This paper conducts a broad-based comparison of iterated and direct multi-step forecasting approaches applied to both univariate and multivariate models. Theoretical results and Monte Carlo simulations suggest that iterated forecasts dominate direct forecasts when estimation error is a...

This paper considers a simple model of credit risk and derives the limit distribution of losses under different assumptions regarding the structure of systematic risk and the nature of exposure or firm heterogeneity. We derive fat-tailed correlated loss distributions arising from Gaussian risk...

This paper provides a review of the literature on unit roots and cointegration in panels where the time dimension (T), and the cross section dimension (N) are relatively large. It distinguishes between the first generation tests developed on the assumption of the cross section independence, and...

This paper proposes a pair-wise approach to testing for output convergence that considers all N(N-1)/2 possible pairs of log per capita output gaps across N economies. A general probabilistic definition of output convergence is also proposed. The approach is compatible with individual output...

This paper extends the cross sectionally augmented panel unit root test proposed by Pesaran (2007) to the case of a multifactor error structure. The basic idea is to exploit information regarding the unobserved factors that are shared by other time series in addition to the variable under...

This paper considers the statistical analysis of large panel data sets where even after conditioning on common observed e¤ects the cross section units might remain dependently distributed. This could arise when the cross section units are subject to unobserved common e¤ects and/or if there are...

This paper analyzes the consequences of introducing stochastic technological progress and stochastic labor input into a Solow-Swan exogenous growth model and an 'AK' endogenous growth model with general savings and production functions.

This paper considers the problems facing decision makers using econometric models in real time. It identifies the key stages involved and highlights the role of automated systems in reducing the effect of data snooping. It sets out many choices that researchers face in construction of automated...

Autoregressive models are used routinely in forecasting and often lead to better performance than more complicated models. However, empirical evidence is also suggesting that the autoregressive representations of many macroeconomic and financial time series are likely to be subject to structural...