Multiregional Model Research Articles

The Slope of the Phillips Curve: Evidence from U.S. States

We estimate the slope of the Phillips curve in the cross section of U.S. states using newly constructed state-level price indexes for non-tradeable goods back to 1978. Our estimates indicate that the slope of the Phillips curve is small and was small even during the early 1980s. We estimate only a modest decline in the slope of the Phillips curve since the 1980s. We use a multi-region model to infer the slope of the aggregate Phillips curve from our regional estimates. Applying our estimates to recent unemployment dynamics yields essentially no missing disinflation or missing reinflation over the past few business cycles. Our results imply that the sharp drop in core inflation in the early 1980s was mostly due to shifting expectations about long-run monetary policy as opposed to a steep Phillips curve, and the greater stability of inflation since the 1990s is mostly due to long-run inflationary expectations becoming more firmly anchored. Institutional subscribers to the NBER working paper series, and residents of developing countries may download this paper without additional charge at www.nber.org.

Exporters, Multinationals and Residual Wage Inequality: Evidence and Theory

This paper studies the implications for wage inequality of two distinct forms of globalisation, namely trade and foreign direct investment. I use German linked employer-employee data to (1) jointly estimate the exporter and the multinational wage premium and (2) to further distinguish between wage premia of multinational firms that are foreign owned (inward FDI) and domestically owned (outward FDI). My findings exhibit a clear hierarchy of firms’ international activities with regard to wage premia and workforce ability. I interpret these patterns using a theoretical framework, which incorporates ex-ante homogeneous workers, heterogeneous firms and search and matching frictions into a multi-region model of trade and FDI with monopolistic competition. The model allows me to account for the observed empirical patterns, and delivers novel insights about the interplay between trade, FDI and labour market institutions.

METHODOLOGICAL APPROACHES FOR INCLUSION OF FACTORS OF A "GREEN ECONOMY" INTO MEDIUM TERM FORECASTING MODELS FOR REGIONAL DEVELOPMENT

Topicality. This is based on the importance of coordinating national and regional socio-economic policy with a recognition of the need for “green” growth and an assessment of government policy measures based on the application of multi-regional modeling methodology to analyze the effects of public policy in a regional context, and on medium-term forecasting of a country's sustainable socio-economic development.Aim and tasks. The aim of the study is to improve the scientific validity of methodology for medium-term forecasting of the main parameters of a country's socio-economic development in terms of individual regions by aligning the objectives and priorities of public policy. The objective is to develop, based on a review of international literature, methodological approaches for obtaining coherent medium-term forecast estimates of major groups of territorial economic, social and environmental indicators, based on modern methodologies for measuring the targeted effects of improving living standards, “green” growth, and overall competitiveness of the national economy in its spatial dimension.
 Research results. The results of the research are based on a review of international literature and the justification for methodology to apply modern multi-regional models for the assessment of the effects of interconnected economic, social and environmental policies in the analysis of interactions between national and regional factors of sustainable economic growth, regional disparities, and strengthening of national competitiveness.
 Conclusion. Modern multi-regional models for medium-term forecasting have passed several stages of development, and have incorporated into them theories of the regional economy and the mathematical tools for socio-economic systems modeling. The most effective current policy application is in the practice of recent EU regional policy. Methodology for application of complex multi-regional models has to be flexible, with the application of complementary modeling tools, and providing for further development of model modules to describe the mutual interaction of national and regional factors of sustainable economic growth, including indicators for “green” investment. A number of specific modeling tools (special engineering simulation models, GIS-based models) are usedto assess environmental parameters of spatial development. Our research proposes to incorporate the main indicators of “green” growth into national and regional blocks of multi-regional models, starting with the simplest options such as small econometric models of partial equilibrium, into which - based on a specially conducted analysis - the most significant factors of sustainable economic growth and exogenous parameters of public policy are included. A special place is given to testing the effectiveness of “green” economy measures.

A multi-period and multi-regional modeling and optimization approach to energy infrastructure planning at a transient stage: A case study of China

Meeting growing energy demand and taking low carbon transition are two main energy issues in most countries. Planning and operation of energy supply systems are challenging tasks with multiple energy types, supply sources, transmission options, processing technologies, end-consumers, and large quantity of costly infrastructure. Energy planning models could reduce costs as well as address growing and transition issues. In this study, a mathematical modeling framework describing a national scale low carbon transition and optimizing energy system deployment is developed. The energy system of China, which is the largest energy consumer in the world, is used as a reference when developing the framework. Compared to previous studies, spacial and temporal resolution is greatly improved to cover regional variations in energy resources, inter-regional energy transmission, and monthly fluctuations of energy demand. A case study of China's energy infrastructure planning up to 2050 is presented to illustrate the capability of the proposed framework.

Spillovers and Redistribution through Intra-Firm Networks: The Product Replacement Channel

We study how regional shocks spill over across US local markets through intra-firm market networks and explore how such spillovers reshape household welfare across regions. We identify spillovers by linking data on barcode-region-level prices and quantities with producer-level information and by exploiting variation in firms' exposure to sudden differential drops in local house prices. We find that a firm's local sales decrease in response to a direct negative local demand shock and do so more strongly to indirect negative demand shocks originating in its other markets. The intra-firm cross-market spillover effects occur because (i) firms replace higher-value products---higher sales per product, unit price, and organic sales share---with lower-value products in response to negative demand shocks, and (ii) such product replacements are synchronized across markets within each firm. Counterfactual analysis using multiregion model with endogenous quality adjustment shows that our channel generates a novel and economically sizable regional redistribution effect during the Great Recession.

Radiomic features based on MRI for prediction of lymphovascular invasion in rectal cancer

To investigate the value of radiomics in predicting lymphovascular invasion (LVI) status of rectal cancer based on MRI. The retrospective study included 188 patients based on MRI with histologically confirmed rectal cancer and evaluated LVI status. Clinical factors and image data were collected, and radiomics features were extracted from multi-region (tumor and mesorectum) and single region (tumor), respectively, on T2WI and DWI. Spearman correlation analysis and the LASSO algorithm were used for radiomic feature extraction and selection; preliminarily selection of an optimal classifier by the results of the fivefold cross-validation performance in the six preselected specific machine learning classifier. Multi-regional and single-regional predictive models were both built and evaluated by calculating the area under the ROC curve (AUC) and corresponding accuracy, specificity, sensitivity, etc. A Ridge Classification model was constructed with 21 features (2 clinical features, 10 radiomics features from mesorectum region, and 9 radiomics features from tumor region) selected by Spearman correlation and LASSO analysis. The multi-regional model shows a good performance in the differentiation of the status of LVI in training data sets (AUC = 0.87, accuracy = 0.79). The model was further validated in the testing data sets, giving an AUC and an accuracy of 0.74 and 0.68, respectively. Furthermore, the performance of single-regional model (AUC = 0.72, accuracy = 0.67) is lower compared to the values given by the multi-regional model. The radiomics model which we developed demonstrates that multi-regional radiomics features based on multiparametric MRI are useful for preoperatively predicting lymphovascular invasion in patients with rectal cancer.

How to Deal with Existing Coal Production Capacity on a Low-Carbon Transition Pathway? A Case Study of China

In recent years, driven by climate change and air pollution, the global energy structure is on a low-carbon transition way. Coal production capacity is expected to gradually shrink. Without proper planning, mismatch between capacity shrinking and increasing demand would lead to over-tight energy supplies, on the contrary, it would lead to overcapacity and waste of social resources. A quantitative method considering an overall planning horizon is needed to facilitate policy-making. In this paper, a monthly-scale multi-period and multi-regional modelling and optimization framework of a coal supply system at a transient stage is proposed. China’s coal supply system is taken as a case study. The optimal reduction path of China's coal production capacity and the optimal operation strategy of the coal supply system are obtained by minimising the overall cost by 2050. Results show that the capacity concentration policy would lead to more coal transmission, which results in higher total supply cost.

Economic evaluation of the effects of exerting green tax on the dispersion of bioenvironmental pollutants based on multi-regional general equilibrium model (GTAP-E)

ABSTRACT The present study calculates the temporal value of energy money based on green scenario of tax on the dispersion of bioenvironmental pollutants using global trade analysis project-energy substitution (GTAP-E) and investigates the changes brought about in carbon dioxide, GDP along with CIF for 2016 in Iran and eventually presents an evaluation of such sectors as coal, oil, gas, and petroleum products. The results indicated that the implementation of green tax scenario along with technological progress causes reduction by −0.19% in temporal value of pollution money in coal sector and the effect of monetary value of energy carriers on oil was also found reduced by −0.67% and the percentage reduction is about −0.1 in contrast to the other countries. At first, the direct and indirect coefficients (Leontief inverse) and the multiplying coefficients of bioenvironmental pollutants were computed using input-output matrix table technique. It was figured out that the highest pollution is caused by CO2 in this sector. But, the highest pollution in agriculture and mine sectors, substantially as a result of gasoil consumption, is caused by CO that is currently showing an ascending trend. Thus, it is recommended that the government should provide with the possibility of having access to modern global technologies via making imports. In the energy sector, Iran is recommended to reduce its CO2 production compared to what is currently being produced. The speed of pollutants emissions can be reduced by raising taxes in the energy sector.

Multi-region model for reaction-diffusion process in a catalyst particle

multi-region model for reaction-diffusion process in a catalyst particle

Understanding Business Disruption and Economic Losses Due to Electricity Failures and Flooding

Failure of critical national infrastructures can cause disruptions with widespread economic impacts. To analyze these economic impacts, we present an integrated modeling framework that combines: (1) geospatial information on infrastructure assets/networks and the natural hazards to which they are exposed; (2) geospatial modeling of the reliance of businesses upon infrastructure services, in order to quantify disruption to businesses locations and economic activities in the event of infrastructure failures; and (3) multiregional supply-use economic modeling to analyze wider economic impacts of disruptions to businesses. The methodology is exemplified through a case study for the United Kingdom. The study uses geospatial information on the location of electricity infrastructure assets and local industrial areas, and employs a multiregional supply-use model of the UK economy that traces the impacts of floods of different return intervals across 37 subnational regions of the UK. The results show up to a 300% increase in total economic losses when power outages are included in the risk assessment, compared to analysis that just includes the economic impacts of business interruption due to flooded business premises. This increase indicates that risk studies that do not include failure of critical infrastructures may be underestimating the total losses.

The Effect of Chinese Population Aging on Income Inequality: Based on a Micro-Macro Multiregional Dynamic CGE Modelling Analysis

ABSTRACT This paper uses simulation results from a dynamic computable model as well as estimates by the United Nations of trends in China’s population in 2010–2050 to determine the impact of the aging of the population on changes in commodities and price factors at the macro level. Then, the paper uses a top-down and bottom-up cyclic link to connect macroeconomic variables to a micro-level family simulation model, based on the regional characteristics of the distribution of population aging in the country. The empirical results suggest that, with an aging population, the working population decreases, which induces increases in income inequality. Moreover, older families in western China would suffer from the most severe income inequality, and gaps between groups in different regions are progressively increasing as the population ages.

Modelling and optimization of a natural gas supply system at a transient stage: a case study of China

The global energy structure is on a low-carbon transition path featuring more natural gas consumption, and global natural gas demand has been increasing fast. Planning and operation of a natural gas supply system at a transient stage with multiple supply sources, end-consumers, and large infrastructure with multiple sub-systems are challenging tasks. Spatial and seasonal mismatch of natural gas supply and demand makes the natural gas distribution and infrastructure construction planning problem even more complex. Without proper planning, insufficient construction could lead to a shortage of natural gas supply, whilst excessive construction could lead to a higher cost. Quantitative analysis technologies are needed to facilitate decision-making during the transient stage of a natural gas system. In this work, we propose a monthly-scale multi-period and multi-regional modelling and optimization framework for planning and operation of a natural gas supply system at a transient stage, with a case study of the natural gas supply system in China. The optimal planning and operation strategy of the natural gas supply system in China by 2050 is obtained by minimizing the lifespan overall cost. Gaps between actual planning and the optimal planning are pointed out. Finally, policy suggestions are summarized, including establishing market-oriented pricing mechanisms, managing infrastructure centrally, promoting coordination amongst provinces when formulating projections, accelerating current infrastructure construction, and predicting natural gas demand and prices reasonably.

Population structure and the evolution of Homo sapiens in Africa.

It has been proposed that a multiregional model could describe how Homo sapiens evolved in Africa beginning 300,000 years ago. Multiregionalism would require enduring morphological or behavioral differences among African regions and morphological or behavioral continuity within each. African fossils, archeology, and genetics do not comply with either requirement and are unlikely to, because climatic change periodically disrupted continuity and reshuffled populations. As an alternative to multiregionalism, I suggest that reshuffling produced novel gene constellations, including one in which the additive or cumulative effect of newly associated genes enhanced cognitive or communicative potential. Eventual fixation of such a constellation in the lineage leading to modern H. sapiens would explain the abrupt appearance of the African Later Stone Age 50-45 thousand years ago, its nearly simultaneous expansion to Eurasia in the form of the Upper Paleolithic, and the ability of fully modern Upper Paleolithic people to swamp or replace non-modern Eurasians.

Learning multi-region features for vehicle re-identification with context-based ranking method

Vehicle re-identification is to identify a target vehicle in different cameras with non-overlapping views. It is a challenging task due to various viewpoints of vehicles, diversified illuminations and complicated environments. Most existing vehicle re-identification methods focus on learning global features, while neglecting the importance of local features. In this paper, we propose a Multi-Region Model (MRM) to learn powerful features for vehicle re-identification. In addition to extracting global region features, MRM also extracts features from a series of local regions. For each local region, instead of utilizing the rigid part to extract features directly, a Spatial Transformer Network (STN) based localization model is introduced to localize local regions which contain more distinctive visual cues. In order to further improve the performance of re-identification, we design a context-based ranking method which generates the ranking list by taking context and content into consideration to measure the similarity between neighbors. Experimental results clearly demonstrate that our method achieves excellent performance on both VehicleID dataset and VeRi-776 dataset.

Potential impacts of climate change on groundwater resources: A multi-regional modelling assessment

The complexity of understanding the groundwater resources in relation to climate change is caused by direct and indirect effects of climate change on hydrological processes. The study herein aims at implementing a physically based groundwater model to investigate the effects of climate change on groundwater system under 15 general circulation models (GCMs) in a semi-arid region from 2020 to 2044. A non-parametric probability density function estimator was used to quantify the level of uncertainties in the simulations. The method was applied to an area of 2073 km\(^{2}\) in southwest Iran, consisting of five plains: western Dez, eastern Dez, Sabili, Deymche and Lor. The results indicate that there is a decline in the recharge in April, May, June and October. The range of changes in the recharge was determined to be between \(-10\%\) and \(+13\%\) in the Sabili plain, \(-6\%\) and \(+10\%\) in the Deymche plain, \(-4\%\) and \(+10\%\) in the western-Dez plain, \(-6\%\) and \(+26\%\) in the eastern-Dez plain, and \(-40\%\) and \(+100\%\) in the Lor plain. The most significant decline in the groundwater level occurred in the Sabili plain in September. The largest uncertainty in the simulation of recharge under GCM scenarios was determined to be in August, September and December. This study highlights that climate change can have a significant effect on groundwater resources in the region that reinforces the need for groundwater management plans and a long-term perspective.

Genetic kinship and admixture in Iron Age Scytho-Siberians.

Scythians are known from written sources as horse-riding nomadic peoples who dominated the Eurasian steppe throughout the Iron Age. However, their origins and the exact nature of their social organization remain debated. Three hypotheses prevail regarding their origins that can be summarized as a "western origin", an "eastern origin" and a "multi-regional origin". In this work, we first aimed to address the question of the familial and social organization of some Scythian groups (Scytho-Siberians) by testing genetic kinship and, second, to add new elements on their origins through phylogeographical analyses. Twenty-eight Scythian individuals from 5 archeological sites in the Tuva Republic (Russia) were analyzed using autosomal Short Tandem Repeats (STR), Y-STR and Y-SNP typing as well as whole mitochondrial (mtDNA) genome sequencing. Familial relationships were assessed using the Likelihood Ratio (LR) method. Thirteen of the 28 individuals tested were linked by first-degree relationships. When related, the individuals were buried together, except for one adult woman, buried separately from her mother and young sister. Y-chromosome analysis revealed a burial pattern linked to paternal lineages, with men bearing closely related Y-haplotypes buried on the same sites. Inversely, various mtDNA lineages can be found on each site. Y-chromosomal and mtDNA haplogroups were almost equally distributed between Western and Eastern Eurasian haplogroups. These results suggest that Siberian Scythians were organized in patrilocal and patrilineal societies with burial practices linked to both kinship and paternal lineages. It also appears that the group analyzed shared a greater genetic link with Asian populations than Western Scythians did.

Role of Media and Effects of Infodemics and Escapes in the Spatial Spread of Epidemics: A Stochastic Multi-Region Model with Optimal Control Approach

Mass vaccination campaigns play major roles in the war against epidemics. Such prevention strategies cannot always reach their goals significantly without the help of media and awareness campaigns used to prevent contacts between susceptible and infected people. Feelings of fear, infodemics, and misconception could lead to some fluctuations of such policies. In addition to the vaccination strategy, the movement restriction approach is essential because of the factor of mobility or travel. However, anti-epidemic border measures may also be disturbed if some infected travelers manage to escape and infiltrate into a safer region. In this paper, we aim to study infection dynamics related to the spatial spread of an epidemic in interconnected regions in the presence of random perturbations caused by the three above-mentioned reasons. Therefore, we devise a stochastic multi-region epidemic model in which contacts between susceptible and infected populations, vaccination-based and movement restriction optimal control approaches are all assumed to be unpredictable, and then, we discuss the effectiveness of such policies. In order to reach our goal, we employ a stochastic maximum principle version for noised systems, state and prove the sufficient and necessary conditions of optimality, and finally provide the numerical results obtained using a stochastic progressive-regressive schemes method.

Migration impact on China’s population dividing line driven by hybrid features: perspectives of climate change and wage gap

The development of China’s population distribution boundary (Hu Line) in the future will have mixed driving characteristics: (1) driven by potential agricultural production in the long term; (2) driven by the wage gap between the eastern and the western provinces in the short term. At the same time, China’s unique pattern of migrant workers has increased the complexity of the issue of population migration between the Hu Line. This paper establishes a population support model based on the Potential Agricultural Production and a multi-regional Computable general equilibrium model considering a transfer mechanism of remittance. Results show that the population proportion caused by climate change in the provinces west of the Hu Line will increase in the long term, but the stability of the Hu Line has not been broken down. In the short term, as the wage-driven migration of western labor force expands, the country’s total economy shows a growing trend, and the wage gap between regions gradually narrows with the expansion of the migration scale. When the migration rate of the western labor force is 30%, the per capita GDP gap between the eastern and western regions of the Hu Line is the minimum, and when the rate is 10%, the per capita income gap between the eastern and western regions is the smallest. Though the rural migrant workers from the western province can improve the living standards of families in the western regions, it has little impact on the national and regional economy overall.

How to model a complex national energy system? Developing an integrated energy systems framework for long-term energy and emissions analysis

In order to manage an energy system responsibly and maintain its benefits indefinitely, science-based decision-making should be valued during energy policy making and energy management. This research presents a framework for developing a scientific tool with the long-range energy alternatives planning (LEAP) system for evaluating energy consumption and greenhouse gas (GHG) emission mitigation pathways for a national energy system. The framework developed is applied to create a bottom-up (technology-explicit), data-intensive (over 2 million data points), multi-regional (13 integrated regions) energy model of Canada, one of the world's most energy and emission intensive nations. Model accuracy was validated with historical data showing emissions varied 0-1.2% proving the framework can provide accurate assessments. The model was used to generate baseline Canadian energy-emissions outlooks to 2050 that do not currently exist in literature. The developed framework provides robust capabilities that are helpful for energy efficiency analysis, energy planning, and GHG mitigation assessment.

Predicting the Fate of Preferentially Moving Herbicides

Core Ideas A simple multiregion model predicts herbicide transport well using tracer data. A chloride tracer is used to characterize the preferential flow paths. A surface layer in the model distributes water and solutes to the preferential pathways. Simulation of preferential flow remains a challenge despite being a recognized phenomenon. With short‐interval data, we adapted and tested the preferential flow model (PFM) to simulate the vertical transport of herbicides to lower soil layers. The PFM divides the soil profile into a top distribution zone and a conveyance zone below. The distribution zone acts as a reservoir, with an exponential loss of solutes to the conveyance zone. In the conveyance zone, water and solutes move as convective–dispersive flow through multiple flow paths—preferential and matrix—to shallow groundwater. Our field experiment was performed on a structured Hudson silty clay loam soil (a fine, illitic, mesic Glossaquic Hapludalf) that exhibits preferential flow. The site was instrumented with a variety of soil water samplers placed at depths of 60 cm to monitor the volume and quality of the leachate. Agronomic application of atrazine [6‐chloro‐N‐ethyl‐N′‐(1‐methylethyl)‐1,3,5‐triazine‐2,4‐diamine] and 2,4‐D [2‐(2,4‐dichlorophenoxy)acetic acid] was used, followed by 75 cm of controlled and natural rainfall over 100 d. In addition, Cl− was applied as a conservative tracer. All samplers monitored during this period showed a fast breakthrough of solutes consistent with the occurrence of preferential flow, with two groups of breakthrough curves observed. By fitting the Cl− breakthrough curve for each group, PFM input parameters were estimated including water velocity in preferential flow paths and the fraction of water moving through each flow path. With two additional parameters for herbicide adsorption and degradation rates, the model successfully simulated the extent of preferential flow of herbicides.