A multiregional model of China and its application

China's rapid economic transformation since 1979 has been accompanied by a stark regional disparity with the coastal provinces integrating swiftly into the world markets while inland regions lagging far behind in the industrialisation process. The growth imbalance has placed China's provinces into different stages of development and called for different policy responses to deal with different challenges they are facing. Similarly, a national policy initiated by the central government is likely to be interpreted and implemented in different ways when local governments take into consideration the different conditions in their localities. Therefore, it would be extremely valuable for policy makers and researchers to have an analytical tool that is capable of studying interactions among the provincial economies and the dynamic relationship between the centre and local governments. The multiregional econometric model of China presented in this paper is the first attempt to provide such a tool. The pioneering model consists of over 1200 equations, covering 30 provinces of China that are linked by inter-regional flows of goods and services. The model is used to study the impact of fiscal recentralisation in the 1990s. The counterfactual simulation results show that when China's central government diverted tax revenue from provincial governments, it achieved higher budgetary revenue for the central government but at the expense of lower overall budgetary revenue and slower economic growth.     

DEVELOPING A MULTI-SCALE MULTI-REGION INPUT–OUTPUT MODEL

Many efforts have recently been devoted to developing global multi-region input–output (GMRIO) models. Unfortunately, the scales of GMRIO models do not allow them to capture the heterogeneity of regions within a single country. Multi-scale models can provide more comprehensive analyses capable of capturing the interdependencies of the global economy while preserving regional differences. The primary objective of this research is to develop methods for integrating multi-region input–output data sets from multiple spatial scales into multi-scale multi-region input–output (MSMRIO) models. These methods result in models that may have unusual features such as non-square trade coefficient matrices and a mix of industry-by-industry and commodity-by-commodity technical coefficients. To demonstrate the feasibility of MSMRIO modelling, a Canada-centric model was developed. This model includes 47 countries and Canada's 13 subnational regions. A MSMRIO model provides a tool to analyse global issues with a more spatially detailed focus.     

MAXIMUM-LIKELIHOOD ESTIMATES OF A US MULTIREGIONAL HOUSEHOLD EXPENDITURE SYSTEM

This paper applies the maximum-likelihood equation to a model that produces US regional household expenditure estimates using national-level data on average expenditures by type of household and regional data on the number of households by type. Empirical results follow the analytical properties of the model and demonstrate an impressive capacity to recover regional statistics. These findings are useful in applied regional studies since they demonstrate a general framework to assess the input data and the overall estimation model.     

A Simple Multi-Regional Input–Output Account for Waste Analysis

The present paper provides a simple multiregional input–output model for waste analysis with which to estimate intraregional and interregional effects of industrial wastes embodied in regional final consumptions. The empirical analyses using 1995 nine-regions input–output tables reveals the regional properties of the interregional linkage effects. The Kanto and Kinki regions remarkably control the industrial waste emissions and waste landfills within their own regions by importing waste-intensive intermediate goods and services from the other regions. The Chugoku and Shikoku regions greatly contributed to the production of the waste-intensive goods and services for the other regions, considering the waste emissions and waste landfills relative to the commodity production levels. We also find that the household consumption behaviour in other regions indirectly plays a more important role in waste emissions than the municipal waste disposal behaviour in the region in question at least in 1995.     

A STRUCTURAL DECOMPOSITION APPROACH TO COMPARING MRIO DATABASES

The construction of multi-regional input–output tables is complex, and databases produced using different approaches lead to different analytical outcomes. We outline a decomposition methodology for investigating the variations that exist when using different multiregional input–output (MRIO) systems to calculate a region's consumption-based account. Structural decomposition analysis attributes the change in emissions to a set of dependent determinants, such as technical coefficients, the Leontief inverse and final demands. We apply our methodology to three MRIO databases – Eora, GTAP and WIOD. Findings reveal that the variation between Eora and GTAP can be attributed to differences in the Leontief inverse and emissions’ data, whereas the variation between Eora and WIOD is due to differences in final demand and the Leontief inverse. For the majority of regions, GTAP and WIOD produce similar results. The approach in this study could help move MRIO databases from the academic arena to a useful policy instrument.     

A METHOD TO CREATE CARBON FOOTPRINT ESTIMATES CONSISTENT WITH NATIONAL ACCOUNTS

Although multiregional input–output (MRIO) databases use data from national statistical offices, the reconciliation of various data sources results in significantly altered country data. This makes it problematic to use MRIO-based footprints for national policy-making. This paper develops a potential solution using the Netherlands as case study. The method ensures that the footprint is derived from an MRIO dataset (in our case the World Input–Output Database (WIOD)) that is made consistent with Dutch National accounts data. Furthermore, usage of microdata allows us to separate re-exports at the company level. The adjustment results in a foreign footprint in 2009 that is 22% lower than the original WIOD estimates and a significantly altered country allocation. We demonstrate that already in the data preparation phase due to the treatment of re-exports and margins, large differences arise with Dutch national statistics, which may help explain the variation in footprint estimates across MRIO databases.     

Comparing apples and oranges: Some confusion about using and interpreting physical trade matrices versus multi-regional input–output analysis

The questions of how to account for upstream land requirements is highly relevant for assigning responsibility for global land use. Two approaches, physical trade flow analysis and multi-regional input–output analysis have been frequently used for land accounting of international trade leading to diametrically opposed results for countries such as China. In this study, we investigate and explain the differences by comparing the estimates of cropland embodied in international trade for China from studies using physical trade flows (PTF) and multi-regional input–output (MRIO) analysis and provide a step-wise calculation to explain the gap between estimates from these different approaches and their interpretation. Our results show that the gap between PTF and MRIO is largely due to the system boundary selection and truncation errors from the boundary cut-off. These two approaches should be used for different research purposes. If focusing on the flows of a particular product, in particular primary products such as rice, wheat or other grains, among countries the higher level of detail of physical flow model is more suited. Whereas when accounting for the total embodied land in trade and consumption-based land use by recipient countries to analyze drivers of land use, MRIO is more suitable for tracking entire global supply chains.     

A Simple Multi-Regional Input–Output Account for Waste Analysis

The present paper provides a simple multiregional input–output model for waste analysis with which to estimate intraregional and interregional effects of industrial wastes embodied in regional final consumptions. The empirical analyses using 1995 nine-regions input–output tables reveals the regional properties of the interregional linkage effects. The Kanto and Kinki regions remarkably control the industrial waste emissions and waste landfills within their own regions by importing waste-intensive intermediate goods and services from the other regions. The Chugoku and Shikoku regions greatly contributed to the production of the waste-intensive goods and services for the other regions, considering the waste emissions and waste landfills relative to the commodity production levels. We also find that the household consumption behaviour in other regions indirectly plays a more important role in waste emissions than the municipal waste disposal behaviour in the region in question at least in 1995.     

Accounting for value added embodied in trade and consumption: an intercomparison of global multiregional input–output databases

Global multiregional input–output (MRIO) tables constitute detailed accounts of the economic activity worldwide. Global trade models based on MRIO tables are being used to calculate important economic and environmental indicators such as value added in trade or the carbon footprint of nations. Such applications are highly relevant in international trade and climate policy negotiations, and consequently MRIO model results are being scrutinized for their accuracy and reproducibility. We investigate the variation in results from three major MRIO databases by comparing underlying economic data and territorial and consumption-based results across databases. Although global value-added accounts were similar across databases, we find some significant differences at the level of individual countries and sectors. Model disagreement was relatively stable from the territorial to the consumption perspective. Pairwise matrix comparison statistics indicated that the Global Trade Analysis Project and World Input-Output Database MRIO tables were overall more similar to each other than either was to the Eora database.     

Emissions burden shifting in global value chains – winners and losers under multi-regional versus bilateral accounting

ABSTRACT

International trade leads to emissions burden shifting and threatens mitigation targets. Multiregional input–output (MRIO) and bilateral trade input–output (BTIO) models are widely used to analyse emissions embodied in trade and global value chains. Especially, the last one is used in analysing border tax adjustment (BTA) on the carbon content of imports. The model choice is not trivial. The analysis shows BTIO's inability to capture the consumer-principle throughout the production chain and its inadequacy as an option for consumption-based accounting, because it allocates emissions to the first importing country and to the sector of production, instead to the consumer (both country and region). Regarding the BTA assessment, BTIO tax domestic carbon content of direct imports, but not indirect imported carbon content. MRIO does provide incentives for mitigation in third countries. The differences in allocation of emissions and taxes’ burden of both models have different consequences for developed and undeveloped regions.