# Demand Forecast of Petroleum Product Consumption in the Chinese Transportation Industry

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## Abstract

**:**

## 1. Introduction

## 2. Literature Review

## 3. Industry Development Status quo and Petroleum Product Consumption

#### 3.1. Economic Support of Transportation Development

**Table 1.**Growth of GDP, added value of transport and per capita annual expenditure in transport: urban and rural.

Year | GDP (Billion Yuan) | Added value of transport (Billion Yuan) | Per capita annual expenditure in transport | |
---|---|---|---|---|

Urban households (Yuan) | Rural households (Yuan) | |||

2000 | 1305.63 | 78.68 | 426.83 | 93.19 |

2001 | 1332.38 | 80.64 | 493.74 | 110.04 |

2002 | 1340.31 | 82.10 | 625.91 | 128.58 |

2003 | 1375.00 | 81.70 | 721.41 | 162.46 |

2004 | 1470.28 | 83.91 | 843.90 | 192.69 |

2005 | 1527.90 | 86.50 | 996.83 | 245.06 |

2006 | 1586.12 | 89.85 | 1147.07 | 288.84 |

2007 | 1707.20 | 96.31 | 1357.66 | 328.51 |

2008 | 1839.75 | 100.56 | 1416.60 | 360.21 |

2009 | 1828.58 | 98.68 | 1682.70 | 402.94 |

2010 | 1948.62 | 102.78 | 1984.34 | 460.97 |

#### 3.2. Status quo of Transportation Development

**Figure 2.**Trend-growth of relevant infrastructure indexes of four types of transport model: 1980–2010 (value in 1980 = 100).

**Figure 3.**Trend-growth of number of vehicles in transport of private cars, civilian vehicles, road transport vehicles and road vehicles for freight: 1985–2010 with value in 1985 = 100.

**Figure 4.**Trend-growth of volume indexes of passenger, freight, freight turnover and passenger turnover in transport: 1980–2010 (value in 1980 = 100).

#### 3.3. Petroleum Products Consumption of Transportation

**Figure 6.**The ratio of energy consumption in transport sector to energy consumption in total of 1980–2010 (value in 1980 = 100).

**Figure 7.**Trend-growth of energy consumption ratio of petrol (diesel) in transport sector in total amount of petrol (diesel) consumption of the whole national economy.

## 4. Experimental Analysis Results and Discussion

#### 4.1. Data

#### 4.2. Model

- $petro{l}_{i}={c}_{i}+{a}_{i}{x}_{i}+{\epsilon}_{i}\text{}(i=1,2,3,4)\phantom{\rule{0ex}{0ex}}diese{l}_{j}={c}_{j}+{a}_{j}{x}_{j}+{\omega}_{j}\text{}(j=1,2,3,4)$
- $\mathrm{ln}petrol={c}_{i}+{a}_{i}\mathrm{ln}{x}_{i}+{\epsilon}_{i}\text{}(i=1,2,3,4)\phantom{\rule{0ex}{0ex}}\mathrm{ln}diesel={c}_{j}+{a}_{j}\mathrm{ln}{x}_{j}+{\omega}_{j}\text{}(j=1,2,3,4)$

_{i}and c

_{j}are the intercepts of both Equations, respectively, that illustrate the basic consumption levels of the petrol products, a

_{i}and a

_{j}are the coefficients of explanatory variables standing for the marginal effect of the explanatory variables on the petrol products, and e

_{i}and w

_{i}the random disturbing terms describing the other factors’ effect on the petrol products except for the explanatory variables selected here.

#### 4.3. Parameter Estimation

Item | Mean | Sd | MC_error | Val2.5pc | Median | Val97.5pc | Start | Sample |
---|---|---|---|---|---|---|---|---|

a_{1} | 101.1000 | 0.9305 | 0.0186 | 99.2600 | 101.1000 | 102.9000 | 15000 | 5001 |

a_{2} | 0.0011 | 0.0001 | 0.0000 | 0.0010 | 0.0011 | 0.0012 | 15000 | 5001 |

a_{3} | 0.0012 | 0.0001 | 0.0000 | 0.0011 | 0.0012 | 0.0014 | 15000 | 5001 |

a_{4} | 0.0005 | 0.0000 | 0.0000 | 0.0004 | 0.0005 | 0.0005 | 15000 | 5001 |

c_{1} | −19.7000 | 0.4385 | 0.0082 | −20.5600 | −19.7000 | −18.8500 | 15000 | 5001 |

c_{2} | 5.7680 | 0.5543 | 0.0114 | 4.6860 | 5.7660 | 6.8310 | 15000 | 5001 |

c_{3} | 1.2080 | 0.7193 | 0.0175 | −0.1981 | 1.2010 | 2.5910 | 15000 | 5001 |

c_{4} | 5.8730 | 0.6562 | 0.0127 | 4.5840 | 5.8700 | 7.1330 | 15000 | 5001 |

Item | Mean | Sd | MC_error | Val2.5pc | Median | Val97.5pc | Start | Sample |
---|---|---|---|---|---|---|---|---|

a_{1} | 305.8000 | 0.9683 | 0.0138 | 303.9000 | 305.8000 | 307.7000 | 15000 | 5001 |

a_{2} | 0.0034 | 0.0001 | 0.0000 | 0.0032 | 0.0034 | 0.0036 | 15000 | 5001 |

a_{3} | 0.0008 | 0.0000 | 0.0000 | 0.0008 | 0.0008 | 0.0009 | 15000 | 5001 |

a_{4} | 0.0015 | 0.0001 | 0.0000 | 0.0014 | 0.0015 | 0.0016 | 15000 | 5001 |

c_{1} | −74.2100 | 0.6761 | 0.0085 | −75.5400 | −74.2000 | −72.8700 | 15000 | 5001 |

c_{2} | 2.5130 | 0.7831 | 0.0131 | 0.9880 | 2.5140 | 4.0310 | 15000 | 5001 |

c_{3} | −8.8480 | 0.8585 | 0.0154 | −10.5500 | −8.8480 | −7.2020 | 15000 | 5001 |

c_{4} | 2.4380 | 0.8563 | 0.0130 | 0.7623 | 2.4490 | 4.1050 | 15000 | 5001 |

_{i}and a

_{j}and that of the intercept of c

_{i}and c

_{j}. When we regard the a

_{i}, a

_{j}, c

_{i}, and c

_{j}as the dynamic varying terms, there is strong evidence that demonstrates we get the a reliable value of the coefficients and intercepts. Figure 10 shows that in Equation (8) the coefficient a

_{4}has validity in the process of value-obtaining and the same thing happens in Equation (5) with respect to the intercept, whereas the result of coefficient estimation of the petrol consumption forecast function shows us the perfect value with high stabilities. However, these validities never change the reliability of the coefficient and intercept.

**Figure 9.**(

**a**) Explanatory coefficient stability upon petrol consumption model; (

**b**) Constant stability upon petrol consumption model.

**Figure 10.**(

**a**) Explanatory coefficient stability on diesel consumption model; (

**b**) Constant stability on diesel consumption model.

#### 4.4. Forecast Analysis

#### 4.4.1. Scenario Design

Item | Scenario | UP | PCGDP | CVN | TPA | TFA |
---|---|---|---|---|---|---|

devised indicator (accumulation) | basic indicator | 4.00 | 40.26 | 92.6 | 37.90 | 31.50 |

optimism indicator | 5.00 | 50.36 | 130.72 | 45.00 | 39.00 | |

pessimism indicator | 3.50 | 37.00 | 53.81 | 24.00 | 24.00 | |

average indicator annual | basic indicator | 1.55 | 7.00 | 13.97 | 6.64 | 5.63 |

optimism indicator | 1.93 | 8.50 | 18.20 | 7.71 | 6.81 | |

pessimism indicator | 1.36 | 6.50 | 8.99 | 5.39 | 4.40 |

#### 4.4.2. Forecast Result

**Figure 11.**The growth trends of petrol and diesel consumptions for the period 1985–2015, where before the year 2010 actual consumption values of the petrol and diesel are showed and after the predicted values are described: (

**a**) with predicted result of petrol and diesel consumption under basic indicator; (

**b**) with predicted result of petrol and diesel consumption under optimism indicator; (

**c**) with predicted result of petrol and diesel consumption under pessimism indicator.

**Table 5.**Predicted value of petroleum products consumption from 2011 to 2015: petrol (million tonnes).

Scenario | Year | UP | PCGDP | CVN | TPA | ARIMA |
---|---|---|---|---|---|---|

Basic indicator | 2011 | 31.58 | 31.58 | 31.58 | 50.33 | 31.76 |

2012 | 32.38 | 32.38 | 32.38 | 56.54 | 32.96 | |

2013 | 33.19 | 33.19 | 33.19 | 63.62 | 32.71 | |

2014 | 34.01 | 34.01 | 34.01 | 71.68 | 33.68 | |

2015 | 34.84 | 34.84 | 34.84 | 80.87 | 34.63 | |

Optimistic indicator | 2011 | 31.77 | 41.56 | 37.11 | 51.98 | 31.76 |

2012 | 32.76 | 44.61 | 39.88 | 60.37 | 32.96 | |

2013 | 33.77 | 47.91 | 42.87 | 70.29 | 32.71 | |

2014 | 34.80 | 51.49 | 46.08 | 82.02 | 33.68 | |

2015 | 35.85 | 55.38 | 49.54 | 95.87 | 34.63 | |

Pessimistic indicator | 2011 | 31.49 | 40.90 | 36.34 | 48.39 | 31.76 |

2012 | 32.19 | 43.19 | 38.23 | 52.21 | 32.96 | |

2013 | 32.89 | 45.62 | 40.23 | 56.38 | 32.71 | |

2014 | 33.61 | 48.21 | 42.33 | 60.92 | 33.68 | |

2015 | 34.34 | 50.97 | 44.54 | 65.87 | 34.63 |

**Table 6.**Predicted value of petroleum products consumption from 2011 to 2015: diesel (million tonnes).

Scenario | Year | UP | PCGDP | TFA | CVN | ARIMA |
---|---|---|---|---|---|---|

Basic indicator | 2011 | 80.91 | 111.62 | 107.20 | 135.81 | 81.49 |

2012 | 83.32 | 119.26 | 113.73 | 154.44 | 83.18 | |

2013 | 85.76 | 127.43 | 120.63 | 175.67 | 85.44 | |

2014 | 88.25 | 136.18 | 127.92 | 199.86 | 87.80 | |

2015 | 90.77 | 145.53 | 135.62 | 227.43 | 90.09 | |

Optimistic indicator | 2011 | 81.48 | 113.15 | 108.49 | 140.76 | 81.49 |

2012 | 84.48 | 122.56 | 116.48 | 165.94 | 83.18 | |

2013 | 87.53 | 132.76 | 125.02 | 195.69 | 85.44 | |

2014 | 90.65 | 143.83 | 134.13 | 230.87 | 87.80 | |

2015 | 93.83 | 155.84 | 143.86 | 272.44 | 90.09 | |

Pessimistic indicator | 2011 | 80.62 | 111.11 | 105.84 | 129.99 | 81.49 |

2012 | 82.73 | 118.17 | 110.89 | 141.46 | 83.18 | |

2013 | 84.87 | 125.69 | 116.15 | 153.96 | 85.44 | |

2014 | 87.04 | 133.70 | 121.65 | 167.59 | 87.80 | |

2015 | 89.24 | 142.22 | 127.38 | 182.44 | 90.09 |

## 5. Concluding Remarks

## Acknowledgments

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**MDPI and ACS Style**

Chai, J.; Wang, S.; Wang, S.; Guo, J.
Demand Forecast of Petroleum Product Consumption in the Chinese Transportation Industry. *Energies* **2012**, *5*, 577-598.
https://doi.org/10.3390/en5030577

**AMA Style**

Chai J, Wang S, Wang S, Guo J.
Demand Forecast of Petroleum Product Consumption in the Chinese Transportation Industry. *Energies*. 2012; 5(3):577-598.
https://doi.org/10.3390/en5030577

**Chicago/Turabian Style**

Chai, Jian, Shubin Wang, Shouyang Wang, and Ju’e Guo.
2012. "Demand Forecast of Petroleum Product Consumption in the Chinese Transportation Industry" *Energies* 5, no. 3: 577-598.
https://doi.org/10.3390/en5030577