3.1 Freakonomics

Before starting this assignment, make sure to complete the reading: Freakonomics Introduction and Chapter 1 (on Blackboard).

Daycare Problem

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Problem:

  • Day-care center policy: Children must be picked up by 4 p.m.
  • Frequent late pickups by parents.
  • Results: Anxious children and teachers waiting longer.

Proposed Solution:

  • Fine tardy parents $3 per late pickup.
  • After all, why should teachers have to work extra for free?

Study:

Key Insights:

  • Fine backfired, making lateness seem acceptable as long as parents paid.
  • Financial incentives can undermine intrinsic motivations (e.g., moral obligation to be on time).
  • Replacing social norms with a small transactional fee can lead to unintended consequences.


Economics: the Study of Incentives

Economists love incentives.

  • They love to dream them up and enact them, study them and tinker with them.
  • Incentives can solve almost any problem.
  • But the solution might not be pretty! (coercion, exorbitant penalties, violations of civil liberties)

You Respond to Incentives All the Time (Positive and Negative)

  • Touch a hot stove –> burn your finger
  • Bring home straight A’s –> get a new bike
  • Pick your nose in class –> you are ridiculed
  • Make the basketball team –> move up the social ladder
  • Ace the SAT’s –> get in to a good college
  • Flunk out of law school –> have to go work at your father’s insurance company

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Incentives: tools to encourage good behavior and discourage bad behavior.

Three Types of Incentives:

  1. Economic: Give the subject something, or take something away; Financial rewards or penalties ($3 “sin tax” on cigarettes)
  2. Social: Use peer pressure or create a social norm (banning smoking on college campuses).
  3. Moral: Appeal to ethics or values; talk to the subject about what’s “right” (government suggesting black market cigarette sales fund terrorists).

Creating Personal Incentives:

  • To overcome procrastination and stay focused on your goals, Stanford Neuroscientist Andrew Huberman suggests using a variable reward system (inspired by casinos):
  • After completing a task, flip a coin:
    • Heads: Celebrate and reward yourself.
    • Tails: Move on without a reward.
  • This keeps you engaged and motivated by creating anticipation.


Exercise 1: Incentives

For each scenario below, identify one economic incentive, one moral incentive, and one social incentive that could help achieve the desired outcome. Then, recommend which incentive you think would work best in each case.

  1. A teacher wants their students to come to class more.
  2. A parent wants their kids to go to bed on time.
  3. A woman wants her boyfriend to propose.
  4. A doctor wants their patient to exercise.
  5. A coach wants their athletes to train during the off-season.


Exercise 2: Bagel Data Project

Based on Chapter 1 of Freakonomics, which describes Paul Feldman’s bagel business and his detailed payment records, I want to help you analyze a simulated dataset that mirrors his observations.

To begin, attach the tidyverse to your current session and read in the bagel data set.

library(tidyverse)
bagel <- read_csv("https://media.githubusercontent.com/media/cobriant/320data/refs/heads/master/bagel.csv")

a) Payment Rates and Office Size

Write a query using group_by and summarize that shows smaller offices (only a few dozen employees) consistently paid for their bagels 3-5% more than large offices (with a few hundred employees). Freakonomics suggests smaller offices experience less theft due to stronger social and shame-based incentives.

# bagel %>%
#   group_by(_____) %>%
#   summarize(_____)

b) The 9/11 Effect

Following the events of September 11, 2001, write a query using lm() to show the payment rate increased by 2%, rising from 87% to 89%. This higher payment level persisted after the initial spike. According to Freakonomics, this sustained increase can be attributed to a rise in empathy among people during that time.

# lm(_____ ~ I(date >= "2001-09-11"), data = _____)

c) Weather Effects

Write a query showing that unseasonably pleasant weather leads to higher payment rates. Cold weather leads to more cheating, and heavy rain and wind also leads to more cheating.

# bagel %>%
#   group_by(_____) %>%
#   summarize(_____)

d) Holiday Effects

Write a query to analyze theft rates during different types of holidays. Specifically, compare holidays associated with high stress and expectations (e.g., major holidays like Christmas or Thanksgiving) to simple long-weekend holidays (e.g., Labor Day or Presidents’ Day). The goal is to demonstrate that theft rates tend to increase during high-stress holidays but decrease during relaxed, long-weekend holidays.

# lm(_____ ~ _____, data = _____)