Provincial GDP figures rekindle marginalisation debate

LAST week, the government released its routine post-cabinet briefing. Of interest was the publication of Gross Domestic Products (GDPs) for all the country’s 10 provinces. 

The provincial production data from the post-cabinet briefing was divided into two parameters: gross domestic and per capita (per person). 

We need to understand the meaning of these parameters—the post-cabinet briefing did not define the meaning of these two parameters. GDP is the value of new products made and exchanged (bought and sold) during a specific period of time in a specific geographical area.

In terms of provincial GDPs, it means a provincial GDP, as per the post-cabinet briefing data, is the total value of products made in the province and then bought and sold within both Zimbabwe and out of Zimbabwe.

That would be the logical economic definition of provincial GDP. Per capita GDP is simply the GDP divided by the population of the area in which the GDP is generated within  a particular time  period.

Economists use per capita GDP to approximate the relative wealth, levels of prosperity and standards of living. Provincial per capita GDP should be taken to mean the GDP generated in a province divided by the population of the province in a particular year, 2018, in the case of the data presented at last week’s post-cabinet briefing. 

Prior to presenting a critical analysis of issues attendant in provincial GDPs, the performance of each province, GDP-wise, is listed. According to the post-cabinet briefing, the data is for 2018.

Based on the data in the post-cabinet briefing, the GDP performance of each province, in order of size from the biggest to the smallest is as follows:

1. Harare, US$9.56 billion
2. Bulawayo, US$2.26 billion
3. Mashonaland East, US$2.22 billion
4. Mashonaland West, US$2.14 billion
5. Midlands, US$1.94 billion
6. Manicaland, US$1.46 billion
7. Masvingo, US$1.41 billion
8. Matabeleland North, US$1.16 billion
9. Mashonaland Central, US$1.08 billion
10. Matabeleland South, US$0.94 billion

On a per capita (per person) GDP basis, from the highest per capita GDP to the least, the performance turns out as follows:

1. Harare, US$3 614
2. Bulawayo, US$3 048
3. Mashonaland East, US$1 408
4. Matabeleland North, US$ 1 333
5. Mashonaland West, US$1 206
6. Matabeleland South, US$1 186
7. Midlands, US$1 026
8. Masvingo, US$820
9. Mashonaland Central, US$784
10. Manicaland, US$743

There are a number of salient issues embedded in the provincial economic production data.

Assuming the provincial GDP data originating from ZimStat is accurate, the disparity in terms of economic production between Harare metropolitan and Bulawayo metropolitan is astounding. Harare metropolitan produces 4.23 times what Bulawayo metropolitan produces.

Put differently, Bulawayo’s economy is less than a quarter of Harare’s economy. We do not have the baseline data for the GDPs of Harare and Bulawayo pre-Independence and soon after Independence. As such, we can only qualitatively argue on the glaring disparity in the sizes of the two largest provincial economies.

Intuitively, the disparity is concerning because Bulawayo used to be Zimbabwe’s largest industrial hub. It can be strongly argued that years of de-industrialisation of Bulawayo, with firms relocating to Harare, others moth-balling with others completely shutting down is what has cumulatively led to Harare’s economy more than quadrupling Bulawayo’s. 

Two broad processes drove Bulawayo’s de-industrialisation. The first process was the take-all administrative structure that incentivised the capital as a strategic location and the excuse that water problems in Bulawayo were a risk to be compensated for by relocating to the capital.

The second process is the  destruction of agro-based value chains and the disintegration of the agglomerations that had accreted around agro-value chains. Land reform had a significant impact in diminishing primary agricultural production in the provinces supplying raw material for value-addition in Bulawayo.

The agro-value chain around beef production is a case in point. Loss of beef production in Matabeleland South directly impacted the Cold Storage Company’s ability to value-add. Sanctions linked to the land reform also meant the CSC lost the beef export quota to the European Union. 

Supporting industries such as the mighty mechanical engineering Bulawayo cluster and the National Railways of Zimbabwe were strangled as a result of the disintegration of the beef value chain. It does not make sense for Mashonaland East’s economy to be practically the size of Bulawayo—it strongly underlines the severity of the de-industrialisation Bulawayo has experienced systemically. 

Per capita GDP results present serious ironies that intuitively do not make sense. The data would have us believe Manicaland is the poorest province in Zimbabwe. The same data would also have us believe that Bulawayo and Harare are almost equally prosperous, with Harare being slightly more affluent.

The same data would have us believe that Matabeleland South is the 6th most prosperous province despite being the smallest provincial economy, producing under US$1 billion of economic output. We have to reconcile these counterintuitive results. Despite Bulawayo’s incessant industrial haemorrhaging, it seems to be as prosperous as Harare.

We have to look into the population dynamics. The population statistics have been disputed by a number of critics, with the accusation that Bulawayo’s population is under-counted. If this claim were true, then Bulawayo’s per capita GDP is exaggerated, meaning the province is not that prosperous but relatively poorer.

The other school of thought argues that the systematic de-industrialisation of Bulawayo has led to emigration of economically active people from the province to the diaspora and to the capital city, leaving a dwindled population responsible for the high per capita GDP. 

To many people I shared the provincial per capita GDP data ranking, the implied conclusion embedded in the ranking that Matabeleland provinces are not the poorest was counterintuitive. It led them to question the credibility of the data.

It does not make sense for many to accept that Manicaland is the poorest province and that Matabeleland South is significantly wealthier than Manicaland, Midlands, Masvingo and Mashonaland Central.

It causes cognitive dissonance for some to reconcile with the thought that a province such as Manicaland with diamond production, fruit production, tea estates, timber, tourism and dairy production can lag behind Matabeleland South, prosperity-wise, with  mining and a diminished beef industry and a relatively small horticultural sector centred around Beitbridge’s citrus plantations. These are legitimate reactions of scepticism. 

We need to understand the limitations of per capita GDP as a measure of relative wealth. GDP aggregates monetary value of formally produced goods and services; it does not measure the quality of the output in terms of its impact on the life of the people.

Per capita GDP would include the value of education expenditure but would not tell us about the quality of education such as access to education within a province and the quality of educational facilities.

A common outcry in Matabeleland South is over high rate of school dropouts and poorly-staffed schools. Per capita GDP does not mean equal income distribution; it can hide serious income inequalities. Does it mean that citizens of Matabeleland South have better incomes than those from Manicaland, Mashonaland Central, Masvingo and the Midlands?

It does not intuitively seem so. The argument that our economy is highly informalised and therefore does not capture the entire gamut of production that is exchanged outside the informal sector can be dealt with by looking at quality-of-life measures.

Many point out Tsholotsho as an aberration due to its general symbols of relative prosperity such as well-built rural residences with modern conveniences. This reflects the impact of Gross National Income (GNI), which accounts for diaspora flows.

There is a case for provincial GNIs at theoretical level. Practically, it is next to impossible to measure provincial GNIs as such foreign inflows come through informal means. This challenge buttresses that our analysis of prosperity should embrace as many dimensions as possible. 

The initiative to disaggregate GDP to provinces is a step in the right direction. We need to go a step further and accompany provincial GDP data with more refined measures of quality of life in each province and sub-provincial polity.

Human Development Indices (HDIs) need to be measured and reported at provincial and sub-provincial levels. We need to know how many people within each province and sub-province have access to clean  and safe water, access to reliable power, access to quality nutrition, food security, access to quality education, access to quality communication, access to quality transportation, quality of infrastructure, levels of infant mortality rates, income levels per household, access to happiness, to mention a few.

This should lead us to revisit our national vision of transforming our country to an upper middle-income economy. As famously put by the African Development Bank chief Akinwumi Adesina that people do not eat GDP, we need to tie our per capita GDP and per capita GNI metrics to quality of life improvements—this is the true test of prosperity.

This will also remove doubts in the minds of many people who think the provincial economic output and productivity data is not credible—it is because people see a disconnect between the quality of life they experience on a day-to-day basis and the technical economic data. If people cannot see improvements in their day-to-day life, metrics such as GDP growth or which province has the biggest economy or is more productive than the other are meaningless. Quality of life is the rub of the matter. 

We need to correct the economic production disparity between the northern  and southern provinces, especially the huge disparity between Harare and Bulawayo. Resuscitating agricultural value chains in the southern provinces will revolve around addressing the security of tenure of the beef farms and water development.

Normalising relations with international power brokers is a must as it will re-establish export value chains once enjoyed by southern provinces. Value-addition within provinces must be a key policy imperative in the National Development Strategy Two and Two.

Imagine what would happen to the economy of Mutare if diamond polishing were,  as a matter of policy,  done in Manicaland where the diamonds are produced? Any national economic growth must result in increases in incomes in all provinces and sub-provinces.