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The Behavior of South African PPI Before and During COVID-19

Various factors have been hypothesized to influence the performance of an economy. Such factors include availability of natural resources, labor, capital i.e., physical and human capital, technology, high investment rates, and entrepreneurship (Upreti, 2015). According to (Wijaya, 2017), high economic growth, as well as the underlying country’s sustainability, make up the main conditions of sustainability economic country development. Factors such as large-scale pandemics have been studied in relation to among other effects, their role in the disruption of economies through ripple effects occurring as a result of the shocks of “…simultaneous disruptions to both supply and demand in an interconnected world economy” (Chudik, et al., 2020).

A country’s gross domestic product (GDP) has been proposed by various studies as an indicator of economic growth

 The ongoing Corona virus pandemic is arguably one of the most widespread pandemics of modern times which according to various studies while marring the global economy with the deepest recession since the end of World War II (Yeyati & Filippini, 2021), has had its silver linings such as a boost to productivity growth (Carlsson-Szlezak & Swartz, 2021). Mixed feelings.

Since the onset of the Coronavirus pandemic in late 2019, the world has had to deal with issues such as big shifts in the stock markets (Jones, et al., 2021), an increase in unemployment rates (Falk, et al., 2021), an increase in the demand of food due to stockpiling (Nicola, et al., 2020), imposition of travel restriction that have affected industries such as tourism and international transport (World Tourism Organization, 2020), increase in productivity (Carlsson-Szlezak & Swartz, 2021).

Previous studies on the dynamics of COVID-19 have examine the effect of the virus from various fronts including Unemployment (Klein & Smith, 2021), Health, Social and Political (Yunfeng, et al., 2021). Ideally, the effects of the Corona Virus pandemic on the growth of various economies around the globe are apparent but to what extent does it affect an individual? The current study is centered around examining the effect of the coronavirus in South Africa. In particular, the current study seeks to examine how the pandemic affects economic growth if it does.

The current work proposes the examination of the change of the Producer Price Index in South Africa before and after the Corona Virus epidemic. To my knowledge, there exists limited research focusing on the effects of Covid-19 on the Producer Price Index. Therefore, this study will examine the behavior of PPI before and during Covid-19 to establish whether Covid-19 which is considered a modern-day pandemic affected the PPI of South Africa. Based on the findings, we will use an ARIMA model to predict whether the country’s PPI will show an upward or downward trend.

To address the research objective, the following questions will be answered regarding the behavior of the South African PPI:

  1. How does the PPI of South Africa compare before and after the onset of the global coronavirus pandemic?
  2. What is expected of the price changes in South Africa over time?

South Africa is considered one of the fastest-growing economies in Africa an observation attributed to the country’s mutual interaction openness with the rest of the world (Joshua, et al., 2020). Based on the 2021 economic index, the country was ranked the 99th freest economy is an increase of 0.9 points, which is attributed to the improvement of the judicial effectiveness (The Heritage Foundation, 2021). However, according to a report by the (World Bank, 2021), the coronavirus pandemic has had a significant effect on South Africa’s economy. The World Bank estimates that the economy contracted by approximately 7% as of 2020 given that the pandemic affected both external and internal activities following the containment measures adopted by the government.

Factors Influencing the Growth of South Africa's Economy

(Upreti, 2015) argues that high volume exports, significant supply of natural resources, longer life expectancy, as well as high levels of investment tend to have a positive effect on the performance of developing economies implying that a disruption to any of these factors will adversely affect the underlying economy. (Woodruff, 2019) on the factors affecting the economic growth of the South African economy supports the observations by (Upreti, 2015). According to (Woodruff, 2019), human resources, investment in physical capital, quantity and availability of natural resources, advancement in technology, as well as commodity prices (Stoddard, 2021) are among the important factors that shape the growth of South Africa’s economy.

 In practice, the extensive contraction of the South African economy in 2019 is observed to have led to an increase in the number of individuals living under poverty level by an estimated 2 million persons i.e., “…living below the poverty line for upper-middle income countries, $5.5 per day in 2011 Purchasing Power Parity exchange rates, PPP” (World Bank, 2021).

The country entered the years following the pandemic after several years of relatively low growth. For instance, in 2019, the economy expanded by 0.2%, 0.8% in 2018 which was partially caused by the reappearance of load shedding linked with operational and financial strains at the energy utility Eskom (World Bank, 2021). Just before the pandemic, the levels of unemployment in South Africa were approximately 31.3% while that among men was 27.2% in Quarter 4 of 2019 (Statistics South Africa, 2019).

The percentage of the population living below the upper-middle-income-country poverty line dropped from approximately 68% to about 56% between 2005 and 2010 (World Bank, 2021). However, the proportion of the population living in poverty since shown an upward trend reaching 57% in 2015 with forecasts showing that it is expected to peak up to 60% in 2020.

In essence, in the years following 2020, the Coronavirus disease 2019 (COVID-19) pandemic has been associated with catastrophic health and economic effects globally (Chitiga, et al., 2021). South Africa reported the first COVID-19 case on the 1st of March 2020 (Chitiga?Mabugu, et al., 2020) and as of January 12th 2020, the country had recorded up to 3,534,131 cases with approximately 92,649 mortalities (Worldometer, 2022).

Beginning with specific smaller measures as of March 15, 2020 onwards, the government put in place a national lockdown from March 27, 2020. The associated lockdown measure included the complete closure of childcare, institutions of primary and higher education and all public leisure activities (Schröder, et al., 2021). Other measures include severe physical distancing conditions, an up to 70% reduction of shopping, 85% of on-site work force as well as a 90% reduction in other activities.

Emergence of COVID-19 has replaced Eskom’s role as the main risk to the economy (Stoddard, 2021). (Stoddard, 2021) argues that on its own, Eskom would have to crumple to lead to a 51% gross domestic product (GDP) drop on its own. Structural hurdles coupled by weak growth have undermined progress in combating poverty, which have been amplified by the COVID-19 pandemic (World Bank, 2021). Various studies show that the imposition of lockdown measures by the government in March 2020 had a negative shock on the economy (Arndt, et al., 2020; Álvarez-Iglesias, et al., 2021; Posel, et al., 2021) leading to among other factors, job loss (Álvarez-Iglesias, et al., 2021), widening income inequality (World Bank, 2021; Chitiga?Mabugu, et al., 2020), etcetera.

Impact of COVID-19 on South Africa's Economy

(Ndoricimpa, 2017) observes that low inflation has a positive effect on the growth of middle-income countries with a threshold of 6.5% above which, inflation is harmful to the economy. According to (Sattarov, 2011), in the long run, there exists a positive relationship between inflation and economic growth an observation supported by (Ekinci, et al., 2020) who when studying the relationship between price stability and economic growth notes that below a specified threshold level (4.182%), inflation-growth relationship is insignificant while above the threshold, inflation has a negative effect on the economic growth of a country.

Both PPI and CPI are popular measures of inflation where PPI measures inflation from the perspective of costs to industry or producers of products (Pinkasovitich, 2021). For investors, inflation is important given that it can be used to predict the future direction of interest rates. Primarily, interest rates are negatively associated with market returns (Pinkasovitich, 2021). Conceptually, since the PPI measures changes in prices before they reach the consumers, it can be considered as an early predictor of inflation hence useful for addressing the current work’s research objective.

An empirical research design was adopted for this work since it is the optimal approach for the proposed time series data analysis. The design will allow for the exploration of the behavior of the PPI time series data which will be sampled at various intervals to be studied before a specified model is applied. As such, the adopted empirical methodology will help avoid the possibility of generating wrong results and subsequently wrong conclusions. Besides, the nature of the analytical model to be applied will depend on the actual behavior of the PPI data instead of a perceived notion.


To measure the volatility of PPI before and after the coronavirus pandemic, information related to the producer price index of South Africa was collected from the Federal Reserve Bank of St. Louis data repository  which includes PPI for manufactured goods from January 1970 to June 2021. The PPI was computed using 2015 as the base year. Similar information is contained in South Africa’s government data repository i.e., as well as the OECD repository  which however uses 2020 as the base year but offers a wide range of PPI for different products.

In particular, the current study sought to examine the changes exhibited by the Producer price indices in manufacturing which measure the rate of change in prices of commodities sold as they leave the producer. The data from the Federal Reserve Bank of St. Louis data repository is more readily usable compared to that from the government's repository and since the information from the three repositories is similar except for the base year for SA’s government repository, the information contained is assumed to be accurate enough to be used for the current research.


Following the worldwide spread of the novel coronavirus which was first reported outside China on January 24th, 2020, and in SA on March 5th, 2020 the country adopted serious restrictions from March 15th (Wiysonge, 2020) and national lockdown from 27th March 2020. As such, the periods of interest i.e., the inclusion criterion for the current study include the period before March 27th and the period after March 27th. Using this inclusion criterion, the details of the sampled data are given in table 1 below.

Table 1: Data Samples



Number of observations


01/01/1970 to 01/06/2021


First Sample (Period before the novel coronavirus was first reported in SA)

01/01/2000 to 26/03/2020


The second sample (Period after the first case of covid was reported in SA)

27/03/2020 to 01/06/2021


Two approaches were adopted for the final analysis including t-test and ARIMA forecasting.


We were also interested in determining whether on average, the PPI before the pandemic was significantly different from the observed PPI after the pandemic. To test for this difference, we proposed the use of an independent samples t-test tested at 0.1 level of significance.

Null Hypothesis

The means South African PPI for the period before and after lockdown are equal.

Alternative hypothesis

The means for the two populations are not equal.

ARIMA Forecasting

During our preliminary analysis we had established that the South African PPI was observed to be stationary after 1st order differencing at 90% confidence interval hence the time series was differenced and fitted using ARIMA model. To generate a stationary time series model, we implemented a differencing which is essentially suitable for removing the time-dependency of the data by stabilizing the mean through removing changes in the level of a time series (Brownlee, 2017). In our case, we differenced both time-series datasets with k = 1. Table 1 below provides an overview of the Dickey-Fuller test on the differenced time-series data.

Table 2: Dickey-Fuller test on the differenced time-series data


Dickey-Fuller Statistic








At 0.1 level, we observe that after differencing, both time-series data exhibit stationarity hence suitable for testing for time series modeling. In our case, we will use the data to forecast the trend of the South African PPI.

Descriptive Statistics

Table 3 below provides an overview of the summary statistics of the South African PPI.

Table 3: Summary statistics


N = 246



2001-01-01 to 2021-06-01


Median (IQR)

79 (56 - 107)

Mean (SD)

83 (27)


42 - 135


After Lockdown

15 / 246 (6.0976%)

Before Lockdown

231 / 246 (93.902%)

We note from table 3 above that the mean PPI for the period between 1st January 2001 and 1st June 2021 is (M = 83, SD = 27, N = 246). Moreover, the lowest recorded PPI is 56 while the highest is 107.

Cite This Work

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