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An inflated multivariate integer count hurdle model: an application to bid an...
In this paper we develop a model for the conditional inflated multivariate density of integer count variables with domain n, n. Our modelling framework is based on a copula... -
Measuring forecast uncertainty by disagreement: The missing link (replication...
Using a standard decomposition of forecast errors into common and idiosyncratic shocks, we show that aggregate forecast uncertainty can be expressed as the disagreement among... -
Combining forecast densities from VARs with uncertain instabilities (replicat...
Recursive-weight forecast combination is often found to an ineffective method of improving point forecast accuracy in the presence of uncertain instabilities. We examine the... -
Path forecast evaluation (replication data)
A path forecast refers to the sequence of forecasts 1 to H periods into the future. A summary of the range of possible paths the predicted variable may follow for a given... -
Forecast evaluation of small nested model sets (replication data)
We propose two new procedures for comparing the mean squared prediction error (MSPE) of a benchmark model to the MSPEs of a small set of alternative models that nest the... -
Forecast comparisons in unstable environments (replication data)
We propose new methods for comparing the out-of-sample forecasting performance of two competing models in the presence of possible instabilities. The main idea is to develop a... -
A comparison of forecast performance between federal reserve staff forecasts,...
This paper considers the real-time-- forecast performance of the Federal Reserve staff, time-series models, and an estimated dynamic stochastic general equilibrium (DSGE)... -
Extracting a robust US business cycle using a time-varying multivariate model...
We develop a flexible business cycle indicator that accounts for potential time variation in macroeconomic variables. The coincident economic indicator is based on a... -
Introducing the euro-sting: Short-term indicator of euro area growth (replica...
We set out a model to compute short-term forecasts of the euro area GDP growth in real time. To allow for forecast evaluation, we construct a real-time dataset that changes for... -
What do we learn from the price of crude oil futures? (replication data)
Despite their widespread use as predictors of the spot price of oil, oil futures prices tend to be less accurate in the mean-squared prediction error sense than no-change... -
Steady-state priors for vector autoregressions (replication data)
Bayesian priors are often used to restrain the otherwise highly over-parametrized vector autoregressive (VAR) models. The currently available Bayesian VAR methodology does not... -
Risk of catastrophic terrorism: an extreme value approach (replication data)
This paper models the stochastic behavior of large-scale terrorism using extreme value methods. We utilize a unique dataset composed of roughly 26,000 observations. These data... -
On portfolio optimization: How and when do we benefit from high-frequency dat...
We examine how the use of high-frequency data impacts the portfolio optimization decision. Prior research has documented that an estimate of realized volatility is more precise... -
On the effect of prior assumptions in Bayesian model averaging with applicati...
We consider the problem of variable selection in linear regression models. Bayesian model averaging has become an important tool in empirical settings with large numbers of... -
Assessing the prudence of economic forecasts in the EU (replication data)
We estimate the EU Commission loss preferences for major economic forecasts of 12 Member States. Based on a recently proposed method by Elliott, Komunjer and Timmermann (2005)... -
Feasible estimation of firm-specific allocative inefficiency through Bayesian...
Both the theoretical and empirical literature on the estimation of allocative and technical inefficiency has grown enormously. To minimize aggregation bias, ideally one should... -
Boosting diffusion indices (replication data)
In forecasting and regression analysis, it is often necessary to select predictors from a large feasible set. When the predictors have no natural ordering, an exhaustive... -
A nonparametric decomposition of the Mexican American average wage gap (repli...
This paper shows that average wage gap decompositions between any two groups of workers can be carried out using nonparametric wage structures. It also proposes an algorithm to... -
An alternative approach to estimate the wage returns to private-sector traini...
This paper follows an alternative approach to identify the wage effects of private-sector training. The idea is to narrow down the comparison group by only taking into... -
Comparing smooth transition and Markov switching autoregressive models of US ...
Logistic smooth transition and Markov switching autoregressive models of a logistic transform of the monthly US unemployment rate are estimated by Markov chain Monte Carlo...
