Impacts of Transport Infrastructure on Productivity and Economic Growth: Recent Advances and Research Challenges

ABSTRACT

The paper provides an update of the survey focusing on estimating the contribution of transport infrastructure to productivity and economic growth. The central questions addressed are possible reasons behind the conflicting results reported in the literature on the elasticity of economic output with respect to transport infrastructure investment. After providing a systematic review of recent empirical studies on the effects of transport infrastructure on productivity and economic growth, the paper notes that controversial results can be attributed to ten causes (grouped into three categories for distinguishing): (1) related to different contexts: research period, geographical scales, and country's capability in enabling economic development; (2) related to different phenomena that are being measured: different economic sectors, different types of transport infrastructure, and different quality levels of transport infrastructure; and (3) related to distinct ways of measuring a similar phenomenon: measures used to describe the dependent variable and explanatory variable, functional specification, and estimation method of the econometric model. Strong network externalities of transport infrastructure may result in nonlinearity of the relationship between transport infrastructure and economic growth. Moreover, the absence of spatial concerns in infrastructure's impacts is another important source of inconclusive results. Finally, building on recent literature, the paper has discussed policy implications and identified several research avenues for further research.     

The influence of the road network on private productivity measures using Data Envelopment Analysis: A case study from Spain

We evaluate the economic effects of investment in the road network on private regional activity. We employ provincial Spanish panel data from 1980 to 2007 to perform non-parametric frontier techniques based on Data Envelopment Analysis and to obtain the Malmquist productivity indexes, thus enabling us to examine the evaluation of the productivity growth via technological changes or efficiency gains. Additionally, we analyze the role of transport infrastructure on the evolution of Total Factor Productivity and its components through econometric techniques. Our results show important spillover effects. Moreover, our findings have significant implications for policy makers if we take into account the fact that the use of the road network in economic activity or in commercial relations greatly influences productivity growth.     

Has the transport-led economic growth effect reached a peak in China? A panel threshold regression approach

Using China’s province-level panel data from 1987 to 2010, this study explores the optimal level of transport infrastructure accumulation maximizing the growth rate. We investigate under what circumstances can additional transportation infrastructure capacity positively affect economic growth, based on panel threshold regression models. Our empirical findings suggest that there is a non-monotonic relationship between the stock of transport infrastructure and the long-run growth rate. The magnitude of transport-led economic growth effect significantly depends on the level of the existing transport network. The empirical results identify two endogenous cut-off points of efficiency of transport-led economic growth effect. When the highway network density is lower than 0.17 km/km², an insignificant positive relationship between highway infrastructure accumulation and economic growth was found. When the highway density is estimated between 0.17 and 0.38 km/km² or higher than 0.38 km/km², expanding the highway network has a significant positive effect on economic growth, but the magnitude of the impact is weaker in the latter, with the estimated coefficients equal to 0.23 and 0.09 respectively. Although China still enjoys a positive economic growth effect led by building more large-scale highway infrastructure, the magnitude of the effects of most provinces in China has already passed the saturation point and continuously expanding the highway network is not very productive.     

The impact of high-speed rail investment on economic and environmental change in China: A dynamic CGE analysis

This study investigates the impact of high-speed rail investment on the economy and environment in China using a computable general equilibrium (CGE) model. The analysis is implemented in a dynamic recursive framework capturing long-run capital accumulation and labor market equilibrium. A national level impact was simulated through direct impact drivers including land use conversion, output expansion, cost reduction, productivity increase, transport demand substitution and induced demand. The results suggest that rail investment in China over the past decade has been a positive stimulus to the economy, while the effect on CO₂ emissions generation has been large. Overall, the economic impacts of rail investment are achieved primarily through induced demand and output expansion, whereas the contribution from a reduction of rail transportation costs and rail productivity increases were modest. In addition, negligible negative impacts were found from land use for rail development and the substitution effect among other modes. Emissions reduction from substitution of rail for other modes was small and offset by output expansion due to lowered rail transport costs and induced demand.     

Empirical analysis of transportation investment and economic development at state, county and municipality levels

Numerous studies have found positive correlation between transportation infrastructure investment and economic development. Basically these studies use a conventional production function model augmented by a public capital input, mainly highways, rail and other transportation facilities. While the range of the measured economic growth effects varies widely among studies, the positive elasticity between transportation investment and economic development is now commonly accepted. Still a major puzzling issue is that the magnitude of the measured effect seems to decline significantly as the econometric model is further refined, mainly with regard to space and time lags. That is, the use of national or state data produces elasticity results, which are much larger than when using county or municipality data. Similarly, when we introduce into the econometric model a lag between the times when the transportation investments are made and when the economic benefits transpire, the measured elasticities decline with the size of the lag. Thus, the main objective of this paper is to investigate these issues analytically and empirically and provide a plausible explanation. We do so by using alternative econometric models, applying them to a database, which is composed of longitudinal state, county and municipality observations from 1990 to 2000. The key result is that transportation investments produce strong spillover effects relative to space and time. Unless these factors are properly accounted for many reported empirical results are likely to be overly biased, with important policy implications.     

Logistics as a driving force for development under the Belt and Road Initiative – the Chinese model for developing countries

ABSTRACT

An important objective of “the Belt and Road Initiative” is to promote the economic growth of countries in the region. China’s successful development experience, proposed in the initial stage of reform, can be summarised as “Looking for development, building the highway first”. This study is the first to evaluate whether logistics infrastructure has indeed contributed to economic growth by employing an error correction model with panel data from 2003 to 2014. In addition, we compare the influence levels of different sectors of logistics infrastructure in different regions, i.e. developed and developing regions. We focus on developing regions as they represent good development experiences for developing countries in the Silk Road Economic Belt. For developing regions, we find that the most influential factors are telecommunication and airway transportation, which should be the foci of attention in order to promote economic growth and reduce inter-region economic inequalities. The research confirms that logistics is indeed a driving force for economic growth in China, and that the contributions of specific sectors can be a useful reference for developing countries to determine prioritisation of investment in different logistics sectors across regions.     

Decomposition analysis of decoupling freight transport from economic growth in China

Freight transport industry plays a significant role in boosting economic growth, while also creating many negative externalities for social welfare and the environment. Using data from 1997 to 2017, this study employs the complete decomposition technique to identify the driving forces of freight transport and explores its internal relations with economic growth in China. The decomposition analysis focuses on four factors that are responsible for freight transport: economic activity, industrial structure, transport intensity, and haulage distance. Then, the decoupling index is adopted to examine the decoupling relationship between freight transport and economic growth in China. The results showed that weak decoupling between freight transport and economic growth was the main state during the study period. A strong decoupling effect was identified in 1997–1998, 2012–2013, and 2014–2015, whereas no decoupling effect was observed in 1998–1999, 2008–2009, and 2011–2012. The transport intensity was the most important contributor to the decoupling progress, the industrial structure effect played a role in promoting the decoupling progress over half of the years during the research period, and the haulage distance effect facilitated the decoupling progress in more than one-third of the years examined.     

Long-term impacts of transport infrastructure networks on land-use change: an international review of empirical studies

Improvements in geographical information systems, the wider availability of high-resolution digital data and more sophisticated econometric techniques have all contributed to increasing academic interest and activity in long-term impacts of transport infrastructure networks (TINs) on land use (LU). This paper provides a systematic review of recent empirical evidence from the USA, Europe and East Asia, classified regarding the type of transport infrastructure (road or rail), LU indicator (land cover, population or employment density, development type) and outcome (significance, relationship’s direction) as well as influential exogenous factors. Proximity to the rail network is generally associated with population growth (particularly soon after the development of railway infrastructure), conversion to residential uses and the development of higher residential densities. Meanwhile, proximity to the road network is frequently associated with increases in employment densities as well as the conversion of land to a variety of urban uses including commercial and industrial development. Compared with road infrastructure, the impact of rail infrastructure is often less significant for land cover or population and employment density change. The extent of TINs’ impact on LU over time can be explained by the saturation in TIN-related accessibility and LU development.     

Transport infrastructure costs in low-carbon pathways

The rate and manner in which transport infrastructure (e.g. roads, railway tracks, airports) is deployed, will play an important role in determining energy demand, greenhouse gas emissions and the economic impact of the transport sector. This paper describes an exercise where the costs of infrastructure deployment for the transport sector have been incorporated into the IMACLIM-R Global E3 IAM. In addition to adding these costs, the modelling of the criteria for the deployment of infrastructure for roads has also been improved. It is found that this model recalibration results in a more accurate baseline as compared to historically observed data (2001–2013) for investments in energy demand, road infrastructure, and passenger kilometers travelled. Regarding macroeconomic effects, it is found that the imposition of a carbon emission trajectory to 2100 cause GDP to decrease relative to the newly calibrated baseline – this is a standard IAM result. However, when the deployment of infrastructure for roads and air travel is further constrained, the GDP loss is less than with a fixed carbon emission trajectory only. This is because early restriction of infrastructure for roads and air travel allows an expansion of public transport infrastructure which is adequate to meet low-carbon transport service demand whereas when less public transport infrastructure is available, more costly mitigation investments must be made in other parts of the economy. This suggests that restricting infrastructure deployment as a complementary policy to carbon pricing, lowers the cost of mitigation.     

Institutional issues in planning for more uncertain futures

Future travel demand has always been difficult to estimate. Recent trends of a slow down or stagnation in traffic growth combined with substantial demographic, economic, and technological shifts further complicate that task. This poses a significant planning challenge given that decision-making is often based on the benefits of infrastructure investments which accrue over periods as long as 60 years. In contrast to the changing ideas around what mobility in the future will look like and the types of demand it may need to service, the practice of forecasting future travel demand remains largely unchanged as do the decision-making processes which flow from this. Alternative approaches to thinking about futures such as scenario planning exist but have had more limited deployment in the transport sector. This paper explores the institutional issues surrounding the purpose, practice and barriers to changing the approaches of forecasting and decision-making through an exploration of the state of practice in the UK drawing on interviews with 23 practitioners. Drawing on Hall’s work on policy change, the research finds that there is a strong policy paradigm built around the relationships between transport investment and traffic growth. This has strengthened since the recession with an increased focus on the relationship between transport and job creation. The forecasting approaches in use today are an important part of a complex decision-making apparatus reflective of specialized policy arenas like transport. Challenges in acknowledging, representing and communicating uncertainty are identified leaving a growing tension between planning visions and planning practice. We conclude by reflecting on events which may stimulate a broader reframing of how we plan for transport futures whilst embracing key uncertainties.

     

Economic analyses of sea-level rise adaptation strategies in transportation considering spatial autocorrelation

This paper reports the impacts of economic analysis results on sea-level rise adaptation decision making with different economic analysis methods. The methodology was applied to Hillsborough County, Florida. A general conclusion is that partial shoreline protection should be implemented to reduce the potential impacts of sea-level rise on important land use, then transportation infrastructure is preferred to be protected or accommodated, and finally managed relocation should be adopted. More specifically, the results show that the best adaptation strategy is shoreline protection plus transportation infrastructure accommodation; the length of shoreline protection plays an important role in the economic analysis results, and shoreline protection and accommodation adaptation strategies for all areas are not recommended because of either high costs or low benefits; the value of travel time saving and spatial autocorrelation play important roles in the economic analysis results of accommodation strategy, which highlights the importance of including indirect economic factors and spatial autocorrelation impacts when making sea-level rise adaptation decisions.     

Influences on commuter trip departure time decisions in Singapore

This paper provides empirical evidence to support the widely held view that institutional factors such as official work start times and staggered working hours are powerful policy tools in traffic management and in influencing travel behaviour. This approach is to be preferred over continued investment in infrastructure given the scarcity of land in Singapore. A more efficient use of existing infrastructure could be achieved by spreading peak travel. Full utilisation of the Mass Rapid Transit will depend on changing the commuter's perception on multi mode travel in addition to using public transport. While many studies have been carried out on modal choice, research on commuter trip departure decisions have been few and remain largely least understood. This paper employs multinomial logit and simultaneous nested logit analysis to model the choice of departure time (using household data collected in Singapore in 1983). Preliminary findings show that schedule delay, travel cost, and journey time to be important influences on commuter's choice of trip departure time to work. Some difficulties are highlighted and suggestions for further research are made.     

Linking land use and transportation in a rapidly urbanizing context: A study in Delhi,India

Cities in developing countries like India are facing some of the same concerns that North American cities are: congestion and urban growth. However, there is a sense of urgency in cities like Delhi, India in that this growth is far more rapid as both urbanization and motorization are ongoing processes that have not yet peaked. In this paper, we examine land use change and its relationship with transportation infrastructure and other planning related variables in a spatial context. We estimate land use change models at two different scales from separate data. Cellular automation and Markov models were used to understand change at the regional scale and discrete choice models to predict change at the local level. The results suggest that land use in the Delhi metropolitan area is rapidly intensifying while losing variety. These changes are affected by industrial, commercial and infrastructure location and planners and policy-makers need to better understand the implications of location decisions. We also examine these results in the context of a policy framework for data-based planning that links land use and transportation models for Delhi.     

New highways and land use change: Results from a quasi-experimental research design

Understanding links from new highway construction or capacity expansion to regional growth patterns is crucial for transportation planners and policy makers. In this paper, we incorporate a lagged adjustment regional growth model into a quasi-experimental research design to examine the association between new highway investments and land use change in three California counties. Our study areas provide a mix of urban, small town, and exurban highway projects in order to explore the different effects across project types and geographic contexts. The central finding of this research is that while improvements in surface transportation infrastructure can have large impacts on growth patterns, the nature of the effect depends on the context of the highway investment.     

Transport infrastructure and long-run economic growth in OECD countries

This paper provides an empirical evaluation of the growth impact of public infrastructure in a panel of 18 OECD countries during 1870–2009. This study goes beyond the traditional analysis of growth accounting models by exploring the indirect effect of stock of core infrastructure on output growth through its impact on productivity. Constructing a long-run historical dataset on infrastructural capital formation spanning from 1870, estimated results show that growth in both labour productivity and total factor productivity are positively, but not substantially, influenced by growth in the stock of infrastructure. Furthermore, applying the system GMM technique (Generalised Method of Moments) revels that although rate of returns to investment in infrastructure exceed the private rate in OECD countries, it is not as high as positive externalities associated with investment in equipment and structure investment.     

Estimation and validation of a microscopic model for spatial economic effects of transport infrastructure

The spatial economic effects in integrated land use and transport models are increasingly disaggregate and can benefit from improved knowledge into the effect of accessibility and agglomeration on the spatial behaviour of firms. This article strives to contribute to this knowledge by first analysing the influence of accessibility and agglomeration on firm behaviour with exceptionally detailed firm data for the province of South Holland in The Netherlands. Next the added value of incorporating such effects in urban simulation models is tested with two series of validation runs with a microscopic model for firm dynamics.The presented Spatial Firm-demographic Micro-simulation (SFM) model simulates transitions and events in the firm population, including firm relocations, firm growth, firm dissolution and firm formation. Accessibility is measured with proximity to infrastructure access points and logsums of business and commuting trips from a transport model. Agglomeration measures are based on theories from urban economics and integrate travel time range bands into measures for specialisation and diversification. Estimation results confirm a significant influence of accessibility and agglomeration on the choice behaviour of firms. Application of these measures prove to increase the validity of the firm-demographic simulation model to a significant but modest extend.     

The spatial productivity of transportation infrastructure

Transportation infrastructure services may cause an impact on the economy of the region in which they are located and, additionally, they are likely to have an impact on other regions. This effect has been labeled the spillover effect. In this study, the existence of direct and spillover effects of road, railway, airport and seaport infrastructure projects is tested by estimating a production function. Together with this primary objective, two common concerns in the literature are addressed: the lack of theoretical foundations for spatial econometrics models and the likely endogenous relationship between transport infrastructure and economic development. The estimated production function takes the form of a Spatial Durbin Model and is estimated using panel data from the 47 peninsular Spanish provinces by alternatively applying a Maximum Likelihood estimator and Instrumental Variables/Generalized Method of Moments estimators. According to the estimates, road transport infrastructure positively affects the output of the region in which the infrastructure is located and its neighboring provinces, while the remaining modes of transportation projects cause no significant impacts on average.     

A cost performance analysis of transport infrastructure construction in Slovenia

Due to limited data availability only a few studies have been able to provide statistically significant evidence on cost overruns in transport infrastructure investments and their systematic nature, and fewer still for road infrastructure investments. The body of available evidence refers to the most economically developed countries, while very little evidence was found regarding other countries. In this article the authors focus on cost performance of road infrastructure constructed through the National Motorway Construction Programme in Slovenia. Methodologically the study departs from other studies in this field by building on detailed expenditure data and not aggregate reports from the relevant institution. This enabled the analysis of four individual project cost categories (construction cost, land acquisition damages and others) and comparably more accurate results. A representative sample of randomly selected completed projects in the period 1995–2007 revealed that the cost overruns (19%; SD = 46.10%) in the entire period studied do not appear to be higher than in other comparable studies. At the same time the study results showed that cost overruns were unstable, i.e. much higher for older projects.     

Accessibility and transport infrastructure improvement assessment: The role of borders and multilateral resistance

The market potential indicator is a commonly used tool in transport planning for evaluating the potential economic effects derived from improvements in transport infrastructures. The general assumption is that exports from a given region will rise with increased accessibility, thus benefiting economic activities. However, the specification of the market potential model is typically very simple and ignores both the impact of competing rivals and the role of international borders, which leads to unrealistic results. Spatial interaction models on bilateral trade have already proved that international trade is affected by multilateral resistance, borders, adjacency, language or currency. Nevertheless, apart from some recent analyses that simply calibrate the distance decay parameter from trade datasets, these variables have hardly been integrated into research on market potential. This paper sets out to demonstrate that more realistic results are obtained by calibrating the distance-decay parameter and introducing the impact of competing rivals and border effects into the market potential formulation. The proposed model is then applied to the assessment of the accessibility impacts of new road transport infrastructure in the European Union between 2001 and 2012, which shows that the greatest improvements in accessibility were experienced by peripheral countries with high road infrastructure investment.     

Socially and environmentally appropriate urban futures for the motor car

In its relatively short life, the automobile has provided a level of mobility unlikely to have been feasible with a reliance on conventional forms of land based public transport. It has contributed in both a positive and negative way to the quality of life, transforming our cities, our way of life, and giving us a greater command over time and space. Concern over the undesirable social and environmental impacts has increased over time, with calls for governments to take action to reduce the automobile's dominant role. New investment in fixed-track public transport and bus priority systems together with strategies to discourage travel have been proposed to improve accessibility and to aid in cleaning up the physical environment. This paper reviews some of the issues facing society as it works to identify policies to achieve an economically and environmentally sustainabie future. There is a need for a broader set of policies to facilitate alternative land use-transport lifestyles while facing appropriate pricing signals. Some of the key issues are adjustments in the relative prices of location and transport, spatial incentives to make public transport economically viable (i.e. changing urban densities, zoning/incentive changes to allow more infill), road pricing (i.e. charging cars the economic cost of using the roads), new information technology systems (e.g. IVHS) to improve the efficiency and effectiveness of transport infrastructure, major improvements in the fuel efficiency of fossil fuelled vehicles, and alternative-fuelled vehicles (clean-air vehicles).