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How the baby boomers' retirement wave distorts model‐based output gap estimat...
This paper illustrates, based on an example, the importance of consistency between empirical measurement and the concept of variables in estimated macroeconomic models. Since... -
Exploiting tail shape biases to discriminate between stable and student t alt...
The nonnormal stable laws and Student t distributions are used to model the unconditional distribution of financial asset returns, as both models display heavy tails. The... -
Ancestry and development: New evidence (replication data)
We revisit the relationship between ancestral distance and barriers to the diffusion of development by replicating previous results with a new genomic dataset on human... -
Structural estimation of behavioral heterogeneity (replication data)
We develop a behavioral asset pricing model in which agents trade in a market with information friction. Profit-maximizing agents switch between trading strategies in response... -
Dynamic factor model with infinite‐dimensional factor space: Forecasting (rep...
The paper compares the pseudo real-time forecasting performance of three dynamic factor models: (i) the standard principal component model introduced by Stock and Watson in... -
What are the macroeconomic effects of high‐frequency uncertainty shocks? (rep...
This paper evaluates the effects of high-frequency uncertainty shocks on a set of low-frequency macroeconomic variables representative of the US economy. Rather than estimating... -
Spillovers among sovereign debt markets: Identification through absolute magn...
This paper studies spillovers among US and European sovereign yields. We employ absolute magnitude restrictions on the impact matrix to identify the countries that were the main... -
UK term structure decompositions at the zero lower bound (replication data)
This paper employs a zero lower bound (ZLB) consistent shadow-rate model to decompose UK nominal yields into expectation and term premium components. Compared to a standard... -
Using a Bayesian Structural Time–Series Model to Infer the Causal Impact on C...
The Bayesian structural time series model, used in conjunction with a state–space model, is a novel means of exploring the causal impact of a policy intervention. It extends the... -
Program code for "Does compressing high school duration affect students' stre...
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