The Experts below are selected from a list of 77094 Experts worldwide ranked by ideXlab platform
Kristina Kostial - One of the best experts on this subject based on the ideXlab platform.
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the disappearing tax base is foreign direct investment fdi eroding corporate income taxes
IMF Working Papers, 2000Co-Authors: Reint Gropp, Kristina KostialAbstract:This paper analyzes the link between FDI, corporate taxation, and corporate tax revenues. We find strong evidence that FDI in (out) flows are affected by tax regimes in the host (home) countries and FDI flows in turn affect the corporate tax base. Simulations of European Union (EU) Harmonization (isolating the revenue effect of FDI on the tax base from direct effects through the rate Harmonization) suggest that high (low) tax countries would gain (lose) revenue from Harmonization; these effects may be substantial. Our results also suggest that EU tax Harmonization would significantly affect the net FDI position of some countries.
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the disappearing tax base is foreign direct investment fdi eroding corporate income taxes
IMF Working Papers, 2000Co-Authors: Reint Gropp, Kristina KostialAbstract:This paper analyzes the link between FDI, corporate taxation, and corporate tax revenues. We find strong evidence that FDI in (out) flows are affected by tax regimes in the host (home) countries and FDI flows in turn affect the corporate tax base. Simulations of European Union (EU) Harmonization (isolating the revenue effect of FDI on the tax base from direct effects through the rate Harmonization) suggest that high (low) tax countries would gain (lose) revenue from Harmonization; these effects may be substantial. Our results also suggest that EU tax Harmonization would significantly affect the net FDI position of some countries.
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the disappearing tax base is foreign direct investment eroding corporate income taxes
Social Science Research Network, 2000Co-Authors: Reint Gropp, Kristina KostialAbstract:This paper analyzes the link between Foreign Direct Investment (FDI), corporate taxation, and corporate tax revenues. We find strong evidence that FDI in (out) flows are affected by tax regimes in the host (home) countries and FDI flows in turn affect the corporate tax base. Simulations of EU Harmonization (isolating the revenue effect of FDI on the tax base from direct effects through the rate Harmonization) suggest that high (low) tax countries would gain (lose) revenue from Harmonization; these effects may be substantial. Our results also suggest that EU tax Harmonization would significantly affect the net FDI position of some countries.
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the disappearing tax base is foreign direct investment eroding corporate income taxes
2000Co-Authors: Reint Gropp, Kristina KostialAbstract:This paper analyzes the link between Foreign Direct Investment (FDI), corporate taxation, and corporate tax revenues. We find strong evidence that FDI in (out) flows are affected by tax regimes in the host (home) countries and FDI flows in turn affect the corporate tax base. Simulations of EU Harmonization (isolating the revenue effect of FDI on the tax base from direct effects through the rate Harmonization) suggest that high (low) tax countries would gain (lose) revenue from Harmonization; these effects may be substantial. Our results also suggest that EU tax Harmonization would significantly affect the net FDI position of some countries. JEL Classification: H25, H87, F21, F42, F47
Reint Gropp - One of the best experts on this subject based on the ideXlab platform.
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the disappearing tax base is foreign direct investment fdi eroding corporate income taxes
IMF Working Papers, 2000Co-Authors: Reint Gropp, Kristina KostialAbstract:This paper analyzes the link between FDI, corporate taxation, and corporate tax revenues. We find strong evidence that FDI in (out) flows are affected by tax regimes in the host (home) countries and FDI flows in turn affect the corporate tax base. Simulations of European Union (EU) Harmonization (isolating the revenue effect of FDI on the tax base from direct effects through the rate Harmonization) suggest that high (low) tax countries would gain (lose) revenue from Harmonization; these effects may be substantial. Our results also suggest that EU tax Harmonization would significantly affect the net FDI position of some countries.
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the disappearing tax base is foreign direct investment fdi eroding corporate income taxes
IMF Working Papers, 2000Co-Authors: Reint Gropp, Kristina KostialAbstract:This paper analyzes the link between FDI, corporate taxation, and corporate tax revenues. We find strong evidence that FDI in (out) flows are affected by tax regimes in the host (home) countries and FDI flows in turn affect the corporate tax base. Simulations of European Union (EU) Harmonization (isolating the revenue effect of FDI on the tax base from direct effects through the rate Harmonization) suggest that high (low) tax countries would gain (lose) revenue from Harmonization; these effects may be substantial. Our results also suggest that EU tax Harmonization would significantly affect the net FDI position of some countries.
-
the disappearing tax base is foreign direct investment eroding corporate income taxes
Social Science Research Network, 2000Co-Authors: Reint Gropp, Kristina KostialAbstract:This paper analyzes the link between Foreign Direct Investment (FDI), corporate taxation, and corporate tax revenues. We find strong evidence that FDI in (out) flows are affected by tax regimes in the host (home) countries and FDI flows in turn affect the corporate tax base. Simulations of EU Harmonization (isolating the revenue effect of FDI on the tax base from direct effects through the rate Harmonization) suggest that high (low) tax countries would gain (lose) revenue from Harmonization; these effects may be substantial. Our results also suggest that EU tax Harmonization would significantly affect the net FDI position of some countries.
-
the disappearing tax base is foreign direct investment eroding corporate income taxes
2000Co-Authors: Reint Gropp, Kristina KostialAbstract:This paper analyzes the link between Foreign Direct Investment (FDI), corporate taxation, and corporate tax revenues. We find strong evidence that FDI in (out) flows are affected by tax regimes in the host (home) countries and FDI flows in turn affect the corporate tax base. Simulations of EU Harmonization (isolating the revenue effect of FDI on the tax base from direct effects through the rate Harmonization) suggest that high (low) tax countries would gain (lose) revenue from Harmonization; these effects may be substantial. Our results also suggest that EU tax Harmonization would significantly affect the net FDI position of some countries. JEL Classification: H25, H87, F21, F42, F47
Dany Doiron - One of the best experts on this subject based on the ideXlab platform.
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maelstrom research guidelines for rigorous retrospective data Harmonization
International Journal of Epidemiology, 2016Co-Authors: Isabel Fortier, Dany Doiron, Ronald P Stolk, Parminder Raina, Edwin R Van Den Heuvel, Lauren Griffith, Camille Craig, Matilda Saliba, Bartha Maria Knoppers, Vincent FerrettiAbstract:Background: It is widely accepted and acknowledged that data Harmonization is crucial: in its absence, the co-analysis of major tranches of high quality extant data is liable to inefficiency or error. However, despite its widespread practice, no formalized/systematic guidelines exist to ensure high quality retrospective data Harmonization. Methods: To better understand real-world Harmonization practices and facilitate development of formal guidelines, three interrelated initiatives were undertaken between 2006 and 2015. They included a phone survey with 34 major international research initiatives, a series of workshops with experts, and case studies applying the proposed guidelines. Results: A wide range of projects use retrospective Harmonization to support their research activities but even when appropriate approaches are used, the terminologies, procedures, technologies and methods adopted vary markedly. The generic guidelines outlined in this article delineate the essentials required and describe an interdependent step-by-step approach to Harmonization: 0) define the research question, objectives and protocol; 1) assemble pre-existing knowledge and select studies; 2) define targeted variables and evaluate Harmonization potential; 3) process data; 4) estimate quality of the harmonized dataset(s) generated; and 5) disseminate and preserve final Harmonization products. Conclusions: This manuscript provides guidelines aiming to encourage rigorous and effective approaches to Harmonization which are comprehensively and transparently documented and straightforward to interpret and implement. This can be seen as a key step towards implementing guiding principles analogous to those that are well recognised as being essential in securing the foundational underpinning of systematic reviews and the meta-analysis of clinical trials.
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data Harmonization and federated analysis of population based studies the bioshare project
Emerging Themes in Epidemiology, 2013Co-Authors: Dany Doiron, Paul Burton, Yannick Marcon, Amadou Gaye, Bruce H R Wolffenbuttel, Markus Perola, Ronald P Stolk, Luisa Foco, Cosetta MinelliAbstract:Individual-level data pooling of large population-based studies across research centres in international research projects faces many hurdles. The BioSHaRE (Biobank Standardisation and Harmonisation for Research Excellence in the European Union) project aims to address these issues by building a collaborative group of investigators and developing tools for data Harmonization, database integration and federated data analyses. Eight population-based studies in six European countries were recruited to participate in the BioSHaRE project. Through workshops, teleconferences and electronic communications, participating investigators identified a set of 96 variables targeted for Harmonization to answer research questions of interest. Using each study’s questionnaires, standard operating procedures, and data dictionaries, Harmonization potential was assessed. Whenever Harmonization was deemed possible, processing algorithms were developed and implemented in an open-source software infrastructure to transform study-specific data into the target (i.e. harmonized) format. Harmonized datasets located on server in each research centres across Europe were interconnected through a federated database system to perform statistical analysis. Retrospective Harmonization led to the generation of common format variables for 73% of matches considered (96 targeted variables across 8 studies). Authenticated investigators can now perform complex statistical analyses of harmonized datasets stored on distributed servers without actually sharing individual-level data using the DataSHIELD method. New Internet-based networking technologies and database management systems are providing the means to support collaborative, multi-center research in an efficient and secure manner. The results from this pilot project show that, given a strong collaborative relationship between participating studies, it is possible to seamlessly co-analyse internationally harmonized research databases while allowing each study to retain full control over individual-level data. We encourage additional collaborative research networks in epidemiology, public health, and the social sciences to make use of the open source tools presented herein.
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is rigorous retrospective Harmonization possible application of the datashaper approach across 53 large studies
International Journal of Epidemiology, 2011Co-Authors: Isabel Fortier, Dany Doiron, Ronald P Stolk, Bartha Maria Knoppers, Vincent Ferretti, Julian Little, Francois Lheureux, Thomas J Hudson, Paul R BurtonAbstract:Background Proper understanding of the roles of, and interactions between genetic, lifestyle, environmental and psycho-social factors in determining the risk of development and/or progression of chronic diseases requires access to very large high-quality databases. Because of the financial, technical and time burdens related to developing and maintaining very large studies, the scientific community is increasingly synthesizing data from multiple studies to construct large databases. However, the data items collected by individual studies must be inferentially equivalent to be meaningfully synthesized. The DataSchema and Harmonization Platform for Epidemiological Research (DataSHaPER; http://www.datashaper.org) was developed to enable the rigorous assessment of the inferential equivalence, i.e. the potential for Harmonization, of selected information from individual studies. Methods This article examines the value of using the DataSHaPER for retrospective Harmonization of established studies. Using the DataSHaPER approach, the potential to generate 148 harmonized variables from the questionnaires and physical measures collected in 53 large population-based studies (6.9 million participants) was assessed. Variable and study characteristics that might influence the potential for data synthesis were also explored. Results Out of all assessment items evaluated (148 variables for each of the 53 studies), 38% could be harmonized. Certain characteristics of variables (i.e. relative importance, individual targeted, reference period) and of studies (i.e. observational units, data collection start date and mode of questionnaire administration) were associated with the potential for Harmonization. For example, for variables deemed to be essential, 62% of assessment items paired could be harmonized. Conclusion The current article shows that the DataSHaPER provides an effective and flexible approach for the retrospective Harmonization of information across studies. To implement data synthesis, some additional scientific, ethico-legal and technical considerations must be addressed. The success of the DataSHaPER as a Harmonization approach will depend on its continuing development and on the rigour and extent of its use. The DataSHaPER has the potential to take us closer to a truly collaborative epidemiology and offers the promise of enhanced research potential generated through synthesized databases.
Vincent Ferretti - One of the best experts on this subject based on the ideXlab platform.
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maelstrom research guidelines for rigorous retrospective data Harmonization
International Journal of Epidemiology, 2016Co-Authors: Isabel Fortier, Dany Doiron, Ronald P Stolk, Parminder Raina, Edwin R Van Den Heuvel, Lauren Griffith, Camille Craig, Matilda Saliba, Bartha Maria Knoppers, Vincent FerrettiAbstract:Background: It is widely accepted and acknowledged that data Harmonization is crucial: in its absence, the co-analysis of major tranches of high quality extant data is liable to inefficiency or error. However, despite its widespread practice, no formalized/systematic guidelines exist to ensure high quality retrospective data Harmonization. Methods: To better understand real-world Harmonization practices and facilitate development of formal guidelines, three interrelated initiatives were undertaken between 2006 and 2015. They included a phone survey with 34 major international research initiatives, a series of workshops with experts, and case studies applying the proposed guidelines. Results: A wide range of projects use retrospective Harmonization to support their research activities but even when appropriate approaches are used, the terminologies, procedures, technologies and methods adopted vary markedly. The generic guidelines outlined in this article delineate the essentials required and describe an interdependent step-by-step approach to Harmonization: 0) define the research question, objectives and protocol; 1) assemble pre-existing knowledge and select studies; 2) define targeted variables and evaluate Harmonization potential; 3) process data; 4) estimate quality of the harmonized dataset(s) generated; and 5) disseminate and preserve final Harmonization products. Conclusions: This manuscript provides guidelines aiming to encourage rigorous and effective approaches to Harmonization which are comprehensively and transparently documented and straightforward to interpret and implement. This can be seen as a key step towards implementing guiding principles analogous to those that are well recognised as being essential in securing the foundational underpinning of systematic reviews and the meta-analysis of clinical trials.
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is rigorous retrospective Harmonization possible application of the datashaper approach across 53 large studies
International Journal of Epidemiology, 2011Co-Authors: Isabel Fortier, Dany Doiron, Ronald P Stolk, Bartha Maria Knoppers, Vincent Ferretti, Julian Little, Francois Lheureux, Thomas J Hudson, Paul R BurtonAbstract:Background Proper understanding of the roles of, and interactions between genetic, lifestyle, environmental and psycho-social factors in determining the risk of development and/or progression of chronic diseases requires access to very large high-quality databases. Because of the financial, technical and time burdens related to developing and maintaining very large studies, the scientific community is increasingly synthesizing data from multiple studies to construct large databases. However, the data items collected by individual studies must be inferentially equivalent to be meaningfully synthesized. The DataSchema and Harmonization Platform for Epidemiological Research (DataSHaPER; http://www.datashaper.org) was developed to enable the rigorous assessment of the inferential equivalence, i.e. the potential for Harmonization, of selected information from individual studies. Methods This article examines the value of using the DataSHaPER for retrospective Harmonization of established studies. Using the DataSHaPER approach, the potential to generate 148 harmonized variables from the questionnaires and physical measures collected in 53 large population-based studies (6.9 million participants) was assessed. Variable and study characteristics that might influence the potential for data synthesis were also explored. Results Out of all assessment items evaluated (148 variables for each of the 53 studies), 38% could be harmonized. Certain characteristics of variables (i.e. relative importance, individual targeted, reference period) and of studies (i.e. observational units, data collection start date and mode of questionnaire administration) were associated with the potential for Harmonization. For example, for variables deemed to be essential, 62% of assessment items paired could be harmonized. Conclusion The current article shows that the DataSHaPER provides an effective and flexible approach for the retrospective Harmonization of information across studies. To implement data synthesis, some additional scientific, ethico-legal and technical considerations must be addressed. The success of the DataSHaPER as a Harmonization approach will depend on its continuing development and on the rigour and extent of its use. The DataSHaPER has the potential to take us closer to a truly collaborative epidemiology and offers the promise of enhanced research potential generated through synthesized databases.
Ronald P Stolk - One of the best experts on this subject based on the ideXlab platform.
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maelstrom research guidelines for rigorous retrospective data Harmonization
International Journal of Epidemiology, 2016Co-Authors: Isabel Fortier, Dany Doiron, Ronald P Stolk, Parminder Raina, Edwin R Van Den Heuvel, Lauren Griffith, Camille Craig, Matilda Saliba, Bartha Maria Knoppers, Vincent FerrettiAbstract:Background: It is widely accepted and acknowledged that data Harmonization is crucial: in its absence, the co-analysis of major tranches of high quality extant data is liable to inefficiency or error. However, despite its widespread practice, no formalized/systematic guidelines exist to ensure high quality retrospective data Harmonization. Methods: To better understand real-world Harmonization practices and facilitate development of formal guidelines, three interrelated initiatives were undertaken between 2006 and 2015. They included a phone survey with 34 major international research initiatives, a series of workshops with experts, and case studies applying the proposed guidelines. Results: A wide range of projects use retrospective Harmonization to support their research activities but even when appropriate approaches are used, the terminologies, procedures, technologies and methods adopted vary markedly. The generic guidelines outlined in this article delineate the essentials required and describe an interdependent step-by-step approach to Harmonization: 0) define the research question, objectives and protocol; 1) assemble pre-existing knowledge and select studies; 2) define targeted variables and evaluate Harmonization potential; 3) process data; 4) estimate quality of the harmonized dataset(s) generated; and 5) disseminate and preserve final Harmonization products. Conclusions: This manuscript provides guidelines aiming to encourage rigorous and effective approaches to Harmonization which are comprehensively and transparently documented and straightforward to interpret and implement. This can be seen as a key step towards implementing guiding principles analogous to those that are well recognised as being essential in securing the foundational underpinning of systematic reviews and the meta-analysis of clinical trials.
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data Harmonization and federated analysis of population based studies the bioshare project
Emerging Themes in Epidemiology, 2013Co-Authors: Dany Doiron, Paul Burton, Yannick Marcon, Amadou Gaye, Bruce H R Wolffenbuttel, Markus Perola, Ronald P Stolk, Luisa Foco, Cosetta MinelliAbstract:Individual-level data pooling of large population-based studies across research centres in international research projects faces many hurdles. The BioSHaRE (Biobank Standardisation and Harmonisation for Research Excellence in the European Union) project aims to address these issues by building a collaborative group of investigators and developing tools for data Harmonization, database integration and federated data analyses. Eight population-based studies in six European countries were recruited to participate in the BioSHaRE project. Through workshops, teleconferences and electronic communications, participating investigators identified a set of 96 variables targeted for Harmonization to answer research questions of interest. Using each study’s questionnaires, standard operating procedures, and data dictionaries, Harmonization potential was assessed. Whenever Harmonization was deemed possible, processing algorithms were developed and implemented in an open-source software infrastructure to transform study-specific data into the target (i.e. harmonized) format. Harmonized datasets located on server in each research centres across Europe were interconnected through a federated database system to perform statistical analysis. Retrospective Harmonization led to the generation of common format variables for 73% of matches considered (96 targeted variables across 8 studies). Authenticated investigators can now perform complex statistical analyses of harmonized datasets stored on distributed servers without actually sharing individual-level data using the DataSHIELD method. New Internet-based networking technologies and database management systems are providing the means to support collaborative, multi-center research in an efficient and secure manner. The results from this pilot project show that, given a strong collaborative relationship between participating studies, it is possible to seamlessly co-analyse internationally harmonized research databases while allowing each study to retain full control over individual-level data. We encourage additional collaborative research networks in epidemiology, public health, and the social sciences to make use of the open source tools presented herein.
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is rigorous retrospective Harmonization possible application of the datashaper approach across 53 large studies
International Journal of Epidemiology, 2011Co-Authors: Isabel Fortier, Dany Doiron, Ronald P Stolk, Bartha Maria Knoppers, Vincent Ferretti, Julian Little, Francois Lheureux, Thomas J Hudson, Paul R BurtonAbstract:Background Proper understanding of the roles of, and interactions between genetic, lifestyle, environmental and psycho-social factors in determining the risk of development and/or progression of chronic diseases requires access to very large high-quality databases. Because of the financial, technical and time burdens related to developing and maintaining very large studies, the scientific community is increasingly synthesizing data from multiple studies to construct large databases. However, the data items collected by individual studies must be inferentially equivalent to be meaningfully synthesized. The DataSchema and Harmonization Platform for Epidemiological Research (DataSHaPER; http://www.datashaper.org) was developed to enable the rigorous assessment of the inferential equivalence, i.e. the potential for Harmonization, of selected information from individual studies. Methods This article examines the value of using the DataSHaPER for retrospective Harmonization of established studies. Using the DataSHaPER approach, the potential to generate 148 harmonized variables from the questionnaires and physical measures collected in 53 large population-based studies (6.9 million participants) was assessed. Variable and study characteristics that might influence the potential for data synthesis were also explored. Results Out of all assessment items evaluated (148 variables for each of the 53 studies), 38% could be harmonized. Certain characteristics of variables (i.e. relative importance, individual targeted, reference period) and of studies (i.e. observational units, data collection start date and mode of questionnaire administration) were associated with the potential for Harmonization. For example, for variables deemed to be essential, 62% of assessment items paired could be harmonized. Conclusion The current article shows that the DataSHaPER provides an effective and flexible approach for the retrospective Harmonization of information across studies. To implement data synthesis, some additional scientific, ethico-legal and technical considerations must be addressed. The success of the DataSHaPER as a Harmonization approach will depend on its continuing development and on the rigour and extent of its use. The DataSHaPER has the potential to take us closer to a truly collaborative epidemiology and offers the promise of enhanced research potential generated through synthesized databases.
