Individual Experience of Positive and Negative Growth is Asymmetric: Global Evidence from Subjective Well-being Data

A very interesting new Centre for Economic Performance Discussion Paper by Jan-Emmanuel De Neve (who presented at our last ESRC-funded workshop), George W. Ward, Femke De Keulenaer, Bert Van Landeghem, Georgios Kavetsos and Michael I. Norton.

Abstract: Are individuals more sensitive to losses than gains in macroeconomic growth? Using subjective well-being measures across three large data sets, we observe an asymmetry in the way positive and negative economic growth are experienced, with losses having more than twice as much impact on individual happiness as compared to equivalent gains. We use Gallup World Poll data drawn from 151 countries, BRFSS data taken from a representative sample of 2.5 million US respondents, and Eurobarometer data that cover multiple business cycles over four decades. This research provides a new perspective on the welfare cost of business cycles with implications for growth policy and our understanding of the long-run relationship between GDP and subjective well-being.

Investing in LEDs

Yesterday’s Nobel prize in physics was awarded for “the invention of efficient blue light-emitting diodes which has enabled bright and energy-saving white light sources.” Many people know the benefits of switching from traditional incandescent lightbulbs to energy-saving bulbs (CFLs); LEDs are an even better technology, although struggling to gain public awareness.

LEDs are much better than CFLs. The slow warm-up time of CFLs meant some people were reluctant to switch over from traditional incandescent bulbs; this is not a problem with LEDs. LEDs hit full brightness on switch-on. LEDs emit less heat than CFLs, and are even more energy-efficient. LEDs also last much longer than CFLs. While CFLs last longer (8,000 hours) than incandescent bulbs (1,000) hours, LEDs again trump the pack at 30,000 hours+.

LEDs are more environmentally-friendly than CFLs, but LEDs can lead to big savings too. Switching to LEDs could save the nation 10% of its electricity bill, while the technology itself is constantly improving. LED bulbs are now available for pretty much any household light fitting. LEDs come in warm white (a similar colour light to traditional bulbs), or cool white (a sharper and brighter white).

Meanwhile, political debate in the UK is centred on how spending cuts, especially benefits cuts, can help reduce the deficit. The UK government can currently borrow for 30 years (around the life of LED bulbs) at a cost of 3%/year. Research by the Energy Savings Trust on LEDs in public housing suggests a pay-back period of around nine years (p.24) – good enough to justify investment, but a period which could be reduced further with technological improvements and scale efficiencies. Investing in LEDs for public infrastructure would be one way to cut the UK’s long-term deficit. Although borrowing will go up today, since the annual cost savings exceed the interest rate, the public purse would be significantly better-off in thirty years’ time.

Hopefully this well-deserved Nobel prize will help raise more awareness among households, firms and governments about the environmental and economic benefits of investing in LEDs.

Behavioural Exchange 2015 (BX2015)

Details of this very exciting event below from the Behavioural Insights Team website. 

"On 2 and 3 September 2015, the Behavioural Insights Team will host the largest gathering of the world’s greatest behavioural scientists and policy practitioners.
There will be space for some 500 delegates over two days, with sessions that combine the latest academic findings with real-world results from projects being undertaken by governments around the world.

We already have a stellar cast list of speakers, including:

Professor Daniel Kahneman, Nobel Laureate and author of Thinking, Fast and Slow

Professor Richard Thaler, author of Nudge and long-term advisor to the Behavioural Insights Team

Professor Max Bazerman, author of The Power of Noticing and co-director of the Harvard Behavioral Insights Group

Dr David Halpern, author of The Hidden Wealth of Nations and Chief Executive of the Behavioural Insights Team.

You can register your interest in attending BX2015 by sending an email with the subject heading ‘Register My Interest’ to: BX2015@behaviouralinsights.co.uk " 

Nalmefene

A story discussed a lot in the media today (e.g. here here) is the proposal to extend the prescription of Nalmefene, an opioid receptor modulator used to reduce alcohol cravings, to up to 600 thousand heavy drinkers (loosely defined as people drinking 3 pints or half a bottle of wine per night) in the UK. It would be offered free on the standard NHS prescription package. The proposal has the initial backing of  the National Institute for Clinical Excellence (NICE ) based on their estimates of the cost of alcohol dependence, the costs of the drug and associated treatments, and the potential effectiveness of the drug in reducing alcohol craving. The proposal raises a lot of fascinating questions about the ethics, effectiveness and desirability of different types of behavioural interventions. In terms of the debate on libertarian paternalism, there is arguably an element of "nudging" in the proposal in that it is being offered to people to take up voluntarily. However, it is not usual to think of nudges as being consumed in the form of pharmaceutical products. Also, those who believe policy should be more directed at creating supportive choice environments might baulk at the potential nihilism inherent in a strategy that seeks to act directly on individual-level neurological mechanisms. Furthermore, those who support strategies to improve individual autonomy may be concerned that policies relying on pharmaceutical interventions further reduce the autonomy of the individual. On the other hand, if the drug is indeed effective beyond the clinical trials it could be argued that it is possible for individuals to take such a product as an autonomous choice and also that it could help them in creating the conditions for future further autonomy through breaking the patterns of habit and addiction. It will be very interesting to track the debate on this policy throughout the next year.

**The NICE Guidance document with details of the proposal is available here 

Wellbeing in Britain and Ireland

After yesterday's post on life satisfaction in Europe, Liam noted to me that it was quite unusual to see Ireland ranking below Britain given how highly Ireland usually scores on wellbeing indexes. I went back to the European Social Survey to double-check the life satisfaction figures and I supplemented them with a measure of happiness. The same pattern is borne out in both measures - Ireland seems to have experienced a notable drop in wellbeing between 2008 and 2010, the worst years of the recession, and this drop persists up to 2012 at least.

Life satisfaction in 15 European countries

Fig 1. Countries used &
number of people.

One well-known finding in the wellbeing literature is that there is a U-shape over the lifecycle. In other words, young and old people report high levels of wellbeing but the middle-aged report the lowest wellbeing scores. I was thinking about this and wondered to what extent the U-shape varied by country, so I looked it up.

I used data from round 6 of the European Social Survey (2012), a randomized cross-sectional survey of people aged 15+ from many countries in Europe. The EES, which is free to access, has been conducted every 2 years since 2002. The 2012 edition contains data from 29 countries but I examined only 15 of these for my own arcane reasons (I couldn't fit them all in one graph). There are over 29,000 people in my sample and the frequency distribution by country is described in Figure 1.

The question I was interested in was "How satisfied are you with life as a whole?" ranked on a scale of 0 (extremely dissatisfied) to 10 (extremely satisfied). Among the 15 countries I examined, Denmark ranks first on this measure with an average score of 8.57 and four of the top five scoring countries are from Scandanavia, with Switzerland making up the other spot. The top five here are also the 5 highest-ranked European countries in the Legatum 2013 Prosperity Index, which measures prosperity via a mix of income and wellbeing measures.

The top five are followed by Netherlands, Germany, Britain and Poland who all report average scores over 7. Spain, Ireland, Italy and France are next with scores in the 6.4-6.8 range (I knew France had low wellbeing scores, which apparently motivated former President Sarkozy to set up the Stiglitz-Sen-Fitoussi Commission a few years ago, but I'm a little surprised at how low Ireland is. A major recession will do that I suppose). Portugal and Russia are the two most dissatisfied countries.

Next I examined wellbeing at each decade in life from age 20 to 80. The below figure replicates the famous U-shape of wellbeing by using predicted probabilities of life-satisfaction after controlling for age and age squared. The Stata code I used to produce it is below. The outcome variable "ls" is life-satisfaction. The double ## symbol is a shortcut in Stata which tells it to calculate both the independent effects and interaction effects of the two variables either side of the hashtags - in other words it's the same as including separate variables for age and age squared. The "c." before the "age" variable informs Stata that it is a continuous variable. Looking at the regression again I'm now thinking I should have clustered the regression by country but since this is just for fun I'll let it slide.

Stata code
reg ls c.age##c.age
margins, at(age=(20 30 40 50 60 70 80))
marginsplot

Lastly, I wanted to see whether the U-shape varied by country. I used a very nice command created by Ben Jann called coefplot rather than marginsplot because the former has some nicer graphing options. In order to get all the different estimates in one graph, I ran the regression country-by-country, stored the estimates, and then combined them using coefplot. In the "coefplot" line of code, the command "vertical" recasts the graph along the vertical axis and "nooffset" forces all the data to be plotted on the same plane. The "recast" and "symbol" commands just specify aesthetic changes and "noci" suppresses confidence intervals. Switzerland and Spain are omitted from the below regressions because I forgot to include them.

Stata code
reg ls c.age##c.age if country == "Britain"
margins, at(age=(20 30 40 50 60 70 80)) post
estimates store BritainWB

reg ls c.age##c.age if country == "Denmark"
margins, at(age=(20 30 40 50 60 70 80)) post
estimates store DenmarkWB

... (repeat the above for all countries)

coefplot BritainWB DenmarkWB Finland WB FranceWB GermanyWB IrelandWB ItalyWB NetherlandsWB NorwayWB PolandWB PortugalWB RussiaWB SwedenWB, vertical nooffset recast(connected) noci symbol(point)

The U-shape seems most symmetrical in Germany, Britain, Ireland, Poland and to a lesser extent in Norway, Netherlands and France. There's more of a steady increase in Sweden which is relatively flat from age 20-40 and then rises steadily for each subsequent decade. Old people in Denmark seem to be the most satisfied people in Europe, possibly the world. The way the curve bends for old Danes makes me think there's probably some 100 year old in Copenhagen who reports a score of 11. Italy, Portugal and Russia are exceptions to the U-trend due to low levels of life-satisfaction in the 60-80 age range.

Update 6.11.14
Here is the Stata code I used to produce the above analysis (now with Spain & Switzerland included):

use "C:\File Location\ESS6e02.dta", clear
keep  idno cntry stflife  agea
rename idno id
rename cntry c
rename stflife ls
rename age a
drop if a > 90 | ls > 10 
drop if c == "AL" | c == "BE" | c == "BG" | c == "HR" | c == "CY" | c == "CZ" | c == "EE" | c == "HU" | c == "IL" | c == "IS" | c == "LT" | c == "SI" | c == "SK" | c == "UA" | c == "XK"

reg ls c.a##c.a if c == "CH"
margins, at(a=(20 30 40 50 60 70 80)) vsquish post
estimates store Swiss

reg ls c.a##c.a if c == "DE"
margins, at(a=(20 30 40 50 60 70 80)) vsquish post
estimates store Denmark

reg ls c.a##c.a if c == "DK"
margins, at(a=(20 30 40 50 60 70 80)) vsquish post
estimates store Germany

reg ls c.a##c.a if c == "ES"
margins, at(a=(20 30 40 50 60 70 80)) vsquish post
estimates store Spain

reg ls c.a##c.a if c == "FI"
margins, at(a=(20 30 40 50 60 70 80)) vsquish post
estimates store Finland

reg ls c.a##c.a if c == "FR"
margins, at(a=(20 30 40 50 60 70 80)) vsquish post
estimates store France

reg ls c.a##c.a if c == "GB"
margins, at(a=(20 30 40 50 60 70 80)) vsquish post
estimates store GB

reg ls c.a##c.a if c == "IE"
margins, at(a=(20 30 40 50 60 70 80)) vsquish post
estimates store Ireland

reg ls c.a##c.a if c == "IT"
margins, at(a=(20 30 40 50 60 70 80)) vsquish post
estimates store Italy

reg ls c.a##c.a if c == "NL"
margins, at(a=(20 30 40 50 60 70 80)) vsquish post
estimates store Netherlands

reg ls c.a##c.a if c == "NO"
margins, at(a=(20 30 40 50 60 70 80)) vsquish post
estimates store Norway

reg ls c.a##c.a if c == "PL"
margins, at(a=(20 30 40 50 60 70 80)) vsquish post
estimates store Poland

reg ls c.a##c.a if c == "PT"
margins, at(a=(20 30 40 50 60 70 80)) vsquish post
estimates store Portugal

reg ls c.a##c.a if c == "RU"
margins, at(a=(20 30 40 50 60 70 80)) vsquish post
estimates store Russia

reg ls c.a##c.a if c == "SE"
margins, at(a=(20 30 40 50 60 70 80)) vsquish post
estimates store Sweden

coefplot Denmark Germany Finland France GB Ireland Italy Netherlands Norway Poland Portugal Russia Spain Sweden Swiss, nooff vertical recast(connected) noci symbol(point)

This is part of a series of posts designed to highlight the usefulness of the margins command & various graphing capabilities in Stata. It draws on the 3rd edition of "Regression Models for Categorical Dependent Variables using Stata" by Long & Freese as a primary reference.

Fully funded PhD researcher in Applied Behavioral Sciences (Paris, France)

Via Olivier Oullier

Fully funded PhD researcher in Applied Behavioral Sciences (Paris, France)
BVA Group Paris & Aix-Marseille University (AMU)

JOB DESCRIPTION
The PhD researcher will work with BVA’s Innovation Team, she/he will participate in designing and implementing new market research using cutting insights from behavioral economics/nudge, social affective neuroscience and psychology.

The research will first require an extensive literature review on how behaviorally and neuroscientifically evidence-informed laboratory and field research can improve strategies in both the public and the private sectors. Topics covered will range from finance to public health including food, voting behavior, education, law, sustainable consumption etc.

Then, the researcher will implement behavioral insights in ongoing market research in the private and the public sectors. BVA Group is currently leading the effort in implementing nudges in national policy making, the applied part of the PhD work will therefore constitute a significant part of the job.
The candidate will participate in designing lab and field studies (RCTs), controlling the way data is collected (qualitative and quantitative), analyzed (coding scheme and statistical plan) and presented (datavizualisation and report). In order to gain experience, she/he will work with BVA’s Business Units to take into account the reality of the market and production constraints. At the academic level, the work will be supervised and supported by the Behavior, Cognition and Brain Institute and the Cognitive Psychology Lab of Aix-Marseille University/CNRS, France’s leading institution in bridging theoretical and applied work in behavioral and brain sciences to real life issues.
In addition to the research work, the selected candidate is expected to participate in the training of market researchers on behavioral insights and help them with their work in this domain.

CANDIDATE PROFILE
The candidate must display a strong interest and knowledge in behavioral sciences applied to market research and policy-making. Prior experience in behavioral economics, nudging, social psychology, or social neuroscience/neuroeconomics will be prioritized. An academic and/or professional background in one of the following fields: cognitive, social or differential psychology, behavioral economics, neuroscience will be appreciated together with high-level skills in statistics and data visualization.
A Masters Degree is required to become a PhD candidate at Aix-Marseille University.
Fluent English is compulsory. French speaking will be appreciated but is not mandatory.

STATUS
The PhD candidate will preferably have a 3-year French private/public contract (called CIFRE in France) between BVA Group and Aix-Marseille University. Other contracts to be discussed, depending on the candidate’s current status. Salary will depend on experience.

SUPERVISION & LOCATION
The work at BVA will be supervised by Etienne Bressoud, Innovation and Marketing Sciences Manager together with the PhD supervisor, Olivier Oullier, Professor of Behavioral and Brain Sciences at Aix-Marseille University. The main location of the work will be Boulogne-Billancourt (near Paris, for the office work) where BVA labs are located. The PhD researcher will have to undergo mandatory graduate classes (approximately 2 weeks each year) in Marseille. The candidate should be ready to travel in France and abroad to conduct research an present her/his work.

RECRUITMENT & BEGINNING OF WORK
The recruitment is open as of today until the position is filled. Ideally the chosen candidate should not start later than the end of November, 2014 (deadline for PhD applications in France)

APPLICATION
The candidate is expected to send a motivation letter, detailed CV, and letters of recommendation.

CONTACT
Applications and further questions should be sent via email to both etienne.bressoud@bva.fr & olivier.oullier@univ-amu.fr