3.2. Firm closures

3.2. Firm closures

The survey allows us to look at other firm outcomes. The first outcome that we explore is firm (temporary) closure. The firms are asked to report on the status of their business at the time of the survey. From the answers, we generate a dummy variable that takes the value of 1 if the firm is temporarily or permanently closed at the time of the interview and estimate equation 1 with this dummy variable as the outcome variable. The results of these estimations are presented in Table 5. The interpretation of the estimated coefficients becomes in terms of the share of firms thatare closed or the likelihood that a firm closes. It is important to note that while there are a few firms that report being permanently closed, firms that have exited the market are naturally less likely to respond to the survey. We estimate that around 9 and 7 percent of all firms are closed in waves 1 and 2 respectively. This share is highest for the smallest firms (12% and 10% in waves 1 and 2 respectively), whereas this share is 5% lower than the smallest firms for firms between 24-49 workers in wave 1, and 8.4% and 6.6% lower for the largest firms (50+ workers) in waves 1 and 2 respectively. This suggests that the larger firms were less likely to close shop in the wake of the pandemic. In terms of countries, the share of firms that closed is highest in Jordan and Egypt (10.5 and 10% in the two waves respectively), and lower in Morocco (by 3.5 and 7% in waves 1 and 2 respectively relative to Jordan) and Tunisia (by 4 and 6.6% in waves 1 and 2 respectively). With respect to sectors, the highest share of closures is estimated for the reference industry (agriculture, fishing, and mining) and accommodation and food service in wave 1, whereas all other industries, have significantly lower shares of closures relative to the reference industry, with the lowest being recorded in the education sector. In wave 2, the shares of closures are not statistically different across the industries from the reference industry (around 7%). Therefore, once again, we learn that larger firms are less likely to close (temporarily) and we observe the least negative outcomes in terms of firm closures for Tunisian and Moroccan firms, whereas accommodation and food services along with agriculture, mining, and fishing are most likely to close down, reflecting the importance of human interaction in these sectors. Hence, if firm closure is a measure of resilience, the larger firms are significantly most resilient, and it seems that the industries that require human physical interaction are the least resilient (agriculture, fishing, and mining and accommodation and food services).