Transportation Economics

Modes of transport:

There exist different modes of transport and these include road transport, railway transport, air transport and sea way transport. Some modes are expensive while others are cheap; others are fast whereas others take long to travel. This paper investigates why some industries will choose some modes of transport while others will opt to other modes. Air transport is the fasted mode of transport and yet does not face such problems as traffic congestion apart from times of crisis such as extreme weather conditions. Railway transport is mostly used by people who prefer to transport heavy goods.

Modes of transport:

The choose of the mode of transport by industries will depend on the nature of a good whether perishable or non perishable, whether bulky or light weight, cost of the mode of transport, custom duties by the export or import duties, the source and *destination* of the goods.

Perishable and non perishable goods:

For the perishable goods industries will choose the fastest mode of transport and discard the slow methods of transportation, for the case of perishable goods the mode of transport preferred is air transport, an example of these perishable goods include flowers, fruits and other agricultural products. For the non perishable goods the industries will use other modes.

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*Transportation economics*

*Bulk* or light weight goods:

The mode of transport to be used for bulky goods will not be air transport the reason being that it is very expensive, bulky goods will usually be transported by road, rail or shipment. For light weight goods the mode of transport will be air transport.

Custom and exercise duties;

The existence of duties by the government will also determine the mode of transport to be used by an industry, some transportation modes experience high taxation levels and therefore most industries avoid them as a result.

Source and destination of goods:

The source of the good and their destination will also determine the mode of transport to be chosen by the industries, for short distance transportation the mode of transport to be used will be road transport but if the distance is long then the mode hereto be used is rail, air or even the use of sea transport.

Advantages and disadvantages of the various modes of transport:

Air transport:

This mode of transport is used for perishable goods and also fragile goods and goods that are

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not bulky, this is a very fast mode of transportation and therefore used for goods that need fast delivery. The bulk per value ratio will determine the choice of this mode of transportation.

Advantages:

– It is a fast mode of transportation

– It has an advantage in that there is the issue of time saving for delivery of goods

– It is a reliable means of transport

Disadvantages:

– There exist freight delays and cancellation in case of crisis such as weather problems

– High duties Levied on goods delivered through these means

– This is a very costly method of transportation

Sea transport:

This mode is used by industries especially when goods to be delivered are bulky and the distance between the source and the destination is large.

Advantages:

– It is a good mode for the transportation of bulky goods

– Transportation of goods for large distance is made possible

– It is less costly than other modes of transportation

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Disadvantages:

– It takes longer time to deliver goods from the source to their destination

– Cannot be used in the transportation of perishable goods

– It is usually hard to monitor the location of goods being transported oedr the time period the goods will be under transit.

Rail transport:

This is also a reliable mode of transportation for bulky goods and it is used to transport coal and other bulky goods

Advantages:

– It is a fast mode of transport

– It can be used to transport heavy and bulky goods

– It is a safe mode of transportation

– Rail transport is a reliable mode of transport

Disadvantages:

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– There may be delays in the transportation of __goods__

– It might be unreliable where the destination of the goods is not covered by the rail network and therefore there is need to change the mode of transport.

Road transport:

This is the most widely used mode of transportation; this is a reliable mode of transport because there exist a reliable transport network which is extensive to every part of a region.

Advantages:

– It is a cost effective mode of transportation

– Reliable in that it offers fast delivery of goods

– It is an ideal means of transport over short distances

– Monitoring of goods over transit is made easy due to ease of communication and locating the exact location

Disadvantages:

– Traffic congestion may cause delay of delivery of goods

– There may be breakage of fragile goods as a result of caress driving

– Traffic regulations on speed may cause delays

We will use the data given to analyse the relationship that exist between the miles covered and the tonnes transported by the modes of transports, then we will get the regression models that give us the relationship that exist between the mode of transport and the tonnes and also the miles travelled, afterwards we will compare this regressed models with each mode to analyse what causes the industries to choose differing modes of transport.

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METHOD:

We will consider data that depict the miles covered by rail transport, road transport (highway miles) and air transport and finally the GDP level of the economy at the time, we are set to find out what determines the choice of transport by industries and our first regression will be to determine the effect of income on the choose of transport. Here we will consider the relationship that exist between the level of GDP and the mode of transport, this will include

1. GDP level and rail transport

2. GDP level and road transport

3. GDP level and air transport

GDP level and rail transport:

In this estimation we estimate the model of the form

Y = b0 + b1X

Where Y is the miles travelled and X is the GDP level

The estimated model is as follows:

Y = 75.75234213 + 0.066655757 X

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Therefore from the above model it is clear that we have a positive autonomous value, and then increase in miles travelled as we increase GDP level is 0.06666 miles

The above model shows that an increase in income will negligibly increase the miles travelled by rail transport.

The R squared which is the correlation of determination is 0.862551199 and this shows the strength of the relationship that exist between rail transport and increase GDP level, the value is that there exist a weaker relationship between GDP and miles travelled by rail as compared to other values we will get from other regressions.

Hypothesis test:

The test hypothesis is for both the autonomous value and the slope of the model

Hypothesis test:

The test hypothesis is for both the autonomous value and the slope of the model

Autonomous value b0

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Null hypothesis:

H0: b0 = 0

Alternative hypothesis

Ha: b0 ≠ 0

For Autonomous value b0 testing at 0.05 significant levels

T critical 1.770933

T calculated 135.9412476

T critical < t calculated

Therefore we accept the null hypothesis

When we accept the null hypothesis this means that the autonomous value is not statistically significant

For the slope b1:

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Null hypothesis:

H0: b1 = 0

Alternative hypothesis

Ha: b1 ≠ 0

For slope b1 testing at 0.05 significant level

t critical 1.770933

t calculated 9.283886104

t critical < t calculated

Therefore we accept the null hypothesis

When we accept the null hypothesis this means that the slope is not statistically significant

GDP level and road transport

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In this estimation we estimate the model of the form

Y = b0 + b1X

Where Y is the miles travelled and X is the GDP level

The estimated model is as follows:

Y = -6463.79099+ 318.3163124X

from the estimated model it is clear that we have a negative autonomous value, then increase in miles travelled as we increase GDP level is 318.3163124 miles, the negative value of the autonomous value depict that if the level of real GDP was zero then the miles travelled by road will be negative.

The above model shows that an increase in income will highly increase the miles travelled by rail transport.

The R squared which is the correlation of determination is 0.862551199 and this shows the strength of the relationship that exist between road transport and increase GDP level, the value is that there exist a strong relationship between GDP and miles travelled by road

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Transportation economics

Hypothesis test:

The test hypothesis is for both the autonomous value and the slope of the model

Autonomous value b0

Null hypothesis:

H0: b0 = 0

Alternative hypothesis

Ha: b0 ≠ 0

For Autonomous value b0 testing at 0.05 significant levels

T critical 1.770933

T calculated -45.6190148

T critical > t calculated

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Therefore we reject the null hypothesis

When we accept the null hypothesis this means that the autonomous value is statistically significant

For the slope b1:

Null hypothesis:

H0: b1 = 0

Alternative hypothesis

Ha: b1 ≠ 0

For slope b1 testing at 0.05 significant level

t critical 1.770933

t calculated 174.363

t critical < t calculated

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**Transportation economics**

Therefore we accept the null hypothesis

When we accept the null hypothesis this means that the slope is not statistically significant

GDP level and air transport

In this estimation we estimate the model of the form

Y = b0 + b1X

Where Y is the miles travelled and X is the GDP level

The estimated model is as follows:

Y = -104.019+ 0.58514X

Therefore from the above model it is clear that we have a negative autonomous value, then increase in miles travelled as we increase GDP level is 0.58514miles

The above model shows that an increase in income will negligibly increase the miles travelled by rail transport.

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The R squared which is the correlation of determination is 0.994554 and this shows the strength of the relationship that exist between air transport and increase GDP level, the value is that there exist a weaker relationship between GDP and miles travelled by air

Hypothesis test:

The test hypothesis is for both the autonomous value and the slope of the model

Autonomous value b0

Null hypothesis:

H0: b0 = 0

Alternative hypothesis

Ha: b0 ≠ 0

For Autonomous value b0 testing at 0.05 significant levels

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T critical 1.770933

T calculated -114.791

T critical > t calculated

Therefore we reject the null hypothesis

When we accept the null hypothesis this means that the autonomous value is statistically significant

For the slope b1:

Null hypothesis:

H0: b1 = 0

Alternative hypothesis

Ha: b1 ≠ 0

For slope b1 testing at 0.05 significant level

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T critical 1.770933

T calculated 50.11764

T critical < t calculated

Therefore we accept the null hypothesis

When we accept the null hypothesis this means that the slope is not statistically significant

Results:

From then above findings it is clear that there exist a strong relationship between the GDP level and the mode of transport, this is evident from the high values of the correlation of determination that is close to the value one. this is because the value one of the correlation of determinations indicates a perfect and strong relationship between variables, the rejected hypothesis however is as a result of a very high stochastic variable, this is to say that the error term is high in all the estimated model, the solution to this is to add more independent variables to explain changes in miles travelled.

However from the above findings it is evident that as the income or real GDP level increases then the miles travelled per mode of transport increases, the most effective mode is the road transport, when the real GDP increases then the miles travelled by road increases by a high proportion than any other mode.

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Therefore firms that use other modes of transport and the real GDP increases then they will tend to use more of road transport. This can also explain why firms with high levels of income and profits use the road transport network.

for railway transport the increase in income will result into a very negligible change in the miles travelled and also that if we hold all other factors constant then the autonomous value of miles travelled will be positive in the rail network, therefore firms will still use rail transport despite the income level, this can mean that railway transport is used not because of the cost but because of other factors such as bulk transportation.

for air transport it is evident that the increase in income will result into a slight but higher level of miles travelled than rail transport, this is to mean that an increase in income will result into an increase in the miles travelled by air, the autonomous value of the regression on air transport is negative and this shows that for zero income levels then the miles travelled by air will be negative, this shows the effect of income on air transport, only the industries with high levels of income and profits will sue air transport and that income levels are a determining factor in choosing air transport.

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