This article was written by Michael Morris, one of the creators of the VACI. References to the VACI in this article refer to the 2017 version of the Index.
The Voiceless Animal Cruelty Index (VACI) measures human abuse of farmed animals at the country level. It was devised to encourage debate and challenge citizens worldwide to reduce needless farmed animal suffering. It is a composite measure that tracks suffering from three perspectives: the perpetrators (producers of animal products); the enablers (the consumers) and the facilitators (governments).
In terms of ethical theory, it combines a utilitarian and a virtue ethics stance. The weighted counts of animals killed (producing cruelty) and eaten (consuming cruelty) are about consequences. Sanctioning cruelty, derived from World Animal Protection’s Animal Protection Index, is about collective intent.
Inevitably the weights used to construct and aggregate the three VACI dimensions are judgemental, constrained by data limitations, and subject to revision and challenge. The VACI does however capture vital information relevant to the rights and welfare of farmed animals. This blog seeks to identify relationships between the VACI and country socio-economic indicators.
The Kuznets Conjecture
According to Simon Kuznets (1959), as an economy develops, market forces first increase and then decrease economic inequality. Is a similar phenomenon present in the animal welfare domain just as in some aspects of social and environmental well-being?
Among developed countries, just about every social ill is more prevalent in more unequal societies. Environmental protection, educational achievement and numbers of patents are higher in more equal countries (Wilkinson and Pickett 2009). Similarly, the association between inequality and human health and wellbeing has been found to be associated with levels of trust. People are more trusting in more egalitarian environments, and this improves wellbeing (Rozer et al. 2016).
We already know that more equal societies display lower meat consumption and more regulations protecting animals (Morris 2013). Countries with higher levels of democracy also seem to generate better animal welfare, as measured by the Animal Protection Index (Holst and Martens 2016). A link between the affordability of animal products and their consumption at the individual level has already been established (Gossard and York 2003). What other correlations exist between inequality, democracy and the VACI?
Economic indicators were obtained from World Bank data (2015). The per capita Gross National Income and the Purchasing Power Parity (PPP) were both used.
The Gini coefficient for inequality was obtained from the UN Human Development Index, and is a composite figure for 2001-2015. Two comparisons for the Gini coefficient were run. The first compared the Gini coefficient for all 50 countries of the VACI sample. In the second analysis, only high-income countries were counted, according to the methods of Wilkinson and Pickett (2009).
Measures for freedom were taken from the 2017 Freedom House report, Freedom in the World.
The cruelty indices used for analysis were Producing Cruelty, the two sub-indices of Enabling Cruelty (percentage consumption of animal protein and total number of animals consumed), the Sanctioning Cruelty rank, and the ranked overall VACI. Correlations between each economic indicator and each animal welfare indicator were run on an Excel spreadsheet that fitted linear, quadratic, cubic and quartic curves (MacDonald 2008)1 . The spreadsheet calculated two P values for the first three polynomials. The first one tested the null hypothesis that there was no relationship between the variables. The second (for the quadratic, cubic and quartic) tested the null hypothesis that the true relationship was the lower level polynomial.
So when determining the best relationship, if the first P value for a linear relationship was > 0.05, it was assumed there was no relationship. If the value was 0.05 or less, then the quadratic fit was examined. If the second P value for the quadratic was > 0.05 it was assumed that the best fit was linear. Otherwise, the cubic fit was examined, and the same procedure was followed for this fit and for the quartic.
VACI and income
Analysis using GNP as a dependent variable showed a general increase in both the total number of animals and proportion of animal protein consumed. There was a slight dip with an inflection point at $40K for animal protein consumption, but the general trend was still upwards. Producing cruelty showed no significant trend, and nor did the overall VACI rank. Sanctioning cruelty showed a clear downward trend as wealth increased.
When PPP was used instead of GNP, the trends were clearer. There was a clear increase of animal protein consumption with wealth, though this tapered off in the wealthier countries. There was a cubic Kuznets’ effect for numbers of animals consumed, and for producing cruelty, with consumption and production being highest in countries with a PPP of around $30-35K. Finally there was a linear downward trend for sanctioning cruelty and a significant cubic Kuznets’ effect curve for the VACI index overall, with an inflection at a PPP of about $30K (Fig 1).
There was no significant correlation between inequality, as measured by the Gini coefficient, and any of the VACI indicators, when all the countries were counted. There was an overall increase in equality with an increase in income (both PPP and GNP), though little indication of the original Kuznets effect.
Revealingly, when only the 16 richest countries were included, there was a linear increase in animals consumed, animals slaughtered and sanctioning cruelty with increasing inequality (Fig 2).
The relationship between consuming cruelty and freedom was a quadratic. The more free countries generally consumed more animal products. Sanctioning cruelty declined linearly with increased freedom (Fig 3). There was a positive correlation between freedom and both measures of wealth (PPP and GNP).
When only the wealthier 16 countries were counted, there was no correlation between freedom and any of the ACI indices.
This is the first recorded instance of a Kuznets effect for animal welfare. It appears that increasing wealth increases both producing and consuming cruelty. This tapers off and declines in the wealthiest countries. As some of the country profiles show, this could be due to greater awareness, and more vegetarian options available for wealthy consumers. Vegetarianism is, arguably, for the very poor and the very rich.
Sanctioning cruelty shows a different trend to the other sub-indices, declining in a linear fashion with increasing wealth. This probably reflects the greater legal resources of wealthy countries, and their pre-occupation with seeming to do the right thing in the face of a gruesome reality (Beatson 2009).
The relationship between inequality and animal welfare indices in wealthy countries is aligned with previous findings for animal welfare (Morris 2013) and other social indicators (Wilkinson and Pickett 2009). This is possibly due to better choices, greater awareness higher levels of trust and more political power for activism groups in countries that are both egalitarian and wealthy (Wilkinson and Pickett 2009).
The relationship with animal welfare and freedom showed a surprising result in that consuming cruelty mostly increased with freedom, an association explained by the fact that wealthier countries tend to be freer and consume more animal products.
However, sanctioning cruelty is lower in freer countries. This confirms the finding of Holst and Martens (2016): they found that animal welfare improved with greater democracy. Taken together these associations emphasise once again the ways in which the VACI captures results whereas the API mostly addresses legislative intent.
- The spreadsheet calculated two P values for the first three polynomials. The first one tested the null hypothesis that there was no relationship between the variables. The second (for the quadratic, cubic and quartic) tested the null hypothesis that the true relationship was the lower level polynomial.When determining the best relationship, if the first P value for a linear relationship was > 0.05, it was assumed there was no relationship. If the value was 0.05 or less, then the quadratic fit was examined. If the second P value for the quadratic was > 0.05 it was assumed that the best fit was linear. Otherwise, the cubic fit was examined, and the same procedure was followed for this fit and for the quartic.
The views and opinions expressed in this article are those of the author. Voiceless does not necessarily endorse the views and opinions, nor guarantee the accuracy or completeness of the material provided.
Beatson, P. (2008) Falls the shadow: the animal welfare debate in New Zealand. Oral presentation to the New Zealand Law Commission, 28 August 2008. http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.524.5421&rep=rep1&type=pdf. Accessed July 2017.
Gossard, M. H., & York, R. (2003). Social structural inﬂuences on meat consumption. Human Ecology Review 10, 1–9.
Holst, A., Martens, P. (2016) Determinants of Animal Protection Policy: A Cross-Country Empirical Study. Politics and Animals [S.l.], p. 1 – 14. http://journals.lub.lu.se/ojs/index.php/pa/article/view/15296/14694, accessed July 2017.
Kuznets, S. (1955). Economic growth and income inequality. American Economic Review 45, 1–28.
McDonald, J.H. (2008) Handbook of biological statistics. http://www.biostathandbook.com/HandbookBioStatFirst.pdf, accessed July 2017.
Morris, M.C. (2013) Improved animal welfare is more related to income equality than it is to income. Journal of Applied Animal Welfare Science 16, 272-293.
Rozer, J., Kraaykamp, G., Huijts, T. (2016) National income inequality and self-rated health: the differing impact of individual social trust across 89 countries. European Societies 18, 245-263.
Wilkinson, R and Pickett, K. (2009) The spirit level: why equality is better for everyone. Allen Lane.