<iframe src="https://giphy.com/embed/chzz1FQgqhytWRWbp3" width="150" height="150" frameBorder="0" class="giphy-embed" allowFullScreen></iframe>

The World Happiness Report (WHR) claims that:

5 latent (psychological variables) are assessed:

1. Happiness:

   “Please imagine a ladder, with steps numbered from 0 at the bottom to 10 at the top. The top of the ladder represents the best possible life for you and the bottom of the ladder represents the worst possible life for you. On which step of the ladder would you say you personally feel you stand at this time?”

2. Social Support

   “If you were in trouble, do you have relatives or friends you can count on to help you whenever you need them, or not?” Response scale: O e 1.

3. Freedom to make life choices

   “Are you satisfied or dissatisfied with your freedom to choose what you do with your life?” Response scale: O e 1.

4. Generosity

   “Have you donated money to a charity in the past month?” Generosity is the residual of regressing national average of response to the GWP question “Have you donated money to a charity in the past month?” on GDP per capita

5. Perception of Corruption:

   “Is corruption widespread throughout the government or not” and “Is corruption widespread within businesses or not?” The overall perception is just the average of the two 0-or-1 responses.

Additionaly, gdp per capta and healthy life expectancy at birth are also assed.

![distribution] (/Users/Juliana/Desktop/Ironhack/Projects/World-Happiness-Project2/figures/Life ladder.png)

The variables of the WHR are either strongly correlated (log gdp per capta,social support,life expectancy) or moderated correlated (freedom to make choices, negative affect, positive affect, and corruption). Generosity is weakly correlated and is the only one in the reverse direction than expected.

![correlation WHP] (https://github.com/ju-br/World-Happiness-Project2/blob/main/figures/correlation%20heatmap%20happiness.png)

![correlation] (/Users/Juliana/Desktop/Ironhack/Projects/World-Happiness-Project2/figures/correlation heatmap happiness.png)

However, when we are measuring latent variables we have to be sure that we are measuring what we want to assess.

As latent variables cannot be observed, there are some criteria that should be met:

1. Multiple items to operationalize:

Life ladder ❌

Social Support ❌

Corruption ❌

Freedom of choice ❌

Generosity ❌ WHP: latent variables measured with a single item

With one item you cannot check reliability statistics

2. To aggregate data, in a higher level, measured with a different referent we need to check if the higher level influence (country) the smaller one(person). Aggregation statistics:

Icc 1 - Percentage of aggregated influence of country level on person ❌

ANOVA - variance between countries ❌

ADI - agreement within countries ❌

Alternative: multilevel measure ❌

3. Content validity: Refers to how well a survey or test measures the construct that it sets out to measure.

Life ladder ❌

Social Support ✅

Corruption ✅

Freedom of choice ✅

Generosity ❌

4. Criterion validity: Criterion validity indicates how well the scores or responses of a test converge with criterion variables with which the test is supposed to converge.

Life ladder - inequality ✅

![ladder-inequality] (/Users/Juliana/Desktop/Ironhack/Projects/World-Happiness-Project2/figures/correlation heatmap happiness.png)

Life ladder - depression ✅

![ladder-depression] (/Users/Juliana/Desktop/Ironhack/Projects/World-Happiness-Project2/figures/correlation heatmap happiness.png)

Life ladder - alcohol use ❌

![ladder-alcohol] (/Users/Juliana/Desktop/Ironhack/Projects/World-Happiness-Project2/figures/correlation heatmap happiness.png)

Life ladder - drug use ❌

![ladder-drug] (/Users/Juliana/Desktop/Ironhack/Projects/World-Happiness-Project2/figures/correlation heatmap happiness.png)

Life ladder - anxiety ❌

![ladder-anxiety] (/Users/Juliana/Desktop/Ironhack/Projects/World-Happiness-Project2/figures/correlation heatmap happiness.png)

Life ladder - suicide ❌

![ladder-suicide] (/Users/Juliana/Desktop/Ironhack/Projects/World-Happiness-Project2/figures/correlation heatmap happiness.png)

It might be the case the latent variables within WHR are highly correlated due to self report bias

Curiosity: Life ladder - temperature (omitted variable?)❌

![ladder-temperature] (/Users/Juliana/Desktop/Ironhack/Projects/World-Happiness-Project2/figures/correlation heatmap happiness.png)

Cross-cultural explorations reveal varying, multiple and often conflicting beliefs within and between groups. Happiness research has been criticised for producing not simply descriptive but prescriptive accounts based upon unacknowledged value judgments and (western) social norms.

Moreover, to attest that all countries have the same perception and, therefore, their scores are comparable, measurement invariance should be evaluated.

In recent years, interest in happiness has been growing across numerous disciplines, particularly in the fields of psychology and economics. It has also become an increasingly significant object of public policy both domestically and internationally with governments around the world considering measures of happiness, or ‘subjective well-being,’ as progress indicators and tools for appraising policy. Yet, the findings from happiness surveys are nonetheless often taken to be data about an objectively verifiable construct (rather than a socially mediated expression of feelings), and are used to issue advice to governments about policies that should maximise happiness’ (Duncan 2005). This, according to Jugureanu et al., (2014), is the ‘axiomatic error’ of happiness studies: ‘the search for an eternal, unchanging, all-encompassing definition of happiness involves the epistemological fallacy that happiness “has” a kind of essence that can be rendered conceptually. However, there is often mixed, weak or inadequate evidence to support frequent claims. Further problems are: claims and activities of advocacy groups are often cited as ‘research evidence’ (Ecclestone 2007:460), conclusions drawn from findings not replicated in subsequent research (Freese et al. 2007; Lazarus 2003b; Mongrain and Anselmo-Matthews 2012)5 or extrapolated from small studies or unrepresentative groups (Fitzpatrick 2006; Miller 2008; Morrall 2009), and correlations treated causally (Ehrenreich 2009, Miller 2008; Saunders and Evans 2010).

The majority of variables of interest focus on abstract phenomena and one cannot measure them directly (e.g. job engagement). In order to subsidize strategic decision making, the ability to choose or develop assessments valid and reliable data is an essential capability to be successful. Using validated measures is the safest and more economical choice. They are more reliable and developed following a strict process. An alternative to finding such measures is the Academy of Management Measurement Chest. Problems with measures’ reliability and validity often lead to unreliable metrics. For example, usually, in-house solutions are developed without a rigorous literature review to define the phenomena and to formulate items.

For more about why HR measures fail: [https://www.aihr.com/blog/in-house-hr-assessment/?utm_source=linkedin&utm_medium=social&utm_campaign=blog&utm_content=a-hr-assessment]

For more on measurement developments: [https://link.springer.com/article/10.1007/s10551-021-04864-7]