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Research indicates that strong protection against laying off permanent workers induces firms to hire more temporary workers than permanent workers.21 _The

underlying intuition is that layoff protection increases the burden placed on em- ployers when they hire permanent workers. In this section, I discuss whether the intuition holds in my model. Recently the Japanese government started a discussion about whether it should create clearer rules for laying off workers, including laws that require firms to pay lump-sum transfers to workers who are being fired. Such policies are said to produce effects that resemble those produced by the lenient layoff protection policy. Underlying the discussion is a question: do firms, which are inherently risk-averse, hesitate to lay off workers because the current layoff protection policies are vague? Many argue that loos-

ening layoff protection laws should promote a more invigorated flow within the labor market, which would help to alleviate occupational mismatches. I inves- tigate this issue within my model’s framework.

In this model, the parameter, φ, controls the difficulty of firing a permanent worker. Note that in my model φ is a pure waste that is not transferred to un- employed workers. In the experiment presented below, I compute the model statistics using different values of φ. Other parameter values are set according to the baseline calibration presented in Section 1.7. Throughout the experiment the steady-state annual growth rate is set to equal 1% and the annual real in- terest rate equals 2.79%. Note that in our baseline calibration, the estimated value of φ, 9.3714 is approximately equal to six months of the average wages of permanent workers. Table 1.7 summarizes the results of the model statistics.

Table 1.7: Model statistics with different layoff policies

(1) (2) (3) (4) (5)

φ = 0 φ = 9.37/2 φ = 9.37 φ = 9.37 × 2 φ = 9.37 × 4

in terms of monthly wages 0 month 3 months 6 months 12 months 24 months

Job finding rate 0.1536 0.1518 0.1543 0.1551 0.1522

Ratio of job finding rate: perm/temp 0.4550 0.4550 0.4496 0.4372 0.4170

Job separation rate 0.0034 0.0034 0.0035 0.0036 0.0036

Share of temporary worker 0.1398 0.1398 0.1623 0.1860 0.2110

Average wage ratio perm/temp 1.7938 1.8004 1.8282 1.8638 1.9135

Unemployment rate 3.46% 3.50% 3.49% 3.52% 3.63%

Job-finding rate in perm. sector 0.1364 0.1347 0.1341 0.1317 0.1255

Job-finding rate in temp. sector 0.2968 0.2960 0.2994 0.3013 0.3011

Cutoff level, h∗ _{0.6711 0.6711 0.7047 0.7383 0.7718}

Each column in Table 1.7 shows the model statistics; corresponding values of φ are at the top of the table. I first compare the results from column (1) and col- umn (2) against the baseline result in column (3) where φ is approximately equal to 6 months of wages. Column (1) shows that when φ = 0, the share of tempo-

rary workers is 13.98%. Compare this to 16.23%, which is the share of temporary workers in the baseline calibration in column (3). The share of temporary work- ers decreases because in this economy the job-finding rate for permanent jobs is high, which increases the value of searching jobs in the permanent market and induces more people to search permanent jobs. Accordingly, the cutoff level, h∗also decreases to 0.6711 (column (1)) from 0.7047 (column (3)) of the baseline calibration, which indicates that unemployed workers with a skill level between 0.6711 and 0.7047 find it optimal to search for temporary jobs rather than per- manent jobs. The job-finding rate for permanent jobs is elevated because firms are posting more vacancies in the permanent market. Since the present value of permanent jobs increases as the firing cost goes down, firms will compete with each other to post more vacancies until the value of posting vacancies becomes zero. The separation rate for the overall economy also decreases because there is a decreased share of temporary workers, and so the unemployment rate goes down.

Columns (4) and (5) report model statistics when φ’s are equal to as much as 12 months and 24 months, respectively, of average monthly wages. When φ equals 24 months of average monthly wages, the share of temporary workers goes up to a strikingly high level of 21.10% that is strikingly high compared to the baseline case of 16.23%. This is caused by the significant reduction in the job-finding rate in the permanent market, which is caused by the fact that firms now post fewer permanent market vacancies. As φ increases, the number of va- cancy posting firms and the job-finding rate for permanent jobs decrease, which causes the value of searching in the permanent market to drop, too. Thus, the cutoff skill level when φ equals 12 months and 24 months of monthly wages in- creases to 0.7383 and 0.7718, respectively, which encourages workers who have

skills below these new cutoff levels to search for jobs in the temporary market instead of the permanent market. In these economies, the job-finding rate in the permanent market is so low that workers who previously has searched in the permanent market now find it optimal to search in the temporary market. Finally, the job separation rate for overall economy goes up because the share of temporary workers increases, which results in unemployment rates that are higher than those found in the baseline model.

In summary, reducing firing cost decreases unemployment and the share of temporary workers. This conclusion is consistent with [17]’s finding that in- creasing the firing cost induces firms to substitute permanent workers for tem- porary workers. Loosening of layoff protection removes the burden placed on firms of hiring permanent workers and increases the value of permanent jobs, which motivate firms to post more vacancies in the permanent market. Thus, more job-seeker are attracted to the permanent market, and the share of tempo- rary workers decreases.