Hard Data Versus Soft Sentiment: The Sequel
This week is a busy one for financial market participants, with corporate earnings reports, economic data and policy all competing for the market’s attention. The European fiscal situation remains at the top of the list of worries for markets, as policymakers scramble to hit a self-imposed early November deadline to have a grand plan in place to address Greece and European banks’ exposure to Greek and other troubled sovereign debt. As we have noted in several of our recent commentaries, markets are still crying out for bold, coordinated policy actions here and abroad. Markets in the past week or so have become increasingly confident that such actions will be taken — although the devil is in the details.
But this week, a barrage of third-quarter corporate results (including guidance for the fourth quarter and next year), key data on housing, inflation and manufacturing in the United States, as well as several speeches from Federal Reserve officials (including Ben Bernanke) will all also compete for the market’s attention. The most closely watched report of the week is likely to be the Fed’s Beige Book, a qualitative assessment of business and banking conditions in each of the 12 Federal Reserve districts (Boston, Richmond, Dallas, Kansas City, Cleveland, etc.), compiled eight times a year prior to each of the Federal Open Market Committee (FOMC) meetings. China completes the release of its September and third-quarter data early in the week, with the third-quarter report on gross domestic product, as well as the September reports on industrial production and retail sales.
The Sentiment Data Versus the “Hard Data”: The Debate Continues
We have written extensively over the past several months about the conflicting messages being sent by the “hard” data on the economy, and the “soft”, or sentiment, data on the economy. Hard data statistically measures what consumers or businesses are doing, for example:
· How many homes were sold?
· How much revenue did a company generate?
· What were a company’s earnings after expenses?
· How much did consumers spend on groceries, or computers or television sets?
· How many cars were produced and sold?
· How many jet engines were exported overseas?
· How many new orders for business equipment were placed?
· How many jobs were created (or lost)?
· How much oil or gasoline was produced and/or consumed?
On the other hand, the “soft” data are reports that measure sentiment, and do not actually measure anything other than how people or businesses feel.
The mood of consumers or businesses is, of course, greatly influenced by what they see around them every day. It is also impacted by what they see on television, in newspapers, on the Internet, on talk radio or from friends, neighbors and colleagues. And of course, lately, the media has been full of bad news on virtually every topic. However, the media itself is thriving on the bad news with some of the highest ratings, readers and listeners in history.
In recent months, the hard data has painted a stronger picture of the U.S. economy than that reflected by the sentiment data. But at times, the opposite is true, and the sentiment runs far ahead of the actual data, as was the case in 1999 and 2000 at the peak of the tech bubble and in the mid- 2000s as the housing bubble was just about to burst.
We expect, however, that the trend of the hard data painting a better picture of the economy than the soft data will continue this week. Ultimately, it is the hard data — not the sentiment (or soft) data — that will tell us whether or not we have re-entered a recession, have started to shed jobs again, or seen an uptick in inflation. However, poor sentiment (in both the consumer and business oriented segments of the economy) can feed on itself, and lead to a pullback in spending, which would then begin to negatively impact the hard data. We have not seen that yet, but those in the marketplace calling for a recession believe that the transition from poor sentiment to poor data is inevitable. We do not, and continue to place the odds of recession in the near term at about one in three.
As this report was being prepared, we received hard data for September (industrial production) and sentiment for October (the Empire State Manufacturing Index). Often, the sentiment data has the benefit (from the market’s perspective) of being timelier. For example, for the most part, this week’s hard data on the economy references September, but the week’s sentiment-based data is measuring sentiment in October.
True to recent form, the industrial production data revealed that overall industrial output (factories, utilities, and mining) increased by a modest 0.2% between August and September, and that output of factories alone increased by 0.4%. Industrial production, a key gauge of whether or not the economy is in or out of recession, is up nearly 4% from a year ago and continues to push higher. Overall, industrial production in the manufacturing sector has increased in 24 of the past 27 months since the end of the Great Recession in June 2009.
On the other hand, the Empire State Manufacturing Index, which measures how manufacturing contacts in New York state feel about their overall business (as well as employment, shipments, orders, etc.), remained below zero in October, indicating that manufacturing in the New York state region contracted for the fifth consecutive month. The good news here is that the contraction has not picked up momentum.
The other examples of hard data (mainly for September and early to mid- October) due out this week include:
· Producer Price Index (PPI)
· Consumer Price Index (CPI)
· Housing starts
· Building permits
· Existing home sales
· Initial claims for unemployment insurance
· Weekly retail sales
· Weekly mortgage applications and
· Weekly car and light truck production
This rest of the week’s sentiment based data (for September and October) includes:
· The National Association of Homebuilders Sentiment Index
· The Fed’s Beige Book
· The Philadelphia Fed Index
In addition, the index of leading economic indicators (LEI) for September is due out at the end of the week. The index is a compilation of ten data series. Seven of the components of the LEI are hard data, with two being sentiment based. The final component of the LEI is the stock market (as measured by the S&P 500 Index), which is hard data of course, but is often driven over short periods of time by sentiment. The LEI is expected to increase by 0.3% month-over-month in September, which would leave the index a robust 6.0% above its year-ago reading, a clear sign that despite the negative sentiment, the economy continues to grow, albeit modestly.
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Manufacturing Sector: Companies engaged in chemical, mechanical, or physical transformation of materials, substances, or components into consumer or industrial goods.
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The Consumer Price Index (CPI) is a measure of the average change over time in the prices paid by urban consumers for a market basket of consumer goods and services.
The Producer Price Index (PPI) program measures the average change over time in the selling prices received by domestic producers for their output. The prices included in the PPI are from the first commercial transaction for many products and some services.
Empire State Manufacturing Survey is a monthly survey of manufacturers in New York State conducted by the Federal Reserve Bank of New York.
The Philadelphia Fed Survey is a business outlook survey used to construct an index that tracks manufacturing conditions in the Philadelphia Federal Reserve district. The Philadelphia Fed survey is an indicator of trends in the manufacturing sector, and is correlated with the Institute for Supply Management (ISM) manufacturing index, as well as the industrial production index.
The Industrial Production Index (IPI) is an economic indicator that is released monthly by the Federal Reserve Board. The indicator measures the amount of output from the manufacturing, mining, electric and gas industries. The reference year for the index is 2002 and a level of 100.
This research material has been prepared by LPL Financial.
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