Immigrant Segregation in Auckland, New Zealand

1. Immigrant Segregation in Auckland, New Zealand David C Maré Motu Economic and Public Policy Research & University of Waikato with Ruth Pinkerton and Jacques Poot New Zealand Treasury National Institute of Demographic and Economic Analysis

2. Overview • Auckland • Population composition • Describe immigrant residential patterns • Degree of residential clustering • Assimilation and location choice • Explanations of location choice • Summary of regression estimation

3. AUCKLAND “Super City” since 2010 Population 1.5 million (1/3 of NZ population) More than half of foreign born population lives in Auckland About 40 % of Auckland population is foreign born Growing ethnic diversity Greater spatial clustering

4. Auckland is an immigrant cityThe Australasian context% of metropolitan population foreign born

5. Auckland is increasingly an Asian city Percentage of metropolitan population Asian born

6. There is residential segregation in AucklandPrevious research Broad findings (by ethnicity): • Pacific people are the most segregated group from Europeans, followed by Maori • Segregation among Maori and Pacific people is slightly decreasing, increasing among Asians • Levels of segregation are relatively low compared to the US Selected References: • Crbic D, Ishizawa H and Crothers C (2010) Ethnic residential segregation in New Zealand, 1991-2006. Social Science Research 39: 25-38. • Johnston R, Poulsen M, Forrest J (2002) Rethinking the analysis of ethnic residential patterns: segregation, isolation, or concentration thresholds in Auckland, New Zealand, Geographical Analysis 34: 245-261. • Johnston, R., Poulsen, M., & Forrest, J. (2008). Asians, Pacific Islanders, and ethnoburbs in Auckland, New Zealand. Geographical Review 98: 214-241.

7. Location choice and migrant settlementSpatial assimilation theory • Ethnic residential integration (less clustering) occurs when minority groups acculturate and achieve socio-economic mobility. This depends on • Group characteristics • Ecological context • Weigh up the benefits of ‘within-group’ versus broader networks and interactions • Do patterns reflect dispersion from a fixed set of ‘entry areas’, or diversification of ‘entry areas’ as new entrants follow existing concentrations?

8. Global dissimilarity and spatial correlation measures capture different patterns Moran’s I index (-1,1) Mountain range Hills Hillocks Isolated peaks Segregation/ Dissimilarity Index (0,1)

9. Data • 1996, 2001 and 2006 unit record data aggregated to 334 Area Units within Auckland region (location is population centroid) • Population aged 25-65 • Five immigrant groups plus NZ-born

10. Disclaimer • Access to the micro data used in this study was provided by Statistics New Zealand under conditions designed to give effect to the security and confidentiality provisions of the Statistics Act 1975. • All frequency counts using Census data are subject to base three rounding in accordance with Statistics New Zealand’s release policy for census data. • The views, opinions, findings and conclusions or recommendations expressed in these papers are strictly those of the authors and do not necessarily represent, and should not be reported as, those of the New Zealand Treasury, Motu Economic and Public Policy Research, and the National Institute of Demographic and Economic Analysis.

11. Results: global indices by country of birth groups Note: Moran’s I calculated for a radius of 3km using population centroids; row-standardised spatial weight matrix with weights proportional to population;

12. The evolution of local clustering with increasing years of residence: 1991-96 cohort arrivals from PRC Housing markets

13. Arrivals from PRC: Cohort or year effects? New Arrivals

14. Arrivals from UK: Cohort or year effects? New Arrivals Housing markets

15. Other findings • Similar patterns for other immigrant groups • Increased segregation; in a more diverse set of areas • New arrivals follow current group members • Within country groups, there is (secondary) segregation by income • Segregation and clustering is evident by ‘language groups’

16. Accounting for different population location patterns • Why are groups making different location choices? • Differing tastes for amenities • Different land-price sensitivity • Social sorting • Spatial equilibrium • If entrants were homogeneous, they would be indifferent between all (populated) locations

17. Empirical Approach(Joint with Andrew Coleman) • Count-data (Negbin) model of the number of entrants (from group g) choosing each location (x) • Consistent with random utility model [Guimarães et al (2003)] • W is a spatial weight matrix (2km straight-line radius) IV (control function) using temporal lags Proxy using spatial lag

18. Impact of own-group sorting

19. Conclusions Degree of segregation • Immigrant residential segregation is increasing in Auckland. • Globally across groups, high segregation and isolation often imply (relatively) low neighbourhood similarity (Moran’s I) and vice versa • Disaggregation by income leads to higher segregation and isolation indices, but lower global spatial correlation. (isolated peaks) • There is significant clustering by language groups. Immigrant Assimilation • Immigrant groups becoming segregated in a wider range of locations • Network effects stronger than ‘ports of entry’ effects: new immigrants disproportionally locate where previous immigrants already reside. • Potential influence of housing markets • Social sorting dominates - residential location choice not accounted for by proximity to amenities, by land rents, or by other population characteristics

20. THANK YOU

22. Location ChoiceBid Rent Curves, with heterogeneous preferences and multiple amenities $ Equilibrium Rent R*(x ) Bid - Rent curve i V ( x ) 0 X Amenity Amenity A1 Location A2

23. Neighbourhoods of Area Units Spatial weights matrix: captures all Aus with centroids within certain range Row standardized Weights proportional to AU population

24. Distance decay in clustering

25. Measuring segregation

26. Formulae

27. Explanations for Residential Clustering • Market sorting (linked to local ‘amenities’) • People with similar tastes live together because they are convenient to local amenities (Catholics live near Catholic churches; surfers like beaches) • Group members have similar income and choose places they can afford • Social Sorting (could occur anywhere) • People like to live near similar people • People like to live apart from dissimilar people Economic equilibrium theory • Spatial equalisation of utility • as function of consumer goods, accessibility, land use, housing, amenities and network externalities • subject to income, prices (incl. rents), taxes. • Population heterogeneity generates sorting/clustering.

28. Where to from here? • Further descriptive work • Other birthplace groups • Wellington and Christchurch; or nationwide • Cohort analysis over longer timespan • Locational choice model • E.g. Coleman and Maré (2010) • Counts data negative binomial model of approx. 8000 Auckland meshblocks, 2001 & 2006 • Impacts analysis • Labour market, housing market, amenities

29. Residential segregation by income group

30. Language clustering: definition of languages

31. Segregation by language groups

32. In related work . . . Population Location regression estimation • Entrants into meshblock = f ( Population, turnover, Land prices, Observed amenities,Housing (detached/ rental)Population composition and density, Other amenities (proxy=neighbourhood price))

33. Population Location Insights • The main insights are what is evident in the raw spatial patterns: • Sorting along social lines • Future spatial patterns depend on who enters • Group concentration may lead to localised price pressures, and the seeding of a new concentration elsewhere • Eg: Pacifica in 1970s; Chinese in late 1990s • Location may depend on where housing supply is expanding when the price pressure needs relieving

34. Residential Clustering • We document the extent to which different groups cluster • An isolation index measures the extent that people from a group live in neighbourhoods that have a lot of people from the same group. It ranges from 0- 1 (evenly spread to fully concentrated. • Eg Pacific Islanders are 11% of Auckland population, but the average Pacific person lives in a Meshblock that is 35% Pacific. • Isolation index is (0.35-0.11)/(1-0.11) = 0.28

35. Residential Clustering • The Moran Statistic measures the extent that meshblocks with a high (low) concentration of people from a group are surrounded by meshblocks that also have a high (low) concentration of people from the same group (also called Spatial correlation). • Ranges from 0 - 1 • A group can have a high isolation index but a small Moran statistic if it lives in very concentrated neighbourhoodspepperpotted all over the place.

36. Residential Clustering • The Getis and Ordmeasure calculates the fraction of a group’s population in an area around a meshblock. • It calculates the fraction that would exceed (be below) a certain level if the group were randomly distributed across the city. • It graphs areas where the concentration is greater than (less than) would be expected by chance (5%) to indicate where groups are clustered • If a lot more than 5% of meshblocks are concentrated, it indicates clustering.

37. Global clustering measures

38. Localized measure of clustering: Getis and OrdG*

39. Change in segregation with duration of residence Arrival cohorts aged 25-50 when 0-4 years in NZ