Please work in Groups of 4 - Due Oct. 9, 2019 at the Beginning of the Lecture (submit one version of this homework per group to the assignment 2 folder created on mycourses).
For exercise 1 and 2, consider the data extract Canjuly18.txt based on the July 2018 wave of the Canadian Labor Force Survey collected by StatCan. For exercise 3, consider the time series database TsCanada. The data are available in a zip file (LFSCan.zip, which contains excel file, text file and .dta file for each database) in the folder “TA Conf”.
The propose of this exercise is to estimate the elasticity of labor supply with respect to hourly wage using Canadian Data from Labor Force Survey (LFS,Statistic Canada, July 2018). We will consider the Usual hours per week at their main job (uhrsmain) as the labor supplied by an individual at given hourly wage (hrlyearn).
Each group should choose one Census Metropolitan Area (CMA) as well as the province in which the CMA lies (see Table 1). The codes are useful for those using Stata.
Possible answer
The majority of canadians are working more than 35 hours per week i.e full time at their main job. However, other are working partial time at their main job (less than 30 hours). This result suggest that not all canadians are workin full time. By gender, we observe a left-skewed distribution for men and a right-skewed distribution for women. This result suggest that the fraction of women working partial time at their main job is much higher the fraction of men.
\[ h_i = \beta_0 +\beta_1 \omega_i +\varepsilon_i \]
Estimate | Std. Error | t value | Pr(>|t|) | |
---|---|---|---|---|
Country | Canada | |||
constant | 32.64402 | 0.0955 | 341.80445 | 0 |
log wage | 0.13837 | 0.00322 | 42.93507 | 0 |
Province | Alberta | |||
constant | 32.56817 | 0.30414 | 107.08257 | 0 |
log wage | 0.15366 | 0.00884 | 17.3766 | 0 |
Province | British Columbia | |||
constant | 30.70814 | 0.28917 | 106.19427 | 0 |
log wage | 0.18742 | 0.00973 | 19.26642 | 0 |
Province | Manitoba | |||
constant | 32.32418 | 0.31692 | 101.99595 | 0 |
log wage | 0.1614 | 0.01176 | 13.72249 | 0 |
Province | NewBrunswick | |||
constant | 35.47828 | 0.45526 | 77.93004 | 0 |
log wage | 0.0993 | 0.01796 | 5.52978 | 0 |
Province | Newfoundland_Labrador | |||
constant | 34.86002 | 0.60824 | 57.31334 | 0 |
log wage | 0.13154 | 0.02154 | 6.10552 | 0 |
Province | NovaScotia | |||
constant | 33.27812 | 0.40739 | 81.68675 | 0 |
log wage | 0.15362 | 0.01555 | 9.88155 | 0 |
Province | Ontario | |||
constant | 32.34865 | 0.18691 | 173.0739 | 0 |
log wage | 0.1299 | 0.00602 | 21.56292 | 0 |
Province | PrinceEdIsland | |||
constant | 34.39774 | 0.59296 | 58.00996 | 0 |
log wage | 0.10996 | 0.02465 | 4.46066 | 1e-05 |
Province | Quebec | |||
constant | 32.80834 | 0.20417 | 160.68961 | 0 |
log wage | 0.10985 | 0.00723 | 15.20258 | 0 |
Province | Saskatchewan | |||
constant | 31.73455 | 0.36177 | 87.72001 | 0 |
log wage | 0.16875 | 0.01192 | 14.15272 | 0 |
Possible answer
The theorical model predict a backward bending labor supply, which is the result of substitution and income effects. In this empirical result, as wage increase the labor supplied by a worker increases. This result suggest that the substitution effect is much higher than the income effect (Of course the linear model is an assumption).
\[ \log(h_i) = \beta_0 + \beta_1 \log(\omega_i) +\varepsilon_i\]
Estimate | Std. Error | t value | Pr(>|t|) | |
---|---|---|---|---|
Country | Canada | |||
constant | 2.90608 | 0.01127 | 257.75559 | 0 |
log wage | 0.1998 | 0.00353 | 56.56082 | 0 |
Province | Alberta | |||
constant | 2.78867 | 0.03581 | 77.87064 | 0 |
log wage | 0.23301 | 0.01073 | 21.70615 | 0 |
Province | BritishColumbia | |||
constant | 2.7279 | 0.03432 | 79.48506 | 0 |
log wage | 0.24847 | 0.0107 | 23.22013 | 0 |
Province | Manitoba | |||
constant | 2.86586 | 0.03753 | 76.37157 | 0 |
log wage | 0.21687 | 0.0121 | 17.93018 | 0 |
Province | NewBrunswick | |||
constant | 3.02274 | 0.05208 | 58.041 | 0 |
log wage | 0.18401 | 0.01704 | 10.79777 | 0 |
Province | Newfoundland_Labrador | |||
constant | 3.01096 | 0.05883 | 51.17888 | 0 |
log wage | 0.1842 | 0.01884 | 9.77941 | 0 |
Province | NovaScotia | |||
constant | 2.99769 | 0.0417 | 71.88127 | 0 |
log wage | 0.18615 | 0.0136 | 13.687 | 0 |
Province | Ontario | |||
constant | 2.83663 | 0.02365 | 119.95811 | 0 |
log wage | 0.21409 | 0.0073 | 29.32981 | 0 |
Province | PrinceEdIsland | |||
constant | 3.0752 | 0.06747 | 45.5767 | 0 |
log wage | 0.16051 | 0.02238 | 7.17315 | 0 |
Province | Quebec | |||
constant | 3.02924 | 0.02362 | 128.2522 | 0 |
log wage | 0.16078 | 0.00747 | 21.51592 | 0 |
Province | Saskatchewan | |||
constant | 2.79446 | 0.04312 | 64.80858 | 0 |
log wage | 0.23137 | 0.01338 | 17.28653 | 0 |
Possible answer
The elasticity of labor supply is positive. If the wage rate increases, the worker will supply more labor.
Men | Women | |
---|---|---|
(Intercept) | 3.0784885 | 2.8544354 |
log(hrlyearn) | 0.1658351 | 0.1959058 |
Possible answer:
The empirical result suggest that the elasticity of labor supply is more elastic for women than for men.
Census Metropolitan Area | Rest of the province | |
---|---|---|
Edmonton | Alberta | |
Intercept | 2.78263 | 2.7906 |
log(wage) | 0.23254 | 0.23323 |
Hamilton | Ontario | |
Intercept | 2.69865 | 2.84583 |
log(wage) | 0.24922 | 0.2117 |
Montréal | Quebec | |
Intercept | 3.09289 | 3.00952 |
log(wage) | 0.1413 | 0.16685 |
Ottawa | Ontario | |
Intercept | 2.8803 | 2.82549 |
log(wage) | 0.18723 | 0.21851 |
Québec | Quebec | |
Intercept | 3.03295 | 3.02731 |
log(wage) | 0.15596 | 0.16182 |
Toronto | Ontario | |
Intercept | 2.98219 | 2.79527 |
log(wage) | 0.17089 | 0.22644 |
Vancouver | BritishColumbia | |
Intercept | 2.95642 | 2.60448 |
log(wage) | 0.18197 | 0.28472 |
Winnipeg | Manitoba | |
Intercept | 2.93138 | 2.72242 |
log(wage) | 0.19496 | 0.26472 |
Answer Both elasticities are are positive. The conclusion between CMA and the rest of the province depend on your province.
Answer The main concerns are the problems of cofounding and omitted variables. Also, the linear model is a strong assumption. Thus, these estimates are probably biased.
“Unions are collective organizations whose primary objective is to improve the well-being of their members. In Canada, this objective is met primarily through collective bargaining with the employer. The outcome of this process is a collective agreement specifying wages and non-wage benefits”.
To test whether unions have impact on wage in Canada (this is an exercise, in reality, we need more to test this assumption), consider the database Canjuly18.txt based on the July 2018 wave of the Canadian Labor Force Survey collected by StatCan.
** Answer** This result is similar what yoi have in the lecture notes. We observed some disersion acrross province.
##
## Female Male
## Non-Union member 65.34273 69.90245
## Union Member 34.65727 30.09755
Estimate | Std. Error | t value | Pr(>|t|) | |
---|---|---|---|---|
(Intercept) | 24.44570 | 0.07232 | 338.01954 | 0 |
union_memUnion Member | 5.90609 | 0.12713 | 46.45843 | 0 |
Answer
Many empirical work in the union literature aims at estimating the wage effect of unions, i.e. the union-nonunion wage gap. This exercise confirmed the Union wage premia. Both right-to-manage or efficient bargaining model could explain this result.
Consider the database of Labour Force Survey from 2009 to 2017, TsCanada.txt. This is a yearly data. Use all provinces. An unit of observation is a province-year.
Plot the employment rate against the average hourly earnings. Put the employment rate on the y-axis and the average wave (hrlyearn) on the x-axis.
Discuss: is this Demand, Supply, or something else. (Less than 200 words)
Possible answer
This graph illustrates only a set of equilibria.