Counting Happiness from Individual Level to Group Level EDSEL L. BEJA JR. Ateneo de Manila University

Bibliography Alkire and Foster (2011). Counting and multi-dimensional poverty measurement, Journal of Public Economics 95(7-8): pp. 476-487 Balisacan (2011). What Has Really Happened to Poverty in the Philippines? New Measures, Evidence, and Policy Implications, UP School of Economics, Working Paper 2011-14

Bibliography Ura, Alkire, and Zangmo (2012). Bhutan: Gross national happiness and the GNH index, in Helliwell, Layard, and Sachs (editors), World Happiness Report (pp. 109-147) Beja and Yap (2013). Counting Happiness from the Individual Level to the Group Level, Social Indicators Research 114(2): pp. 621-637

Methodology Suppose n persons and m life domains. Each life domain can be a single dimension or comprised of multiple dimensions. Putting multiple dimensions together as single life domain requires predetermined weights (e.g., use stated individual ranking or external ranking).

Methodology Define y = [yij] as a matrix of subjective well-being (i.e., happiness) of person i = 1...n (row) for life domain j = 1…m (column), 10 > yij > 0. Hence, row expression (yi1, yi2… yim) is person i’s self-report for life domain 1 to j; the column expression (y1j, y2j… ynj)T is 1…n persons’ self-reports for a specific life domain j.

Methodology First step: define threshold value for each life domain as 10 > yj* > 0. (It is possible to have the same y* across domains for simplicity.) Then, gij = 1 iff yij ≥ yj* and gij = 0 otherwise; thus, obtain g = [gij] as a matrix composed of 1 and 0 values.

Methodology Second step: get the horizontal sum across life domains (i.e., Σgij) and obtain vector s = [si], where m ≥ si > 0. (Recall, m is number of columns.) That is, each element in s represents the total number of life domains of person i that is above threshold.

Methodology Third step: the identification of happy people is by censoring s. Thus, h = [hi] as censored vector s with hi = 1 iff si ≥ d and hj = 0 otherwise. The number of life domains, d, used for censoring may be set ex ante. Group level happiness is therefore (Σh)/n with Σh as the count of happy people who fulfill the cutoff number of life domains that exceed a threshold

Measurement Scale ├──┼──┼──┼──┼──┼──┼──┼──┼──┼──┤ Gallup: Cantril Scale (Cantril 1967) ├──┼──┼──┼──┼──┼──┼──┼──┼──┼──┤ 0 1 2 3 4 5 6 7 8 9 10 World Values Survey (Campbell et al 1976) ├──┼──┼──┼──┼──┼──┼──┼──┼──┤ 1 2 3 4 5 6 7 8 9 10

Example d1 d2 d3 d4 d5 d6 Person 1 8 6 9 7 Person 2 5 Person 3 Raw data for five individuals for six domains.

Example d1 d2 d3 d4 d5 d6 Person 1 8 6 9 7 Person 2 5 Person 3 Define threshold per domain. Let’s set value at 7 regardless of domain, for simplicity; i.e., gij = 1 iff yij ≥ 7.

Example d1 d2 d3 d4 d5 d6 Person 1 8 6 9 7 Person 2 5 Person 3 Define threshold per domain. Let’s set value at 7 regardless of domain, for simplicity; i.e., gij = 1 iff yij ≥ 7.

Example g1 g2 g3 g4 g5 g6 Person 1 1 Person 2 Person 3 Person 4 Person 2 Person 3 Person 4 Person 5 Define threshold per domain. Let’s set value at 7 regardless of domain, for simplicity; i.e., gij = 1 iff yij ≥ 7.

Example s h Person 1 5 1 Person 2 Person 3 Person 4 3 Σh = Person 5 4 Σh = Person 5 4 n = h = [hi] as censored vector s with hi = 1 iff si ≥ d and hj = 0 otherwise. Suppose d = 5.

Other Issues Measurement Scale (specifically, issues about cardinality and comparability) Validity (i.e., how accurate do we measure a construct) and Reliability (i.e., how precise are we measuring a construct)

Measurement Scale ├──┼──┼──┼──┼──┼──┼──┼──┼──┼──┤ 0 1 2 3 4 5 6 7 8 9 10 ├─┼─┼─┼─┼─┼─┼─┼─┼─┼─┤ 0 1 2 3 4 5 6 7 8 9 10

Measurement Scale ├──┼──┼──┼──┼──┼──┼──┼──┼──┼──┤ 0 1 2 3 4 5 6 7 8 9 10 ├┼┼─┼─┼─┼───┼───┼───┼────┼────┤ 0 12 3 4 5 6 7 8 9 10

Parable of the Half Full Glass

Ateneo College Students Measurement Scale (Beja) 0% 100% ├──┼──┼──┼──┼──┼──┼──┼──┼──┼──┤ 0 1 2 3 4 5 6 7 8 9 10

Ateneo College Students

Ateneo College Students

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