A nonsurvey multiregional input–output estimation allowing cross-hauling: partitioning two regions into three or more parts

Abstract

This paper describes a nonsurvey method for estimating multiregional trades without eliminating cross-hauling, when a national biregional input-output table is available. Domestic outflows are assigned by interpolating the biregional trades on the basis of the gravity ratio between the origin and the destinations, with parameters estimated from an earlier survey on interregional transactions. The method is then applied to evaluate multiregional industrial waste disposal and landfill attributed to consumption in the city of Nagoya. Three-regional input-output tables with and without cross-hauling are estimated by partitioning the biregional table between Aichi prefecture and the rest of Japan. JEL Classification

Construction of a multi-regional input-output table for Nagoya metropolitan area, Japan

“…Sargento et al (2012) compared and assessed the performance of some gravity models for explaining the interregional trade among regions. Nakano and Nishimura (2013) estimated one type of gravity model with crosshauling using a survey on interregional transactions and constructed three-regional IOTs of Japan.…”

Linking city‐level input–output table to urban energy footprint: Construction framework and application

“…Normally, sample data would be required to estimate these parameters, but trade data between cities were not available. Therefore, we followed the approach of Nakano and Nishimura () and Yamada () and used transaction data from the 2012 China MRIO table as a proxy for sample data for each sector. Because our estimates are for the Hebei cities, we chose the transaction data between Hebei and the surrounding provinces or megacities (e.g., Beijing, Tianjin, Shanxi, and Shandong).…”

“…Multiregion input–output models (MRIOs) have been widely recognized as good assessment tools that can track the supply chain and capture regional homogeneity as well as heterogeneity, thus accurately reflecting environmental and socioeconomic implications (Bachmann, Roorda, & Kennedy, ; Dietzenbacher, Lenzen, et al., ; Miller & Blair, ; Wang, ). Over the recent decade, many efforts have been made to develop MRIO databases at international level: EORA (Lenzen, Kanemoto, Moran, & Geschke, ; Lenzen, Moran, Kanemoto, & Geschke, ), WIOD (Dietzenbacher, Los, et al., ), GTAP‐MRIOT (Peters, Andrew, & Lennox, ), and Asian International Input–Output Table produced by IDE‐JETRO (Meng, Zhang, & Inomata, ); or the national level such as China (Liu, Li, Liu, Tang, & Guan, ; Mi et al., ; Zhang, Shi, & Zhao, ), the UK (Yu, Hubacek, Feng, & Guan, ), Japan (Nakano & Nishimura, ; Yamada, ), and Australia (Lenzen et al., ). Although these databases have helped gain a comprehensive understanding of regional disparities and spillover effects in interregional and international trade, none of current MRIOs (national or provincial) offer insights in assessment at the local scale, particularly at the city level.…”

On the accuracy of gravity-RAS approaches used for inter-regional trade estimation: evidence using the 2005 inter-regional input–output table of Japan

“…Note that parameters entering the gravity equation, such as the betas in Equation 1, cannot be estimated beforehand since doing so would require interregional data, which is going to be estimated by the gravity equation. If this is the case, sector-specific paramers might be estimated in four different ways: (1) from another period for which observations are available (Boero et al, 2018); (2) from another geographical area (Nakano & Nishimura, 2013;Yamada, 2015); (3) by arbitrarily assuming parameter values or calculating them with help of known column and row totals (Sargento et al, 2012); or (4) by adapting estimates from other econometric analyses in the literature (Krebs, 2018).…”

“…For instance, Lindall at al. (2006) and Boero et al (2018) use a similar approach to estimate flows between regions in the U.S., Liu et al (2015) dof it for China, Nakano and Nishimura (2013) and Yamada (2015) for Japan, and Krebs (2018) for Germany. 13 G o i can be calculated as…”