Category: Chart of the Week

The Improving Outlook for Construction Jobs

This week’s chart shows the month over month change in construction jobs and the month over month change in annualized housing starts in the U.S. (based on rolling six month averages for each). As the chart illustrates, the steep drop off in housing starts that began in late 2006 resulted in significant job losses in the construction sector starting in mid-2007. However, over the past several months, a positive trend has started to emerge in new housing starts.

This week’s chart shows the month over month change in construction jobs and the month over month change in annualized housing starts in the U.S. (based on rolling six month averages for each). As the chart illustrates, the steep drop off in housing starts that began in late 2006 resulted in significant job losses in the construction sector starting in mid-2007. The construction sector, which added approximately 1.1 million jobs from January 2003 to December 2006 (an average of about 24,000 jobs a month), lost approximately 2.1 million jobs from January 2007 to December 2010 (an average of about 44,000 jobs per month) according to ADP payroll data. However, over the past several months, a positive trend has started to emerge in new housing starts. This positive trend in housing starts has largely been driven by an increase in construction of multifamily housing units (i.e. apartment buildings) due to the increased demand for apartments (as a result of many households transitioning from homeowners to renters).

While this improvement is a welcome development in the housing market and construction sector, the recent increase in construction jobs is nowhere close to the kind of growth required to make up for the lost construction jobs during the recession and its aftermath. We have had an increase in construction jobs for five consecutive months with approximately 56,000 construction jobs added in the U.S. At this pace, it would take over 15 years to recover all the construction jobs that were lost from January 2007 to December 2010.

Beware of Changing Correlations!

This week’s chart shows the dynamic nature of correlations between asset classes by comparing correlations amongst traditional asset classes over 20-year and 5-year historical periods. The chart above shows how much these correlations have all increased when comparing the 5-year figures to the longer dated 20-year period.

This week’s chart shows the dynamic nature of correlations between asset classes by comparing correlations amongst traditional asset classes over 20-year1 and 5-year2 historical periods.3 The chart above shows how much these correlations have all increased when comparing the 5-year figures to the longer dated 20-year period. What does this mean for investors? We see two main takeaways:

  1. For those that rely on mean-variance optimization programs for determining their asset allocation, it is imperative to understand the exact timeframe reflected in the correlations used as inputs, as different time periods will yield not only different correlations but critically, different portfolio structures.
  2. The correlation amongst traditional asset classes has increased in the last five years, thus it is more difficult to truly create a “diversified” portfolio that offers protection from large draw downs in the equity markets. This was never more apparent than during the financial crisis of 2008-2009.

As now outlined in both this chart and “Correlation Doesn’t Tell the Whole Story”, correlations can be helpful in conducting asset allocation studies, but they also feature some notable shortcomings that should be well understood by those who rely on them for portfolio decisions.

1 March 1992 – February 2012
2 March 2007 – February 2012
3 Indices used for analysis were Russell 1000, Russell 2000, MSCI EAFE, MSCI Emerging Markets, and BarCap Aggregate

Velocity of Money

This week’s chart shows the change in the velocity of the money from 1959 through 2011 along with the growth in the monetary base. Velocity measures the frequency with which a unit of money changes hands in an economy over a given period of time. This figure can be viewed as a general gauge of activity taking place within an economy.

This week’s chart shows the change in the velocity of the money from 1959 through 2011 along with the growth in the monetary base. Velocity measures the frequency with which a unit of money changes hands in an economy over a given period of time. This figure can be viewed as a general gauge of activity taking place within an economy. The monetary base represents liquid currency as well as close substitutes for money including currency in circulation, bank vaults, and bank reserves. In monetary economics, the quantity theory of money states that money supply multiplied by velocity equals real GDP times the price level.

Money Supply * Velocity = Real GDP * Price Level

This implies that the price level has a direct relationship with the supply of money in an economy. As the chart shows, the monetary base is at the highest level on record, which would normally lead to an increase in the price level (inflation). However, velocity is at the lowest level since record keeping began in 1959 and is the primary reason inflation remains subdued, despite the large increase in the money supply.

The Federal Reserve has more than doubled the monetary base since December 2007 through quantitative easing in hopes of stimulating borrowing and spending. However, increases in the monetary base have largely sat idle in bank reserves as banks increased their capital ratios, tightened lending standards, and overall loan demand levels decreased, causing the velocity of money to fall. Given the current economic slack in the U.S., it is unlikely that the Federal Reserve’s monetary policies will cause inflationary issues in the near term as long as velocity remains low. However, once economic activity begins to pick up, policy tightening will be essential to reduce potential inflation pressures.

More Challenges for Greece

Another round of bailouts, totaling €130 billion, was approved for Greece on Tuesday. As with other Greek bailouts, the receipt of the money was contingent on further budget cuts and austerity. Going forward, Greece faces two main concerns, one short-term, and one long-term.

Another round of bailouts, totaling €130 billion, was approved for Greece on Tuesday. As with other Greek bailouts, the receipt of the money was contingent on further budget cuts and austerity. Going forward, Greece faces two main concerns, one short-term, and one long-term. In the short-term, Greece will likely continue to experience solvency/liquidity pressures, as large debt and deficits require continued aid and debt write-downs. The approved bailouts help relieve these pressures.

However, continued austerity in the face of negative GDP growth and large deficits may exacerbate Greece’s financing problems. Austerity has improved Greece’s finances less than expected, as budget cuts result in lower GDP and thus lower tax revenues. As recently as March 2011, the IMF expected Greece’s contraction to bottom in 2010, and resume growth by 2012. New estimates from the Eurogroup expect the GDP contraction in Greece to bottom in 2012, and resume growth by 2014. It is difficult to see how this goal is achievable utilizing similar policy prescriptions that have failed to work in the past. Forecasts may still be overly optimistic.

Regardless, short-term solvency issues can continue to be relieved by further bailouts as long as there is political will. Longer-term competitiveness problems may be more difficult to solve. EU officials hope that Greece can transform into a competitive, export-driven economy. Currently Greece, along with other PIIGS countries, runs a large current account deficit. Simultaneously, Germany runs a large current account surplus. One of the main drivers in the competitiveness gap between Greece and Germany are differences in unit labor costs. Unit labor costs measure the average costs per unit of output, and are calculated as the ratio of total labor costs to real output.

The chart above shows the change in unit labor costs for select Eurozone countries since 2002. Greece’s labor costs over this period have risen significantly, while Germany’s have barely budged. The two main solutions to this gap are relative inflation in Germany (unlikely given its history), or years of wage deflation in Greece. This suggests that the adjustment period for Greece as long as it remains in the Eurozone could be quite long indeed.

Unemployment by Education Level

This week’s chart shows the historical unemployment rates for various education levels and their respective averages over the time period of 1992 – present. Despite the well publicized recent drop in the overall unemployment rate, the current unemployment rates for each education level still remain near their 20 year highs and around twice their 2007 pre-recession levels. Also, since the recession began, the unemployment rate for those with only a high school degree has been higher than the unemployment rate for the general population for the first time.

This week’s chart shows the historical unemployment rates for various education levels and their respective averages over the time period of 1992 – present. While the general ordering of the unemployment rates is not surprising, there are some notable takeaways from the chart. First, despite the well publicized recent drop in the overall unemployment rate, the current unemployment rates for each education level still remain near their 20 year highs and around twice their 2007 pre-recession levels. Also, since the recession began, the unemployment rate for those with only a high school degree has been higher than the unemployment rate for the general population for the first time. This shows the growing importance of higher education towards finding and keeping a job.

As the recession carries on, the gap in unemployment rates between those with a college degree and those without remains elevated at historic highs. In addition, for the first time those who have earned a high school degree but continued no further in their education have fallen behind the general population in terms of unemployment. All of this shows that the current recession has exasperated the long term trend of the less educated experiencing much higher unemployment levels than those with a high school or college degree.

Lower Oil Prices?

Domestic energy production has experienced a renaissance over the last few years, mainly driven by natural gas production. While oil prices hovered around $100/barrel for most of 2011 natural gas prices hit lows not seen since the 1990’s.

Domestic energy production has experienced a renaissance over the last few years, mainly driven by natural gas production. While oil prices hovered around $100/barrel for most of 2011 natural gas prices hit lows not seen since the 1990’s. As this chart shows, the relative price of oil to natural gas (shown in gold) was fairly stable during the 1990’s and most of the 2000’s but has soared over the last few years. In the short term some divergence is understandable, but over the long term these two energy sources are substitutes and we would expect to see energy consumers switch from oil to natural gas given the price differential.

The line in gray shows the number of natural gas drilling rigs in the U.S. and the explosion of drilling in 2006 and 2007 led to the increased production and lower prices we see today. What is also interesting is natural gas drilling activity has remained fairly stable over the last two years while oil drilling activity has reached levels not seen in the last twenty years (black line). Will the increase in oil drilling lead to more production and lower prices? If natural gas is any indication, Americans might see more oil production and lower prices at the pump in the years ahead.

Higher Rates for Japanese Debt?

This week’s Chart of the Week chronicles Japan’s trade deficit over the last five years. In the graph, the red line represents Japan’s month-end trade balance, while the charcoal line is the 100-day moving average of the trade balance.

This week’s Chart of the Week chronicles Japan’s trade deficit over the last five years. In the graph, the red line represents Japan’s month-end trade balance, while the charcoal line is the 100-day moving average of the trade balance. Most important in the chart is that Japan logged its first annual trade deficit in more than 30 years for 2011, as measured by the aggregation of month end trade deficits (note that although month-end trade deficits were larger in late 2008 and early 2009, the total trade balance for each of those years was actually positive). The 2011 trade deficit of 2.49 trillion yen (approximately $32 billion) is due at least in part to the March earthquake and tsunami, which paralyzed production/exports and provoked a surge of costly fuel imports to cover for the loss of nuclear power. Shortly after the March 2011 earthquake devastation, Japanese exports – the leading engine of Japan’s economic growth the last six years – declined 12.0% in April, and continued to decline in May. Furthermore, a persistently strong yen contributed to the reduction of total exports by 2.7% since last year while imports surged by 12%.

In terms of market impact, the emergence of a trade deficit in Japan leaves to question how much longer the country can fund its gross national debt, currently just under 230% of GDP, without reliance on foreign investors. If exports continue to fall and imports rise, the need for foreign investment will increase. However, foreign investors are unlikely to accept the low yields of the past, so a rise in rates for Japanese debt would seem probable.

The Changing Composition of Consumption

While traditional “active” consumer spending undoubtedly makes up a large percentage of G.D.P., increased spending on health care (through Medicare and Medicaid) over time has likely overstated this popular statistic.

It is common to hear that consumption contributes 65 to 70% of total GDP, hence its importance to economic growth. More insightful, though, is to understand the underlying components of consumption and how accurately it truly reflects consumption on behalf of consumers. To do this, we use the Personal Consumption Expenditures (PCE) data which is the source of that 65 – 70% number. Critically, one must understand the elements of PCE data: in addition to the traditional consumption items (clothing, electronics, food and drink, housing, transportation, etc.), non-profit spending and expenditures made “on behalf” of consumers, such as Medicare and Medicaid, are also included. While traditional “active” consumer spending undoubtedly makes up a large percentage of G.D.P., increased spending on health care (through Medicare and Medicaid) over time has likely overstated this popular statistic.

Indeed, this is reflected in the historical data: in 1959, over 73% of consumer spending was spent in four main traditional consumer spending categories: housing, transportation, food and drink, and personal care/clothing. Over the last 50 years, the percentage spent on these four categories decreased to just over 50% of all spending in 2011. The biggest reason for the change is increased spending on healthcare – it accounted for less than 6% of overall PCE in 1959, while today it accounts for nearly 20%. This massive increase has certainly decreased the percentage of total PCE that is attributable to traditional, active consumer spending choices.

PCE is not a great indicator of average consumer expenditures, because the “spending” on Medicare and Medicaid is not distributed evenly among consumers, nor is it an “elected” expenditure in that consumers freely choose to spend or not spend on the two items. So if consumers aren’t actually spending 20% of their expenditures on healthcare, what are they buying? To get a sense for what consumers are actually spending their money on, the Bureau of Labor Statistics performs a survey called the Consumer Expenditure Survey that attempts to collect data on the spending habits of American consumers. Based on these results, healthcare accounts for less than 7% of annual spending for the average consumer.

Category % of Avg. Annual Expenditures
Food 12.7%
Housing 34.4%
Apparel and services 3.5%
Transportation 16.0%
Healthcare 6.6%
Entertainment 5.2%
Cash contributions 3.4%
Personal insurance and pensions 11.2%
Other 7.0%

 

Delinquency Rates

This week’s Chart of the Week examines four types of loans and their delinquency rates over the past twenty years. A loan is considered to be delinquent if it is past due by thirty or more days. The delinquency rate is the percentage of loans that are considered to be delinquent.

This week’s Chart of the Week examines four types of loans and their delinquency rates over the past twenty years. A loan is considered to be delinquent if it is past due by thirty or more days. The delinquency rate is the percentage of loans that are considered to be delinquent.

The chart shows all four delinquency rates are on a noticeable decline from their peaks as the economy has made some improvements over the last two years. In fact, three of the four rates have fallen below their respective twenty year averages. Business loan delinquency rates have followed the pattern of the business cycle therefore it is not surprising to see the rates go down as we emerge from recession. Consumer and credit card delinquency rate declines are due in large part to commercial banks writing off bad debt, a tightening of lending standards, and consumers deleveraging. More individuals are no longer paying their mortgages, thus freeing up money to pay off other debts.

The delinquency rate for single family mortgages remains considerably higher than its twenty year average. Many homes are now valued significantly lower than their loan balances. This fact, coupled with a challenging job market, has contributed to the high delinquency rate. The potential that these delinquent properties will eventually end up in foreclosure make it an even more challenging environment for residential real estate. Foreclosures will increase the supply in an already oversupplied market and exacerbate the downward pressure on home prices. As discussed in our 2012 Market Preview, this environment has led to a boom for owners of rental units: the apartment sector has benefitted because individuals are now turning to rentals rather than purchasing homes.

Correlation Doesn’t Tell the Whole Story

Over the past five years, as globalization has become more pronounced and economies more intertwined, correlations have certainly increased to all time high levels. But since correlation does not capture magnitude of returns, investors should continue to utilize an asset allocation model that takes potential risk and return into account.

This week’s Chart of the Week covers increased correlations among asset classes. Correlation is a statistical measure showing how two variables move in relation to each other. It can range anywhere from -1 to1, and refers only to the direction of changes. Perfect negative correlation (-1), implies that two items move in completely opposite directions and perfect positive correlation (+1), implies that two items move in lock-step. The chart above shows the five-year correlations between the S&P 500 and a broad set of sample asset classes. As evident, all risk-assets have had a very high positive correlation to the S&P 500 over the past five years. Referring to the chart, aside from the three Treasury indices, no other asset class has a correlation less than .90, which is extremely high.

However, correlation only tells part of the story: just because two asset classes have high correlation does not mean that their returns will end up being the same. In fact, this will most likely never be the case. For example, over the time-frame captured above, despite very high correlations, emerging markets, the S&P 500, and the REIT index have annualized returns of 2.8%, -.56% and -3.48% respectively. Over the past five years, as globalization has become more pronounced and economies more intertwined, correlations have certainly increased to all time high levels. But since correlation does not capture magnitude of returns, investors should continue to utilize an asset allocation model that takes potential risk and return into account.