Pub Date : 2023-11-07DOI: 10.1007/s11135-023-01778-6
İbrahim Özmen, Selçuk Bali, Festus Victor Bekun
{"title":"Is Abrams curve a myth or reality? Evidence from two Baltic countries","authors":"İbrahim Özmen, Selçuk Bali, Festus Victor Bekun","doi":"10.1007/s11135-023-01778-6","DOIUrl":"https://doi.org/10.1007/s11135-023-01778-6","url":null,"abstract":"","PeriodicalId":49649,"journal":{"name":"Quality & Quantity","volume":"19 5","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-11-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135480366","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-11-02DOI: 10.1007/s11135-023-01773-x
Faruk Yüksel, Üzeyir Kement, Samet Can Aksu, Mehmet Kabacik, Raffaela Ciuffreda
{"title":"Do social media use and gadget loving affect innovative job performance? The moderation role of generation cohort: an evaluation of the kitchen chefs","authors":"Faruk Yüksel, Üzeyir Kement, Samet Can Aksu, Mehmet Kabacik, Raffaela Ciuffreda","doi":"10.1007/s11135-023-01773-x","DOIUrl":"https://doi.org/10.1007/s11135-023-01773-x","url":null,"abstract":"","PeriodicalId":49649,"journal":{"name":"Quality & Quantity","volume":"11 2","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-11-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135972876","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-11-02DOI: 10.1007/s11135-023-01755-z
Nina Deliu
Abstract Reinforcement learning (RL) algorithms have been long recognized as powerful tools for optimal sequential decision making. The framework is concerned with a decision maker, the agent, that learns how to behave in an unknown environment by making decisions and seeing their associated outcome. The goal of the RL agent is to infer, through repeated experience, an optimal decision-making policy, i.e., a sequence of action rules that would lead to the highest, typically long-term, expected utility. Today, a wide range of domains, from economics to education and healthcare, have embraced the use of RL to address specific problems. To illustrate, we used an RL-based algorithm to design a text-messaging system that delivers personalized real-time behavioural recommendations to promote physical activity and manage depression. Motivated by the recent call of the UNECE for government-wide actions to adapt to population ageing, in this work, we argue that the RL framework may provide a set of compelling strategies for supporting population research and informing population policies. After introducing the RL framework, we discuss its potential in three population-study applications: international migration, public health, and fertility.
{"title":"Reinforcement learning for sequential decision making in population research","authors":"Nina Deliu","doi":"10.1007/s11135-023-01755-z","DOIUrl":"https://doi.org/10.1007/s11135-023-01755-z","url":null,"abstract":"Abstract Reinforcement learning (RL) algorithms have been long recognized as powerful tools for optimal sequential decision making. The framework is concerned with a decision maker, the agent, that learns how to behave in an unknown environment by making decisions and seeing their associated outcome. The goal of the RL agent is to infer, through repeated experience, an optimal decision-making policy, i.e., a sequence of action rules that would lead to the highest, typically long-term, expected utility. Today, a wide range of domains, from economics to education and healthcare, have embraced the use of RL to address specific problems. To illustrate, we used an RL-based algorithm to design a text-messaging system that delivers personalized real-time behavioural recommendations to promote physical activity and manage depression. Motivated by the recent call of the UNECE for government-wide actions to adapt to population ageing, in this work, we argue that the RL framework may provide a set of compelling strategies for supporting population research and informing population policies. After introducing the RL framework, we discuss its potential in three population-study applications: international migration, public health, and fertility.","PeriodicalId":49649,"journal":{"name":"Quality & Quantity","volume":"11 9","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-11-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135933475","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-11-02DOI: 10.1007/s11135-023-01761-1
Kokulo K. Lawuobahsumo, Bernardina Algieri, Arturo Leccadito
Abstract This study aims to jointly predict conditional quantiles and tail expectations for the returns of the most popular cryptocurrencies (Bitcoin, Ethereum, Ripple, Dogecoin and Litecoin) using financial and macroeconomic indicators as explanatory variables. We adopt a Monotone Composite Quantile Regression Neural Network (MCQRNN) model to make one- and five-steps-ahead predictions of Value-at-Risk (VaR) and Expected Shortfall (ES) based on a rolling window and compare the performance of our model against the Historical simulation and the standard ARMA(1,1)-GARCH(1,1) model used as benchmarks. The superior set of models is then chosen by backtesting VaR and ES using a Model Confidence Set procedure. Our results show that the MCQRNN performs better than both benchmark models for jointly predicting VaR and ES when considering daily data. Models with the implied volatility index, treasury yield spread and inflation expectations sharpen the extreme return predictions. The results are consistent for the two risk measures at the 1% and 5% level both, in the case of a long and short position and for all cryptocurrencies.
{"title":"Forecasting cryptocurrencies returns: Do macroeconomic and financial variables improve tail expectation predictions?","authors":"Kokulo K. Lawuobahsumo, Bernardina Algieri, Arturo Leccadito","doi":"10.1007/s11135-023-01761-1","DOIUrl":"https://doi.org/10.1007/s11135-023-01761-1","url":null,"abstract":"Abstract This study aims to jointly predict conditional quantiles and tail expectations for the returns of the most popular cryptocurrencies (Bitcoin, Ethereum, Ripple, Dogecoin and Litecoin) using financial and macroeconomic indicators as explanatory variables. We adopt a Monotone Composite Quantile Regression Neural Network (MCQRNN) model to make one- and five-steps-ahead predictions of Value-at-Risk (VaR) and Expected Shortfall (ES) based on a rolling window and compare the performance of our model against the Historical simulation and the standard ARMA(1,1)-GARCH(1,1) model used as benchmarks. The superior set of models is then chosen by backtesting VaR and ES using a Model Confidence Set procedure. Our results show that the MCQRNN performs better than both benchmark models for jointly predicting VaR and ES when considering daily data. Models with the implied volatility index, treasury yield spread and inflation expectations sharpen the extreme return predictions. The results are consistent for the two risk measures at the 1% and 5% level both, in the case of a long and short position and for all cryptocurrencies.","PeriodicalId":49649,"journal":{"name":"Quality & Quantity","volume":"16 5","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-11-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135934625","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-10-31DOI: 10.1007/s11135-023-01766-w
Sakiru Adebola Solarin, Mufutau Opeyemi Bello
{"title":"Modelling labour productivity and the role of research intensity in 129 years: evidence from a new dynamic instrumental variable estimation approach","authors":"Sakiru Adebola Solarin, Mufutau Opeyemi Bello","doi":"10.1007/s11135-023-01766-w","DOIUrl":"https://doi.org/10.1007/s11135-023-01766-w","url":null,"abstract":"","PeriodicalId":49649,"journal":{"name":"Quality & Quantity","volume":"22 5","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135809198","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-10-28DOI: 10.1007/s11135-023-01769-7
Julien Noble, Antoine Jardin
{"title":"Correction: Mapping fear of crime: defining methodological orientations","authors":"Julien Noble, Antoine Jardin","doi":"10.1007/s11135-023-01769-7","DOIUrl":"https://doi.org/10.1007/s11135-023-01769-7","url":null,"abstract":"","PeriodicalId":49649,"journal":{"name":"Quality & Quantity","volume":"20 8","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136232767","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-10-21DOI: 10.1007/s11135-023-01756-y
Fatma Kürüm Varolgüneş, Sadık Varolgüneş, María de la Cruz del Río-Rama, Amador Durán-Sánchez
{"title":"A proposal for the selection of green building standards through the analytical hierarchy process (AHP): a roadmap for green hotels in Turkey","authors":"Fatma Kürüm Varolgüneş, Sadık Varolgüneş, María de la Cruz del Río-Rama, Amador Durán-Sánchez","doi":"10.1007/s11135-023-01756-y","DOIUrl":"https://doi.org/10.1007/s11135-023-01756-y","url":null,"abstract":"","PeriodicalId":49649,"journal":{"name":"Quality & Quantity","volume":"10 6","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135513175","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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