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 distinction between real-time data and final data matters for the impact of...

We analyze the effect of measurement error in macroeconomic data on economics research using two features of the estimates of latent US output produced by the Bureau of Economic Analysis (BEA). First, we use the fact that the BEA publishes two theoretically identical estimates of latent US...

We introduce a class of large Bayesian vector autoregressions (BVARs) that allows for non-Gaussian, heteroscedastic and serially dependent innovations. To make estimation computationally tractable, we exploit a certain Kronecker structure of the likelihood implied by this class of models. We...

Survey non-response has risen in recent years which has increased the share of imputed and underreported values found on commonly used datasets. While this trend has been well-documented for earnings, the growth in non-response to government transfers questions has received far less attention....

Measurement error causes a downward bias when estimating a panel data linear regression model. The panel data context offers various opportunities to derive moment conditions that result in consistent GMM estimators. We consider three sources of moment conditions: (i) restrictions on the...

Overconfidence is a well-established bias in which someone's subjective confidence in their own judgments is systematically greater than their objective accuracy. There is abundant anecdotal evidence that overconfident people increase their exposure to risk. In this paper, we test whether...

Estimates of the most common mobility measure, the intergenerational elasticity, can be severely biased if snapshots are used to approximate lifetime income. However, little is known about biases in other popular dependence measures. We use long Swedish income series to provide such evidence for...

In this article, we have tested the volatility of the monthly returns of an equity hedge fund for changing conditional variances by using a log likelihood model. Generalized autoregressive conditional heteroskedastic models, (GARCH) with t-distributed errors, and exponential generalized...