Can hairdressers be better economic forecasters than economists?
By Cheryl Yau, Hwa Chong Insitution
Can hairdressers be better economic forecasters than economists; to the uninitiated, this may seem like an irrelevant question: rationally speaking, of course the trained ‘professional’, the economist, will be in better stead to forecast economic conditions. However, this obsession and dependence on rationality is precisely the Achilles heel of the subject. When economists assume rationality (and with it, perfect information) to build their crystal balls, this is clearly not entirely reliable – we don’t always know what is the cheapest option around, governments don’t always act in the best interest of their people and people rack up credit card bills to pay for things they cannot afford (and perhaps from a more philosophical point of view, what is “rational”?). Humans are ultimately feeling, impulsive (and perhaps occasionally rational) creatures, incapable of being modeled or predicted.
At the Princeton commencement in 2013, Ben Bernake, ex-Chairman of the Federal Reserve, delivered a humorous but thoughtful speech, noting that “economics is a highly sophisticated field of thought that is superb at explaining to policymakers precisely why the choices they made in the past were wrong. About the future, not so much” Even if we can make provisions for assumptions and sources of market failure (as most statistical models do), Bernake surfaces the complexity of variables involved and hence the limited predictive ability of economics. We’ve seen this in economic history: no one predicted the dawn of the Asian Financial Crisis (AFC), but today, it has been explained as ‘a crisis waiting to happen’. When Mahathir moved in to impose capital control in the wake of the crisis, he was lambasted by the International Monetary Fund (IMF) and other leading economists. The same organizations and individuals later congratulated Mahathir and explained the success of his policy in stabilizing speculative activity in the county. In the same vein, while my Economics Tutor, who worked as an economic forecaster at a local think tank, once predicted that Singapore would suffer its first negative quarterly growth in years (which did happen), he was asked to adjust one of the variables such that it would reflect a soft landing which was congruent with the results of other reputable institutions. This reflects the arbitrary process by which the weight of individual variables is decided and together with the above examples, show the volume and interconnectedness of variables that make it near impossible to produce any all-encompassing prediction.
Economic forecasting is made all the more complex due to the presence of unpredictable and even non- economic variables, ranging from a new law mandating compulsory savings (like the Central Provident Fund system in Singapore), to the fanatical whims of leaders (demonetization carried out by Ne Win) and an unfortunate natural disaster. This is exacerbated by increasing globalization and the perceived or actual interconnectedness of national economies, which means that economists not only have to grapple with the overwhelming number of variables within their countries, but also be sensitive and attuned to global happenings. For instance, a natural disaster in one country and the subsequent devastation of part of the country’s economy will definitely have an impact on other countries, her trade partners in particular. Returning to the example of the AFC, even if there was a small dissident voice about growing asset-price inflation and unregulated speculative activity in Thailand, no economist projected for Singapore, with its robust growth rates and sound financial system, to experience a hard landing in 1997. This case highlights two points: the irrationality of stakeholders and the impact of globalization. The devaluation of the baht in Thailand led to a plummet in investor confidence and hence, rapid withdrawal of capital from the entire region as the economies of other Southeast Asia were instinctively seen as linked to the Thai economy (globalization). However, this ‘instinctive’ reaction may not have been rational at all as investors were merely responding to the ‘herd mentality’ and certain countries, like Singapore, was later found to be structurally sound. While any forecast premised in rationality and economic data from Singapore would have projected for continued growth, we see that this is incongruent with what actually happened due to irrationality, unpredictability and globalization.
If mankind, complex, irrational and unpredictable, is doomed to be a species incapable of any mapping, how are hairdressers able to fare any better in forecasting economic conditions? The answer may lie in a healthy dose of realism. Hairdressers are, unsurprisingly, able to obtain both quantitative (through profit levels, customer statistics) and qualitative (through casual chats) data about the state of the economy and more importantly, expectations of the state of the economy which will be useful for any prediction. The limits the number of assumptions that a hairdresser has to make, and allows for a more accurate assessment of the real economic situation. This is particularly so as hairdressing services can generally be classified as a normal good, where the demand for hairdressing varies more than proportionately to changes in income (which is in turn an important indicator of economic health). Even lower-end hairdressing services, classified as inferior goods, can provide insight into income levels as demand would move in the inverse direction.
However, the predictive power of a hairdresser is ultimately limited, not least of which by its geographical region and customer type. For instance, if the hairdresser prospers within a region of the country which enjoys the benefits of development, it may not be apposite to conclude that the entire country is doing economically well. Similarly, if the hairdresser mainly serves the rich and wealthy, it may be seen as a ‘necessity’, and hence be income inelastic and serve as a poor indicator for fluctuations in income. Furthermore, income is just one of the many determinants for the demand for hairdressing services. Demand may be affected by many possible factors, for instance if there has been changes in quality of the service, or if a rival company just opened in the vicinity. Hence, the analysis of demand trends of a singular hairdressing shop may be insufficient to make any significant predictions about the larger economy. In a sense, hairdressers do not face the problem of ‘complexity’ as other variables are not addressed altogether, while their ‘forecasts’ are equally susceptible to unpredictable variables and the effects of globalization.
In the larger context of the question, the strength of the hairdressing business should be seen as one of the many indicators of economic health (which a good economists must synthesis alongside many other indicators); how representative this indicator can be is affected by the aforementioned circumstances. At its best, we may find it to be astoundingly accurate in its forecast of a specific region, much more so than that of an economist who has to grapple with different sets of data, time lags and data deception, but it is by no means sufficient in making bold statements about the larger national or global economy.
Interestingly, the economist may have an edge over the hairdresser in economic forecast simply because he/she is an economist. The idea of a self-fulfilling prophecy posits that when people believe that something will happen, they act in accordance with that expectation, eventually contributing to the occurrence of the event or phenomena. Through their forecasts, economists (particularly respected and influential individuals) imbue expectations of the economy into various stakeholders, potentially setting a self fulfilling prophecy in motion. For instance, the Eurozone debt crisis snowballed as investor confidence dipped and sovereign credit default swap prices rose, putting increasing pressure on Eurozone governments. Some argue that the drop in investor confidence can in turn by attributed to gloomy forecasts and stern revaluations about the state of the Europe economy, particularly as the problem of a budget deficit had already existed for a relatively long time prior to the crisis. If we agree with the self-fulfilling prophecy theory, the strength of an economist’s forecast lies not in accurately identifying cause and effect, but interestingly, in being the cause itself to a certain extent.
Ultimately, in economic forecasting, the economists and hairdressers both build models, models with very different inputs, strengths and weaknesses. An economist’s model is premised upon many assumptions, carries the weight of interconnected and complex variables, and built upon availability and reliability of statistics while the hairdresser’s model is simpler, more grounded but also likely to be less representative. A straight answer to the question would be to say that hairdressers can be better forecasters in certain circumstances, but they may not be in other circumstances; an answer that feeds into a rather cynical view about forecasting as a whole. To me, forecasting is like a game of poker: there may be some skill and manipulation involved, but it really boils down to luck and circumstances which cannot be predicted or controlled. From another perspective, both models are inept in capturing the nuances and complexity of society; it is simply a matter of how well one model happens to adhere to ever-changing and unpredictable circumstances. While the essay does posit that greater simplicity and linearity (the hairdresser) would more likely triumph attempted holistic manipulation (the economist) in forecasts pertaining to a specific region, there is no real fixed formula and circumstances throw out arbitrary winners between the two. As a Chinese saying goes, “chance contrives better than we ourselves”.