixed effects model which controlled for the shared history between languages.  Specifically, we show that knowing what language was being spoken does not help predict what type of repair was used, over and above factors which cause problems.  I’m quite proud of this mix of qualitative coding, quantitative measures and statistical methods.  With 12 authors from 6 institutions, it’s also a great example of collaborative science.  12 languages may not seem like much compared to typological studies of language structure, but it has to be kept in mind that the instances come from recordings of ordinary conversations which are then transcribed, translated and coded (48 hours of video in total!).  The languages are also far from a convenience sample, ranging from Yeli Dyne in Papua to Argentine Sign Language.

As far as we know, no other species has this kind of sophisticated set of tools for solving communication problems.  In fact, even basic repair seems to be unique to humans.  We suggest, then, that this system of repair is a universal principle of human communication which emerges from a need to be understood in a noisy world.

You can read the paper here, and some more details on the ideophone blog.

EvoLang paper submission now open

The website for paper submission to EvoLang XI is now open.  The link is here (external EasyChair link).

The deadline is September 4th, 2015.

This year there will be no printed book of papers.  All accepted papers will be made available online.  The submission form also allows an optional tweet-length summary, which will be included in the printed proceedings alongside the title and will be live-tweeded during the conference.

It’s possible to include supplementary materials alongside the submission.  Authors are encouraged to make data or code available, but all information necessary to understand and evaluate the submission should be included in the main paper.  Reviewers will not see the supplementary materials.

All supplementary materials should be submitted within a single zip file, which should also include a readme file describing the contents.  Supplementary materials should be referenced in the main text (e.g. “see supplementary materials”).

See the conference website for more details.

EvoLang XI: Call for workshop proposals

In addition to the general session, The 11th Evolution of Language Conference will be able to host a number of thematically focused half-day workshops to be held between 09:00 and 13:45 on the first day of the conference March 21st (e.g. accommodating 8 half-hour slots, 15 minutes for an introduction, and 30 minutes for a coffee break).

Workshop proposals should be sent to EvoLang2016@gmail.com by October 2nd, 2015.  Proposals should include a title, the names of the organisers and a one paragraph summary of the theme.

Notification of acceptance will be given by October 16th, 2015. The responsibility for the detailed scheduling of the workshops and for the quality of workshop contributions will rest with workshop conveners. It is suggested that the workshop contributions be short papers (e.g. 4 pages) in the format of the main submissions to the conference (see the Call for Papers section of the website).  It will be possible to publish the workshop papers online, alongside the main conference papers.  A list of workshops from the previous conferences is available here.

For more information, see the EvoLangXI website.

Plenaries for EvoLang announced

The plenary speakers for EvoLang XI have been announced.  As well as standard plenaries, there are two discussion plenaries, focussed on a theme with discussants taking different positions.

The deadline for paper submission is the 4th of Setpember 2015 (see the conference website).

EvoLangXIPlenaries2

Discussion Plenaries

Language localization in the brain

Gricean communication

Single Plenaries

  • Vincent Janik (dolphin communication, Biology, University of St. Andrews)
  • Joan Bybee (usage-based grammaticalization, Linguistics, University of New Mexico)
  • Ljiljana Progovac (Evolution of Syntax, Linguistics,Wayne State University)
  • Erich Jarvis (neurobiology of birdsong, Neurobiology, Duke University)
  • Dean Falk (paleoneurology/motherese, Anthropology, Florida State University)

Future tense and saving money: methods

Our recent paper on testing the correlation between future tense and saving money uses a variety of statistical methods, which I’ll summarise in this post.

The challenge was looking at correlations between traits of individual people while controlling for properties of their cultural history. Saving money is an individual trait which can change in the short term, while languages are properties of groups which change over very long periods of time. In addition, we would like to control for three sources of non-independence: similarities between people’s economic conditions caused by them being in the same state, similarities in their language and culture caused by historical relations and similarities in their language and culture caused by cultural contact. So if you’re one of those people who always have a hard time saving money, this might be your chance to do so thanks to resources like the Cryptsy blog.

Continue reading “Future tense and saving money: methods”