A student in my managerial economics course asked me a very interesting question today concerning the U.S. federal government’s “Cash for Clunkers” (also known as “CARS”, which is an acronym for “Car Allowance Rebate System”) program.  Specifically, she was interested in knowing how to assess the social costs and benefits of government programs like CARS from an economics perspective.

Let’s look at CARS and its cousin, the so-called “first-time-home-buyer tax credit” (FTHBTC).  It’s worthwhile reading the October 28 Edmunds.com article about the economics of CARS.  Apparently the net cost to taxpayers of CARS, per marginal sale, was $24,000.  Coincidentally, MIT economist (and former IMF chief economist) Simon Johnson published a Washington Post article about FTHBTC earlier this week which reports a net cost to taxpayers of FTHBTC of between $43,000 to $80,000 per marginal sale.  Thus the net effect of both policies has been to create a rather muted, temporary, and highly inefficient stimulus at a substantial cost to the taxpayer (the same points could be made about any number of other stimulus measures taken this year by the U.S. government, but I digress).  Professor Johnson notes (and I agree) that “Putting cash in pockets does have a stimulative effect because some of that cash will turn into consumption. But as far as stimulus measures go, it has a low multiplier (the ratio of new economic activity to stimulus spending).” 

In the case of CARS, a social cost of $24,000 provides a maximum net private benefit of $4,500 (note that the clunker would have to be literally worthless in order for the net private benefit to be equal to $4,500!), and in the case of FTHBTC, a social cost of $43,000 – $80,000 provides a maximum net private benefit of $8,000 (note that since the FTHBTC is means-tested, the average net benefit must be less than the $8,000 maximum).  In the case of FTHBTC, Professor Johnson asserts (and I agree), that most, if not all of the private benefit (i.e., additional “surplus”) is enjoyed by the seller of the home in the form of a higher price than she would have otherwise received from the buyer in the absence of the FTHBTC.  With the FTHBTC, the buyer will naturally become less reticent about paying top dollar for owner-occupied housing because up to $8,000 of the price is covered by taxpayers (also note that other public policies such as the tax deductibility of mortgage interest and mortgage securitization by the likes of Fannie Mae, Freddie Mac, the FHA, et al. have similar effects with respect to inflating the value of our nation’s housing stock).  For these very same reasons, I also suspect that much of the “surplus” associated with CARS ended up benefitting sellers by making new car buyers less price sensitive than they otherwise would have been.

Finally, bringing this question “closer to home”, I often think about the economic effect of government subsidies on higher education.  To the extent that the government subsidizes tuition (e.g., in the form of scholarships and below-market interest rates on student loans) this also has the effect of increasing the producer surplus enjoyed by universities by making students and their families less sensitive to price.  I am convinced that an important reason why education costs generally and higher education costs specifically have been increasing faster than overall inflation for some time now is due to the role played by government subsidies.  There’s also an obvious cautionary tale in all of this for health care reform, but I’ll leave that to a future discussion.

Last night on the local (Austin, TX) news, there was a segment concerning how the local public transportation agency (AKA “Capital Metro”) apparently is planning to raise fares. The reporter was speculating about how large of an impact Capital Metro’s pricing decision might have upon ridership. 

Earlier this month, I began teaching a managerial economics course in Baylor University’s Executive MBA program in Austin.  Fortuitously, I just covered the topic of the price elasticity of demand this past week.  This concept measures how sensitive product demand is to price changes for a good or service.  Therefore, I think that my MBA students and I are in a much better position than the reporter was to predict what will likely happen.  Since we know that the price elasticity of demand for public transportation is quite low, averaging around -0.3 in the United States, this statistic implies that the proposed fare increase should reduce overall ridership, but not by nearly as much in percentage terms as the increase in the fare itself. Furthermore, since market demand will decrease in response to an increase in fares, so will overall system costs, assuming that Capital Metro managers not only have the good sense to scale back costs in response to a decline in market demand, but also have the flexibility (particularly from a labor contract and labor relations viewpoint) to do so. The “good” news (from a taxpayer viewpoint, anyway) is that the net effect will be that Capital Metro’s “fare recovery ratio”, or FRR (which measures the percentage of the bus route’s cost that is paid by riders rather than taxpayers) should increase. According to a recent Capital Metro report (see http://bit.ly/2bbGi3), its FRR was just 9% in 2007. Out of 32 North American public transportation systems referenced at http://en.wikipedia.org/wiki/Farebox_recovery_ratio, this is by far and away the worst FRR performance; the average FRR for this group is nearly 40%, and the standard deviation is 18%, which implies that Capital Metro is, in every sense of the term, a true “statistical outlier”.