Punjab may lose most jobs due to Covid-19: experts

ISLAMABAD: Punjab could be the worst hit by pandemic Coronavirus among all the four provinces on account of losing jobs as in the worst case scenario, 10 to 12 million daily wagers might be laid-ff, the highest from the neglected agriculture sector.

This alarming assessment has been made by the Pakistan Institute of Development Economics (PIDE), an affiliate arm of the Planning Commission of Pakistan here on Thursday.

“Our analysis shows that in Punjab, 10 to 12 million of those who are vulnerably employed can face losing their jobs in Stages II and III (worst case scenario) respectively.

The same numbers for Sindh are 3.3 to 4.1 million, and around two million for KP and under a million for Balochistan,” the latest estimates worked out by the PIDE and shared with The News disclosed on Thursday.

Regarding the expected layoffs by employment status by sectors across the provinces shows that except for Punjab, where the agriculture sector employs the majority of those in the labour force, all the other provinces are dominated by the services sector. Most layoffs in all the provinces, however, would be in the agriculture sector, followed by services sector.

Consequently, the total layoffs across the provinces are the highest in the agriculture sector, it added.

It further stated that in all the provinces, the daily wage workers are most vulnerable and hence should be put on priority for any social protection interventions that are being designed at the federal and provincial levels. The services sector, which has the largest number of vulnerably employed, needs special attention. It is a trend found across all the provinces.

Hence, any relief package for the business sector to encourage them to retain their employees must take these factors into account. These packages should vary across the provinces to prioritize the most vulnerable sectors in the province accordingly.

The PIDE said Punjab has the highest total and vulnerable employment in absolute numbers. Being the most populated province, this is expected but PIDE is concerned about numbers, and not just proportions, here because any relief that is provided should be according to the number of those affected across the provinces.

Proportionally, Sindh has the least vulnerability across four sectors – agriculture, manufacturing, construction, and wholesale and retail sector.

The vulnerability in hospitality, and transport and communication sectors is also lower in Sindh than in Punjab and KP.

Overall, the Sindh province is relatively less vulnerable in terms of its share in employment. However, when it comes to the number of layoffs, the situation is not encouraging.

For instance, agriculture is the most vulnerable sector in the KP province, whereas the share of vulnerable employment in manufacturing and wholesale and retail sectors is the highest in Balochistan.

Likewise, the share of vulnerable employment in hospitality sector is the highest in the Punjab province.

Interestingly, the construction sector has the least vulnerable employment among all the sectors in all the provinces.

Moreover, the variation in vulnerability across provinces is also small for this sector. Manufacturing and transport and communication sectors have the largest variations in vulnerability across the provinces.

Sindh, despite being the least susceptible province in terms of the share of vulnerable employment, will have more than four million people losing their jobs.

The absolute numbers, of course, are the highest for the most populated province of Punjab, with 13.5 million people projected to be laid-off. Protecting the affected households in these two provinces is therefore a difficult task and requires more focused interventions.

The majority of the layoffs across all the provinces would be of the daily-wage workers and workers paid by piece rate simply because they constitute the bigger proportion in these employment groups.

The vulnerability in terms of employment status remains the same in the four provinces as was observed in the national level analysis, it concluded.