Ethnic Discrimination in the Rental Housing Market

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Ethnic Discrimination in the Rental Housing Market The Role of Additional Information and Market Structure Knut Petzold Seminar Analytische

1 Ethnic Discrimination in the Rental Housing Market The Role of Additional Information and Market Structure Knut Petzold Seminar Analytische Soziologie: Theorie und empirische Anwendungen Venice International University, San Servolo November 2017 Faculty of Social Science Sociology Section

2 Introduction Ethnic Discrimination in the Rental Housing Market Venice

3 Introduction Ethnic discrimination refers to unequal treatment of persons or groups on the basis of their race or ethnicity. (Pager & Shepherd 2008, 182) Unequal treatment of migrants in rental housing markets Sweden (Ahmed & Hammarstedt 2008; Ahmed et al. 2010; Bengtsson et al. 2011; Carlson & Eriksson 2014) Norway (Andersson et al. 2012; Beatty & Sommervoll 2012) US (Carpursor & Loges 2006; Hanson & Hawley 2011; Ewens et al. 2014) Canada (Hogan & Berry 2011) Italy (Baldini & Frederici 2011) Spain (Bosch et al. 2010) Czech Republic (Bartoš et al. 2013) Belgium (Van der Bracht et al. 2015) Germany (Auspurg et al. 2017) à Clear evidence for ethnic discrimination à Mixed evidence regarding (contextual ) moderators Ethnic Discrimination in the Rental Housing Market Venice

4 Research questions Can evidence for ethnic discrimination in the rental housing market be replicated for Arabic applicants in Germany? Does ethnic discrimination vary according to applicant s characteristics? Does ethnic discrimination vary across regional and market conditions? Ethnic Discrimination in the Rental Housing Market Venice

5 Theoretical framework Preference-based discrimination (Becker 1957) Results from affective tastes for and against particular social groups, i.e. Arabs Objectives against certain social groups are part of individuals' utility function Offenders have to bear a costly tax for discrimination Discrimination should decline in contested markets Ethnic Discrimination in the Rental Housing Market Venice

6 Theoretical framework Statistical discrimination (Phelps 1972; Arrow 1973) Results from imperfect information Offenders use observable markers for assessment of others, i.e. ethnicity Related expectations are based on previous interactions and commonly known average values Especially effective in situations of high risk, i.e. high rents (cf. Hogan & Berry 2011; Bengtsson et al. 2012; Auspurg et al. 2017) Discrimination should decrease if missing information is added (cf. Bosch et al. 2010; Baldini & Frederici 2011; Auspurg et al. 2017) Ethnic Discrimination in the Rental Housing Market Venice

7 Theoretical framework Discrimination by customers (Becker 1957) Lessors discriminate migrants to avoid trouble with existing tenants Customers preferences and minority group size - Ethnic competition theory (Shepers et al. 2002), Social identity theory (Tajfel & Turner 1979) - Intergroup contact theory (Allport 1954) When lessors have doubts, they will play it save The larger the minority group size, the more should lessors discriminate against migrants (see also Ewens et al. 2014; Hogan & Berry 2011) à In contrast to spatial steering Ethnic Discrimination in the Rental Housing Market Venice

8 Set of hypotheses Causal hypotheses H1: If the sender has an Arabic name as compared to a German name, enquiries will gain less response. H2: If additional information is provided, ethnic discrimination will be reduced. Moderation hypotheses H3a: The higher the financial risk, the stronger will be ethnic discrimination. H3b: The higher the financial risk, the more will ethnic discrimination be reduced by additional information. H4a: The less the market situation is in favour of the lessor, the lower will be ethnic discrimination. H4b: The lower ethnic discrimination, the less important will be additional information. H5a: The larger the minority group size, the stronger will be ethnic discrimination. H5b: The larger the minority group size, the less will information reduce ethnic discrimination. Ethnic Discrimination in the Rental Housing Market Venice

9 Experimental design Correspondence test (see Riach & Rich 2002; Pager 2007; Keuschnigg & Wolbring 2015; Bertrand & Duflo 2017) Two enquiries for appointments regarding vacant rental apartments 2 x 2 x 2 x 2 = 16 experimental conditions Within variation: applicants name Between variation: applicants gender, information about employment, information about family background Behavioural outcome: response by lessors Stephan Unger (stephan.unger@posteo.de) Programmer Wife & child Omar Benali (omar.benali@mailbox.org) IT sector Wife & child Julia Brockmann (julia.brockmann@mailbox.org) Bank clerc Husband & child Fatima Aynan (fatima.aynan@posteo.de) Insurance sector Husband & child Ethnic Discrimination in the Rental Housing Market Venice

10 Examples of enquiries Ethnic Discrimination in the Rental Housing Market Venice

Data collection Advertisements for rental 2/3 room-apartments from www.immobilienscout24.

11 Data collection Advertisements for rental 2/3 room-apartments from January - February 2017 Regional quotation, random ( route ) selection Urban & rural areas East, West, North, South Enquiries via Lessors were subjected only once to the study Two days between both enquiries, balanced order Recherche of adresses when missing Final sample 1768 enquiries according to 884 vacant rental apartments (196 deleted) 223 counties Ethnic Discrimination in the Rental Housing Market Venice

12 Proportions of experimental conditions Treatment N Percent Level Ethnic name German % 0 Arabic % 1 Gender Male % 0 Female % 1 Job status No information % 0 Information % 1 Family background No information % 0 Information % 1 Total % Variables Ethnic name Gender Information job status Information family background Pearson s r; * p < 0.01 Ethnic Discrimination in the Rental Housing Market Venice

13 Sample composition Variables N / M Percent / SD Range Rooms room % 3-room % Living space in m² Basic rent in Lessor type 0-2 Private landlord % Housing association % Real estate agent % Region 0-1 Urban % Rural % Federal state 1-16 Bavaria % North Rhine-Westphalia % Saxony-Anhalt % Thuringia % Schleswig-Holstein % Berlin % Baden-Württemberg % Rhineland-Palatinate % Hesse % Lower Saxony % Saxony % Brandenburg % Mecklenburg-Vorpommern % Saarland % Hamburg % Bremen % Total % Ethnic Discrimination in the Rental Housing Market Venice

14 Merged contextual information Additional county-level data from INKAR & GENESIS (for 2015) Variables M SD Range Population Population density (inhabitants per km²) Average age in years Rent index in Average living space per capita in m² Proportion of 2/3-room apartments in % Average net household income in Housing allowance in of households Proportion of foreigners in % Proportion of foreigners - km²-grid in % Demand for new apartments Ethnic Discrimination in the Rental Housing Market Venice

15 Net discrimination effect (response rates) Proportion response % % Proportion resonse % ATT = % ,6 % No Response Yes German name Arab name Ethnic Discrimination in the Rental Housing Market Venice

16 Treatment effects Treatment effects Arab name (ref. German) Female (ref. male) Information job (ref. no) Information family (ref. no) Effects on response probability Model 1 Model 2 Model 3 Model 1: logit, no covariates Model 2: LPM/OLS, no covariates Model 3: LPM/OLS, covariates (characteristics of apartment and region) Clustered SE, 95% CI Napartments = 884; Nenquiries = 1768 Ethnic Discrimination in the Rental Housing Market Venice

17 Taste-based discrimination and statistical discrimination No information job Conditional discrimination effects -.18 ATT= Name * Job information: b=.08, p= Information job Male -.14 Female -.14 No information family -.14 Information family Effects on response probability Model: LPM/OLS, covariates (characteristics of apartment and region) Clustered SE, 95% CI Napartments = 884; Nenquiries = 1768 Ethnic Discrimination in the Rental Housing Market Venice

18 Basic rent Basic rent Total rent in Euro without without heating and electricity Proportion M = Basic rent in Euro Ethnic Discrimination in the Rental Housing Market Venice

19 Basic rent Effects on response probability Name * Basic rent: b=.000, p= Basic rent in Euro Model: LPM/OLS, conditional effects, clustered SE, 95% CI, covariates Napartments = 874; Nenquiries = 1748 AIC: , BIC: Ethnic Discrimination in the Rental Housing Market Venice

20 Basic rent and job Effects on response probability Basic rent in Euro No information Information job Model: LPM/OLS, conditional effects, clustered SE, 95% CI, covariates Napartments = 874; Nenquiries = 1748; AIC: , BIC: Ethnic Discrimination in the Rental Housing Market Venice

21 Discrimination and living space per capita Living space per capita Living space in residential buidlings per inhabitant in square meters Proportion M = Average living space in qm Ethnic Discrimination in the Rental Housing Market Venice

22 Average living space Effects on response probability Name * Average living space: b=.014, p= Average living space in qm Model: LPM/OLS, conditional effects, clustered SE, 95% CI, covariates Napartments = 878; Nenquiries = 1756 AIC: , BIC: Ethnic Discrimination in the Rental Housing Market Venice

23 Average living Space and job Effects on response probability Average living space in qm No information Information job Model: LPM/OLS, conditional effects, clustered SE, 95% CI, covariates Napartments = 878; Nenquiries = 1756; AIC: , BIC: Ethnic Discrimination in the Rental Housing Market Venice

24 Discrimination and foreigners proportion Foreigners proportion Proportion of (all) foreigners of all inhabitants Proportion M = Proportion foreigners in percent Ethnic Discrimination in the Rental Housing Market Venice

25 Proportion foreigners Effects on response probability Name * Proportion foreigners: b= -.004, p= Proportion foreigners in % Model: LPM/OLS, conditional effects, clustered SE, 95% CI, covariates Napartments = 884; Nenquiries = 1768 AIC: , BIC: Ethnic Discrimination in the Rental Housing Market Venice

26 Proportion foreigners and job Effects on response probability Proportion foreigners in % No information Information job Model: LPM/OLS, conditional effects, clustered SE, 95% CI, covariates Napartments = 884; Nenquiries = 1768; AIC: , BIC: Ethnic Discrimination in the Rental Housing Market Venice

27 One additional consideration H6a: The better financial risk can be assessed by context information, the lower will be ethnic discrimination. H6b: The better financial risk can be assessed by context information, the less important will additional information be. Ethnic Discrimination in the Rental Housing Market Venice

28 Discrimination and housing allowance Housing allowance Households who receive housing allowance Per households Proportion M = Housing allowance per thousand Ethnic Discrimination in the Rental Housing Market Venice

29 Housing allowance Effects on response probability Name * Housing allowance: b=.000, p= Housing allowance of households in Model: LPM/OLS, conditional effects, clustered SE, 95% CI, covariates Napartments = 884; Nenquiries = 1768 AIC: , BIC: Ethnic Discrimination in the Rental Housing Market Venice

30 Housing allowance and job Effects on response probability Housing allowance of households in No information Information job Model: LPM/OLS, conditional effects, clustered SE, 95% CI, covariates Napartments = 884; Nenquiries = 1768; AIC: , BIC: Ethnic Discrimination in the Rental Housing Market Venice

31 Summary There is remarkable ethnic discrimination in the rental housing market (H1) Ethnic discrimination is moderated by information about employment status (H2) competition among applicants (living space) (H4a) minority group size (H5a) (financial risk (basic rent, H3a)) Employment status is disregarded when relevant information is provided by context (housing allowance, H6b) there is low competition among applicants (living space, H4b) Ethnic Discrimination in the Rental Housing Market Venice

32 Discussion & conclusions Evidence for preference-based and statistical discrimination Evidence for interaction between the objections against certain social groups and regional and market conditions Open questions How can we explain the discriminatory baseline? What are the sources of tastes against Arabs? Is there still imperfect information? What ist the true causally relevant geographic context (Kwan 2012)? Ethnic Discrimination in the Rental Housing Market Venice

33 Limitations & prospects Treatment construction Sampling and sample size (external validity) Context variable choice Regional scale of context information Content of response mails à Further replications are needed! Ethnic Discrimination in the Rental Housing Market Venice

34 Thank you for your attention and your comments! Ethnic Discrimination in the Rental Housing Market Venice

35 References Ethnic Discrimination in the Rental Housing Market Venice

36 Theoretical framework Preference formation Realistic Group Conflict Theory (Coser 1956; LeVine & Campbell 1972) Social Identity Theory (Tajfel & Turner 1979) Ethnic Competition Theory (Scheepers et al. 2002) The larger a (threatening) outgroup, the more ethnic threat is perceived und and negative attitudes are developed (Empirical evidence: e.g. Weins 2011; Wagner et al. 2006) Intergroup Contact Theory (Allport 1954; Pettigrew 1998) The larger an outgroup, the more intergroup interaction. Intergroup contact as efficient mean to reduce prejudice (Empirical evidence: e.g. Schneider 2008; Savelkoul et al. 2011) Discrimination by customers (Becker 1957) Lessors discriminate migrants to avoid trouble with existing tenants The larger the minority group size, the more should lessors discriminate against migrants (see also Ewens et al. 2014; Hogan & Berry 2011) (In contrast to spatial steering) Ethnic Discrimination in the Rental Housing Market Venice

37 Robustness check treatment effects Treatment effects Arab name (ref. German) Female (ref. male) Information job (ref. no) Information family (ref. no) Effects on response probability Logit/AME-clustered SE GLS-cases OLS+covar-clustered SE OLS-clustered SE GLS-counties Covariates (characteristics of appartment and region) 95% CI Napartments = 884; Nenquiries = 1768 Ethnic Discrimination in the Rental Housing Market Venice

38 Basic rent ML model Basic rent Effects on response probability _at 3._at 4._at 3656._at 7._at 8._at _at 11._at 12._at _at 15._at 16._at _at 19._at 20._at _at 23._at 24._at _at 27._at 28._at _at 31._at 32._at 1765 Basic rent in Euro Model: LPM/OLS, conditional effects, clustered SE, 95% CI, covariates Napartments = 874; Nenquiries = 1748 AIC: , BIC: Ethnic Discrimination in the Rental Housing Market Venice

39 Living space per capita ML model Average living space Effects on response probability _at38.94._at40.96._at42.98._at _at _at _at _at _at 54.9 Average living space in qm Model: LPM/OLS, conditional effects, clustered SE, 95% CI, covariates Napartments = 878; Nenquiries = 1756 AIC: , BIC: Ethnic Discrimination in the Rental Housing Market Venice

40 Housing allowance ML model Housing allowance Effects on response probability _at44._at66._at88._at1010._at 12._at 14._at 16._at 18._at 20._at 222._at 2424._at 2626._at 2828._at 30._at Housing allowance of households in Model: LPM/OLS, conditional effects, clustered SE, 95% CI, covariates Nappartments = 874; Nreques ts = 1748 AIC: , BIC: Ethnic Discrimination in the Rental Housing Market Venice

41 Proportion foreigners ML model Proportion foreigners and job Effects on response probability Proportion foreigners in % Model: LPM/OLS, conditional effects, clustered SE, 95% CI, covariates Napartments = 884; Nenquiries = 1768 AIC: , BIC: Ethnic Discrimination in the Rental Housing Market Venice

42 Rent index Average living space per capita * Proportion of 2/3-room apart * * Average net household income * * * Housing allowance * * * * Proportion of foreigners * * * * * Proportion of foreigners - km² grid * * * * * * Population * * * * * * * Population density * * * * * * * * Average age in years * * * * * * * * * Demand for new apart * * * * * * * * * Region (urban / rural) * * * * * * * * * * * Pearson s r; * p < 0.01 Ethnic Discrimination in the Rental Housing Market Venice

43 Rent index Effects on response probability Rent index in Euro Model: LPM/OLS, conditional effects, clustered SE, 95% CI, covariates Nappartments = 874; Nrequests = 1748 AIC: , BIC: Ethnic Discrimination in the Rental Housing Market Venice

44 Rent index and job Effects on response probability Rent index in Euro No information Information job Model: LPM/OLS, conditional effects, clustered SE, 95% CI, covariates Nappartments = 874; Nrequests = 1748; , BIC: Ethnic Discrimination in the Rental Housing Market Venice

45 Average household income Effects on response probability Average household income in Euro Model: LPM/OLS, conditional effects, clustered SE, 95% CI, covariates Nappartments = 874; Nrequests = 1748 AIC: , BIC: Ethnic Discrimination in the Rental Housing Market Venice

46 Average household income and job Effects on response probability Average household income in Euro No information Information job Model: LPM/OLS, conditional effects, clustered SE, 95% CI, covariates Nappartments = 878; Nrequests = 1756; AIC: , BIC: Ethnic Discrimination in the Rental Housing Market Venice

47 Average living space Effects on response probability Average living space in qm Model: LPM/OLS, conditional effects, clustered SE, 95% CI, covariates Nappartments = 874; Nrequests = 1748 AIC: , BIC: Ethnic Discrimination in the Rental Housing Market Venice

48 Average living Space and job Effects on response probability Average living space in qm No information Information job Model: LPM/OLS, conditional effects, clustered SE, 95% CI, covariates Nappartments = 878; Nrequests = 1756; AIC: , BIC: Ethnic Discrimination in the Rental Housing Market Venice

49 Proportion 2/3-room Effects on response probability Proportion 2/3-room in % Model: LPM/OLS, conditional effects, clustered SE, 95% CI, covariates Nappartments = 874; Nrequests = 1748 AIC: , BIC: Ethnic Discrimination in the Rental Housing Market Venice

50 Proportion 2/3-room and job Effects on response probability Proportion 2/3-room in % No information Information job Model: LPM/OLS, conditional effects, clustered SE, 95% CI, covariates Nappartments = 878; Nrequests = 1756; AIC: , BIC: Ethnic Discrimination in the Rental Housing Market Venice

51 Proportion foreigners Effects on response probability Proportion foreigners in % Model: LPM/OLS, conditional effects, clustered SE, 95% CI, covariates Nappartments = 874; Nrequests = 1748 AIC: , BIC: Ethnic Discrimination in the Rental Housing Market Venice

52 Proportion foreigners and job Effects on response probability Proportion foreigners in % No information Information job Model: LPM/OLS, conditional effects, clustered SE, 95% CI, covariates Nappartments = 878; Nrequests = 1756; AIC: , BIC: Ethnic Discrimination in the Rental Housing Market Venice

53 Proportion foreigners 1km2 Effects on response probability Proportion foreigners in % Model: LPM/OLS, conditional effects, clustered SE, 95% CI, covariates Nappartments = 854; Nrequests = 1708; AIC: , BIC: Ethnic Discrimination in the Rental Housing Market Venice

54 Proportion foreigners 1km2 and job Effects on response probability Proportion foreigners in % No information Information job Model: LPM/OLS, conditional effects, clustered SE, 95% CI, covariates Nappartments = 854; Nrequests = 1708; AIC: , BIC: Ethnic Discrimination in the Rental Housing Market Venice

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