OECD Life Satisfaction Index - What makes people happy?

Recently, OECD published its life satisfaction index across its member countries. How's Life?: Measuring Well Being gives an overview of the OECD Better Life Index methodology, which is focused on households and individuals rather than aggregate economic conditions, and on well-being outcomes as opposed to well-being drivers. In particular, life satisfaction measures how people rate their general satisfaction with life on a scale from 0 to 10. The surveys show that Hungary, Portugal, Russia, Turkey and Greece have a relatively low level of overall life satisfaction while  Denmark, Norway, the Netherlands and Switzerland have a high level of overall life satisfaction. 201205242132.jpg

In addition to life satisfaction, OECD survey also captures various indicators under the topics of housing, income, jobs, community, education, environment, civic engagement, health, safety, and work-life balance. For instance, the housing topic includes the rooms per person (average number of rooms shared by person in a dwelling), dwellings with basic facilities (percentage of people with indoor flushing toilets), and housing expenditure (housing expenditure as a percentage of disposable household income) indicators. In contrast, the jobs topic includes the employment rate (percentage of people currently employed in a paid job), long term unemployment rate (percentage of unemployed people who have been actively looking for a job for over year), personal earnings (average annual earnings for a full-time employee), and job security (share of employment with a tenure less than 6 months) indicators. 201205242205.jpg The chart on the left shows the indicator values for Hungary. In general, Hungarians are less satisfied with their lives than the OECD average. 65% of Hungarians have more positive experiences (feelings of rest, pride in accomplishment, enjoyment, etc) than negative ones (pain, worry, sadness, boredom, etc) on a daily basis in contrast to the OECD average of 72%.

As the chart shows Hungarians feel safe, are happy with the water and air quality, find their work-life balance acceptable, have a strong sense of community, and are happy with the general quality of the education. For instance, 89% of Hungarians believe that they know someone they could rely on in time of need. Yet in life satisfaction, Hungary scores the lowest.

Referring back to the chart, the scores for housing, jobs, civic engagement, and health for Hungary are lower than the OECD average while income is considerably lower than the OECD average. In Hungary, the average person earns about $13K a year, less than the OECD average of $22K a year. It seems like the low life satisfaction score for Hungary is connected to low living standards stemming from sub-par income levels coupled with a lack of jobs. For instance,  around 55% of Hungarians aged 15 to 64 have a paid job, well below the OECD employment average of 66%.

In contrast, sense of community is the lowest score for Turkey. For instance, 69% of Turks believe that they know someone they could rely on in time of need, lower than the OECD average of 91%. Is there a correlation between life satisfaction and indicators for living conditions and quality of life? If yes, does the correlation hold across the OECD countries?

201205242219.jpgThe OECD Web site has a mixer tool that lets a user to select the relative rankings of the indicators and analyze the ranked list of countries based on these preferences. The customized index enables the comparison of well-being across countries based on personal preference of the importance of 11 topics the OECD has identified as essential, in the areas of material living conditions and quality of life.

While the OECD mixer is a nice tool for engaging readers, as a modeler, we see the life satisfaction sentiment indicator as an output while the rest of the indicators (housing, income, jobs, etc.) as inputs. In other words, we believe that the input indicators drive people how people feel about their life experiences. To test this hypothesis, we performed a correlation analysis between the life satisfaction index and the rest of the indicators in order to understand which factors contribute the most or the least to the life satisfaction sentiment. The correlation analysis is shown on the right.

In terms of topics, life satisfaction has high correlation with income, jobs, housing, health, low correlation with education and no correlation with safety. In terms of individual indicators, room per person has the highest correlation with life satisfaction while job security, housing expenditure, employees working long hours, educational attainment, years in education, student skills, consultation on rule making, air pollution, homicide and assault rate indicators have very low correlation with life satisfaction.

The indicators under each topic show some interesting results. For the jobs topic, while employment rate, personal earnings, long term unemployment rate indicators are correlated with life satisfaction whereas job security is not. Similarly, for the environment topic, while water quality has a high correlation with life satisfaction, air pollution does not.

It would be interesting of comparison if there was a similar survey for non-OECD countries. Perhaps the OECD country values are dominated by the population's desire for the ability to collect as many material possessions as possible. Relatively poorer country values may not follow this correlation.

Wiki Surveys for Social Science Research

Surveys and interviews form the central methodology for analyzing and discovering attitudes and opinions in social science research. With the advent of Web, online surveys have become an efficient way for researchers to collect and analyze large amounts of data. The popularity of the online survey tools like SurveyMonkey , Zoomerang, SurveyGizmo , etc. are testament to the productivity enabled by surveys. However, surveys represent a top-down rigid methodology forcing the survey designer to account for all possible answers up front, which is an impossible feat. In contrast, interviews allow the unanticipated information to bubble up bottoms up from the respondents. For instance, Integrity Watch Afghanistan (IWA), Afghan Perceptions and Experiences with Corruption: A National Survey 2010 primary data, involves interviewing randomly selected 6,500 respondents in 32 provinces on over 100 questions that deal with sectors where people experienced corruption; levels of bribes people paid to obtain services; what type of access people had to essential services; who people trusted to combat corruption; and experiences with corruption in the judiciary, police, and land management. However, the interview methodology is expensive and time-consuming as it requires implementation by research companies with expertise in effective research design, and precise management of data collection over several months.

Is there an alternative to surveys and interviews in social science research? Prof. Salganik's team at Princeton came up with a hybrid approach, "wiki surveys", that combines the structure of a survey with the open-endedness of an interview. To date, various organizations have created more than 1000 wiki surveys on the project Web site - All Our Ideas, generating in 45,000 ideas with 2 million votes. Wiki surveys range from the New York City Mayor's Office's engagement with citizens in shaping the city’s long term sustainability plan to the Catholic Relief Services surveying their 4000 employees to find out what makes an ideal relief worker. The figure below shows how the third question in Tactical Conflict Assessment Planning Framework (TCAPF) would be be implemented as a wiki survey:

tcapf wiki survey.jpg

Inspired by extending the kittenwar concept to ideas, the user interface guides the respondent to choose between two random alternatives, while encouraging the respondents to add their ideas into the mix of alternative responses. The additional ideas are added into the survey’s marketplace and voted up or down by the other survey-takers. Prof. Salganik says that “One of the patterns we see consistently is that ideas that are uploaded by users sometimes score better than the best ideas that started it off. Because no matter how hard you try, there are just ideas out there that you don’t know.”

All Our ideas have some basic visualization features to make sense of the wiki survey responses. Here is the visualization for the responses - "What do you think the Digital Public Library of America (DPLA) should be like?":

DPLA Survey Reponse.jpg

It is worth noting that the top scoring 15 ideas starting with DPLA interoperability with Government Printing Office (GPO), Defense Technical Information Center (DTIC), an National Records Archive Administration (NARA) are all uploaded ideas not in the original set of alternatives. A powerful argument for crowd sourcing!

Admittedly, we still need boots on the ground to collect TCAPF data in Afghanistan given the demographics of the people we want to reach. On the other hand, wiki surveys hold great potential in reaching the younger generation fueling the Arab spring and the like.

Tribal Human Terrain of Afghanistan

Under the sponsorship of the OSD Human Social Culture Behavior (HSCB) program, we are developing a semantic wiki for Complex Operations. The envisioned operational impact of our effort is to foster collaboration and sharing of knowledge for whole-of-government approach, and to improve COIN/SSTR operations analysis and execution by focusing on population as center of gravity. The development of such a wiki presents several challenges that include the broad domain area of knowledge complex operations require, a large number of doctrine publications to wikify and semantify, several out of print key references, etc. With these challenges, we saw an opportunity to develop an open source culturepedia for Afghan and Pakistan human terrain as such knowledge is not aggregated and not readily available.

The Complex Operations wiki currently contains more than 1,000 articles on the various tribal dynamics and locational knowledge for the Afghanistan and Pakistan region, outlining tribal meta-knowledge such as the sub-groups, primary locations, traditional alliances, and traditional disputes of various groups to support situational awareness about the human terrain. Here is the wiki page for the covered Afghanistan Organizational Groups. We have created over 150 concept maps (an example shown below) to capture the knowledge about 1,000 ethnic groups, tribes, sub-tribes, clans within Afghanistan and Pakistan region to make this human terrain knowledge readily accessible to the complex operations practitioner.

tribal concept map.png

Our use of a semantic wiki platform enables the representation of the human terrain knowledge as facts and relationships. For instance, the wiki page for the Achakzai tribal group lists the the known facts and relationships about this ethnic group both a human consumable form using semantic forms:

Achakzai Semantic Form.tiff

, and a machine consumable form as semantic RDF relationships:

Achakzai RDF.tiff

By inspecting the semantic form, the reader can deduce that Achakzai is a sub-tribe of Zirak, which is a sub-tribe of the Durrani super-tribe, primarily located in the Chora and Khas Uruzgan districts, and traditionally have disputes with the Nurzai, Panjpai and Kakar tribes. The representation of this knowledge in a semantic wiki has the additional advantage for faceted browsing and answers engine queries. For instance, the semantic wiki can answer questions like "What are the tribes in Kandahar Province and their traditional disputes?" as a table which gets automatically updated every time a new tribe in this province is added to the wiki: Tribes in Kandahar.tiff There are also several groups in Afghanistan that do not organize around tribal kinship ties, including Uzbeks, Tajiks, and Hazaras. In addition to tribal affiliation, social organizations such as solidarity groups - a group of people that acts as a single unit and organizes on the basis of some shared identity, and patronage networks - led by local warlord or khan - play an important role in understanding of the human terrain. Afghan and Pakistan human terrain and situational awareness knowledge base can be extended to include other populations of interest to the community, such as Yemen or Somalia.