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Recurrent conditional heteroskedasticity (replication data)
We propose a new class of financial volatility models, called the REcurrent Conditional Heteroskedastic (RECH) models, to improve both in-sample analysis and out-of-sample... -
ARDL bounds test for cointegration: Replicating the Pesaran et al. (2001) res...
This paper replicates the UK earnings equation using the autoregressive distributed lag (ARDL) modeling approach and the bounds test for cointegration by Pesaran et al. (Journal... -
Extremal connectedness of hedge funds (replication data)
We propose a dynamic measure of extremal connectedness tailored to the short reporting period and unbalanced nature of hedge funds data. Using multivariate extreme value... -
Optimal forecast under structural breaks (replication data)
This paper develops an optimal combined estimator to forecast out-of-sample under structural breaks. When it comes to forecasting, using only the postbreak observations after... -
Oil prices, gasoline prices, and inflation expectations (replication data)
It has long been suspected, given the salience of gasoline prices, that fluctuations in gasoline prices shift households' 1-year inflation expectations. Assessing this view... -
Making text count: Economic forecasting using newspaper text (replication data)
This paper examines several ways to extract timely economic signals from newspaper text and shows that such information can materially improve forecasts of macroeconomic... -
How is machine learning useful for macroeconomic forecasting? (replication data)
We move beyond Is Machine Learning Useful for Macroeconomic Forecasting? by adding the how. The current forecasting literature has focused on matching specific variables and... -
Robust inference under time‐varying volatility: A real‐time evaluation of pro...
In many forecast evaluation applications, standard tests as well as tests allowing for time-variation in relative forecast ability build on... -
The role of precautionary and speculative demand in the global market for cru...
Contemporary structural models of the global market for crude oil jointly specify precautionary and speculative demand shocks as a composite shock, named a storage demand shock.... -
Generalized band spectrum estimation with an application to the New Keynesian...
This paper proposes a new method for estimating linear dynamic structural models. The proposed generalized band spectrum estimator (GBSE) generalizes band spectrum regression to... -
Nowcasting tail risk to economic activity at a weekly frequency (replication ...
This paper focuses on nowcasts of tail risk to GDP growth, with a potentially wide array of monthly and weekly information used to produce nowcasts on a weekly basis. We...
