On March 8, 2019, South Africa’s Minister of Finance posted a comment on Twitter. The comment had a thesis-like title: “Of Economists, Graphs and Econometric Equations”. And then he wrote, “one of the hard lessons learnt over the many years in policy making is not to use data, graphs and econometric equations at policy meetings to argue economic policy positions. It can be nasty and unhelpful.” A heated debate ensued.
By Alfred M. Mthimkhulu
As a teacher of econometrics and its reluctant user in my southern Africa backyard, I empathise with the minister’s comment. I expected the debate but still wish I knew what had prompted him to post the comment. It is an unusual comment not just from a minister of finance but a former governor of a leading central bank in the continent.
We know that central banks globally are the hubs of such analyses hence the strangeness of the comment. Most of us will never know what triggered it. What we know is that four days later, he and members of his team were at the Meikles Hotel in Harare. They were discussing with their local counterparts how South Africa could help in the economic recovery of Zimbabwe.
A lot was going on in the policy-making front in that first quarter on 2019. The Government was a few months old but seemed to be hitting the ground running.
The Zimbabwe National Industrial Development Policy (2019-2023) was already being spoken of. A few months earlier, the National Critical Skills Audit Report had been published. Currency reform was gathering pace with major announcements around the corner.
We discussed these and other policy matters even in this column. With hindsight we should have paid closer attention to the African Development Bank Economic Report on Zimbabwe of 2018 titled “Building a new Zimbabwe: targeted policies for growth and job creation.” It is available online for us to read at will.
The Report was produced on the request of the Government of Zimbabwe. The bank was asked “to urgently prepare an economic report on the country to support renewal and transformation”. Studied carefully, it sheds a lot of light for us on the economic policy mind-set of this Government if not now then in those early months of its existence.
In the Foreword, the Report observes that “the Industrial Revolution was primarily the result of ideas”. It notes that in that era “people and business leaders found innovative ways of adopting technology and making it commercially viable so that it could boost productivity”.
It further notes that some of the innovations were idle for years until “some wise and very practical people” came along “to design the institutions that would create appropriate conditions for their broader use by firms and households”.
A number of articles I have shared in these pages have deliberated on several industrialists and bankers at the forefront of the Industrial Revolution. The goal in digging-up that history has not been to plead for a reincarnation in Zimbabwe of nineteenth century men of North America and Europe or late twentieth century entrepreneurs from southeast Asia. Rather, it has been to help us reflect on alternative pathways to our grand prosperity desires.
The message from most of those yesteryear stories is that as entrepreneurs rolled out innovative products and ideas fitting their circumstances, their economies leaped to an unprecedented growth trajectory. If we try to mimic them, we will fail.
In fact, the AfDB Report observes that many developing countries have failed trying to play catch-up with developed countries. “In the last half-century” the Report notes, “only 28 countries have closed the income gap with industrial countries by 10 percent or more — only 12 of them were non-European and non-resource-based countries”. It is, in any case, impossible in definitional terms to win in a game called catch-up.
Chapter 3 of the Report titled “Investment in Zimbabwe: alternative growth scenarios to 2030” is a must-read. It discusses how the Bank used an econometrics-driven method acronymed SDGSIM to come up with eight scenarios of Zimbabwe from 2019 to 2030.
The bank’s economists have what they called the “base scenario” which is the economy in 2018 configured from 2016 figures (because 2018 was still in session). From that base scenario they then used the SDGSIM model to come up with the seven scenarios of 2019 to 2030. We can discuss the scenarios some other time.
For now, let us consider the adequacy of the method in providing a road map to our futures, Vision 2030. In other words, is the econometric analysis underpinning the scenarios reasonable?
This is the kind of question policy makers such as South Africa’s Minister of Finance worry about — not because the analysis is shallow or wrong but because it is pitched as a primary input than a supplementary one in a policy deliberation. No forecasting method is perfect and for that reason it is important to share the shortcomings of any method before expending energies on its results.
With regard to the analysis by the economists at the AfDB, their method assumed that the economy of Zimbabwe would remain structurally the same in terms of the types of industries or sectors. This assumption is also implicit in the National Industrial Development Policy.
This is a problem. Why? Because we know that economies that leapfrog do so because they deliberately and substantially alter their industrial structure and the local skills-set. The “business-as-usual” base scenario AfDB shared which benchmarked other scenarios did not consider necessary shifts in the structure of the economy.
We need a lot more alternative methods for mapping our futures, methods that force us to start the analysis on a clean page. With a clean page we can, for instance, factor in the increasing ravages of climate change than call them exogenous shocks.
As such, mapping futures requires a broad set of expertise including the seemingly derided ones in Zimbabwe such as Anthropology or Sociology for great could be the insights from these fields on the management of far-reaching sociocultural changes induced by a series of droughts.
As economists, we study how markets co-ordinate themselves and allocate scarce resources. It could be time we played an even more subservient role to society: that of coordinating other experts and quantifying their outlooks to model our futures.
When gunning for structural change of an economy, a fixation on data from a long established structure can indeed be nasty and unhelpful. There is no greater liberation than stepping out of the equilibrium and realising that there can never be glory in playing catch-up.
Alfred M. Mthimkhulu, Senior Lecturer, Graduate School of Business, NUST, Email: firstname.lastname@example.org, Twitter: @mthimz