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.
Is China fudging its figures? Evidence from trading partner data
How reliable are China?s GDP and other data? We address this question by using trading-partner exports to China as an independent measure of its economic activity from 2000-2014. We find that the information content of Chinese GDP improves markedly after 2008. We also consider a number of plausible, non-GDP indicators of economic activity that have been identified as alternative Chinese output measures. We find that activity factors based on the first principal component of sets of indicators are substantially more informative than GDP alone. The index that best matches activity in-sample ...
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 ...
“Free” Internet Content: Web 1.0, Web 2.0, and the Sources of Economic Growth
The Internet has evolved from Web 1.0, with static web pages and limited interactivity, to Web 2.0, with dynamic content that relies on user engagement. This change increased production costs significantly, but the price charged for Internet content has generally remained the same: zero. Because no transaction records the ?purchase? of this content, its value is not reflected in measured growth and productivity. To capture the contribution of the ?free? Internet, we model the provision of ?free? content as a barter transaction between the content users and the content creators, and we value ...
Assessing the macroeconomic impact of bank intermediation shocks: a structural approach
We take a structural approach to assessing the empirical importance of shocks to the supply of bank-intermediated credit in affecting macroeconomic fluctuations. First, we develop a theoretical model to show how credit supply shocks can be transmitted into disruptions in the production economy. Second, we use the unique micro-banking data to identify and support the model's key mechanism. Third, we find that the output effect of credit supply shocks is not only economically and statistically significant but also consistent with the vector autogression evidence. Our mode estimation indicates ...
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 ...
Cyclical Lending Standards: A Structural Analysis
Lending standards are a direct measure of credit conditions. We use the micro data merged from three separate sources to construct this measure and document that an uncertain macroeconomic outlook, rather than banks' balance sheet positions, was an important reason that a majority of banks tightened bank lending standards during the Great Recession. Our extensive data analysis disciplines how we introduce credit frictions in the banking sector into a macroeconomic model. The model estimation reveals that an exogenous shock to credit supply drives cyclical lending standards and accounts for a ...
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 ...
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 ...