Hungary: ten years of the new economic mechanism

SIGLELD:8318.172(SSRC-HR--5528) / BLDSC - British Library Document Supply CentreGBUnited Kingdo

Board Share-Ownership and Takeover Performance

We investigate the relation between takeover performance and board share-ownership in the acquiring company for a sample of 363 UK takeovers completed in the period 1985-96. In investigating this relationship we pay particular attention to the composition of board shareholdings as well as their size. Thus, in addition to the analysis of total board holdings, we analyse the separate impact of CEO shareholdings and of the pattern of non-executive and executive holdings within the board. In addition to our detailed examination of board holdings we assess the impact of non-board holdings. Our analysis controls for a number of non-shareholding constraints on discretionary director behaviour and for a variety of other influences on takeover outcomes including: the means of payment; acquirer size and market to book value; the relative size of the acquirer and the target; the nature of the bid in terms of hostility and industrial direction; and the pre-takeover performance of the acquiring company. We assess performance in terms of announcement returns, long run share returns and a portfolio of accounting measures. We find evidence that overall board ownership has a strong positive impact on long run share returns and a weak positive impact on operating performance. However, much stronger effects are found when the overall board measure is split into CEO, executive, and non-executive directors. We find strong evidence of a positive relation between takeover performance and CEO ownership, which holds for both long run returns and operating performance measures. This finding is robust to controlling for other factors that determine takeover performance and holds in a two stage least squares framework that controls for endogeneity effects. Shareholdings of other executive directors, non-executive directors, and non-board holdings are found to have no significant effect on takeover performance. Copyright Blackwell Publishers Ltd, 2006.

Pleiotropy-guided transcriptome imputation from normal and tumor tissues identifies candidate susceptibility genes for breast and ovarian cancer

Familial, sequencing, and genome-wide association studies (GWASs) and genetic correlation analyses have progressively unraveled the shared or pleiotropic germline genetics of breast and ovarian cancer. In this study, we aimed to leverage this shared germline genetics to improve the power of transcriptome-wide association studies (TWASs) to identify candidate breast cancer and ovarian cancer susceptibility genes. We built gene expression prediction models using the PrediXcan method in 681 breast and 295 ovarian tumors from The Cancer Genome Atlas and 211 breast and 99 ovarian normal tissue samples from the Genotype-Tissue Expression project and integrated these with GWAS meta-analysis data from the Breast Cancer Association Consortium (122,977 cases/105,974 controls) and the Ovarian Cancer Association Consortium (22,406 cases/40,941 controls). The integration was achieved through application of a pleiotropy-guided conditional/conjunction false discovery rate (FDR) approach in the setting of a TWASs. This identified 14 candidate breast cancer susceptibility genes spanning 11 genomic regions and 8 candidate ovarian cancer susceptibility genes spanning 5 genomic regions at conjunction FDR 1 Mb away from known breast and/or ovarian cancer susceptibility loci. We also identified 38 candidate breast cancer susceptibility genes and 17 candidate ovarian cancer susceptibility genes at conjunction FDR < 0.05 at known breast and/or ovarian susceptibility loci. The 22 genes identified by our cross-cancer analysis represent promising candidates that further elucidate the role of the transcriptome in mediating germline breast and ovarian cancer risk