This paper summarises distinct housing and demographic patterns across neighbourhoods in New Zealand’s main urban areas, using data from the 2018 Census of Population and Dwellings. It uses exploratory factor analysis to classify neighbourhood types. It contributes background information for a broader research programme - WERO: Working to End Racial Oppression.

Income support policies: balancing benefits and costs In April 2020 and April 2021, the New Zealand Government increased abatement thresholds (the amount beneficiaries can earn before their benefit reduces) for some government benefits, including Jobseeker Support (JSS), Sole Parent Support (SPS), and Supported Living Payment. This study analyses these changes' effects on recipients' employment, earnings, and net incomes. Government income support policies face a delicate balance: providing adequate income, maintaining work incentives, and managing fiscal costs. Recent changes to abatement thresholds aim to improve support and work incentives, though they may increase costs to the government. Understanding abatement policies Under abatement policies, beneficiaries can earn up to a threshold without affecting their benefits. This can discourage recipients from earning beyond the threshold, leading to a ‘bunching’ effect, where many earn up to the threshold but no more. Data sources for this research This analysis uses data from Statistics New Zealand’s Integrated Data Infrastructure (IDI), including Inland Revenue earnings information for MSD benefit recipients. Policy implications for Aotearoa New Zealand The recent increases to abatement thresholds provided an average of $6-7 more per week to beneficiaries who have an income. However, as most recipients don’t earn income, few benefited. The data shows that recipients' work behaviour didn't significantly change due to the new abatement rules, and the net income gains were modest compared to the increases from higher benefit rates. Summary Raising abatement-free earnings thresholds allowed benefit recipients to boost their incomes, though the effect was limited to a small fraction of recipients. Most recipients did not significantly alter their earnings behaviour, and the overall impact on their incomes was minor.

This study examines whether working in a Māori-led firm contributes to the earnings of Māori employees. It uses administrative data for 2005-2020 to identify Māori-led firms, based on the ethnicity and descent of working proprietors, and using an improved method of measuring descent. Almost 8% of Māori employees work in Māori-led firms. Controlling for firm and worker characteristics, we find that Māori-led firms have slightly lower than average multi-factor productivity and wage levels. The wage effects for Māori of working in a Māori-led firm are small but there is some evidence to suggest that moving between Māori-led firms contributes to wage growth for wāhine Māori, and that in Māori-led firms there is stronger pass-through of firm performance to earnings levels for tāne Māori.

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One of the main challenges facing non-metropolitan regions is the attraction and retention of highly-educated young people. A loss of the brightest can lead to reduced business creation, innovation, growth and community well-being in such regions. We use rich longitudinal microdata from New Zealand to analyse the determinants and geography of the choice of destination of recent university and polytechnic graduates 2 years and 4 years after graduation. Rather than considering a range of location-specific consumption and production amenities, we assume spatial equilibrium and calculate, following Chen and Rosenthal (J Urban Econ 64:519–537, 2008), ‘quality of life’ and ‘quality of business’ indicators for urban areas that encompass all amenities that are utility and/or productivity enhancing (or reducing, in the case of disamenities). Specifically, we test whether students locate in places that are regarded as good to live or good to do business; and how this differs by field of study. Our estimates are conditional on students’ prior school (home) location and the location of their higher education institution. We find that graduates are attracted to locate in urban places that have high quality production amenities. High quality consumption amenities have heterogeneous effects on the location choice of students. Creative arts and commerce graduates are relatively more likely to locate in places that are attractive to business, consistent with a symbiosis between bohemians and business. Decision makers can leverage their existing local strengths, in terms of production and/or consumption amenities, to act as drawcards for, or to retain, recent graduates in specific fields.

In this paper we introduce a measure of cultural diversity that takes ‘social difference’ between country of birth and ethnic groups into account. We measure social difference using exploratory factor analysis of subjective identity, attitude and value responses in Aotearoa New Zealand’s 2016 General Social Survey. We examine the level of, and change in, our social difference-based measure of cultural diversity in 31 urban areas between 1976 and 2018, using census data. We compare these patterns with those derived from a standard fractionalisation measure of diversity based on population composition by country of birth and ethnicity. We find that the two diversity measures are highly correlated across the urban areas. Diversity increased everywhere between 1976 and 2018, whether social difference is taken into account or not. However, the social difference-based measure increased much faster than the standard measure in all but one of the urban areas. This suggests that growth in the fractionalisation measure of diversity is likely to have underestimated the trend in experienced social difference. Both measures also show evidence of spatial convergence in diversity: urban areas with low diversity in 1976 – which tended to be in the South Island – exhibited faster increases. Population diversity increased strikingly in Queenstown, which was the 19th most diverse urban area in 1976, in terms of social difference, but second only to Auckland in 2018.

In this paper we analyse behavioural responses to changes in financial incentives associated with the 2018 Families Package. For this analysis, we followed the methods pioneered by Saez (2010) and Chetty et al. (2013), which use bunching around kink points in the income schedule to estimate the degree of behavioural response. In general, the role of financial incentives in labour supply behaviour has been the subject of investigation for many decades, and although there is considerable concern about adverse labour supply responses to increased generosity of benefits, the available evidence on labour supply responses is mixed and surprisingly muted. We find no evidence of response around the salient kink points related to the policy changes; however, in contrast to the lack of bunching around the policy points, we see clear evidence of bunching around the top two marginal tax rate (MTR) thresholds, as well as at twice these amounts by coupled parental units. This suggests the methodology is able to identify such behavioural responses if they exist. Moreover, according to the theoretical model established in Saez (2010), the degree of bunching around the MTR thresholds should be similar if not less than that around the Families Package policy points we examine. The results in that respect are surprising, though Saez (2010), Chetty et al. (2013), and others find that bunching tends to occur around high visibility, easily understood kink points which have large impacts on disposable income.

The COVID-19 pandemic has caused substantial disruption in social and economic activity since March 2020. The New Zealand Government reacted early, introducing stringent lockdowns to restrict the spread of the virus. At the same time, it introduced a series of economic policies designed to support the health response, the largest of which was the COVID-19 Wage Subsidy Scheme (WSS). The WSS was a high-trust policy that provided subsidy payments to firms who expected to have a substantial drop in revenues because of the pandemic. The objectives of the WSS were to avoid widespread layoffs, help firms maintain employment relationships with their workers, and maintain workers’ incomes to help meet their essential needs during lockdown periods. This paper analyses the impacts of the WSS on both firm and worker level economic outcomes. We adopt a ‘doubly-robust’ estimation approach, that uses propensity score methods both to match subsidy receiving firms to similar non-subsidised firms, and to weight the outcomes analysis. Our analysis focuses on the first four WSS-waves: the March 2020 (Original), Extension, Resurgence, and March 2021 waves. First, we analyse whether the WSS reached the intended people and businesses. For the March 2020 wave, subsidised firms experienced substantially greater revenue declines than unsubsidised firms: the modal reduction in revenue for subsidised firms was about 50%. We also observe larger revenue losses relative to a year earlier for subsidised firms in the Extension and Resurgence waves, but revenue changes for the March 2021 wave are confounded by the March 2020 effects. As the subsidy payments were tied to firms, it was less effective in supporting more precarious jobs and workers. Second, we analyse the effects of the WSS on firm survival and resilience over the short (6 months) and medium (12 months) term. We estimate that receiving WSS payments had a positive effect on firm survival rates over the following 12 months for three of the four WSS waves. However subsidised firms experienced slower subsequent employment growth than nonsubsidised firms. Third, we analyse the effects of the wage subsidy scheme on worker level outcomes. We estimate positive effects of WSS receipt on job-retention over both the short term (6-months) and medium term (12-months) for the March 2020, Extension and March 2021 waves; and roughly zero effects for the Resurgence wave. We also find positive employment effects for workers over the short term for the March 2020, Extension and March 2021 waves, and over the medium term for the March 2020 and Extension waves; and slightly negative effects for the Resurgence wave. However, conditional on being employed, we estimate that workers who COVID-19 Wage Subsidy: Outcome evaluation iii received March 2020 wage subsidy payments experienced slower subsequent monthly earnings growth than comparable non-subsidised workers. The estimates for the later waves are more mixed. We find no compelling evidence that the WSS supported non-viable firms, although the higher survival rate and lower employment growth of subsidised firms suggests that the WSS may have kept firms with poorer growth prospects in operation. We also find no systematic evidence that firms did not comply with their obligations to pass on subsidy payments to workers and endeavour to pay them at least 80% of their usual earnings. However, we find that some subsidy receiving firms paid workers at either the part-time or full-time subsidy rate, or at 80% of their prior earnings, during periods of subsidy receipt. This was relatively more likely to occur during the original (March 2020) subsidy wave, and to a lesser degree the Extension-wave.

We consider whether external urban economic advantages (agglomeration economies) vary with time and space using a simple economic model and detailed micro-data on 134 locations in New Zealand for the period 1976–2018. We find subtle temporal variation, with estimates peaking in 1991 and then falling over the next 15-years by approximately 1%. Since 2006, however, estimates have remained broadly stable. Our results reveal more significant spatial variation: Large cities offer net benefits in production, but not in consumption, whereas small locations close to large cities (“satellites”) experience agglomeration economies that are stronger than average.

In this paper we analyse the effects on rents of the substantial April 2018 changes in the Accommodation Supplement (AS) policy. These policy changes adjusted which geographic locations were assigned to each AS-area, and the AS-maxima were increased to reflect the rising costs of housing in each AS-area. The result of these changes was that the maximum ASpayments for recipients in all locations increased, and the increases varied across geographic locations within redefined AS-areas. We exploit the relative changes in maxima that occurred on either side of such AS-area boundaries to identify the effects of the policy changes on relative rents in these boundary areas. First, we estimate that recipients on the side of boundaries with larger increases in the AS-maxima received on average about $14-19 per week more in accommodation support relative to recipients on the other side. Although we estimate that the relative raw rent increase in the second year after the policy change was about $9 per week on the boundary-sides that received larger increases, once we control for observable and fixed unobservable characteristics of clients, we find negligible differences in rent changes. We conclude that higher-rent new AS-recipients to the treatment areas largely explain the composition changes in these areas, but explain little of the increase in average support. Finally, regression kink analysis shows only weak evidence of stronger rent increases for AS-recipients directly affected by the policy changes.

New Zealand is a small open economy, with large international labor flows and skilled immigrants. Since 2000, employment growth has kept pace with strong migration-related population growth. While overall employment rates have remained relatively stable, they have increased substantially for older workers. In contrast, younger workers as well as the Maori and Pasifika ethnic groups experienced a sharp decline in employment rates and a rise in unemployment around the time of the global financial crisis. Wage gains have been modest and there has been a compression of earnings differentials by gender as well as by skill.

We use linked employer-employee microdata for New Zealand to examine the relationship between firm-level productivity, wages and workforce composition. Jointly estimating production functions and firm- level wage bill equations, we compare migrant workers with NZ-born workers, through the lens of a derived "productivity-wage gap" that captures the difference in relative contribution to output and the wage bill. Whether we look at all industries using a common production function, or separately estimate results for the five largest sectors, we find that skilled and long-term migrants make contributions to output that exceed moderately-skilled NZ-born workers, with that higher contribution likely being due to a mix of skill differences and/or effort which is largely reflected in higher wages. Conversely, migrants that are not on skilled visas are associated with lower output and lower wages than moderately-skilled NZ-born, also consistent with a skills/effort narrative. The share of employment for long-term migrants has grown over time (from 2005 to 2019) and we show that their relative contribution to output appears to be increasing over the same period. Finally, we present tentative evidence that high-skilled NZ-born workers make a stronger contribution to output when they work in firms with higher migrant shares, which is suggestive of complementarities between the two groups or, at least, positive mutual sorting of these groups into higher productivity firms.

This paper examines the impact of homogamy on the distribution of household income in New Zealand at the national level and across different sized cities. We focus on homogamy by age, education, hours worked, employment status, and migration status. We present a new index of homogamy that takes account of maximum potential homogamy. Our index is less sensitive to categories with small population shares than the commonly used concentration ratios. We compare the inequality impact of actual matching with that of randomized matching by means of the additional randomization method. Contrary to public perception, homogamy of the highly educated has declined relative to random matching. Nonetheless, homogamy has had an inequality-increasing impact on the distribution of income and this effect has grown over time: from around 5% of the mean log deviation (MLD) measure of income inequality in 1986 to 16% in 2013. Allowing for simulated labor supply responses reduces this effect by less than 1%. Spatially, the effect of homogamy is larger and increases more in metropolitan areas than in other urban areas. In Auckland, New Zealand's largest city (around a third of the population), homogamy accounted for a fifth of MLD inequality by 2013, up from 6% in 1986. Educational homogamy plays the biggest role in this process, but the effects of hours worked, employment status and migration status are relatively important too. Homogamy by age has little effect on income inequality. Using the Gini index as an alternative inequality measure yields similar results.

We continue our examination of inclusive growth at the firm level by examining heterogeneity in rent sharing in New Zealand using linked employer-employee data. We test for heterogeneity in rent sharing across a range of worker and firm characteristics including gender, ethnicity, age, qualifications, tenure, firm size, firm age, and industry. We also refine our measure of quasirents and estimate the level of excess quasi-rents per worker, or the amount of rents above the threshold beyond which rent sharing occurs. We find that between 20% and 30% of workers are in firms that earn zero excess rents. These workers are concentrated in the hospitality, administrative services, and retail industries and are more likely to be women, to be Māori or Pacific peoples, and have lower-level qualifications. We find an overall rent-sharing elasticity of 0.03, which is equivalent to a $38 increase in annual wages in response to a $1,000 increase in excess rents per worker. We find differences in rent sharing by levels of highest qualification, tenure, and ethnicity. We find no differences in rent sharing by firm size or firm age. Rent sharing is similar across industries, with workers in most industries receiving between $1,500 and $2,000 of rents per year. The auxiliary finance and professional, scientific, and technical services sectors share the most, while grocery retailing, food and beverage manufacturing and utilities share the least. Insurance type behaviour by firms is consistent with the variation in rent sharing across industries, although differences in bargaining power are also likely to play a role in explaining differences in rent sharing across groups

This paper analyses the effects of the Winter Energy Payment (WEP), that was introduced as part of the 2018 Families Package. The WEP amounts to a relatively small fraction of receiving households’ income and total expenditure (nearly 7% of main benefit support on average, 5% of total income support, and about 4% of total household income and expenditure); but is a substantial fraction of energy expenditures (120% on average, and 60% median). We focus on four sets of analyses: the WEP effects on recipient expenditure patterns (particularly on power) and self-report measures of wellbeing; whether WEP affected health outcomes, as measured by hospitalisations; the financial incentive of WEP to be on a main benefit during the winter months; and whether WEP had any effect on the receipt of hardship grants. Our analyses find predominantly statistically insignificant effects of the WEP across each of these outcomes, either because the effect sizes or the samples are relatively small, making it difficult to draw definite conclusions. However, the direction of estimated effects are generally suggestive that the WEP caused recipient households to increase their expenditures on electricity and power, alleviated material hardship and improved wellbeing, and positively affected health outcomes. We find little evidence of any increase in benefit receipt in response to the increased financial incentives of the WEP to be on-benefit.

We examine whether bilateral regional migration flows are driven by the city’s quality of life (QL) or quality of business (QB). The QL and QB measures are constructed using (quality-adjusted) rents and wages in each city. QL and QB reflect the willingness to pay of households and firms, respectively, for local amenities. The measures are constructed for 31 urban areas in New Zealand using five-yearly census data covering 1986 to 2013. We adopt a gravity model of regional migration – augmented by destination and origin QL and QB – to model bilateral flows of working-age migrants (post tertiary education and pre-retirement age). We also model flows between urban and rural areas and flows for the urban areas to and from overseas locations. We find different attractors for international versus domestic migrants according to the type of city amenity. International migrants are more attracted to cities with productive amenities whereas domestic migrants are more attracted to places with consumption amenities. Thus, in deciding on the type of city amenity to enhance, city officials implicitly choose the type of migrant that they attract as well as the type of city that may result.