In the lecture, we discussed this regression output from Breunig et al. (2017) which provides evidence on the labour market consequences of immigration in Australia: TABLE 3 Estimated Values of e from Equation (1): SIH, Selected Subsamples Log annual earnings Log weekly earnings Log wage rate Weekly hours Participation rate Unemployment rate -0.848 (3.226) 0.131 (0.101) -0.037 (0.051) 8.112* (4.803) 0.209* (0.104) -0.039 (0.050) Male only 0 0.064 0.064 0.068 (0.164) (0.181) (0.196) Female only e 0.155 0.153 -0.029 (0.184) (0.170) (0.203) All individuals with 15 years of experience or less 0.247 -0.082 -0.254 (0.332) (0.445) (0.406) Males with 15 years of experience or less e 0.298 0.240 0.359 (0.222) (0.278) (0.398) Females with 15 years of experience or less 0 0.071 -0.122 -0.038 (0.348) (0.354) (0.586) 3.465 (9.117) 0.175 (0.207) -0.098 (0.094) -5.202 (3.885) -0.049 (0.106) 0.033 (0.087) 7.417 (7.253) 0.100 (0.160) -0.189* (0.099) Notes: Models include full set of time dummies, education and experience fixed effects and full set of interactions. * indicates statistical significance at the 10% level. Yijt = The table shows results of the following regression: Opijt + controls + Eijt, (1) where the unit of observation is the group of people with education level i and job market experience level j in year t. (a) (5 marks) Explain how the regressor of interest Pijt, the immigration measure, is calculated. In the lecture, we discussed this regression output from Breunig et al. (2017) which provides evidence on the labour market consequences of immigration in Australia: TABLE 3 Estimated Values of e from Equation (1): SIH, Selected Subsamples Log annual earnings Log weekly earnings Log wage rate Weekly hours Participation rate Unemployment rate -0.848 (3.226) 0.131 (0.101) -0.037 (0.051) 8.112* (4.803) 0.209* (0.104) -0.039 (0.050) Male only 0 0.064 0.064 0.068 (0.164) (0.181) (0.196) Female only e 0.155 0.153 -0.029 (0.184) (0.170) (0.203) All individuals with 15 years of experience or less 0.247 -0.082 -0.254 (0.332) (0.445) (0.406) Males with 15 years of experience or less e 0.298 0.240 0.359 (0.222) (0.278) (0.398) Females with 15 years of experience or less 0 0.071 -0.122 -0.038 (0.348) (0.354) (0.586) 3.465 (9.117) 0.175 (0.207) -0.098 (0.094) -5.202 (3.885) -0.049 (0.106) 0.033 (0.087) 7.417 (7.253) 0.100 (0.160) -0.189* (0.099) Notes: Models include full set of time dummies, education and experience fixed effects and full set of interactions. * indicates statistical significance at the 10% level. Yijt = The table shows results of the following regression: Opijt + controls + Eijt, (1) where the unit of observation is the group of people with education level i and job market experience level j in year t. (a) (5 marks) Explain how the regressor of interest Pijt, the immigration measure, is calculated
