The use and abuse of \"real-time\" data in economic forecasting
We distinguish between three different ways of using real-time data to estimate forecasting equations and argue that the most frequently used approach should generally be avoided. The point is illustrated with a model that uses monthly observations of industrial production, employment, and retail sales to predict real GDP growth. When the model is estimated using our preferred method, its out-of-sample forecasting performance is clearly superior to that obtained using conventional estimation, and compares favorably with that of the Blue-Chip consensus.
Data Revisions of Aggregate Hours Worked: Implications for the Europe-U.S. Hours Gap
In this article, we document that the Organisation for Economic Co-operation and Development (OECD) and the Conference Board?s Total Economy Database (TED) have substantially revised their measures of hours worked over time. Relying on the data used by Rogerson (2006) and Ohanian et al. (2008), we find that, for 2003, hours worked per person in Europe is 18 percent lower than hours worked in the United States. Using the 2016 releases of the same data for 2003 yields a gap that is 40 percent smaller?that is, only 11 percent lower. Using labor force survey data, which are less subject to data ...
Raiders of the Lost High-Frequency Forecasts: New Data and Evidence on the Efficiency of the Fed's Forecasting
We introduce a new dataset of real gross domestic product (GDP) growth and core personal consumption expenditures (PCE) inflation forecasts produced by the staff of the Board of Governors of the Federal Reserve System. In contrast to the eight Greenbook forecasts a year the staff produces for Federal Open Market Committee (FOMC) meetings, our dataset has roughly weekly forecasts. We use these new data to study whether the staff forecasts efficiently and whether efficiency, or lack thereof, is time-varying. Prespecified regressions of forecast errors on forecast revisions show that the staff's ...
The Anatomy of Financial Vulnerabilities and Crises
We extend the framework used in Aikman, Kiley, Lee, Palumbo, and Warusawitharana (2015) that maps vulnerabilities in the U.S. financial system to a broader set of advanced and emerging economies. Our extension tracks a broader set of vulnerabilities and, therefore, captures signs of different types of crises. The typical anatomy of the evolution of vulnerabilities before and after a financial crisis is as follows. Pressures in asset valuations materialize, and a build-up of imbalances in the external, financial, and nonfinancial sectors follows. A financial crisis is typically followed by a ...
Measuring Aggregate Housing Wealth : New Insights from an Automated Valuation Model
We construct a new measure of aggregate U.S. housing wealth based on Zillow's Automated Valuation Model (AVM). AVMs offer advantages over other methods because they are based on recent market transaction prices, utilize large datasets which include property characteristics and local geographic variables, and are updated frequently with little lag. However, using Zillow's AVM to measure aggregate housing wealth requires overcoming several challenges related to the representativeness of the Zillow sample. We propose methods that address these challenges and generate a new estimate of aggregate ...
FRED-QD: A Quarterly Database for Macroeconomic Research
In this paper we present and describe a large quarterly frequency, macroeconomic database. The data provided are closely modeled to that used in Stock and Watson (2012a). As in our previous work on FRED-MD, our goal is simply to provide a publicly available source of macroeconomic “big data” that is updated in real time using the FRED database. We show that factors extracted from this data set exhibit similar behavior to those extracted from the original Stock and Watson data set. The dominant factors are shown to be insensitive to outliers, but outliers do affect the relative influence ...
The domestic segment of global supply chains in China under state capitalism
This paper proposes methods to incorporate firm heterogeneity in the standard IO-table based approach to portray the domestic segment of global value chains in a country. Using Chinese firm census data for both manufacturing and service sectors, along with constrained optimization techniques, we split the conventional IO table into sub-accounts, which are used to estimate direct and indirect domestic value added in exports of different types of firm. We find that in China, both state-owned enterprises (SOEs) and small and medium domestic private enterprises (SMEs) have much higher shares of ...
Sourcing substitution and related price index biases
We define a class of bias problems that arise when purchasers shift their expenditures among sellers charging different prices for units of precisely defined and interchangeable product items that are nevertheless regarded as different for the purposes of price measurement. For business-to-business transactions, these shifts can cause sourcing substitution bias in the Producer Price Index (PPI) and the Import Price Index (MPI), as well as potentially in the proposed new true Input Price Index (IPI). Similarly, when consumers shift their expenditures for the same products temporally to take ...
FRED-QD: A Quarterly Database for Macroeconomic Research
In this article, we present and describe FRED-QD, a large, quarterly frequency macroeconomic database that is currently available and regularly updated at https://research.stlouisfed.org/econ/mccracken/fred-databases/. The data provided are closely modeled to that used in Stock and Watson (2012a). As in our previous work on FRED-MD (McCracken and Ng, 2016), which is at a monthly frequency, our goal is simply to provide a publicly available source of macroeconomic "big data" that is updated in real time using the FRED® data service. We show that factors extracted from the FRED-QD dataset ...
Communicating Data Uncertainty: Multi-Wave Experimental Evidence for UK GDP
Economic statistics are commonly published without any explicit indication of their uncertainty. To assess if and how the UK public interprets and understands data uncertainty, we conduct two waves of a randomized controlled online experiment. A control group is presented with the headline point estimate of GDP, as emphasized by the statistical office. Treatment groups are then presented with alternative qualitative and quantitative communications of GDP data uncertainty. We find that most of the public understands that uncertainty is inherent in official GDP numbers. But communicating ...