A large body of literature considers the productive advantages of cities, or “agglomeration economies”. Most empirical studies report positive agglomeration economies, although large variation exists in the magnitude of estimates. We use a meta-analysis to explore this variation, drawing on 6,684 estimates from 295 studies that cover 54 countries and span six decades. Using rich data and robust methods, we unify and extend earlier reviews. For our preferred combination of study attributes, we find agglomeration elasticities are likely to lie in the range 2.7–6.4%. Our findings confirm the controls enabled by detailed data give rise to smaller estimates. We also document several trends, with overall estimates rising from 1980–2000 and then falling. Estimates for manufacturing sectors, in contrast, fell for the entire six decades covered by our data. We speculate on possible causes of these trends, such as urban congestion, technological shocks, freight costs, and regulatory settings.

We study the effects of crime and agglomeration on urban amenity using data for 134 locations in New Zealand and report three key findings. First, the negative effects of crime operate mostly via rents, with elasticities that range from −0.15 to −0.44. Accounting for endogeneity leads to larger elasticities in some specifications, possibly due to sorting effects. Second, crime has negative effects on the value of urban amenities, with elasticities that range from approximately −0.03 to −0.06 for firms and −0.02 to −0.09 for workers. Using reduced-form models, we show that these effects imply an elasticity of population with respect to crime of −0.04 to −0.10. Third, controlling for crime causes estimates of agglomeration economies to increase by approximately 0.01–0.02 points, on average. Our findings confirm that crime is an important urban congestion cost that erodes productivity and well-being.

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.

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.

Auckland offers a case study of where, why, and how policy changes have caused parking supply and prices to adjust toward a more efficient level. Since the 1990s, the city has trailed and extended new approaches to parking management, including removal of minimum parking requirements from business and mixed-use zones and introduction of priced parking to manage on-street parking demand. Auckland's policy approach has emphasized (1) complementary strategic policy settings for managing the supply and price of parking and (2) the use of low-cost trials to gather evidence and build the case for further changes to policy.

We formulate and estimate a simple dynamic spatial general equilibrium model of urban development. Notwithstanding its simplicity, the model allows for adjustment frictions in housing markets; workers with heterogeneous productivities and preferences; and agglomeration economies in production and consumption. We estimate our model as a system of equations using panel data for workers residing in 132 urban settlements in New Zealand for the period 1976 to 2013. In terms of housing markets, we find strong evidence of increasing marginal costs and large adjustment frictions. The latter suggests demand shocks lead to temporarily elevated prices. In terms of agglomeration economies, we find New Zealand’s cities and towns offer economies of scale to producers, in the form of higher wages, but diseconomies of scale to consumers. By exploiting the panel structure of our data, we consider whether our findings are stable over time. We use the results of our model to compare relative productivity and amenity levels in New Zealand’s cities and towns and consider implications for research and policy.

The NSW Treasury commissioned and collaborated with Veitch Lister Consulting (VLC) to explore net public transport expenditure per capita (“net PTE”) in major Australian capital cities. The purpose of the research was to identify factors that are arguably outside the short-term control of state governments, including—but not limited to—geography, density, and congestion. To identify effects on net PTE, VLC developed a suite of regression models using detailed micro-data on public transport supply and demand. In these models, effects are identified from variation both within and between capital cities in Australia. Results identify several factors that give rise to relatively large differences in net PTE between Australian cities, which are robust to a range of controls, specifications, and controlling for endogeneity.

Using theoretically consistent measures derived within the urban economics literature, we compile quality of life and quality of business indicators for 130 ‘cities’ (settlements) from 1976 to 2013, using census rent and wage data. Our analyses both include and exclude the three largest cities (Auckland, Wellington, Christchurch). Places that are attractive to live in tend to be sunny, dry and near water (i.e. the sea or a lake). Since the mid-1990s, attractive places have also had relatively high shares of the workforce engaged in education and (to a lesser extent) health. Attractive places have high employment shares in the food, accommodation, arts and recreation service sectors; however (unlike for education and health) we find no evidence that quality of life is related to changes in employment share for these sectors. The quality of business is highest in larger cities, and this relationship is especially strong when the country’s three largest cities are included in the analysis.

We analyse which factors attract people and firms (and hence jobs) to different settlements across New Zealand. Using theoretically consistent measures derived within the urban economics literature, we compile quality of life and quality of business indicators for 130 ‘cities’ (settlements) from 1976 to 2013, using census rent and wage data. Our analyses both include and exclude the three largest cities (Auckland, Wellington, Christchurch). Places that are attractive to live in tend to be sunny, dry and near water (i.e. the sea or a lake). Since the mid1990s, attractive places have also had relatively high shares of the workforce engaged in education and (to a lesser extent) health. Attractive places have high employment shares in the food, accommodation, arts and recreation service sectors; however (unlike for education and health) we find no evidence that quality of life is related to changes in employment share for these sectors. The quality of business is highest in larger cities, and this relationship is especially strong when the country’s three largest cities are included in the analysis.

Many policy-makers are grappling with the twin challenges posed by growing travel demands and persistent socioeconomic inequality. To address these issues, numerous studies propose and apply "justice tests", which relate the effects of transport policies to prevailing socioeconomic deprivation. While the theoretical foundations of justice tests are well-established, there exists less agreement on methodological aspects and empirical specifications. In this paper, we propose a new criterion for evaluating the results of justice tests namely the correlation coefficient and explore its sensitivity to empirical assumptions by way of a case study of a major public transport investment. In comparison to other criteria identified in the literature, our proposed criterion appears to generate relatively stable results while being simple to calculate, interpret, and communicate.

Many cities are grappling with the twin challenges posed by growing travel demands and persistent socioeconomic inequality. From a policy perspective, major transport investments would ideally be efficient – in that their economic benefits exceed their costs – as well as equitable – in that the distribution of benefits favour the less well-off. To this end, this study formulates and applies a justice test for public transport investments that relates accessibility to inequality. The specification of the justice test enables comparisons between projects and across jurisdictions. We apply the proposed justice test to Auckland’s City Rail Link and test the sensitivity of results to changes in key assumptions. We conclude that well-specified justice tests are a straightforward adjunct to the policy frameworks that are currently used to evaluate public transport investments in many jurisdictions. NOTE TO READER An extended version of this paper has been submitted to the journal Transport Policy, where it has been conditionally accepted for publication subject to revisions. 1 PhD student, University of Auckland; MA (Urban and Regional Planning); IPENZ Transportation Group member;; sadli@gmail.com 2 Principal, Veitch Lister Consulting; IPENZ Transportation Group member; BA (History), ME (Eng. Sci.), MPhil. (Economics); PhD student, Vrije Universiteit Amsterdam; stuart.donovan@veitchlister.com.au Applying Justice Tests to Public Transport Adli and Donovan Page 1 IPENZ Transportation Group 2018 conference, Queenstown 21 – 23 March 2018

Accessibility is generally accepted as an important benefit of public transportation (PT) systems. Consistent measurement, however, remains a challenge. In this paper we propose methods for measuring accessibility, which we apply to cities in Auckland, Brisbane, Perth, and Vancouver. As our proposed method relies only on open data, meaningful comparisons are possible across a wide-range of jurisdictions. Our results indicate that Auckland performs relatively poorly in accessibility compared to Brisbane, Perth, and Vancouver. The methodology developed into this paper is provided as a GIS toolbox, providing planners and analysts with a simple and fast tool to calculate accessibility.

In the Venables model, commuting costs determine the size of the Central Business District (CBD) workforce and thus the productivity and wage premium generated by agglomeration economies in the CBD. Improvements in public transit modes increase numbers willing to commute to work in the CBD, and generate additional productivity gains. The resulting efficiencies can greatly exceed estimates of direct travel time savings from the PT innovation. The Venables model is operationalised and extended, and applied illustratively to two actual PT innovations in Auckland: improved bus lanes, and improved rail service.

This paper considers the financial costs of a rapid national transition to electric vehicles (EVs) in comparison to a baseline scenario that is characterised by continuing use of internal combustion engine vehicles (ICEs). The Australian car fleet, which is responsible for 8% of national greenhouse emissions, is used as a case study. To explore the potential range of costs associated with rapid climate mitigation via the transport sector, the transition is assumed to occur very rapidly (by 2025). The analysis focusses on urban areas, where extensive charging infrastructure is assumed to be made available, including rapid charging facilities. Due to uncertainty over input variables, two "boundary" scenarios were constructed. In the High Cost Scenario, a rapid shift to EVs was found to cost approximately 25% more than the continuing use of ICEs, assessed over the period 2015-2035. However, in the Low Cost Scenario, where costs of EVs (especially batteries) fall more rapidly, EV maintenance costs are at the lower end of projections, and liquid fuel costs at the higher end of projections, a rapid transition to EVs is found to cost approximately the same as the use of ICE vehicles. This suggests that a rapid transition towards EV technologies for urban car travel may offer a cost-effective second-best climate change mitigation strategy. More comprehensive transport sector transformation, including changes in transport and land use policy designed to facilitate mode shift, might further reduce the costs of such a transition. (C) 2016 Elsevier Ltd. All rights reserved.

Urban form describes the physical shape and settlement/land use patterns of cities and towns. This research addressed two key questions: 1) How urban form impacts on transport and economic outcomes and 2) How regional and local council planning policies can contribute to a more efficient and durable urban form. We found that urban form has modest impacts on transport outcomes, through reductions in vehicle ownership and drive mode share. On the other hand, urban form was found to have relatively large impacts on economic outcomes, primarily by virtue of its impacts on agglomeration economies. Several promising areas of further research have been identified that would seek to strengthen and deepen our understanding of the linkages between urban form, transport, and economic outcomes.

This work develops a wind intensity interference coefficient which captures the interference caused by an upwind turbine on a downwind turbine in the same wind flow. This coefficient includes the use of a Weibull distribution to handle variability in the wind velocity, and also accounts for the geometric relationship between the turbines and the boundaries of the wind sector. This interference coefficient then forms part of a mixed integer linear program (MILP) which is used to optimise the locations of wind turbines within a wind farm site. The MILP approach is an exact method that can guarantee that the turbine locations determined by the model are optimal with respect to an a priori chosen set of possible turbine locations. Tests on an example data set (based on a demonstration case in the WindFarmer software) show, for the particular wind resource used, that interference results in a loss of power of approximately 4.2% when compared to the power production which would be predicted without accounting for interference.

There is significant potential for optimizing the design of a wind farm in New Zealand. The complex nature of the wind resource and the larger size of the wind farms being built increase the complexity of the decisions that need to be made, while tight economic margins create a drive for greater efficiency. Current industry practice utilises commercial packages that are heuristic in nature and limited in the types of constraints that can be modelled. A mixed integer programming model for optimizing the layout of a wind farm has been developed that is capable of determining the optimal locations of turbines subject to constraints on the number of turbines, turbine proximity, and turbine wake. Results have shown that this model produces layouts that are comparable to those from a commercial package. Moreover, this model can be extended to include capital budget constraints, noise and line of sight restrictions, constraints relating to wind quality such as maximum gusts, inflow angles and turbulence, as well as modelling reticulation and different mixes of turbines.