Hasil untuk "Economics as a science"

K. Rennert, F. Errickson, Brian C. Prest et al.

The social cost of carbon dioxide (SC-CO2) measures the monetized value of the damages to society caused by an incremental metric tonne of CO2 emissions and is a key metric informing climate policy. Used by governments and other decision-makers in benefit–cost analysis for over a decade, SC-CO2 estimates draw on climate science, economics, demography and other disciplines. However, a 2017 report by the US National Academies of Sciences, Engineering, and Medicine1 (NASEM) highlighted that current SC-CO2 estimates no longer reflect the latest research. The report provided a series of recommendations for improving the scientific basis, transparency and uncertainty characterization of SC-CO2 estimates. Here we show that improved probabilistic socioeconomic projections, climate models, damage functions, and discounting methods that collectively reflect theoretically consistent valuation of risk, substantially increase estimates of the SC-CO2. Our preferred mean SC-CO2 estimate is $185 per tonne of CO2 ($44–$413 per tCO2: 5%–95% range, 2020 US dollars) at a near-term risk-free discount rate of 2%, a value 3.6 times higher than the US government’s current value of $51 per tCO2. Our estimates incorporate updated scientific understanding throughout all components of SC-CO2 estimation in the new open-source Greenhouse Gas Impact Value Estimator (GIVE) model, in a manner fully responsive to the near-term NASEM recommendations. Our higher SC-CO2 values, compared with estimates currently used in policy evaluation, substantially increase the estimated benefits of greenhouse gas mitigation and thereby increase the expected net benefits of more stringent climate policies. Coupling advances in socioeconomic projections, climate models, damage functions and discounting methods yields an estimate of the social cost of carbon of US$185 per tonne of CO2—triple the widely used value published by the US government.

W. Adger, S. Dessai, M. Goulden et al.

A. Abbasi, Suprateek Sarker, Roger H. L. Chiang

A. Eagly, Linda L. Carli

H. Simon

E. Miguel, Colin Camerer, K. Casey et al.

Emmanuel Oyasor

Investors are generally concerned about the share prices of listed firms as they depict the risk-return characteristics of their investments. The study examined firm-specific and macro-economic determinants of share pricing of listed firms in Nigeria. The study focused the listed consumer goods firms and data which were extracted from the audited annual report of eighteen (18) firms from 2010 to 2022. Macro-economic data were also obtained from World Bank Database and the Central Bank of Nigeria statistical bulletin. Two-step System Generalized Method of Moments (GMM) was used to analyze the data. Findings showed positive effects of dividend payout and leverage, on share prices at 1% and 5% significant levels respectively. Return on assets and firm growth was found to have had negative, effect on share prices at 1% and 10% significant level, respectively. Also, money supply had negative effect at 1% significant level, while crude oil price had positive effect at 10% significant level. The result further showed that political event had negative effect on share prices at 1% significant level. The study concluded that firm-specific factors and macro-economic variables significantly influence share prices of listed consumer goods firms in Nigeria. The study recommended that potentials investors should monitor the movement of dividend payout, leverage, and return on asset, firm growth, money supply and crude oil price when making investment decision in the sector

Milica Inđić, Aleksandra Marcikić Horvat, Milos Pjanić

By examining intermediate, operating, and profitability aspects, this paper aims to construct a performance model for evaluating the relative efficiency and potential for improvement of 20 banks operating in Serbia for the 2022-2023 period. Data Envelopment Analysis (DEA), which belongs to relatively new data-oriented techniques, was used in the research to measure efficiency. To achieve its goals, the paper makes use of the CCR and BCC, two fundamental DEA models, and three approaches: intermediary, operating and profitability. The results of the analysis showed that the highest efficiency can be attributed o the use of the intermediate approach, while the lowest efficiency of banks can be attributed to the profitability approach. Additionally, the BCC model has higher efficiency compared to the CCR model. According to the analysis results, efficiency has generally grown and is comparatively stable.

Julija Mosina, Grigorij Žilinskij

Pairs trading has been a successful tool for traders since its inception in the 1980s and has evolved significantly with the introduction of algorithmic, machine, and AI trading. This evolution has compli­cated the implementation of this strategy that traditionally benefits institutional or specialized investors. Despite this, the simplicity of pairs trading remains accessible, indicating potential benefits for ordinary traders. By focusing on the strategy’s fundamental principles and employing a real-time market test on a popular trading platform, the study aims to reveal its applicability and efficacy for short-term equity trading. Utilizing basic trading platform tools and Excel functions, the research aims to demonstrate a simplified approach to pairs trading. The findings will provide insights into the strategy’s effectiveness, providing non-expert traders with a viable approach to navigate today’s volatile markets through a simplified yet effective pairs trading model. The experiment’s findings highlight varying performances across different stock pairs, with notable differences in volatility. While five out of 11 pairs achieved positive returns, only two met the closure criteria within the short-term horizon, suggesting that a longer trading period and a more diversified pair’s portfolio may be necessary to fully capture expected price convergence.

DUNE Collaboration, A. Abed Abud, R. Acciarri et al.

The Pandora Software Development Kit and algorithm libraries perform reconstruction of neutrino interactions in liquid argon time projection chamber detectors. Pandora is the primary event reconstruction software used at the Deep Underground Neutrino Experiment, which will operate four large-scale liquid argon time projection chambers at the far detector site in South Dakota, producing high-resolution images of charged particles emerging from neutrino interactions. While these high-resolution images provide excellent opportunities for physics, the complex topologies require sophisticated pattern recognition capabilities to interpret signals from the detectors as physically meaningful objects that form the inputs to physics analyses. A critical component is the identification of the neutrino interaction vertex. Subsequent reconstruction algorithms use this location to identify the individual primary particles and ensure they each result in a separate reconstructed particle. A new vertex-finding procedure described in this article integrates a U-ResNet neural network performing hit-level classification into the multi-algorithm approach used by Pandora to identify the neutrino interaction vertex. The machine learning solution is seamlessly integrated into a chain of pattern-recognition algorithms. The technique substantially outperforms the previous BDT-based solution, with a more than 20\% increase in the efficiency of sub-1\,cm vertex reconstruction across all neutrino flavours.

P. A. Nechaeva, G. R. Yusupova

In the modern economy, digitalization has become one of the key components of the Russian Federation regions socio-economic development. Enterprises of various industries are faced with the need to process large amounts of data, which greatly complicates data management, and therefore the relevance of the analysis of artificial intelligence technologies increases. Training employees for industrial processes is a major challenge in any industry. Effective human resource management requires an accurate assessment and presentation of available competencies, as well as an effective mapping of the required competencies for specific positions. Competences enable the company to achieve high production and economic results.   The aim of the study is to develop a structural model of a predictive expert system for managing data on the competencies of a modern manager by combining artificial and human intelligence, which can serve as a decision support tool for managers in real conditions to improve the efficiency of a particular enterprise.   The study of the demand for managers and requirements for candidates in the Russian Federation and the Republic of Tatarstan was conducted on the data of the largest Russian Internet recruitment company HeadHunter. To develop a structural model of the proposed expert system, information from specialized scientific publications published in the Russian and foreign scientific literature of the Web of science and Scopus databases was used. The expert system will allow the manager to find the best options for using employees, predict the development of the enterprise as a whole and its individual divisions, which will significantly increase the key performance indicators of any company.

ILIE (MARIN) NICOLETA, TODERASC STEFAN ALIN, OPREA IULIA ALEXANDRA

Digital transformation represents one of the most current points of interest for the European Union. However, in agriculture, is digitalization a reality of the present or just a vision for the future? More and more processes are integrating into modern agriculture as offline and online activities increasingly converge in today's transition to digital agriculture. As the entire process is continuously developing, real opportunities emerge for all countries. A resilient agriculture that offers a secure future, based on minimal resources and sustainability, can only be built through a common concentration of efforts. Digital technologies have the potential to revolutionize agriculture and help farmers work more precisely, efficiently, and sustainably. Perspectives created from concrete data can improve decision-making processes and performance in favor of the environment, making the job itself more attractive to the new generations of farmers. Digital technologies also provide increased transparency for end consumers throughout the distribution chain. The digitalization of Romanian agriculture can represent a turning point towards development at its true capacity, even in the current small-scale context. This paper aims to outline the opportunities and limitations that may arise on the path towards the digitalization of Romanian agriculture.

Janaska Nurrachmat

Purpose This study aims to investigate the relationship between market power and firms’ performance in the Indonesian manufacturing industry.   Design/methodology/approach Using the Statistik Industri Besar dan Sedang from BPS we extract the data about the market share and productivity of each firm that will represent market power and the firms’ performance respectively. The dataset also allows us to apply dynamic panel data that might address the endogeneity and reverse causality problem which could occur in the estimation.   Findings The results suggest that market power has an inverted U-shaped relationship with firms’ productivity. Further analysis shows similar conditions also occur in all selected industries except automotive.   Research limitations/implications This study could help policymakers if they want to influence firms’ performance based on their market share.   Originality/value This paper applies the DPD method to address the endogeneity problem that might occur in the previous studies.

Sabirin Sabirin, Aulia Azimi, Harry Wahyudi

Tujuan penelitian ini adalah untuk mengetahui pengaruh etika profesi auditor dan fee audit terhadap kualitas audit. Desain / metodologi / pendekatan: dalam penelitian ini dilakukan analisis statistik deskriptif dengan pendekatan kuantitatif yang menggunakan teknik analisis regresi linear berganda dengan alat analisis SPSS 24. Temuan Penelitian: Hasil dari penelitian ini menunjukkan bahwa etika profesi dan fee audit memiliki pengaruh terhadap kualitas audit. Kontribusi Teoretis / Orisinalitas: Perbedaan penelitian ini dengan penelitian sebelumnya adalah pada teknik analisis yang digunakan, selain itu objek penelitian juga berbeda, pada penelitian ini yang menjadi objek penelitian adalah Kantor Akuntan Publik yang berada di Kota Pontianak dan Bandung dan struktur bisnis yang kompleks sehingga menjadikan penelitian layak untuk diteruskan. Berdasarkan permasalahan di atas, dan melihat pentingnya etika profesi serta sangat sensitifnya fee audit penulis tertarik untuk meneliti kembali dengan fokus KAP di Pontianak Bandung sebagai responden. Keterbatasan dan implikasi penelitian: Peneliti menyadari keterbatasan dalam penelitian ini yang tentunya memerlukan perbaikan dan pengembangan untuk penelitian selanjutnya. Keterbatasan dalam penelitian ini adalah Variabel independen dalam penelitian belum memberikan kontribusi yang baik terhadap variabel dependen. Hal tersebut terlihat dari analisis koefisien determinasi dimana nilai R2 sebesar 66,6%. Sisanya sebesar 33.4% dipengaruhi oleh variabel lain diluar model ini sehingga disarankan bagi peneliti selanjutnya untuk menambahkan variabel-variabel independen yang secara teoritis dapat berpengaruh lebih besar terhadap kualitas audit. Selain itu data yang dikumpulkan untuk diteliti dan dianalisis berdasarkan pada persepsi masing-masing responden terhadap item-item instrumen penelitian sehingga dapat memungkinkan terjadinya bias atau miss perseption.

Iryna Poruchynska, Volodymyr Poruchynsky, Andrij Slashchyk

У статті досліджено різні погляди науковців відносно змісту понять «бренд» та «брендинг». Узагальнено визначення поняття «спортивний бренд», як ресурсу, на основі якого реалізується функція впливу на цілісне сприйняття і споживчий вибір. Визначено, що серед спортивних брендів сучасності важлива роль надлежить футбольним брендам. З’ясовано фактори, які впливають на вартість бренду футбольного клубу. Виокремлено складові елементи бренду футбольного клубу, які забезпечують його максимальну унікальність для створення єдиного образу мислення споживачів. Подано рейтинг найдорожчих футбольних брендів світу у 2022 році за даними консалтингової компанії з оцінки брендів Brand Finance. Охарактеризовно особливості розвитку найдорожчих футбольних брендів у 2021-2022 років. Зазначено, що основним завданням маркетингу для футбольних брендів є покращення їх іміджу, враховуючи соціально-економічні та політичні умови, які мають найбільший вплив.

Dmitry Petrenko, Marina Dolzhikova, Alexander Kudrya et al.

The article is devoted to the study of the humanistic approach in school physical education with the aim of turning the school towards a child, respecting his personality, dignity, trust in him, accepting his personal goals, demands and interests, creating the most favorable conditions for revealing his physical abilities and developing his abilities in physical culture and sport, as well as for its successful self-determination in life, the realization of a healthy lifestyle.

N. S. Evsegneeva

The article was prepared on the basis of the results of the sociological research “Social networks and electoral potential”. The research methods included conducting focus groups involving young people aged 17 to 25 and subsequent content analysis of the data obtained. The purpose of the survey was to identify the opinion of young people about the heroes of our time, the concept of heroism and heroic professions. The study is unique in its analysis of the blogosphere and bloggers from the point of view of contemporary heroism and the identification of the social networks role in this process. The results of the study showed that Generation Z is striving to acquire a social mission in their activities and the theme of heroism moves into the plane of everyday life: everyone can become a hero.

Nikolay Chepachenko, Marina Yudenko, Anna Gospodinova et al.

The current trend of globalization of the world economy necessitates the use of high-tech developments and innovations that allow achieving strategic goals at the national, regional, and sectoral levels. The prerequisites of the study are determined by the urgency of finding solutions to problematic issues of formation and implementation of priority strategic guidelines for the development of enterprises of the construction sector, designed to ensure an adequate contribution to the strategic vector of advanced industrial, technological and socio-economic development of the construction industry and the national economy. This determines the need to find a solution to the problem of forming and implementing priority strategic guidelines for the development of enterprises mainly by increasing technological and innovative potentials that form the economic potential of the development of enterprises by the type of activity "Construction". The purpose of the study is to identify strategic guidelines for the development of enterprises of the construction sector that meet the targets of the fourth scientific and technological revolution and the achievement of strategic goals for the development of national economies. The findings of the paper outline the key signs of development, inherent in the nature of the development of material objects and economic entities of the economy are revealed. This allowed us to propose a systematization of the formation of priority strategic guidelines for the economic development of construction enterprises, reflecting the relationship with the targets for achieving national goals and strategic objectives for the development of economies of various countries and meeting the targets of the fourth scientific and technological revolution Industry 4.0. The practical implications refer to enterprises of the construction sector.

DUNE Collaboration, A. Abed Abud, B. Abi et al.

Measurements of electrons from $ν_e$ interactions are crucial for the Deep Underground Neutrino Experiment (DUNE) neutrino oscillation program, as well as searches for physics beyond the standard model, supernova neutrino detection, and solar neutrino measurements. This article describes the selection and reconstruction of low-energy (Michel) electrons in the ProtoDUNE-SP detector. ProtoDUNE-SP is one of the prototypes for the DUNE far detector, built and operated at CERN as a charged particle test beam experiment. A sample of low-energy electrons produced by the decay of cosmic muons is selected with a purity of 95%. This sample is used to calibrate the low-energy electron energy scale with two techniques. An electron energy calibration based on a cosmic ray muon sample uses calibration constants derived from measured and simulated cosmic ray muon events. Another calibration technique makes use of the theoretically well-understood Michel electron energy spectrum to convert reconstructed charge to electron energy. In addition, the effects of detector response to low-energy electron energy scale and its resolution including readout electronics threshold effects are quantified. Finally, the relation between the theoretical and reconstructed low-energy electron energy spectrum is derived and the energy resolution is characterized. The low-energy electron selection presented here accounts for about 75% of the total electron deposited energy. After the addition of lost energy using a Monte Carlo simulation, the energy resolution improves from about 40% to 25% at 50~MeV. These results are used to validate the expected capabilities of the DUNE far detector to reconstruct low-energy electrons.