Intergenerational Persistence and Misallocation. Section 6

(1) - (2) +10% (3) +25% (4) -10% (5) -25% 1.719 - 1.702 (-0.024) 1.675 (-0.061) 1.735 (0.022) 1.758 (0.054) - (-0.000) (-0.001) (0.000) (0.000) Sorting along comparative advantage (sons) 0.726 0.728 0.733 0.724 0.721 Sorting along preferences (sons) 0.524 0.521 0.516 0.526 0.529 Sorting along comparative advantage (fathers) 0.656 0.656 0.656 0.656 0.656 Sorting along preferences (fathers) 0.594 0.594 0.594 0.594 0.594 Output per worker (=1 in baseline) 1.000 1.001 1.004 0.999 0.997 Log Wage Variance (rel. change from baseline) 0.166 (0.002) (0.002) (-0.002) (-0.005) Welfare CV (rel. change from baseline) 0.190 (-0.000) (-0.001) (0.000) (0.001) Unemployment Rate (rel. change from baseline) 0.061 (0.026) (0.075) (-0.022) (-0.048) Average UE Rate (rel. change from baseline) 0.125 (-0.013) (-0.037) (0.012) (0.026) Average EU Rate (rel. change from baseline) 0.005 (0.025) (0.072) (-0.021) (-0.046) Equilibrium Tightness 1.564 (-0.027) (-0.073) (0.023) (0.054) 1.616 - 1.611 (-0.008) 1.599 (-0.026) 1.543 (-0.119) 1.549 (-0.108) - (-0.002) (-0.009) (0.001) (0.002) Sorting along comparative advantage (sons) 0.997 0.997 0.995 0.939 0.942 Sorting along preferences (sons) 0.253 0.254 0.256 0.311 0.308 Sorting along comparative advantage (fathers) 0.781 0.778 0.777 0.783 0.786 Sorting along preferences (fathers) 0.469 0.472 0.472 0.466 0.464 Output per worker (=1 in baseline) 1.000 1.000 0.999 0.986 0.986 Log Wage Variance (rel. change from baseline) 0.022 (0.013) (0.034) (0.176) (0.153) Welfare CV (rel. change from baseline) 0.091 (-0.001) (-0.002) (0.008) (0.011) Unemployment Rate (rel. change from baseline) 0.083 (0.085) (0.293) (-0.107) (-0.149) Average UE Rate (rel. change from baseline) 0.092 (-0.045) (-0.135) (0.056) (0.086) Average EU Rate (rel. change from baseline) 0.005 (0.082) (0.272) (-0.123) (-0.163) Equilibrium Tightness 0.850 (-0.087) (-0.251) (0.115) (0.179) Change in b (∆% from baseline) Baseline Economy Occupational Persistence (rel. change from baseline) Welfare (rel. change from baseline) Restricted Model Occupational Persistence (rel. change from baseline) Welfare (rel. change from baseline) Table 13. Policy Experiment: eect of changes in unemployment benets. 68 relationship between persistence and misallocation, and to derive welfare implications. A simple model of occupational persistence and search frictions in which both abilities and contacts are transmitted across generations delivers clearcut testable predictions on employment prospects and wages, which are conrmed in UK data. We have extended our theory to a more complete dynamic model of occupational choice, allowing for mobility over the lifecycle and accumulation/depreciation of human and social capital. We have found that all channels are quantitatively relevant, and that a model based only on transmission of ability (restricted model) would be at odds with several dimensions of the data. We have also studied how changes in search frictions can cause at the same time large dierentials in both output per worker and unemployment rates. Importantly, the restricted model would largely understate the harmful eects of frictions on the allocation of workers to occupations. When we study the cost of increasing unemployment benets, the restricted model overstates such costs by almost an order of magnitude. Hence, we conclude that modeling multiple sources of intergenerational transmission is crucial not only to understand the consequences of persistence, but also for the assessment of labor market policy in general. 69 References Abbott, Brant, Gallipoli, Giovanni, Meghir, Costas, & Violante, Giovanni L . 2013. cation policy and intergenerational transfers in equilibrium. Edu- Tech. rept. National Bureau of Economic Research. Acemoglu, Daron, & Shimer, Robert . 2000. Productivity gains from unemployment insurance. European Economic Review, 44(7), 11951224. Aina, Carmen, & Nicoletti, Cheti nepotism versus abilities. . 2014. The intergenerational transmission of liberal professions: University of York Discussion Papers in Economics. Andres, Lesley, Anisef, Paul, Krahn, Harvey, Looker, Dianne, & Thiessen, Victor . 1999. The persistence of social structure: Cohort, class and gender eects on the occupational aspirations and expectations of Canadian youth. Journal of youth studies, 2(3), 261282. Arulampalam, Wiji . 2001. Is unemployment really scarring? Eects of unemployment experiences on wages. The Economic Journal, 111. Becker, Gary S, & Tomes, Nigel . 1979. An equilibrium theory of the distribution of income and intergenerational mobility. The Journal of Political Economy, 11531189. Bentolila, Samuel, Michelacci, Claudio, & Suarez, Javier pational Choice. . 2010. Social Contacts and Occu- Economica. Björklund, Anders, & Jäntti, Markus family background. . 2009. Intergenerational income mobility and the role of Oxford Handbook of Economic Inequality, Oxford University Press, Oxford. Black, Sandra E, & Devereux, Paul J . 2010. Recent developments in intergenerational mobility. Tech. rept. National Bureau of Economic Research. 70 Blau, Peter M, & Duncan, Otis Dudley . 1967. The American occupational structure. Calvó-Armengol, Antoni, & Jackson, Matthew O . 2007. and employment dynamics and inequality. ERIC. Networks in labor markets: Wage Journal of economic theory, 132(1), 2746. Carrillo-Tudela, Carlos, & Visschers, Ludo . 2014. Unemployment and Endogenous Realloca- tion over the Business Cycle. Celik, Murat Alp Innovation. . 2015. Does the Cream Always Rise to the Top? The Misallocation of Talent and Tech. rept. Mimeo. Checchi, Daniele . 1997. study. Working Paper. Education and intergenerational mobility in occupations: a comparative American journal of Economics and Sociology, 331351. Chevalier, Arnaud, Denny, Kevin, & McMahon, Dorren . 2009. and education equality. Education and inequality across Europe, Intergenerational mobility 260281. Cingano, Federico, & Rosolia, Alfonso . 2012. People I know: job search and social networks. Journal of Labor Economics, 30(2), 291332. Constant, Amelie F, & Zimmermann, Klaus F . 2004. Occupational choice across generations. CEPR Discussion Paper. Corak, Miles . 2006. Do poor children become poor adults? Lessons from a cross country comparison of generational earnings mobility. Research on Economic Inequality, 13. Corak, Miles, & Piraino, Patrizio of Labor Economics, 29(1), . 2011. The intergenerational transmission of employers. Journal 3768. Di Pietro, Giorgio, & Urwin, Peter . 2003. Intergenerational mobility and occupational status in Italy. Applied Economics Letters, 10(12), 793797. 71 Dustmann, Christian . 2004. Parental background, secondary school track choice, and wages. Oxford Economic Papers. Dustmann, Christian, Glitz, Albrecht, & Schönberg, Uta . forthcoming. Referral-based job search networks. Review of Economic Studies. Eberharter, Veronika B. 2008. Parental Background and Intergenerational Occupational Mobility - Germany and the United States compared. The Journal of Income Distribution, 17(2). Ermisch, John, & Francesconi, Marco . 2002. Intergenerational mobility in Britain: new evidence from the BHPS. Generational income mobility in North America and Europe (Cambridge University Press: Cambridge). Ermisch, John, Jantti, Markus, & Smeeding, Timothy M . 2012. intergenerational transmission of advantage. Escriche, Luisa . 2007. Russell Sage Foundation. Persistence of Occupational Segregation: the Role of the Intergenerational Transmission of Preferences*. Galenianos, Manolis From parents to children: The The Economic Journal, 117(520), . 2014. Hiring through referrals. 837857. Journal of Economic Theory, 152, 304323. Gayle, George-Levi, Golan, Limor, & Soytas, Mehmet A . 2015. What is the source of the intergenerational correlation in earnings? Working Paper. Golosov, Mikhail, Maziero, Pricila, & Menzio, Guido residual income inequality. Granovetter, Mark S . 2013. Taxation and redistribution of Journal of Political Economy. . 1973. The strength of weak ties. American journal of sociology, 13601380. Güell, Maia, Pellizzari, Michele, Pica, Giovanni, & Mora, José Vicente Rodriguez 2015. Correlating Social Mobility and Economics Outcomes. 72 Working Paper. . Hellerstein, Judith K, & Morrill, Melinda Sandler impact of fathers on womenâs occupational choices. . 2011. Dads and daughters the changing Journal of Human Resources, 46(2), 333372. Hensvik, Lena, & Skans, Oskar Nordstrom . 2013. Social networks, employee selection and labor Journal of Labor Economics, forthcoming. market outcomes: Toward an empirical analysis. Hertz, Tom . 2006. Understanding mobility in America. Center for American Progress Discussion Paper. Hobijn, Bart, & “ahin, Ay³egül Letters, 104(3), . 2009. Job-nding and separation rates in the OECD. Economics 107111. Horváth, Gergely . 2014. Occupational mismatch and social networks. & Organization, 106, Journal of Economic Behavior 442468. Hout, Michael, & Beller, Emily comparative perspective. . 2006. Intergenerational social mobility: The United States in The Future of Children, 16(2), 1936. Hsieh, Chang-Tai, Hurst, Erik, Jones, Charles I, & Klenow, Peter J of talent and us economic growth. . 2013. The allocation Tech. rept. National Bureau of Economic Research. Kambourov, Guergoui, & Manovskii, Iourii . 2009. Occupational Mobility and Wage Inequality. The Review of Economic Studies, 76(2). Keane, Michael P., & Wolpin, Kenneth I. 1997. The Career Decisions of Young Men. Journal of Political Economy, 105(3). Kramarz, Francis, & Skans, Oskar Nordström . 2014. When strong ties are strong: Networks and youth labour market entry. The Review of Economic Studies, 81(3), Laband, David N, & Lentz, Bernard F 11641200. . 1983. Like father, like son: Toward an economic theory of occupational following. Southern Economic Journal, 73 474493. Lee, Sang Yoon, & Seshadri, Ananth status. . 2014. On the intergenerational transmission of economic Unpublished manuscript, University of WisconsinMadison, Department of Economics. Lentz, Bernard F, & Laband, David N . 1989. Why so many children of doctors become doctors: Nepotism vs. human capital transfers. Journal of Human Resources, Lo Bello, Salvatore, & Morchio, Iacopo Evidence from the UK. . 2013. Parental Links and Labor Market Outcomes: Working paper. Long, Jason, & Ferrie, Joseph the United States since 1850. McCall, Brian P. 396413. . 2013. Intergenerational occupational mobility in Great Britain and The American Economic Review, 103(4), 1991. A Dynamic Model of Occupational Choice. 11091137. Journal of Economic Dynamics and Control. Miller, Robert A. 1984. Job Matching and Occupational Choice. Journal of Political Economy, 92(6). Montgomery, James D . 1991. analysis. Social networks and labor-market outcomes: Toward an economic The American economic review, 81(5), Mora, José V Rodríguez . 2009. 14081418. The misallocation of talent. CREI, Centre de Recerca en Economia Internacional. Munshi, Kaivan, & Rosenzweig, Mark and the rural-urban wage gap. Papageorgiou, Theodore Studies, . 2016. Networks and misallocation: Insurance, migration, The American Economic Review, 106(1), 4698. . 2013. Learning your comparative advantages. The Review of Economic rdt048. Pellizzari, Michele . 2010. Do friends and relatives really help in getting a good job? Labor Relations Review, 63(3), 494510. 74 Industrial & Pellizzari, Michele, Pica, Giovanni, et al. 2011. Liberalizing professional services: Evidence from U. of Bocconi working paper (May 2011). italian lawyers. Petrongolo, Barbara, & Pissarides, Christopher A . 2001. survey of the matching function. Journal of Economic literature, 39(2), Restuccia, Diego, & Urrutia, Carlos of Early and College Education. Sinha, Rishabh . 2014. Looking into the black box: A 390431. . 2004. Intergenerational Persistence of Earnings; The Role The American Economic Review, 94(5). Intergenerational Occupational Mobility and Labor Productivity. Working Paper. Solon, Gary . 1992. Intergenerational income mobility in the United States. Review, The American Economic 393408. Solon, Gary . 2002. Cross-country dierences in intergenerational earnings mobility. Economic Perspectives, 16(3), 5966. Stier, Haya, & Grusky, David B . 1990. American Sociological Review, An overlapping persistence model of career mobility. 736756. Topa, Giorgio . 2001. Social interactions, local spillovers and unemployment. Studies, 68(2), The Journal of The Review of Economic 261295. Wiczer, David . 2014. Long Term Unemployment: Attached and Mismatched? 75 Working Paper. 7 Appendix Proofs Lemma 1 Proof. Taking the derivative of m∗ w.r.t. µ: −ρ(1 + µ(1 − 2ρ)) − (1 − µρ)(1 − 2ρ) ∂m∗ = ∂µ [1 + µ(1 − 2ρ)]2 The numerator can be simplied to: ∂m∗ ∂µ (1 + µ)(ρ − 1), which is clearly nonpositive, ∀ ρ ≤ 1. Therefore, ≤ 0. Taking the derivative of m∗ w.r.t. ρ: ∂m∗ −µ(1 + µ(1 − 2ρ)) − (1 − µρ)(−2µ) = ∂ρ [1 + µ(1 − 2ρ)]2 The numerator can be simplied to: ∂m∗ ∂ρ (1 + µ)µ, which is clearly nonnegative, ∀ µ ≥ 0. Therefore, ≥ 0. Lemma 2 Proof. Taking the derivative of Ψ∗ w.r.t. µ: ∂Ψ ∗ (1 − 2ρ)[1 + µ(1 − 2ρ) − ρ − µ + 2µρ] = ∂µ [1 + µ(1 − 2ρ)]2 The numerator can be simplied to: ∂Ψ ∗ ∂µ (1 − 2ρ)(1 − ρ), ≤ 0. 76 which is clearly nonpositive, ∀ρ≥ 1 . Therefore, 2 Taking the derivative of Ψ∗ w.r.t. ρ: ∂Ψ ∗ (1 − 2µ)[1 + µ(1 − 2ρ)] + 2µ[ρ + µ − 2ρµ] = ∂ρ [1 + µ(1 − 2ρ)]2 The numerator can be simplied to: 1 − µ, which is clearly nonnegative, ∀ µ ≤ 1. Therefore, ∂Ψ ∗ ∂ρ ≥ 0. Lemma 3 Proof. Taking the derivative of γ∗ w.r.t. µ: ∗ ∗ [(1 − Ψ ∗ )(1 + N ) − µ(1 + N ) ∂Ψ U ∗ − (1 − Ψ ∗ )µ(1 + N ) ∂U ∂γ ∗ ∂µ ∂µ =− ∗ 2 ∂µ (U ) h − (1 − Ψ )[(1 + N )U − µ(1 + The numerator can be rearranged to: second term is clearly nonpositive, as that: ∗ U ∗ ≥ µ ∂U ∂µ ∗ ∂Ψ ∗ ∂µ ≤ 0. ∂Ψ ∗ ∂µ ≤ 0. ∗ N ) ∂U ] ∂µ − µ(1 + Cancelling terms yields: 1 + µN + Ψ (1 − µ)n, while the righthand side is: ∗ 1 + Ψ ∗ n ≥ µ ∂Ψ (1 − µ)n, ∂µ which is always satised, Hence, the whole term in square brackets is non-negative, and therefore Taking the derivative of γ∗ w.r.t. i ∗ N ) ∂Ψ U ∗ . The ∂µ For what concerns the rst term, it suces to show . The lefthand side reads as follows: µN + µ ∂Ψ (1 − µ)n − µΨ n. ∂µ as ∗ ∂γ ∗ ∂µ ≤ 0. ρ: −µ(1 + N ) ∂γ ∗ =− ∂ρ The numerator can be rearranged to: ∂Ψ ∗ ∂ρ ∗ − (1 − Ψ ∗ )µ(1 + N ) ∂Ψ [(1 − µ)n] ∂ρ (U ∗ )2 ∂Ψ ∗ [−µ(1 + N ) − (1 − Ψ ∗ )µ(1 + N )(1 − µ)n]. The term in square ∂ρ brackets is nonpositive, and the fact that ∂Ψ ∗ ∂ρ ≥0 completes the claim that 77 ∂γ ∗ ∂ρ ≥ 0. Lemma 4 Evaluating the freeentry condition at equilibrium: q(θ∗ )(1 − β)(1 + γ ∗ a) = κ Given that q 0 (θ) < 0, The fact that ∂γ ∗ ∂µ ≤ 0, this implies that ∂γ ∗ ∂ρ ≥0 θ∗ adjusts to the new equilibrium in the same direction as (shown in Lemma 3) completes the claim that ∂θ∗ ∂µ ≤0 and ∂θ∗ ∂ρ γ ∗. ≥ 0. Proposition 1 Evaluating persistence at equilibrium: P ∗ = µ + (1 − µ)Ψ ∗ Now take the derivative of P∗ w.r.t. µ: ∂P ∗ ∂Ψ ∗ = (1 − µ) + (1 − Ψ ∗ ) ∂µ ∂µ The rst term is negative, while the second one is always positive. We can show that even in the case µ = 0 (that is, when we make the negative term as large as possible), the sum of the two is still positive. To see this, using some of the expressions derived earlier: (1 − Ψ ∗ ) = 1−ρ (1 − 2ρ)(1 − ρ) ∂Ψ ∗ ≥− = − , [1 + µ(1 − 2ρ)] [1 + µ(1 − 2ρ)]2 ∂µ where the inequality follows from the fact that derivative of P∗ w.r.t. 1 ≥ −(1 − 2ρ)(1 − µ). ρ: ∂P ∗ ∂Ψ ∗ = (1 − µ) , ∂ρ ∂ρ 78 Hence, ∂P ∗ ∂µ ≥ 0. Now take the which is clearly positive, given that ∂Ψ ∗ ∂ρ ≥ 0. Proposition 2 We focus on equilibria in which ηV (θ) ≥ (1 − β), so that the indirect eect (GE eect) of an increase in µ (ρ) is negative (positive). Here we provide a sucient condition for the direct eect of an increase in µ (ρ) to be also negative (positive). Look at the direct eect of µ: ∂W ∂U ∂γ = 2 [p(θ)(1 + γa)y − κθ] + 2p(θ)ayU ∂µ ∂µ ∂µ Substituting away  Replacing ∂U ∂µ ∂γ with the expression found in Lemma 3 and regrouping terms: ∂µ    ∂U ∂Ψ ≤ a (1 − Ψ )(1 + N ) − µ(1 + N ) U (1 + γa)β + a(1 − Ψ )µ(1 + N ) ∂µ ∂µ 2 = N + ∂Ψ (1 − µ)n − Ψ n ∂µ and dening A ≡ [U 2 (1 + γa)β + a(1 − Ψ )µ(1 + N )], one can get:   ∂Ψ ∂Ψ − A (1 − µ)n + (Ψ n − N ) −a(1 − Ψ )(1 + N ) ≤ −aµ(1 + N ) ∂µ ∂µ One can easily verify that (1 − µ)n ∂Ψ ≤ N − Ψn ∂µ if the following condition is satised: ρ + µ − 2ρµ N (1 − 2ρ)(1 − ρ)(1 − µ)n + ≤ 2 n [1 + µ(1 − 2ρ)] [1 + µ(1 − 2ρ)] Hence, dW dµ Turning to dW dρ ≥ 0, ≤ 0. ∂W , in the text we have already shown that it has to be nonnegative. As a consequence, ∂ρ being the sum of two positive components. 79 Additional Empirical Evidence Figure 4. Plot of Average Persistence Index (weighted average of occupationspecic likelihood ratios, by region) vs. Average Regional Wage. Source: BHPS. 80 Occupational code 11 12 13 14 16 17 19 21 22 23 25 31 32 34 36 37 38 39 40 41 42 43 44 50 51 52 53 54 57 58 59 61 62 71 72 80 82 84 85 86 87 88 89 90 92 94 95 99 Occupational sector Production Managers in Manuf., Construction Specialist Managers Oce Managers Managers in Transport and Storing Managers in Farming Managers in Service Industry Managers and Administrators NEC Engineers and Technologists Health Professionals Teaching Professionals Business and Financial Professionals Draughtspersons Computer Analyst/Programmers Health Associate Professionals Business and Financial Associate Professionals Social Welfare Associate Professionals Literary, Artistic and Sports Professionals Associate Professionals and Technical Occupations NEC Administrative/Clerical Ocers Numerical Clerks and Cashiers Filing and Record Clerks Clerks Stores and Despatch Clerks Construction Trades Metal Machining Electrical/Electronic Trades Metal Forming, Welding and Related Vehicle Traders Woodworking Trades Food Preparation Trades Other Craft and Related Occupations NEC Security and Protective Service Catering Occupations Sales Representatives Sales Assistants and Check-out Operators Food, Drink and Tobacco Process Operatives Chemicals, Paper, Plastics Operatives Metal Working Process Operatives Assemblers/Lineworkers Other Routine Process Operatives Road Transport Operatives Other Transport and Machinery Operatives Plant and Machine Operatives NEC Other Occupations in Agriculture, Forestry and Fishing Other Occupations in Construction Other Occupations in Communication Other Occupations in Sales and Services Other Occupations NEC Average (unweighted) Average (weighted) Likelihood Ratio 6.23 2.03 0.00 4.69 33.05 1.92 3.04 4.79 0.00 1.67 12.19 1.77 0.00 10.66 6.23 0.00 3.01 2.52 2.71 0.00 2.05 0.82 3.16 5.81 1.64 6.43 2.57 5.78 7.81 29.71 0.50 5.08 3.20 1.72 0.28 35.81 5.42 3.82 5.16 3.51 4.54 7.25 4.09 16.96 11.78 0.42 9.22 0.45 5.69 4.71 Table 14. Occupational Persistence (Likelihood Ratios), 2digit level. Occupation Share 0.0133 0.0210 0.0129 0.0084 0.0084 0.0301 0.0083 0.0144 0.0064 0.0112 0.0102 0.0109 0.0301 0.0066 0.0186 0.0051 0.0264 0.0056 0.0088 0.0380 0.0188 0.0285 0.0276 0.0424 0.0363 0.0541 0.0360 0.0317 0.0322 0.0103 0.0185 0.0059 0.0268 0.0166 0.0534 0.0086 0.0120 0.0088 0.0132 0.0148 0.0320 0.0055 0.0138 0.0108 0.0096 0.0080 0.0336 0.0120 In the table we report the likelihood ratios of the occupations that employ at least 0.5% of the workforce, due to the limited size of the sample. Averages are taken with respect to all occupations, including the ones not reported in the table. 81 Occupational sector Managers & Administrators 1.49 0.82 1.51 Professional 2.93 2.61 2.35 Associate Professional & Technical 1.40 1.84 1.60 Clerical & Secretarial 1.43 1.45 1.01 Craft & Related 1.64 1.57 1.46 Personal & Protective Service 1.81 2.72 0.50 Sales 0.99 1.56 1.47 Plant & Machine 2.49 1.48 1.88 Agriculture & Elementary 3.02 2.31 2.72 Average (unweighted) 1.91 1.82 1.61 Average (weighted) 1.79 1.63 1.65 Table 15. Figure 5. Likelihood Ratio Bottom 33% Mid 33% Top 33% Occupational Persistence Indexes, by Father's Income (Likelihood Ratios). Plot of Average Persistence Index (weighted average of occupationspecic likelihood ratios, by region) vs. Herndahl index of occupations (at the 1digit level) . Source: BHPS. 82 Occupational sector (contemporaneous) Table 16. Figure 6. Likelihood Ratio <20 20-25 25-30 30+ Managers & Administrators 1.78 1.46 1.28 1.20 Professional 3.83 Associate Professional & Technical 2.05 2.36 2.62 2.33 0.91 1.86 2.27 Clerical & Secretarial 1.50 0.73 1.15 2.23 Craft & Related 1.32 1.48 1.73 1.68 Personal & Protective Service 1.19 1.53 2.69 0.61 Sales 1.55 1.45 0.98 1.49 Plant & Machine 1.27 2.07 2.06 1.89 Agriculture & Elementary 2.48 2.31 2.86 4.51 Average (unweighted) 1.88 1.59 1.91 2.03 Average (weighted) 1.62 1.49 1.83 1.92 Occupational Persistence Indexes, by Ospring's Age Group (Likelihood Ratios). Average marginal eect of πi,t (coecient of Column 1 of Table 4), by age group. The red line is the average marginal eect for the entire sample. Source: BHPS. 83 Dependent Variable: Job Finding Rate (1) (2) (3) POLS RE FE 0.0481*** 0.0497** 0.0564** (0.016) (0.020) (0.025) Average insample JF 0.125 0.125 0.125 N R2 4098 4098 4098 0.055 - 0.047 - 400 400 0.0821*** 0.0793** 0.0882** (0.025) (0.032) (0.039) Average insample JF 0.115 0.115 0.115 N R2 2093 2093 2093 0.084 - 0.074 - 212 212 Panel A Father in same occupation (πi,t ) Number of pairs Panel B Father in same occupation (πi,t ) Number of pairs Standard errors in parentheses ∗ p < 0.1, ∗∗ p < 0.05, ∗∗∗ p < 0.01 Table 17. Robustness Checks: Employed); coecient for Regressions of Job Finding Rate (transition from Unemployed to father in same occupation (dummy variable), standard errors and average job nding rate in the regression sample. Model 1 is a pooled OLS regression, model 2 is a random eects GLS regression, model 3 is a xed eects regression. All models include a third-degree polynomial in age and dummies for education, gender, region of residence, smoking behavior, marital status, ethnicity, quarter, occupation of search/employment. In Panel A, we exclude from the estimation the spells of selfemployment. In Panel B, we exclude all the workers who report having been selfemployed at least once in their life. 84 Figure 7. Wage proles by proportion of job spell with the father in the same occupation. In the upper graph, groups are dened with respect to the entire job spell length. In the lower graph, groups are dened with respect to the start of the job spell. Source: BHPS. 85 Dependent Variable: Log Hourly Wage Panel A Share of time in same occ. as father (qi ) (1) (2) (3) (4) (5) POLS RE POLS RE FE -0.134*** -0.155*** (0.016) (0.031) -0.0730*** -0.0316** -0.00698 (0.013) (0.013) (0.014) Father in same occupation (πi,t ) N R2 Number of pairs Panel B Share of time in same occ. as father (qi ) 6324 6324 4664 4664 4664 0.617 - 0.602 - 0.639 - 908 - 833 833 -0.0967*** -0.109*** (0.015) (0.029) -0.0504*** -0.0190 -0.00349 (0.012) (0.012) (0.012) 5664 4159 4159 4159 0.547 - 0.540 - 0.606 - 866 - 788 788 Father in same occupation (πi,t ) N R2 Number of pairs 5664 Standard errors in parentheses * p < 0.1, ** p < 0.05, *** p < 0.01 Table 18. Robustness Checks: Regressions of Log Hourly Wage; coecient for share of time spent in same occupation as father (from 0 to 1), standard errors and father in same occupation (dummy variable). Models 1 and 3 are pooled OLS regressions, models 2 and 4 are random eects GLS regressions, model 5 is a xed eects regression. All models include a third-degree polynomial in age and dummies for education and occupation, a second order degree occupational tenure and potential labor market experience polynomial, rm size, region of residence, smoking behavior, marital status, ethnicity, year. Panel A excludes from the estimating sample all wage observations above percentile 99 or below percentile 1. Panel B excludes from the estimating sample all wage observations above percentile 95 or below percentile 5. 86