How Do Firms Adapt to Rising Climate Risks?
Revisiting "The Curse of Dimensionality" in Economics
An exciting development in climate change adaptation economics focuses on how different firms in different nations are adapting to the serious challenges they now face. If firms fail to adapt, then extreme weather such as heat waves, PM2.5 spikes, drought and storms will lower their productivity. In aggregate this will disrupt our economy’s economic growth, reduce worker earnings and disrupt our overall quality of life.
In recent years, new papers have been written about how firms in Pakistan adapt to flood risk, how small manufacturing firms in Uganda adapt to high levels of PM2.5, and investigations of how firms in developed nations deploy costly durable goods to offset extreme weather risk exposure.
A key point I want to make here is that the firm level adaptation menu features an almost infinite number of permutations. Recall permutations. Jane flips 3 coins. Eight different outcomes can occur. One of them is (heads, heads , heads) another is (tails, heads, tails). If she flipped 4 coins, then 16 outcomes can occur.
Suppose that a Chinese restaurant at lunch time has 10 different items at the buffet. Taking the portion size as constant, you have a choice. You can either take some (an Egg Roll!) or not of each of the 10 items. Note that you can create 2 to the 10th different lunches here. You have 1024 different choices on your menu! Now suppose that you can either take zero, medium or huge portion of each of these. Your menu combinations is now really, really big. In this blog post, this is what I mean by the “Benefit of Dimensionality”.
The “Curse of Dimensionality” is an old idea in data analysis. Suppose that people differ by age (young , old), height (tall , short), education (college educated or not), by gender (male , female), by race (white, not white), immigration status (USA born, foreign born). Even with this short list, note that there are 2^6 = 64 different types of people. If a Survey researcher surveyed 640 people, on average there would be only 10 people in each of these categories. The researcher quickly runs out of data in using non-parametric methods to study people’s conditional average behavior.
MY POINT
Firms seeking to adapt to weather challenges they anticipate they will face, face the Chinese Lunch Menu problem. They have a such a huge number of choices to adapt that many researchers simply look at a very small subset. This underestimates the adaptation possibility menu.
Suppose that Matthew wants to open a factory that makes a part that is used to make an electric scooter. There is a literature that explores where factories choose to locate; factor prices such as electricity, labor and land are key inputs in determining what is the cost minimizing location. A firm that makes heavy output will benefit from locating “close” to final consumers (depending on how the firm’s output is shopped to final consumers). A firm that uses heavy inputs will benefit (all else equal) from locating close to its input suppliers.
Given these points, now let’s introduce “crazy weather”. Let’s assume that the factory has some data on specific risks its workers and physical equipment will face in each location. If the factory choose a “hellish” location, workers will be unsafe and unhappy and they will only work for the factory if it pays a wage premium (combat pay). The firm’s profits are lower if its costs are higher. NOTE my point. A for profit firm (even if run by a “Climate Denier”) has incentives to avoid areas where workers don’t want to live and work.
This effect is accentuated if insurers charge more in such risky, nasty places and if capital lenders charge higher interest rates in riskier places. So, the firm has an incentive to factor in “climate risks” into its extensive margin locational choice. The U.S has over 3000 counties and a competition will play out concerning which are more climate resilient. Those that prove to be more climate resilient will enjoy an influx of economic activity. Read my 2010 Climatopolis book.
ONCE, the firm chooses where to build its factory, it must now configure the factory. What material is it built out of? What protective durables are inside and operating in the factory? What is the topography of the structure? Is it located at the bottom of a hill? Or is it elevated? Does it have a white roof so it heats up less? Once the factory is producing, how does the firm handle extreme days? Does it call a “Siesta” and tell workers to stay at home? What infrastructure is the factory connected to? What contingency plans does the factory have if the infrastructure is damaged in the short run? What redundancies has the factory built in if it can’t access needed inputs and parts in the short run? Does it hold these in inventory? Can the firm hold output inventories or does it quickly sell everything it produces?
Note that similar to the Chinese restaurant, the number of permutations here are huge. Now suppose that the factory is part of a bigger firm with multiple factories spread out across the nation, what diversification possibilities does this create? What weather risks can be hedged through this self-protection strategy?
In this blog post, I have sketched out the microeconomics of how firms will adapt to the serious risks. I am highly confident that more and more of the real economy will be less injured by the harder punches we are facing. The anticipation that the weather shocks are growing more severe causes firms to take costly steps to self-protect themselves. As more firms demand climate solutions, this causes innovation by other firms who seek to make profit by supplying solutions. This is the Boskin Report optimism applied to climate change adaptation.
Market specialization (Adam Smith’s pin factory) will be applied to adapting to climate change. This lowers the price for adaptation goods and this helps poorer and poorer people to adapt to the serious challenges we face.
Management and Big Data
Suppose that managers of firms are unaware that crazy weather is lowering their productivity. Such managers study their quarter to quarter revenue and output. They would quickly see a negative shock and ask “why”? If their Lieutenants cannot answer this question, they will call in a consultant to diagnose what is the issue and what might be cost-effective solutions. This demand for climate resilience solutions will create new opportunities for young people. We will see Universities starting to offer engineering and planning and economics degrees in climate resilience. Demand creates supply!
The profit motive will nudge managers to address climate resilience as this will become another cost factor that they will take seriously.