Mergers & Acquisitions and Innovation Performance in the Telecommunications Equipment Industry

In response to global market forces such as deregulation and globalization, technological change and digital convergence, the telecommunications in the 1990s witnessed an enormous worldwide round of Mergers & Acquisitions (M&A). Given both M&A and Innovation a major means of today’s competitive strategy development, this paper examines the innovation determinants of M&A activity and the consequences of M&A transactions on the technological potential and the innovation performance. We examine the telecommunications equipment industry over the period 1988-2002 using a newly constructed data set with firm-level data on M&A and innovation activity as well as financial characteristics. By implementing a counterfactual technique based on a matching propensity score procedure, the analysis not only controls for merger endogeneity and ex-ante observable firms characteristics but also takes account of unobserved heterogeneity. The study provides evidence that M&A realize significantly positive changes to the firm’s post-merger innovation performance. The effects of M&A on innovation performance are in turn driven by both the success in Research and Development (R&D) activity and the deterioration in internal technological capabilities at acquiring firms prior to a merger.Mergers & Acquisitions, Innovation Performance, Telecommunications Equipment Industry.

Assessing the long-term effects of conditional cash transfers on human capital : evidence from Colombia

Conditional cash transfers are programs under which poor families get a stipend provided they keep their children in school and take them for health checks. Although there is significant evidence showing that they have positive impacts on school participation, little is known about the long-term impacts of the programs on human capital. This paper investigates whether cohorts of children from poor households that benefited up to nine years from Familias en Acción, a conditional cash transfer program in Colombia, attained more school and performed better on academic tests at the end of high school. Identification of program impacts is derived from two different strategies using matching techniques with household surveys, and regression discontinuity design using a census of the poor and administrative records of the program. The authors show that, on average, participant children are 4 to 8 percentage points more likely than nonparticipant children to finish high school, particularly girls and beneficiaries in rural areas. Regarding long-term impact on tests scores, the analysis shows that program recipients who graduate from high school seem to perform at the same level as equally poor non-recipient graduates, even after correcting for possible selection bias when low-performing students enter school in the treatment group. Although the positive impacts on high school graduation may improve the employment and earning prospects of participants, the lack of positive effects on test scores raises the need to further explore policy actions to couple the program's objective of increasing human capital with enhanced learning.Education For All,Tertiary Education,Primary Education,Secondary Education,Teaching and Learning

Assessing the Long-term Effects of Conditional Cash Transfers on Human Capital: Evidence from Colombia

Conditional Cash Transfers (CCT) are programs under which poor families get a stipend provided they keep their children in school and take them for health checks. While there is significant evidence showing that they have positive impacts on school participation, little is known about their long-term impacts on human capital. In this paper we investigate whether cohorts of children from poor households that benefited up to nine years from Familias en Acción, a CCT in Colombia, attained more school and performed better in academic tests at the end of high school. Identification of program impacts is derived from two different strategies using matching techniques with household surveys, and regression discontinuity design using census of the poor and administrative records of the program. We show that, on average, participant children are 4 to 8 percentage points more likely than nonparticipant children to finish high school, particularly girls and beneficiaries in rural areas. Regarding long-term impact on tests scores, the analysis shows that program recipients who graduate from high school seem to perform at the same level as equally poor non-recipient graduates, even after correcting for possible selection bias when low-performing students enter school in the treatment group. Even though the positive impacts on high school graduation may improve the employment and earning prospects of participants, the lack of positive effects on the test scores raises the need to further explore policy actions to couple CCT's objective of increasing human capital with enhanced learning.Conditional Cash Transfers, school completion, academic achievement, learning outcomes

Evaluating Merging Strategies for Sampling-based Uncertainty Techniques in Object Detection

There has been a recent emergence of sampling-based techniques for estimating epistemic uncertainty in deep neural networks. While these methods can be applied to classification or semantic segmentation tasks by simply averaging samples, this is not the case for object detection, where detection sample bounding boxes must be accurately associated and merged. A weak merging strategy can significantly degrade the performance of the detector and yield an unreliable uncertainty measure. This paper provides the first in-depth investigation of the effect of different association and merging strategies. We compare different combinations of three spatial and two semantic affinity measures with four clustering methods for MC Dropout with a Single Shot Multi-Box Detector. Our results show that the correct choice of affinity-clustering combination can greatly improve the effectiveness of the classification and spatial uncertainty estimation and the resulting object detection performance. We base our evaluation on a new mix of datasets that emulate near open-set conditions (semantically similar unknown classes), distant open-set conditions (semantically dissimilar unknown classes) and the common closed-set conditions (only known classes).Comment: to appear in IEEE International Conference on Robotics and Automation 2019 (ICRA 2019

Can Governments Do It Better? Merger Mania and Hospital Outcomes in the English NHS

The literature on mergers between private hospitals suggests that such mergers often produce little benefit. Despite this, the UK government has pursued an active policy of hospital merger. These mergers are initiated by a regulator, acting on behalf of the public, and justified on the grounds that merger will improve outcomes. We examine whether this promise is met. We exploit the fact that between 1997 and 2006 in England around half the short term general hospitals were involved in a merger, but that politics means that selection for a merger may be random with respect to future performance. We examine the impact of mergers on a large set of outcomes including financial performance, productivity, waiting times and clinical quality and find little evidence that mergers achieved gains other than a reduction in activity. In addition, mergers reduce the scope for competition between hospitals.

Mergers & Acquisitions and Innovation Performance in the Telecommunications Equipment Industry

The telecommunications in the 1990s witnessed an enormous worldwide round of Mergers & Acquisitions (M&A). This paper examines the innovation determinants of M&A activity and the consequences of M&A transactions on the technological potential and the innovation performance. We examine the telecommunications equipment industry over the period 1988-2002 using a newly constructed data set with firm-level data describing M&A and innovation activity as well as financial characteristics. Based on a matching propensity score procedure, the study provides evidence that M&A realize significantly positive changes to the firm's post-merger innovation performance.Mergers & Acquisitions, Innovation Performance, Telecommunications Equipment Industry

Can governments do it better? Merger mania and hospital outcomes in the English NHS

The literature on mergers between private hospitals suggests that such mergers often produce little benefit. Despite this, the UK government has pursued an active policy of hospital mergers, arguing that such consolidations will bring improvements for patients. We examine whether this promise is met. We exploit the fact that between 1997 and 2006 in England around half the short term general hospitals were involved in a merger, but that politics means that selection for a merger may be random with respect to future performance. We examine the impact of mergers on a large set of outcomes including financial performance, productivity, waiting times and clinical quality and find little evidence that mergers achieved gains other than a reduction in activity. Given that mergers reduce the scope for competition between hospitals the findings suggest that further merger activity may not be the appropriate way of dealing with poorly performing hospitals.Hospital mergers, event study, quality, political influence.

The impact of higher education institution-firm knowledge links on establishment-level productivity in British regions

This paper estimates whether sourcing knowledge from and/or cooperating on innovation with higher education institutions impacts on establishment-level TFP and whether this impact differs across domestically-owned and foreign-owned establishments and across the regions of Great Britain. Using propensity score matching, the results show overall a positive and statistically significant impact although there are differences in the strength of this impact across production and non-production industries, across domestically-owned and foreign-owned firms, and across regions. These results highlight the importance of absorptive capacity in determining the extent to which establishments can benefit from linkages with higher education institutions.Universities; University-Industry knowledge links; Firm-level productivity

Reconciliation between operational taxonomic units and species boundaries

The development of high-throughput sequencing technologies has revolutionised the field of microbial ecology via 16S rRNA gene amplicon sequencing approaches. Clustering those amplicon sequencing reads into operational taxonomic units (OTUs) using a fixed cut-off is a commonly used approach to estimate microbial diversity. A 97% threshold was chosen with the intended purpose that resulting OTUs could be interpreted as a proxy for bacterial species. Our results show that the robustness of such a generalised cut-off is questionable when applied to short amplicons only covering one or two variable regions of the 16S rRNA gene. It will lead to biases in diversity metrics and makes it hard to compare results obtained with amplicons derived with different primer sets. The method introduced within this work takes into account the differential evolutional rates of taxonomic lineages in order to define a dynamic and taxonomic-dependent OTU clustering cut-off score. For a taxonomic family consisting of species showing high evolutionary conservation in the amplified variable regions, the cut-off will be more stringent than 97%. By taking into consideration the amplified variable regions and the taxonomic family when defining this cut-off, such a threshold will lead to more robust results and closer correspondence between OTUs and species. This approach has been implemented in a publicly available software package called DynamiC