Intergenerational solidarity, human values and consideration of the future

99 Pages·2015·7.97 MB·English

Intergenerational solidarity, human values
and consideration of the future

Jamie McQuilkin

Faculty of Psychology
University of Iceland
2015
Jamie McQuilkin

60 ECTS thesis submitted in partial fulfilment of a
Magister Scientiarum degree in Environment and Natural Resources

Advisors:
Ragna Benedikta Gar!arsdóttir
"röstur "orsteinsson
Brynhildur Davi!sdóttir

Faculty Representative
Hulda "órisdóttir

Faculty of Psychology
School of Health Sciences
University of Iceland
Reykjavík, May 2015
Intergenerational solidarity, human values and consideration of the future
60 ECTS thesis submitted in partial fulfilment of a Magister Scientiarum degree in
Environment and Natural Resources

Copyright © 2015 Jamie McQuilkin
All rights reserved

Faculty of Psychology
School of Health Sciences
University of Iceland
Sæmundargötu 2
101 Reykjavík, Iceland
Telephone: [phone]

Bibliographic information:
Jamie McQuilkin, 2015, Intergenerational solidarity, human values and consideration of
the future, Master’s thesis, Faculty of Psychology, University of Iceland, pp. 93.

ISBN XX

Printing: XX
Reykjavik, Iceland, May 2015
Abstract
In order to advance our understanding of our individual and collective attitudes and
behaviour towards the future, this interdisciplinary thesis constructs and explores
psychometric and econometric measures of values, consideration of future consequences
and intergenerational solidarity. First, a novel global index of intergenerational solidarity
combining environmental, economic and social dimensions is constructed to enable intra-
and international comparisons of the flows of capital that make up the inheritance of future
generations. This covers >90% of world population in 120 countries and reveals striking
global patterns, with Confucian and Nordic countries scoring above-average, and will
facilitate further research into intergenerational solidarity. Second, the links between basic
human values and consideration of future consequences in a sample (n=833) of Icelandic
students are explored after robust validation of newly-translated measurement constructs,
revealing that values predict a quarter of the variation in future orientation. Further patterns
and implications for further research are discussed.
For Bec
and for the old people planting trees
Table of Contents
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List of Figures
Figure 1: The 19-value model, with 10-, 4- and 2-value labels written
circumferentially (Schwartz et al., 2012). .......................................................... 4!
Figure 2: Self-Enhancement model for analysis of four latent values showing factor
loadings and covariances. ................................................................................... 5!
Figure 3: MDS results showing items clustered into 19 values.. .......................................... 7!
Figure 4: The 19-value model, with 10-, 4- and 2-value labels written
circumferentially (Schwartz et al., 2012) ......................................................... 14!
Figure 5: Strength of correlation between values and CFC. ............................................... 20!
Figure 6: Index of Economic Wellbeing weighting tree (Osberg & Sharpe, 2002) ............ 32!
Figure 7: Relationship between forest degradation indicator scores and annual forest
loss. Points from real-world dataset used in the indicator. ............................... 36!
Figure 8: Relationship between carbon footprint indicator scores and annual forest
loss. ................................................................................................................... 38!
Figure 9: GDP and Carbon Footprint (2011 data). .............................................................. 39!
Figure 10: Relationship between low-carbon energy generation indicator scores and
low-carbon energy generation, including for export. ....................................... 40!
Figure 11: Calculating Adjusted Net Savings (World Bank, 2006). ................................... 42!
Figure 12: Relationship between ANS indicator score and ANS. ....................................... 43!
Figure 13: Relationship between current account balance indicator scores and current
account balance. ................................................................................................ 44!
Figure 14: How the Gini Index is calculated. ...................................................................... 46!
Figure 15: Relationship between wealth inequality indicator scores and wealth-Gini
coefficient. ........................................................................................................ 47!
Figure 16: Relationship between pupil-teacher ratio indicator score and pupil-teacher
ratio. .................................................................................................................. 49!
Figure 17: Relationship between fertility rate indicator and adjusted fertility rate. ............ 51!
Figure 18: Log-log relationship between child mortality and GDP/c in 2012. ................... 53!
Figure 19: Choropleth map of index score. ......................................................................... 54
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List of Tables
Table 1: Definitions and groupings of values used to partition the CFA .............................. 6!
Table 2: CFA Goodness of Fit Indices. ................................................................................. 7!
Table 3: Means, standard error and standardised regression weights of value items on
their latent values.. .............................................................................................. 8!
Table 4: Correlations between values... ............................................................................... 10!
Table 5: Definitions and groupings of values (Schwartz et al., 2012). ............................... 15!
Table 6: Predicted relationships between values and CFC. ................................................ 16!
Table 7: Partial correlations between values and CFC, controlling for age, gender and
parenthood. ....................................................................................................... 20!
Table 8: Bivariate correlations between values. .................................................................. 21!
Table 9: Equation, definition and data source for net forest degradation indicator. ........... 35!
Table 10: Equation, definition and data source for consumption-based carbon
footprint indicator. ............................................................................................ 37!
Table 11: Equation, definition and data source for low-carbon energy use indicator. ........ 40!
Table 12: Equation, definition and data source for Adjusted Net Savings indicator. ......... 42!
Table 13: Equation, definition and data source for current account balance indicator. ...... 44!
Table 14: Equation, definition and data source for wealth inequality indicator. ................ 46!
Table 15: Equation, definition and data source for primary pupil-teacher indicator. ......... 48!
Table 16: Equation, definition and data source for fertility rate indicator. ......................... 50!
Table 17: Equation, definition and data source for child mortality indicator. .................... 52!
Table 19: Selected mean index scores and ranges of different groups of countries. ........... 55!
Table 19: Descriptive statistics of indicators and index. Deciles are determined based
on final index score, not indicator score. .......................................................... 56!
Table 20: Bivariate correlations (Spearman’s !) of indicators, averages and selected
variables.. .......................................................................................................... 56!

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Acknowledgements
This thesis would not have been possible without the advice, support and academic
solidarity of many people. My advisors, Ragna, Brynhildur and "röstur, have given many
helpful comments on revisions and ensured that I avoided vague concepts and murky
writing. Shalom Schwartz and Jan Cieciuch helped with understanding factor analysis and
multidimensional scaling. My flatmates, Kalli and Tinna, ensured that I ate occasionally
and spoke to someone at least once per day, and Beth and Bec gave me what every student
adrift in new subjects needs most – company and conversation and camaraderie in trying to
understand the world.
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