Our book, House of Debt, makes an evidence-based case for what caused the severe Great Recession and what explains the continued economic weakness. The debt-fueled housing boom artificially boosted household spending from 2000 to 2006, and then the collapse in house prices forced a sharp pull-back because indebted households bore the brunt of the shock. The lack of policies targeting this problem exacerbated the effects of the housing crash on consumer spending.

The BEA released state-level personal consumption expenditure data today, and it strongly supports our view. In the charts below, we take the 20% U.S. states that had the largest decline in housing net worth from 2006 to 2009, and we compare [...]]]> Economists of all stripes are baffled by continued economic weakness in the United States. The easiest way to see the weakness is to compare where we are in terms of GDP today relative to historical trend growth, something we did in a previous post. It is clear that one of the main drivers of this weakness is the tepid recovery in consumer spending since the Great Recession. We made note of this fact in another previous post, but we are certainly not alone in noticing this fact.

Our book, House of Debt, makes an evidence-based case for what caused the severe Great Recession and what explains the continued economic weakness. The debt-fueled housing boom artificially boosted household spending from 2000 to 2006, and then the collapse in house prices forced a sharp pull-back because indebted households bore the brunt of the shock. The lack of policies targeting this problem exacerbated the effects of the housing crash on consumer spending.

The BEA released state-level personal consumption expenditure data today, and it strongly supports our view. In the charts below, we take the 20% U.S. states that had the largest decline in housing net worth from 2006 to 2009, and we compare them to the 20% states U.S. states that had the smallest decline over the same time period. The states with the largest decline are: Arizona, California, Florida, Michigan, and Nevada. The states with the smallest decline are: Arkansas, Iowa, Kentucky, Louisiana, Nebraska, North Carolina, North Dakota, Oklahoma, Pennsylvania, South Dakota, and Wyoming. We make sure each group contains 20% of the population,  which is why there are more states in the smallest decline category.

Here is total consumption, indexed to 2006, for the biggest decline and smallest decline states:

The pattern is striking. The collapse in total consumption was much larger in states that were hit hardest by the decline in house prices, something we show in our book. It wasn’t just the fact that house prices collapsed. It was also because these states had the highest debt levels when house prices crashed. It was the combination of the two that decimated household spending in these states. Even in 2012, there continues to be a very large difference in the level of consumption. The very large gap between the blue and red lines shows how long-lasting the effects of the housing crash have been.

Total consumption can be broken down into three categories: durable consumption, non-durable consumption, and services. Here are the graphs of all three:

Across all three categories of consumption, there is a large gap between hard hit states and states that largely avoided the housing collapse. And that gap has persisted all the way through 2012. The gap is smallest for non-durable goods like groceries and clothing. This makes sense because these are necessities–even people who have seen their wealth decimated need to eat. The gap is largest for durable goods, which also makes sense given that the housing market directly fuels purchases of durable goods such as furniture, electronics, and home appliances. The services gap is quite large as well, which is a bit surprising to us. Further, the gap between consumption of services appears to be getting larger even through 2012.

Many have argued that we overstate the importance of housing and household debt in explaining the Great Recession and weak recovery. They point to the banking crisis, policy uncertainty, or excessive regulation as equally or even more important. The data released today by the BEA show pretty clearly that the arguments we make in House of Debt remain relevant for thinking about economic weakness today. In our view, the explanation we provide is the most consistent with the striking difference in consumption across states.

]]> http://houseofdebt.org/2014/08/08/more-evidence-supporting-the-house-of-debt.html/feed 9 http://houseofdebt.org/2014/07/30/gdp-update.html http://houseofdebt.org/2014/07/30/gdp-update.html#comments Wed, 30 Jul 2014 14:44:15 +0000 http://houseofdebt.org/?p=832 A strong 2014Q2 GDP report came out today, registering in at 4% annualized real GDP growth. This is good news, but it is worth looking at it in the context of the full recovery. Much of the recovery data was also revised, so we are updating our chart showing recoveries after every post WWII recession in the United States.

Here it is, including 2014q2:

The uptick at the end of the red line is today’s strong GDP report. But it is useful to put it into the context of the longer recovery, which has been the weakest in history (by far).

Real GDP growth for 2014q1 was revised downward today to -3.0% on an annualized basis. Yes, our reading of Table 1.1.3 of NIPA shows -3.0%, not -2.9%.

Here is real GDP indexed to the quarter before each recession for all 10 recessions since 1950, taking into account this morning’s revision. Notice the significant bend downward in the last quarter for the 2007-2009 recession (solid red line). It makes the recent recovery look even  worse relative to previous recoveries.

Just a terrible recovery. Terrible.

In the chart below, we plot retail spending on appliances, furniture, and home improvement, or “home-related spending” (blue line) and spending on new autos (red line) from 1998 through 2014. We have highlighted the two major subprime lending booms we’ve seen in that period — the subprime mortgage lending boom from 2003 to 2006, and the subprime auto loan boom from 2010 to 2014. In order to be able to include 2014, we focus only on the first four months of each year.

When subprime mortgage lending was booming from 2003 to 2006, so were purchases of home-related goods. As soon as the subprime mortgage lending market crashed, so did home-related spending. In fact, in 2014, home-related spending is still below its 2006 level in nominal terms. It’s a pretty incredible boom and bust.

For auto spending, growth was positive prior to the Great Recession, but unspectacular. But as soon as subprime auto lending heated up in 2011 [...]]]> A concern that we highlighted in yesterday’s post is that the only way the U.S. economy can generate significant consumer spending is through aggressive lending to borrowers with low credit scores. Here is more evidence supporting that view.

In the chart below, we plot retail spending on appliances, furniture, and home improvement, or “home-related spending” (blue line) and spending on new autos (red line) from 1998 through 2014. We have highlighted the two major subprime lending booms we’ve seen in that period — the subprime mortgage lending boom from 2003 to 2006, and the subprime auto loan boom from 2010 to 2014. In order to be able to include 2014, we focus only on the first four months of each year.

When subprime mortgage lending was booming from 2003 to 2006, so were purchases of home-related goods. As soon as the subprime mortgage lending market crashed, so did home-related spending. In fact, in 2014, home-related spending is still below its 2006 level in nominal terms. It’s a pretty incredible boom and bust.

For auto spending, growth was positive prior to the Great Recession, but unspectacular. But as soon as subprime auto lending heated up in 2011 and afterward, so did purchases of new auto vehicles. The growth in new auto sales from 2011 to 2014 has been really impressive. So once again, spending in a particular market is strongest when subprime lending in that market is strongest.

It appears that the key to boosting spending in the U.S. economy is subprime lending. The financial system was lending against homes before the Great Recession, and now it has moved to lending against cars. But the basic message is the same.

First, new auto purchases have been an important driver of household spending for the past two years. The chart below plots year over year spending (in nominal terms) from January to April for 2013 and 2014. The blue bar shows total spending, and the red bar shows spending excluding new auto purchases.

Over the past two years, nominal spending growth has been about 3% on a year-over-year basis. But if we exclude auto sales, the numbers are much worse, especially for 2014. Spending excluding autos in the first four months of 2014 has been less then 1.5% nominal, which implies a decline in real terms. This includes March and April, so it is hard to argue that weather alone explains this weakness.

So purchases of new vehicles have been an important boost to household spending and the overall economy. But what is driving this great performance of auto sales? A clue [...]]]> Census retail sales for May came out today, and they missed the consensus forecast slightly on the downside. But there is another pattern that may be more concerning. Let’s take a closer look at what has been going on with household spending.

First, new auto purchases have been an important driver of household spending for the past two years. The chart below plots year over year spending (in nominal terms) from January to April for 2013 and 2014. The blue bar shows total spending, and the red bar shows spending excluding new auto purchases.

Over the past two years, nominal spending growth has been about 3% on a year-over-year basis. But if we exclude auto sales, the numbers are much worse, especially for 2014. Spending excluding autos in the first four months of 2014 has been less then 1.5% nominal, which implies a decline in real terms. This includes March and April, so it is hard to argue that weather alone explains this weakness.

So purchases of new vehicles have been an important boost to household spending and the overall economy. But what is driving this great performance of auto sales? A clue comes from looking across zip codes that differ in credit scores.

In the chart below, we plot the year-over-year growth in new auto purchases for the lowest and highest credit score zip codes. These are the bottom and top quartile of the overall credit score distribution, where the quartiles are population weighted to ensure we are looking at the same number of people.

The growth in new auto purchases has been much stronger in low credit score zip codes over the past two years. In 2014, the growth was more than twice as strong in low credit score zips relative to high credit score zips.

So total spending is being driven in large part by auto purchases, and auto purchases are being driven in large part by purchases by low credit score individuals. What explains this pattern?

A very sharp rise in auto loans, especially to low credit score individuals. We showed this pattern in a previous post. It also makes intuitive sense. Wage growth has been pretty stagnant, especially among middle and lower income Americans. So it makes sense that the only way low credit score individuals are able to buy cars is by taking on debt. They certainly haven’t seen improved income.

So what is the big picture? One view is that all of this is benign. Credit conditions were overly tight during the Great Recession, and now credit is flowing back to low credit score individuals who are purchasing cars at a fast clip. We should expect durable purchases by low credit score individuals to help fuel a spending recovery.

Another view, closely related to the secular stagnation idea, is that the only way we can generate real demand is by lending to individuals that have low income and low income prospects. The financial system is channeling funds toward individuals for whom economic circumstances remain poor, which offers only a fleeting boost to spending. This is closely related to arguments we make in our new book, House of Debt.

Can debt-fueled purchases of new autos continue to drive the spending recovery? This is a pattern worth watching closely.

At the end of this post we tell you where to get the data and we give you the Stata code. We did this pretty quickly, so happy to be told if we’ve made some mistake.

The SCF is not a huge sample, so we have chosen to look at the top 20% (80% to 100%) of the wealth distribution versus the middle 20% (40% to 60%) of the distribution every year. Below, we plot the ratio of wealth of the richest 20% versus the middle 20%. We took the averages within each of these quintiles.

The graph shows that the top 20% of the wealth distribution had 15x the wealth of the middle 20% of the distribution in 1992. In 2010, the richest 20% has more than 25x the wealth of the [...]]]> It seems crazy to have such a heated debate on facts that are so easily measurable. Here we use the SCF from 1992 to 2010 to show the pretty unambiguous rise in wealth inequality in the United States. The housing boom hid the rise in inequality to some degree, but the crash in house prices from 2007 to 2010 made inequality transparent.

At the end of this post we tell you where to get the data and we give you the Stata code. We did this pretty quickly, so happy to be told if we’ve made some mistake.

The SCF is not a huge sample, so we have chosen to look at the top 20% (80% to 100%) of the wealth distribution versus the middle 20% (40% to 60%) of the distribution every year. Below, we plot the ratio of wealth of the richest 20% versus the middle 20%. We took the averages within each of these quintiles.

The graph shows that the top 20% of the wealth distribution had 15x the wealth of the middle 20% of the distribution in 1992. In 2010, the richest 20% has more than 25x the wealth of the middle 20%. How is that not a substantial increase in wealth inequality?

The pattern is especially stark if we exclude home equity. This is a useful exercise because we know from 2010 to 2013 financial assets have performed very well. Housing has performed decently as well, but much of the strong performance of housing is driven by investors who are likely part of the richest 20% of the distribution. We don’t yet have the 2013 SCF available.

To be clear, the split of households into quintiles is still based on total net worth. The graph below plots the ratio of non-home equity wealth of the richest 20% to the middle 20%:

That looks like a pretty sharp rise in wealth inequality to us. In 1998 the richest 20% had 25x the non-home equity wealth of the middle 20%. it has risen to almost 45x in 2010.

Just to complete the story, here is inequality using home equity wealth:

The rise in wealth inequality focusing only on home equity is smaller in magnitude, but goes in the same direction overall. Interestingly, the middle 20% made gains on the top 20% from 2004 to 2007, which reflects the fact that house prices rose fastest in middle and lower income areas, something we have documented in our research.

We are happy to be corrected here. Like we said earlier, we did this quite fast. The data sets are available from the Fed. They are the Stata data sets based on the SCF bulletins. For example, here is the link to the 2010 data. And here is our Stata code — let us know if there is a mistake:

**5/24/2014: Piketty and SCF
foreach num of numlist 1992 1995 1998 2001 2004 2007 2010{
cd $scf
use rscfp`num’, clear
sort YY1
by YY1: keep if _n==1
xtile t1=networth [aw=wgt], nq(5)
foreach x of numlist 1/5{
gen networth`x’=networth if t1==`x’
gen networthhom`x’=homeeq if t1==`x’
gen networthnhm`x’=(networth-homeeq) if t1==`x’
}

collapse (mean) networth? networthhom? networthnhm? [aw=wgt]
gen year=`num’
cd $datapath
save t`num’, replace
clear
}
foreach num of numlist 1992 1995 1998 2001 2004 2007 2010{
append using t`num’
erase t`num’.dta
}
foreach y in networth networthhom networthnhm{
gen `y’rat=`y’5/`y’3
}
*graphs
# delimit ;
graph twoway line networthrat year,
scheme(s1mono) title(“Ratio of richest 20% to middle 20%” “Total wealth”)
xtitle(“”) ytitle(“”)  lc(maroon) lw(thick)
xlabel(1992 1995 1998 2001 2004 2007 2010) lw(thick)
caption(
“houseofdebt.org, @AtifRMian & @profsufi, Data source: SCF”,
size(vsmall)
) xsize(4.25) ysize(3);
# delimit cr
graph export “$output\houseofdebt_20140524_1.png”, replace
# delimit ;
graph twoway line networthnhmrat year,
scheme(s1mono) title(“Ratio of richest 20% to middle 20%” “Non-home equity wealth”)
xtitle(“”) ytitle(“”) lc(navy) lw(thick)
xlabel(1992 1995 1998 2001 2004 2007 2010) lw(thick)
caption(
“houseofdebt.org, @AtifRMian & @profsufi, Data source: SCF”,
size(vsmall)
) xsize(4.25) ysize(3);
# delimit cr
graph export “$output\houseofdebt_20140524_2.png”, replace
# delimit ;
graph twoway line networthhomrat year,
scheme(s1mono) title(“Ratio of richest 20% to middle 20%” “Home equity wealth”)
xtitle(“”) ytitle(“”) lc(dkgreen) lw(thick)
xlabel(1992 1995 1998 2001 2004 2007 2010) lw(thick)
caption(
“houseofdebt.org, @AtifRMian & @profsufi, Data source: SCF”,
size(vsmall)
) xsize(4.25) ysize(3);
# delimit cr
graph export “$output\houseofdebt_20140524_3.png”, replace

One way to see the scars of the housing bust is to look at the unemployment rate today in counties that saw the biggest decline in house prices. As we argue in the book, such an approach actually significantly underestimates the impact of the house price-driven spending collapse. This is because even people living in areas that were not hit by housing lost their jobs when people living in areas where house prices crashed stopped buying goods. But even with this under-estimation, here is the picture we get:

The unemployment rate in counties hit hardest by the housing crash is more than 3% higher in 2013 relative to 2006. The rise in the unemployment rate is twice as high as the rise in counties with the smallest decline in house prices. The housing crash has led to a large and persistent increase in unemployment. The evidence is undeniable.

New York Times: The Case Against the Bernanke-Obama Financial Rescue

Economist Free Exchange: The Opposite of Insurance

Paul Krugman (NYT): Springtime for Bankers

Book Interview on RT Boom/Bust

Washington Post: Why Tim Geithner is Wrong on Homeowner Debt Relief

New York Times: Housing Crisis Was Overlooked

Huffington Post: Did Washington Rescue the Wrong Economy?

Economist Free Exchange: The Unwinnable War

Brad DeLong at Equitablog

In the end, the story of economic policy since 2008 has been that of a remarkable double standard. Bad loans always involve mistakes on both sides — if borrowers were irresponsible, so were the people who lent them money. But when crisis came, bankers were held harmless for their errors while families paid full price.

And refusing to help families in debt, it turns out, wasn’t just unfair; it was bad economics. Wall Street is back, but America isn’t, and the double standard is the main reason.

In some of the early reviews of our book, our argument is caricatured as saying we should have let the banks fail and we should have saved homeowners. We do not make such an extreme claim. In fact, we commend both Ben Bernanke and Tim Geithner for some of their policies that were directed at stopping dangerous runs in the banking system. We agree that bank runs threaten the payment system and the entire economy, and policies should be undertaken [...]]]> Paul Krugman has an excellent column this morning hitting many of the same themes we discuss in our new book. As he puts it:

In the end, the story of economic policy since 2008 has been that of a remarkable double standard. Bad loans always involve mistakes on both sides — if borrowers were irresponsible, so were the people who lent them money. But when crisis came, bankers were held harmless for their errors while families paid full price.

And refusing to help families in debt, it turns out, wasn’t just unfair; it was bad economics. Wall Street is back, but America isn’t, and the double standard is the main reason.

In some of the early reviews of our book, our argument is caricatured as saying we should have let the banks fail and we should have saved homeowners. We do not make such an extreme claim. In fact, we commend both Ben Bernanke and Tim Geithner for some of their policies that were directed at stopping dangerous runs in the banking system. We agree that bank runs threaten the payment system and the entire economy, and policies should be undertaken to prevent such runs.

The problem we have with the Geithner view of the world is that it is far too extreme — it is a “save the banks, save the economy” view which has been thoroughly discredited in both the United States and Europe. The fact that Geithner still adheres to this view despite all the evidence to the contrary is truly remarkable.

The problem with the economy in 2008 and 2009 is not that banks are not lending enough. It’s absurd to argue that we need more bank lending when demand is collapsing throughout the economy.

Here is the passage from our book that speaks on this issue:

When a financial crisis erupts, lawmakers and regulators must address problems in the banking system. They must work to prevent runs and preserve liquidity. But policy makers have gone much further, behaving as if the preservation of bank creditor and shareholder value is the only policy goal. The bank lending view has become so powerful that efforts to help home owners are immediately seen in an unfavorable light. This is unacceptable. The dramatic loss in wealth of indebted home owners is the key driver of severe recessions. Saving the banks won’t save the economy. Instead, bolstering the economy by attacking the levered-losses problem directly would save the banks.

History seems to understand this lesson well. The 48th provision of the Code of Hammurabi, written more than 3,500 years ago in Mesopotamia, states that: “If any one owe a debt for a loan, and a storm prostrates the grain, or the harvest fail, or the grain does not growth for lack of water, in that year he need not give his creditor any grain, he washes his debt-tablet in water and pays no rent for this year.” The main threat to economic activity in ancient Mesopotamia was a drought, and one of the first legal codes understood that debt should be forgiven if such a negative shock occurred.

In 1819 when agricultural prices in the United States plummeted leaving farmers overly indebted and unable to pay their mortgages, politicians ran to their defense. Many [...]]]> In the face of large-scale economic shocks, enforcing debt contracts places an unbearable burden on debtors, who cut back their spending and send the entire economy into deep recession. One of the main arguments we make in our new book is that debt forgiveness makes a lot of sense when the economy experiences a large-scale negative shock that is beyond the control of any one individual.

History seems to understand this lesson well. The 48^th provision of the Code of Hammurabi, written more than 3,500 years ago in Mesopotamia, states that: “If any one owe a debt for a loan, and a storm prostrates the grain, or the harvest fail, or the grain does not growth for lack of water, in that year he need not give his creditor any grain, he washes his debt-tablet in water and pays no rent for this year.” The main threat to economic activity in ancient Mesopotamia was a drought, and one of the first legal codes understood that debt should be forgiven if such a negative shock occurred.

In 1819 when agricultural prices in the United States plummeted leaving farmers overly indebted and unable to pay their mortgages, politicians ran to their defense. Many state governments immediately imposed moratoria on debt payments and foreclosures. Senator Ninian Edwards of Illinois pushed through national legislation to forgive farmers’ debt, arguing that the country should have sympathy for the farmers who, like the rest of the country, got caught up in the short-lived “artificial and fictitious prosperity.”

During the Great Depression, President Roosevelt nixed Gold Clauses in debt contracts which led to an immediate and sizable forgiveness in debt. Research suggests this policy helped both debtors and creditors. The government-funded Home Ownership Loan Corporation established in the 1930s also helped ease debt burdens and reduce foreclosures by lowering interest payments.

During the Great Recession, policy-makers followed a very different strategy. Underwater homeowners were left drowning, with no meaningful assistance. It is a striking contrast, one that everyone should contemplate. What was different this time? Almost every reason for lack of action was likely present in the previous episodes.

We aren’t alone in noticing the historical discrepancy. Here is Brad DeLong, a top economic historian, in his review of our book:

All I can say is that I thought that this was the system that we had. I thought–from the Great Depression era history of the HOLC and the RFC, from the 1980s history of the Latin American debt crisis, from the 1990s history of the RTC, from innumerable emerging-market crises, et cetera, that we understood very well that this is what we should do. Whenever the financial system got sufficiently wedged we resolved it–we turned debt into equity, and we crammed losses down onto debt holders whose investments were ex post judged to have been ex ante unwise.

And from my standpoint the true puzzle is why Bernanke, Geithner, and Obama were so uninterested in pulling out the Walter Bagehot-Hyman Minsky-Charlie Kindleberger playbook and following it in housing finance from 2009-2014. Did they read no history?

The architects of the crisis response typically cite history as motivation for aggressive bank bailouts. But on the problem of excessive household debt, it appears that much history was forgotten.