According to our survey about climate risk perceptions, institutional investors believe climate risks have financial implications for their portfolio firms and that these risks, particularly ...regulatory risks, already have begun to materialize. Many of the investors, especially the long-term, larger, and ESG-oriented ones, consider risk management and engagement, rather than divestment, to be the better approach for addressing climate risks. Although surveyed investors believe that some equity valuations do not fully reflect climate risks, their perceived overvaluations are not large.
Using data on 800,000 corporate publications and patent citations to these publications between 1980 and 2015, we study how corporate investment in research is linked to its use in the firm’s ...inventions, and to spillovers to rivals. We find that private returns to corporate research depend on the balance between two opposing forces: the benefits from the use of science in own downstream inventions, and the costs of spillovers to rivals. Consistent with this, firms produce more research when it is used internally, but less research when it is used by rivals. As firms become more sensitive to rivals using their science, they are likely to reduce the share of research in R&D.
Abstract
Building on signaling theory, the current research proposes an empirical framework to help firms understand the degree to which cross‐category purchases affect the revenue generated for each ...category and how within‐category purchases influence the cross‐category spillover effects. The framework is applied to novel individual‐level, cross‐sectional, and time‐series transaction details from a leading lifestyle conglomerate in the Middle East. The empirical results provide strong support for the presence of revenue spillover across multiple categories of brand extensions, with the spillover being more pronounced in categories in which customers have infrequently purchased and thus had less within‐category experience. These results add to the ongoing stream of research on brand extensions by offering evidence that both within‐ and cross‐category learning play a significant role in revenue generation from brand extensions for multi‐product or service firms.
Learning efficient logic programs Cropper, Andrew; Muggleton, Stephen H.
Machine learning,
07/2019, Letnik:
108, Številka:
7
Journal Article
Recenzirano
Odprti dostop
When machine learning programs from data, we ideally want to learn efficient rather than inefficient programs. However, existing inductive logic programming (ILP) techniques cannot distinguish ...between the efficiencies of programs, such as permutation sort (
n
!) and merge sort
O
(
n
l
o
g
n
)
. To address this limitation, we introduce Metaopt, an ILP system which iteratively learns lower cost logic programs, each time further restricting the hypothesis space. We prove that given sufficiently large numbers of examples, Metaopt converges on minimal cost programs, and our experiments show that in practice only small numbers of examples are needed. To learn minimal time-complexity programs, including non-deterministic programs, we introduce a cost function called
tree cost
which measures the size of the SLD-tree searched when a program is given a goal. Our experiments on programming puzzles, robot strategies, and real-world string transformation problems show that Metaopt learns minimal cost programs. To our knowledge, Metaopt is the first machine learning approach that, given sufficient numbers of training examples, is guaranteed to learn minimal cost logic programs, including minimal time-complexity programs.
We study subgame-perfect implementation (SPI) mechanisms that have been proposed as a solution to incomplete contracting problems. We show that these mechanisms, which are based on off-equilibrium ...arbitration clauses that impose large fines for lying and the inappropriate use of arbitration, have severe behavioral constraints because the fines induce retaliation against legitimate uses of arbitration. Incorporating reciprocity preferences into the theory explains the observed behavioral patterns and helps us develop a new mechanism that is more robust and achieves high rates of truth-telling and efficiency. Our results highlight the importance of tailoring implementation mechanisms to the underlying behavioral environment. (JEL C92, D44, D82, D86, D91)
Abstract
This paper investigates the effect on academic performance of an exogenous educational reform that reduced the school calendar of non‐fee‐paying schools in the Madrid region (Spain) by ...approximately two weeks, leaving the basic curriculum unchanged. To identify the consequences of such a measure, we exploit the fact that it did not affect private schools (control group) and the existence of an external cognitive test that measures academic performance before and after its application in the region. We find that the reform worsened students' educational outcomes by around 0.13 of a standard deviation. This effect was especially strong in the subjects of Spanish and Mathematics. We further explored quantile effects across the distribution of exam scores, finding that the disruption had a more negative effect on students in the upper quartile than those in the lower quartile. Overall, the analysis shows a reduction in the gap across non‐fee‐paying schools and an increase in the gap between non‐fee‐ and fee‐paying schools.
The color of pyroclasts is fundamental, because it reflects various magma properties and eruption processes, including particle morphology, chemistry, and petrological characteristics. However, ...deriving the componentry ratio (CR) of pyroclasts for ongoing eruption monitoring remains challenging due to the lack of a robust quantitative standard. The derivation of the CR, as well as other petrological analyses, is too laborious and time-consuming to introduce as a sustainable monitoring method. To address this, we employed spectroscopic colorimetry to rapidly and quantitatively describe eruptive product colors, enabling CR derivation based on clear, objective standards for ash particle classification. Through color spectroscopy of bulk and sieved ash samples, we analyzed the major size fraction for time-series samples during the waxing stage of the 2017–2018 Shinmoe-dake eruption in Kirishima volcano, Southwest Japan. Our findings reveal that the color changes in bulk ash systematically changed with the evolution of componentry. This temporal color change was due to an increase in the amount of vesicular particles with clear glass against dark angular lava particles, as well as a grain size change, which we interpret as an indication of a transition from phreatic/phreatomagmatic to magmatic eruption. Subsequently, the color of the ash changed when the amount of different lava particles increased gradually, coinciding with a shift toward a more dominant effusion of lava. As the lava effusion continued, a slight reddening of the ash, indiscernible to the naked eye, was clearly detected by the spectrometer before the onset of intermittent Vulcanian eruptions. We interpreted this reddening as oxidation resulting from decreased ascent speed and caprock formation, which accumulates overpressure for Vulcanian explosions. These results highlight the potential of rapid, objective color value and componentry derivation for sustainable quasi-real-time monitoring of ongoing eruption materials.
Graphical Abstract