REGIONAL DEMAND FORECASTING STUDY FOR TRANSPORTATION

FUELS IN TURKEY

Özlem Atalay

Prof. Gürkan Kumbaroğlu

Bogazici University

INTRODUCTION

The prediction of fuel consumption has been an important tool for energy planning, with the following purposes which cited as to

• (i) develop right pricing and taxation systems,

• (ii) help decide future investments on fuels,

• (iii) aid address emission and pollution issues, and

• (iv) plan of future energy needs, identify national infrastructure and research and development requirements.

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INTRODUCTION

In general, established models can be handled in six main categories.

• Multi Linear Regression Models (region-based and yearly)• Moving Average (region-based and yearly)• Double Moving Average (region-based and yearly)• Simple Exponential Smoothing (region-based and yearly)• Double Exponential Smoothing (region-based and yearly)• Time series models Holt–Winters’ model (region-based and

quarterly)

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Regions and Fuel Distribution According to

Regions for the year 2013

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Figure. Regions and Fuel Distribution According to Regions for

the year 2013

THE TRANSPORT SECTOR IN TURKEY

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Figure. Road Transportation Fuel Demand

Figure . The Percentage Distribution of Vehicles According to Fuel Type in Turkey and Istanbul

INDEPENDENT VARIABLES

• Population

• Gross Value Added

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Forecast 2013 MSE MAD MAPE

MA=2 177,921,777 TL 182,197,788,884,410 11,606,205 7.980%

MA=3 171,083,829 TL 282,149,287,971,249 15,117,907 10.291%

Table. Forecasts and Accuracy Results of Istanbul for MA=2 and MA=3

Figure. MA=2 Results of GVA for Istanbul

INDEPENDENT VARIABLES

• Selling Price

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Forecast

2013MSE MAD MAPE

Gasoline MA =2 2.162 TL 0.165 0.280 16.440%

MA =3 2.178 TL 0.213 0.300 15.335%

Diesel MA =2 1.890 TL 0.120 0.259 18.495%

MA =3 1.898 TL 0.155 0.294 18.340%

LPG Regression 1.311 TL 0.001 0.031 2.761%

MA =2 1.263 TL 0.005 0.064 5.331%

Table . Forecasts and Accuracy Results of Selling Prices for Isatnbul

Figure. MA=2 Result of Gasoline Selling Price for Istanbul

INDEPENDENT VARIABLES

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Figure. MA=2 Result of Diesel Selling Price for Istanbul

Figure. Regression Analysis of LPG Selling Price for Istanbul

INDEPENDENT VARIABLES

• Car Park

CP (it) = b0+ b1* GVA (t) / P (t) + b2 * CP (i, t-1)

- i is the fuel type index,- t is the year index,- CP (it) is the car park of fuel type i in time t,- GVA (t) is the Gross Value Added in time t, - P (t) is the population in time t,- CP (i, t-1) is the car park of fuel type i in time t-1,- b0 is the fixed sales value,- b1 is the increment of the rate of the GVA and Population which

causes the car park,- b2 is the increment of the car park from previous year which

causes the car park.

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INDEPENDENT VARIABLES

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Table. Car Park (Gasoline)

Car Park (Gasoline) Istanbul =

-23.343 +0.870 * GVA/Population

+ 1.057 * The car park from previous

year(Gasoline)

Figure. Regression Results of Car Park for Istanbul

Regression Analysis

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Table. Regression Analysis of Gasoline

Regression Analysis

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Regression Analysis

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Figure. Regression Results of the Amount of Yearly Gasoline Sales for Istanbul

COMPARISON OF THE FUEL DEMAND

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Figure. Comparison of the Amount of Yearly Gasoline Sales for Istanbul (MA=2)

Figure. Comparison of the Amount of Yearly Gasoline Sales for Istanbul (MA=3)

MSE MAD MAPE

9.54E+09 73,368 13.119%

MSE MAD MAPE

15,195,631,702 111,514 20%

COMPARISON OF THE FUEL DEMAND

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Figure. Comparison of the Amount of Yearly Gasoline Sales for Istanbul (Regression)

Figure. Comparison of the Amount of Yearly Gasoline Sales for Istanbul (DMA=2)

MSE MAD MAPE

16,696,051,537 127,953 24%

MSE MAD MAPE

1,220,000,000 31,770 4.930%

COMPARISON OF THE FUEL DEMAND

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Figure. Comparison of the Amount of Yearly Gasoline Sales for Istanbul (SES)

Figure. Comparison of the Amount of Yearly Gasoline Sales for Istanbul (DES)

MSE MAD MAPE

7,915,307,493 71,488 12.571%

MSE MAD MAPE

6,567,972,636 67,549 11.518%

TRIPLE EXPONENTIAL SMOOTHING

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MSE MAD MAPE Q1 113593

1.04E+08 8029.888 6.016% Q2 121716

Α β γ Q3 119491

0.523525 0.223519 0.912047 Q4 117046

Table. Accuracy of Winter’s Method for Gasoline Sales

Figure. Winter’s Method for The Amount of Yearly Gasoline Sales (Quarterly)

CONCLUSION

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Regions The Best Performing Method 2013 2014 RegionsThe Best Performing

Method2013 2014

Istanbul

Regression (G) -26% -29%

Central Anatolia

Regression (G) -4% -6%

MA=3 (D) -7% -2% Regression (D) +7% +5%

Regression (LPG) +1% +1% Regression (LPG) +9% +9%

West Marmara

Regression (G) +2% -6%

West Black Sea

Regression (G) +1% -1%

Regression (D) +6% +8% Regression (D) +2% -1%

Regression (LPG) +10% +10% DES (LPG) +10% +18%

Aegean

Regression (G) +0,37% -3%

East Black Sea

Regression (G) -0,95% -3%

Regression (D) +3% +5% Regression (D) +5% +12%

DES (LPG) +10% +19% DES (LPG) +10% +18%

East

Marmara

Regression (G) -3% -6%

Northeast Anatolia

Regression (G) -4% -8%

DMA=2 (D) +8% +14% Regression (D) +4% +3%

Regression (LPG) +2% +1% Regression (LPG) -14% -10%

West

Anatolia

Regression (G) -6% -9%

Central East

Anatolia

MA=3 (G) +0,24% -0,48%

Regression (D) +4% +4% Regression (D) +5% +10%

DES (LPG) +8% +15% Regression (LPG) +10% +19%

Mediterranean

SES (G) -11% -13%

South East Anatolia

SES (G) +10% +11%

Regression (D) -8% +7% Regression (D) +11% +9%

DES (LPG) +11% +20% Regression (LPG) +7% +9%

Table. Best Performing Methods and Percent Change Projections for Fuel Demand