Disasters and investment: Assessing the performance of the underlying economy following a large-scale stimulus in the built environment

Disasters are often followed by a large-scale stimulus supporting the economy through the built environment, which can last years. During this time, official economic indicators tend to suggest the economy is doing well, but as activity winds down, the sentiment can quickly change. In response to the damaging 2011 earthquakes in Canterbury, New Zealand, the regional economy outpaced national economic growth rates for several years during the rebuild. The repair work on the built environment created years of elevated building activity. However, after the peak of the rebuilding activity, as economic and employment growth retracts below national growth, we are left with the question of how the underlying economy performs during large scale stimulus activity in the built environment. This paper assesses the performance of the underlying economy by quantifying the usual, demand-driven level of building activity at this time. Applying an Input–Output approach and excluding the economic benefit gained from the investment stimulus reveals the performance of the underlying economy. The results reveal a strong growing underlying economy, and while convergence was expected as the stimulus slowed down, the results found that growth had already crossed over for some time. The results reveal that the investment stimulus provides an initial 1.5% to 2% growth buffer from the underlying economy before the growth rates cross over. This supports short-term economic recovery and enables the underlying economy to transition away from a significant rebuild stimulus. Once the growth crosses over, five years after the disaster, economic growth in the underlying economy remains buoyant even if official regional economic data suggest otherwise

The regional consequence of a disaster: Assessing employment transition during economic recovery

Orientation: Large-scale events such as disasters, wars and pandemics disrupt the economy by diverging resource allocation, which could alter employment growth within the economy during recovery. Research purpose: The literature on the disaster–economic nexus predominantly considers the aggregate performance of the economy, including the stimulus injection. This research assesses the employment transition following a disaster by removing this stimulus injection and evaluating the economy’s performance during recovery. Motivation for the study: The underlying economy’s performance without the stimulus’ benefit remains primarily unanswered. A single disaster event is used to assess the employment transition to guide future stimulus response for disasters. Research approach/design and method: Canterbury, New Zealand, was affected by a series of earthquakes in 2010–2011 and is used as a single case study. Applying the historical construction–economic relationship, a counterfactual level of economic activity is quantified and compared with official results. Using an input–output model to remove the economy-wide impact from the elevated activity reveals the performance of the underlying economy and employment transition during recovery. Main findings: The results indicate a return to a demand-driven level of building activity 10 years after the disaster. Employment transition is characterised by two distinct periods. The first 5 years are stimulus-driven, while the 5 years that follow are demand-driven from the underlying economy. After the initial period of elevated building activity, construction repositioned to its long-term level near 5% of value add. Practical/managerial implications: The level of building activity could be used to confidently assess the performance of regional economies following a destructive disaster. The study results argue for an incentive to redevelop the affected area as quickly as possible to mitigate the negative effect of the destruction and provide a stimulus for the economy. Contribution/value-add: This study contributes to a growing stream of regional disaster economics research that assesses the economic effect using a single case study

The displacement of retail spending by students in host cities owing to Covid-19: A case study

The regulations implemented by governments in response to COVID-19 to limit the movement of people affected the nature of consumer spending. Consumption behaviour change, resulting from disasters or government-enforced regulation, is visible through spending displacement and response to fast-moving changes in circumstances. This study examines student spending in the host cities of universities and how a pandemic, such as COVID-19, may reduce or eliminate the spending injections into the economy through displaced spending. The pre-Covid-19 student survey spending results revealed that 81 per cent of students’ monthly retail spending takes place inside the host city with the rest spent outside. The Covid-19 enforced move towards online learning, and the potentially longer-term shifts from contact to online learning, will have a significant spending displacement effect on the host city. The results show that students are indifferent to spending during the week or on weekends and that most students are content to stay within the host city during weekends. No obvious time preference between the week and weekend for spending was found. The results show that student spending represents significant spending in the host city and for the time the COVID-19 restrictions remain in place, the spending displacement and loss of income for local businesses will be significant. The loss of student spending amounts to approximately R2 million daily. This not only highlights the cost of enforced lockdown measures, but also provides important indicators to university management upon considering replacing the existing tuition model of contact learning with one of online learning. Such a decision will lead to a significant negative impact on the economic activity of the Potchefstroom business community with far-reaching implications for employment, income generation and wealth disbursement in this university city

The effect of spatial unemployment on the neighbouring regions’ economies: A regional case study of KwaZulu-Natal in South Africa

This article investigates the degree of spatial dependence of unemployment on neighbouring economies with possible implications for cross-border community development initiatives. The local municipalities within the KwaZulu-Natal province in South Africa are used as a case study. Spatial econometric techniques are employed that incorporate dependence between regions in close geographical proximity. Disaggregated data and knowledge about the dynamics at a sub-regional level are usually unavailable for designing employment policies, especially for regional economies in under-developed countries. The results suggest an absence of spatial unemployment clustering and autocorrelation between neighbouring economies. The absence of externalities implies that little mutual dependence exists between adjacent economies, and therefore municipal unemployment patterns can be viewed as spatially random. The economy of a region is therefore fundamentally heterogeneous in that its unemployment rates are determined and influenced by its unique and diverse factors rather than neighbouring unemployment trends or patterns

A new affordable housing development and the adjacent housing-market response

Background: Cities continue to grapple with a rising demand for housing, which affects affordability and the well-being of its citizens. This growth continues to put pressure on the delivery of adequate, affordable housing in well-located areas while the availability of infrastructure and proximity to economic nodes remains a challenge. This has led to increasing infill development of medium-density to high-density affordable housing in greenfield areas located adjacent to higher-income neighbourhoods. Aim: This study investigates how a new affordable housing development influences the locational and structural values of the adjacent, existing housing market. Setting: Transactional data of residential sales for two areas in South Africa are used to measure the value change. Both areas are located within an urban setting next to an open, greenfield area that was redeveloped for affordable housing. Methods: Two case studies are used and analysed with hedonic pricing modelling to identify and measure the value change for the locational and structural characteristics before and after the development of affordable housing. Results: The results reveal a changing housing market as the locational and structural characteristics change in value, further highlighting the importance of careful planning that preserves the existing market and also supplies affordable housing. Conclusion: The value of several structural characteristics of properties will change, revealing just how consumer preference responds when affordable housing is introduced in an existing housing market. Distance to an affordable housing project continues to influence the house market value and careful consideration should be made when planning to integrate an affordable housing development in an existing neighbourhood

The triple blow effect: Retailing in an era of disasters and pandemics—The case of Christchurch, New Zealand

In the last two decades, the retail sector has experienced unprecedented upheaval, having severe implications for economic development and sustenance of traditional inner-city retail districts. In the city of Christchurch, New Zealand, this effect has been exacerbated by a series of earthquakes in 2010/2011 which destroyed much of the traditional retail precinct of the city. After extensive rebuild activity of the city’s infrastructure, the momentum of retailers returning to the inner city was initially sluggish but eventually gathered speed supported by increased international visitation. In early 2020, the return to retail normality came to an abrupt halt after the emergence of the COVID-19 pandemic. This study uses spending and transaction data to analyze the compounding impact of the earthquake’s aftermath, shift to online shopping, and the retail disruption in the Christchurch central retail precinct because of COVID-19. The findings illustrate how consumers through their spending respond to different types of external shocks, altering their consumption patterns and retail mode (offline and online) to cope with an ever-changing retail landscape. Each event triggers different spending patterns that have some similarities but also stark differences, having implications for a sustainable and resilient retail industry in Christchurch. Implications for urban retail precinct development are also discussed

The Effect of Spatial Unemployment on the Neighbouring Regions’ Economies: A Regional Case Study of KwaZulu-Natal in South Africa

This article investigates the degree of spatial dependence of unemployment on neighbouring economies with possible implications for cross-border community development initiatives. The local municipalities within the KwaZulu-Natal province in South Africa are used as a case study. Spatial econometric techniques are employed that incorporate dependence between regions in close geographical proximity. Disaggregated data and knowledge about the dynamics at a sub-regional level are usually unavailable for designing employment policies, especially for regional economies in under-developed countries. The results suggest an absence of spatial unemployment clustering and autocorrelation between neighbouring economies. The absence of externalities implies that little mutual dependence exists between adjacent economies, and therefore municipal unemployment patterns can be viewed as spatially random. The economy of a region is therefore fundamentally heterogeneous in that its unemployment rates are determined and influenced by its unique and diverse factors rather than neighbouring unemployment trends or patterns

Exploring CBD retail performance, recovery and resilience of a smart city following COVID-19

The city of Christchurch, New Zealand, incurred significant damage due to a series of earthquakes in 2010 and 2011. The city had, by the late 2010s, regained economic and social normalcy after a sustained period of rebuilding and economic recovery. Through the concerted rebuilding effort, a modern central business district (CBD) with redesigned infrastructure and amenities was developed. The Christchurch rebuild was underpinned by a commitment of urban planners to an open and connected city, including the use of innovative technologies to gather, use and share data. As was the case elsewhere, the COVID-19 pandemic brought about significant disruptions to social and economic life in Christchurch. Border closures, lockdowns, trading limitations and other restrictions on movement led to changes in traditional consumer behaviors and affected the retail sector’s resilience. In this study, we used CBD pedestrian traffic data gathered from various locations to predict changes in retail spending and identify recovery implications through the lens of retail resilience. We found that the COVID-19 pandemic and its related lockdowns have driven a substantive change in the behavioral patterns of city users. The implications for resilient retail, sustainable policy and further research are explored

Canterbury game industry action plan 2022

This report reviews the video game and interactive media industry landscape, and is intended for game studios, local and international investors in the games industry, regional policy makers, central government, local government agencies, Christchurch City Council, and sector stakeholders

A family of process-based models to simulate landscape use by multiple taxa

Context: Land-use change is a key driver of biodiversity loss. Models that accurately predict how biodiversity might be affected by land-use changes are urgently needed, to help avoid further negative impacts and inform landscape-scale restoration projects. To be effective, such models must balance model realism with computational tractability and must represent the different habitat and connectivity requirements of multiple species. Objectives: We explored the extent to which process-based modelling might fulfil this role, examining feasibility for different taxa and potential for informing real-world decision-making. Methods: We developed a family of process-based models (*4pop) that simulate landscape use by birds, bats, reptiles and amphibians, derived from the well-established poll4pop model (designed to simulate bee populations). Given landcover data, the models predict spatially-explicit relative abundance by simulating optimal home-range foraging, reproduction, dispersal of offspring and mortality. The models were co-developed by researchers, conservation NGOs and volunteer surveyors, parameterised using literature data and expert opinion, and validated against observational datasets collected across Great Britain. Results: The models were able to simulate habitat specialists, generalists, and species requiring access to multiple habitats for different types of resources (e.g. breeding vs foraging). We identified model refinements required for some taxa and considerations for modelling further species/groups. Conclusions: We suggest process-based models that integrate multiple forms of knowledge can assist biodiversity-inclusive decision-making by predicting habitat use throughout the year, expanding the range of species that can be modelled, and enabling decision-makers to better account for landscape context and habitat configuration effects on population persistence