The applet requires Java 1.4.1 or higher. It will not run on Windows 95 or Mac OS 8 or 9. Mac users must have OS X 10.2.6 or higher and use a browser that supports Java 1.4. (Safari works, IE does not. Mac OS X comes with Safari. Open Safari and set it as your default web browser under Safari/Preferences/General.) On other operating systems, you may obtain the latest Java plugin from Sun's Java site.
powered by NetLogo
view/download model file: the_pursuit_of_happiness.nlogo
Our aim was to build a model in Netlogo that allowed us to simulate the Happiness Paradox. This could be defined a "social model": we used the computer and Netlogo like a laboratory in oder to investigate the relationship between happiness and wealth. Besides we try to understand the role that factors such as the reference groups, the education and the confidence play in the determination of the final level of happiness.
We wanted to recreate a real situation in the initial scenery (Setup). So the environment is a metaphorical and not a real place. We splited the world into four different areas that represent the main four income areas in Italy, in according to the data provided by the Italian Department of Economy and Finance in March 2010. The white area represents a gross income area inferior to 15.000 euros per year, the turquoise one identifies a gross income between 15.000 and 35.000 euros per year, the light-blue area is related to an annual gross income between 35.000 and 100.000 euros and the blue area represents the higher income (superior to 100.000 euros per year).
We provided to place the agents in these areas in according to the Italian economic situation at the end of 2008 (the latest data). So the 49,79% of the agents is located in the white area, the 40,61% is in the turquoise area, the 8,65% is in the light-blue space and the remaining 0,95% occupies the blue area.
BASIC SCENERY: In this first elementary scenary we recreate the following situation: there are not reference groups, agents in different areas behave in according to different rules. We hypothesize that all the agents aim to improve their income even if they are not always able to succeed in their purpose (set heading random-float 360). If they succeed, they move toward the top of the world, otherwise they move in the opposite direction. All the agents own an internal measurement of their "well-being": they consume it during the pursuit of happiness.
Happy agents are represented in green, while the unhappy ones are purple. When the
ammount of the parameter "Well-being" achieves given levels (defined in according to the mean and the standard deviation of the Well-being Bell Curve), the agents turn into the opposit status (happy if they are unhappy and viceversa).
REFERENCE GROUPS: In this second scenery, we hypothesize that a foreign company established in the word: so there is an extra work supply. The agents decide to accept or reject the extra job considering their neighbors. As above, the agents own an internal measurement of their "well-being" and they consume it during their pursuit of happiness.
SCHOOLING versus SCHOOLING-AND-REFERENCE GROUPS: In these new sceneries, we hypothesize again that a foreign company established in the word: so there is an extra work supply. The agents decide to accept or reject the extra job considering their education (in the first instance) and their education and their neighbors (in the second instance). As above, the agents own an internal measurement of their "well-being" and they consume it during their pursuit of happiness.
CONFIDENCE: In this last scenery, we hypothesize again that a foreign company established in the word: so there is an extra work supply. The agents decide to accept or reject the extra job considering their neighbors and the level of trust in them. As above, the agents own an internal measurement of their "well-being" and they consume it during their pursuit of happiness.
Thanks to a slider renamed "People", the end users of the simulation model can individually choose how many agents create: they can give life to a minimum of 10 agents and to a maximum of 1.000 agents.
Happiness has been represented by colors: green agents are happy, the purple ones are unhappy. Using the slider "Happiness", the end users can choose the percentage of initial happy agents. Immediately below these sliders, there are two monitors that count and show how many happy and unhappy people fill the world in every moment. In order to allow an immediate visualization of the outcoming of the experiment we are conducting, it has been created a chart that shows the number of happy and unhappy people over the time. The agents own an inner measurement of their well-being, education and trust. These parameters are supposed to be distributed like a Normal Curve. The users can change the values of the mean and the standard deviation for each parameter using the appropriated sliders.
After pushing the button "Setup" and having created the world and the agents, the user can choose the desired level for all the parameters mentioned above. Then he can make the model run pushing one of the 5 buttons described in the previous paragraph. Pushing again the same button, the simulation stops.
The end users can choose the level of different parameters: they can choose how many agents they want to create and the initial percentage of happy (green) people. In addition, they can change the level of the mean and the standard deviation fot the following parameters: education, trust and well-being. Moving the sliders, the users are able to conduct different experiments and investigate the influence that each parameter has in the building of happiness.
It is possible to complicate the procedure. We can take a step forward changing the rules that make the agents move: they move toward the top of the world or in the opposite direction in according to very simple rules that consider a few number of variables. We could introduce more variables and a more complex system of rules. In addition, we could introduce a Rule Maker in the program: at the moment it is present only a Rule Master. Then complicating the model, giving the agents a memory, a larger sight of the environment and a deep capacity of action we can turn this model from an emergentist into an imergentist model.
This model is related to the Segregation Model by Schelling [1973] and to a model listed in the Library section of Netlogo, the Cooperation Model in the Social Science section.
In order to build the model, it was necessary to look for data and information. These are the papers and the website we used to get the information:
- Bruni, Sacco, Zamagni, L’economia e i paradossi della felicità. Complessità relazionale e comportamento economico, verso un nuovo paradigma di razionalità, Il Mulino, Bologna, 2002
- http://www.chinadaily.cn/opinion/2010-04/09/content_9708996.htm
- Frank, Choosing the right pond: human behavior and the quest for status, New York: Oxford University Press, 1985
- Bergheim, The happy variety of capitalism, Deutsche Bank Research, Frankfurt am Main, 2007
- De Biase, Economia della felicità. Dalla blogosfera al valore del dono e oltre, Feltrinelli, Milano, 2007
- Ministero dell'Economia e delle Finanze, Anticipazione statistiche delle dichiarazioni fiscali relative al periodo d’imposta 2008, http://www.finanze.gov.it/stat_anticipazioni2008/stat_2008.htm, marzo 2010
- Daniel Kahneman, Alan B. Krueger, David Schkade, Norbert Schwarz, Arthur A. Stone, Would You Be Happier If You Were Richer? A Focusing Illusion, CEPS Working Paper No. 125, May 2006 (http://www.morgenkommichspaeterrein.de/ressources/download/125krueger.pdf)