Quantitative Spatial Model Research Articles

Faster, taller, better: Transit improvements and land use policies

We study the interaction between transit improvements and land use policies. Bengaluru, one of India’s largest cities, inaugurated a metro system in 2011 but has extremely low building heights, even near metro stations. We build a rich dataset and a quantitative spatial model in which heterogeneous workers choose among different commuting modes. We find that the metro increases citywide output and welfare, even net of costs. However, the net gains are several times larger with transit-oriented development (TOD), i.e., when height limits are relaxed near stations. Moreover, TOD and the construction of the metro are complementary policies.

Urban Transit Infrastructure and Inequality

Abstract We propose a quantitative spatial model featuring heterogeneous worker groups and their travel to consume non-tradable goods and services. We consider the opening of the Downtown Line (DTL) in Singapore, which connected regions where high-income households have residential amenities to where non-traded sectors are productive. Leveraging transit farecard data, we show that high-income workers saw large welfare gains but low-income workers gained little. Everyone enjoyed improved access to consumption opportunities, but low-income jobs in non-tradables moved to less attractive workplaces. Abstracting from consumption travel understates the disparate impact across worker groups three-fold.

Cross-regional economic impact of carbon emission regulations: A quantitative spatial equilibrium model for China

We develop and quantitatively evaluate a spatial general equilibrium model that incorporates carbon emission regulations. We study the impact of emission regulation on the economies of regions within a country under climate change mitigation goals, and how the impact of emission regulation in one region influences other regions through regional‒sectoral linkages. The model is calibrated using Chinese regional and sectoral data, and several counterfactual exercises are performed. The results indicate that undifferentiated increases in emission regulation across regions have resulted in inter-regional differences in real GDP changes; however, “equity-oriented” regionally differentiated emissions regulations reduce this imbalance. Regarding interactions between regions, negative impacts on the economy are characterized by geographical proximity, whereas positive impacts are not geographically constrained. Sectoral linkages exacerbate the negative economic impacts of emission regulations and widen regional disparities. Additionally, we demonstrate the extended application of our model through two case studies.

Short-term impact of climate change on labor market in China: Quantitative spatial analysis based on an oligopsony model

Assessing the impact of climate change on the economy is an important issue for designing climate policy. By constructing an oligopsony model to depict the incompleteness of the labor market and using the quantitative spatial model analysis method, we quantitatively estimated the short-term impact of climate change on the labor market in China. Then, to control climate change, the optimal climate change governance intensities (CCGI) of multi-governments satisfying CD preferences and Stackelberg game are designed and solved. The results show that climate change leads to a decrease in wages and labor supply in labor market equilibrium and a loss of market aggregate income and labor scale. Climate change has led to a shift in labor from the agricultural and dirty sectors to the clean sector. The regional labor distribution is also being “disrupted” due to climate change. Moreover, declining migration costs and increased subsidies help to reduce the negative impacts of climate change. The optimal CCGI of the central government is higher than that of the provincial government. The optimal CCGI is higher in the eastern provinces than in the central and western regions. Implementing CCGI would mitigate the negative climate change shocks to the labor market in China and increase welfare. The conclusions of this paper provide strong support for preventing climate change risks and actively participating in global climate change governance.

Impact of urban form on housing affordability stress in Chinese cities: Does public service efficiency matter?

Residential housing affordability stress is an important catalyst of class solidification and the growing worldwide social divide. Based on a quantitative spatial model that considers government utility and decision-making and uses nighttime lighting data, this study utilizes potential urban footprint as an instrumental variable to examine the mechanisms underlying the effects of the urban form on housing affordability stress and the moderating effect of government public service expenditure efficiency. The theoretical model and empirical results indicate the following. (i) The compact urban form increases housing affordability stress through productivity and urban living amenities. (ii) The efficiency of government public service expenditures affects industrial agglomeration externalities and public service accessibility, precipitating a negative moderating effect on the relationship between urban form and housing affordability stress. (iii) Based on LandScan data, a polycentric layout was found to weaken the compact urban form's ability to reduce housing affordability stress and reduce the government spending efficiency's negative moderating effect on public services. These findings demonstrate that the positive externalities of agglomeration production and the rationalization of government public service expenditures play important roles in housing market stabilization, which is helpful in facilitating better resource factor allocations by the government in the urban sprawl process.

Internal migration, remittances and economic development

We develop a quantitative spatial equilibrium model with endogenous migration and remittance decisions within households to examine the joint effect of migration and remittances on economic development. We apply the model to internal migration in China. Counterfactual analysis of the calibrated model shows that the presence of remittances increases migration and welfare, reduces regional inequality and facilitates structural change. Compared to a conventional single-person migration model, our household model suggests a larger reduction in regional inequality and stronger reallocation of employment from agriculture to manufacturing and services in response to the decline in migration costs over the period of 2000 to 2010.

Local causes and aggregate implications of land use regulation

I study why some cities have strict land use regulation, how regulation affects the U.S. economy, and how policymakers can mitigate its negative consequences. I develop a quantitative spatial equilibrium model where local regulation is determined endogenously, by voting. Landowners in productive cities with attractive amenities vote for strict regulation. The model accounts for 40% of the observed differences in regulation across cities. Quantitative experiments show that excessive local regulation reduces aggregate productivity, but not necessarily welfare because, unlike renters, landowners benefit from regulation. I propose federal policies that raise productivity and welfare by weakening incentives to regulate land use.

Commuting, Labor, and Housing Market Effects of Mass Transportation: Welfare and Identification

Abstract I study Los Angeles Metro Rail's effects using panel data on bilateral commuting flows, a quantitative spatial model, and historically motivated quasi-experimental research designs. The model separates transit's commuting effects from local productivity or amenity effects, and spatial shift-share instruments identify inelastic labor and housing supply. Metro Rail connections increase commuting by 16% but do not have large effects on local productivity or amenities. Metro Rail generates $94 million in annual benefits by 2000 or 12–25% of annualized costs. Accounting for reduced congestion and slow transit adoption adds, at most, another $200 million in annual benefits.

The economic costs of trade sanctions: Evidence from North Korea

This paper investigates the economic costs of the recent United Nations sanctions on North Korea. Exploiting a novel data set on North Korean firms, we construct measures of regional exposure to export and intermediate input sanctions and show that trade sanctions cause sharp declines in local nighttime luminosity. Additional analysis of newly available product-level price data reveals that import sanctions led to significant increases in market prices. We then estimate a quantitative spatial equilibrium model using cross-region variations. The model implies that the sanctions reduced the country's manufacturing output by 12.9% and real income by 15.3%. We further quantify the potential impact of alternative sanction scenarios.

Simulation and Prediction of Territorial Spatial Layout at the Lake-Type Basin Scale: A Case Study of the Dongting Lake Basin in China from 2000 to 2050

The study of spatial layout in China is changing from land use/land cover to territorial spatial layout and is mostly carried out at the administrative division scale. However, the driving factors affecting the evolution of territorial spatial layout are not all influenced by administrative boundaries. As cities are mostly centered on lakes and water systems, the evolution of territorial spatial layout in lake-type basins must have its own special characteristics. Taking the Dongting Lake Basin (DLB), a representative lake-type basin in China, as an example, this study identifies its territorial spatial layout elements and couples the system dynamics model with the patch-generating land-use simulation model based on multi-layer perceptron artificial neural networks. This study identified the best combination of driving factors and research step size affecting the evolution of territorial spatial layout. An improved quantitative spatial coupling model was used to simulate the territorial spatial layout of the DLB from 2000 to 2050 and identify its evolutionary characteristics and trends at both the elemental level and for three types of space. The simulation and prediction of territorial spatial layout from the lake-type basin hydrology scale can provide a reference for the formulation of regional territorial spatial planning policies.

Market Power and Spatial Competition in Rural India

Abstract Market power of intermediaries contributes to the low incomes of farmers in India. I study the role of spatial competition between intermediaries in determining the prices that farmers receive in India by focusing on a law that restricts farmers to selling their goods to intermediaries in their own state. I show that the discontinuities in market power generated by the law translate into discontinuities in prices. Increasing spatial competition by one standard deviation causes prices received by farmers to increase by 6.4%. I propose and estimate a quantitative spatial model of bargaining and trade to shed light on spatial and aggregate implications. Estimates from the structural model suggest that removing the interstate trade restriction in India would increase competition between intermediaries. Thereby average farmer prices and their output would increase by at least 11% and 7%, respectively. The value of the national crop output would increase by at least 18%. However, there are distributional consequences as well, as some farmers stand to lose due to increased local production.

Immigration and Spatial Equilibrium: The Role of Expenditures in the Country of Origin

We document that international migrants concentrate more in expensive cities—the more so, the lower the prices in their origin countries are—and consume less locally than comparable natives. We rationalize this empirical evidence by introducing a quantitative spatial equilibrium model, in which a part of immigrants’ income goes toward consumption in their origin countries. Using counter-factual simulations, we show that, due to this novel consumption channel, immigrants move economic activity toward expensive, high-productivity locations. This leads to a more efficient spatial allocation of labor and, as a result, increases the aggregate output and welfare of natives. (JEL F24, J15, J31, J61, R23)

Labour market and redistributive consequences of the Syrian refugees in Turkey

Abstract This paper analyses the labour market effects and redistributive consequences among natives of the arrival of the Syrian refugees in Turkey. For that, we use the quantitative spatial model developed in Loayza et al. (2021), in which low- and high-skill workers can choose where to live/work and firms within each region can choose to operate in the formal or informal sectors and, if formal, whether to hire their workers formally or not. We use the estimated model to quantify the effects of the ‘refugee shock’ on informality, wages, profits, and tax revenues across regions and the country as a whole. We show that informality increases among low-skill but decreases among high-skill workers and the skill premium increases. Wages of low-skill workers decline substantially in the most affected regions, but tax revenues and profits per worker increase. Redistributing tax revenues can substantially reduce low-skill workers’ losses in most affected areas. In addition, redistributing profits can completely revert both low- and high-skill workers’ losses, even in the most affected regions.

Propagation and Ampli cation of Local Productivity Spillovers

This paper shows that local productivity spillovers propagate throughout the economy through the plant-level networks of multi-region firms. Using confidential Census plant-level data, we show that large manufacturing plant openings not only raise the productivity of local plants but also of distant plants hundreds of miles away, which belong to multi-region firms that are exposed to the local productivity spillover through one of their plants. To quantify the significance of plant-level networks for the propagation and amplification of local productivity shocks, we develop and estimate a quantitative spatial model in which plants of multi-region firms are linked through shared knowledge. Our model features heterogeneous regions, which interact through goods trade and labor markets, as well as within-location, across-plant heterogeneity in productivity, wages, and employment. Counterfactual exercises show that while knowledge sharing through plant-level networks amplifies the aggregate effects of local productivity shocks, it widens economic disparities between individual workers and regions in the economy. Institutional subscribers to the NBER working paper series, and residents of developing countries may download this paper without additional charge at www.nber.org.

Local Industrial Policy and Sectoral Hubs

We study the desirability of industrial policies that generate sectoral hubs using a quantitative spatial model with cognitive nonroutine and other occupations. The productivity of each occupation in an industry depends on sector-specific production externalities, which we estimate using a model-implied instrumental variable approach. We find that the optimal policy gives rise to national hubs in coastal cities in tradable services, like professional services, and smaller regional hubs in less tradable services, like health and education. The optimal policy prescribes developing manufacturing in smaller towns. We decompose the implied changes in local costs and the available varieties in each sector.

This Town Ain't Big Enough? Quantifying Public Good Spillovers

Despite long-standing theoretical interest, empirical attempts at investigating the appropriate level of decentralization remain scarce. This paper develops a simple and flexible framework to test for the presence of public good spillovers between fiscally autonomous jurisdictions and to investigate potential welfare gains from marginal fiscal integration. We build a quantitative spatial equilibrium model with many local jurisdictions, mobile households and endogenous local public goods causing spillovers across jurisdictional boundaries. We show how one can exploit migration and housing price responses to shocks in local public goods at different geographic scales to reveal the intensity of spillovers. Applying our framework to the particularly fragmented French institutional setting, we structurally estimate the model using a unique combination of municipal administrative panel datasets. Estimation relies on plausibly exogenous variations in government subsidies to instrument changes in the supply of public goods. We find that public goods in a municipality account for 4--11% of the local public good bundle enjoyed by its residents, and that public goods in each neighbor municipality account for an average 3.2--3.5% of this bundle. Finally, we simulate the effect of a reform increasing fiscal integration and find substantial welfare gains

Propagation and Amplification of Local Productivity Spillovers

This paper shows that local productivity spillovers propagate throughout the economy through the plant-level networks of multi-region firms. Using confidential Census plant-level data, we show that large manufacturing plant openings not only raise the productivity of local plants but also of distant plants hundreds of miles away, which belong to multi-region firms that are exposed to the local productivity spillover through one of their plants. To quantify the significance of plant-level networks for the propagation and amplification of local productivity shocks, we develop and estimate a quantitative spatial model in which plants of multi-region firms are linked through shared knowledge. Our model features heterogeneous regions, which interact through goods trade and labor markets, as well as within-location, across-plant heterogeneity in productivity, wages, and employment. Counterfactual exercises show that while knowledge sharing through plant-level networks amplifies the aggregate effects of local productivity shocks, it widens economic disparities between individual workers and regions in the economy.

Integration of spatial distortion effects in a 4D computational phantom for simulation studies in extra-cranial MRI-guided radiation therapy: Initial results.

Spatial distortions in magnetic resonance imaging (MRI) are mainly caused by inhomogeneities of the static magnetic field, nonlinearities in the applied gradients, and tissue-specific magnetic susceptibility variations. These factors may significantly alter the geometrical accuracy of the reconstructed MR image, thus questioning the reliability of MRI for guidance in image-guided radiation therapy. In this work, we quantified MRI spatial distortions and created a quantitative model where different sources of distortions can be separated. The generated model was then integrated into a four-dimensional (4D) computational phantom for simulation studies in MRI-guided radiation therapy at extra-cranial sites. A geometrical spatial distortion phantom was designed in four modules embedding laser-cut PMMA grids, providing 3520 landmarks in a field of view of (345×260×480)mm3 . The construction accuracy of the phantom was verified experimentally. Two fast MRI sequences for extra-cranial imaging at 1.5T were investigated, considering axial slices acquired with online distortion correction, in order to mimic practical use in MRI-guided radiotherapy. Distortions were separated into their sources by acquisition of images with gradient polarity reversal and dedicated susceptibility calculations. Such a separation yielded a quantitative spatial distortion model to be used for MR imaging simulations. Finally, the obtained spatial distortion model was embedded into an anthropomorphic 4D computational phantom, providing registered virtual CT/MR images where spatial distortions in MRI acquisition can be simulated. The manufacturing accuracy of the geometrical distortion phantom was quantified to be within 0.2mm in the grid planes and 0.5mm in depth, including thickness variations and bending effects of individual grids. Residual spatial distortions after MRI distortion correction were strongly influenced by the applied correction mode, with larger effects in the trans-axial direction. In the axial plane, gradient nonlinearities caused the main distortions, with values up to 3mm in a 1.5T magnet, whereas static field and susceptibility effects were below 1mm. The integration in the 4D anthropomorphic computational phantom highlighted that deformations can be severe in the region of the thoracic diaphragm, especially when using axial imaging with 2D distortion correction. Adaptation of the phantom based on patient-specific measurements was also verified, aiming at increased realism in the simulation. The implemented framework provides an integrated approach for MRI spatial distortion modeling, where different sources of distortion can be quantified in time-dependent geometries. The computational phantom represents a valuable platform to study motion management strategies in extra-cranial MRI-guided radiotherapy, where the effects of spatial distortions can be modeled on synthetic images in a virtual environment.

Quantitative spatial distribution model of site-specific loess landslides on the Heifangtai terrace, China

Landslide disasters are associated with severe losses on the Loess Plateau of China. Although early warning systems and susceptibility mapping have mitigated this issue to some extent, most methods are qualitative or semi-quantitative in the site-specific range. In this paper, a quantitative spatial distribution model is presented for site-specific loess landslide hazard assessment. Coupled with multi-temporal remote sensing images and high-precision UAV cloud point data, a total of 98 loess landslides that have occurred since 2004 on the Heifangtai terrace were collected to establish a landslide volume-date and retreating distance database. Eleven loess landslides are selected to construct a numerical model for parameter back analysis, and the accuracy of the simulation results is quantitatively evaluated by the centroid distance and overlapping area. Different volumes and receding distance rates of landslides are fitted to determine the relationship between cracks and potential volume, and different volumes and parameters are combined to simulate the spatial distribution of potential loess landslides. The results of this study reveal that landslide volumes mainly range between 1 × 103 and 5 × 105 m3, and the historical occurrence probability reaches 0.551. The optimal parameters are estimated by the maximum likelihood method to obtain a uniform distribution parameter value probability model, and the results show that the error of the estimated length within a range of 0.05 from the optimal parameter does not exceed 15%. In the selected slope slide case, farmland near the toe of the slope primarily includes exposed hazards with probabilities greater than 0.7. This work provides a useful reference for local disaster reduction and a theoretical methodology for hazard assessments.

A Quantitative Spatial Model of Urban Sprawl and its Application to Dehradun Urban Agglomeration, India

The unregulated and scattered pattern of urban footprints is termed as urban sprawl. Urban sprawl being a dynamic phenomenon is facing many uncertainties with respect to methods for studying its dynamism. The present study aims at quantifying the urban sprawl process in Dehradun Urban Agglomeration (DUA), India, based on two criteria, viz. urban built-up density and open space fragmentation. On the basis of these two criteria, six structural classes, viz. urban, suburban and rural built-up, urbanized open space, captured open space and rural open land, were delineated. The spatio-temporal variation of these structural classes provided the basis for defining the urban sprawl patterns, i.e. infill, extension and leapfrog. The results revealed that urbanization patterns in DUA valley shifted from leapfrog to extension and then to infill pattern. The study thus attempts to develop a model for objectively defining the process of urban sprawl.