The Euro and SUT-RAS methods: some further considerations

Jaramillo, Juan Manuel Valderas; Rueda‐Cantuche, José M.; Beutel, Joerg

doi:10.1080/09535314.2021.1883553

Cited by 4 publications

(3 citation statements)

References 9 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…2.1), or choosing 25 The explicit partition of the set of missing entries into validation and test sets is not reported in the figure, since such partition is randomly generated. 26 It is well known from the standard practice of projection of I/O tables that it is typically better to use a table in previous years to project missing pieces of current I/O tables than using current I/O tables of similar countries (Rueda-Cantuche et al 2018;Valderas-Jaramillo et al 2021). One reason is that the former gathers detailed country-specific information that is not expected to change in the short term.…”

Section: Matrix Completion Applied To Historical Data For Groups Of S...mentioning

confidence: 99%

Hierarchical clustering and matrix completion for the reconstruction of world input–output tables

et al. 2022

View full text Add to dashboard Cite

Multi-regional input–output (I/O) matrices provide the networks of within- and cross-country economic relations. In the context of I/O analysis, the methodology adopted by national statistical offices in data collection raises the issue of obtaining reliable data in a timely fashion and it makes the reconstruction of (parts of) the I/O matrices of particular interest. In this work, we propose a method combining hierarchical clustering and matrix completion with a LASSO-like nuclear norm penalty, to predict missing entries of a partially unknown I/O matrix. Through analyses based on both real-world and synthetic I/O matrices, we study the effectiveness of the proposed method to predict missing values from both previous years data and current data related to countries similar to the one for which current data are obscured. To show the usefulness of our method, an application based on World Input–Output Database (WIOD) tables—which are an example of industry-by-industry I/O tables—is provided. Strong similarities in structure between WIOD and other I/O tables are also found, which make the proposed approach easily generalizable to them.

show abstract

Section: Matrix Completion Applied To Historical Data For Groups Of S...mentioning

confidence: 99%

Hierarchical clustering and matrix completion for the reconstruction of world input–output tables

et al. 2022

View full text Add to dashboard Cite

show abstract

“…Similarly, the CE method also has multiple variants to deal with various situations, such as the modified CE (MCE), generalized CE (GCE), and composite CE (CCE) . Currently, the effectiveness and efficiency of the RAS-based methods and CE-based methods compared with other nonsurvey methods (e.g., Euro method , ) have been widely demonstrated in previous studies. ,,,, …”

Section: Introductionmentioning

confidence: 99%

Using Deep Learning to Fill Data Gaps in Environmental Footprint Accounting

Zhao

Shuai

et al. 2022

Environ. Sci. Technol.

View full text Add to dashboard Cite

Environmental footprint accounting relies on economic input–output (IO) models. However, the compilation of IO models is costly and time-consuming, leading to the lack of timely detailed IO data. The RAS method is traditionally used to predict future IO tables but suffers from doubts for unreliable estimations. Here we develop a machine learning-augmented method to improve the accuracy of the prediction of IO tables using the US summary-level tables as a demonstration. The model is constructed by combining the RAS method with a deep neural network (DNN) model in which the RAS method provides a baseline prediction and the DNN model makes further improvements on the areas where RAS tended to have poor performance. Our results show that the DNN model can significantly improve the performance on those areas in IO tables for short-term prediction (one year) where RAS alone has poor performance, R 2 improved from 0.6412 to 0.8726, and median APE decreased from 37.49% to 11.35%. For long-term prediction (5 years), the improvements are even more significant where the R 2 is improved from 0.5271 to 0.7893 and median average percentage error is decreased from 51.12% to 18.26%. Our case study on evaluating the US carbon footprint accounts based on the estimated IO table also demonstrates the applicability of the model. Our method can help generate timely IO tables to provide fundamental data for a variety of environmental footprint analyses.

show abstract

“…The explicit partition of the set of missing entries into validation and test sets is not reported in the figure, since such partition is randomly generated 24. It is well-known from the standard practice of projection of I/O tables that it is typically better to use a table in previous years to project missing pieces of current I/O tables than using current I/O tables of similar countries[34,44]. One reason is that the former gather detailed country-specific information that is not expected to change in the short term.…”

mentioning

confidence: 99%

Hierarchical Clustering and Matrix Completion for the Reconstruction of World Input-Output Tables

Metulini¹,

Gnecco²,

Biancalani³

et al. 2022

Preprint

View full text Add to dashboard Cite

World Input-Output (I/O) matrices provide the networks of within-and cross-country economic relations. In the context of I/O analysis, the methodology adopted by national statistical offices in data collection raises the issue of obtaining reliable data in a timely fashion and it makes the reconstruction of (part of) the I/O matrices of particular interest. In this work, we propose a method combining hierarchical clustering and Matrix Completion (MC) with a LASSO-like nuclear norm penalty, to impute missing entries of a partially unknown I/O matrix. Through simulations based on synthetic matrices we study the effectiveness of the proposed method to predict missing values from both previous years data and current data related to countries similar to the one for which current data are obscured. To show the usefulness of our method, an application based on World Input-Output Database (WIOD) tables -which are an example of industry-by-industry I/O tables -is provided. Strong similarities in structure between WIOD and other I/O tables are also found, which make the proposed approach easily generalizable to them.

show abstract

The Euro and SUT-RAS methods: some further considerations

Cited by 4 publications

References 9 publications

Hierarchical clustering and matrix completion for the reconstruction of world input–output tables

Hierarchical clustering and matrix completion for the reconstruction of world input–output tables

Using Deep Learning to Fill Data Gaps in Environmental Footprint Accounting

Hierarchical Clustering and Matrix Completion for the Reconstruction of World Input-Output Tables

Contact Info

Product

Resources

About