In this paper, we propose a simple methodology for investigating how shocks to trend and cycle are correlated in unidentified unobserved components models, in which the correlation is not identified. The proposed methodology is applied to U.S. and U.K. real GDP data. We find that the correlation...

This paper derives unbalanced versions of the test statistics for first- order serial correlation and random individual effects summarized in Sosa-Escudero and Bera (2001, Stata Technical Bulletin Reprints, vol. 10, pp. 307–311), and up- dates their xttest1 routine. The derived test statistics...

This article proposes a memory-saving decomposition of the design matrix to facilitate the estimation of a linear model with two high-dimensional fixed effects. A common way to fit such a model is to take into account one of the effects by including dummy variables and to sweep out the other...

A coincident business cycle indicator for the Milan area is built on the basis of a monthly industrial survey carried out by Assolombarda, the largest territorial entrepreneurial association in Italy. The indicator is extracted from three time series concerning the production level and the...

We propose two indexes to measure the agglomeration forces acting within and between different regions. Unlike the existing measures of agglomeration, our model-based indexes allow for simultaneous treatment of both aspects. Local plant diffusion in a given industry is modelled as a spatial...

Drawing on the conceptual foundations of feedback and behavior modeling we investigate the effects of managers' coaching intensity on the performance of those they supervise, at multiple levels of an organizational hierarchy. Data from 328 sales associates reporting to 114 middle managers, and...

The relative importance of permanent versus cyclical shocks to GDP has been found to depend on the presence or absence of a single break in mean growth. We estimate unobserved components models conditional on a trend break having occurred in any specified quarter and use the Bayesian model...