Productivity, equity, and sustainability: A trilemma for contemporary human development?

ABSTRACT

Productivity, equity and sustainability are regarded as ‘essential components’ in the human development paradigm. They reflect structural aspects of an economic system and create the material conditions for widespread human development and wellbeing. Nevertheless, the consistency among these principles is significantly questioned in the economic literature, depicting a potential ‘trilemma’ for contemporary human development. This paper analyses the ability of different economies to consistently advance productivity, equity, and sustainability. A new composite indicator – the Human Development Structural Consistency (HDSC) index – is introduced to measure the integrated performance in productivity, equity and sustainability of 66 economies from 2006 to 2019. The analysis shows a general progressive improvement in the ability of economies to advance the three structural components of human development consistently, although the three measures continue to appear incompatible with each other, whereby the process of economic growth is still associated with rising environmental degradation and a weak contrast to inequalities. This paper discusses the possible policy solutions to this ‘trilemma’, such as the structural changes necessary to ensure that improvements in productivity are accompanied by rising equity, sustainability, and effective human wellbeing.

KEYWORDS:

• productivity
• equity
• sustainability
• human development
• industrial policy
• structural change
• economic growth
• leisure time
• relational goods
• composite indicators

JEL CLASSIFICATIONS:

• L50
• O10
• O25
• O33
• O44
• Q50

Acknowledgments

I would like to express my gratitude to the anonymous reviewers, for having provided very useful inputs and insights.

Disclosure statement

No potential conflict of interest was reported by the author.

Notes

1. In Haq (1995), empowerment is also mentioned as a fourth ‘essential component’ of the human development paradigm. In this work, we focus in particular on productivity, equity, and sustainability inasmuch as factors that can be more directly observable as features of the economic structure of a country (rather than as effective abilities of people or groups), aiming at drawing from our analysis indications on changes in the conformation of economic structure that are suitable for promoting human development.

2. There is no generalisable correspondence between the ‘material conditions’ of people (e.g. the economic resources available to individuals) and the level of human development and capabilities they reach. While material goods do not vary their characteristics according to the person who possesses them, what an individual can be or do with such a material endowment depends strictly on his or her personal characteristics, goals, aspirations, knowledge, skills, etc. Thus, the actual impact of economic resources on an individual’s human development depends on the so-called ‘conversion factors’, which allow people to effectively convert the available goods and services into actual well-being and opportunities (see, e.g. Nambiar 2013). For further discussions on human development, the capability approach and its connections with social and collective dynamics, see, e.g. Biggeri and Ferrannini (2014), Clark, Biggeri, and Frediani (2019), Deneulin and McGregor (2010), Evans (2002), Ferrannini et al. (2021), Ibrahim (2006), and Tassinari (2023).

3. On the notion of structural change, see, in particular, Bianchi and Labory (2019) and Cardinale and Scazzieri (2018).

4. After the selection of the 66 countries, some values were missing for the Gini index variable. In these cases, the imputation of the missing values was carried out by calculating the average between the values of the previous and following year available for the country under consideration or by using the value of the adjacent year (when values related to the previous or subsequent years were not available).

5. In this type of consistency, the ‘noncompensation’ of improvements with worsenings depends essentially on the kind of correlation between the variables of the index (e.g. the consistency grows when the decoupling between economic growth and environmental degradation is increasing). This ‘noncompensation’ must not be confused with the methodological issue of avoiding compensation among variables in calculating the composite indicators. In this latter case, the noncompensatory calculation methods have the objective of avoiding excessively high values in one variable (e.g. outliers) compensating for low values of other variables, reporting a distorted value of the index (e.g. the per capita GDP is so high as to compensate for the low equity). Compensatory methods of calculating composite indicators can lead to policy distortions because they can incentivise the concentration of policy efforts on some specific components at the expense of others to boost the index’s overall performance. To avoid this methodological distortion, we will adopt the geometric mean as a typical noncompensatory aggregation procedure (e.g. OECD 2008, 105).

6. See, for instance, Di Tommaso et al. (2020); Galambos (1983); Hrebenar (1997); Jessop (1990); Kalecki (1976); Lustig (1982); Tassinari (2019), Tassinari (2021).

7. The idea that economic growth should not be regarded as the main goal of a society is not new at all in the history of economic thought (e.g. Macekura 2020), and it has inspired the development of various alternative schools of thought about economic growth (EEA 2020), including ‘Degrowth’ (Demaria et al. 2013), ‘Postgrowth’ (Wiedmann et al. 2020), and ‘Doughnut economics’ (Raworth 2017).

8. In current research, well-being can be understood from two different perspectives. While the hedonic approach defines well-being as pleasure attainment and pain avoidance (often evaluated in terms of subjective happiness or subjective well-being), the eudaimonic approach defines well-being in terms of quality of life achieved by fulfilling one’s potential. Interpersonal relationships may be deemed relevant in well-being from both perspectives (e.g. Deci and Ryan 2001).

9. More generally, the relationships between economic growth and human wellbeing have been framed, for instance, by the so-called ‘paradox of happiness’ (Easterlin 1974; Easterlin et al. 2010) and related literature (e.g. Binswanger 2006; Clark, Frijters, and Shields 2008; Stevenson and Wolfers 2008).

10. The method used to evaluate the robustness of the ranking (i.e. the uncertainty analysis) is usually applied both to the selection of the weighting scheme and the selection of the aggregation rules. In our case, however, the human development paradigm tends to assign equal relevance to productivity, equity, and sustainability, which deserve to be consistently promoted (Haq 1995). As explained above, to evaluate this consistency, we have decided to not vary the weight assigned to the variables, attributing them the same relevance. The equal weight attributed to the different dimensions of the composite indicators is a typical feature in studies adopting the HDI (e.g. Klugman, Rodríguez, and Choi 2011) and the SDGs (e.g. Biggeri et al. 2019, 2023; Sachs et al. 2020). At any rate, we provide an evaluation of the robustness of the analysis by assessing the uncertainty associated with the ranking with respect to the change in the combination functions.

11. The uncertainty of the result when using different combining functions is a rather common issue in analyses in which composite indicators are adopted. However, the advantage of using different combining functions is to make this kind of uncertainty transparent, allowing us to show the possible spaces to manipulate the indices’ results. In this respect, the uncertainty generated from using different combining functions does not generally compromise the use of the results, as confirmed in a number of studies adopting this methodology to analyse the uncertainty generated from using different aggregating formulas (see, e.g. Assiri et al. 2020; Di Tommaso et al. 2017, 2020).

Additional information

Funding

This work has been funded by the European Union - NextGenerationEU under the Italian Ministry of University and Research (MUR) National Innovation Ecosystem grant ECS00000041 - VITALITY - CUP D83C22000710005.