Industry Structure Similarities, Trade Agreements, and Business Cycle Synchronization

This paper analyzes the effects of industry structure similarities, free trade agreements, and geographic borders on regional business cycle correlation, using fifty US states, 10 Canadian provinces, and 1 Canadian territory as a case study. Using two cross-sectional OLS regressions and one panel data OLS regression, this study finds that pair-wise gross territorial product growth correlation decreased significantly after NAFTA ratification for state-state, province-province, and state-province territorial pairs, contrary to previous literature’s results. NAFTA effectively decoupled intra-national business cycles in the US and Canada while also desynchronizing cross-border pair-wise GSP growth correlation, but cross-border pair-wise GSP growth correlation was much less desynchronized post-NAFTA relative to intra-national pairs. These results indicate that NAFTA and the US-Canada border may produce two opposing forces that dampen each other’s desynchronizing effects

Modified Linear Projection for Large Spatial Data Sets

Recent developments in engineering techniques for spatial data collection such as geographic information systems have resulted in an increasing need for methods to analyze large spatial data sets. These sorts of data sets can be found in various fields of the natural and social sciences. However, model fitting and spatial prediction using these large spatial data sets are impractically time-consuming, because of the necessary matrix inversions. Various methods have been developed to deal with this problem, including a reduced rank approach and a sparse matrix approximation. In this paper, we propose a modification to an existing reduced rank approach to capture both the large- and small-scale spatial variations effectively. We have used simulated examples and an empirical data analysis to demonstrate that our proposed approach consistently performs well when compared with other methods. In particular, the performance of our new method does not depend on the dependence properties of the spatial covariance functions.Comment: 29 pages, 5 figures, 4 table

c=1 Matrix Models: Equivalences and Open-Closed String Duality

We give an explicit demonstration of the equivalence between the Normal Matrix Model (NMM) of c=1 string theory at selfdual radius and the Kontsevich-Penner (KP) model for the same string theory. We relate macroscopic loop expectation values in the NMM to condensates of the closed string tachyon, and discuss the implications for open-closed duality. As in c<1, the Kontsevich-Miwa transform between the parameters of the two theories appears to encode open-closed string duality, though our results also exhibit some interesting differences with the c<1 case. We also briefly comment on two different ways in which the Kontsevich model originates.Comment: 27 pages, latex, 1 figure, typos, discussion added, acknowledgements update

EEMCS final report for the causal modeling for air transport safety (CATS) project

This document reports on the work realized by the DIAM in relation to the completion of the CATS model as presented in Figure 1.6 and tries to explain some of the steps taken for its completion. The project spans over a period of time of three years. Intermediate reports have been presented throughout the project’s progress. These are presented in Appendix 1. In this report the continuous‐discrete distribution‐free BBNs are briefly discussed. The human reliability models developed for dealing with dependence in the model variables are described and the software application UniNet is presente