The Microeconomics of the Rise of Green Buildings and Climate Change Adaptation: A California Example

 In this blog post, I’d like to introduce a “mashup” where I combine ideas about green buildings, the rise of Work from Home, climate change adaptation, and non-linear pricing of electricity to make some predictions about the rise of the green economy. People who know my work, know that I’ve published several papers on green buildings.  

To make my main point, I need to establish several other points;

Point #1;  In California, there is a sharp geographic temperature gradient such that areas closer to the water (Santa Monica, Berkeley) are much cooler than more inland places (say 30 or 40 miles inland).

Point #2;  Climate Change is likely to exacerbate this spatial temperature gradient;  UCLA’s Alex Hall makes some very nice maps of these likely impacts.  Here is an example documenting the past map of hot days in the recent past versus in the medium term future in the LA area.

Point #3;  Many California electric utilities feature non-linear increasing block tariffs for electricity such that the more electricity your household consumes per month, you will face a higher marginal price for consumer more power.  Frank Wolak and I explore this issue in our 2013 paper.  The introduction of dynamic pricing (such that the marginal price of electricity spikes during peak summer hours would only accentuate the discussion below because it would act as an incentive to “go green”.)

Point #4;   Homes are durable goods that last for 50 years or longer and the initial attributes of the home often determine how the current owner uses the home.  A buyer of a used home faces adjustment costs for upgrading the home. This includes the financial costs and the hassle of the upgrade.

Point #5;  The rise of Work from Home in the post-covid economy could lead to more people seeking to live further inland where land is even cheaper even though these places get quite hot.  Nick Bloom’s surveys indicate that people will go to work 2 days a week post-covid and this effectively reduces the cost of commuting per mile.  

Point #6;  The fixed cost of building green homes charged by solar panels are getting cheaper and there are increased synergies between having such a solar home charge a family’s electric vehicles. See our Tesla paper.

Point #7;  Center Cities (especially progressive center cities) limit the ability of developers to build new housing due to costly red tape.   See my 2011 paper; 

Combining these points yields the following “theorem”;  

The combination of climate change,  non-linear pricing for electricity, the rise of Work from Home, and center city NIMBYism limiting new housing construction will lead to a rising share of homes at the Suburban fringe and a rising % of these homes will be zero energy homes even if there is no new low carbon regulation.

Suppose that each household features 1 person and he chooses where to live.   If this person lives far from the city center in a hot place; he exposes himself to average temperature T_j for the year where “j” indexes the geographic location.    To keep this simple, let each location j differ on 2 dimensions; distance from the city center (d_j) and temperature T_j.

The non-linear pricing function of electricity is defined as p(E_j) which is an increasing and convex function of E.  E_j is an increasing and convex function of T_J and a convex function of the home’s square footage.   Home square footage is an increasing function of distance from the city center because land prices fall with distance from city center.    

People who live further from the city drive more miles (see my 2000 paper).     Assume that a person who lives j miles from the city center drives M_j miles.  Assume the conventional vehicle achieves 30 miles per gallon and the price of gasoline per gallon = 2.

The annual energy bill for a person at location j = 2*M_j/30   + p(E_j)*E(T_j, d_j).

Note that if the person installs a solar panel home that fuels the EV then the annual energy bill = $0!

Assume a fixed cost $F for this install.  We now have the theorem. The cost minimizing person will “go green” even if he doesn’t have Greta Thurnberg’s preferences if the cost savings are large enough. He will compare the expected present discounted value of the cost savings from going green to the upfront cost.

 Note that climate change is one of the causes of this greening! (since this increases temperature and the status quo electricity bill).

This blog post is meant to teach you the microeconomics of climate change adaptation.  We are not passive victims.  This rising demand for green low operating costs homes will induce innovation.  This is a key theme of my 2021 Yale Press book Adapting to Climate Change.  Note that there is no government in this economy as its rational agents use markets to mitigate carbon (unintentionally as they seek to reduce their energy bills) and to adapt to the rising heat.

Let’s return to point #2 above.  Climate Scholars such as Alex Hall do a great job documenting the likely climate gradient of future high heat but such scholars often assume that we are passive victims here as Riverside and other inland areas “heat up”.  Such scholars focus on Government to solve the problem.  As this blog post has noted, the private sector offers an alternative adaptation strategy here.  We are not passive victims in the face of a serious threat.