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Where economic analysts are getting it wrong

Chris Chenga

It is important to make a distinction between which policymakers are likely to make a potent impact on people’s welfare and the ones who are merely generically inclined on data and statistics. The latter offer what has become the predominant ineffectual growth that are causing civil unrest world over. Informed by data and statistics, there is a positive narrative in global governance institutions that the overcast set forth by the last global recession is making way for brighter days, supposedly to be credited to diligent policy decisions. Yet, materially citizens in many regions feel excluded from the sun rays and warm vibes, resulting in palpable civil discontent. Why is there this disconnect between policymakers and citizens?

Perhaps the challenge citizens should start to put forward to their governments, is for policymakers to shift economic mindsets from being obedient to standardised data and statistics – which are often confined within generic benchmarks such as GDP growth, employment figures, and capacity utilisa­tion – towards mindsets that pursue material, po­tent, improved welfare of citizens. Of course this is not to render data and statistics as futile or ir­relevant, but to highlight that there is a growing disparity between these figures from the material welfare of citizens.

The cause of this increasing disparity is the ab­sence of appreciation for the structural reality of economies. Data and statistics have become stand­ardised, interpreted within themselves, without an appreciation and context of the structural reality of the economies they intend to narrate. Structural omission is the cause of disconnect between data and statistics and many citizens’ material welfare.

For instance, economic growth rates ranging from 5 to 7 percent have become generically in­terpreted as impressive for developing economies. Opportunistically, policymakers in economies showing such data and stats have adopted such benchmarks to demand commendable appraisal of their policy decisions. Materially, however, in most cases of developing economies such rates of 5 to 7 percent are structurally inadequate for policymak­ers who truly perceive policy as a means to bring about potent impact on citizens’ welfare. Consider Zimbabwe’s general acceptance of GDP growth rate targets set around 5 to 7 percent. Multiple political party manifestos have boasted ability to deliver such growth rates if elected in elections. But reflect on the fact that according to the IMF, Zimbabwe’s GDP growth rates between 2010 and 2013 averaged just over 10 percent.

The economy has not structurally changed since then. Much of the growth in that time frame is correctly attributed to mere “confidence”, and not to any significant structural differences between then and now. This implies that even without any structural adjustments, the promised 5 to 7 percent growth rates are well beneath the economy’s poten­tial as it is today; let alone with actual structural adjustments that are needed going ahead.

Thus, any credible economic analyst must already un­derstand that the promises of 5 to 7 percent GDP growth rates over the next five years are structur­ally omitting. It seems all prospective policymak­ers lack any structural astuteness to the economy’s inadequacies. If whichever elected party does bring about such 5 to 7 percent benchmarks, many citi­zens’ welfare will not materially change, and we will end up at the juncture as aforementioned whereby data and statistics tells of good times but citizens feeling left out. But fault does not end at active and prospective policymakers. Many eco­nomic analysts are shifting their observations of Zimbabwe’s economy; as supposedly reflected by a well performing stock market, improved corporate profits, and capacity utilisation. But what these analysts miss is these are exactly the impotencies of a structurally flawed economy.

Consider the often referenced increase is capac­ity utilisation for instance. Structurally industry is in serious need of a readjustment that enhances productivity, and capacity utilisation isn’t the cor­rect benchmark. There is a technical aspect missed by many economic analysts here; productivity does not necessarily reflect in more output from a factory or greater use of that factory’s machinery as widely assumed in our discourse.

Productivity means that per output unit by a worker, the real value added by that worker results in an increase in that worker’s real wages. That is not what is going on in industry. Industry instead has merely started churning more output from idle machinery with­out increasing the real value added by workers, hence GDP will show an increase, but for work­ers this growth will not reflect in their wage and income welfare. More simply, increased capacity utilisation is structurally detached from improved welfare.

Global institutions are also at fault of the same structural omissions. A few

weeks ago, the Inter­national Labour Organisation (ILO) backed Zim­Stats’ data that Zimbabwe has an employment rate of 93%. Whether one chooses to interpret this figure as representative of satisfactory job creation is open to subjective posturing; but what is objec­tive is that these figures are structurally divorced from people’s welfare.

It is a precise example of how data and statistics cause ineffectual policy justification. Over time people in Zimbabwe have found means of sustenance which is being defined as jobs, matching employment criteria of the ILO. But, these jobs do not provide any gainful income. In fact, most incomes are so low workers within this 93% employment rate that workers are in a perpetually unforgiving poverty cycle; where they earn an income which cannot supersede their standard of living.

This employment as defined by the ILO does not offer medical, retirement or insurance benefits and entitlements that make for a productive social safety net. So indeed Zimba­bwe may have an employment rate of 93%, but that data and statistics omits the fact that this em­ployment is representation of many citizens being within a poverty trap and marginalised from civil protections provided by a productive economy.

Zimbabwe needs to awaken to the flaws of struc­tural omission in interpreting data and statistics. It is a disservice to citizens to accept generic notions of data and statistics. Unfortunately, diverse stake­holders such as policymakers, economic analysts and some global institutions within Zimbabwe re­main susceptible to this structural omission.

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