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Working Paper
Growth-at-Risk is Investment-at-Risk
We investigate the role financial conditions play in the composition of U.S. growth-at-risk. We document that, by a wide margin, growth-at-risk is investment-at-risk. That is, if financial conditions indicate U.S. real GDP growth will be in the lower tail of its conditional distribution, we know that the main contributor is a decline in investment. Consumption contributes under extreme financial stress. Government spending and net exports do not play a role. We show that leverage plays a key role in determining both consumption- and investment-at-risk, which provides support to the financial ...
Working Paper
Two Measures of Core Inflation: A Comparison
Trimmed-mean Personal Consumption Expenditure (PCE) inflation does not clearly dominate ex-food-and-energy PCE inflation in real-time forecasting of headline PCE inflation. However, trimmed-mean inflation is the superior communications and policy tool because it is a less-biased real-time estimator of headline inflation and because it more successfully filters out headline inflation?s transitory variation, leaving only cyclical and trend components.
Working Paper
On the Real-Time Predictive Content of Financial Conditions Indices for Growth
We provide evidence on the real-time predictive content of the National Financial Conditions Index (NFCI), for conditional quantiles of U.S. real GDP growth. Our work is distinct from the literature in two specific ways. First, we construct (unofficial) real-time vintages of the NFCI. This allows us to conduct out-of-sample analysis without introducing the kind of look-ahead biases that are naturally introduced when using a single current vintage. We then develop methods for conducting asymptotic inference on tests of equal tick loss between nested quantile regression models when the data are ...
Working Paper
Forecasting Consumption Spending Using Credit Bureau Data
This paper considers whether the inclusion of information contained in consumer credit reports might improve the predictive accuracy of forecasting models for consumption spending. To investigate the usefulness of aggregate consumer credit information in forecasting consumption spending, this paper sets up a baseline forecasting model. Based on this model, a simulated real-time, out-of-sample exercise is conducted to forecast one-quarter ahead consumption spending. The exercise is run again after the addition of credit bureau variables to the model. Finally, a comparison is made to test ...
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Real-time inflation forecasting in a changing world
This paper revisits the accuracy of inflation forecasting using activity and expectations variables. We apply Bayesian-model averaging across different regression specifications selected from a set of potential predictors that includes lagged values of inflation, a host of real activity data, term structure data, nominal data, and surveys. In this model average, we can entertain different channels of structural instability by incorporating stochastic breaks in the regression parameters of each individual specification within this average, allowing for breaks in the error variance of the ...
Working Paper
Forecasting GDP Growth with NIPA Aggregates
Beyond GDP, which is measured using expenditure data, the U.S. national income and product accounts (NIPAs) provide an income-based measure of the economy (gross domestic income, or GDI), a measure that averages GDP and GDI, and various aggregates that include combinations of GDP components. This paper compiles real-time data on a variety of NIPA aggregates and uses these in simple time-series models to construct out-of-sample forecasts for GDP growth. Over short forecast horizons, NIPA aggregates?particularly consumption and GDP less inventories and trade?together with these simple ...
Working Paper
The Labor Market Impact of a Pandemic: Validation and Application of a Do-It-Yourself CPS
The Current Population Survey (CPS) is a central source of U.S. labor market data. We show that, for a few thousand dollars, researchers can quickly design and implement their own online survey to supplement the CPS. The survey closely follows core features of the CPS, ensuring that outcomes are conceptually compatible and allowing researchers to weight and validate results using the official CPS. Yet the survey also allows for faster data collection, added flexibility and novel questions. We show that the survey provided useful estimates of U.S. labor market aggregates several weeks ahead of ...
Working Paper
Bootstrapping out-of-sample predictability tests with real-time data
In this paper we develop a block bootstrap approach to out-of-sample inference when real-time data are used to produce forecasts. In particular, we establish its first-order asymptotic validity for West-type (1996) tests of predictive ability in the presence of regular data revisions. This allows the user to conduct asymptotically valid inference without having to estimate the asymptotic variances derived in Clark and McCracken’s (2009) extension of West (1996) when data are subject to revision. Monte Carlo experiments indicate that the bootstrap can provide satisfactory finite sample size ...
Working Paper
Out-of-Sample Inference with Annual Benchmark Revisions
This paper examines the properties of out-of-sample predictability tests evaluated with real-time data subject to annual benchmark revisions. The presence of both regular and annual revisions can create time heterogeneity in the moments of the real-time forecast evaluation function, which is not compatible with the standard covariance stationarity assumption used to derive the asymptotic theory of these tests. To cover both regular and annual revisions, we replace this standard assumption with a periodic covariance stationarity assumption that allows for periodic patterns of time ...
Working Paper
Measurement Errors and Monetary Policy: Then and Now
Should policymakers and applied macroeconomists worry about the difference between real-time and final data? We tackle this question by using a VAR with time-varying parameters and stochastic volatility to show that the distinctionbetween real-time data and final data matters for the impact of monetary policy shocks: The impact on final data is substantially and systematically different (in particular, larger in magnitude for different measures of real activity) from theimpact on real-time data. These differences have persisted over the last 40 years and should be taken into account when ...