Economic Indicators

How do individual asset classes react to monthly inflation indications? To investigate, we relate future monthly returns for the following 10 asset class exchange-traded fund (ETF) proxies to monthly changes in the U.S. Consumer Price Index (CPI):

• Equities:
  • SPDR S&P 500 (SPY)
  • iShares Russell 2000 Index (IWM)
  • iShares MSCI EAFE Index (EFA)
  • iShares MSCI Emerging Markets Index (EEM)
• Bonds:
  • iShares Barclays 20+ Year Treasury Bond (TLT)
  • iShares iBoxx $ Investment Grade Corporate Bond (LQD)
  • iShares JPMorgan Emerging Markets Bond Fund (EMB)
• Real assets:
  • Vanguard REIT ETF (VNQ)
  • SPDR Gold Shares (GLD)
  • Invesco DB Commodity Index Tracking (DBC)

Using monthly CPI data (all items) and monthly dividend-adjusted returns for the above 10 asset class proxy ETFs as available from July 2002 through September 2023, we find that: Keep Reading

Does quantified uncertainty in government economic policy reliably predict stock market returns? To investigate, we consider the U.S. Economic Policy Uncertainty (EPU) Index, created by Scott Baker, Nicholas Bloom and Steven Davis and constructed from three components:

1. Coverage of policy-related economic uncertainty by prominent newspapers.
2. Number of temporary federal tax code provisions set to expire in future years.
3. Level of disagreement in one-year forecasts among participants in the Federal Reserve Bank of Philadelphia’s Survey of Professional Forecasters for both (a) the consumer price index (CPI) and (b) purchasing of goods and services by federal, state and local governments.

They normalize each component by its own standard deviation prior to 2012 and then compute a weighted average of components, assigning a weight of one half to news coverage and one sixth each to tax code uncertainty, CPI forecast disagreement and government purchasing forecast disagreement. They update the index monthly at the beginning of the following month, potentially revising recent months. Using monthly levels of the EPU Index and the S&P 500 Index during January 1985 through August 2023, we find that: Keep Reading

Each month, the Institute for Supply Management (ISM) each month generates the Services Purchasing Managers Index (PMI), aggregating monthly inputs from purchasing and supply executives in services firms across the U.S. regarding business activity, new orders, employment and supplier deliveries. ISM releases Services PMI for a month on the third business day of the following month. Does the monthly level of Services PMI or the monthly change in Services PMI predict U.S. stock market returns? Using monthly seasonally adjusted Services PMI data during January 2008 through January 2016 from the Federal Reserve Bank of St. Louis and from press releases thereafter through August 2023, and contemporaneous monthly S&P 500 Index closes, we find that: Keep Reading

According to the Institute for Supply Management (ISM) each month generates the Manufacturing Purchasing Managers’ Index (PMI), aggregating monthly inputs from purchasing and supply executives in manufacturing firms across the U.S. regarding new orders, production, employment, deliveries and inventories. ISM releases Manufacturing PMI for a month at the beginning of the following month. Does Manufacturing PMI predict stock market returns? Using monthly seasonally adjusted Manufacturing PMI data during January 1948 through January 2016 from the Federal Reserve Bank of St. Louis (discontinued and removed) and from press releases thereafter through August 2023, and contemporaneous monthly S&P 500 Index closes, we find that:

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A subscriber asked whether aggregate U.S. state tax revenues, as an indicator of economic activity, lead the U.S. stock market. To investigate, we compare behaviors of total quarterly state tax collections and SPDR S&P 500 ETF Trust (SPY). Because these series are not stationary (generally increasing rather than mean reverting), we relate changes in them. Because the state tax revenues exhibit strong seasonality, we focus on a 4-month simple moving average (SMA4) of state tax revenues. Because the SMA4 series involves substantially overlapping measurements that can distort statistics, we also look at annual measurements. Using quarterly state tax collections data and quarterly dividend-adjusted prices for SPY as available from the first quarter of 1994 (limited by tax collections data) through the second quarter of 2023, we find that: Keep Reading

Do stock prices confirm that firms with high market power maintain profitability during times of high inflation because they can raise prices, while those with low market power cannot? In their August 2023 paper entitled “Stagflationary Stock Returns and the Role of Market Power”, Benjamin Knox and Yannick Timmer study effects of inflation news on stocks of firms ranked by market power. They define:

• Inflation news as the difference between total consumer price index (CPI) releases and the median inflation forecast from Bloomberg back to 1997, and before that from Haver Analytics back to 1977.
• Market power as firm ability to set its price above marginal costs (markup), estimated as sales over cost of goods sold multiplied by the output elasticity of inputs (from a production function estimate).

They decompose stock returns into risk premium, risk-free rate and cash flow news components. They designate firms above the 75th (below the 25th) percentile of market power as high-market power (low-market power) firms to assess stock price responses to inflation news. Using total CPI releases, associated median inflation forecasts, accounting data for a broad sample of U.S. common stocks and daily returns for both individual stocks and the broad U.S. stock market during 1977 through 2022, they find that: Keep Reading

In response to “PPI and the Stock Market”, a subscriber hypothesized that increases and decreases in the ratio of the Consumer Price Index (CPI) to the Producer Price Index (PPI) are bullish and bearish for the stock market, respectively. The reasoning for the hypothesis is that CPI reflects aggregate corporate revenue, while PPI reflects aggregate costs. The ratio CPI/PPI therefore relates to aggregate profitability, which should translate to stock market level. To test this hypothesis, we construct U.S. CPI/PPI monthly from non-seasonally adjusted CPI and non-seasonally adjusted PPI. We then relate changes in this ratio to S&P 500 Index returns. Using CPI and PPI values and S&P 500 Index levels as available during December 1927 through July 2023, we find that: Keep Reading

Inflation at the producer level (per the Producer Price Index, PPI) is arguably an advance indicator for inflation downstream at the consumer level (per the Consumer Price Index, CPI). Do investors reliably react to changes in PPI as an indicator of the future wealth discount rate? In other words, is a high (low) producer-level inflation rate bad (good) for the stock market? Using monthly, non-seasonally adjusted PPI from the Bureau of Labor Statistics (BLS) and S&P 500 Index levels as available during December 1927 through July 2023, we find that: Keep Reading

During 1989 through 2019, the S&P 500 Index generated 5.5% real annual return, compared to just 2.5% annual real growth in U.S. gross domestic product (GDP). How can this disconnect happen? Can it continue? In the June 2023 version of his paper entitled “End of an Era: The Coming Long-Run Slowdown in Corporate Profit Growth and Stock Returns”, Michael Smolyansky examines interactions between U.S. stock market performance and declines in interest rates and corporate tax rates over the last three decades. He focuses on S&P 500 non-financial stocks adjusted for index additions/deletions and for changes in firm shares outstanding, allowing computation of per share metrics. He decomposes stock returns into: (1) change in price-earnings ratio (P/E);  (2) change in earnings before interest and taxes (EBIT); (3) change in interest expenses; and, (4) change in effective corporate tax rate. Using the specified annual data during 1962 through 2019, he finds that: Keep Reading

Does an expectation of an unusually large number of firm defaults in the coming year usefully predict stock and bond market returns? In their May 2023 paper entitled “Systematic Default and Return Predictability in the Stock and Bond Markets”, Jack Bao, Kewei Hou and Shaojun Zhang apply an iterative process to estimate the probability that non-financial, non-microcap firms will default during the next year due to exposures to common shocks. The main inputs for their estimate are: (1) firm-level balance sheets and past stock returns; and, as common shocks, (2) past stock market returns. They relate estimated next-year default rate probability, focusing on a threshold of 2% of firms, to future stock market and corporate bond market index returns at horizons from one month to five years. They conduct in-sample tests of the default rate probability-index return relationships based on all data. They conduct out-of-sample index return predictions based on inception-to-date data starting at the sample half-way point. For robustness, they consider default rate probability thresholds other than 2%. Using firm balance sheets/monthly stock returns, plus monthly value-weighted U.S. stock market index and Dow Jones Corporate Bond Return Index returns during March 1961 through December 2021, they find that: Keep Reading