REVISITING DECOMPOSITION ANALYSIS FOR CARBON DIOXIDE EMISSIONS FROM CAR TRAVEL: INTRODUCTION OF MODIFIED LASPEYRES INDEX METHOD

摘要

Decomposition analyses are helpful to policymakers and analysts who aim to reduce carbondioxide (CO_2) emissions from car travel. A large number of decomposition methods have beenproposed till date. However, there is still no consensus regarding the best decompositionmethod because each method has certain advantages and disadvantages. Which method isvalid for the decomposition of the changes in CO_2 emissions from car travel? In this paper, werevisit the Refined Laspeyres Index (RLI) method, Logarithmic Mean Divisia Index I (LMDI)method, and Modified Laspeyres Index (MLI) method. After a discussion of theoretical issues,we focus on period-wise, time-series, and cross-region decompositions of the changes in CO_2emissions from passenger cars in Japan, using the three methods. While the RLI and LMDImethods are the most widely used by researchers and analysts, these methods containtheoretical problems with the attribution and distribution of interaction terms, particularlywhen some factors change positively and others change negatively. The recently proposedMLI method helps in resolving these issues by attributing and distributing the interactionterms to related factors according to the changes in each factor. Our case studies in Japan alsoindicate that differences in the attribution of the interaction term to the related factors betweenthe three methods influence the decomposition results significantly. We conclude that the MLImethod generates more valid decomposition results than do the RLI and LMDI methodsbecause of the reasonable attribution and distribution of the interaction terms.