To RAS or not to RAS? What is the difference in outcomes in multi-regional input–output models?

ABSTRACT The global resource accounting model (GRAM), which is based on OECD input–output and bilateral trade data, is a multi-regional input–output model covering 53 countries and 2 regions. What differentiates GRAM from other state-of-the-art models in this field is that it does not use a matrix balancing technique, such as RAS, after the initial construction of the global intermediate coefficient and final demand matrices. Instead, it reproduces prescribed intermediate and final demand, and determines value added residually. This choice was made to alter the original data as little as possible and keep the calculations traceable. This simpler solution technique might, however, yield different results. This paper aims at identifying the difference between the current solution of GRAM and the solution of a RASed version of GRAM, thus contributing to the assessment of currently used methodologies in this research field. The short conclusion is that, even though some differences during the calculations are present, the calculated output (production) matrix does not differ substantially. The results show that larger differences are brought about by poor assumptions regarding missing or conflicting data rather than by applying or not applying a RAS procedure to the constructed global matrices.

[1]  Manfred Lenzen,et al.  Application of a novel matrix balancing approach to the estimation of UK input-output tables , 2007 .

[2]  E. Dietzenbacher,et al.  An Illustrated User Guide to the World Input–Output Database: The Case of Global Automotive Production , 2015 .

[3]  Kirsten S. Wiebe,et al.  CALCULATING ENERGY-RELATED CO2 EMISSIONS EMBODIED IN INTERNATIONAL TRADE USING A GLOBAL INPUT–OUTPUT MODEL , 2012 .

[4]  Manfred Lenzen,et al.  International trade drives biodiversity threats in developing nations , 2012, Nature.

[5]  Colin Webb,et al.  PROJECTION OF SUPPLY AND USE TABLES: METHODS AND THEIR EMPIRICAL ASSESSMENT , 2010 .

[6]  Norihisa Sakurai,et al.  The Measurement of CO2 Embodiments in International Trade: Evidence from the Harmonised Input-Output and Bilateral Trade Database , 2009 .

[7]  Glen P. Peters,et al.  CONSTRUCTING AN ENVIRONMENTALLY-EXTENDED MULTI-REGIONAL INPUT–OUTPUT TABLE USING THE GTAP DATABASE , 2011 .

[8]  Manfred Lenzen,et al.  UNCERTAINTY ANALYSIS FOR MULTI-REGION INPUT–OUTPUT MODELS – A CASE STUDY OF THE UK'S CARBON FOOTPRINT , 2010 .

[9]  Aie.  Energy Balances of non-OECD Countries 2010 , 2010 .

[10]  Manfred Lenzen,et al.  Structural path analysis of ecosystem networks , 2007 .

[11]  W. F. Gossling,et al.  Estimating and projecting input output coefficients , 1975 .

[12]  Manfred Lenzen,et al.  A STRUCTURAL DECOMPOSITION APPROACH TO COMPARING MRIO DATABASES , 2014 .

[13]  Arnold Tukker,et al.  GLOBAL MULTIREGIONAL INPUT–OUTPUT FRAMEWORKS: AN INTRODUCTION AND OUTLOOK , 2013 .

[14]  Jan Oosterhaven,et al.  The Solution of Updating or Regionalizing a Matrix with both Positive and Negative Entries , 2003 .

[15]  Iain Buchanan,et al.  A QUADRATIC PROGRAMMING APPROACH TO INPUT‐OUTPUT ESTIMATION AND SIMULATION* , 1984 .

[16]  Daniel C. Knudsen,et al.  Matrix Comparison, Goodness-of-Fit, and Spatial Interaction Modeling , 1986 .

[17]  Manfred Lenzen,et al.  EFFECTS OF SECTOR AGGREGATION ON CO2 MULTIPLIERS IN MULTIREGIONAL INPUT–OUTPUT ANALYSES , 2014 .

[18]  Manfred Lenzen,et al.  BUILDING EORA: A GLOBAL MULTI-REGION INPUT–OUTPUT DATABASE AT HIGH COUNTRY AND SECTOR RESOLUTION , 2013 .

[19]  G. Peters,et al.  A synthesis of carbon in international trade , 2012 .

[20]  Richard Stone,et al.  The Precision of National Income Estimates , 1942 .

[21]  Michael L. Lahr,et al.  A Strategy for Producing Hybrid Regional Input-Output Tables , 2005 .

[22]  Manfred Lenzen,et al.  INVESTIGATING ALTERNATIVE APPROACHES TO HARMONISE MULTI-REGIONAL INPUT–OUTPUT DATA , 2014 .

[23]  Manfred Lenzen,et al.  The sustainability practitioner's guide to multi-regional input-output analysis , 2013 .

[24]  Umed Temurshoev,et al.  A NOTE ON THE GRAS METHOD , 2013 .

[25]  Karen R. Polenske,et al.  A LINEAR PROGRAMMING APPROACH TO SOLVING INFEASIBLE RAS PROBLEMS , 1987 .

[26]  M. Lenzen.  Consumer and producer environmental responsibility: A reply , 2008 .

[27]  M. Lenzen,et al.  MATRIX BALANCING UNDER CONFLICTING INFORMATION , 2009 .

[28]  Anna Nagurney,et al.  Algorithms for quadratic constrained matrix problems , 1992 .

[29]  Manfred Lenzen,et al.  A NON-SIGN-PRESERVING RAS VARIANT , 2014 .

[30]  Stephan Moll,et al.  Towards a global multi-regional environmentally extended input-output database , 2009 .

[31]  S. Giljum,et al.  Materials embodied in international trade – Global material extraction and consumption between 1995 and 2005 , 2012 .

[32]  F. van der Ploeg.  Reliability and the Adjustment of Sequences of Large Economic Accounting Matrices , 1982 .

[33]  Matthias Schroder,et al.  Input–Output Analysis , 2011 .

[34]  Colin Webb,et al.  Projection of Supply and Use Tables: Methods and their Empirical Assessment , 2010 .

[35]  Louis de Mesnard,et al.  Biproportional Techniques in Input-Output Analysis: Table Updating and Structural Analysis , 2004 .

[36]  Manfred Lenzen,et al.  Mapping the structure of the world economy. , 2012, Environmental science & technology.

[37]  R I G Allen,et al.  SOME EXPERIMENTS WITH THE RAS METHOD OF UPDATING INPUT–OUTPUT COEFFICIENTS* , 2009 .

[38]  Manfred Lenzen,et al.  Estimating Generalized Regional Input–Output Systems: A Case Study of Australia , 2009 .

[39]  Manfred Lenzen,et al.  A flexible approach to matrix balancing under partial information , 2006 .