Canada

This past week, smoke from wildfires in Canada once again drifted southward and gave very unhealthy air in parts of the U.S. Several sources I checked indicated that it is unrealistic to expect human effort to extinguish these fires (see here , here, and here). The Canadian forests are just too huge in relation to the fire-fighting resources. What usually happens, even during a normal fire season, is that summer fires just keep burning until they are dampened down by winter rain, snow, and cold. Most of the fire-fighting efforts are devoted to saving communities that are in the path of the flames.

Thus, we may expect periodic episodes of unhealthy air for the next several months. The most hazardous smoke particles are those less than 2.5 microns in size. Particles this small make it past your body’s defenses and penetrate deep into your lungs, promoting a number of serious medical conditions. These smoke particles are made of toxic chemicals like polycyclic aromatic hydrocarbons.

What to do to protect yourself? A first line of defense is to don an effective mask, even indoors. We all probably have Chinese KN95 or Korean KM94 masks left over from pandemic days, and (properly fitted around the nose) these should filter out most of the smoke, including the particles that are less than 2.5 microns. (I prefer the more-comfortable KM94 masks, as discussed here.) These masks are supposedly about as effective as the more-rigid N95 masks that are the U.S. standard.

Air Filters in Your Furnace

See here for some general tips on dealing with smoke in the home, e.g. damp-mop non carpet floors rather than vacuuming, to avoid shooting settled particles into the air. However, what is really needed is some means to filter the smoke out of the air in your home, otherwise over time the air inside may be as polluted as the air outside. All furnace/central air conditioning systems have a filter in the circuit. A simple solution would be to use an air filter which can catch the smoke particles. The problem here is that the better the filter is at catching small particles, the more restrictive of air flow it is.

Most air filters are rated according to MERV values. MERV 13 filters can remove most smoke particles in a single pass. Unfortunately, most home heating/cooling systems cannot handle that much restriction in air flow; the fan motor would get overloaded and perhaps burn out. One solution here is to install a parallel air filter, with its own booster fan, using a MERV 13 filter. Here, only part of the home air circulation goes through the MERV 13 filter on each pass, but with time most of the home air gets cleaned.

Another approach is to install a MERV 11 or (if your furnace is newer) MERV 12 filter in the furnace. A MERV 11 filter might only capture around 25% of smoke particles per pass, but in the course of a day your whole house air volume should pass through the filter several times. If you have a common size air filter, you can probably get a MERV 11 that would fit on Amazon or at a local big box store. For uncommon sizes, try here.

Make Your Own High-Capacity Filter Box

In addition to working with your furnace/air conditioning filter, you can buy a compact stand-alone air purifier for your home. This Shark HP202 model will provide a continuous read-out of air quality.

For even more air-cleaning muscle, you can make a box-style air purifier by duct-taping together four MERV 13 furnace air filters (four sides of a cube), and adding a box fan on top. Instructions (including YouTube links) for doing this are here, with further details here. These diagrams give the general picture:

An example of a finished product is below; note the red tape covering the outer part of the fan outlet. Blocking that outer area, giving a smaller diameter opening for the air to blow out, increases the net air flow significantly. (It prevents back-eddies of air around the edges).

It turns out that the air flow through one of these home-made air filters is so high that, even though the per-pass capture efficiency is lower than a HEPA filter, the home-made filter box can remove more particulates from a room than a store-bought HEPA filter.

I have made two of these filter boxes so far, using premium and regular filters. They have worked quite well in clearing the smoke from our rooms: the benefit is well worth the cost of parts and labor. See here for more on my experiences and construction tips.

Some on-line resources:

Accuweather seems to have straightforward reporting of air quality, including specifically the less than 2.5 micron particles. (Search on your location, then find Air Quality and click Details).

NOAA provides a real time satellite map of smoke patterns (click on “Surface Smoke”), but don’t rely on their color coding to decide whether your local condition is orange or red.

This web site from Natural Resources Canada shows locations of current wildfires in Canada. See Overlays for the meaning of the symbols; red denotes fires that are out of control. You can click Fire Perimeter Estimate to see the enormous extents of some of these fires.

A few weeks ago, my friend James Dean (see his website here, he will soon be a job market candidate and James is good) and I received news that the Journal of Institutional Economics had accepted our paper tying economic freedom to income mobility. I think its worth spending a few lines explaining that paper.

In the last two decades, there has been a flurry of papers testing the relationship between economic freedom (i.e. property rights, regulation, free trade, government size, monetary stability) and income inequality. The results are mixed. Some papers find that economic freedom reduces inequality. Some find that it reduces it up to a point (the relationship is not linear but quadratic). Some find that there are reverse causality problems (places that are unequal are less economically free but that economic freedom does not cause inequality). Making heads or tails of this is further complicated by the fact that some studies look at cross-country evidence whereas others use sub-national (e.g. US states, Canadian provinces, Indian states, Mexican states) evidence.

But probably the thing that causes the most confusion in attempts to measure inequality and economic freedom is the reason why inequality is picked as the variable of interest. Inequality is often (but not always) used as a proxy for social mobility. If inequality rises, it is argued, the rich are enjoying greater gains than the poor. Sometimes, researchers will try to track the income growth of the different income deciles to go at this differently. The idea, in all cases, is to see whether economic freedom helps the poor more than the rich. The reason why this is a problem is that inequality measures suffer from well-known composition biases (some people enter the dataset and some people leave). If the biases are non-constant (they drift), you can make incorrect inferences.

Consider the following example: a population of 10 people with incomes ranging from 100$ to 1000$ (going up in increments of 100$). Now, imagine that each of these 10 people enjoy a 10% increase in income but that a person with an income of 20$ migrates to (i.e. enters) that society (and that he earned 10$ in his previous group). The result will be that this population of now 11 people will be more unequal. However, there is no change in inequality for the original 10 people. The entry of the 11th person causes a composition bias and gives us the impression of rising inequality (which is then made synonymous with falling income mobility — the rich get more of the gains). Composition biases are the biggest problem.

Yet, they are easy to circumvent and that is what James Dean and I did. We used data from the Longitudinal Administrative Database (LAD) in Canada which produces measures of income mobility for a panel of people. This means that the same people are tracked over time (a five-year period). This totally eliminates the composition bias and we can assess how people within that panel evolve over time. This includes the evolution of income and relative income status (which decile of overall Canadian society they were in).

Using the evolution of income and relative income status by province and income decile, we tested whether economic freedom allowed the poor to gain more than the rich from high levels of economic freedom. The dataset was essentially the level of economic freedom in each five-year window matching the LAD panels for income mobility. The period covered is 1982-87 to 2013-18.

What we found is in the table below which illustrates only our results for the bottom 10% of the population. What we find is that economic freedom in each province heavily affects income mobility.

More importantly, the results we find for the bottom decile are greater than the results “on average” (for all the panel) or than for the top deciles. In other words, economic freedom matters more for the poor than the rich. I hope you will this summary here to be enticing enough to consult the paper or the public policy summary we did for the Montreal Economic Institute (here)