Gross domestic product for the U.S. in the fourth-quarter is on track to rise by 1.5%, according to the average of The Capital Spectator’s five econometric “nowcasts”. That’s up slightly from the 1.2% average in our previous update on November 23. The improvement isn’t surprising, considering the recent round of upbeat economic reports, including the revivals in industrial production and retail sales numbers for November. Today’s GDP nowcast for Q4 reflects the latest fourth-quarter indicators, and the prevailing wind at the moment is blowing positive, albeit modestly so.
Even if the 1.5% nowcast holds for Q4, it represents a slower rate of growth vs. Q3, which posted a substantially higher 2.7% increase, the Bureau of Economic Analysis reported last month. Looking ahead, the government’s official Q4:2012 GDP estimate is scheduled for release on January 30, which means that there’s still a long road ahead for new data and nowcast updates. Apart from the usual mystery that surrounds future data releases, there’s also an extra layer of macro uncertainty lurking in the weeks ahead due to the ongoing fiscal cliff talks in Washington. Nonetheless, it’s encouraging to see our average nowcast rise a bit. Here’s how each of the individual nowcasts compare with recent history and The Wall Street Journal’s forecasts via a survey of economists from earlier this month:
Next, here’s a recap of how our nowcasts for Q4:2012 GDP have evolved so far:
Most of November’s indicators are published–the key missing pieces for last month’s data profile at this point are personal income and spending, which will be updated this Friday (Dec. 21). Meantime, the trend seems to be moving in the right direction. Is more of the same on tap with Friday’s income and spending news? Yes, according to the consensus forecast of economists. Income is expected to rise 0.3% for November, according to Econoday.com, which would compare favorably with October’s unchanged reading. Economists also expect a better report on consumer spending: a 0.4% increase for November vs. -0.2% previously.
As for the numbers in hand, here’s a brief review of how they’re sliced and diced to generate The Capital Spectator’s GDP nowcasts:
4-Factor Nowcast. This estimate is based on a multiple regression of quarterly GDP in history relative to quarterly changes for four key economic indicators: real personal consumption expenditures, real personal income less government transfers, industrial production, and private non-farm payrolls. This model compares the data on a quarterly basis, looking for relationships with GDP within each quarter from the early 1970s to the present. The four independent variables are updated monthly and so the nowcast is revised as new data is published. In effect, this model is telling us what the data trends in the current quarter imply for the quarter’s GDP growth.
10-Factor Nowcast. This model also uses a multiple regression framework based on historical data from the early 1970s onward and updates the estimates as new numbers arrive. The methodology here is identical to the 4-factor model except that it uses additional factors—10 in all. In addition to the data quartet in the 4-factor model, the 10-factor nowcast also incorporates the following series:
• ISM Manufacturing PMI Composite Index
• housing starts
• initial jobless claims
• the stock market (S&P 500)
• crude oil prices (spot price for West Texas Intermediate)
• the Treasury yield curve spread (10-year Note less 3-month T-bill)
ARIMA Nowcast. The econometric engine for this nowcast is known as an autoregressive integrated moving average. The technique is using only real GDP’s history, dating from the early 1970s onward, for anticipating the current quarter’s change. As the most recent quarterly GDP number is revised, so too is the ARIMA nowcast, which is calculated in R software via the “forecast” package, which optimizes the prediction model based on the data set’s historical record.
ARIMA 4 Nowcast. This model is similar to the ARIMA technique above in terms of the econometric technique, but with a key difference. Instead of using GDP’s historical data as a lone input, the ARIMA 4 model analyzes four historical data sets to predict GDP: real personal consumption expenditures, real personal income less government transfers, industrial production, and private non-farm payrolls.
VAR Nowcast. The vector autoregression model looks to several data series in search of interdependent relationships for estimating GDP. The historical data sets in the 4-factor and ARIMA 4 models above are also used to generate VAR nowcasts of GDP. As new data is published, so too is the VAR nowcast. The basic idea here is to let the data specify the model’s parameters. The data sets are based on historical records from the early 1970s, using the “vars” package for R to crunch the numbers.