Econ 330: Urban Economics

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# Econ 330: Urban Economics
## Lecture 13
### Andrew Dickinson
### 10 August, 2021

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# Lecture 14: Automobiles

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# Schedule

.pull-left[
.ul[.bigger[.hi-gold[Today:]]]

.hi-white[(i). US automobile use]

.hi-white[(ii). Externalities]

.hi-white[(iii). Congestion Pricing]

]

.pull-right[
.ul[.bigger[.hi-gold[Upcoming:]]]

- .hi-white[Reading:] (Chapter 8)
  
  - .hi-white[Book Report:] Due August 15
  
  - .hi-white[PS02:] Due August 15
  
]

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# Automobile use data

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# Auto use in the US

.pull-left[
![](./figures/modal-commuter.png)
]

.pull-right[
.hi[Facts about American auto use:]
- 88 percent of commuters use the car
- Only 5 percent of commuters use public transit at the national level
- Only 2 metro areas have public transit use above 10 percent
  - NYC
  - Chicago]

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# Vehicle Miles Traveled

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# US: People like Cars

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# Carbon Emissions

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# Climate crisis

A recent [UN scientific report](https://www.ipcc.ch/report/ar6/wg1/#SPM) leaves no doubt that humans are responsible for the current climate crisis

Increased frequency of extreme weather including:

.pull-left[
- Wildfires
- Winter storms
- Hurricanes]
.pull-right[
- Heat waves
- Floods
- Droughts
]

Other consequences include:

.pull-left[
- Mass extinctions
- Changes in ocean currents]
.pull-right[
- Loss of habitat (reefs, rainforest, ice sheets)
- Sea level rise
]

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# Climate crisis

![](./figures/greenhouse.png)

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# Carbon emissions

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# Carbon emissions

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# Policy questions

--
  
.center[.hi[Currently per capita CO2 emissions in develping countries skyrocket?]]

--
  
.center[.hii[The future of global carbon emissions depends heavily on how car ownership rates evolve in China and other emerging economies]]

<br>

.center[.hi[How do we reduce CO2 per capita emissions?]]

.center[.hii[What axiom can we apply to improve our understanding of usage?]]

.center[.hi[Do drivers fully internalize the costs of CO2 emissions?]]

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# Externalities

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# Externalities

.hi[Recall Axoim 3:] .hii[Externalities cause inefficiency]

What are some externalities from driving?

--
.pull-left[
- Congestion
- Environmental Damage
- Collisions]
.pull-right[
- Blight (parking lots instead of parks)
- Noise Pollution]

.hi[How costly is congestion?]

Typical commuter spends .hi[47 hours per year] in traffic
- Very high in some metro areas (LA: 93, SF: 72, Atlanta: 67)
- Estimated gasoline cost due to congestion delays: .hi[5 billion per year]
- Time + Gas cost estimate: .hi[63 billion per year]

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# Externalities

.smallerer[
.hi[.ul[Definition:] Marginal Social Cost] (MSC)
> Added cost to _society_ from one extra unit of production/consumption

.hi[Note:] `$MSC \neq  MC$`
]

.smallerer[.hi[.ul[Definition:] Marginal Private Cost] (MPC)

> Added cost to _agent_ from one extra unit of production/consumption

.hi[MSC is the marginal cost (private) plus the marginal external cost (social)]
]

.smallerer[
.hi[.ul[Definition:] Marginal Social Benefit] (MSB)

> Added benefit to _society_ from one extra unit of production

]

.smallerer[
.hi[.ul[Definition:] Marginal Private Benefit] (MPB)

19 / 34

> Added benefit to _society_ from one extra unit of production

]

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# Externalities: Example

Consider the market for .hi[gasoline]

Using gasoline in cars causes air pollution and generates greenhouse gases

Gasoline producers pays its input suppliers and workers but does not consider the external costs to society
- MSC > MPC

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# Congestion externalities

Let's start by assuming the only externality from driving is congestion

.hi[Consider a commute within a metro area with the following characteristics:]
- Distance ( `$d$` ): Let the commute distance be 10 miles `$d = 10$`
- Monetary travel cost ( `$m$` ): Monetary costs are \$0.2 per mile `$m = 0.2$`
- Time cost ( `$c$` ): Opportunity cost of time is \$0.1 per minute `$c = 0.1$`

Thus the total cost of the trip is `$(m + c)\cdot 10$`

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# Congestion externalities

.center[
![](./figures/table10.png)
]

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# Congestion externalities

.center[
![:scale 90%](./figures/fig10-3.png)
]

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# Congestion pricing

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# Congestion pricing

How do we fix .hi[Congestion?]

.hii[Popular Answer:] Build more roads

--
  
Building more roads `$\Rightarrow$` more space for cars `$\Rightarrow$` congestion will decrease

.qa[Q]: What assumption must we make when stating

.center["_building roads will reduce congestion_"]

.qa[A]: The number of drivers will remain the same after the road is built

.hi[Is this true?]

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# My nightmare: LA Traffic

![](figures/la_traffic.jpg)

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# Congestion pricing: Cost incentives

Obvious when we think about the incentives of drivers

.hi[(i).] People avoid driving because it is costly
- Time cost
- Gas cost
- Matinence cost

.hi[(ii).] Building a new road makes it less costly
- Time cost `$\downarrow$`

.hi[(iii).] On the .hi[margin], people will start to drive when the new road is built

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# Tangent: How do traffic jams start?

What actually causes congestion/traffic?

</center>

[Overbreaking](https://youtu.be/iHzzSao6ypE)

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# Externalities: Pigouvian taxes

Roads: Not a great solution. Better idea?

No more monkies driving on the roads? Tech isnt there yet.

.center[.hi[Pigouvian taxes]]

.hi[Main insight:]

The social cost of driving exceeds private cost

So how can we raise the MPC such that `$MPC = MSC$`

.center[.hi[How can we do this?] .hii[Tax them.]]

The pigouvian tax specific to reducing road congestion is .hi[congestion pricing]
  
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# Externalities: Pigouvian taxes

Many cities across the globe have enacted or are planning to enact congestion pricing

.pull-left[
- London
- Singapore
- Milan]
.pull-right[
- Stockholm
- Bejing
- NYC, LA, SF (coming soon)
]

.hi[Results:]

Following enactment of congestion pricing in London:

- Traffic was reduced by 15%
- Reduced travel times in the city by 30%

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# Congestion pricing: London

.center[
![](./figures/london.png)
]

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# Congestion pricing: London

.center[
![](./figures/london_pricing.jpg)
]

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# Congestion pricing: London

.center[
![:scale 115%](./figures/london_cars.png)
]

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# Model with Pigouvian Taxes

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# Peak vs. Off Period Taxes

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# Mechanisms

Model demonstrated congestion taxes reduce traffic volume. How?

.hi[(i).] Modal substition: switch to carpool, public transit

.hi[(ii).] Switch to off-peak travel

.hi[(ii).] Switch route

.hi[(iv).] Location decisions: change residence or workplace

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# Discussion

Congestion taxes sound like a good idea, right? What are the problems?

- Roads aren't always congested. So tax needs to be time-varying. Gets very complicated

- Are all autos charged the same amount (semis and prius?)

How can this idea be adapted to combat the .hi[climate crisis?]

.center[.hii[Put a tax on carbon]]