# POL101Y1 Lecture Notes - Shool, Causal Inference, Dependent And Independent Variables

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Published on 5 Dec 2012
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Nov 5 Lecture
Experiments in Democracy
how we use experiments to learn about the political world*
milk or tea first? Scientist’s (man and women) met, she insisted that she
could tell the order of milk put in (first or after); they decided to run an
experiment to see if she could actually tell; 8 cups, half milk in first, other half
tea in first, randomize and give to girl; identifies all 8 correctly: “Was she
lucky?” “How could we know?”
The Fisher Exact Test
- the probability that she could get all cups correct, by chance, is 1 in 70
So what’s important?
- we can learn from experiments
- we can test peoples claims
- treatment and control
- randomization
- measurement
Some important questions
- Does federalism lead to better political representation?
- Are voters superficial?
- How do we stop patronage and instead get public goods? Does contact
from political campaigns matter in an election
Defining Experiments
- Treating/ Conditions
- Assignment to treatment or control/ comparison groups is random and
the process of randomization is known
- Ex-post measurement of results
- Example: does Prof. Kopstein teach better when he wears a tie?
Treatments
- A treatment is a stimulus
- Anything that is thought to have an effect on some outcome
- It is applied to some people and not to others
- Or, it is applied at some times and not others
- Example: whether Prof. Kopstein wears a tie to class to teach
Random Assignment
- We put some subjects in treatment and some in control
- We do it randomly
- What does it mean that this is done randomly?
- Example: we could flip a coin before every class to see whether Prof.
Kopstein would wear a tie
Ex-post measurement of results
- For an experiment to be complete, we need to measure the results
- What we want to measure are casual effects
- Example: we could measure exam performance at the end of the year
Example
- Question: does wearing a tie make Prof. Kopstein teach better
- Treatment: wearing a tie or not
- Random assignment: flip a coin before class
- Measurement: exam results
What if we didn’t have one of the parts?
Treatment: wearing a tie (needs to have variation)
Random assignment: Kopstein decided on his own when to wear a tie
(wouldn’t work- his decision)
Measurement: no measurement after exams (wouldn’t know results- no
experiment?
All necessary for an experiment
To make a causal inference, we must have all three parts
Causal inference: if there’s x, theres y (if you exercise more frequently, you
will be healthier)
Measuring Effects
- difference in outcomes between two states of the world, treated versus
untreated
- Why is this problematic?
- We cannot observe an given subject in both its treated and untreated
state
- “fundamental problem of causal inference”
- Random assignment enables us to create two groups whose treated and
untreated states are the same in expectation
Casual effect:
- exam results (tie) exam results (without a tie)
Why do an experiment?
- Because we want to make casual inferences
- But we want to make them about important things
1. Does federalism increase representation?
2. Can politicians win by providing public goods rather then patronage?
3. Are elections won for superficial reasons?
Examples
- Field experiments
- Natural experiments
- Survey experiments
- Laboratory experiments
Field experiments?
- What if you intervene in the world?
- And what if subjects do not know they are part of an experiment
- Than you can have a “field experiement”
Example:
-You could randomly assign some people to receive emails telling them to
vote
- You could give some people free tuition and see if it increases or
decreases shool performance
- More example to come
Natural Experiments
- Sometime the world provides for experiments
o Natural disasters
o Lotteries
o School vouchers
- If we can measure the effects of these, we can conduct “natural
experiments”
Survey/ Lab Experiments
- Provide treatments in less natural environments
- They could be don’t over the phone, or online, or in a computer room
- Treatments are often different wordings of a question, or exposure to a
picture, or video content
- More examples to come
- Federalism generates jurisdictional boundaries
- There is a federal government and provincial governments
- Some responsibilities are unique, but some are shared
- These are not always clear, especially to voters
- Who do you contact for help?
- Do boundaries lead to a doubling up? Or, do they lead to an empty core?
Federalism Experiments
- Subjects
o Randomly choose 101 federal and 101 provincial politicians
- Treatments
o Send politicians emails from “citizens”. See how the politican
respond
o Employment insurance, finding a family doctor, student loans
o We also randomize “citizen’s” characteristics, including gender,
ethnicity, and past political support
What are we measuring? (dependent variable)
o All emails are blinded
o Each response was scored on helpfulness, measured from 0 to 5, by
two coders
Clientalism and Voting
- Why do some countries provide for numerous public goods, like roads,
schools, sanitation, etc?
- Why do countries instead provide private or clientalist goods? And
corrupt government?
What do politicians want?
- First, to win office
- Second, to provide good public policy
- So, why don’t they provide for good public policy?