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Problematic of the master thesis

Impact of the globalization on wages and umployment by Alexandre Desaunay Supervisor Lionel Fontagné. Problematic of the master thesis. To what extent the North -South trade is it responsible for disparity in wages in the Northern countries ?. Main References.

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Problematic of the master thesis

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  1. Impact of the globalization on wages and umploymentby Alexandre DesaunaySupervisor Lionel Fontagné

  2. Problematic of the master thesis To whatextent the North-South tradeisitresponsiblefor disparity in wages in the Northern countries ?

  3. Main References Biscourpand Kramarz (2007) " Employment, skill structure and international trade” Feenstra and Hanson (1996) “Globalization, Outsourcing and Wage Inequality” Grossman and Rossi-Hansberg (2008) ” Tradingtasks: A simple Theory of offshoring ”

  4. The main empiricalobjectives • Seewhatprecisely the sources of wideningwageinequalitybetweenskilled and unskilledworkers in developedcountries and more precisely the impact of outsourcing on wages and employementof unskilled and skilledworkers. • Exonerateor not the role of globalization in the rise in inequalitywages in the northern countries

  5. Contribution • Look the real wagesof skilled and unskilledworkersinstead of consideringthe ratio of unskilledwage to skilledwage • Take a longer period 1958-2005 instead of 1979-1997 (Feenstra and Hanson )

  6. Construction of the empiricalpart (1/4) • Benchmark USA • Average 100 industries • Period 1958-2005 • Macro data (NBER productivity)

  7. Construction of the empirical part (2/4)

  8. Construction of the empirical part (3/4) Interest variables: - real wagesskilled and unskilledworkers (source nberproductivity) - unskilledshareskilled for the employment part Explanatory variables: - proxy outsourcing  Feenstra and Hanson (1996) - GDP  source world bank - TFP(total productivity factor)  nberproductivity +BLS - Emp(employment)  nberproductivity - created variable openness-rate - prode production workers

  9. proxy outsourcing Construction • same method used by Feenstra and Hanson (1996) • Proxy outsourcing= dsimat1a - dsimat1b Wheredsimat1a = change in outsourcing (broad) dsimat1b = change in outsourcing (narrow)

  10. Construction of the empirical part (4/4) • Estimateequationsby Ordinary Least Squares First regression: Wages - Real wages production workers = β0+β1proxyoutsourcing+β2openness rate+β3tfp+β4gdp - Real wagesunproductionworkers= β0+β1proxyoutsourcing+β2openness rate+β3tfp+β4gdp Second regression: employment Production workersshareunproductionworker= β0+β1emp+ β2outsourcing+ β3openness_rate +β4simat1a+ β5simat1b+ β6ptfp+β7gdp+ β8prode

  11. Descriptive statistics (1/3) • real wages production workers Variable | Obs Mean Std. Dev. Min Max ---------------- |------------------------------------------------------------------- realwgpwork | 21952 418.3542 829.8488 3.461236 16352.61 • real wagesunproductionworkers Variable | Obs Mean Std. Dev. Min Max ---------------------|------------------------------------------------------------------- realwgunpr~s | 21952 670.3387 1310.836 3.749672 21558.19 1st observation the average wage of unskilled lower than those of qualified

  12. Descriptive statistics(2/3) • significance of the mean Variable | Obs Mean Std. Err. Std. Dev. [95% Conf. Interval] --------------------------------------------------------------------------------------------------- realwg~k | 21952 418.3542 5.600953 829.8488 407.3759 429.3325 Ha: mean < 670.3387 Ha: mean != 670.3387 Ha: mean > 670.3387 Pr(T < t) = 0.0000 Pr(|T| > |t|) = 0.0000 Pr(T > t) = 1.0000 - the wages difference is significant

  13. Descriptive statistics(3/3) First correlationbetweenreal wageunproductionworkers and openness _rate | realwg~sopenne~e -------------------|--------------------------- realwgunpr~s | 1.0000 | | openness_r~e | 0.0391 1.0000 0.0000 Secondcorrelationbetweenunproduction and outsourcing | unprowoutsourcing ---------------|-------------------------- Unprow | 1.0000 | | outsourcing | 0.0278 1.0000 | 0.0741 • Wecan observe a correlationbetweenskilledworkerswages and openness-rate and outsourcing • Be careful !! A correlationis not a causality,

  14. graph

  15. First regressionsestimated by MC0 skilled and unskilled Wages Robust lrealwgunpCoef. Std. Err. t P>|t| [95% Conf. Interval] ------------------------------------------------------------------------------------- loutsourcing.068935 .0143992 4.79 0.000 .0407029 .0971671 lopenness_~e .3620002 .0942176 3.84 0.000 .1772707 .5467298 cons 5.987788 .1628123 36.78 0.000 5.668567 6.307009 lrealwgpworkCoef. Std. Err. t P>|t| [95% Conf. Interval] ------------------------------------------------------------------------------------------------------ loutsourcing.0682394 .0136726 4.99 0.000 .0414319 .0950469 lopenness_~e .3407036 .0876146 3.89 0.000 .1689203 .512487 _cons 5.650848 .1515531 37.29 0.000 5.353702 5.947994

  16. Estimatesunskilledshareskilled Robust part Coef. Std. Err. t P>|t| [95% Conf. Interval] ----------------------------------------------------------------------------- emp .0178614 .0006887 25.94 0.000 .0165112 .0192116 outsourcing -.0000694 .0041664 -0.02 0.987 -.0082384 .0080996 openness_r~e-.1175274 .0617178 -1.90 0.057 -.238535 .0034803 simat1a -.0997868 .0334008 -2.99 0.003 -.1652743 -.0342993 ptfp .0008362 .0013092 0.64 0.523 -.0017307 .0034031 gdp .0010262 .0007716 1.33 0.184 -.0004866 .002539 prode-.0238617 .0008046 -29.66 0.000 -.0254392 -.0222842 _cons .3198838 .0248227 12.89 0.000 .271215 .3685526 - Some coefficients are significantsuch as: emp, openness-rate, simat1a, Prode - No instrumental variable

  17. Expectedresults - The wageinequalitybetweenskilled and unskilledfrom the factthatdeveloped countries have outsourced(= import of intermediategoods) a part of theirproduction ( negativesign and significant for the proxy outsourcing) For Nowwefind the opposite - openness rate has a impact negativeon the wages of unskilled.

  18. Challenges • Find an instrumental variable for outsourcing to correct the endogeneity problem • Have the expected signs of coefficients and significant by adding more controle variables( add education, growth rate…)

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