Desktop version

Home arrow Business & Finance

  • Increase font
  • Decrease font

<<   CONTENTS   >>
Table of Contents:

Innovative features

The analysis reported in Chapters 2 through 6, and outlined earlier, has

several innovative features:

  • • The first, in Chapter 2, is the concept of “equally distributed happiness”.4 The idea here is that social welfare is reduced if happiness is unequally distributed and that, therefore, one might be willing to accept a lower level of overall happiness providing it was equally distributed. How much lower would depend on the extent to which one was averse to inequality in the distribution of happiness, and Chapter 2 presents estimates of “equally distributed happiness” with respect to different levels of inequality aversion.
  • • The second, in Chapter 3, is to use an econometric model with interaction effects which allows men and women to respond differently to each of several depression/anxiety/anger-inducing factors. This allows one to test whether there is a significant gender difference in responses to these conditions.
  • • The third, also in Chapter 3, is to use a decomposition methodology to quantify the contribution of differences in exposure and differences in response (to condition-inducing factors) to inter-gender differences in depression, anxiety, and anger rates.
  • • The fourth, in Chapter 4, is to use a joint model to estimate the likelihood of emotional and physical abuse of married women in order to allow for the fact that the two probabilities are likely to be correlated.
  • • The fifth, also in Chapter 4, is to use inequality decomposition to measure the individual contributions of household wealth, alcohol, and controls to the likelihood of wives being subject to violence from their husbands.
  • • The sixth, in Chapter 5, is to suggest and implement a methodology for measuring the extent to which the stop rate of an ethnic group is the result of racial bias by the police and the extent to which it is due to location (i.e., living in areas where there are a large number of police stops).
  • • The seventh, also in Chapter 5, is to use a Bayesian methodology to show how any post-stop arrests could be aligned with the initial stops to examine whether groups that are disproportionately stopped are also disproportionately more likely to offer a reason for arrest.
  • • The eighth, in Chapter 6, is the use of techniques borrowed from analysis of poverty to develop the concept of a “xenophobia score” which is used to measure the amount of xenophobia in different regions of the world.
  • • The ninth, also in Chapter 6, is the decomposition of homophobia into two parts: as exercised by those who regard homosexuality as wrong (intolerance) and as exercised by those who do not think homosexuality as wrong but who are, nevertheless, anxious to conform to societal norms (conformity). The outcome with respect to overall homophobia is then a weighted average of intolerance and conformity.
  • • The tenth, also in Chapter 6, is to define the concept of gender tension in terms of a disjoint between male and female attitudes towards gender equality and to provide measures of such tension for the world’s regions and its major religions.
  • • Finally, and most important, threaded through the chapters is a prediction technique which forms the foundation for many of the reported results. This is the method of recycled predictions.5 In evaluating the effect of two characteristics A and В on the likelihood of a particular outcome, the method of recycled predictions compares two sets of average probabilities: first, under an “all have the characteristic A” scenario and, then, under an “all have the characteristic B” scenario, with the values of the other variables remaining unchanged between the scenarios. The difference in the two probabilities is then entirely due to the attributes represented by A and В (e.g., caste/racial differences in Chapter 2 or gender differences in Chapter 3). These probabilities are referred to as the predicted probabilities of an event under A and B.

The book covers a diversity of issues using the technical apparatus of economics to rigorously interrogate the relevant data. It has been written so that every chapter is self-contained and can be read independently of the others. Since some of the techniques are used in more than one chapter their explanation is repeated in the chapters in order to maintain this feature of self-containment.


  • 1 Prominent among these dissenting economists are Blanchflower and Oswald (2000), Clark (1996, 1999, 2001), Clark and Senik (2014), Clark et al. (2019), Easterlin (1974, 1987, 2001, 2015), Frank (1985, 1997, 1999), Frey and Stutzer (2002), Frey (2008), Hirsch (1976), Fayard (2011, 2020), Oswald (1997), and Scitovsky (1976).
  • 2 Using World Values Survey (WVS) data, Dowling and Yap examine the strength of factors determining both happiness and life satisfaction for respondents in three regions: Asia, Africa and Fatin America. In so doing, they first consider all respondents to the WVS in their entirety and, second, those respondents to the WVS who could be considered “poor” either in terms of income, education, or health.
  • 3 See, for example, Borooah (2011) and Lamberth (1998).
  • 4 Derived from Atkinson’s (1970) concept of “equally distributed income”.
  • 5 See Fong and Freese (2014, chapter 4) and estimation.pdf.


Atkinson, A.B. (1970), “On the Measurement of Inequality”, Journal of Economic Theory, 2: 244-263.

Blanchflower, D. and Oswald, A. (2000), “Well-Being Over Time in Britain and the USA”, NBER Working Papers, no. 7487, Cambridge, MA: National Bureau of Economic Research.

Borooah, V.K. (2006), “What Makes People Happy? Some Evidence from Northern Ireland”, Journal of Happiness Studies, 7: 427-465.

Borooah, V.K. (2011), “Racial Disparity in Police Stop and Searches in England and Wales”, Journal of Quantitative Criminology, 27: 453^173.

Clark, A.E. (1996), “Job Satisfaction in Britain”, British Journal of Industrial Relations, 34: 189-217.

Clark, A.E. (1999), “Are Wages Habit Forming? Evidence from Micro Data”,/o«r- nal of Economic Behaviour and Organisation, 39: 179-200.

Clark, A.E. (2001), “What Really Matters in a Job? Hedonic Measurement Using Quit Data”, Labour Economics, 8: 223-242.

Clark, A.E., Fleche, S., Fayard, R., Powdthavee, N. and Ward, G. (2019), The Origins of Happiness: The Science of Well-Being over the Life Course, Princeton, NJ: Princeton University Press.

Clark, A.E. and Senik, C. (2014), Happiness and Economic Growth, Oxford: Oxford University Press.

Dowling, J.M. and Yap, C-F. (2013), Happiness and Poverty in Developing Countries, Basingstoke: Palgrave Macmillan.

Easterlin, R.A. (1974), “Does Economic Growth Improve the Human Lot? Some Empirical Evidence”, in P.A. David and M.W. Reder (eds.), Nations and Households in Economic Growth: Essays in Honour of Moses Abramowitz, pp. 89-125, New York: Academic Press.

Easterlin, R.A. (1987), Birth and Fortune: The Impact of Numbers on Personal Welfare, Chicago, IL: Chicago University Press (2nd edition).

Easterlin, R.A. (2001), “Income and Happiness: Towards a Unified Theory”, Economic Journal, 111: 465-484.

Easterlin, R.A. (2015), “Happiness and Economic Growth: The Evidence”, in W. Glatzer, L. Camfield, V. Mailer and M. Rojas (eds.), Global Handbook of Quality of Life, pp. 280-300. Dordrecht: Springer.

Frank, R.H. (1985), Choosing the Right Pond, Oxford: Oxford University Press.

Frank, R.H. (1997), “The Frame of Reference as a Public Good”, Economic Journal, 107: 1832-1847.

Frank, R.H. (1999), Luxury Fever: Money and Happiness in an Era of Excess, Princeton, NJ: Princeton University Press.

Frey, B.S. (2008), Happiness: A Revolution in Economics, Cambridge, MA: MIT Press.

Frey, B.S. and Stutzer, A. (2002), Happiness and Economics, Princeton, NJ: Princeton University Press.

Hirsch, F. (1976), The Social Limits to Growth, Cambridge, MA: Harvard University Press.

Famberth, J. (1998), “Driving While Black: A Statistician Proves that Prejudice Still Rules the Road”, Washington Post, 16 August, p. cOl.

Fayard, R. (2011), Happiness: Lessons from a New Science, London: Penguin Books.

Layard, R. (2020), Can We Be Happier: Evidence and Ethics, London: Pelican Books.

Long, J.S. and Freese, J. (2014), Regression Models for Categorical Dependent Variables Using Stata, College Station, TX: Stata Press.

Marks, N. (2004), “Towards Evidence Based Public Policy: The Power and the Potential of Using Well-Being Indicators”, paper presented at an International Seminar on Internationalising the Concept of Gross National Happiness, Thimphu, Bhutan, (accessed 14 February 2020).

Oswald, A. (1997), “Happiness and Economic Performance”, Economic Journal, 107: 1815-1831.

Scitovsky, T. (1976), The Joyless Economy, New York: Oxford University Press.

<<   CONTENTS   >>

Related topics