Interdisciplinary research on measuring the progress towards sustainability and well-being (SaW) from different perspectives and in various contexts has developed dramatically over recent decades. This growth in the literature has not only added an enormous number of dimensions to the SaW debate, but the sheer scale of the expansion has challenged researchers to be able to conduct a comprehensive analysis of the available SaW indicators. In this work, we have proposed a hybrid method comprised of sophisticated scientometric analysis to summarise scientific developments in the massive text corpus of the SaW literature in conjunction with a more traditional literature review to categorise the 'fuzzy' details that remain. Scientometric analysis highlights that the developed OECD countries play a vital role in the development and applications of SaW indicators and we describe key developments in this regard via a range of graphical approaches. Using an extensive collection of existing SaW indicators, the analysis is then summarised in a matrix of ranked indicators which serve as a powerful tool to compare, contrast, filter and select indicators for SaW assessment with minimum redundancies between indicators. The approach undertaken in this study is intended to be flexible and can be extended and applied to other fields of research.

The key aims of this paper are to: i) to extend the World Bank's (WB) measure of Genuine Savings (GS) for New Zealand by using a longer time-series of data, 1950-2015; ii) improve GS estimates for New Zealand by adding additional dimensions to GS i.e. forestry; iii) investigate the relationship between several GS measures and the discounted values of GDP per capita and consumption per capita, used to proxy well-being; iv) test a series of hypotheses which relate GS to the change in future well-being using the framework proposed by (Ferreira, Hamilton, & Vincent, 2008) and v) investigate the effects of a growing population on the availability of future capital stocks by considering the consequences of 'wealth-dilution' as defined by Ferreira, et. al., (2008). The paper makes a contribution to the literature on GS, particularly in the context of New Zealand, by considering patterns of GS and well-being over a longer time span of data than has been previously used and adds to a relatively small, but growing literature on tests of GS using long-or relatively long-time series data (see e.g. Greasley,

In this paper, the electricity shortage in Pakistan is addressed through an examination of data over the period 1971-2010 with a time-series analysis. The novelty of the study lies in characterizing energy shortages using both an index comprising the demands for electricity, gas and oil, and information on the public electricity supply. This index allows for a simple empirical approach where energy shortages cannot be directly measured as data. The main findings are as follows: first, end consumers adjust their energy demands to prices only in the long run; second, the underutilization of installed power-generation capacity encourages fossil fuel consumption for private electricity; third, an uninterrupted electricity supply could be attained by regulating private electricity generation; and fourth, the relative demand for electricity increases with an increase in real income and then starts to decrease as income increases beyond the threshold of $1,127. Overall, the results of the study suggest that the price adjustment tactics adopted by the Government of Pakistan are not an effective policy to deal with power shortages in the short run. Rather, the Government should focus on improving the utilization rate of installed power plants and on rechannelling the use of oil and gas for public electricity generation. Otherwise, energy shortages will worsen with economic growth in Pakistan.

We analyse the relationship between subjective wellbeing (SWB) and the World Bank’s measure of a country’s economic sustainability, adjusted net savings (ANS). We model SWB at individual level and at aggregated group level as a function of past ANS levels, after controlling for a country’s initial levels of SWB. The empirical models utilise World Values Surveys (WVS) data for self-reported life-satisfaction (our proxy for SWB). Our results show that ANS is negatively associated with future SWB outcomes over relatively short timespans (10-15 years) but this relationship is neutralised, or even reversed, for a longer timespan (20 years). The results demonstrate an important challenge in political economy. Governments that choose to save less in the short term may be able to spend more on the well-being of the current generation (i.e. current voters) but they diminish the reserves available to improve future generations’ wellbeing. At a more technical level, our results reinforce the concept that ANS is a useful sustainability indicator for infinite (or at least very long) time horizons, but it is not a good indicator of well-being developments over short time horizons.

We analyse the relationship between subjective wellbeing (SWB) and the World Bank's measure of a country's economic sustainability, adjusted net savings (ANS). We model SWB at individual level and at aggregated group level as a function of past ANS levels, after controlling for a country's initial levels of SWB. The empirical models utilise World Values Surveys (WVS) data for self-reported life-satisfaction (our proxy for SWB). Our results show that ANS is negatively associated with future SWB outcomes over relatively short timespans (10-15 years) but this relationship is neutralised, or even reversed, for a longer timespan (20 years). The results demonstrate an important challenge in political economy. Governments that choose to save less in the short term may be able to spend more on the well-being of the current generation (i.e. current voters) but they diminish the reserves available to improve future generations' wellbeing. At a more technical level, our results reinforce the concept that ANS is a useful sustainability indicator for infinite (or at least very long) time horizons, but it is not a good indicator of well-being developments over short time horizons.