Demand for ground transportation fuels in 10 Asian countries: An application of the autoregressive distributed lag bounds testing approach

• DOI: http://doi.org/10.1111/1468-0106.12245
• Date: 01 October 2019
• Published date: 01 October 2019
• Author: Wen‐Hsien Liu,Kai‐Jen Lin

ORIGINAL MANUSCRIPT

Demand for ground transportation fuels in 10 Asian

countries: An application of the autoregressive

distributed lag bounds testing approach

Wen-Hsien Liu

1

| Kai-Jen Lin

1,2

1

National Chung Cheng University, Chiayi,

Taiwan

2

Central Taiwan Science Park Administration,

Ministry of Science and Technology, Taichung,

Taiwan

Correspondence

Wen-Hsien Liu, Department of Economics and

Institute of International Economics, National

Chung Cheng University, Chiayi 62102, Taiwan.

Email: whl@ccu.edu.tw

Abstract

This study applies the recently developed autoregressive

distributed lag bounds testing approach to investigate

demands for gasoline and diesel in the ground transporta-

tion sectors of 10 Asian countries from 1983 to 2013.

Results reveal an inelastic fuel demand with respect to

price, except in Hong Kong. This relation implies that the

government is unable to limit fuel consumption by con-

trolling price. Moreover, fuel demand with respect to

income is generally greater than price elasticity. In other

words, if the growth of the national income is faster than

that of fuel price, fuel consumption will continually

increase. Long-term income elasticity is greater than unity

in half of the examined countries. The demand for trans-

portation fuel in these countries is expected to grow at a

rate faster than the growth of GDP over a wide range of

economies in Asia, with the implication that the concern

regarding the scarcity of fossil fuel is not misplaced.

1|INTRODUCTION

Since the first oil crisis in the 1970s, considerable attention has been devoted to the importance of

oil consumption in the global economy. Table 1 shows the shares of primary sectors in global oil

consumption in 1973, 2004 and 2014. Among these sectors, transport consumed the largest amount

of oil in the examined periods. Its share of oil consumption increased from 42.3% in 1973 to 57.7

and 64.5% in 2004 and 2014, respectively. Therefore, the dominance of the transport sector in

global oil consumption cannot be disregarded nor can too much emphasis be placed on the role of

oil in the transport sector. Furthermore, compared with the world average of 3.26%, the annual

growth rate of oil consumption in the transport sector of Asian economies reached 7.33% in 2004

Received: 24 May 2015 Revised: 30 April 2017 Accepted: 10 September 2017

DOI: 10.1111/1468-0106.12245

606 © 2017 John Wiley & Sons Australia, Ltd wileyonlinelibrary.com/journal/paer Pac Econ Rev. 2019;24:606–627.

and surpassed that of other areas in the world. The major source of growth in oil consumption is,

therefore, Asian economies.

This study aims to estimate the demand for major ground transportation fuels, namely, gasoline

and diesel, in 10 Asian countries that vary in terms of economic development level and transporta-

tion characteristics. Following the autoregressive distributed lag (ARDL) model proposed by Hasa-

nov (2015), we estimate and compare the price and income elasticities of gasoline and diesel in

each country. The empirical results indicate that short-term income elasticity is inelastic and greater

than price elasticity in most countries. This finding implies that fuel consumption will persistently

increase if the growth of the national income is faster than the growth of fuel price. Estimates of

long-term income elasticity are also greater than unity for 5 out of the 10 countries. This result pro-

vides evidence that the demand for transportation fuel is expected to grow at a rate faster than the

growth in GDP over a wide range of economies in Asia, with the implication that the concern

regarding the scarcity of fossil fuel is not misplaced.

The rest of the paper is organized as follows. Section 2 introduces related empirical studies.

Section 3 describes of the empirical model and presents the data sources. Section 4 discusses the

empirical results of our model and provides policy implications. Section 5 presents the conclusions.

2|LITERATURE REVIEW

Early studies, such as those of Houthakker, Verleger, and Sheehan (1974) and Ramsey, Pasche, and

Allen (1975), primarily focused on estimating the price and income elasticities of the demand for

gasoline. Houthakker et al. (1974) used the flow-adjustment model and pooled data of 48 states in

the United States during 1963–1972 to calculate the elasticity of the demand for gasoline. They con-

cluded that short-term elasticity is smaller than long-term elasticity because gasoline is a non-

durable good. Ramsey et al. (1975) divided the gasoline demand into personal and commercial uses.

They applied the two-stage least-squares method to estimate the gasoline demand for personal and

commercial uses during 1947–1969. They observed that gasoline demand with respect to price is

inelastic, and a negative relation exists between diesel price and gasoline demand for

commercial use.

Further international evidence on the elasticity of the demand for energy was provided in subse-

quent studies. For example, Nordhaus (1977) estimated the energy demand of five sectors (agricul-

ture, transport, household, industry and energy) by using pooled data of six industrial countries

(UK, France, Germany, Italy, Belgium and the Netherlands). They concluded that the energy

demand of the transport sector is the most inelastic with respect to price because the use of oil in

this sector is not technologically substitutable. Wheaton (1982) used cross-sectional data to estimate

the price elasticity of the gasoline demand in 25 industrial countries in 1972. The empirical results

indicated that gasoline demand, in the long term, is inelastic with respect to price but elastic with

TABLE 1 1973, 2004 and 2014 shares of global oil consumption by sector

Sector 1973 2004 2014

Industry (%) 20.9 9.9 8

Transport (%) 42.3 57.7 64.5

Non-energy use (%) 12.2 16.8 16

Others (%) 24.6 15.6 11.8

Source: International Energy Agency (2006, 2016). Note: Other sectors comprise agriculture, commercial and public service, residen-

tial and non-specified others.

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