This article analyzes the evolution of protest participation in Sudan from 2011 to 2018 using the data provided by the Arab Barometer Surveys. It finds that participation evolved substantially in both size and demographic determinants, reflecting the strong deterioration of the population’s socio-economic conditions over the last decade. The Arab Barometer surveys are the only cross-country source of data available for Arab countries. They were collected over five different waves in the last two decades. The analysis of the data they provide allows us to see specific phenomena from a different, data-based angle. For instance, it can help us observe the changes that occurred regarding protest participation throughout different countries and time periods. In most countries, including Sudan, such changes have not just been quantitative – i.e., different shares of the population have been joining protests in different time periods – but also qualitative – i.e., different social groups have been more likely to join protests in different time periods.
Although such differences are observable for several Arab countries, Sudan is a rather interesting case. In fact, by comparing the data on protest participation in 2011 and 2018 it is possible to observe radical differences in both the size of participation and in its main demographic determinants. This may be the consequence of important changes that occurred within Sudanese society over the last decade. In particular, it may be the result of the profound socio-economic transformations sparked by the secession of South Sudan in 2011.
Like most Arab countries, Sudan was hit by the wave of protests that originated in Tunisia at the beginning of 2011 and spread throughout the entire MENA region. Since January 2011 up until the spring of the same year protests occurred in the capital Khartoum and in several other cities such as Al-Ubayyid and Kassala. However, they ceased almost completely during the summer, as popular attention was catalyzed by the long-awaited secession of South Sudan.
This event caused severe damage to the Sudanese economy, as the country lost two-thirds of its oil resources. In order to balance the loss of oil revenues, in 2012 the government started implementing a harsh program of austerity measures aimed at reducing public expenditures. This led to a new wave of protests in 2012 followed by hard repression on the part of the government. As a result, the country’s economy never bounced back in the following years. On the contrary, continuous socio-economic deterioration, coupled with the regime’s lack of political accountability, have been pointed to as the key factors behind the movement that in 2019 ended the three-decade presidency of Omar al-Bashir.
The dramatic increase in protest participation is quite evident from the data provided by the third and fifth waves of the Arab Barometer surveys (Figure 1). From 2011 to 2018, the percentage of people who declared having taken part in at least one demonstration over the previous three years almost doubled and in 2018 the share of participants reached the impressive figure of almost one-third of the population. Such a figure is even more astonishing if we consider that the Arab Barometer survey was conducted in Sudan before the even bigger protests occurred in 2019.
Figure 1 – Comparison of protest participation share between 2011 and 2018
However, the differences between the protests in 2011 and those in 2018 are not limited to the size of the participants’ share. In Table 1 and 2 are displayed the results of logit regressions investigating the demographic determinants of participation in 2011 and 2018. Participation was used as a dependent variable while the main socio-economic indicators included in the Arab Barometers surveys – age, gender, urban/rural provenience, level of education, level of income, and level of religiosity – were used as independent variables.
Table 1 – Determinants of protest participation in 2011
Table 2 – Determinants of protest participation in 2018
As shown by the data, radical transformations occurred in the factors behind protest participation between the two waves of surveys, which may have been caused by different sets of motives spurring participation in 2011 and in the following years. Analogous investigations conducted by the author on other MENA countries showed in most cases a significant level of continuity between the results of 2011 and those of 2018-2019. In Sudan, apart from the level of education, which is positively associated with participation in both waves, all other determinants changed between 2011 and 2018, showing a radical transformation in the social composition of participation between the two waves.
For instance, while in 2011 being from rural regions was strongly associated with participation, in 2018 being from either urban or rural environments was no longer a significant determinant. Such a difference may be the result of much stronger socio-economic motives behind participation in recent years: while in 2011 protesters were mainly from marginalized regions, often inhabited by discriminated minorities, over the following years protests extended also to the biggest urban areas. This was most probably due to the economic fatigue that the austerity measures introduced by the government since 2012 caused also among the urban population. Moreover, while age was not a significant determinant in 2011, it was in 2018, showing a different, rather younger, composition of the more recent protests. Gender and level of religiosity saw their significance as protest determinants changed too. While in 2011 being male or female was not a strong predictor of participation, being male became strongly associated with higher chances to be a protester in 2018. On the contrary, while being averagely less religious was associated with higher chances of participation in 2011, it was no longer so in 2018.
The only constant determinant between the two waves is the level of education, which is always positively associated with participation (i.e., having achieved a higher education level makes participation more probable). This last finding is consistent with similar observations from several other Middle Eastern and North African countries, where education is always positively associated with protest participation.
The profound differences observed between the protest determinants in 2011 and those in 2018 are probably the symptom of the crisis sparked by the secession of South Sudan in 2012 and the consequent economic crisis that hit the rest of the country. In 2011 the wave of protest was relatively limited compared to those seen in other MENA countries, and mostly confined within rural areas. In the rest of Sudan socio-economic deterioration was still not as pronounced as elsewhere in the Arab world, also thanks to the oil revenues generated mostly in the southern part of the country. However, the socio-economic situation began deteriorating quickly after 2012, dramatically hitting the interests of urban citizens, previously less likely to take part in demonstrations. The share of people participating in protests increased dramatically, involving especially the youngest generations, those most hit by the new austerity measures.
In sum, the comparison between the two waves of surveys clearly shows the effects of the profound economic crisis begun in 2012 on the social pact that had underpinned Sudan’s ruling regime over the previous decades. The loss of South Sudan, coupled with the regime’s inability to reform, emerges as the main factor behind that exacerbation of the population’s propension to participate in contentious actions.
 Income was normalized to be compared across the three waves. In the third wave respondents were asked to indicate their precise monthly income. However, in the fourth and fifth waves they were simply asked to indicate whether their income was above or beneath the population’s median. Hence, I transformed the income variable of the third wave accordingly into a binary variable indicating whether the respondent’s income is above or beneath the median calculated on the income figures indicated in the original variable.
 To measure the respondents’ level of religiosity I used, as proxy, the question “do you pray daily?”, whose possible answers are “Always”, “Most of the time”, “Sometimes”, “Rarely”, and “Never”.
 For more information about the methodology employed see this similar work published by the author
 The stars beside each value indicate the level of statistical significance of the results. No star means that they are not significant (beneath the 95% confidence interval). One * represents significance above the 95% interval, two ** means significance above the 99% interval and three *** represents significance above the 99.9% interval.