# Accounting for Changes in Automobile Gasoline Consumption in Japan: 2000–2007

- Shigemi Kagawa
^{1}Email author, - Yuriko Goto
^{2}, - Sangwon Suh
^{3}, - Keisuke Nansai
^{4, 5}and - Yuki Kudoh
^{6}

**1**:9

https://doi.org/10.1186/2193-2409-1-9

© S. Kagawa et al.; licensee Springer. 2012

**Received: **12 December 2011

**Accepted: **7 November 2012

**Published: **12 December 2012

## Abstract

This paper analyzes gasoline consumption in Japan for the period 2000–2007 using the index decomposition analysis (IDA). The changes in gasoline consumption in Japan were attributed to five factors: (1) change in the annual average driving distance of new and vintage cars, (2) change in the market share of new passenger cars, (3) change in the total number of new passenger cars, (4) change in the fuel economy of new passenger cars, and (5) change in the stock of vintage cars. We used the IDA results to estimate the economy-wide direct rebound effect, where improved fuel mileage causes additional travel. We found that the total gasoline saved by shifting from vintage ordinary passenger cars to both new kei passenger cars and new hybrid cars during fiscal 2006–2007 amounted to 395 ML, while about half of the gasoline savings from car replacement were lost by the direct rebound effects. The analysis shows that the direct rebound effect can be crucial in the effort of reducing overall gasoline consumption as well as household CO_{2} emissions from passenger cars.

**JEL Classification:** Q41, Q43.

## Keywords

## 1 Introduction

In July 2001, the Japanese Ministry of Economy, Trade, and Industry (METI), the Ministry of the Environment (MOE), and the Ministry of Land, Infrastructure, Transport, and Tourism (MLIT) jointly implemented the “Action Plan for the Development and Diffusion of Low-emission Vehicles”. The action plan promotes the use of cars powered by natural gas (CNG), electricity, methanol, and hybrid cars that have higher fuel efficiencies (METI [2011]). In the same year, anti-pollution incentives were incorporated into the car taxation system. Specifically, the special measures adopted for calculating tax rates included the following: taxes were reduced for cars with low environmental loads (i.e., cars with higher fuel efficiencies and low gas emissions) and taxes were raised by approximately 10 % for cars that were older than a specified number of years (13 years after registration for gasoline-powered cars and 11 years for diesel-powered cars).

As a result of these measures, consumers began purchasing and replacing their older vehicles with newer vehicles that had lower environmental loads (MLIT [2011]). A notable fact is that the Japanese gasoline consumption associated with private cars consequently slightly increased by 0.4 % during the fiscal period 2001–2007 (METI [2010]). Accordingly, household CO_{2} emissions from cars have been *not* declining since 2001, but the driving factors responsible for this change are still not known. The clarification of the responsible factors is crucial in understanding why the action plan stated above has not contributed to decreasing gasoline consumption and designing a more effective energy policy.

In this article, we first estimated annual gasoline consumption in Japan by using running test values of fuel consumption instead of actual fuel consumption data obtained from fuel logs is that the influence of different driving style by automobile users is removed from the factors affecting changes in fuel consumption. This means that the real influence of fuel consumption performance of automobiles can be extracted. Three types of target vehicles were considered: standard-sized, gasoline-powered cars (ordinary passenger cars; engine displacement > 660 cc), light gasoline-powered cars (kei passenger cars; engine displacement ≤ 660 cc), and hybrid cars with a gasoline-powered engine. Gasoline consumption was estimated by year and by vehicle type for fiscal 2000–2007.

Subsequently, using the index decomposition analysis (IDA) method (Sun [1998]; Ang [2004]; Ang et al. [2003, 2009]; Hoekstra and van den Bergh [2003]), changes in gasoline consumption over time were decomposed into five factors: change in the state of ownership by vehicle type and by model (year), change in the number of new cars being registered, change in the market share of new cars, change in fuel consumption by vehicle type, and change in the annual average travel distance by vehicle type. Although there is a variety of IDA methods, we employed the Shapley/Sun IDA method in the spirit of Sun ([1998]). In this article, following Ang et al. ([2009]), we formulated the Shapley/Sun IDA method equivalent to the Shapley decomposition method proposed by Shapley ([1953]).^{1} The decomposition results of the study will facilitate a quantitative assessment of the extent to which the recent expansion of light vehicles and hybrid cars in the market is contributing to a reduction in gasoline consumption.

In addition, we reconciled the well-known rebound effect analysis for motor vehicles (see Greene [1992]; Jones [1993]; Goldberg [1998]; Greene et al. [1999]; Greening et al. [2000]; Small and Van Dender [2007]; Mizobuchi [2011]) with the IDA method proposed in this study and estimated the economy-wide energy impacts of the *direct* rebound representing that improved fuel mileage causes additional travel. Specifically, the economy-wide energy impacts of the direct rebound were estimated by substituting the dependent relationship between fuel economy change and travel distance change into the index decomposition formula regarding the effect of the change in travel distance on gasoline consumption. The main objective of this article is to finally analyze the sources of changes in gasoline consumption in Japan over time by investigating the contributions of the five factors mentioned above and the direct rebound effects for motor vehicles.

This article is organized as follows: Sect. 1 describes the research motivation and background, Sect. 2 formulates the Shapley/Sun IDA method regarding gasoline consumption, Sect. 3 illustrates the data construction, Sect. 4 presents results and discussion, and Sect. 5 concludes the paper.

## 2 Methodology

### 2.1 Estimate of Annual Gasoline Consumption

*t*is defined as ${C}_{t}$ and the market share of the new cars of type

*k*is defined as ${\gamma}_{t,k}$, the number of new cars of type

*k*in the year

*t*can be expressed as ${\gamma}_{t,k}{C}_{t}$. Accordingly, the annual driving distance of the type

*k*cars can be obtained as ${d}_{t,k}{\gamma}_{t,k}{C}_{t}$ (km), where ${d}_{t,k}$ is the annual average distance driven per car. Dividing this annual driving distance ${d}_{t,k}{\gamma}_{t,k}{C}_{t}$ (km) by the fuel economy of the type

*k*cars, ${e}_{t,k}$ (km/L), yields the annual gasoline consumption of the type

*k*cars. Summing over all of the type

*k*cars, we can estimate the annual gasoline consumption of new cars as follows (see Kagawa et al. [2011]):

We examined three types of cars: ordinary passenger cars (cars that exceeded any of the kei passenger car specifications are classified into this category), kei passenger cars (engine displacement ≤ 660 cc, vehicle length ≤ 3.40 m, vehicle width ≤ 1.48 m, vehicle height ≤ 2.00 m), and hybrid passenger cars (cars fitted with a gasoline engine and an electric motor), the respective market shares of which can be represented as ${\gamma}_{t,1}+{\gamma}_{t,2}+{\gamma}_{t,3}=1$.

*k*during the year $t-y$, then ${r}_{t}$ is the proper value indicating that the oldest vehicles existing in the year

*t*were registered during the year $t-{r}_{t}$, and the stock of the vintage passenger cars can be obtained as

*y*is $1\le y\le {r}_{t}$. Here, assuming that the annual average driving distance of a vintage car of type

*k*is equivalent to the annual average driving distance of a new car of type

*k*, we can estimate the annual gasoline consumption of vintage cars by dividing the annual driving distance of vintage cars, ${d}_{t,k}{K}_{t,k}^{t-y}$ (km), by the fuel economy of vintage cars, ${e}_{t,k}^{t-y}$ (km/L) (see Kagawa et al. [2011]).

Here, the first term on the right-hand side of Eq. (4) represents the annual gasoline consumption of new cars and the second term represents the annual gasoline consumption of vintage passenger cars.

### 2.2 Decomposition Analysis

*t*can be written as

*t*and $t-1$ can be written as

*t*can be obtained as follows:

where the first term on the right-hand side of Eq. (9) is the effect of the change in the annual average driving distance on gasoline consumption of new cars, the second term is the effect of the change in the market share of new passenger cars, the third term is the effect of the change in the total number of new passenger cars, and the forth term is the effect of the change in the fuel economy of new passenger cars. Following Dietzenbacher and Los ([1998, 2000]) and Ang et al. ([2003]), for example, taking an average of the first terms on the right-hand side of Eq. (9) yields the average effects of the annual average driving distance.^{2}

*N*denotes the number of determinants (i.e., sources examined in the study) and $|{s}_{1}|$ is the number of determinants with a subscript

*t*. Similarly, using the expression shown in Eq. (10), the average effects of the changes in the market share of new passenger cars, the changes in the total number of new passenger cars, and the change in the reciprocal of the fuel economy on gasoline consumption can be formulated as

*k*in the years

*t*and $t-1$ can be estimated by using Eq. (3) as follows:

For example, if we set $t=2000$ and $y=5$ in Eq. (19), the fuel economy of the vintage passenger cars newly purchased in 1995 and owned in 2000 can be expressed as ${e}_{2000,k}^{1995}$. If we set $t=2001$ and $y=6$ in Eq. (19), then the fuel economy of the vintage passenger cars newly purchased in 1995 and owned in 2001 can also be expressed as ${e}_{2001,k}^{1995}$. In this study, we assumed that if the vintages (superscripts) are the same, then the fuel economy of passenger cars will also be the same, irrespective of year. For the above example, this means that ${e}_{2000,k}^{1995}={e}_{2001,k}^{1995}$, or more generally that ${e}_{t,k}^{v}={e}_{t-1,k}^{v}$, where *ν* represents the car vintage. It should be noted that the fuel economy across car ages is different as shown Table 6.

*t*is equal to car age in the year $t-1$ plus 1, Eq. (19) can be further transformed into an algebraic form as follows:

In this study, we abbreviated the effect of the change in the annual average driving distance on gasoline consumption of new and vintage cars (the first term of Eq. (25) (or Eq. (26)) plus the fifth term of Eq. (25) (or Eq. (26))), the effect of the change in the market share of new passenger cars (the second term of Eq. (25) or (26)), the effect of the change in the total number of new passenger cars (the third term of Eq. (25) or (26)), the effect of the change in the fuel economy of new passenger cars (the fourth term of Eq. (25) or (26)), and the effect of the change in the stock of vintage cars (the sixth term of Eq. (25) or (26)) as AD-effect, MS-effect, NR-effect, FM-effect, and the NM-effect, respectively.

## 3 Data Compilation

Number of passenger automobiles (kei, ordinary, and hybrid vehicles) newly registered during 2000–2007 in Japan (unit: number of cars)

Year | Model type | Total | ||
---|---|---|---|---|

Ordinary (cars) | Hybrid (cars) | kei (cars) | ||

2000 | 3,005,753 | 13,353 | 1,312,199 | 4,331,305 |

2001 | 2,931,342 | 24,675 | 1,278,718 | 4,234,735 |

2002 | 3,191,374 | 17,243 | 1,343,194 | 4,551,811 |

2003 | 3,112,555 | 37,421 | 1,300,782 | 4,450,758 |

2004 | 3,328,413 | 64,496 | 1,389,259 | 4,782,168 |

2005 | 3,278,396 | 60,204 | 1,396,799 | 4,735,399 |

2006 | 2,938,394 | 88,495 | 1,488,290 | 4,515,179 |

2007 | 2,873,461 | 90,980 | 1,472,687 | 4,437,128 |

Number of vintage ordinary passenger vehicles registered each year during 2000–2007 in Japan (unit: number of cars)

Initial year registered | Year | |||||||
---|---|---|---|---|---|---|---|---|

2000 (cars) | 2001 (cars) | 2002 (cars) | 2003 (cars) | 2004 (cars) | 2005 (cars) | 2006 (cars) | 2007 (cars) | |

1981 | 250,208 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |

1982 | 45,026 | 252,605 | 0 | 0 | 0 | 0 | 0 | 0 |

1983 | 85,786 | 62,841 | 269,797 | 0 | 0 | 0 | 0 | 0 |

1984 | 136,758 | 104,941 | 73,980 | 297,585 | 0 | 0 | 0 | 0 |

1985 | 234,297 | 155,968 | 119,186 | 83,617 | 328,980 | 0 | 0 | 0 |

1986 | 348,293 | 264,698 | 176,335 | 135,693 | 96,254 | 392,497 | 0 | 0 |

1987 | 603,189 | 405,989 | 312,151 | 208,743 | 160,868 | 129,696 | 478,612 | 0 |

1988 | 1,016,133 | 787,407 | 540,031 | 414,002 | 281,204 | 234,581 | 188,904 | 539,241 |

1989 | 1,774,187 | 1,315,319 | 1,054,034 | 742,539 | 582,911 | 438,577 | 371,358 | 266,678 |

1990 | 2,460,426 | 2,048,085 | 1,571,353 | 1,258,446 | 919,832 | 746,801 | 569,553 | 439,662 |

1991 | 2,781,722 | 2,390,736 | 2,019,399 | 1,577,578 | 1,281,045 | 973,976 | 792,818 | 581,328 |

1992 | 2,895,942 | 2,622,111 | 2,279,351 | 1,941,167 | 1,547,298 | 1,273,780 | 965,299 | 757,587 |

1993 | 2,899,058 | 2,734,061 | 1,798,744 | 2,174,709 | 1,860,806 | 1,514,192 | 1,248,397 | 944,145 |

1994 | 3,111,534 | 2,963,010 | 2,796,776 | 2,550,079 | 2,265,051 | 1,971,473 | 1,605,436 | 1,323,208 |

1995 | 3,375,645 | 3,299,348 | 3,144,819 | 2,982,268 | 2,738,469 | 2,469,138 | 2,158,256 | 1,779,737 |

1996 | 3,735,200 | 3,641,643 | 3,559,815 | 3,403,418 | 3,244,693 | 3,017,667 | 2,738,366 | 2,423,330 |

1997 | 3,769,299 | 3,743,988 | 3,644,708 | 3,566,199 | 3,403,383 | 3,268,465 | 3,031,984 | 2,778,584 |

1998 | 3,427,139 | 3,360,067 | 3,332,114 | 3,238,007 | 3,180,912 | 3,036,232 | 2,913,306 | 2,708,835 |

1999 | 3,216,751 | 3,202,322 | 3,141,402 | 3,109,253 | 3,039,136 | 2,961,426 | 2,819,202 | 2,704,506 |

2000 | 0 | 3,369,102 | 3,356,308 | 3,293,904 | 3,269,023 | 3,176,312 | 3,081,761 | 2,934,795 |

2001 | 0 | 0 | 3,389,424 | 3,375,268 | 3,328,370 | 3,288,064 | 3,186,334 | 3,084,956 |

2002 | 0 | 0 | 0 | 3,368,979 | 3,375,179 | 3,311,220 | 3,265,189 | 3,162,819 |

2003 | 0 | 0 | 0 | 0 | 3,323,690 | 3,305,316 | 3,235,297 | 3,183,519 |

2004 | 0 | 0 | 0 | 0 | 0 | 3,256,635 | 3,240,882 | 3,171,013 |

2005 | 0 | 0 | 0 | 0 | 0 | 0 | 3,234,372 | 3,216,564 |

2006 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 2,980,343 |

Total | 36,166,593 | 36,724,241 | 36,579,727 | 37,721,454 | 38,227,104 | 38,766,048 | 39,125,326 | 38,980,850 |

Number of vintage hybrid passenger vehicles registered each year during 2000–2007 in Japan (unit: number of cars)

Initial year registered | Year | |||||||
---|---|---|---|---|---|---|---|---|

2000 (cars) | 2001 (cars) | 2002 (cars) | 2003 (cars) | 2004 (cars) | 2005 (cars) | 2006 (cars) | 2007 (cars) | |

1981 | – | – | – | – | – | – | – | – |

1982 | – | – | – | – | – | – | – | – |

1983 | – | – | – | – | – | – | – | – |

1984 | – | – | – | – | – | – | – | – |

1985 | – | – | – | – | – | – | – | – |

1986 | – | – | – | – | – | – | – | – |

1987 | – | – | – | – | – | – | – | – |

1988 | – | – | – | – | – | – | – | – |

1989 | – | – | – | – | – | – | – | – |

1990 | – | – | – | – | – | – | – | – |

1991 | – | – | – | – | – | – | – | – |

1992 | – | – | – | – | – | – | – | – |

1993 | – | – | – | – | – | – | – | – |

1994 | – | – | – | – | – | – | – | – |

1995 | – | – | – | – | – | – | – | – |

1996 | – | – | – | – | – | – | – | – |

1997 | 300 | 282 | 287 | 279 | 277 | 267 | 253 | 229 |

1998 | 17,519 | 17,203 | 16,984 | 16,843 | 16,362 | 15,708 | 15,192 | 14,559 |

1999 | 15,444 | 15,366 | 14,997 | 14,944 | 14,574 | 14,306 | 13,706 | 13,328 |

2000 | 0 | 13,852 | 13,808 | 13,528 | 13,456 | 13,192 | 12,977 | 12,305 |

2001 | 0 | 0 | 17,471 | 17,291 | 18,592 | 18,397 | 18,213 | 17,779 |

2002 | 0 | 0 | 0 | 20,659 | 22,174 | 21,909 | 21,806 | 21,377 |

2003 | 0 | 0 | 0 | 0 | 27,941 | 27,864 | 27,634 | 27,285 |

2004 | 0 | 0 | 0 | 0 | 0 | 68,794 | 68,687 | 68,082 |

2005 | 0 | 0 | 0 | 0 | 0 | 0 | 59,973 | 59,895 |

2006 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 79,408 |

Total | 33,263 | 46,703 | 63,547 | 83,544 | 113,376 | 180,437 | 238,441 | 314,247 |

Number of vintage kei passenger vehicles registered each year during 2000–2007 in Japan (unit: number of cars)

Initial year registered | Year | |||||||
---|---|---|---|---|---|---|---|---|

2000 (cars) | 2001 (cars) | 2002 (cars) | 2003 (cars) | 2004 (cars) | 2005 (cars) | 2006 (cars) | 2007 (cars) | |

1981 | 61,746 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |

1982 | 11,111 | 67,489 | 0 | 0 | 0 | 0 | 0 | 0 |

1983 | 21,170 | 16,790 | 78,785 | 0 | 0 | 0 | 0 | 0 |

1984 | 33,748 | 28,038 | 21,603 | 90,742 | 0 | 0 | 0 | 0 |

1985 | 57,818 | 41,671 | 34,803 | 25,498 | 106,204 | 0 | 0 | 0 |

1986 | 85,949 | 70,721 | 51,492 | 41,377 | 31,074 | 133,365 | 0 | 0 |

1987 | 148,851 | 108,471 | 91,151 | 63,652 | 51,934 | 44,068 | 171,266 | 0 |

1988 | 250,755 | 210,377 | 157,694 | 126,243 | 90,782 | 79,706 | 67,597 | 206,814 |

1989 | 437,822 | 351,423 | 307,788 | 226,424 | 188,183 | 149,020 | 132,886 | 102,279 |

1990 | 607,168 | 547,202 | 458,851 | 383,741 | 296,953 | 253,749 | 203,808 | 168,624 |

1991 | 686,455 | 638,751 | 589,684 | 481,055 | 413,565 | 330,938 | 283,700 | 222,957 |

1992 | 714,642 | 700,569 | 665,593 | 591,925 | 499,520 | 432,806 | 345,420 | 290,558 |

1993 | 715,411 | 730,479 | 525,251 | 663,139 | 600,731 | 514,493 | 446,723 | 362,109 |

1994 | 767,844 | 791,649 | 816,686 | 777,601 | 731,235 | 669,868 | 574,485 | 507,491 |

1995 | 833,020 | 881,511 | 918,318 | 909,390 | 884,070 | 838,965 | 772,305 | 682,584 |

1996 | 921,749 | 972,965 | 1,039,501 | 1,037,812 | 1,047,496 | 1,025,345 | 979,890 | 929,422 |

1997 | 930,163 | 1,000,309 | 1,064,291 | 1,087,449 | 1,098,727 | 1,110,561 | 1,084,958 | 1,065,673 |

1998 | 845,727 | 897,734 | 973,010 | 987,373 | 1,026,906 | 1,031,653 | 1,042,491 | 1,038,922 |

1999 | 793,809 | 855,588 | 917,320 | 948,112 | 981,136 | 1,006,235 | 1,008,817 | 1,037,262 |

2000 | 0 | 900,148 | 980,075 | 1,004,418 | 1,055,351 | 1,079,249 | 1,102,770 | 1,125,585 |

2001 | 0 | 0 | 989,745 | 1,029,228 | 1,074,510 | 1,117,220 | 1,140,190 | 1,183,176 |

2002 | 0 | 0 | 0 | 1,027,311 | 1,089,622 | 1,125,088 | 1,168,408 | 1,213,039 |

2003 | 0 | 0 | 0 | 0 | 1,072,999 | 1,123,082 | 1,157,711 | 1,220,978 |

2004 | 0 | 0 | 0 | 0 | 0 | 1,106,541 | 1,159,710 | 1,216,181 |

2005 | 0 | 0 | 0 | 0 | 0 | 0 | 1,157,380 | 1,233,652 |

2006 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1,143,054 |

Total | 8,924,958 | 9,811,885 | 10,681,641 | 11,502,490 | 12,340,998 | 13,171,952 | 14,000,515 | 14,950,360 |

Average annual travel distance of each passenger automobile (kei, ordinary, and hybrid vehicles) during 2000–2007 in Japan (unit: km/y)

Year | Model type | ||
---|---|---|---|

Ordinary [km/y] | Hybrid [km/y] | kei [km/y] | |

2000 | 10,420 | 10,420 | 7,643 |

2001 | 10,595 | 10,595 | 7,693 |

2002 | 10,467 | 10,467 | 7,671 |

2003 | 10,286 | 10,286 | 7,700 |

2004 | 10,071 | 10,071 | 7,664 |

2005 | 9,761 | 9,761 | 7,593 |

2006 | 9,483 | 9,483 | 7,576 |

2007 | 9,438 | 9,438 | 7,620 |

$10\cdot 15$-mode fuel efficiencies of passenger automobiles (kei, ordinary, and hybrid vehicles) during 1981–2007 in Japan (unit: km/L)

Initial year registered | Model type | ||
---|---|---|---|

Ordinary [km/y] | Hybrid [km/y] | kei [km/y] | |

1981 | 13.1 | – | 17.7 |

1982 | 13.7 | – | 18.5 |

1983 | 14.0 | – | 18.6 |

1984 | 14.0 | – | 20.4 |

1985 | 13.8 | – | 20.6 |

1986 | 13.8 | – | 19.9 |

1987 | 13.5 | – | 20.9 |

1988 | 13.3 | – | 18.8 |

1989 | 12.7 | – | 17.9 |

1990 | 12.4 | – | 17.4 |

1991 | 12.1 | – | 15.9 |

1992 | 11.6 | – | 16.7 |

1993 | 11.7 | – | 16.2 |

1994 | 11.8 | – | 15.9 |

1995 | 11.6 | – | 16.5 |

1996 | 11.8 | – | 15.4 |

1997 | 11.9 | 31.4 | 15.8 |

1998 | 12.1 | 31.4 | 15.8 |

1999 | 12.3 | 31.4 | 15.7 |

2000 | 12.6 | 31.4 | 16.6 |

2001 | 13.3 | 31.4 | 16.6 |

2002 | 13.9 | 26.6 | 17.0 |

2003 | 13.9 | 23.6 | 17.7 |

2004 | 13.9 | 26.8 | 17.8 |

2005 | 14.1 | 33.3 | 17.8 |

2006 | 13.9 | 31.1 | 18.1 |

2007 | 14.4 | 29.8 | 18.7 |

Average | 13.0 | 29.8 | 17.6 |

## 4 Results and Discussion

### 4.1 Annual Gasoline Consumption of Cars During Fiscal 2000–2007

Estimated annual total gasoline consumption for passenger automobiles during 2000–2007 in Japan and annual changes in consumption for each year

Year | 2000 | 2001 | 2002 | 2003 | 2004 | 2005 | 2006 | 2007 |

Annual total [10 | 38,533 | 39,791 | 39,519 | 39,884 | 39,788 | 39,089 | 38,262 | 38,034 |

Term | ’00–’01 | ’01–’02 | ’02–’03 | ’03–’04 | ’04–’05 | ’05–’06 | ’06–’07 | – |

Change [10 | 1259 | −273 | 366 | −96 | −698 | −828 | −228 | – |

### 4.2 Effects of Changes in Average Annual Travel Distance

### 4.3 Effects of Changes in the Number of Newly Registered Automobiles

### 4.4 Effect of Changes in Fuel Mileage

### 4.5 Effect of Changes in the Market Share of Newly Registered Automobiles

We will now examine whether the shift observed during fiscal 2005–2006 occurred during other periods. The periods during which a reduction in gasoline consumption was attributable to a decrease in the number of existing cars owned was apparent in fiscal 2005–2006, 2001–2002, and 2006–2007. Examining the market share data for these periods revealed that an increase in the market share of ordinary passenger cars occurred during fiscal 2001–2002, and in kei passenger cars and hybrid cars during fiscal 2006–2007. In other words, a shift from vintage ordinary passenger cars to new ordinary passenger cars occurred during fiscal 2001–2002, and from ordinary passenger cars to kei passenger cars and hybrid cars during fiscal 2006–2007.

First, the effects of shifts during fiscal 2001–2002 were examined. Effects attributable to an increase in the market share of new ordinary passenger cars in this period amounted to 30.3 ML, while those that could be attributed to a reduction in the number of existing vintage ordinary passenger cars owned was −377 ML. Overall, the effects associated with shifting from vintage ordinary passenger cars to new ordinary passenger cars during fiscal 2001–2002 could be calculated as $30.3\text{ML}-377\text{ML}=-346.7\text{ML}$.

The effects of increased market shares of new kei passenger cars and hybrid cars during fiscal 2006–2007 were equivalent to 4.21 ML and 1.26 ML, respectively. Since the effects attributable to a reduction in the number of existing vintage ordinary passenger cars were −400 ML, the total effect of shifting from vintage ordinary passenger cars to new kei passenger cars and new hybrid cars during fiscal 2006 to fiscal 2007 could be calculated as $4.21+1.26-400=-394.53\text{ML}$. Importantly, this reduction corresponds to approximately 1 % of the annual gasoline consumption in fiscal 2007, which is equivalent to twice the annual average travel distance of gasoline-powered ordinary passenger cars to the decrease in gasoline consumption during fiscal 2006–2007.

The effect of consumers shifting between different car models on gasoline consumption revealed that in 2005–2006 and 2006–2007, booms in both compact and hybrid car sectors caused shifts from old ordinary passenger car models to new kei and hybrid car models, respectively. We found that in 2005–2006 and 2006–2007 the effect of the car replacement boom on annual gasoline consumption has significantly increased from −0.005 % to −1 % and that the car replacements played a crucial role in reducing annual gasoline consumption.

### 4.6 How Much Did the Direct Rebound Effect Contribute to the Change in Gasoline Consumption?

The annual variation in the gasoline price, obtained from the Petroleum Information Center at the Japan Energy Economics Institute (PIC [2009]), shows that average annual gasoline prices increased from ¥101.5/L in 2003 to ¥124.6/L in 2005; an increase of approximately ¥23/L over two years. When passenger transport by railway, truck, and automobiles (bus, taxi, etc.) is considered, no changes in the number of passengers or distance were observed over the two-year period when gasoline prices increased. However, the use of railways and trucks for passenger transport increased dramatically after 2004. The effects associated with changes in the annual average travel distance shown in Fig. 1 reveal that during the period when gasoline prices increased rapidly (2002–2005), gasoline consumption decreased. However, the price influence of gasoline subsequently increased gradually during the period 2002–2005 (see Fig. 2).

*d*is the average annual travel distance, ${e}^{-1}$ is liters of gasoline per kilometer (i.e., reciprocal of fuel mileage), ${p}_{g}$ is the gasoline price, and ${p}_{s}={e}^{-1}\times {p}_{g}$ represents the gasoline price per kilometer (i.e., energy service price). The above equation shows that the gasoline cost-per-kilometer elasticity of driving is negative and that it is −0.18. If we consider the changes in average annual travel distance and fuel mileage of new ordinary passenger cars ($k=1$) registered during year 2006 and 2007, we find the following dependent relationship between average annual travel distance and fuel mileage from Eq. (27)

Equation (29) captures the economy-wide energy consumption impact of the direct rebound representing that improved fuel mileage causes additional travel. From Eq. (29), we estimated the shift in gasoline consumption associated with the direct rebound of ordinary passenger cars during 2006–2007 as 192 ML, which corresponds to approximately 0.5 % of the annual gasoline consumption in fiscal 2007. In other words, improvements in fuel mileage during 2006–2007 increased the gasoline consumption by 192 ML. Since the total effect of shifting from vintage ordinary passenger cars to new kei passenger cars and new hybrid cars during fiscal 2006 to fiscal 2007 was −395 ML (see Sect. 4.5), the environmental benefit from the car replacements was reduced by half through the direct rebound effects. The direct rebound effect seems to be crucial to reducing overall gasoline consumption as well as household CO_{2} emissions from cars.

## 5 Conclusions

The results of this study showed that the consumption of gasoline for automobile use fluctuated considerably during fiscal 2000–2003, decreasing slightly in 2004 and then markedly during fiscal 2005–2006. The findings also showed that a reduction in the average annual travel distance contributed significantly to the observed reduction in the annual gasoline consumption. Conversely, increases in the number of kei and hybrid cars owned contributed to an increase in fuel consumption associated with the use of kei and hybrid cars.

If the effect of vehicle type is considered, then the fact that 70 % of the automobiles owned in Japan are ordinary passenger cars is an important consideration. It was confirmed quantitatively that a reduction in the annual average travel distance of standard-sized cars has contributed considerably to reducing gasoline consumption in the country. In Japan, although practical sales of hybrid cars started in 1997, relatively few hybrid cars are owned in Japan and their influence on decreasing overall fuel consumption was shown to be extremely low. However, since the number of cars in this category is expected to increase in the future, gasoline consumption in Japan is likely to decrease in the future. The results also showed that kei passenger cars (light gasoline-powered vehicles) increased steadily throughout the analysis period and that this increase in the ownership of light cars has had the effect of decreasing overall gasoline consumption.

Regarding the effect of shifting between model types on gasoline consumption, shifting from old ordinary passenger cars to new ordinary passenger cars occurred during fiscal 2001–2002. Subsequently, in 2005–2006 and 2006–2007, booms in the compact and the hybrid car markets resulted in consumer preference shifting from old ordinary passenger cars to new kei and hybrid cars, respectively. The results show that these shifts in model types, which occurred three times during the period examined in this study, contributed to a reduction in gasoline consumption in every period. Importantly, we found that in 2005–2006 and 2006–2007 the effect of the car replacement boom on the annual gasoline consumption increased significantly from −0.005 % to −1 % and that the car replacements played a crucial role in reducing the annual gasoline consumption.

By reconciling the rebound effect analysis in Japan (Mizobuchi [2011]) with the IDA proposed in this study, we estimated the economy-wide direct rebound effect of ordinary passenger cars during 2006–2007 to be 192 ML. Since the total effect of shifting from vintage ordinary passenger cars to new kei passenger cars and new hybrid cars during fiscal 2006 to fiscal 2007 was −395 ML, the environmental benefit attributable to car replacements was reduced by half through the economy-wide rebound effects.

However, the extent to which this shift in model type contributed to an overall reduction in gasoline consumption cannot be concluded based solely on the findings presented in this study, which also examined gasoline consumption at different life cycle stages associated with automobile use. Future studies should analyze the influence of shifting between models on energy consumption at the automobile manufacturing stage and disposal stage. Furthermore, long-term trends in these shifts should be analyzed in detail.

Thus, based on the results of the analyzes presented in this study, the reduction in fuel consumption resulting from the decrease in the annual average travel distance is greater than the reduction in gasoline consumption resulting from fuel consumption improvements. This means that limitations to short-term reductions in CO_{2} emissions cannot be affected by improving fuel consumption for new cars alone. In other words, our results show that changes in usage patterns by users have been more effective at reducing automobile gasoline consumption than the improvements made by automobile manufacturers to the fuel consumption efficiency of vehicles to date.

Another recommended method is the log mean Divisa index (LMDI) method from the point of view of desirable properties such as factor reversal, time reversal, and completeness (see Ang [2004] for details). Since we aim to combine the gasoline decomposition analysis with the input-output structural decomposition analysis (SDA) (e.g., Dietzenbacher and Los [1998, 2000]) in near future, we decided to employ the Shapley/Sun IDA method consistent with the Dietzenbacher/Los SDA method (see Hoekstra and van den Bergh [2003] for a comparison between IDA and SDA). We think that the Shapley/Sun/Dietzenbacher/Los decomposition method and the LMDI method will present similar decomposition results as in Ang ([2004]). Also, see Fig. 3 in Su and Ang ([2012]) for guidelines on decomposition method selection.

## Declarations

## Authors’ Affiliations

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