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AN ECONOMIC EVALUATION OF THE JOBS CREDIT SCHEME Tan Boon Seng Assistant Professor The Hong Kong Polytechnic University Department of Management and Marketing Hung Hom, Kowloon, Hong Kong Telephone: 852-27664057; Fax: 852-27650611 Email: [email protected] Abstract We estimated the effect of the Jobs Credit Scheme (JCS) in saving local worker’s job from retrenchment using a standard one-period production model of output maximization under a labor budget constrain. The JCS was effectively a wage subsidy. We assumed the isoquant was determined by a Cobb Douglas production function using estimated capital cost share from the literature. We evaluated the extent of job loss under four scenarios of economic contractions in 2009: optimistic (-2%), expected (-5%), pessimistic (-10%) and catastrophic (-20%). We found that the JCS would effectively become a fast acting corporate tax cut favoring labor intensive firms because most of the benefit accrued to the firm. The JCS had a substitution effect that could save 5% to 66% of the local worker from job loss that would occur without it, but was less effective in more serious economic contractions. Our model’s prediction of job loss was bias upwards because of rehiring cost in the more realistic multiperiod models, and that firm could use other temporary measures to reduce wage costs. Keywords: Wage Subsidy (H25), Cob Douglas Production Function (D24), Substitution Effect (D21) 1. Introduction The Jobs Credit Scheme (JCS) is a one-year program, announced during the Singapore Budget 2009, to encourage employers to retain local workers. The $4.5 billion program is part of a $20.5 billion stimulus package, the “Resilience Package”, that include fiscal spending for tax reduction, stimulating bank lending, building infrastructure and expanding the civil service. (All currency in this paper is Singapore dollar where 1US$ = S$1.52 approximately in 2008). The package, which costs 6% of Singapore’s GDP, is currently the most aggressive economic stimulus, on a per capita basis, in the world. The parliamentary debate on the package focuses on the cost effectiveness of the JCS: Can the JCS save jobs for local workers? What is the economic cost for providing the benefit? We examine the economics of the JCS and estimate its effect on the choice of worker mix. We use a scenario analysis approach because forecast of future demand is difficult to obtain, but feasible ranges are available. Assuming that decision makers are rational, and output is determined by a Cobb Douglas production function, we estimate the number of local jobs that the JCS can save and the deadweight loss for four scenarios. In the following sections, we review some background information before proceeding with the modeling. Then, we describe some relevant features of Singapore’s labor policy in Section 2, the mechanics of the JCS in Section 3, develop our model in Section 4, discuss the result and limitation in Sections 5 and 6, and summarize our findings in Section 7. 2. Some Aspects of Singapore Labor Policy We focus on two aspects of Singapore’s labor policy to provide a context for the JCS. First, we outline the salient features of the Central Provident Fund (CPF), which influence the wage cost of local, but not foreign, workers. Second, we highlight the classifications of foreign workers in Singapore, and the policy regulating the employment of these classes of foreign workers. This information provides the context of the employment of foreign workers in Singapore. A comprehensive review of other aspects of Singapore labor policy are addressed elsewhere, see for example Fong and Lim (1982). 2.1 The Central Provident Fund (CPF) Scheme The CPF scheme is a mandatory, funded social security scheme for local workers, but foreign workers are excluded. Employers and workers jointly contribute a portion of the gross wage to individual accounts. The CPF does not involve inter-generation transfer through tax because it is accumulated individually during one’s working life. Originally intended as a scheme for funding retirement, the CPF has become the main source of finance for housing and various other schemes. 1 The administration of paying Jobs Credit in the JCS is tied to CPF (more in section 3). If workers receive the same gross wage, CPF payment creates a difference in their net wages because employers need to contribute a share to the local worker’s CPF. However, employers are indifferent to hiring a local or a foreign worker for the same net wage. As of 1 Jan 2009, local workers below age 50 pay 20% of their monthly wages to CPF, and their employers pay another 14.5%, making a total contribution of 34.5% of gross wage. Contribution rates are lower for workers above age 50, and for those earning below $1,500 a month. There is no CPF contribution required for the portion of wage above $4,500. For workers earning between $1,500 and $4,500 a month, the CPF contribution rates are as follows: Employee’s Age Employer Employee Total Below 50 14.5 20.0 34.5 50 to 55 10.5 18.0 28.5 55 to 60 7.5 12.5 20.0 60 to 65 5.0 7.5 12.5 Above 65 5.0 5.0 10.0 Table 1: CPF Contribution Rate as % of Wage by Age (Note: The retirement age is 62 years old as of 1 Jan 2009) If an employer offers a local worker below age 50 a gross monthly wage of $2,000, the net wage is $2,290 including the employer’s CPF contribution, and the local worker takes home $1,800. The employer is indifferent to offering $2,290 for a foreign worker before deducting the applicable levy. The take home pay of the foreign worker is the amount after deducting the foreign worker levy, which ranges from 0 to $470 a month. 2.2 Foreign Labor Policy The non-resident population in Singapore, which is those who are not citizens or permanent residents, was 2.9% in 1970 for a population of 2 million. However, foreign workers constituted 29% of Singapore's total labor force by 2000, which was the highest proportion of foreign workers in Asia. The increasing share of the nonresident population was a direct consequence of policy to attract and rely on foreign manpower, at both the high and low ends, to overcome the limits of local workforce. The number of higher skilled and better-educated foreigners increased rapidly as a result of intensive recruitment and liberalized eligibility criteria in the recent decade. The policy on foreign workers is administered through a system of work permit and employment pass. The work permit, or R pass, for lower skilled worker is based on the principle of confining them as a temporary workforce: The R pass is tied to an employer and not transferable, R pass holders are not eligible for dependent and long term social visit passes, and hiring R pass holders attracts high levies. High skilled workers qualify for employment pass known as P, Q and S passes. These employment passes qualify for dependent pass. P pass qualify for dependent pass and long term 1 The current uses of the CPF also include funding for hospitalization, education, investment and retirement. However, above 50% of the CPF withdrawal each year is for home financing since 1970. social visit pass. The types of employment passes and their essential characteristics are summarized in the following table: Type Eligibility P1 Foreigners with basic monthly salary >S$7,000 P2 Foreigners with basic monthly salary from S$3,500 to S$7,000 with acceptable degrees, professional qualifications, or specialist skills Q Foreigners with basic monthly salary > S$2,500, and with acceptable degrees, professional qualifications, or specialist skills S Foreigners with basic monthly salary > S$1,800 and with acceptable diploma R Foreigners with basic monthly salary < S$1,800 DP Yes Yes LTSVP Yes Yes Yes No Conditional No No No Notes: 1. Dependent Pass (DP) allows the worker’s spouse and children under 21 years old to stay in Singapore. Long Term Social Visit Pass (LTSVP) allows the above group, and also includes parents, parents-in-law, step-children and handicap children. 2. S pass holders may obtain Dependent Passes if the monthly salary > S$2,500 3. R pass holders are subjected to a security bond; a medical examination is required for approving two-year work permits. 4. S pass holders need to pay a levy of S$50/month. R pass holders pay higher levies depending on the sector they are employed and skill categorization. Table 2: Types of Employment Passes and Permits Quotas are set for lower skilled foreign workers, which include R and S pass holders, based on industry, but there is no limit on hiring P and Q pass holders. The minimum proportion of local worker is 12.5% for construction sector, 16.7% for marine sector, 35% for manufacturing sector, and 50% for service sector. The maximum proportion of S pass holders is limited to 25% for all sectors. Source country restrictions apply for all industry sectors. For instance, firms in the services sector are allowed to recruit R pass holders from Malaysia, Hong Kong, Macau, South Korea and Taiwan only. About 580,000 of the 756,300 foreign workers in 2006 were R pass holders (Yeoh, 2007): About 135,000 in the construction industry, 160,000 in domestic maid services, and the remaining 285,000 in service, manufacturing, marine and other industries. The remaining 176,300 foreign workers comprise of about 25,000 S pass holders, 65,000 Q pass holders and 86,300 P pass holders. 3. Mechanism of the JCS Employers, except local and foreign government organizations, who have made CPF contributions for their workers, are automatically eligible to receive Jobs Credit. The Jobs Credit is paid in four installments, and is computed using the employer's CPF contribution data. For workers on the payroll for the months of January, April, July and October in 2009, the employer will receive Jobs Credits in March, June, September and December 2009 respectively. The amount of Jobs Credits is 12% of the first $2,500 of gross wage for each eligible worker. This means the employer will receive up to $900 per worker for each installment (12% x $2,500 x 3 months). Therefore, the Jobs Credits is essentially a wage subsidy of local workers which is paid to the employer. The subsidy is $300 a month for workers with gross salary above $2,500, or 12% of the gross wage for workers with less income. The $2,500 cut off is the median wage for workers in Singapore who pay CPF. There are 1,461,900 CPF members in 2006 (CPF Board, 2007), and the number of workers with gross monthly wage of less than $2,500 is as follow: Monthly Wage ($) Number (000) Up to 200 - 400 - 600 - 800 - 1,000 - 1,500 - 2,000 200 399 599 799 999 1,499 1,999 2,499 21.4 27.4 54.2 79.7 67.2 178.5 192.4 176.9 Table 3: Number of CPF contributor with Monthly Wage below $2,500 in 2007 Using the above data, workers earning below $2,500 a month has an average wage of $1,357. Since the median wage is $2,500, half of all workers contributing CPF in 2006 earn more than $2,500, and half earn less than that. 4. Model Specification The model is set up to answer two questions: Can the JCS save jobs for local workers? What is the cost for providing the benefit? Even when job loss data in 2009 becomes available in future, it is not possible to tell if the job loss will be worse, or better, if the JCS is not implemented. We solve this problem by developing a model as follows: Figure 1: A Model of the Jobs Credit Scheme Consider the economy as one big firm. The y-axis represents the number of foreign workers (Lf) in the economy, the x-axis the number of local workers (Ls) in the economy, the curve is an isoquant which represents the bundles of possible labor inputs to produce a fixed level of output using a fixed level of capital. There are many other isoquants in the diagram which are not drawn. Higher isoquants, which are located on the north-east, have higher outputs. The average monthly wages for a foreign worker and a local worker are wf and ws respectively. The labor cost, which constrains the economy from choosing the highest isoquant possible, is wfLf + wsLs. The labor cost before introducing the JCS is represented by the line AB, which is an isocost line. The economy chooses the optimal mix of labor represented by the bundle X on the isoquant: This is the most north-east isoquant constrains by the isocost line AB. Therefore, X lies on the tangent of AB and the isoquant. The JCS changes the relative price of hiring foreign and local workers, shifting the isocost line to AC. If the economy expands, the new bundle will lie on the tangent of AC and a higher isoquant. If the economy stays the same size, a rational firm maximizing its profit will choose the bundle Y, which has more local and less foreign workers. If the economy contracts, the optimal labor combination will be south west of Y. Depending on the degree of contraction, the number of local workers in employment can be less than at X. The number of local job saved is calculated from the difference between the numbers of local workers in employment with and without the JCS. The difference will always be positive because of the flatter isocost after the price change due to the JCS. The model can be applied to the industry sector level, or the firm level, using suitable data. At the firm level, an expansion of the isoquant is possible for some firms even in a recession. We confine ourselves to the economy level in this paper. Quantitative result can only obtained for a known production function. Therefore, we assume the output of the economy is given by the Cobb Douglas production function Y = AK γ Lαf Lβs Y is the output (GDP), A is the total factor productivity (TFP), K is the level of capital stock, and α,β,γ are parameters of the production function. We can obtain the marginal products of labor, for the foreign and local workers, by partial differentiating the production function. From standard production theory, the marginal product of labor is the net wage for a profit maximizing firm. Therefore, wf = ∂Y ∂L f = AK γ αLαf −1 Lβs , ws = ∂Y ∂Ls = AK γ Lαf βLβs −1 and wf/ws = αLs/βLf Let the parameters in 2008 be denoted with subscript 0, and that of 2009 with subscript 1. For example, Y0 and Y1 are the GDP for 2008 (actual) and 2009 (forecasted) respectively. Taking the difference between the logarithms of the Cobb Douglas production function for these years, we can say that: ln(Y1/Y0)= ln(A1/A0)+ γln(K1/K0)+ αln(Ls1/Ls0)+ βln(Lf1/Lf0), hence αln(Ls1)+ βln(Lf1)= ln(Y1/Y0) - ln(A1/A0)- γln(K1/K0)+ αln(Ls0)+ βln(Lf0)……(1) In the current period, a firm is indifferent to paying the same net wage to local or foreign workers. Therefore wf0/ws0 =1, and hence αLs0 = βLf0. If the JCS is not introduced in 2008, in the next period αLs1 = βLf1. Let us denote the variables after introducing the JCS with an asterisk (*) superscript. With the JCS, the wage ratio changes to a new value θ, where wf1*/ws1* =θ >1, and αLs1* = βθLf1*. Substituting this result into equation (1) to eliminate Lf1*, since we are interested in the effect on local workforce, we obtain after some algebraic manipulation: (α+β)ln(Ls1∗) = ln(Y1/Y0) -ln(A1/A0) -γln(K1/K0) +αln(Ls0)+βln(Lf0)–αln(α/θβ) ......(2) We obtain the case without JCS by letting θ =1: (α+β)ln(Ls1) = ln(Y1/Y0) - ln(A1/A0)- γln(K1/K0)+ +αln(Ls0)+βln(Lf0)- αln(α/β) ......(3) Simplifying (2) and (3), we obtain ln(Ls1∗/Ls1) = (α/(α+β)).ln(θ) ......(4) Equation (4) shows that the incremental percentage of jobs saved by the JCS is independent of the contraction of the economy, but is dependent on the production function parameters and the change in the wage rate. To obtain the number of jobs saved by the JCS requires estimating Ls1 in equation (3) and then solving for Ls1* using equation (4). With the values of Ls1*, Ls1 and Ls0, we calculate the number of jobs saved by the JCS as (Ls1*- Ls1). Following the definition of Calmfors (1994), the cost of saving jobs, which is also known as the deadweight loss, is the wage subsidy received by the firms for the workers that will keep their jobs even if there is no subsidy. Therefore, the deadweight loss is (ws1*- ws1).Ls1. This deadweight loss is a windfall received by firms because vulnerable workers cannot be easily targeted. 5. Data Specification We group the required data to estimate equations (3) and (4) into three groups as follows: a. Production Function Parameters: α, β, γ We obtained the parameters from earlier study of Singapore’s economy. The parameters are factor cost shares in the Cobb Douglas case. Specifically, Young (1995) using a Cobb Douglas production function showed that the labor cost share was 0.51, and hence the assumed capital cost share was 0.49. Ho, Wong, Toh and Ping (2005) obtained a labor cost share of 0.529. We assumed the capital cost share was 0.49, which is γ = 0.49. We decomposed the labor cost share into two components. Given that α + β + γ =1 for a Cobb Douglas function and αLs0 = βLf0, we could determine α and β once γ was fixed. b. Labor Inputs (Lf0, Ls0) and Wage Ratio (θ) We used two sets of labor inputs (Lf0, Ls0) because there was no obvious way to reconcile the discrepancies in official data. For the first set, we used the Labor Force Survey data which was reported in the Yearbook of Statistics 2008 (Singapore Department of Statistics, 2008). We used the number of local workers employed in 2007 to proxy for Lf0, and the Yearbook reported 1,842,100 residents were employed. We used the total number of foreign workers employed in 2007 to proxy for Ls0. The Yearbook did not report a direct figure. We subtracted the 1,842,100 resident workers from the total employment of 2,670,800 to obtain 828,700 foreign workers employed in 2007. For the second set, we used the number of active CPF members from the Yearbook of Statistics 2008 (Singapore Department of Statistics, 2008) to proxy for the number of local workers. The number was only 1,545,000 in 2007. A discrepancy of about 19%, between the number of local workers and the number of active CPF contributors, was consistent with data from previous years. We removed the R pass holders from the foreign workforce in the second set because restrictions prevented R pass holders from competing in the local labor market. Yeoh (2007) estimated that there were about 580,000 R pass holders. Therefore, we have two sets of Lf0, Ls0. The high estimate was 1,842,100 local and 828,700 foreign workers. The low estimate was 1,545,000 local and 248,700 foreign workers To find the wage ratio θ, where wf1*/ws1* =θ, we need wf1* and ws1* on a net basis. The median gross wage was $2,500. The average monthly wage for CPF member’s earning gross wage below $2,500 was $1,357 as shown earlier using table 4. Therefore, the average monthly Jobs Credits would be $231, the average of 12% on $2,500 and $1,357. The employer’s CPF contribution was 14.5% for most workers in 2007. Therefore, the net wage before the Jobs Credits would be $2,500*1.145 = $2,862. This would be wf1*, the foreign worker’s net wage. After deducting the Jobs Credits, local worker’s net wage, ws1*, would be $2,631. Therefore, the wage ratio θ would be 1.088. c. Change in GDP (Y1/Y0), Productivity (A1/A0) and Capital (K1/K0) The Ministry of Trade and Industry forecasted the Singapore GDP to contract by 2% to 5% in 2009 (MTI press release 29 Jan 2009). The Economist Magazine forecasted a contraction of 7.5%, and there were speculations of a 10% contraction. At the peak of the Great Depression, the US GDP contracted 18.2% net of inflation from May 1937 to June 1938. We created four scenarios based on these forecasts. In the optimistic scenario, GDP contracted by 2%, the expected scenario had 5% contraction, the pessimistic scenario had 10% contraction, and the catastrophic scenario had 20% contraction. Using Table 4.14 of the Yearbook of Statistics 2008 (Singapore Department of Statistics, 2008) reproduced below, we found that the correlation between GDP growth and capital growth was 0.473, and the correlation between GDP growth and TFP growth was 0.324. We estimated the capital growth rate and TFP growth rate for each scenario using the correlation with GDP growth rate. Year %GDP Growth %Capital Growth %Labor Growth % TFP Growth 2002 4.1 1.7 -0.7 3.1 2003 3.4 1.4 -0.6 2.6 2004 8.6 1.7 0.8 6.1 2005 7.0 1.6 1.9 3.5 2006 7.9 2.1 2.9 2.9 2007 7.4 2.8 3.7 0.9 Table 4: Component of Singapore GDP Growth Rate for 2002 to 2007 In summary, we had four GDP growth forecasts, and in each forecast two estimates for the size of the labor force, with θ = 1.088 and γ = 0.490, giving eight possible scenarios. These scenarios are tabulated as follows: Scenario Name Ls0 Lf0 Y1/Y0 A1/A0 K1/K0 α β Optimistic, High 0.980 0.994 0.991 0.158 0.352 1,842,100 828,700 Expected, High 0.950 0.984 0.976 0.158 0.352 1,842,100 828,700 Pessimistic, High 0.900 0.968 0.953 0.158 0.352 1,842,100 828,700 Catastrophic, High 0.800 0.935 0.905 0.178 0.332 1,545,000 828,700 Optimistic, Low 0.980 0.994 0.991 0.071 0.439 1,545,000 248,700 Expected, Low 0.950 0.984 0.976 0.071 0.439 1,545,000 248,700 Pessimistic, Low 0.900 0.968 0.953 0.071 0.439 1,545,000 248,700 Catastrophic, Low 0.800 0.935 0.905 0.071 0.439 1,545,000 248,700 Table 5: Table of Parameters for the Scenarios 5. Result and Discussion We summarized the numerical result, which forms the raw data for our analysis, in Appendix A. The table below shows the job losses under the eight scenarios, with and without the JCS, the number of jobs saved for local workers, and the ratio of number of job saved to number of local job loss without JCS expressed in percentage. Job Loss without JCS Job Loss with JCS Job Saved Local Foreign Total Local Foreign Total Local Ratio High Estimate Optimistic Expected Pessimistic Catastrophic Low Estimate Optimistic Expected Pessimistic Catastrophic 32.4 82.0 167.7 350.0 14.6 46.9 36.9 118.9 75.4 243.1 157.4 507.4 -15.8 35.2 123.1 310.2 60.8 45.0 81.8 117.0 118.2 241.3 195.5 505.7 48.2 46.9 44.6 39.7 N.A. 57% 27% 11% 27.2 68.8 140.7 293.5 4.4 31.5 11.1 79.9 22.6 163.3 47.2 340.8 9.3 51.4 124.1 278.7 21.6 30.8 27.8 79.2 38.5 162.6 61.4 340.2 17.9 17.4 16.6 14.8 66% 25% 12% 5% Table 6: Job Loss with and without JCS (in ‘000) by Group We can draw three inferences by examining Table 6. First, the effects of the JCS on total employment is small: comparing total job loss with and without JCS shows savings of less than 2,000 jobs using the Labor Force Survey data in the High estimate, and less than 1,000 jobs using the CPF data in the low estimate. For example, if the economy shrinks by 2% (Optimistic) and using the data from the Labor Force Survey (High), the total job loss is nearly 47,000 without the JCS and nearly 45,000 with JCS, giving a reduction slightly less than 2,000 jobs. Second, despite the small effect on total employment, the JCS has a clear substitution effect shifting the job loss to the foreign workers. In fact, in the “Optimistic, High” scenario, the demand for local workers increases more than 15,000 while foreign workers faced a job loss of more than 60,000. If the JCS has not been implemented, the local workers would face a job loss of more than 32,000, and foreign workers would have a smaller job loss of less than 15,000. The “Optimistic, High” scenario is an unusual case where there is net job gain for local workers. Third, job loss increases rapidly with economic contraction, but the job saved by the JCS decreases slowly. Therefore, the effectiveness of the JCS in reducing job loss, which is measured by the ratio of number of job saved to number of job loss without JCS, decreases as the economic contraction becomes more severe. For example, accounting for the fact that R pass holder cannot enter the local labor market and hence using the “Low Estimate”, we can see that there is decreasing effectiveness: 66% of the job loss is saved by JCS if the economy contracts by 2%, 25% if the contraction is 5%, 12% if the contraction is 10%, and 5% if the contraction is 20%. The “High Estimate” data has an anomaly that there is actually job gain for local worker in the 2% contraction scenario. Next, we explore the question on the economic cost of the JCS using the following table: Job Saved DWL Spend %DWL High Estimate Optimistic Expected Pessimistic Catastrophic Low Estimate Optimistic Expected Pessimistic Catastrophic 48,184 46,862 44,581 39,728 5,026 4,888 4,650 4,144 5,159 5,018 4,774 4,254 97.4% 97.4% 97.4% 97.4% 17,928 17,436 16,587 14,782 4,215 4,099 3,900 3,475 4,265 4,148 3,946 3,516 98.8% 98.8% 98.8% 98.8% Table 7: Job Saved, Deadweight Loss (DWL) in S$m, JCS Spending in S$m under eight Scenarios We can draw two inferences from Table 7 above. First, the JCS spending exceed the budget of S$4.5 in the “High Estimate” for most cases, but is within budget for the “Low Estimate”. Given that the administration of JCS is tied to CPF payment, “Low Estimate” is more likely to occur. Second, most of the spending would become deadweight loss, which is a windfall to firms. Therefore, the scheme effectively becomes a corporate tax credit with three differences from the traditional one: First, there is a substitution effect on the choice of labor between local and foreign workers. Second, the stimulus is administered in quarterly installments instead of one lump sum at the end of the financial year. The effect of the JCS is therefore quicker and could save firms on the verge of bankruptcy. The economic cost of bankruptcy would consist of the loss of firm specific human capital and the worker’s search cost for the placement in a new job. Third, the benefit would accrue primarily to labor intensive industries rather than profitable firms. The size of the JCS stimulus to the firm would be ten times as large as the $0.5b corporate tax cut from 18% to 17% in the Resilience Package. 6. Limitation There are two limitations in our model that arise mainly due to the lack of available data. First, we have modeled the economy as one big firm. Our result would be the same if the economy comprises many homogeneous firms, but this scenario is unrealistic. Modeling heterogeneous firms is an area of further research. Second, our model is static, while reality is dynamic. A dynamic model would have smaller job losses in economic contractions compared to our model, and therefore smaller effect of the JCS. In other words, the actual job loss may be less severe than our model’s prediction. The following figure explains the rationale: Is o q u a n t 2 Lf Is o q u a n t 1 A C X E Y B2 Z Ls F B1 D Figure 2: A Dynamic Model with Rehiring Cost Suppose isoquant 1 is the long run equilibrium and the initial isocost line is AB1 in Figure 2 above. The firm maximizes profit by using the combination of labor at X, and the isocost AB1 is tangent to isoquant 1. In view of the economy contracting to isoquant 2, the government implemented JCS, which shifted the isocost line to AB2. In our static model, we argue that a new equilibrium is established at Z, the new tangent of the isocost EF and isoquant 2. However, in a multi-period model with positive cost for firm to rehire workers when the economy recovers, a profit maximizing firm may not choose Z. If the firm chooses Y, it responds to the incentive in JCS to change the labor mix, but uses more labor than needed to produce the output for isoquant 2. The perpendicular distance between isocost lines CD and EF is the cost of inefficiency in the current period. If the cost of this inefficiency is smaller than the time discounted cost of rehiring in the next period, the firm is better off choosing Y than Z. If the rehiring cost is even higher, the firm is better off not changing the worker mix and stays at X. So, what is the cost of rehiring? There is a smaller direct cost of rehiring in the recruitment process. There is a larger indirect cost that arises from training and accumulation of human capital and social capital. Becker (1962) argues that firm-specific human capital (FSHC), where the investment is worth less when the worker joins another firm, should be jointly invested by the firm and the worker. The worker invests by accepting a wage lower than his alternative wage during training and receives a return from a wage higher than his alternative wage after training. The firm invests by paying a wage higher than the worker’s marginal product during training and receives a return from by paying a wage lower than the worker’s marginal product after training. Parsons (1972) argues that large investment in FSHC causes worker-job separation to be costly and reduces labor mobility. Since the worker’s wage is below his marginal product after training, the firm will not lay off the worker during a minor demand decline because the firm will suffer a capital loss. Retrenching worker has also a powerful and negative effect on the surviving workers. Firms can choose to reduce wage cost by other means, such as mandatory unpaid leave or temporary wage cut, instead of retrenching workers. This is not an altruistic motive but arises because of rehiring cost. Hence, our model’s prediction of job loss is bias upwards. 7. Conclusion In conclusion, the JCS is effectively a fast-acting corporate tax cut that favors firms with large labor force. It has a substitution effect that can save 5% to 66% of the local workers from job loss that would have occurred without it, but JCS is less effective in more serious economic contractions. Our model’s prediction of job loss is bias upwards for two reasons. First, rehiring cost in the more realistic multi-period models can cause profit maximizing firms to retain workers and suffer temporary inefficiency when rehiring cost is high enough. 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Appendix A: Outcome of the Scenarios – Job Saved, Deadweight Loss and Budget Size Scenario Names Budget Ls0 Lf0 Ls1 Lf1 Ls1* Lf1* Job Saved Deadweight Loss Optimistic, High Labor 1,842,100 828,700 1,809,721 814,134 1,857,905 767,942 48,184 $5,025,667,082 $5,159,475,634 Optimistic, Low Labor 1,545,000 248,700 1,517,843 244,329 1,535,771 227,141 17,928 $4,215,110,820 $4,264,896,331 Expected, High Labor 1,842,100 828,700 1,760,066 791,796 1,806,928 746,872 46,862 $4,887,774,657 $5,017,911,819 Expected, Low Labor 1,545,000 248,700 1,476,197 237,625 1,493,633 220,908 17,436 $4,099,458,143 $4,147,877,658 Pessimistic, High Labor 1,842,100 828,700 1,674,397 753,256 1,718,978 710,519 44,581 $4,649,868,686 $4,773,671,593 Pessimistic, Low Labor 1,545,000 248,700 1,404,345 226,059 1,420,932 210,156 16,587 $3,899,922,436 $3,945,985,195 Catastrophic, High Labor 1,842,100 828,700 1,492,143 671,266 1,531,872 633,180 39,728 $4,143,741,818 $4,254,069,080 Catastrophic, Low Labor 1,545,000 248,700 1,251,486 201,453 1,266,267 187,281 14,782 $3,475,425,388 $3,516,474,328