Robust economic frameworks and empirical methods, informed by evidence
Transportation decisions can have large and varied impacts on travellers and their communities. It’s important to measure these effects and consider their impact on various groups when planning projects.
Waka Kotahi uses a framework to decide which transport projects and programmes to pursue. The economic business case must contain a cost–benefit analysis (CBA). CBAs assess the economics of a proposal by valuing (monetising) the costs and benefits to all members of society. However, CBAs sum across a wide range of people and don’t calculate inequities between groups or individuals, or who ultimately benefits from the project.
Transport equity discussions focus on social justice. Equity impact analysis helps policymakers to make good decisions for a wide range of people. Distributional impact analysis needs to be complemented with wider investment and planning considerations. This includes any comprehensive policy framework that accounts for the overlapping effects of transport, housing and taxing policies.
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Torshizian, E., Byett, A., Isack, E., Fehling, A., & Maralani M. (2022). Incorporating distributional impacts in the cost–benefit appraisal framework (Waka Kotahi NZ Transport Agency research report 700).
In this novel application of the infrastructure Wider Economic Benefits approach, we quantify the cost to society of these further delays for the first time, by using the example of the Waikato Expressway. We used our subregional CGE model to estimate the downstream benefits of the Expressway. At a high-level, results of our analysis quantify the annual benefits of having the Waikato Expressway in the economy. Without the expressway in function as early as possible, $334 million of economic benefits were forgone each year.
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Principal Economics. (2022). Great decisions are timely: Benefits from more efficient infrastructure investment decision-making. Report to Infrastructure New Zealand.
This report examines the expected costs and benefits of the reforms. Changes are currently articulated mainly as broad principles and high-level descriptions of the institutional arrangements. Much of the detail is still to be developed, and the benefits of the reforms will depend on the physical outcomes that result, eg how much will pollutant emissions reduce, housing affordability improve, or Māori engagement increase?
It focuses on understanding the nature of costs and benefits under the different domains and how these are expected to change at the margin, eg whether increased environmental quality will yield positive net benefits. We provide an indication of the potential for benefits in different domains. The realisation of these potential benefits is dependent on the final design and implementation of the reforms.
Read the report here.
The Ministry for the Environment (MfE) appointed Principal Economics to review the Housing and Business Development Capacity Assessments HBAs). Our review included all councils’ HBAs, except for Rotorua and Wellington, which were not available at the time of this review. The focus of our review was on the requirements of the National Policy Statement on Urban Development 2020 (NPS-UD 2020). The outcome of our review indicates the areas of improvement for the next round of HBAs both for the councils and for the MfE and HUD (the ministries).
Reviews that have been published online can be found below:
Analysts may have multiple measures of household crowding, and so need to know which measure to emphasise. We analyse the relationships between alternative subjective and objective crowding measures and assess how well these alternative measures predict a measure of residential satisfaction. Statistically, a perceived crowding (PC) measure outperforms the people per bedroom (PPBR) measure, an objective measure of crowding. However, there may be bias in the relationship between PC and the residential satisfaction variable. Amongst objective measures, the Canadian National Occupancy Standard also outperforms PPBR. Nevertheless, all three measures are highly correlated and each helps to predict levels of residential satisfaction. Thus, any of the three measures provides a valid indicator of household crowding when assessing housing stress.
Torshizian, E., Grimes, A. (2021). Household Crowding Measures: A Comparison and External Test of Validity. J Happiness Stud 22, 1925–1951.