Category: financial crisis

Can Montana Escape Recession Ravages?

The answer is evidently now “no”, but until recently the UofM’s Bureau of Business and Economic Research director Patrick Barkey thought so:

“As early as last summer we still thought Montana would escape this recession,” he said. “We knew the national economic climate was uncertain, but Montana had been doing pretty well in the previous two recessions. We now know this is a global recession, and it is a more severe recession, and it’s a recession that’s not going to leave Montana unscathed.”

Indeed, things aren’t as bad here as they are in a lot of other places – yet. Compare our housing prices to Florida’s:

MT vs FL house price indexes

On the other hand, our overall economic situation shows a bigger hit than some places with hard-hit housing markets. Here’s the Fed’s coincident index vs. California:

MT coincident index of economic activity

As one would expect, the construction and resource sectors are particularly hard hit by the double-whammy of housing bubble and commodity price collapse. In spite of home prices that seem to have held steady so far, new home construction has fallen dramatically:

MT housing

Interestingly, that hasn’t hit construction employment as hard as one would expect. Mining and resources employment has taken a similar hit, though you can hardly see it here because the industry is comparatively small (so why is its influence on MT politics comparatively large?).

MT construction & mining employment

So, where’s the bottom? For metro home prices nationwide, futures markets think it’s 10 to 20% below today, some time around the end of 2010. If the recession turns into a depression, that’s probably too rosy, and it’s hard to see how Montana could escape the contagion. But the impact will certainly vary regionally. The answer for Montana likely depends a lot on two factors: how bubbly was our housing market, and how recession-resistant is our mix of economic activity?

On the first point, here’s the Montana housing market (black diamonds), compared to the other 49 states and DC:

State home price index vs 2000

Prices above are normalized to 2000 levels, using the OFHEO index of conforming loan sales (which is not entirely representative – read on). At the end of 2003, Montana ranked 20th in appreciation from 2000. At the end of 2008, MT was 8th. Does the rise mean that we’re holding strong on fundamentals while others collapse? Or just that we’re a bunch of hicks, last to hear that the party’s over? Hard to say.

It’s perhaps a little easier to separate fundamentals from enthusiasm by looking at prices in absolute terms. Here, I’ve used the Census Bureau’s 2000 median home prices to translate the OFHEO index into $ terms:

State median home prices

Among its western region peers, a few other large states, and random states I like, Montana starts to look like a relative bargain still. The real question then is whether demographic trends (latte cowboys like me moving in) can buoy the market against an outgoing tide. I suspect that we’ll fare reasonably well in the long run, but suffer a significant undershoot in the near term.

The OFHEO indices above are a little puzzling, in that so many states seem to be just now, or not yet, peaking. For comparison, here are the 20 metro areas in the CSI index (lines), together with Gallatin County’s median prices (bars):

Gallatin County & CSI metro home prices

These more representative indices still show Montana holding up comparatively well, but with Gallatin County peaking in 2006. I suspect that the OFHEO index is a biased picture of the wider market, due to its exclusion of nonconforming loans, and that this is a truer picture.

Real Estate Roundup

Ira Artman takes a look at residential real estate price indices – S&P/Case-Shiller (CSI), OFHEO, and RPX. The RPX comes out on top, for (marginally) better correlation with foreclosures and, more importantly, a much shorter reporting lag than CSI. This is a cause for minor rejoicing, as we at Ventana helped create the RPX and are affiliated with Radar Logic. Perhaps more importantly, rumor has it that there’s more trading volume on RPX.

In spite of the lag it introduces, the CSI repeat sales regression is apparently sexy to economists. Calculated Risk has been using it to follow developments in prices and price/rent ratios. Econbrowser today looks at the market bottom, as predicted by CSI forward contracts on CME. You can find similar forward curves in Radar’s monthly analysis. As of today, both RPX and CSI futures put the bottom of the market in Nov/Dec 2010, another 15% below current prices. Interestingly, the RPX forward curve looks a little more pessimistic than CSI – an arbitrage opportunity, if you can find the liquidity.

Artman notes that somehow the Fed, in its flow of funds reporting, missed most of the housing decline until after the election.

Random Excellence – Bailouts, Biases, Boxplots

(A good title, stolen from TOP, and repurposed a bit).

1. A nice graphical depiction of the stimulus package, at the Washington post

2. An interesting JDM article on the independence of cognitive ability and biases, via Marginal Revolution. Abstract:

In 7 different studies, the authors observed that a large number of thinking biases are uncorrelated with cognitive ability. These thinking biases include some of the most classic and well-studied biases in the heuristics and biases literature, including the conjunction effect, framing effects, anchoring effects, outcome bias, base-rate neglect, ‘less is more’ effects, affect biases, omission bias, myside bias, sunk-cost effect, and certainty effects that violate the axioms of expected utility theory. In a further experiment, the authors nonetheless showed that cognitive ability does correlate with the tendency to avoid some rational thinking biases, specifically the tendency to display denominator neglect, probability matching rather than maximizing, belief bias, and matching bias on the 4-card selection task. The authors present a framework for predicting when cognitive ability will and will not correlate with a rational thinking tendency.

The framework alluded to in that last sentence is worth a look. Basically, the explanation hinges on whether subjects have “mindware” available, time resources, and reflexes to trigger an (unbiased) analytical solution when a (biased) heuristic response is unwarranted. This seems to be applicable to dynamic decision making tasks as well: people use heuristics (like pattern matching), because they don’t have the requisite mindware (understanding of dynamics) or triggers (recognition that dynamics matter).

3. A nice monograph on the construction of statistical graphics, via Statisitical Modeling, Causal Inference, and Social Science Update: Bill Harris likes this one too.

I'm Shovel Ready

Lots of carping on the ‘net about the likely slow pace of stimulus spending. Nevermind the pace, I want to know what’s in it. You actually have to dig quite a bit to get the details of the package (especially with the CBO web site down today). Fortunately, I always keep my shovel handy. Here’s what I see:

9702bc96-e756-11dd-adce-000255111976 Blog_this_caption(Click through to the live version to see the labels)

A few observations:

  • There’s $90 billion in unstated spending.
  • Infrastructure grabs the headlines, but education and health actually get the lion’s share.
  • The “green” portion of the stimulus looks rather small in context. It also seems out of balance – more $ for energy supply than energy efficiency. I’m not convinced that energy supply subsidies are very green.
  • The distribution of half the tax credits is unstated. How do you know the magnitude without knowing the components? Could it be that business tax credits constitute the majority? If so, that would be highly regressive.

Where’s the consulting sector in all this?

Are We Slaves to Open Loop Theories?

The ongoing bailout/stimulus debate is decidedly Keynesian. Yet Keynes was a halfhearted Keynesian:

US Keynesianism, however, came to mean something different. It was applied to a fiscal revolution, licensing deficit finance to pull the economy out of depression. From the US budget of 1938, this challenged the idea of always balancing the budget, by stressing the need to boost effective demand by stimulating consumption.

None of this was close to what Keynes had said in his General Theory. His emphasis was on investment as the motor of the economy; but influential US Keynesians airily dismissed this as a peculiarity of Keynes. Likewise, his efforts to separate capital projects from ordinary budgets, balanced if possible, found few echoes in Washington, despite frequent mention of his name.

Should this surprise us? It does not appear to have disconcerted Keynes. ‘Practical men were often the slaves of some defunct economist,’ he wrote. By the end of the second world war, Lord Keynes of Tilton was no mere academic scribbler but a policymaker, in a debate dominated by second-hand versions of ideas he had put into circulation in a previous life. He was enough of a pragmatist, and opportunist, not to quibble. After dining with a group of Keynesian economists in Washington, in 1944, Keynes commented: ‘I was the only non-Keynesian there.’

FT.com, In the long run we are all dependent on Keynes

This got me wondering about the theoretical underpinnings of the stimulus prescription. Economists are talking in the language of the IS/LM model, marginal propensity to consume, multipliers for taxes vs. spending, and so forth. But these are all equilibrium shorthand for dynamic concepts. Surely the talk is founded on dynamic models that close loops between money, expectations and the real economy, and contain an operational representation of money creation and lending?

The trouble is, after a bit of sniffing around, I’m not seeing those models. On the jacket of Dynamic Macroeconomics, James Tobin wrote in 1997:

“Macrodynamics is a venerable and important tradition, which fifty or sixty years ago engaged the best minds of the economics profession: among them Frisch, Tinbergan, Harrod, Hicks, Samuelson, Goodwin. Recently it has been in danger of being swallowed up by rational expectations, moving equilibrium, and dynamic optimization. We can be grateful to the authors of this book for keeping alive the older tradition, while modernizing it in the light of recent developments in techniques of dynamic modeling.”
’”James Tobin, Sterling Professor of Economics Emeritus, Yale University

Is dynamic macroeconomics still moribund, supplanted by CGE models (irrelevant to the problem at hand) and black box econometric methods? Someone please point me to the stochastic behavioral disequilibrium nonlinear dynamic macroeconomics literature I’ve missed, so I can sleep tonight knowing that policy is informed by something more than comparative statics.

In the meantime, the most relevant models I’m aware of are in system dynamics, not economics. An interesting option (which you can read and run) is Nathan Forrester’s thesis, A Dynamic Synthesis of Basic Macroeconomic Theory (1982).

Forrester’s model combines Samuelson’s multiplier accelerator, Metzler’s inventory-adjustment model, Hicks’ IS/LM, and the aggregate-supply/aggregate-demand model into a 10th order continuous dynamic model. The model generates an endogenous business cycle (4-year period) as well as a longer (24-year) cycle. The business cycle arises from inventory and employment adjustment, while the long cycle involves multiplier-accelerator and capital stock adjustment mechanisms, involving final demand. Forrester used the model to test a variety of countercyclic economic policies, commonly recommended as antidotes for business cycle swings:

Results of the policy tests explain the apparent discrepancy between policy conclusions based on static and dynamic models. The static results are confirmed by the fact that countercyclic demand-management policies do stabilize the demand-driven [long] cycle. The dynamic results are confirmed by the fact that the same countercyclic policies destabilize the business cycle. (pg. 9)

It’s not clear to me what exactly this kind of counterintuitive behavior might imply for our current situation, but it seems like a bad time to inadvertently destabilize the business cycle through misapplication of simpler models.

It’s unclear to what extent the model applies to our current situation, because it doesn’t include budget constraints for agents, and thus doesn’t include explicit money and debt stocks. While there are reasonable justifications for omitting those features for “normal” conditions, I suspect that since the origin of our current troubles is a debt binge, those justifications don’t apply where we are now in the economy’s state space. If so, then the equilibrium conclusions of the IS/LM model and other simple constructs are even more likely to be wrong.

I presume that the feedback structure needed to get your arms around the problem properly is in Jay Forrester’s System Dynamics National Model, but unfortunately it’s not available for experimentation.

John Sterman’s model of The Energy Transition and the Economy (1981) does have money stocks and debt for households and other sectors. It doesn’t have an operational representation of bank reserves, and it monetizes the deficit, but if one were to repurpose the model a bit (by eliminating the depletion issue, among other things) it might provide an interesting compromise between the two Forrester models above.

I still have a hard time believing that macroeconomics hasn’t trodden some of this fertile ground since the 80s, so I hope someone can comment with a more informed perspective. However, until someone disabuses me of the notion, I have the gnawing suspicion that the models are broken and we’re flying blind. Sure hope there aren’t any mountains in this fog.

What would Jesus bail out?

Shop More

Via Economist’s View, Kotlikoff and Leamer suggest in the FT Economists’ Forum that we need a national holiday sale to fix the economy:

The same defensive mentality that allowed the sale of equities at fire sale prices threatens to cause a sharp drop in consumer spending, which accounts for 72 per cent of US GDP. If this happens, the economy will slide into deep recession.

We need to put a halt to self-fulfilling prophecies of doom. The key is realising that recessions are usually consumer cycles, not business cycles. They’re driven by weakening demand first for homes, then for consumer durables, and finally for non-durables and services. As consumers stop spending, businesses stop investing, and the economy ‘recedes’.A better way to spur consumer spending is for Uncle Sam to run a six-month national sale by having a) state governments suspend their sales taxes and b) the federal government make up the lost state sales revenues. The national sale could be implemented immediately.
…
Here’s how it would work. Uncle Sam would pay each state a fixed percentage ’“ say 5 per cent – of the 2007 consumption of its residents. States would be required to reduce their retail sales tax rates by enough to generate a six-month revenue loss (calculated using 2007 data) equal to the amount they’ll receive from Uncle Sam.

For states with low or zero sales tax rates, implementing this policy requires making their sales tax rates negative, ie subsidising purchases. Shoppers would see a negative tax on their sales receipts, lowering their outlays. State governments would reimburse businesses for paying the subsidy and, in turn, be reimbursed by the Feds.

But wait, wouldn’t that accelerate the Shopocalypse?

Update: More seriously, isn’t this a terrible policy from an income distribution standpoint? It gives vastly different rewards to citizens with different consumption patterns. And how will states that don’t have a sales tax implement a negative one, without the reporting infrastructure to do so?

Policy Resistance in Emerging Markets

A great example of policy undone by feedback, from Paul Krugman’s column, The Widening Gyre:

The really shocking thing, however, is the way the crisis is spreading to emerging markets ’” countries like Russia, Korea and Brazil.

These countries were at the core of the last global financial crisis, in the late 1990s (which seemed like a big deal at the time, but was a day at the beach compared with what we’re going through now). They responded to that experience by building up huge war chests of dollars and euros, which were supposed to protect them in the event of any future emergency. And not long ago everyone was talking about ‘decoupling,’ the supposed ability of emerging market economies to keep growing even if the United States fell into recession. ‘Decoupling is no myth,’ The Economist assured its readers back in March. ‘Indeed, it may yet save the world economy.’

That was then. Now the emerging markets are in big trouble. In fact, says Stephen Jen, the chief currency economist at Morgan Stanley, the ‘hard landing’ in emerging markets may become the ‘second epicenter’ of the global crisis. (U.S. financial markets were the first.)

What happened? In the 1990s, emerging market governments were vulnerable because they had made a habit of borrowing abroad; when the inflow of dollars dried up, they were pushed to the brink. Since then they have been careful to borrow mainly in domestic markets, while building up lots of dollar reserves. But all their caution was undone by the private sector’s obliviousness to risk.

In Russia, for example, banks and corporations rushed to borrow abroad, because dollar interest rates were lower than ruble rates. So while the Russian government was accumulating an impressive hoard of foreign exchange, Russian corporations and banks were running up equally impressive foreign debts. Now their credit lines have been cut off, and they’re in desperate straits.

The unstated closure to the loop is that emerging market governments’ borrowing in domestic markets and hoarding of foreign exchange were likely a cause of higher domestic rate spreads over dollar rates, and thus contributed to the undoing of the policy by driving other borrowing abroad.