A number of countries are starting to do this. India, for instance, where we both work advising the government, is developing an Ease of Living Index, which measures quality of life, economic ability and sustainability. When our measures of development go beyond an inimical fixation towards higher production, our policy interventions will become more aligned with the aspects of life that citizens truly value, and society will be better served.
But before we attempt to improve upon the concept of GDP, it is instructive to understand its roots. Like many of the ubiquitous inventions that surround us, the modern conception of GDP was a product of war. While Simon Kuznets is often credited with the invention of GDP since he attempted to estimate the national income of the United States in to understand the full extent of the Great Depression , the modern definition of GDP was developed by John Maynard Keynes during the second world war.
In , one year into the war with Germany, Keynes, who was working in the UK Treasury, published an essay complaining about the inadequacy of economic statistics to calculate what the British economy could produce with the available resources. According to him, the estimate of national income should be the sum of private consumption, investment and government spending.
It continues to this day. But a measure created to assess wartime production capabilities of a nation has obvious drawbacks in peacetime. For one, GDP by definition is an aggregate measure that includes the value of goods and services produced in an economy over a certain period of time.
There is no scope for the positive or negative effects created in the process of production and development. For example, GDP takes a positive count of the cars we produce but does not account for the emissions they generate; it adds the value of the sugar-laced beverages we sell but fails to subtract the health problems they cause; it includes the value of building new cities but does not discount for the vital forests they replace. Environmental degradation is a significant externality that the measure of GDP has failed to reflect.
Modern economies need a better measure of welfare that takes these externalities into account to obtain a truer reflection of development. Broadening the scope of assessment to include externalities would help in creating a policy focus on addressing them. To create one figure representing quality of life, these different factors must be weighted according to importance.
This is problematic because different individuals derive wellbeing from the same resources in different ways and capacities [Stiglitz ], and there may be differing opinions as to what role a government or society should play in influencing these factors [Cole : 24 ].
Although the issue of the subjectivity of determinants of quality of life is an important one that warrants serious consideration, this only functions as a weak argument for the use of GDP per capita because, as was shown in previous sections of this paper, GDP and GDP per capita are not as stable as many assume, and are in many ways subjective measures themselves.
To circumvent this issue of subjectivity, multiple figures detailing each factor of quality of life would need to be provided. This leads to another argument for the use of GDP per capita.
The extreme oversimplification of the issue of quality of life behind GDP per capita allows for countries and regions to each be assigned one single figure.
The idea of GDP per capita being a magnet for attention is completely true, but the information it is attracting attention towards is highly misleading. Although accurate alternative measures of quality of life might not have the same immediate draw, providing misleading information in their stead is not a commendable solution. Having identified the main drawbacks of using GDP per capita as a measure of quality of life, as well as the strengths that have allowed it to remain as the central measure of quality of life, many alternative measures have been put forward.
This section will evaluate three of the most prominent and promising proposed alternatives. Synthetic indicators have the longest history of any of the proposed alternative measures of quality of life and have thus gained the most traction. They are indices made up of a collection of proxy variables that each aim to contribute to the capture of one aspect or determinant of quality of life [Stiglitz ].
HDI uses GDP per capita alongside indicators of literacy, average life expectancy, and more to create one index, allowing for comparisons of quality of life at the national and regional level [Harvie : ]. MFQLI is an index consisting of a fuzzy set of determinants of quality of life that combine into one index. Synthetic indicators represent a practical solution for more accurately representing quality of life. Detailed data directly conveying factors of quality of life can be difficult to attain in developing countries, so synthetic indicators instead use proxy variables, for which data is easier to attain, in an attempt to capture these factors consistently across all countries.
In this way synthetic indicators are a significant step in the right direction, but they are not without their own drawbacks. Proxy indicators represent a practical solution to a difficult problem, but they also create an opportunity for error. Since proxy indicators indirectly represent factors of quality of life, it is possible that some of them could not be as representative of the determinants they aim to capture as they are currently believed to be [Fleurbaey : ].
Although, especially in the case of HDI, these indicators are thoroughly studied, the method of using proxy variables still represents a source of error that can damage credibility. In addition to this, synthetic indicators have weights for the importance of different determinants of quality of life built into them, which becomes an issue when considering the subjectivity of the importance of different determinants, as detailed in the previous section. However, although synthetic indicators are imperfect, with our current state of technology and data collection ability, they remain an important and useful tool for assessing quality of life, and showing that progress beyond GDP per capita can be achieved [Fleurbaey : ].
An approach to measurement that aims to avoid building a measure on set principles, dictating what influences a high standard of living across a population of individuals with different preferences, is the capability approach.
The capability approach focuses on the capability individuals within a population have to pursue as wide an array as possible of different actions or functions [Stiglitz ]. For example, rather than measuring the degree of participation in politics within a country, the capability approach would focus on measuring the factors that give a person the option to participate in politics, such as education or literacy [Stiglitz ].
In operation, this approach aims to find a set of vectors of opportunities offered to individuals in order to maximize capabilities as a means of bolstering quality of life [Fleurbaey : ]. The capability approach represents a commendably original and forward-thinking way of assessing quality of life, but stands to improve in a number of ways. First, capabilities are subject to outside influence which can make them difficult to accurately measure.
For example, two parents may individually have a high degree of capability to pursue a career, however due to personal responsibility, they may jointly feel that one of them must sacrifice their career to personally raise their child [Fleurbaey : ].
Due to the complicated and interconnected nature of capabilities, they can generally be difficult to measure with current systems and technology, which would make building an index or measurement around them difficult.
Additionally, although most proponents of the capability approach have not advocated for this, if combined into one index, this approach would meet the same pitfalls as the synthetic index if the subjectivity of factors of quality of life is not allowed for. The Adjusted GDP approach attempts to operate within this framework by creating a system to add or deduct from GDP based on factors influencing quality of life.
For example, one such system might take the final figure for GDP and subtract values based on pollution or environmental damage, inequality, health, etc. If gross values are still used, the same issues of not accounting for depreciation of capital and the transnational movement of profits will arise [Stiglitz ].
In addition, after taking this net measure and adding and deducting determinants of quality of life, a median must be used to represent the individual in a population rather than a mean, otherwise this adjusted GDP could be just as misrepresentative as the original GDP per capita.
Although creating such a measure would most likely provide a more accurate picture of quality of life, it would be far from perfect. Regardless of whether proper care is taken to use net instead of gross measures and medians instead of means, measuring in solely monetary terms leads to many of the original pitfalls of GDP and GDP per capita. This adjusted GDP would still have trouble valuing aspects of life that are not priced [Smith : ].
The prices of goods such as health care and child care are not always immediately clear and thus lead to difficulty when deciding how to value them when adding or subtracting from GDP [Stiglitz ]. In addition to this, an adjusted GDP should account for depreciation and destruction of capital; however since the effects of such losses especially environmental can be far reaching, reducing prospects for consumption of future generations, the true total value lost in depreciation can be extremely difficult to accurately calculate [Fleurbaey : ].
How can this be fixed? Catherine Rampell provides a nice summary of the alternative measures that have been proposed, including China's " green GDP ," which attempts to adjust for environmental factors; the OECD's " GDP alternatives ," which adjust for leisure; the " Index of Sustainable Economic Welfare ," which accounts for both pollution costs and the distribution of income; and the " Genuine Progress Indicator ," which "adjusts for factors such as income distribution, adds factors such as the value of household and volunteer work, and subtracts factors such as the costs of crime and pollution.
However, none of these alternatives deal with the main problem discussed in Davos -- how to measure the full impact of technology on our lives. The problem is that GDP assigns a zero value to goods with a zero price, but those goods aren't valued at zero and as they become more prominent, we'll need to find a way of including the benefits they provide in our measures of the standard of living.
None of the measures proposed so far are perfect, and they won't replace the current GDP yardstick anytime soon. But there's still something to be gained from this work. When you hear that your standard of living has gone up, ask yourself what has happened to leisure time -- are you working more or less for the same income? How much of technology's benefits might have been missed -- how often do you use Wikipedia?
And how was the additional GDP distributed across the population -- did it mostly go to the 1 percent?
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