Urban Resilience and Social Security Uptake: New Zealand Evidence from the Global Financial Crisis and the COVID-19 Pandemic

Arbeitspapier

This paper focuses on the spatial variation in the uptake of social security benefits following a large and detrimental exogenous shock. Specifically, we focus on the Global Financial Crisis (GFC) and the onset of the COVID-19 pandemic. We construct a two-period panel of 66 Territorial Authorities (TAs) of New Zealand (NZ) observed in 2008-09 and 2020-21. We find that, despite the totally different nature of the two shocks, the initial increase in benefit uptake due to the COVID-19 pandemic was of a similar magnitude as that of the GFC, and the spatial pattern was also quite similar. We link the social security data with 146 indicator variables across 15 domains that were obtained from population censuses that were held two years before each of the two periods. To identify urban characteristics that point to economic resilience, we formulate spatial panel regression models. Additionally, we use machine learning techniques. We find that the most resilient TAs had two years previously: (1) a low unemployment rate; and (2) a large public sector. Additionally, but with less predictive power, we find that TAs had a smaller increase in social security uptake after the shock when they had previously: (3) a high employment rate (or high female labour force participation rate); (4) a smaller proportion of the population stating ethnicities other than NZ European; (5) a smaller proportion of the population living in more deprived area units. We also find that interregional spillovers matter and that resilient regions cluster.

Object Details

• Language: Englisch

References and Relationships

• Bibliographic citation: Series: IZA Discussion Papers ; No. 15510

Classification and Topics

• Classification: Wirtschaft ; Neural Networks and Related Topics ; Model Evaluation, Validation, and Selection ; National Government Expenditures and Welfare Programs ; Urban, Rural, Regional, Real Estate, and Transportation Economics: Regional Migration; Regional Labor Markets; Population; Neighborhood Characteristics
• Subject: urban economic resilience ; social security ; Global Financial Crisis ; COVID-19 ; panel data ; model selection ; spatial econometrics ; machine learning

Contributors, Places and Time

• Event: Geistige Schöpfung
• (who): Cochrane, William ; Poot, Jacques ; Roskruge, Matthew
• Event: Veröffentlichung
• (who): Institute of Labor Economics (IZA)
• (where): Bonn
• (when): 2022

Further information

• Handle: http://hdl.handle.net/10419/265731
• Last update: 10.03.2025, 11:42 AM CET