Summary of Matthew E. Kahn's Adapting to Climate Change

By IRB Media

Please note: This is a companion version & not the original book. Book Preview:

#1 We are uncertain about how climate change will affect our future quality of life. Few of us are good at predicting the future. Future events such as which team will win the Super Bowl in the year 2030 are random variables today.

#2 As computer power and climate science continue to improve, short-term weather forecasts are becoming more accurate. As these climate risk modelers generate location-specific predictions, how will the public judge the quality of their projections.

#3 The challenge of predicting future climate risks is that it depends on how many people live on earth for each year out to the year 2100, as well as what their average per capita income is.

#4 Climate science today is still grappling with how to incorporate their uncertainty about key parameters into the climate models they create. They want to expand our imaginations about future scenarios.

• Language: English
• Publisher: IRB Media
• Release date: May 13, 2022
• ISBN: 9798822515116

IRB Media

With IRB books, you can get the key takeaways and analysis of a book in 15 minutes. We read every chapter, identify the key takeaways and analyze them for your convenience.

Book preview

Insights on Matthew E. Kahn's Adapting to Climate Change

Contents

Insights from Chapter 1

Insights from Chapter 2

Insights from Chapter 3

Insights from Chapter 4

Insights from Chapter 5

Insights from Chapter 6

Insights from Chapter 7

Insights from Chapter 8

Insights from Chapter 9

Insights from Chapter 10

Insights from Chapter 11

Insights from Chapter 1

#1

We are uncertain about how climate change will affect our future quality of life. Few of us are good at predicting the future. Future events such as which team will win the Super Bowl in the year 2030 are random variables today.

#2

As computer power and climate science continue to improve, short-term weather forecasts are becoming more accurate. As these climate risk modelers generate location-specific predictions, how will the public judge the quality of their projections.

#3

The challenge of predicting future climate risks is that it depends on how many people live on earth for each year out to the year 2100, as well as what their average per capita income is.

#4

Climate science today is still grappling with how to incorporate their uncertainty about key parameters into the climate models they create. They want to expand our imaginations about future scenarios.

#5

The same issue arises when predicting the economic damage caused by climate change. While researchers collect data on well-being indicators, they don’t always study the cause and effect between climate conditions and those indicators.

#6

The three-step method for predicting the likely damage caused by climate change is based on the assumption that the past relation between environmental conditions and outcomes will continue to hold in the future. If the world will be four degrees hotter in the future, and if each extra degree of warmth reduces test scores by five points, then the change in climate will reduce each student’s score by twenty points relative to what each would have scored if the world had not warmed.

#7

The three-stage approach to predicting climate change’s economic impacts is straightforward to implement, and it simplifies the prediction problem because it abstracts from addressing the thorny issue of how technology changes in quality and