WPS8676 Policy Research Working Paper 8676 Labor Market Effects of Demographic Shifts and Migration in OECD Countries Frederic Docquier Zovanga L. Kone Aaditya Mattoo Caglar Ozden Development Economics Development Research Group December 2018 Policy Research Working Paper 8676 Abstract The labor force of each industrial country is being shaped in the age and skill structure favor the low-skilled and hurt by three forces: ageing, education and migration. Drawing the highly skilled across age groups. Immigration plays a on a new database for the OECD countries and a standard relatively minor role, except in a handful of open coun- analytical framework, this paper focuses on the relative and tries, like Australia and Canada, where it accentuates the aggregate effects of these three forces on wages across differ- wage-equalizing impact of ageing and education. Emigra- ent skill and age groups over 2000 to 2010. The variation in tion is the only inegalitarian influence, especially in Ireland the age and educational structure of the labor force emerges and a few Eastern European countries which have seen as the dominant influence on wage changes. The impact is significant outflows of high-skilled labor to Western Euro- uniform and egalitarian: in almost all countries, the changes pean Union countries. This paper is a product of the Development Research Group, Development Economics. It is part of a larger effort by the World Bank to provide open access to its research and make a contribution to development policy discussions around the world. Policy Research Working Papers are also posted on the Web at http://www.worldbank.org/research. The authors may be contacted at cozden@worldbank.org. The Policy Research Working Paper Series disseminates the findings of work in progress to encourage the exchange of ideas about development issues. An objective of the series is to get the findings out quickly, even if the presentations are less than fully polished. The papers carry the names of the authors and should be cited accordingly. The findings, interpretations, and conclusions expressed in this paper are entirely those of the authors. They do not necessarily represent the views of the International Bank for Reconstruction and Development/World Bank and its affiliated organizations, or those of the Executive Directors of the World Bank or the governments they represent. Produced by the Research Support Team Labor Market Effects of Demographic Shifts and Migration in OECD Countries* Frederic Docquiera , Zovanga L. Koneb , Aaditya Mattooc , Caglar Ozdenc a FNRS and IRES, Universite catholique de Louvain (Belgium), and FERDI (France) b COM PAS, University of Oxford (United Kingdom) c Development Research Group, the World Bank (United States) Keywords: Ageing; Emigration; Immigration; OECD countries. JEL codes: F22; Jll; J22. *We thank two anonymous referees for their helpful remarks. We are also grateful for comments from Costanza Biavaschi, Giovanni Peri, Hillel Rapoport, Michel Beine, Chris Parsons, Erhan Artuc, James Otterson and other participants at the 7th Annual Conference on Immigration in OECD Countries in Paris and the 10th International Migration and Development Conference in Clermont-Ferrand. The authors acknowledge financial support from the Knowledge for Change Program, the Research Support Budget and the Multidonor Trust Fund for Trade and Development of the World Bank. The findings in this paper do not necessarily represent the views of the World Bank's Board of Executive Directors or the governments they represent. Any errors or omissions are the authors' responsibility. Figure 1: Changes in population shares by age-education group (in percentage points), 2000- 2010, natives The figure illustrates changes in QQ SA amongst native-born between 2000 and 2010. Data cover to those of age 25-64. Young refers to those of age 25-44 and Old refers to those of age 45-64 Figure 2: Changes in population shares by age-education group (in percentage points), 2000- 2010, immigrants The figure illustrates changes in QQ SA amongst foreign-born between 2000 and 2010. Data cover to those of age 25-64. Young refers to those of age 25-44 and Old refers to those of age 45-64 34 Figure 3: Nest structure of composite labor High-skill Low-skill Old Young Old Young Natives Migrants Natives Migrants Natives Migrants Natives Migrants Note: The figure illustrates the structure of the CES function described in the section where we present our analytical model Figure 4: Observed vs. simulated wage bill shares, 2010 Note: The Y-axis denotes wage bill shares computed using information on earnings from the EU-SILC and the ACS. The X-axis denotes wage bill shares computed as described in the data section 35 Figure 5: Wage effects of socio-demographic changes, 2000 – 2010 (%), by age-education group 30% 20% 10% 0% NZL −10% USA IRL NOR LUX SWE AUS CAN BEL FIN DEU DNK JPN −20% FRA NLD CHE CZE AUT GRC TUR GBR ESP SVK ITA PRT HUN POL −30% Young, LS Old, LS Young, HS Old, HS The figure plots equilibrium wage responses to changes in the age-education composition of natives Figure 6: Decomposition of education and ageing effects Education wage effects Ageing wage effects 30% 30% 20% 20% 10% 10% 0% 0% NZL GRC NOR CZE AUT BEL SWE FIN HUN IRL ESPPRT JPN USA AUS GBR DEU CHEFRA LUX DNK SVK CAN ITA USA NZL NLD POL −10% −10% TUR CAN IRL NOR AUS LUX BEL SWE DEU FIN NLD DNK JPN CHEFRA AUT GBR GRC −20% −20% CZE ESP HUN TUR ITA PRT SVK −30% −30% POL Young, LS Old, LS Young, HS Old, HS The figure splits the equilibrium responses presented in Figure 5 into changes due to ageing and those due to education 36 Figure 7: Wage effects of immigration, 2000 – 2010 (%), by age-education group 6% 4% 2% 0% NLD USA IRL DNK JPN DEU ITA GRC FIN HUN FRA SWE NOR CZE POL TUR ESP −2% PRT BEL AUT SVK GBR −4% CAN NZL CHE −6% LUX AUS Young, LS Old, LS Young, HS Old, HS The figure plots equilibrium wage responses to immigration Figure 8: Wage effects of emigration, 2000 – 2010 (%), by age-education group 6% 4% 2% 0% USA JPN TUR −2% AUS NLD ITA ESP SWE CAN DEU AUT DNK NOR CZE FRA BEL GRC FIN HUN CHE GBR LUX POL NZL SVK −4% PRT −6% IRL Young, LS Old, LS Young, HS Old, HS The figure plots equilibrium wage responses to emigration 37 Figure 9a: Combined wage effects socio-demographic changes, immigration and emigration, 2000 – 2010 (%), for Old Low-Skilled 30% 20% 10% 0% CHE LUX USA CAN AUS NLD ITA ESP PRT JPN TUR GBR DEU AUT FRA BEL GRC DNK SWE NOR FIN CZE HUN POL SVK NZL −10% IRL −20% −30% Socio−demographic Immigration Emigration Combined The figure plots equilibrium wage responses to overall changes in the structure of the labor force Figure 9b: Combined wage effects socio-demographic changes, immigration and emigration, 2000 – 2010 (%), for Young Low-Skilled 30% 20% 10% 0% USA AUS NLD ITA ESP SWE JPN TUR CAN DEU AUT FRA BEL GRC DNK NOR CZE GBR CHE LUX FIN HUN POL NZL SVK PRT IRL −10% −20% −30% Socio−demographic Immigration Emigration Combined The figure plots equilibrium wage responses to overall changes in the structure of the labor force 38 Figure 9c: Combined wage effects socio-demographic changes, immigration and emigration, 2000 – 2010 (%), for Old High-Skilled 30% 20% 10% IRL PRT NZL GBR CZE SVK POL DEU AUT BEL ITA ESP GRC FIN CAN AUS CHE FRA NLD DNK SWE NOR HUN TUR USA JPN 0% LUX −10% −20% −30% Socio−demographic Immigration Emigration Combined The figure plots equilibrium wage responses to overall changes in the structure of the labor force Figure 9d: Combined wage effects socio-demographic changes, immigration and emigration, 2000 – 2010 (%), for Young High-Skilled 30% 20% 10% IRL SVK NZL AUT BEL PRT CZE HUN POL GBR DEU FRA ITA ESP GRC DNK SWE NOR FIN USA CAN AUS CHE NLD JPN TUR 0% LUX −10% −20% −30% Socio−demographic Immigration Emigration Combined The figure plots equilibrium wage responses to overall changes in the structure of the labor force 39 Figure 10: Robustness: Combined wage effects in the baseline vs. involuntary unemployment scenario 30% 20% 45 degree line Involuntary unemployment (with benefit) CHE 10% CHE LUX PRT PRT LUX ESP ESP −20% −10% 0% −30% −30% −20% −10% 0% 10% 20% 30% Baseline scenario Young, LS Young, HS Old, LS Old, HS The figure contrasts equilibrium wage responses in the baseline scenario to those from a scenario where we allow for involuntary unemployment Figure 11: Robustness: Combined wage effects in the baseline vs. fixed capital stock scenario 30% 45 degree line 20% Fixed capital stock scenario −10% 0% 10% −20% −30% −30% −20% −10% 0% 10% 20% 30% Baseline scenario Young, LS Young, HS Old, LS Old, HS The figure contrasts equilibrium wage responses in the baseline scenario to those from a scenario where capital stock is fixed 40 Figure 12: Robustness: Combined wage effects in the baseline vs. moderate technological change scenario 30% 30% 45 degree line 45 degree line 20% 20% CHE GBR Moderate technological change scenario´ CAN ESP AUS 10% 10% JPN LUX HUN PRT GRC POL FRA DNK NLD ITA CZE TUR AUT POL SVK GBR CAN CHE HUN CZE PRT AUS 0% 0% DNK NLDSVK FRA TUR ITAGRC LUX ESP JPN AUT −10% −10% −20% −20% −30% −30% −30% −20% −10% 0% 10% 20% 30% −30% −20% −10% 0% 10% 20% 30% Baseline scenario Baseline scenario Young, HS Old, HS Young, LS Old, LS The figure contrasts equilibrium wage responses in the baseline scenario to those from a scenario where we allow for moderate technological change Figure 13: Robustness: Combined wage effects in the baseline vs. strong technological change scenario 30% 30% 20% 20% 45 degree line 45 degree line Strong technological change scenario´ 10% 10% CHE POL GBR CAN CHE CAN AUS HUN JPN GBR PRT CZE ESP AUS DNK SWE LUX ITA NLD FRA TURSVK NOR GRC LUX DNK HUN NOR SWEFRA ESPGRC NLD CZE PRT JPN DEU POL 0% 0% DEU ITA AUT SVK TUR AUT −10% −10% −20% −20% −30% −30% −30% −20% −10% 0% 10% 20% 30% −30% −20% −10% 0% 10% 20% 30% Baseline scenario Baseline scenario Young, HS Old, HS Young, LS Old, LS The figure contrasts equilibrium wage responses in the baseline scenario to those from a scenario where we allow for strong technological change 41 Tables Table 1: Age distribution of populations in 2010, % (25+ only), Natives Immigrants Emigrants 25-44 45-64 65+ 25-44 45-64 65+ 25-44 45-64 65+ USA 38.80 40.49 20.71 50.01 35.50 14.49 38.71 40.69 20.60 CAN 38.30 42.80 18.90 37.82 39.72 22.46 36.31 38.52 25.17 AUS 42.97 37.55 19.48 39.23 37.76 23.01 58.97 30.03 11.01 NZL 37.06 40.49 22.44 42.73 36.84 20.43 49.98 39.24 10.78 GBR 36.55 38.17 25.28 56.17 29.43 14.40 27.98 42.52 29.50 IRL 43.36 36.27 20.37 67.18 26.43 6.39 27.65 32.67 39.68 DEU 32.37 37.89 29.75 43.19 40.25 16.55 43.18 33.49 23.33 AUT 42.04 43.66 14.30 53.01 37.67 9.33 20.82 39.26 39.92 CHE 40.54 44.30 15.15 52.10 38.42 9.48 52.45 33.17 14.38 FRA 38.70 36.90 24.40 36.39 41.20 22.41 50.37 31.66 17.97 BEL 35.72 38.44 25.84 48.43 35.76 15.81 39.46 38.47 22.08 NLD 36.24 40.53 23.22 50.75 38.72 10.53 26.54 41.57 31.89 LUX 35.27 37.86 26.87 51.56 36.44 12.00 41.42 35.66 22.92 ITA 34.01 36.73 29.26 61.20 31.19 7.61 19.29 40.46 40.25 ESP 39.93 35.21 24.86 62.82 28.84 8.33 30.82 36.72 32.46 PRT 36.37 36.30 27.33 61.42 30.32 8.26 37.34 46.73 15.94 GRC 36.60 34.77 28.63 59.59 31.03 9.38 18.06 43.15 38.79 DNK 35.22 39.14 25.63 57.18 32.61 10.21 33.64 34.38 31.98 SWE 35.12 36.77 28.12 46.70 35.73 17.57 52.59 30.93 16.47 NOR 37.21 38.48 24.32 62.58 30.05 7.37 31.87 33.30 34.83 FIN 33.71 40.80 25.50 64.87 28.14 6.98 19.39 46.07 34.54 CZE 41.01 37.59 21.39 45.42 32.30 22.28 35.29 32.78 31.94 HUN 39.87 37.42 22.71 41.43 28.73 29.84 34.78 26.55 38.67 POL 41.56 40.44 18.00 9.18 12.01 78.81 51.76 33.15 15.09 SVK 44.70 37.86 17.44 25.24 44.87 29.89 43.21 30.17 26.62 JPN 34.55 35.25 30.20 63.06 27.48 9.46 49.58 36.64 13.78 TUR 58.93 34.81 6.26 42.77 44.52 12.71 53.05 35.87 11.09 Table reports the age-group breakdown of all those of age 25 or more 42 Table 2: Relative change in labor quantities, % (∆Q/Q) Natives, socio-demographic Immigrants Natives, emigration Young, LS Young, HS Old, LS Old, HS Young, LS Young, HS Old, LS Old, HS Young, LS Young, HS Old, LS Old, HS USA -16.59 6.45 17.35 41.80 13.41 32.95 47.57 79.42 -0.21 -0.37 -0.46 -0.75 CAN -29.30 17.04 13.92 72.62 -20.29 56.04 -0.65 76.04 1.00 -1.14 -1.06 -5.20 AUS -14.70 38.93 14.65 67.28 0.93 100.32 11.85 83.31 0.25 -3.75 -1.23 -3.81 NZL -20.76 -12.41 24.19 23.78 26.97 87.74 43.92 90.81 0.63 -10.53 -10.97 -17.75 GBR -25.45 36.70 -2.91 82.78 39.14 149.41 15.10 121.76 2.03 -2.38 -0.60 -12.26 IRL -2.42 30.14 9.52 52.80 101.96 94.83 129.36 126.25 4.91 -11.49 13.64 -19.79 DEU -27.25 -8.19 -11.37 21.17 -15.11 4.57 31.28 72.47 -0.11 -2.88 0.19 -4.00 AUT -19.45 13.64 8.28 64.95 24.51 116.97 25.96 97.01 -0.46 -6.90 -0.63 -7.19 CHE -27.99 48.29 3.47 96.48 -7.74 110.41 2.28 88.33 3.21 -4.69 -6.35 -9.17 FRA -17.14 40.05 12.72 65.24 4.88 39.21 16.74 70.09 0.76 -3.56 -0.61 -4.87 BEL -18.60 5.43 7.13 44.67 67.63 2.58 44.38 46.03 0.71 -2.83 -1.47 -5.89 NLD -34.42 12.05 -0.35 41.70 114.34 214.18 322.22 498.67 -0.66 -2.20 -0.27 -5.02 43 LUX -25.10 40.26 8.68 47.50 23.98 71.09 55.74 110.24 13.70 29.67 8.93 27.95 ITA -23.06 50.29 4.72 47.68 102.93 117.22 214.84 179.66 0.30 -3.13 0.25 -5.30 ESP -17.35 41.41 8.91 114.89 145.54 167.96 237.95 285.19 1.12 -0.67 0.08 -2.25 PRT -17.73 81.15 6.52 54.79 21.94 46.78 116.97 118.21 5.33 -8.83 -6.57 -20.97 GRC -18.64 30.97 -8.51 62.46 22.19 11.50 86.53 98.18 0.67 -1.70 2.20 -5.60 DNK -25.21 22.50 -3.36 29.37 29.44 31.53 45.79 55.91 0.45 -2.52 0.37 -3.17 SWE -17.04 21.10 -2.29 11.10 14.44 51.23 12.47 46.24 -0.18 -3.58 -0.12 -2.51 NOR -18.17 16.33 2.07 24.98 52.32 143.23 62.45 91.76 0.52 -2.64 0.37 -3.64 FIN -16.20 2.15 -3.23 40.63 101.80 110.63 150.47 146.29 2.91 -0.72 1.53 -2.29 CZE -2.24 57.05 3.61 21.91 46.35 67.44 -9.95 34.77 -1.53 -9.99 -1.06 -6.59 HUN -10.66 72.75 -4.23 29.72 46.74 107.19 17.33 31.68 -1.93 -13.54 0.59 -1.69 POL -11.12 102.02 20.48 42.68 -86.54 48.54 -87.61 -57.89 -7.89 -25.00 -5.33 -18.93 SVK 6.23 87.64 28.02 53.29 -84.48 -57.68 -67.70 -39.71 -4.80 -26.32 1.30 -8.00 JPN -6.58 4.14 -17.90 45.38 19.10 2.22 16.83 65.66 0.00 -0.25 -0.15 -0.95 TUR 6.80 77.36 32.51 66.09 60.56 127.37 134.79 136.70 -4.69 -9.52 -7.70 -12.78 SA The table reports changes in QQ between 2000 and 2010 for each nativity group Table 3: Parameter values used in simulation δs : Elasticity of substitution between the high and low skilled 1.75 δa : Elasticity of substitution between the old and young 5 δm : Elasticity of substitution between immigrants and natives 20 γ : Elasticity of labor supply .10 Parameters used in the intermediary scenario in DOP; δa comes from Card and Lemieux (2001) 44 Table 4: Extensions with changes in elasticities, median values (minimum, maximum in parentheses) Scenario Young, LS Young, HS Old, LS Old, HS Total 8.23 -10.46 4.84 -13.33 (-0.88 ; 18.05) (-19.71 ; 7.28) (-3.89 ; 14.34) (-21.09 ; 0.87) Socio-demographic 7.65 -10.31 4.37 -12.88 (-0.69 ; 14.55) (-24.63 ; 7.92) (-4.74 ; 10.39) (-20.93 ; 0.34) Baseline Immigration 0.48 -0.47 0.45 -0.30 (-1.34 ; 5.36) (-5.3 ; 1.76) (-0.62 ; 4.9) (-4.97 ; 1.36) Emigration -0.63 0.75 -0.48 0.83 (-3.83 ; -0.04) (-1.48 ; 3.54) (-5.43 ; 0.68) (-1.25 ; 3.91) Total 6.03 -7.27 4.32 -9.75 (0.95 ; 13.96) (-22.38 ; 4.37) (-4.13 ; 10.85) (-20.99 ; -1.81) Socio-demographic 7.03 -8.84 3.48 -11.63 (-0.45 ; 13.1) (-21.84 ; 7.24) (-4.49 ; 8.87) (-18.31 ; -0.4) σs =2 Immigration 0.42 -0.39 0.40 -0.26 (-1.18 ; 4.76) (-4.56 ; 1.58) (-0.46 ; 4.3) (-4.28 ; 1.17) Emigration -1.65 1.20 -0.33 1.47 (-13.62 ; 2.13) (-3.42 ; 8.71) (-4.73 ; 1.88) (-3.74 ; 5.64) Total 7.56 -10.88 5.46 -13.17 (-1.18 ; 17.57) (-19.5 ; 6.81) (-3.34 ; 14.84) (-20.53 ; 2.22) Socio-demographic 7.18 -10.96 4.77 -12.37 (-1.08 ; 13.99) (-24.08 ; 7.38) (-3.99 ; 10.97) (-21.03 ; 1.95) σa =7 Immigration 0.44 -0.47 0.41 -0.37 (-1.2 ; 5.27) (-5.2 ; 1.71) (-0.75 ; 4.98) (-4.8 ; 1.46) Emigration -0.64 0.74 -0.48 0.82 (-3.76 ; 0.07) (-0.77 ; 3.52) (-5.34 ; 0.85) (-0.65 ; 3.78) Total 7.87 -10.75 4.65 -13.37 (-0.91 ; 17.77) (-19.84 ; 7.21) (-3.92 ; 14.28) (-21.21 ; 0.8) Socio-demographic 7.53 -9.90 4.40 -12.86 (-0.72 ; 14.47) (-24.4 ; 7.86) (-4.77 ; 10.43) (-20.78 ; 0.32) σm =1000 Immigration 0.38 -0.64 0.42 -0.37 (-1.75 ; 5.57) (-6.45 ; 1.74) (-0.8 ; 4.72) (-6.67 ; 1.21) Emigration -0.64 0.74 -0.48 0.82 (-3.76 ; 0.07) (-0.77 ; 3.52) (-5.34 ; 0.85) (-0.65 ; 3.78) The table reports equilibrium wage responses when we vary the parameter values in table 3 45 Appendix A Immigration: variations in stocks versus inflows As explained in Section ??, we use the DIOC database to characterize the socio-demographic changes that have taken place between the years 2000 and 2010. In particular, the results presented in Section ?? highlight the wage effects that are due to the (net) variations in the stock of immigrants. These variations result from three forces: new migrant inflows, return migration, mortality. One might wonder whether the effects depicted in Figure 7 hold true when focusing on (gross) inflows of immigrants over the same period. The DIOC database allows identifying the origin, education, and duration of stay of the population. In particular, we can identify the origin and education structures of immigrants who arrived between the years 2000 and 2010 and who were still living in the destination country in 2010. As duration of stay cannot be jointly identified by age group, we assume all recent immigrants are young (i.e. aged 25 to 44). Figure A.1 compares the wage effects induced by the net variation in the immigrant stock (horizontal axis) with those induced by the gross inflow (vertical axis). In most countries, the results are almost identical. The few exceptions are for countries that have experienced drastic increases in immigration. Recent immigration makes the population younger, which increases the age premium and the competition among younger workers. [INSERT FIGURE A.1 HERE] B Elasticities of substitution across groups Our model assumes that the aggregate labor composite q can be modeled as a nested CES (constant elasticity of substitution) function of different worker types. From Eqs. (??), (??) and (??), this means that a one percent increase in the ratio of employment levels within a nest induces a constant response in the wage ratio within the same nest (equal to −1/σM , −1/σA , or −1/σS ), whatever the intital employment levels. However, the elasticity of substitution across groups (i.e. between workers belonging to different nests) is not constant. It depends on initial structure of employment and on the size of the shock. One way to explore the cross-elasticities across nests is to only change the labor supply of one group and see how the wages of different groups respond. Let σSAM denote the cross-elasticity between group (SAM) and any other chosen group (SAN). It follows that: −1 dln( wSAM wSAN ) = σSAM dln( Q SAM QSAN ) 46 Note that dln( wSAM wSAN ) = dln(wSAM ) − dln(wSAN ) and dln(wSAM ) = ∆wSAM wSAM Now, let’s assume that only the stock of the young high-skilled natives (YHN) changes by 1% while those of other groups remain unchanged. In other words, dln( Q SAM QSAN ) = 0 − 0.01 = −0.01 This means: 0.01 σSAM = wSAM dln( wY HN ) We now simulate wage responses to this 1% increase in the stock of young high-skilled (YHN) while maintaining the stocks of other groups unchanged. We then use the above formula to compute the elasticities of interest, for exposition. These are reported in the Appendix Table A1 below. [INSERT TABLE A.1 HERE] C Decomposing the socio-demographic effects A natural question is how to split the combined effect of socio-demographic change into separate “ageing” and “educational change” components. This is not a simple task since the changes in the relative magnitudes of each of our four labor groups are interrelated. The increase in the stocks of the high-skilled workers may arise from both ageing (as younger high-skilled workers move to the older age group while the older low-skilled retire) and an increase in the number of people with more education (as the next generation of younger people receive more education than the previous one). In order to separate these two effects, we need to make certain assumptions about the demographic and education changes. We start our decomposition by assuming that the change in the stock of any given labor category can be expressed as the sum of the changes due to ageing and due to education. These relationships can be expressed as the following, where e denotes education and a denotes ageing: ∆Qe SAN + ∆Qa SAN = ∆QSAN In order to solve this system of four equations and eight unknowns, we need to make several simplifying assumptions. First, the increase in the stocks of low-skilled workers, whether old or young, can only arise from the increase in age within the population be- tween 2000 and 2010. This is merely because years of schooling for a given individual does not decline over time as there is no de-skilling. By implication, ∆Qe LY N = ∆Qe LON = 0. Then we define Ron = QHON /QLON ; and Ryn = QHY N /QLY N . We later make the simplifying assumption that, if there were no changes in educational composition between 2000 and 2010, then Ryn and Ron in 2010 would take the same values they did in 2000. This assumption isolates the changes due to educationa and gives us the following equations: 47     ∆Qa LY N = ∆QLY N  ∆Qa  LON = ∆QLON    e ∆Q HY N + Ryn ∆Qa LY N = ∆QHY N  ∆Qe  a HON + Ron ∆Q LON = ∆QHON with ∆Qa HY N = Ryn ∆Qa LY N ∆Qa HON = Ron ∆Qa LON We compute Ryn and Ron using data from 2000. Only the last two equations then require solving. We subsquently use ∆Qa lyn , ∆Qa LON , ∆Qe HY N , ∆Qa HY N , ∆Qe HON and ∆Qa HON to obtain the wage effects of interest for each of our four groups. Figure 6 presents how these age and education components differ for each labor group in the OECD countries in our sample. D Supplementary tables The tables provided in this Section give the results of the main analysis (see Section ??) for individual countries. [INSERT TABLE A.2 HERE] [INSERT TABLE A.3 HERE] [INSERT TABLE A.4 HERE] [INSERT TABLE A.5 HERE] 48 Appendix Figure A1: Robustness of immigration wage effects: Net changes in stock vs. gross inflows 10% −10% −7.5% −5.0% −2.5% 0% 2.5% 5.0% 7.5% LUX AUS CHE LUX CAN AUS Recent inflows CAN CHE CHE AUS LUX CAN CAN CHE AUS LUX −10% −7.5% −5.0% −2.5% 0% 2.5% 5.0% 7.5% 10% Change in stock Young, LS Young, HS Old, LS Old, HS The figure contrasts equilibrium wage responses due to immigration when using net changes in stock vs. gross inflows between 2000 and 2010 49 Appendix Tables Table A.1: Approximates of elasticity of substitution across labor groups in %, assuming dQHY N /QHY N = 1% Natives Immigrants Young, LS Young, HS Old, LS Old, HS Young, LS Young, HS Old, LS Old, HS USA 3.3 - 3.3 6.2 3.3 21.5 3.3 6.2 CAN 4.2 - 4.2 7.9 4.2 23.7 4.2 7.9 AUS 5.5 - 5.5 10.4 5.5 28.1 5.5 10.4 NZL 3.6 - 3.6 6.7 3.6 17.7 3.6 6.7 GBR 4.3 - 4.3 8.5 4.3 27.6 4.3 8.5 IRL 3.9 - 3.9 8.5 3.9 26.3 3.9 8.5 DEU AUT 3.3 - 3.3 6.6 3.3 23.0 3.3 6.6 CHE 5.4 - 5.4 10.2 5.4 29.9 5.4 10.2 FRA 3.5 - 3.5 7.6 3.5 28.3 3.5 7.6 BEL 2.8 - 2.8 5.8 2.8 21.3 2.8 5.8 NLD - - - - - - - - LUX 6.6 - 6.6 12.5 6.6 28.3 6.6 12.5 ITA 3.8 - 3.8 8.3 3.8 30.4 3.8 8.3 ESP 3.6 - 3.6 7.8 3.6 28.6 3.6 7.8 PRT 4.7 - 4.7 10.5 4.7 36.6 4.7 10.5 GRC 3.4 - 3.4 7.3 3.4 26.5 3.4 7.3 DNK 3.4 - 3.4 6.6 3.4 24.8 3.4 6.6 SWE 3.6 - 3.6 6.9 3.6 24.5 3.6 6.9 NOR 3.3 - 3.3 6.7 3.3 23.5 3.3 6.7 FIN 2.8 - 2.8 5.4 2.8 20.7 2.8 5.4 CZE 4.0 - 4.0 8.5 4.0 31.7 4.0 8.5 HUN 4.2 - 4.2 9.3 4.2 34.9 4.2 9.3 POL 4.5 - 4.5 10.4 4.5 40.8 4.5 10.4 SVK 4.4 - 4.4 9.8 4.4 37.9 4.4 9.8 JPN MEX 1.4 - 1.4 2.9 1.4 10.9 1.4 2.9 TUR 4.0 - 4.0 9.5 4.0 35.8 4.0 9.5 The table illustrates elasticity of substitution value across nests 50 Table A.2: Baseline Scenario – wage effects of socio-demographic (age-education) changes (%) Young, LS Young, HS Old, LS Old, HS USA 7.63 -2.49 2.08 -7.92 CAN 12.62 -4.49 5.41 -10.33 AUS 7.66 -7.06 3.39 -9.71 NZL 3.75 1.55 -3.14 -3.22 GBR 14.55 -12.10 10.39 -18.68 IRL 6.34 -4.48 4.47 -7.42 DEU 6.73 -6.15 3.26 -11.92 AUT 6.63 -9.84 1.64 -17.17 CHE 13.80 -10.91 8.94 -15.93 FRA 10.69 -12.17 5.57 -15.29 BEL 6.88 -4.41 2.43 -10.52 NLD 11.27 -10.82 4.50 -15.56 LUX 6.17 -7.98 1.67 -8.64 ITA 8.27 -21.24 3.14% -20.93 ESP 13.55 -10.78 9.33 -19.08 PRT 10.76 -21.50 6.55 -18.39 GRC 9.42 -13.47 7.81 -17.59 DNK 10.10 -11.59 5.81 -12.85 SWE 6.08 -8.40 3.32 -6.88 NOR 7.54 -6.22 3.95 -7.66 FIN 8.04 -3.90 5.61 -10.49 CZE 4.68 -16.38 3.62 -11.15 HUN 9.22 -21.66 8.03 -15.43 POL 13.20 -24.63 7.88 -16.43 SVK 7.59 -18.93 4.26 -14.20 JPN 6.71 -5.79 9.05 -12.90 TUR 5.98 -17.74 2.16 -16.11 The table reports values of the wage effects depicted in Figure 5 51 Table A.3: Baseline scenario – wage effects of immigration (%) Young, LS Young, HS Old, LS Old, HS USA 0.55 0.09 0.22 -0.02 CAN 5.34 -2.58 4.61 -2.92 AUS 5.36 -5.30 4.90 -4.64 NZL 3.67 -3.44 3.40 -2.91 GBR 2.48 -2.42 2.83 -1.02 IRL 0.97 -0.04 1.96 0.26 DEU 0.36 -0.08 -0.07 -0.25 AUT 0.90 -1.78 1.02 -1.43 CHE 5.28 -4.33 4.80 -3.34 FRA 0.61 -0.37 0.45 -0.69 BEL -1.34 1.76 -0.62 1.36 NLD 0.36 0.54 0.47 0.38 LUX 4.21 -3.85 3.49 -4.97 ITA -0.15 1.01 0.34 0.94 ESP -0.76 1.10 0.18 0.92 PRT 0.79 -0.52 0.62 -1.11 GRC -0.14 1.09 -0.33 0.27 DNK -0.10 0.20 0.04 0.24 SWE 0.51 -0.70 0.61 -0.38 NOR 0.71 -0.63 1.23 -0.12 FIN -0.49 0.38 -0.04 0.52 CZE 0.16 -0.70 0.48 -0.53 HUN 0.29 -0.49 0.44 -0.24 POL 0.20 -0.60 0.30 -0.35 SVK 0.52 -2.01 0.29 -1.97 JPN -0.05 0.05 -0.01 0.02 TUR 0.45 -0.45 0.10 -0.67 The table reports values of the wage effects depicted in Figure 7 52 Table A.4: Baseline scenario – wage effects of emigration (%) Young, LS Young, HS Old, LS Old, HS USA -0.04 0.01 -0.02 0.05 CAN -0.67 0.17 -0.28 0.48 AUS -0.41 0.42 -0.20 0.37 NZL -1.78 1.35 -0.31 1.76 GBR -1.50 0.69 -0.89 1.58 IRL -3.83 3.24 -5.43 3.91 DEU -0.61 1.01 -0.68 1.05 AUT -0.63 1.65 -0.63 1.39 CHE -1.34 0.36 0.28 0.63 FRA -0.74 0.77 -0.48 0.83 BEL -0.84 0.70 -0.45 0.94 NLD -0.35 0.44 -0.47 0.72 LUX -0.48 -1.48 0.68 -1.25 ITA -0.38 0.96 -0.36 1.23 ESP -0.45 0.27 -0.23 0.37 PRT -2.36 1.73 -0.05 3.08 GRC -0.58 0.85 -0.88 1.21 DNK -0.63 0.74 -0.59 0.82 SWE -0.47 0.76 -0.48 0.66 NOR -0.71 0.68 -0.67 0.81 FIN -1.18 0.77 -0.83 0.95 CZE -0.54 1.75 -0.64 1.58 HUN -0.63 1.87 -1.16 0.71 POL -0.73 1.69 -1.56 1.83 SVK -0.98 3.54 -2.04 2.01 JPN -0.11 0.05 -0.07 0.13 TUR -0.18 0.24 0.06 0.63 The table reports values of the wage effects depicted in Figure 8 53 Table A.5: Baseline scenario – total wage effects (%) Young, LS Young, HS Old, LS Old, HS USA 8.30 -2.48 2.37 -8.17 CAN 17.10 -7.45 10.04 -13.96 AUS 13.04 -13.79 8.74 -16.21 NZL 5.49 -0.06 -0.11 -4.04 GBR 16.06 -15.08 12.63 -18.12 IRL 3.76 -0.63 0.89 -2.06 DEU 6.45 -5.16 2.57 -10.86 AUT 6.97 -10.04 2.05 -17.35 CHE 18.05 -16.87 14.34 -20.58 FRA 10.63 -11.67 5.57 -15.16 BEL 5.08 -1.85 1.41 -7.85 NLD 11.84 -10.42 4.77 -15.14 LUX 11.83 -18.63 7.15 -21.09 ITA 8.16 -19.51 3.23 -18.82 ESP 13.58 -9.93 10.06 -18.91 PRT 9.56 -19.71 7.11 -15.16 GRC 9.04 -11.42 6.94 -16.15 DNK 9.55 -10.50 5.30 -11.57 SWE 6.17 -8.37 3.46 -6.61 NOR 7.85 -6.43 4.66 -7.12 FIN 6.79 -2.76 4.90 -8.88 CZE 4.19 -14.31 3.35 -9.44 HUN 8.69 -18.71 7.16 -14.45 POL 11.19 -18.93 5.46 -11.85 SVK 6.11 -13.12 1.61 -11.94 JPN 6.57 -5.68 8.97 -12.69 TUR 6.06 -17.34 2.28 -15.41 The table reports values of the wage effects depicted in Figure 9 54