Moody's Negative Outlook on U.S. Local Government Debt

A few days ago, Moody's Investors Service announced that its outlook for the entire U.S. local government tax-backed and related ratings sector is negative. This is newsworthy not only for municipal bond investors but also for anyone following the U.S. recession. It marks the first time that Moody's issued an outlook on this entire sector, although it has issued ratings on the sector since 1914.

Moody's Investors Service is one of the leading issuers of credit ratings. Investors use these ratings to gauge the risks of investing in debt assets. So, one might conclude that the analysts at Moody's are remarkably pessimistic about the impact that recessionary economic conditions will have on the ability of local governments in the U.S. to meet their debt obligations. This means that the risk of defaults on these debts has risen.

However, Moody's hedged its announcement by mentioning that credit pressures will vary significantly across locales due to differences in economic conditions, property assessment methods, and authority to raise revenue. The varying economic conditions can largely be explained by localities' exposure to industries hit particularly hard by the recession. These include real estate development, auto manufacturing, financial services, tourism, gaming, and general manufacturing. Differences in property tax systems will play a major role. Moody's report shows evidence that about 72% of local government tax revenue comes from property taxes. The bursting of the housing market bubble will bring declines in property tax revenue for most local governments because of falling home values.

Several of these governments might have the authority to increase property, sales, or income tax rates to raise revenue. Whether the elected officials running these localities are willing to do this is an open question. Moody's points out that taxpayers are worried about their own financial conditions and are highly resistant to increases in local taxes. Raising taxes in this environment will be unusually difficult for locally elected officials.

Cutting spending during the economic crisis will not be an attractive option either. In part, this is because many of these governments may face service mandates that prevent them from reducing service-related expenditures. An example of a service mandate is that a state government may mandate that local governments provide health services for the poor. Moody's analysts also reported that the demand for improved government services will make it that much more difficult for these governments to sustain healthy finances. Local officials may find that it is more palatable to default on their bonds rather than raise taxes or cut spending.

The credit crunch is also having a direct impact on local government finance. Moody's report states that access to credit will be more expensive for these governments than it had been in recent years. Moody's negative outlook announcement surely caused investors to demand greater yields on the municipal bonds trading in the credit markets. The company also warned that some localities are in such dire straits that they may be completely shut out of the credit markets.

Yet, the situation ought to be tenable for numerous governments. For instance, some well-managed localities increased their reserves during the boom years and were prudent with the funds generated during the real estate bubble. A simple example from portfolio theory can help show why investors may still be willing to buy the bonds of a cross-section of municipalities.

Suppose that a bond investor purchases three one-year bonds with different expected returns and probabilities of default. For simplicity, we'll assume that the investor is risk-neutral and the bonds pay nothing in the event of default. Bond A has a 25% probability of default this year but pays a coupon of 15% if it avoids default. Bond B has a 50% probability of default this year but pays a coupon of 20% if it avoids default. Bond C has a 75% probability of default this year but pays a coupon of 30% if it avoids default. Let's also assume that all the bonds have a face value of $100 each.

What is the investor's expected payoff from investing in this portfolio? It is


(0.75 × $115) + (0.5 × $120) + (0.25 × $130) =

$86.25 + $60 + $32.50 = $178.75


So, on average, an investor would be willing to pay less than 60% of face value on these bonds to make a positive expected return.

This example was purposefully simple, but from it you can see the advantage of diversification and the problem of gauging risk. If the probabilities of default end up being higher than estimated, the investor might lose money but will only lose all his money in the rare case that all bond issuers default. Yet, if the probabilities of default are lower than estimated, the investor might earn a high rate of return.

Discussion Questions

1. How does the bond portfolio example relate to the impact that mortgage-backed securities had on financial institutions? What must have happened to their default rates for them to become known as "toxic assets"?

2. If you had a large sum of money that you had to use for investment purposes, would you put together a portfolio of U.S. local government debt? If yes, why? If not, explain what your preferred investment would be.

3. Besides an economic recovery, what changes, if any, do you think are needed for local governments to avoid defaults in the future? How feasible are your proposed changes?

Selling Palin Short

"I don't worry about the polls. Polls are just a fancy way of systematically predicting what's going to happen."

Thus spoke Tina Fey-as-Sarah Palin on Saturday Night Live. It made for a good line—but are polls really that systematic? Just how well do polls do at predicting the outcome of an election? How can you take the results of multiple polls and paint a convincing picture out of them? Finally, what other mechanisms are there for predicting the outcomes of elections?



There are a number of sites devoted to analyzing the myriad of polls that come out every day as the election nears. Two good sites that take very different approaches are RealClearPolitics.com and FiveThirtyEight.com. To compare and contrast their analyses, let's take a look at Pennsylvania, which many analysts deem a pivotal state in this election. Here's a list of Pennsylvania polls taken during October:

Poll	Date	Size	Obama	McCain
West Chester U.	10/5	504	52.3	42
Strategic Vision	10/6	1,200	54	40
Rasmussen	10/6	700	54	41
SurveyUSA	10/6	653	55	40
Marist	10/7	757	53	41
Zogby Interactive	10/11	737	51.6	40.2
SurveyUSA	10/12	516	55	40
Susquehanna	10/18	700	48	40
Morning Call	10/19	594	52	41

These polls all varied in their methodology—whom they polled, how they did it (robocall or a human being making a phone call), and how they weighted the results.

RealClearPolitics.com chooses to average the polls it judges are the best reflection of public opinion. Recently, it listed only the last three polls and averaged them together to predict Obama with 51.7% and McCain with 40.3%. (Note that these don't add up to 100% because of undecided voters.)

FiveThirtyEight.com takes a much more sophisticated approach. It adjusts for trends within Pennsylvania, across the nation, and among demographic groups. Instead of just choosing a few polls, it weights them according to methodology and how out-of-date they are. Then it reports three numbers: the raw weighted average of polls, the trend-adjusted average, and the results of a regression analysis that takes into account demographic and other factors. It also makes a prediction of Election Day based on the likely last-minute decisions of undecided voters. Finally, with all of that analysis in mind, the site makes a prediction as to the likelihood that each candidate will win Pennsylvania on Election Day:

	Obama	McCain
Polling Average	50.8	41.8
Trend-Adjusted	52.3	41.0
538 Regression	52.1	40.7
Projection	54.1	44.4
Win %	98%	2%

So far we've looked only at sites which analyze polls. But there's another kind of site devoted to predicting the elections: prediction markets. The thinking behind prediction markets is that, just as prices aggregate private information about buyers' values and sellers' costs in a market for goods and services, a market for future events can aggregate private information about the likelihood of those events happening. Two well-known political futures markets are intrade.com and the Iowa Electronic Markets.

Take a look at the intrade.com page on Pennsylvania. There you can see the probability the market places on Obama winning the state—as I write this, it's about 85%. It's not quite a bet, it's more like a stock price. This is how it works: there's an option that pays $10 if Obama wins Pennsylvania, and $0 if he doesn't. The price of that option is currently about $8.50. In other words, people are willing to pay $8.50 for a piece of paper that pays $10 if Obama wins the state; therefore, we can interpret this to mean that the "market thinks" there's an 85% chance Obama will win Pennsylvania's 21 electoral votes.

Discussion Questions

1. Suppose you wanted to predict the probability that Obama will win Pennsylvania. How would you go about doing it?
2. We saw above that FiveThirtyEight.com assigns a 98% probability to Obama winning Pennsylvania, while the Intrade price assigns an 85% probability. Why the difference? Under what conditions would a prediction market be a better predictor of an outcome than a poll? Under what conditions would the reverse be true?
3. Not all prediction markets have the same price for each contract, despite the fact that arbitrage opportunities abound. Why might this be the case? (For those interested, Nate Silver at FiveThirtyEight.com has an interesting analysis of this phenomenon here.)
4. There are some nonzero prices on intrade for very unlikely events. For example, you might notice that there's an intrade bet on whether Sarah Palin would drop out as the Republican nominee for Vice President, and another market on whether Al Gore will be on the ticket on November 4. Why do these contracts exist? Why do you think they have positive prices?

Sacking Mugabe

The path to growth remains elusive for many of the world's economies. Prescribing effective growth policies is exceedingly difficult. The unique features in each of the world's economies defy formulaic approaches to growth—it's not necessarily clear that Japan's path will work for Cambodia. Economic history offers a bit more clarity when it comes to what won't work. Of the more recent episodes of economic collapse, Zimbabwe's is perhaps the starkest. The Mugabe regime's mismanagement of the Zimbabwean economy reads like a step-by-step guide to economic ruin.

In 2000, Zimbabwe's autocratic ruler, Robert Mugabe, implemented a clumsy and often violent land redistribution program. Mugabe forcefully seized white-owned farmland and gave it to black farmers unfamiliar with commercial farming practices. The absence of any cooperative knowledge transfer between white and black farmers led to a precipitous fall in agricultural output. The failure of the agricultural sector caused a severe contraction in overall economic output, creating massive unemployment. The collapsing economy sapped Mugabe's regime of the tax revenues necessary to pay soldiers and finance government outlays. An autocrat's reign is only as secure as his army is brutal—hungry, underpaid soldiers aren't much for intimidating political opponents or scaring the populace into submission. To maintain his government's outlays, Mugabe turned to borrowing. Of course, the loans would eventually need to be repaid. Lacking the tax base to repay the loans, the government resorted to the capstone of many economic disasters: printing money.

The results were predictable: hyperinflation reached roughly 4 million percent per year as of June 2008. At these levels of inflation, even the most mundane daily transactions involve considerable uncertainty and frustration. Mugabe's response to the hyperinflation that he himself initiated could not have been worse. The government imposed price ceilings, threatening to jail shop owners if they charged more than the official price. The price ceilings led to massive shortages of necessities like bread and milk. Many firms shut down production, escalating an already high unemployment rate.

You don't have to be an economist to recognize the first step to improving Zimbabwe’s economy: get rid of Mugabe. But removing Mugabe from power is easier said than done. Opposition presidential candidate Morgan Tsvangirai gave it an impressive go during this year's elections, but widespread violence against opposition supporters caused Tsvangirai to withdraw from the presidential run-off. At this point, Mugabe remains president.

Discussion Questions

1. Mugabe is 84 years old—why doesn't he just step down? Charlayne Hunter-Gault's article in The Root suggests that Mugabe has strong incentives to maintain his grip on power given the fate of other overthrown tyrants. Hunter-Gault raises an interesting dilemma for freedom-lovers all over the world: we want to get rid of brutal dictators, but the dictators may do everything they can to retain power precisely because they fear what we'll do to them once they're out of office. Should we offer Mugabe amnesty just to get him to step down?

2. In a recent Wall Street Journal editorial, former World Bank president and U.S. Deputy Secretary of Defense Paul Wolfowitz suggests a way to pressure Mugabe out of office. Wolfowitz calls on the international community to very publicly declare promises of aid and debt relief for Zimbabwe under the condition that Mugabe is removed from office. Do you think this strategy would succeed?

3. Mugabe's land redistribution program was catastrophic for Zimbabwe's economy, but as this NPR story points out, several neighboring countries attempted to benefit from the displacement of white farmers in Zimbabwe. How could the Zimbabwean government have balanced the goals of efficiency of the farming sector and equity for the black population that suffered a history of oppression by a ruling white minority?

The Millionaires’ Amendment and the Law of Unintended Consequences

Even more than the law of supply, the law of demand, or the law of diminishing marginal utility, economists love the law of unintended consequences. A brief editorial in the New York Times provides a nice illustration of that law.

One of the McCain-Feingold campaign finance reform laws was an exception to campaign finance limits for the case in which a rich candidate contributes a large amount to his or her own campaign. The idea is simple: campaign finance laws generally govern how candidates for office can raise money from others, but don’t restrict how much money they themselves can spend on their own candidacy. Therefore, if one candidate is of modest means while another is rich, campaign finance laws that make it harder for the poorer candidate to raise money implicitly help the richer candidate.

To solve this problem, McCain-Feingold lifted campaign contribution limits for candidates facing a challenger who spent more than $350,000 of his or her own money on the campaign. This provision of the law is now being challenged as unconstitutional by Jack Davis, a millionaire who ran unsuccessfully for Congress in 2006. Davis claims that the effect of the law is to deter rich people from public service.

The Times editorial makes the following rebuttal:

There is also no sign that the amendment is discouraging the wealthy from running or spending. The very rich are represented in Congress in large numbers. Contrary to Mr. Davis’s claims of “chilling,” the number of candidates who spent more than $1 million of their own money actually increased after the amendment took effect. It is now common for party recruiters to seek out “self-financing”—or wealthy—candidates.

Consider the structure of the two arguments here. Davis argues a theoretical point: that allowing opponents of rich candidates to raise more money will have a “chilling” effect on millionaires running for office. The Times seeks to refute that point with empirical evidence: that the number of wealthy candidates has increased since the amendment was passed.

Now, a fun part of thinking like an economist is being able to parse arguments like this. Here are some questions that get you started.

1. Is Davis’s argument internally consistent? That is, holding all else constant, would you expect this amendment to have a “chilling” effect on millionaire candidates?

2. The amendment cited in the article was part of broader legislation limiting campaign fundraising. What effect would this have on the incentives political party recruiters face when choosing to seek out “self-financing” candidates?

3. Does the Times make the most convincing possible case against Davis? How might you argue the point differently? What is the strongest argument you could use to refute the Times’ point?

4. Think about the goals of John McCain and Russ Feingold, the authors of the campaign finance legislation. How do you think they feel about the fact that one effect of their legislation has been an increase in the recruiting of wealthy candidates? Based on that increase, do you think they would want more or fewer provisions like the Millionaires’ Amendment?