by George Taniwaki

In a Dec 2011 blog post, I critiqued an article in The Fiscal Times that compared the cost of eating a meal at home against dining out at a restaurant. The article purported to show that eating at a restaurant was cheaper. I pointed out the errors in the analysis.

One of the errors was in the way data for expenditures for grocers and restaurants were shown in a line graph. The two lines were at different scales and aligned to different baselines making comparisons difficult. The original and corrected charts are shown below. Correcting the baseline makes it clear that restaurant expenditures are significantly lower than for groceries. Correcting the scale shows that restaurant expenditures are not significantly more volatile than for groceries.


Figures 1a and 1b. Original chart (left) and corrected version (right)

Another error in the article I pointed out was that the lower inflation rate of meals at restaurants compared to meals at home should not favor eating more meals at restaurants. I didn’t give an explanation why. I will do so here.

Consider an office worker who needs to decide today whether to make a sandwich for lunch or to buy a hamburger at a restaurant. Let’s say she knows that the price of bread and lunch meat has doubled over the past year (100% inflation rate) while the cost of a hamburger has not changed (0% inflation rate). Which should she buy?

The answer is, she doesn’t have enough information to decide. The inflation rate over the past year is irrelevant to her decision today, or at least it should be. What is relevant is the actual costs and utilities today.

Let’s say she likes shopping, making sandwiches, and cleaning up, so the opportunity cost for the sandwich option is zero. Let’s also say she likes sandwiches and hamburgers equally and values them equally and doesn’t value variety. Now, if the price today for lunch meat and bread for a single sandwich is 50 cents while a hamburger is 75 cents, then she should make a sandwich. Next year if inflation continues as before, making a sandwich will cost $1.00 while a hamburger remains 75 cents. In that case, she should buy a hamburger. But that decision is in the future.

Let’s consider an extreme case where inflation rates may affect purchase decisions today. What if the price of sandwich fixings are 50 cents today but inflation is expected to be 100% during the work week (so prices will be $.57, $.66, $.76, and $.87 over the next four days) . Such high inflation rates are called hyperinflation and can lead to severe economic distortions.

Let’s also assume hamburgers are 75 cents today and will remain fixed at that price by law. (Arbitrary but stringent price controls are another common feature of an economy experiencing hyperinflation.) Further, let’s assume that sandwich fixings can be stored in the refrigerator for a week for future use but hamburgers cannot be bought and stored for future consumption.

Finally, let’s assume it is early Monday and our office worker has no sandwich fixings or hamburgers but has $5 available for lunches for the upcoming week. What should she buy each day?

I would recommend trying to buy $3.75 in sandwich fixings today (enough for 5 sandwiches). Here’s why. During a period of hyperinflation, you want to get rid of money as fast as possible because cash loses its value every day you hold it. Thus, buying as much food as possible today is a good investment (called a price hedge).

Ah, you say. Why not make sandwiches the first two days of the week and then switch to the relatively cheaper hamburgers for the last three days? That is unlikely to work because the restaurant is caught between paying rising prices for the food it buys while getting a fixed price for what it sells. Long lines will form as customers seek cheap food. The restaurant will either run out of food, go bankrupt, or close its doors. Regardless, our office worker shouldn’t rely on her ability to buy cheap hamburgers later in the week.

So why am I updating a blog post from almost two years ago? Well, it’s because I noticed a big spike in traffic  landing on it last week. It turns out my wife, Susan Wolcott, assigned it as a reading for a class she is teaching to undergraduate business students at Aalto University School of Business, in Mikkeli, Finland. (The school was formerly known as the Helsinki School of Economics.)

Normally, this blog receives about 30 page views a day. On days that I post an entry on kidney disease or organ donation (pet topics of mine) traffic goes up. Of a typical day’s 30 hits, I presume about half of that traffic is not human. It is from web crawlers looking for sites to send spam to (I receive about 15 spam comments a day on this blog).

But check out the big spike in page views for my blog on the day my wife assigned the reading. This blog received 264 page views from 91 unique visitors. That’s the kind of traffic social media experts die for. Maybe I’ve hit upon an idea for generating lots of traffic to a website, convince college professors to assign it as required reading for a class.


Figure 2. Web traffic statistics for this blog

Naturally, I expect another big spike of traffic again today when my wife tells her students about this new blog post.