Do organizations benefit or suffer from cultural and age diversity?

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1 Do organzatons benef or suffer from cultural and age dversy? Increasng Heterogeney and s Impact Nürnberg, December 202 Antje Buche (FAU Monka Jungbauer-Gans (FAU Annekatrn Nebuhr (IAB Cornelus Peters (IAB

2 Outlne Introducton Theory Contrbuton to the lerature Data Estmaton approach Dversy measures Results 2

3 Motvaton Sgnfcant changes n workforce composon Demographc change age structure changes, e.g. share of people >65 years wll ncrease from 20% to 34% n 2060 (German Federal Statstcal Offce 20 Internatonal mobly of labour Annual net mmgraton of people s assumed for the future More than 2 mllon foregn workers n Germany, 40,000 hghsklled foregners (7.3% of all employees Effects of workforce composon on economc performance? 3

4 Trade-off costs and benefs of dversy (Lazear 999, 2000 Benefs due to complementares among dfferent sklls and deas that are specfc for certan groups of workers Costs caused e.g. by barrers to communcaton and conflcts Producton functon (Ottavano and Per 2005: Y A( C Y [ ( dv ] J j ( L j, Y, ( dv (0, 4

5 Contrbuton of the paper Evdence on the mpact of worker dversy on frm productvy n Germany In contrast to others the mpact of dfferent dmenson of staff dversy (age, and cultural background s consdered smultaneously Choosng dfferent dversy measures to dsentangle posve and negatve effects of dversy Deal wh unobserved heterogeney and endogeney 5

6 Data Sources IAB Establshment Panel, survey (~ % of all plants nformaton on value added, capal stock, Establshment Hstory Panel nformaton on ndustry, regon of locaton, frm s age and sze, Process-produced ndvdual data from the IAB detaled nformaton on composon of a frm s workforce Dataset unbalanced panel: ~ 2,800 German plants, (~ 20,000 obs. only frms wh at least 3 employees excluson of frms wh less than 5 observatons the whole publc sector and NGOs are excluded 6

7 Estmaton approach: Cobb-Douglas Producton functon ln( Y ln( A ln( L 2 ln( C ln( L 2 ln( C J j j DIV Culture j K k k DIV Age k L l l Z l d t d mt wh ln( A J j j DIV Culture j K k k DIV Age k L l l Z l d t d mt Y : value added A : total factor productvy L : labor C : capal DIV Culture : cultural dversy DIV Age : age dversy Z : control varables (skll structure, μ : frm level fxed effects d t : year fxed effect d mt : year-ndustry fxed effects 7

8 IV-Estmaton External nstruments: dversy of dentcal frms that are not part of our dataset (< % of all frms are ncluded n our dataset Identfcaton of dentcal frms, : matchng locaton (east / west & regon type: 6 categores ndustry (37 categores frm age (5 categores frm sze (9 categores share hgh-sklled worker (4 categores share low-sklled worker (4 categores Calculaton of external nstruments, example: DIV Cult Cult DIV / j S jt J (For % of the observatons s not possble to dentfy at least one dentcal observaton. set of all frms that are not part of our dataset but have dentcal propertes as frm Lagged dversy measures (referrng to t-3 8

9 Cultural dversy Number of cultural cluster whn a frm as proxy varable for amount of cultural specfc knowledge and ables (Dawson 2007 Cluster based on GLOBE-Cluster (Global Leadershp and Organzatonal Behavor Effectveness Research Project; House et al dfferent cluster: Germany; German-speakng Europe & Benelux; Northern Europe; Latn Europe (France, Italy, Span, ; Eastern Europe; South-east Europe; Anglo Cluster (US, UK, Australa, ; Latn Amerca; Mddle East; Sub-Saharan Afrca; Confucan Asa; South Asa; Rest of the World Share of foregn workers 9

10 Age dversy (Dawson 2007 Age range reflectng the amount of age-specfc knowledge and ables (new techncal knowledge vs. work experence age range A 5 years 65 years age range B Maxmum age gap as an ndcator for communcaton barrers, msunderstandngs and conflcts between younger and older workers maxmum age gap A 5 years 65 years maxmum age gap B 0

11 Results, dep. varable: Value-added N=7,637 (2,526 frms FE FE-IV (2SLS RE RE-IV (2SLS st stage F stat. (FE-IV Number cult. cluster 0.02* *** Share foregn worker Age range * Maxmum age gap Whn R² Between R² Hausman Test (p-value Hansen J-Stat. (p-value Overdentfcaton test (p-value p<0,; * p<0,05; ** p<0,0, p-values are based on robust standard errors (except for RE-IV. control varables: ln(labour, ln(capal, share hgh-sklled, share female, mean(age, tme fxed effects, dummy varables for year x ndustry

12 Fndngs FE & RE model ndcates that: age dversy does (not affect frm productvy cultural dversy matters: lager amount of cultural specfc knowledge / ables has a posve effect on frm productvy but: IV estmaton do not confrm the sgnfcant mpact of cultural dversy on frm productvy 2

13 Thank you very much for your attenton! Cornelus Peters

14 Results, dep. varable: Value-added, alternatve dversy measures N=7,637 (2,526 frms FE FE Number cult. cluster 0.029* Blau-Index (HHI for cult. cluster Share foregn worker 0.38 Blau c 2 foregnc foregn 2 Age range Av. dstance between age & age j SD (age D Sdst 2 N( N N j ( age age j Var (age 0.00 Whn R² p<0,; * p<0,05; ** p<0,0, p-values are based on robust standard errors. control varables: ln(labour, ln(capal, share hgh-sklled, share female, mean(age, tme fxed effects, dummy varables for year x ndustry 4

15 Results, dep. varable: Value-added Only small frms ( 20 emp. N=7,574 (,082 frms FE RE FE-IV Number cult. cluster * Share foregn worker Age range Maxmum age gap Whn R² Between R² Hausman Test (p-value Hansen J-Stat. (p-value Overdentfcaton test (p-value p<0,; * p<0,05; ** p<0,0, p-values are based on robust standard errors. control varables: ln(labour, ln(capal, share hgh-sklled, share female, mean(age, tme fxed effects, dummy varables for year x ndustry 5

16 # smlar observatons Percentles Smallest % 5% 0% 2 Obs % 8 Sum of Wgt % 44 Mean 5.43 Largest Std. Dev % % Varance.44e+07 95% Skewness % Kurtoss

17 AGE Culture Inter- and ntra-class standard devaton of dversy measures, class = group of dentcal frms Standard Devaton Inter-class SD Intra-class SD Number cult. cluster Blau-Index Share foregn worker Range Max dstance Av. dstance SD Statstcs are based on 492,922 observatons (year=2007:,695 groups of dentcal frms & on average 29 observatons per group 7

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