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Objective and Subjective Measurements for Development andWell-being: Some Perspectives from a Bottom-up Study inIndonesia
Andante Hadi PANDYASWARGO1*, Naoya ABE1 and Yunus FRANSISCUS2* 1Graduate School of Science and Engineering,
Department of International Development Engineering (IDE), Tokyo Institute of Technology
2-12-1, O-okayama, Meguro-ku, Tokyo 152-8550, Japan
2
Center for Environmental Studies, University of Surabaya,
Jalan Raya Kalirungkut, Tenggilis, Surabaya 60293, Indonesia*e-mail: andante.hadi@ide.titech.ac.jp

Abstract
The concept of development or, ultimately, well-being or happiness is now under extensive discussion
by many scholars and international organizations. After all, what are we trying to measure and understand,and why? Another important question is whether or not we have a sufficient framework, tools, data andinformation to measure the state of people’s well-being and how it changes. The aim of this article is toconduct extensive reviews on the existing well-being concepts. The study discusses Indonesia’s well-being
measurement framework as a case study. Through the discussion, the gaps between the ideal and the reality
are identified. Based on these findings, directions are proposed to stakeholders on how they can implement
the desirable improvements identified. Indonesia has collected national statistical data to facilitate analysis of
its population’s well-being. This study provides suggestions for improving this collection system byproposing inclusive and participatory subjective measurement as an important supplemental approach toprovide missing pieces of the puzzle in measuring changes in people’s well-being. Civil society often finds
subjective measurements easier to understand and relate to. They are, in fact, the biggest stakeholder indevelopment. If an inclusive framework for subjective measurement can be established, many potential orappropriate development practices may be realized. Important possibilities include international
benchmarking and acceleration of development resonance driven by common people.
Key words: development monitoring, happiness measurement, participatory, quality of life,
subjective well-being

1. Introduction
It is recognized that the well-being of national society
is valuable capital for development. Governments andkey policy makers have tremendous opportunities tocreate environments in which well-being flourishes(Beddington et al., 2008). In order to understand andcapitalize on well-being and help it flourish, one mustmeasure and monitor it so that diagnoses can be madeand the processes of designing and redesigning robust
policies and actions can be undertaken efficiently andeffectively. In the recently published list of indicators
reviewed at the second IAEG-SDG (Inter-Agency andExpert Group on Sustainable Development Goal
Indicators) meeting, the topic of well-being wasaddressed in several goals’ targets. For example, in Goal
3, Target 3.4.1, the promotion of mental health and wellGlobal Environmental Research
19/2015: 207 – 216
printed in Japan

being was emphasized as one of the keys to preventing
premature mortality from non-communicable disease. In
Goal 9, Target 9.1.1, it is mentioned that human wellbeing can be supported by the development of quality,
reliable, sustainable and resilient infrastructure(UNSTATS, 2015). The list of targets published by thesecond IAEG-SDG meeting also addresses critical
criteria or perspectives for policy design and actions
such as equity, equality and/ or justice. This article
focuses only on two aspects of well-being indicators,
objectivity and subjectivity, and does not cover othercritical aspects. Objective and subjective measurementsin the field of monitoring development have their own
advantages and disadvantages. The two approaches,when paired appropriately, could compensate for one
another’s weaknesses and provide a more holistic
understanding of the state of development in a community©2015 AIRIES208

A. H. PANDYASWARGO et al.

(Diener & Suh, 1997). Moreover, appropriate and consistent
data collection would enable national, regional andglobal comparisons (Smith & Exton, 2013). The term
‘development’ in this study refers to the development ofgreater quality of human life. The term ‘well-being’ here
refers to the condition of an individual or group ofpeople in their social, economic, psychological, spiritualand medical state. It is argued that the ultimate goal ofdevelopment is enhanced well-being, where the individual
or group of people is in its best state. The state ofdevelopment and well-being, for example in a community,
can be explained objectively, such as by reporting thenumber of crimes that occur, the number of infant deaths
and other readily quantifiable states. On the other hand, thestate of development can also be measured subjectively,
for example, by asking people how they feel about theirstate of well-being. There are two popular types of wellbeing, hedonic well-being and eudaimonic well-being.
Hedonic well-being is the perspective which defines
well-being in terms of attaining pleasure and avoiding
pain (Ryan & Deci, 2001). The other type, eudaimonic
well-being, is the concept that well-being actually consistsof more than just happiness and that those people whoreport happiness are not necessarily psychologicallywell. Eudaimonia is more concerned with living well or
actualizing human potentials (Deci & Ryan, 2006).
Between these two types of well-being, subjective wellbeing (SWB), commonly used in development studies,
has been associated with the former type, hedonic wellbeing (Kahneman et al., 1999). Measuring well-being interms of life satisfaction, can be used as a proxy for
welfare. Cognitive well-being is usually interpreted bypsychologists and sociologists cardinally. In other words,
it is assumed to be comparable across respondents (forexample, the difference in happiness between a 4 and a
5 for any individual is the same as between an 8 and a 9
for any other individual). On the other hand, economists
usually assume only the ordinality of satisfaction wellbeing (individuals sharing a common opinion of what
happiness is) (Ferrer-i-Carbonell & Frijters, 2004).
Despite these two different assumptions in measuringsatisfaction, Ferreri-i-Carbonell & Frijters (2004) foundthat the two assumptions (cardinal or ordinal) make little
difference. What would make a substantial difference isa measurement that takes personality traits into accountas a fixed effect.
Based on some constructed assumptions, Ferreri-iCarbonell & Frijters (2004) illustrated three models.
The first is the case where general satisfaction (GS)is assumed to be interpersonally cardinally comparable
in an ordinary least square (OLS) model:
GSit = x it β + εit(1)

In the second case, GS is assumed to beinterpersonally ordinally comparable in an ordered
probit or ordered logit model:*

GSit = x it β + εit ,*GSit = k⇔λ k ≤ GSit < λ k+1(2)

They then proposed a third case, an improved model
where fixed effects (personality traits) are incorporated
in an ordered logit model:*

GSit = x it β + fi + εit  ,*i
GSit = k⇔λ ki ≤ GSit < λ k+1(3)

where GS*it is the latent variable; GSit is observed
general satisfaction; X is observed characteristics (e.g.,age, income, living in a partnership, children and health);
β is the estimated parameter or slope; ε is unobserved
characteristics or an error term; f is fixed individual
effects; λ ki is individual specific thresholds; the suffix ‘it’refers to individual i at time t; the suffix ‘t’ = 1,…, T ; thesuffix ‘k’ = the alternatives sets of marginal effects
0,…, K ; and the suffix ‘k + 1’ indicates an assumption thatthe individual specific effect’s intercepts are increasing.
An example of the first model where cardinality is
assumed would be a comparison of aggregate satisfaction
across countries, such as a national aggregate satisfactionof Indonesia compared with that of Japan or thePhilippines. The second model does not lend itself thateasily to individual heterogeneity. There may be proxies
for unobservable conditions. Examples of these proxies
could be age, marital status, work-related information or
number of children. Comparisons must therefore be madewith consideration of these proxies. In the third model,
consideration is given to deeper aspects of individuals
because personality traits are considered a fixed effect.
Consideration of fixed effects like this is gaining
popularity due to its robustness. Ideally, designing thismeasurement approach in satisfaction studies would
require the cooperation of psychologists, sociologists andeconomists. Although due to their simplicity the firstand second models are widely practiced, the third model
could improve precision and accuracy. Longitudinalstudies have been widely performed to determine these
fixed effects (Watabe & Kouno, 2014; Richard, 2007;
Joachim, 1993). When fixed effects are incorporated, theaggregated data also present a truer value. This study
proposes equation (4) as the ideal representation of theaggregated general satisfaction in time t for n number ofindividuals using the third model before any cardinal or
ordinal comparison is performed. When this is put into
practice, it will lead to more valid discussions on gaps inaggregated well-being, minimums, maximums, averages,
and other values of interest if equation (3) is applied
appropriately to gain data on individuals.
nGSt = Σ GSit ,**iGSit = X it β + fi + εit ,
i

*
it

(4)
i

GSit = k⇔λ k ≤ GS < λ k+1

Inclusive of hedonic well-being (as cited in Diener &Suh, 1997), three major philosophical approaches todetermining the quality of life are highlighted. These areObjective and Subjective Measurements for Development and Well-being: Some Perspectives

1) a good life is dictated by normative ideals based onreligious, philosophical or other systems, 2) a good life
is based on satisfaction of preferences, and 3) a good life
is based on individual experiences. An example of thefirst approach is an act of giving, helping others or
generosity that is dictated by religious systems as
something good. An example of the second approach
would be whether or not one has been able to obtainthings he desires. An example of the third approach would
involve the feelings of joy, pleasure and contentment
based on experiences. The conventional SWB criterion
is closely related to the third philosophical approach.
Development organizations, academic research andgovernment institutions use one or several of theseapproaches in combination as a means of measurement
supplemental to objective measurement. There are many
challenges in SWB data collection. A few examples are1) determining what, when, where and whom to ask,
selecting the appropriate words and frequency,
2) deciding how to minimize biases, and finally3) considering how to pair it with objective measurement
data.
Although the importance of SWB is well acknowledged,
having been proven by many studies to provide
meaningful and reliable data (Diener & Suh, 1997;
Clark & Watson, 1988; The WHOQOL Group, 1998;
Smith & Exton, 2013), it is still quite rare to see practicaluse of SWB at the national and regional scales or use ofa ‘pairing’ approach with objective measurements for
guidance. This study aims to describe the current
practice of development and well-being measurement inIndonesia, propose some improvement strategies for the
future development of Indonesian methods of well-being
measurement, and summarize the advantages anddisadvantages of the subjective and objective approaches
based on literature. Indonesia released its first well-being
report in September 2014 based on survey data collected
in 2013 from 9,720 households randomly selected fromall of its provinces. The present study discusses thesurvey methodology used for that particular report andthen proposes improvement strategies based on findings
from a bottom-up participatory workshop conducted in2013 and 2014 in a middle-low income community in
Surabaya, Indonesia. (Pandyaswargo et al., 2013, 2014).
The proposed improvement strategies cover bothtechnical aspects such as appropriate wording anddesign, and basic principles such as policy integration
and added value for the community involved.

2. Indonesia’s First Subjective Well-Being Report:
What was Missing?
Efforts to link subjective and objective measurements
often reach an advanced stage of realization only after
the investigator analyses the results from a subjective
measuring activity intended to supplement objective
measurements. Some developed countries have realized
the importance of measuring well-being subjectively.
EU countries have focused on the collection of209

subjective measurement data, while the UK, Japan (TheCommission on Measuring Well-being, Japan, 2011),
Bhutan and the OECD have started development ofsubjective well-being indicators (SWI). Bhutan’s previous
King Jigme Singye Wangchuk coined the term ‘Gross
National Happiness’ (GNH) in 1972. GNH claims to be
multidimensional because it focuses not only on the
SWB of the individual but internalizes other people andconsiders nine domains: 1) psychological well-being,2) health, 3) time use, 4) education, 5) cultural diversity
and resilience, 6) good governance, 7) community vitality,8) ecological diversity and resilience and 9) living
standards. Indonesia, which is categorized as a lower
middle income country (World Bank, 2015), publishedits first national well-being report in 2014 based on 2013
data. Along with China, India and South Africa, Indonesia
was mentioned as an OECD key partner country whenapplication of the OECD’s Better Life Index was
expanded (OECD, 2014b). The content of the Indonesianwell-being report, however, only presents domain
satisfaction and provides no happiness and life satisfaction
indicators.
Badan Pusat Statistik (BPS) and the Central Statistics
Bureau prepared and published the first Indonesian“National Well-being Report.” BPS is a non-departmental
government agency directly reponsible to the President.
Its main function is to provide data to the government andthe public. It is also mandated to establish cooperation
with international institutions and other countries for the
benefit of Indonesia’s statistical development (BPS, 2012).
The published report states that Indonesia scored 65.11
on a scale of 0 to 100 in national well-being. This result
was based on the satisfaction level of 10 essential life
domains: 1) employment, 2) household income, 3) housing
and assets, 4) education, 5) health, 6) domestic relationships,7) social relationships, 8) availability of leisure time,9) environmental conditions and 10) safety. The sampling
size was 9,720 against a population of nearly 250
million (BPS, 2014). Sampling was done by theprobability sampling method and the references toformulating the survey included the guidelines from the
New Economics Foundation (NEF, 2011; OECD’s Better
Life Index OECD, 2014a), and Eurostat’s Feasibility
Study for Well-Being Indicators (Eurostat, 2008; National
Statistics Bureau, 2015a, b). The members of households
to be interviewed were selected based on a Kish
selection table prepared in advance by Indonesia’snational statistics office (BAPPENAS, 2014). The survey
consisted of direct interviews of selected respondents ina semi-private location with a sufficient amount of time
available to create a conducive environment for honest
answers and avoidance of rushed answers (BPS, 2014).
The publication of this report became a topic ofdiscussion among Indonesian scholars and washighlighted in the media (Beritasatu, 2014) (Metro TV,2014) (National Geographic Indonesia, 2014). The results
and coverage of the index attracted criticism, especiallyfrom university professors and scholars in developmentrelated studies. Some recorded critiques and suggestions

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A. H. PANDYASWARGO et al.

from national experts included:
1. The final published results did not provide enoughdetails. For example, urban communities werementioned as happier than rural communities, but it
is unclear whether the scores on income, domestic
relationships, and environmental conditions cancelledeach other out or not.
2. The sampling size and diversity of respondents
need improvement (BAPPENAS, 2014).
3. The coverage should be expanded, i.e., not justmeasuring cognitive or satisfaction aspects, butalso the spiritual/emotional or affective aspects ofwell-being (CPPS, 2014).
The first argument identifies a problem common to
many statistical analyses where averages are measured.
Detailed information is lost, resulting in the eliminationof meaningful information in the final index score. The
second argument is of dubious concern because thereport stated that random sampling had been practiced
and the statistics office is known for the credibility of its
random sampling (CPPS, 2014). The third criticism
relates to the problem of only collecting materialistic
information and is actually in the same tone as anargument in the Well-being Commission report, namely“there is a weak connection between resources andhuman well-being: it says something about the directionof change but it does not inform about its magnitude or
about the level of well-being of individuals with different
preferences” (Stiglitz et al., 2009). How significant thisargument is may vary regionally. To take an example, inthe time-use diary collected at the Surabaya workshop, it
was revealed that participants allocated a good fifteen
minutes several times a day for their spiritual needs bypraying. When asked about which activities among the
day they would like to reduce, none of the participants
had any problem with the time spent praying each day
because those are the times they enjoy taking a breakfrom hectic daily activities and they feel it helps
rejuvenate their contentment. One may argue that theirpreferences and emotional/spritual well-being may giveinsight into the reported high degree of well-being
despite the objective data of scarce resources. This,
however, is just one result among other possible
products of involuntary interaction among people. The
people one interacts with may affect his or her norms,
aspirations and judgment of what is important, friendly
or threatening (Layard, 2006) and this could varyconsiderably across cultures and regions.
To add to the list of improvement opportunities
addressed by the Indonesian experts through formal
institional meetings and discussions, this study offers
insights from bottom-up practices of development
studies. There were two workshop sessions held in arusunawa, or government-funded affordable housing
complex for people relocated from riverbanks and city
centers, in Surabaya, Indonesia (Pandyaswargo et al.,2013, 2014). The first one, in 2013, was aimed at
capturing the aspirations and challenges of thecommunity. The second one, in 2014, was aimed atdeveloping an indicator of sustainable development. In
the process, certain things became clear that could be
relevant to any sustainability monitoring practice:
1. A participatory workshop style encourages a senseof belonging in a community; leading to a potential
increase in level of well-being.
2. A participatory survey helps engage a community
in reflecting on their lifestyle and behavior, leading
to capacity building and empowerment.
3. A detailed time-use study combined with asubjective analysis of each activity has thepotential to bridge the missing link between
objective and subjective measurement of wellbeing.

2.1 Participatory Workshops as a Promising
Value-adding Platform that Encourages a Sense
of Belonging in a Community
Our first proposal based on the Surabaya workshop
experience is in the same tone as (Helliwell, 2011), whoargued that there should be new models for local
governments where face-to-face interaction and othertrust-building contacts can be made. Furthermore, heargued that reformation of conventional public service
design and delivery was required. When the monitoringprocess can be conducted in a setting where social
cohesiveness is exploited and strengthened, the activityof gathering data itself can be a fertile ground for thedevelopment and application of policies aimed at
improving subjective well-being. A participatory workshop
is one example of a bottom-up platform where such aims
could be achieved.
At the Surabaya workshop, people were asked to rate
their priority challenges in terms of basic needs. The
researchers who conducted the workshop provided
several options such as water, food, energy, jobs andwaste management to provide a starting point for the
discussions, but also explicitly indicated that theparticipants could add further topics of concern. A groupof male participants added “harmony in the community”
as their priority challenge. This triggered an interesting
discussion especially about how other challenges, forexample, in waste management, were the result of lackof coordination, harmony and chances to gather together
to discuss activities for the betterment of their community.
After several participatory workshop sessions in thiscommunity (in 2013, 2014 and 2015) physical voluntary
improvements were made to the community hall where
the workshops and other meetings were taking place andbetter relationships between the residents of thecommunity were established.
2.2 Participatory Surveys Help Engage Communities
to Reflect on their Lifestyle and Behavior
Our second proposal, is to let people have physicalaccess to the materials of analysis. There are many
benefits to this strategy, including self realisation of how
and where their life might be lacking. When performedin groups, it could also promote the benefits mentioned

Objective and Subjective Measurements for Development and Well-being: Some Perspectives

211

in the above proposal. The challenge to this approach is
uniformity of competencies among the respondents, forexample, in filling out questionnaires and surveys on
their own. This is where the role of officials or experts
as facilitators comes into play for quality control andalso for face-to-face interaction.
At the Surabaya workshop, the participants were able
to see the voting results and hear the discussion outputs
instantly, in their own style and language. This advantageof participatory surveys lets individuals at the workshop
immediately compare their answers to those of otherpeople in the community, including what the majority
responses were, whether others shared the same concernsand desires, and whether common challenges could beworked on together. There was one case where a groupof participants who lived in one building felt their tap
water was dirty and smelly while another group living in
the next building felt there was nothing wrong with thequality of their water supply. It was found that thesecond building’s inhabitants had agreed to take turns
cleaning the water filter on the rooftop every month.
Transfer of this knowledge during the workshop has
helped the first building’s residents to identify the sourceof their water supply problem.

each basic need in terms of cleanliness, availability,
affordability, reliability, safety and convenience. An
analysis that combines the output of these two data sets
may help policy makers determine which basic needs inthe particular community have to be prioritized for an
improvement that would efficiently affect their wellbeing, considering both the objective intensiveness oftime and subjective satisfaction of that particular sector
in their daily life. The objective information on timespent on each activity involving each basic need dimension
may explain the intensity of subjective responses
regarding their satisfaction. On the other hand, subjective
satisfaction with regard to the qualities of a particular
basic needs dimension may explain how bad or satisfactory
the living condition is depending on the duration forwhich each dimension is used.
The questions asked regarding subjective satisfactionthat are paired with the time use survey can varydepending on the purpose of the survey. For example, inthis Indonesian case, the interests were in the basic needs
dimensions. In the French time use survey, on the other
hand, questions on satisfaction were asked about the
respondents’ residence, job, leisure and relationships
with their family (INSEE, 2010).

2.3 A Detailed Time-use Study Combined with Subjective
Analysis of Each Activity Has the Potential to
Bridge the Missing Link between Objective andSubjective Measurement of Well-being
Our third proposal is to recommend using combined
objective and subjective measurements with rich detailed
information on how people use their time and to selectmajor things to involve, such as other persons present,means of transportation, for whom the activities are
done, emotional states, utilities involved, etc. Some ofthe established methods include the Day Reconstruction
Method (DRM) (Kahneman et al., 2004), and time-use
studies, also known as time- budget studies or allocationof time (United Nations, 2014). By extending themeasurements into the detailed activities of individuals,
one may see potential biases, hidden values and theexistence or absence of similarities in patterns, occurrencesof events, and lifestyles among the communities. This
benefit could also help investigators identify potential
resources. Since there are international guidelines
provided by the United Nations, comparability andbenchmarking would be possible. On the other hand, theflexibility of combining this approach with othermethods may also help local governments address
specific questions of their communities.
A time-use study with satisfaction questionnaires was
conducted at the second Surabaya workshop. This
time-use diary has revealed how much time in a dayeach person was using for particular activities, howoften the activities were performed during weekdays andon weekends, and which kinds of basic needs (water, food,energy, jobs, community environment) were involved ineach activity. The satisfaction questionnaire, on the other
hand, revealed how satisfied the individuals were regarding

2.4 Recommendations for the Indonesian National
SWB Questionnaire
In addition to the four critiques made by theIndonesian scholars reported in the media and at
meetings and the proposals made based on the Surabaya
bottom-up practices mentioned above, direct observationof the questionnaire used for collecting data for Indonesia’s
first national SWB report (National Statistics Bureau,2013) and available metadata on the survey (National
Statistic Bureau, 2015a, b) generated the following points
of discussion:
1. The final question on emotional well-being (“Howhappy do you feel?”) is asked after inquiring aboutsatisfaction with material aspects. The order ofasking this question should be reconsidered,otherwise it is difficult to distinguish how much ofthat happiness is coming from material satisfactionthat has been reviewed in the interview, and how
much of it is actually the general feeling of theperson.
2. T here was no time-frame or factors to be consideredwhen the respondents were asked to rate their stateof happiness in the final question. This could leadto highly divergent perceptions of the question by
respondents, and perhaps different intrepretations
by the interviewers when they are asked by the
respondents.
3. Using a bipolar question on happiness rather thanunipolar to solve bias due to genetic personality
should be considered.
4. T echnology should be used to improve interpretability.
The first point of discussion is a problem that is also
acknowledged by Kahneman & Krueger (2006). They
found that reported satisfaction or happiness was often

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A. H. PANDYASWARGO et al.

strongly affected by earlier questions in a survey.
Therefore it is important to ask non-leading questions,or to arrange the order in a way that questions that areprone to bias come earlier in the questionnaire. The
second point is self explanatory. Regarding the third
point, for psychologically focused well-being studies it
is recommended that when the investigator would like toreveal an accurate emotional evaluation, both positive
feelings (e.g., energized, happy, competent, enjoying)and negative feelings (e.g., frustrated, hassled, angry,
criticized, tired) must be measured on scales to provide
a cancelling effect when someone tends to respond inmoderation or in extremes as an effect of theirpersonality, some of which is embedded in their genetics(Tellegen et al., 1988; Diener, 2000). This approach iscalled the U-index, coined by Kahneman & Krueger(2006). The last point refers to the use of visual aids
such as touch-screen panels and instant visualizationright after answering the questionnaire to engage therespondent more in the process. It might require a large
financial investment though, so despite its various
benefits, it is perhaps something that nations with more
funding would be able to adopt at the present.

3. International Framework and Challenges
in Objective and Subjective Measurements
Measuring well-being objectively implies that the data
to be measured are scientifically reproducible, quantitative
statistics rather than individual subjective perceptions.
Because well-established measuring procedures exist,
enabling straightforward international comparisons, thelist of indicators reviewed at the second IAEG-SDG
meeting (UNSTATS, 2015) mainly falls into this category.
The benefit of objective measurement is that it can
provide a solid foundation for many stakeholders toform a consensus. The downside of this approach is thatany single data result might not necessarily represent thewell-being status of an individual or a community among
many other individuals or communities, as there isalways considerable variation among scientific statistics
in any objective well-being measurement. One may try
to obtain a collection of these data as an index and claimthat it should represent ‘well-being,’ but it would lead toarguments and controversies such as “why not use a
different set or combination of data?”
Measuring well-being subjectively means that theanalyzed data are based on individual cognitive or
emotional evaluation. The cognitive component of wellbeing measurement refers to a global evaluation of one’s
life, often assessed as life satisfaction. The emotional
component of well-being is reflected in experiences ofpleasant and unpleasant emotions (Diener, 2009). These
two are correlational, though, because often people withhigh life satisfaction tend to report more frequentpleasant emotions (Diener & Fujita, 1995).
The global perspective and acceptance of objective
measurements in development have a longer history
compared to subjective measurements, which wererecognized only recently. Large-scale surveys of happinessonly started in the 1960s (Diener, 2009), but the speed
took off exponentially through the 1980s and 90s. In 2008,
at the urging of President Nicholas Sarkozy of the French
Republic, official demand arose for an internationalscale, better social progress indicator. Sarkozy asked
three prominent economists, Joseph Stiglitz, Amartya
Sen and Jean Paul Fittoussi, among whom two wereNobel Prize winners, to create a commission to address
the limits of GDP and provide suggestions for more
relevant social progress indicators (Stiglitz, et al., 2009).
One of the outcome reports prepared by this commission
suggested that there should be an internationallystandardized
well-being
measurement
method.
Answering this call, the Organization for Economic
Development and Cooperation (OECD) developed toolsthat allow worldwide Internet users to build their own
measure of average well-being, called “Your Better Life
Index.” Incorporating the results from user participationin applying this tool, the OECD also published aguideline on measuring subjective well-being in 2013
(Smith & Exton, 2013). The guideline is thorough,although it left out one of the most important types ofwell-being, eudaimonia (a perspective in well-being
which focuses on meaning and self-realization). Alongwith the well-being measurement, this guideline
suggests collecting objective information such as
demographics, material conditions, employment status
and psychological measurements for a co-variation
analysis. In the past, there have been more straightforward
methods of measuring subjective well-being, taking into
account only the subjective side of the measurement. In theearly development of subjective well-being measurements
between the 1960s and 1980s, there were ‘The D-T
Scale’ (D for ‘delighted,’ and T for ‘terrible’); the ‘selfanchoring ladder,’ asking, “In general how happy or
unhappy do you usually feel?” and inquiring about the
proportions of feeling happy, unhappy or neutral;‘PANAS’ (positive and negative affect); and ‘SWLS’(Satisfaction With Life Scale) (Larsen et al., 1985). The
presently available guidelines tend to attach, combine or
supplement subjective well-being with something
objectively measured.
Providing a framework for the relationship between
objective and subjective measurements could be the firststep toward understanding where subjective measurements
fit in and what kind of role both approaches should playin helping investigators understand society. Figure 1
elaborates the relationships between subjective andobjective measurements of well-being and how thedisadvantages of each approach could actually becompensated for by the advantages of the other approach.
For example, objective measurements could capture
information in standardized units, such as age expectancies
in years, air pollution in parts per million, level offlooding in meters or cubic meters, etc. On the other
hand, units to express well-being have yet to be
standardized. In the subjective approach, the investigatorcan ask, for example, “Taking all things into account,Objective and Subjective Measurements for Development and Well-being: Some Perspectives

how do you rate your happiness from 1 to 10?” and theresult will be a single, holistic, easy-to-understandcomparable unit. Although according to cognitive
response theory of subjective well-being, the individual isin the best position to evaluate his or her life (Schimmack,
et al., 2008), subjective measurement may be prone tobias. Objective measurements could help provide

documentation and tracking of these possible biases. For
example, social status, lifestyle or time spent with family
could give direction in explaining why someone mightfeel constrained or, on the other hand, contented despite
an unstable low income. At the same time, objective
measurements cannot explain the whole story of social
progress. For instance, information solely on income is

Well-being
Other commonly used terms* Contentment

Quality of life HappinessLife satisfaction

Current measurement approaches
Objectively

Subjectively

Definition: based on objective, quantitative statistics
rather than individual subjective perceptions

Other commonly used term

Advantages:
1. Easy comparison(in standardized
multiple units)
2. Often reflect thenormative ideals ofa societySocial Indicator

Disadvantages:
1. Based on common
assumptions
2. May not reflect well-being
based on actual experiences
3. May contain measurement
errors (for example
underreporting due to local
norms)
4. Controversies over variables**Definition: based on an individual’s cognitive andaffective/hedonic reactions to her or his whole life, as
well as to specific domains of life

Advantages:
1. Capture experiencesthat are important to
the individual

Disadvantages
Possible bias due to:
1. Recent event(s)2. Previous questions
asked
3. DNA
4. Unawareness

Optimized measurement

Value adding
platform

Objective

213

DRM
+
TUS***

Subjective

New characteristics:
1. Comparable in both standardized multiple units and as a single unit index
2. Reflects normative ideals of a society but also captures informal practices and culturally sensitive information
3. Can capture both detailed and general experiences important to individuals or society
4. Minimizes errors due to missing variables
5. Causes of bias (if any) could be tracked and properly recorded
6. Contributes to the improvement of well-being directly or indirectly

Fig. 1 Measuring well-being: current and proposed approaches.
* Often commonly used although they may mean different things, causing comparability problems* OftenWell-being:commonly usedtheymean different
things, causing
comparability
problems**Affective
thealthoughbalanceof maypleasureand displeasurein people’s
lives.
Cognitive Well-being: individual
Affective
the balanceof pleasuredispleasurein people’s lives. Cognitive Well-being: individual*** **
DRM: Day Well-being:
Reconstruction
Method,
TUS:and
Time-use
Study*** DRMof: Day
Method,TUS:ofTime-use
Study with their own subjectively constructed ideal
evaluation
theirReconstruction
actual life on
the basisa comparison
evaluation of their actual life on the basis of a comparison with their own subjectively constructed ideal

Source:Constructed byby compilingdata from
Helliwell(2011),
Diener& Suh (1997),
Source:Constructedbyauthorauthorby compiling
dataDiener
from (1998,
Diener2000),(1998),
Diener(2000),
Helliwell(2011), Diener & Suh
Sumner (1996),(1996), andSchimmack
et al.et(2008).
(1997), Sumner
andSchimmackal. (2008).

214

A. H. PANDYASWARGO et al.

linked only very weakly to well-being (Ahuvia A. C.,
2008a, b). These examples are just a few of the plenty ofopportunities to design a way for the two approaches tocompensate for each other’s weaknesses and provide aholistic picture of development and social progress.

4. Conclusions
It has been recognized that the betterment of wellbeing is not just a development goal but also a goal forsocial capital itself to accommodate efficient and effective
sustainable development. To help nations design anenvironment where people can make better decisions
contributing to development, though, an appropriate,accurate means of measurement is required. Subjective
measurements have been considered supplemental toobjective monitoring. In practice, objective measurements
alone do not tell the complete story. On the other hand,ways are still being found to pair subjective measurements
properly with objective measurements. This study mentions
several pairing methods and under which circumstances
they can be performed. The example of Indonesia’s first
SWB report was brought up to demonstrate some concrete
recommendations. Suggestions for effective Indonesian
SWB monitoring, sourcing from national scholars andevidence from previous studies and literature have beenpresented in this study.
The following is a summary of recommendations thatmight also have larger implications in well-being
monitoring in general. 1) Avoid bias by careful ordering ofquestions and incorporating bipolar questions, 2)  Avoid
errors by using time frames and mentioning what toconsider in giving answers, 3) Cover both the cognitiveand emotional states of the respondents 4) Deliver andpresent the interview in an added-value setting, and5) Establish a national-scale official procedure on how tocollect data using a holistic (objectively and subjectively
measured) well-being indicator that is reproducible andultimately allows international comparisons. Further
studies may cover how incorporating technologies could
make the process of data collection even moreinteractive so that identification of missing links andquick reviewing to spot errors can be done together withrespondents. Pilot projects on applying hybrid tools suchas the DRM and optimized time-use studies in developing
countries may be the first step toward designingappropriate strategies for a larger scale implementation.

Acknowledgements
This research was supported by the Environment
Research and Technology Development Fund (S-11) of
the Ministry of the Environment, Japan.

References
Ahuvia, A.C. (2008a) Wealth, consumption, and happiness. In: A.
Lewis, ed., The Cambridge Handbook of Psychology andEconomic Behaviour. Cambridge: Cambridge University Press.

Ahuvia, A.C. (2008b) If money doesn’t make us happy, why do
we act as if it does? Journal of Economic Psychology, 29(4):491–507.
BAPPENAS (2014) Kegiatan Utama. Kementrian PPN/BAPPENAS.
<http://www.bappenas.go.id/berita-dan-siaran-pers/bappenas-bpsfms-diskusikan-indeks-kebahagiaan-indonesia-2013/>(accessed 3 Feb 2015).
Beddington, J., C.L. Cooper, J. Field, U. Goswami, F.A. Huppert,
R. Jenkins et al. (2008) The mental wealth of nations. Nature,
455: 1057–1060.
Beritasatu (2014) BPS Recorded Indonesia’s First Happiness Index
65.11%(available in Bahasa Indonesia). (beritasatu.com, Producer)<http://www.beritasatu.com/ekonomi/187550-pertama-kalinyabps-catat-indeks-kebahagiaan-indonesia-6511.html>(accessed 3 Feb 2015).
BPS (2012) About BPS. Badan Pusat Statistik.
< http: / / www.bps.go.id/ eng/ menutabs1.php? tab= 1& aboutus=
0&tentang=1&id_tentang=1>(accessed 12 Feb 2015).
BPS (2014) Indonesian Happiness Index 2013 (available in Bahasa
Indonesia). Jakarta: BPS.
Clark, L.A. and D. Watson (1988) Development and validation ofbrief measures of positive and negative affect: The PANAS
scales. Journal of Personality and Social Psychology, 54(6):1063–1070.
CPPS (2014) Center for Population and Policy Studies Gadjah
Mada University. Happiness Index is weak: measurement covers
mainly on material factors (available in bahasa Indonesia).
<http://www.cpps.or.id/content/indeks-kebahagiaan-masih-lemahpengukuran-cenderung-gunakan-indikator-kekayaan-materioleh-agus-h-hadna>(accessed 3 Feb 2015).
Deci, E.L. and R.M. Ryan (2006) Hedonia, Eudaimonia, and wellbeing: an introduction. Jounal of Happiness Studies, 9: 1 – 11.
Diener, E. (1998) Subjective well-being and personality. In: D.F.
Barone, M. Hersen, V. B. Hasselt, D. F. Barone, M. Hersen and
V. V. Hasselt, eds., Advanced Personality, 311–334. New York:
Plenum Press.
Diener, E. (2000) Subjective well-being: The science of happinessand a proposal for a national index. American Psychologist,
55(1): 34 – 43.
Diener, E. (2009) The Science of Well-Being: The Collected Worksof Ed Diener. Champaign: Springer.
Diener, E. and F. Fujita (1995) Resources, personal strivings, andsubjective well-being: A nomothetic and idiographic approach.
American Psychological Association, 68(5): 926 – 935.
Diener, E. and E. Suh (1997) Measuring quality of life: economic,
social, and subjective indicators. Social Indicators Research,
40: 189 – 216.
Eurostat (2008) Quality of Life. Eurostat, your key to European
statistics.
< http: / / unstats.un.org/ unsd/ broaderprogress/ pdf/ Feasibility_
study_Well-Being_Indicators.pdf>(accessed 5 Feb 2015).
Ferrer-i-Carbonell, A. and P. Frijters (2004) How important ismethodology for the estimates of the determinants ofhappiness? The Economic Journal, 114: 641– 659.
Helliwell, J.F. (2011) How can subjective well-being be improved?
In: F. Gorbet and A. Sharpe, eds., New Directions for Intelligent
Governemnt in Canada, 283–304, Ottawa: Centre for the Studyof Living Standards.
INSEE (2010) Emploi du Temps 2009 – 2010. Emploi du temps(EDT) .
< http: / / www.cmh.ens.fr/ adisp/ documents/ lil-0695/ EDTDDC_
quest%20chercheur_EN.pdf>(accessed 6 Nov 2015).
Joachim, C.B. (1993) Personal goals and subjective well-being: A
longitudinal study. Journal of Personality and Social Psychology,
1061–1070.

Objective and Subjective Measurements for Development and Well-being: Some Perspectives
Kahneman, D. and A.B. Krueger (2006) Developments in themeasurement of subjective well-being. Journal of Economic
Perspectives, 20(1): 3 – 24.
Kahneman, D., E. Diener and N. Schwarz (1999) Well-being: The
Foundations of Hedonic Psychology. New York: Russell Sage
Foundation.
Kahneman, D., A.B. Krueger, D.A. Schkade, N. Schwarz, N. and
A.A. Stone (2004) A survey method for characterizing daily life
experience: the day reconstruction method. Science, 306: 1776 –1780.
Larsen, R. J., E. Diener and R.A. Emmons (1985) An evaluationof subjective well-being measures. Social Indicators Research,
17: 1 – 7.
Layard, R. (2006) Happiness and public policy: A challenge to theprofession. The Economic Journal, C24–C33.
Metro TV (2014) Ekonomi. Metrotvnews.com.
< http: / / ekonomi.metrotvnews.com/ read/ 2014/ 06/ 02/ 248149/
inilah-karakteristik-indeks-kebahagiaan-indonesia-2013>(accessed 3 Feb 2015).
National Geographic Indonesia (2014) National Geographic
Indonesia. Budaya.
<http://nationalgeographic.co.id/berita/2014/06/orang-indonesiapaling-bahagia-saat-tinggal-di-kota-berpendapatan-tinggi-berkeluarga>(accessed 3 Feb 2015).
National Statistic Bureau (2015a) Happiness Level Measurement
Study (available in Bahasa Indonesia). Sistem Informasi
Rujukan Statistik.
<http://sirusa.bps.go.id/index.php?r=sd/detail&kd=2926&th=
2014> (accessed 5 Mar 2015).
National Statistics Bureau (2015b) Happiness Level Measuring
Study 2013 (available in Bahasa). Sistem Informasi Rujukan
Statistik.
<http://sirusa.bps.go.id/sirusa/index.php/dasar/view?kd=2926&
th=2013> (accessed 5 Feb 2015).
National Statistics Bureau (2013) Kuesioner. Sirusa.
<http://sirusa.bps.go.id/webadmin/kuesioner/2013_2926_ques_
SPTK2013.RT.pdf> (accessed 5 Feb 2015).
NEF (2011) Economics as If People and The Planet Mattered.
New Economics Foundation.
<http://www.neweconomics.org/publications/entry/measuringour-progress> (accessed 5 Feb 2015).
OECD (2014a) Better Life Initiative: Measuring Well-Being andProgress. OECD statistics.
<http://www.oecd.org/statistics/better-life-initiative.htm>(accessed 5 Feb 2015).
OECD (2014b) Frequently Asked Questions. Better Life Index.
<http://www.oecdbetterlifeindex.org/about/better-life-initiative/#question3> (accessed 12 Feb 2015).
Pandyaswargo, A.H., N. Abe and Y. Franciscus (2013) Participatory
Workshop on Bottom-up Study Contributing to The Realizationof Sustainable Development Goals: Surabaya Case Study.
Tokyo Institute of Technology, International Development
Engineering.
Pandyaswargo, A.H., N. Abe and Y. Franciscus (2014) Surabaya
Community Workshop: Bottom-up Study Realizing Sustainable
Development Post 2015. Abe Lab Tokyo Tech.
< http: / / www.ide.titech.ac.jp/ ~ nabe/ wp/ wp-content/ uploads/
2014/09/Community-workshop-program_final.pdf>(accessed 3 Feb 2014).
Richard, E.L. (2007) Long-term disability is associated with lastingchanges in subjective well-being: Evidence from two nationally
representative longitudinal studies. Journal of Personality andSocial Psychology, 92: 717 – 730.
Ryan, R.M. and E.L. Deci (2001) On happiness and humanpotentials: a review of reearch on hedonic and eudaimonic wellbeing. Annual Review of Psychology, 52: 141 – 166.
Schimmack, U., J. Schupp and G. Wagner (2008) The influence ofenvironment and personality on the affective and cognitive
component of subjective well-being. Social Indicator Research,

215(89): 41– 60.
Smith, C. and C. Exton (2013) OECD Guidelines on Measuring
Subjective Well-being. OECD, OECD Better Life Initiative.
OECD Publishing.
Stiglitz, J.E., A. Sen and J.-P. Fitoussi (2009) Report by theCommission on the Measurement of Economic Performace andSocial Progress. Commission on the Measurement of Economic
Performance and Social Progress.
<www.stiglitz-sen-firoussi.fr.>
Sumner, L.W. (1996) Welfare, Happiness, and Ethics. New York,
NY: Oxford University Press.
Tellegen, A., D.T. Lykken, T.J. Bouchard, K.J. Wilcox, N.L. Segal
and S. Rich (1988) Personality similarity in twins reared apartand together. Journal of Personality and Social Psychology,
54(6): 1031–1039.
The Commission on Measuring Well-being, Japan (2011) Measuring
National Well-Being −Proposed Well-being Indicators. Koufukudo.
<http://www5.cao.go.jp/keizai2/koufukudo/pdf/koufukudosian_english.pdf>(accessed 6 Nov 2015).
The WHOQOL Group (1998) Development of the World Heath
Organization WHOQOL-BREF quality of life assessment.
Psychological Medicine, 28, 551 – 558.
United Nations (2014) Economic and Social Development. UN
Department of Economic and Social Affairs.
<http://unstats.un.org/unsd/demographic/sconcerns/tuse/tu3.aspx>(accessed 3 Feb 2015).
UNSTATS (2015) Results of the List of Indicators Reviewed at theSecond IAEG-SDG Meeting. UNSTATS SDGS files.
<http://unstats.un.org/sdgs/files/meetings/iaeg-sdgs-meeting-02/
Outcomes/ Agenda% 20Item% 204% 20-% 20Review% 20of% 20
proposed% 20indicators% 20-% 202% 20Nov% 202015.pdf>(accessed 17 Nov 2015).
Watabe, R. and S. Kouno (2014) 25th Fiscal Year Household Survey
on Quality of Life. Economic and Social Research Institute,Cabinet Office, Tokyo, ESRI.
World Bank (2015) Indonesia.
<http://data.worldbank.org/country/indonesia>(accessed 12 Feb 2015).

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A. H. PANDYASWARGO et al.
Andante Hadi PANDYASWARGO

Andante’s current focus in development covers
well-being as social capital and a basic humanneed in urban areas. Her interest in the dynamics
of social resources came from the realization of
the incompleteness of hard data to explain failures
and respond to challenges in development efforts.
She gained her Ph.D. at Waseda University inenergy and environmental engineering and holds a double master’s degree
in international material flow management engineering and international
cooperation policies. Her experience in international organizations andresearch institutes such as the Asian Development Bank (ADB), United
Nations University (UNU) and Institute for Global Environmental
Strategies (IGES) has given her both practical experience and aconceptual understanding of development practices. She is currently
working at the Tokyo Institute of Technology as a lecturer in the
Department of International Development Engineering.

Naoya ABE
Naoya ABE is currently an associate professor
in the Department of International Development
Engineering, Tokyo Institute of Technology,
Japan. He has worked for the Overseas
Economic Cooperation Fund (OECF) and, from1995 to 2000, the Japan Bank for International
Cooperation (JBIC), which is a Japanese
governmental arm for development aid and international cooperation.
Before joining Tokyo Tech in 2007, he worked at the National Institutefor Environmental Studies (NIES) in Tsukuba, Ibaraki as a researcher
participating in a project on municipal solid waste management. ABE has
research interests in human-centered renewable energy policy, sustainable
operation & maintenance (O&M) of environmentally friendly technologies,
capacity development evaluation in an international cooperation context
and the overlap area between appropriate technology and social
entrepreneurship. He holds both a Bachelor’s and Master’s in Engineeringfrom Tokyo Tech and a Ph.D. in Applied Economics and Managementfrom Cornell University, NY, USA. He was a Fulbright Scholar during
his doctoral study at Cornell University.

Yunus FRANSISCUS
Yunus FRANSISCUS obtained his Master’s Degree
in Environmental Science and Technology at
UNESCO - IHE, Institute for Water Education,
Delft, the Netherlands. His professional career
started from the industrial sector, having worked
for a paper company and the power plant
industry for five years before entering the
University of Surabaya, Indonesia. Recently, he has been in charge as
director of the Center for Environmental Studies at the University ofSurabaya, Indonesia. At the same time, he has been serving as a lecturer
in the Chemical Engineering Department at the same university forenvironmental subjects. His research interests include wastewater
treatment, solid waste management and sustainable development. He has
been involved in several projects, at both the international and national
level in the area of pollution control systems, waste minimization,
environmental education and sustainability, all of which deal withmultiple stakeholders.
(Received 26 May 2015, Accepted 19 November 2015)