Search

This paper examines the effect of peers on a firm's research and development (R&D) policy. We show that firms do not make R&D decisions in isolation, and that industry dynamics play an important role in defining a firm's R&D intensity. Using a large sample of 54,393 firm‐year observations from 1991 to 2015 in the United States, we find that firms' R&D decisions are mainly driven by their industry peers' R&D policies. Moreover, we find that R&D mimicking is significant only in the presence of strong product market competition, whereas we do not find any evidence of information‐based herding in R&D investments. Our additional analysis shows that our main conclusions remain valid even in the presence of financial constraints, and regardless of the firms' market positions. Finally, we provide evidence that R&D mimicking increases firms' future values, future patent outputs, and estimated patent dollar values. Our findings are robust to endogeneity concerns, and to using alternative sample compositions, R&D intensity proxies, and different industry classifications. [ABSTRACT FROM AUTHOR]

This paper investigates the tone newspapers use in reporting information on a company that it is linked with through an ownership tie. Our empirical setting is Italy, a country characterized by dominant national industrial groups' high ownership of newspapers. Based on a sample of about 123,000 articles, we document that newspapers' coverage of firms in conflict of interest is greater, with significantly fewer negative and uncertain words. We also document that the slant increases with ownership stakes and decreases with the newspaper's reputation. [ABSTRACT FROM AUTHOR]

Objective. To evaluate the benefit of pharmacogenetics in antidepressant treatment. Methods. In a simulated trial 100,000 subjects in a current episode of major depressive disorder (MDD) received citalopram or bupropion based on the clinician's decision (algorithm A) or following indications from 5-HTTLPR genetic testing (algorithm B), which effect size of was estimated from a meta-analysis of pharmacogenetic trials. A and B were compared in a cost-utility analysis (12 weeks). Costs (international $$, 2010) were drawn from official sources. Treatment effects were expressed as quality-adjusted life weeks (QALWs). Outcome was incremental cost-effectiveness ratio (ICER). Results. Under base-case conditions, genetic test use was associated with increases in antidepressant response (0.062 QALWs) and tolerability (0.016 QALWs) but cost benefit was not acceptable (ICER == $$2,890; $$1,800-$$4,091). However, when the joint effect on antidepressant response and tolerability was analyzed in two recurrent episodes, ICER dropped to $$1,392 ($$837-$$1,982). Cost-effectiveness acceptability curve (CEAC) showed a >80% probability that ICER value fell below the commonly accepted 3 times Gross Domestic Product (GDP) threshold (World Health Organization) and therefore suggesting cost-effectiveness. Conclusion. Notwithstanding some caveats (exclusion of gene-gene and gene-environment interactions; simple 5-HTTLPR architecture), this simulation is favourable to incorporate pharmacogenetic test in antidepressant treatment. [ABSTRACT FROM AUTHOR]

The positive market reaction at the announcement of most European rights issues can be explained by two major factors which distinguish them from a US public offering: active insiders, and a quasi-split effect which signals a large increase in the dividend yield. An analysis of 428 Italian rights offerings and an event study involving 82 observations in the 1980-94 period show that Italian insiders are completely 'active', and almost 85% of the equity rights issues result in a dividend yield increase, which corresponds to the quasi-split effect in approximately 40% of the issues. The dividend yield rises, on average, by a significant +61% after a combined rights offering and by a significantly lower +20% following a fully-paid rights issue. The market reaction to the announcement is significantly positive for combined rights" offerings" (+2.77%) and positive, but not significant, for the whole sample (+0.79%). The dividend increase signalled by the quasi-split effect explains almost 30% of the abnormal returns' cross-sectional variation and it is" the only significant explanatory variable. [ABSTRACT FROM AUTHOR]

Abstract: In major depression, when a first antidepressant does not cause remission of symptoms (60%–75%), there are several options for continuing treatment in the next step. This study is a cost-utility analysis (CUA) of different second-line approaches. In a simulated trial outpatients with MDD were treated with citalopram for 13 weeks (level 1), then based on two alternative algorithms implemented from the Sequenced Treatment Alternatives to Relieve Depression (STAR*D) study. Algorithm A: citalopram was continued until study endpoint (week 26). Algorithm B: patients who remitted during level 1 continued citalopram. Those who did not remit could opt for switching to another antidepressant (venlafaxine; sertraline) (b1) or adding bupropion to citalopram treatment (augmentation; b2). Algorithm B increased remission rate by 10.6% over Algorithm A (number needed to treat: 9.9; sensitivity range: 9.1–12.5). As a comparison, differences between active antidepressants and placebo are associated with NNT values of 6 to 8. In CUA Algorithm B was dominant with an ICER of $11,813 (sensitivity range=$1783 – $21,784), which is <1GDP per capita cost-effectiveness threshold (USA=$47,193). Among Algorithm B options, switching (b1) dominated Algorithm A with a smaller number of responders than augmentation approach (b2) (NNT 11 vs. 7.7), whereas ICER values were similar (b1: $14,738; b2: $15,458). However we cannot exclude a bias in selecting second treatment. This cost-utility analysis shows (in line with current guidelines) a benefit in modifying antidepressant treatment if response to first-line agent does not occur within 3 months, but not a clear-cut evidence in terms of NNT. [Copyright &y& Elsevier]