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IOpedia Research Paper No. 05
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Author(s): Temursho U., Weitzel M. and R. Garaffa
Title: Projection of household-level consumption expenditures in a macro-micro consistent framework Date: April 2024 Abstract:
This paper presents a new approach for projecting or updating household-level consumption expenditures in line with the existing macro-data (projections) on aggregate consumption and demographic dynamics. Our macro-micro modelling exercises reveal that the use of outdated microdata could lead to an overestimation of direct climate policy costs as well as benefits from compensatory revenue recycling measures. In terms of distributional impacts, using unadjusted microdata may overstate the regressivity of climate policy costs and the progressivity of after-transfer welfare impacts. These results highlight the importance of using fully consistent macro and micro datasets in policy evaluations. The study further emphasizes the value of producing consumer expenditure projections to quantify the relative uncertainties (or robustness) of results in integrated macro-micro modelling, particularly in relation to (un)expected shifts in household consumption patterns, assessment of different policy instruments or scenarios, and comparisons of projected distributional measures, inequality indicators, and other policy-relevant metrics such as energy or transport poverty. |
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IOpedia Research Paper No. 04
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Author(s): Temursho U. and R. Wood
Title: Input-output decomposition analysis: Review and an application of global multi-region structural path decomposition Date: August 2020 Abstract:
The contribution of this paper is twofold. First, it provides a concise review of the approaches and literature on structural decomposition analysis (SDA), focusing on such issues as policy relevance of SDA, methodological approaches to SDA (i.e. additive vs. multiplicative and chaining vs. non-chaining SDAs), methods of correcting for price changes to obtain input-output data of different years in volume terms for SDA purposes, types of SDAs (i.e. single-region, multi-region and global SDAs, further classified as temporal, between-country and between- database SDA), and structural path decomposition (SPD) as an extension of SDA. Second, we apply the SPD method in a global setting, where the drivers of growth in world greenhouse gas emissions along the individual supply chains (or paths) are quantified. |
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IOpedia Research Paper No. 03
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Author(s): Temursho, U.
Title: On the Euro method Date: October 2019 Abstract:
This paper critically examines the Euro method usage for the purposes of updating supply and use tables (SUTs) and/or input-output tables. Its known restricted applicability to only unnecessarily aggregated and symmetric SUTs (not their underlying rectangular versions) is already an issue of concern. However, by studying analytically the nature of Euro's adjustments of the SUT elements and empirically assessing some of its underlying assumptions, including newly revealed ones, it is concluded that the Euro method is a largely ad-hoc updating procedure. Its recently claimed superiority over the generalized RAS approach (GRAS, or SUT-RAS) in the absence of industry output is challenged. It is shown that applying the standard GRAS with exogenously given estimates of industry outputs still outperforms the Euro method. Published version (Economic Systems Research, 2020)
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IOpedia Research Paper No. 02Author(s): Temursho U., Oosterhaven J. and M.A. Cardenete
Title: A multiregional generalized RAS updating technique Date: September 2019 Abstract:
This paper presents an extension of the generalized RAS technique to a multi-regional (MR) or multi-national setting. The framework is applicable to updating/regionalizing/balancing/projecting any partitioned matrix that needs to conform the new row sums, column sums and non-overlapping aggregation constraints. The technique, which we refer to as MR-GRAS, also handles non-exhaustive constraints, in which case the missing values are endogenously recovered in the updating process. We derive the analytical solution of MR-GRAS and propose a simple iterative algorithm for its computation. Further, we discuss the main properties of the method, most of which contribute to the popularity of RAS-type balancing techniques, and we discuss normalization and interpretation of MR-GRAS multipliers. From a wide range of possible MR-GRAS applications, several updating settings, including national and global Supply and Use tables, are examined. Finally, a detailed guide on MR-GRAS implementation in practice through a worked example is presented, using our publicly available MATLAB code. The following is an MR-GRAS code in R, written and kindly shared by Alexandre Bourgeois (INSEE, France). If necessary, he can also be contacted at: [email protected].
Published version (Spatial Economic Analysis, 2020)
An improved version of the guide to implementing MR-GRAS in practice is included in the online supplementary material of the article. |
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IOpedia Research Paper No. 01Author(s): Temursho U. and R.E. Miller
Title: Distance-based shared responsibility Date: March 2019 Abstract:
This paper proposes to use distance-based responsibility shares in applications of the upstream and downstream shared responsibility frameworks developed by Gallego and Lenzen (2005). The concepts of average distance of producers (or an industry) from primary inputs providers along the system's input demand chain and of average distance of producers from final users along the output supply chain are related to the extent of producers' control over their production processes and sales structure. This allows calculation of each producer's responsibility share. Focusing on CO2 emissions, we then apply the shared responsibility approach within a multi-regional input-output (IO) setting, using the 2005 world IO table available from WIOD. Finally, an empirical test of aggregation (in)variance of country-level shared responsibilities is carried out. It is found that the shared responsibilities are more robust to aggregation when the corresponding shares are pegged to distance rather than to value added or final demand. All in all, our results further substantiate the robustness of the shared responsibility accounting principle, and this is important if the principle is to become standard (or alternative) reporting practice. Published version (Journal of Cleaner Production, 2020, Vol. 257, 120481)
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