Table A35.
Effects of the COVID-19 pandemic on different groups of workers by industries.
| Explanatory variables | Industries of employment |
||||||||
|---|---|---|---|---|---|---|---|---|---|
| Agriculture | Fishery | Mining, electricity, water | Manufacture, processing | Construction | Trade | Hotel, restaurant | Transportation | Service | |
| Effects on workers below minimum wages | −0.0403 | −0.1101* | −0.0331 | −0.1138*** | −0.1442*** | −0.3687* | −0.2739** | −0.2463*** | −0.0971*** |
| (0.0357) | (0.0534) | (0.0329) | (0.0248) | (0.0309) | (0.1961) | (0.1184) | (0.0588) | (0.0294) | |
| Effects on workers not below minimum wages | 0.0219 | −0.0125 | 0.0867*** | 0.0011 | −0.0188* | 0.0576 | 0.0565 | −0.0361 | −0.0194*** |
| (0.0189) | (0.0327) | (0.0110) | (0.0236) | (0.0093) | (0.0695) | (0.0751) | (0.0314) | (0.0066) | |
| Effects on workers in wage quintile 1 | −0.0312 | −0.2405*** | −0.0532 | −0.0596 | −0.1273*** | −0.5564*** | −0.3454*** | −0.3456*** | −0.1020*** |
| (0.0417) | (0.0597) | (0.1249) | (0.0353) | (0.0336) | (0.1326) | (0.1166) | (0.0680) | (0.0219) | |
| Effects on workers in wage quintiles 2 to 5 | −0.0289*** | 0.0036 | 0.0415** | −0.0170 | −0.0390*** | 0.0713 | 0.0361 | −0.0693*** | −0.0122 |
| (0.0066) | (0.0228) | (0.0153) | (0.0239) | (0.0057) | (0.0684) | (0.0802) | (0.0218) | (0.0084) | |
| Note: Control variables are the same as in Table 1, including gender, age, age squared, education levels and urban dummy, district and year fixed-effects.Robust standard errors in parentheses (corrected for sampling weight and clustered at the district level and year-by-quarter level) . *** p < 0.01, ** p < 0.05, * p < 0.1. Source: authors’ estimations from the LFSs. | |||||||||