The Motivation

1. Job Chains and Welfare Gains from Employment: Testing an I-O Type Labor Market ModelJoseph PerskyDaniel FelsensteinFunded by the W.E. Upjohn Institute for Employment Research

2. The Motivation • What are the welfare and distributional effects of employment creation? • What is a job worth? • No policy guidance: what kind of jobs to promote? High wage or low wage? For locals or commuters? Service sector or manufacturing? • No adequate model of employment creation in local economic development efforts

3. A Job Chains Model of Local Labor Markets • Assume unemployment and underemployment – slack in labor market • Assume rigid wage structure • A new job, if filled by an employed worker, opens up a chain • Workers move from job to job to improve their welfare • New perspective on employment ‘multipliers’

4. Backward Linkages Suppliers: 30 Indirect Jobs Instrument Plant 100 Direct Jobs Forward Linkages Household-serving: 20 Induced Jobs Light Bulbs Inc. SciSource Supermarket Stores Horizontal Multipliers

5. Direct Indirect Induced ‘Horizontal’ Multipliers

6. Job Changer: Mr. Jones Job Changer: Ms. Dee New Job in SciSource Existing Similar Job in OptiSource Existing Related Job in InstruSource Vacancies In-Migrant to Local Area Ms. Black Terminates Chain Job Chains and Vertical Multipliers

7. Induced Indirect Direct Job Chains and ‘Vertical’ Multipliers Chain Termination Job Chains Vacancies

8. Housing Market Studies— Lansing J.B., Clifton C.W. and Morgan J.N. (1969) Emmi and Magnusson (1994,1995) Organizational Studies — Parishes: White (1970) Orchestras: Abbot and Hrycak (1990) Hermit Crabs Chase, Weissburg and DeWitt (1988) Labor Market Flows Schettkat (1996) Economic Development Webster (1979) Robson, Bradford and Daes (1999) Persky and Felsenstein (1999) Chain Literature

9. The Job Chains Model as an I-O Type Model • Job chains = production chains in I-O • Production chains: estimated by average ‘input vector’ for each industry • Job chains: estimate ‘input vector’ for each type of new job, by wage group. • Chain length=size of employment multiplier • Chains initiated by indirect and induced activity, not just direct.

10. (Q) : A square job flow matrix (origin-destination) qij, elements of Q which show the chance that a job vacancy of a j-type position is taken by a worker currently in an i-type position. tij elements of T matrix, probabilities that chain will terminate due to (1) unemployed, (2) out of labor force and (3) in-migrants. Leontief Model of Job Chains

11. A Job Chains Matrix: Q and T matrices

12. A Housing Chains Matrix Based on Marullo (1985).

13. Chains by Attributes

14. Assumptions of Chain Models

15. Chain Models: the Case Against • Mechanistic, lacking in theoretical basis • No formal maximizing behavior by firms and individuals • Little attention to short run price changes as allocation method • Often assume markets don’t clear, no real closure

16. Chain Models: the Case For • When markets are connected through institutional and structural links (wage agreements, banking regulations etc) not prices • In the presence of fixed mark-ups: suppliers working with fixed prices (flat supply curve). • When quantity changes represent welfare changes (firms receiving fixed mark-up, workers welfare gain through movement). Chains as modeling spread.

17. The Job Chains Model • Mechanics • Data • A supply-side example: • restricting access to employment

18. Mn = 1/(1- qnn) Mn-1 = [1/(1- q(n-1)(n-1))] * [ 1 + qn(n-1)Mn ] Mn-2 = [1/(1- q(n-2)(n-2)) * ( 1 + q(n-1)(n-2)Mn-1 + q(n(n-2)Mn ) 1. Chain Lengths

19. V/wj = wage gains of job changers + (wage- opportunity cost) of non-employed job recruits, as a share of new wages Vj = imij [(kqki *(wi-wk ) + hthi*(wi- chi)]. 2. Welfare Gains (Efficiency Effects)

20. 3. Distributional Effects • A Rawlsian measure(R/w): gains to lowest groups, as a share of new wages Rj = mnj h thn *(wn – chn)

21. Opp.Costs 1: $25.50 - $40.00 75% 2: $16.40 - $25.50 75% 3: $10.50 - $16.40 50% 4: $ 6.70 - $10.50 40% 5: $ 4.25 - $ 6.70 31% Opportunity Costs (w/c)for Unemployed, Out of Labor Force and In-Migrants

22. PSID 1987-1993 (heads and spouses only) 3500 distinct year-to-year job changes 1992 Real average wage gains for job changers Data for four regions and five earnings classes Data

23. Destination Job Group Origin Job Group 1 2 3 4 5 1: $25.50 - $40.00 41.1% 0.0% 0.0% 0.0% 0.0% 2: $16.40 - $25.50 25.0% 52.9% 0.0% 0.0% 0.0% 3: $10.50 - $16.40 4.8% 22.1% 46.6% 0.0% 0.0% 4: $ 6.70 - $10.50 2.2% 1.5% 18.5% 47.3% 0.0% 5: $ 4.25 - $ 6.70 0.0% 0.3% 2.4% 13.3% 34.5% Unemployed 2.9% 3.8% 9.7% 15.8% 24.7% Out of Labor Force 4.0% 3.8% 7.5% 13.5% 30.5% In-Migrant 20.1% 15.6% 15.4% 10.0% 10.2% Column Sum 100.0% 100.0% 100.0% 100.0% 100.0% Flows into Job Vacancies

24. Class of New Job Created Vacancies 1 2 3 4 5 1: $25.50 - $40.00 1.70 0.00 0.00 0.00 0.00 2: $16.40 - $25.50 0.90 2.12 0.00 0.00 0.00 3: $10.50 - $16.40 0.52 0.88 1.87 0.00 0.00 4: $ 6.70 - $10.50 0.28 0.37 0.66 1.90 0.00 5: $ 4.25 - $ 6.70 0.08 0.12 0.20 0.39 1.53 3.48 3.48 2.73 2.28 1.53 Total Job Multiplier Multiplier Effect

25. Efficiency and Distributional Effects Wage Group of Initial New Job 1 2 3 4 5 V/w 0.43 0.42 0.56 0.62 0.69 Per job Share to Job Changers 0.52 0.37 0.21 0.10 0 R/w Per initial new job: Dollars per yr to Lowest-R 397 550 960 7,202 1,888 Dollars per yr to Low 4,654 4,303 6,600 10,582 7,202

26. Wage Group of Initial New Job Alternative Opportunity Cost Assumptions 1 2 3 4 5 Basic Assumptions 0.43 0.42 0.56 0.62 0.69 1 .75 in-migs; .25 all others 0.41 0.39 0.47 0.54 0.62 2 .75 all in-migrants 0.51 0.51 0.57 0.63 0.67 3 .25 all non job-changers 0.74 0.72 0.74 0.74 0.75 4 Efficiency Effect: Sensitivity Analysis

27. A Supply-Side Example of the Job Chains Model • Simulation of three scenarios. New employment created but restricted: • Full local restriction: only locals can take jobs: no in-migrants • First round local restriction: no in-migrants on first round of hiring • First round restriction to local non-employed:only locals (local unemployed or out of labor force) can take jobs on first round

28. Base Case Summary

29. Case 1: Full Local Restriction • Exclude in-migrants from T-matrix • Recalibrate Q and T matrix • Recalculate Leontief inverse • Using new multipliers and q’s recalculate efficiency measure (V/w) • Using new multipliers and q’s recalculate distributional measure (R/w)

30. Case 1: Full Local Restriction – Chain Lengths, Welfare Gains and Distribution

31. Case 2: First Round Local Restriction • Exclude in-migrants from T-matrix for first round only • Use Resulting vacancies and Base Q and T matrices • Recalculate efficiency measure (V/w) • Recalculate distributional measure (R/w)

32. Case 2: First Round Local Restriction: – Chain Lengths, Welfare Gains and Distribution

33. Case 3: First Round Restriction to Local Non-employed • Limit first and only round to local non-employed • All chain lengths are thus 1.0 • Calculate efficiency measure (V/w) • Calculate distributional measure (R/w)

34. Case 3: First Round Restriction to Local Non-employed – Chain Lengths, Welfare Gains and Distribution

35. Comparing the Results Compared to the standard case: • Full local restriction: longest chains, greater efficiency, and more trickle down • First round local restriction: modest increases in chain length, efficiency and trickle down • First round restriction to local non-employed: no chains, lower efficiency and some (non-trickle down) distributional gains

36. Tentative Policy Conclusions • Full local restriction: dramatic returns, but unpalatable politically • First round local restriction: politically feasible, but only modest expected gains • First round restriction to local non-employed: politically feasible, but low return on high-end placements, and only modest gains on low-end placements