Suchergebnisse

The government fragmentation hypothesis (GFH) states that coalition governments spend more than single-party governments due to an underlying common pool problem. Using a large panel data set on 604 local governments in the German state of Baden-Württemberg for the 1994-2014 period, I test the GFH for tax rates, the growth in government debt as well as expenditures and its sub-categories. Studies using standard regression methods fail to identify causal effect as the type of government is generally not random. I apply a RDD, that exploits quasi-random variation generated by close elections. I add external validity to the recent quasi-experimental literature by investigating the GFH for a mayor-council system. I find that contrary to the theoretical prediction, coalition governments do not increase taxes and government debt. There is a non-robust, negative effect on total expenditures, which is mainly driven by administrative expenditures and material expenditures. ; Die Regierungsfragmentierungs-Hypothese (GFH) konstatiert, dass Koalitionsregierungen auf Grund eines Common Pool Problems höhere Staatsausgaben aufweisen als Einparteienregierungen. Ich teste die GFH für die kommunalen Steuersätze, das kommunale Schuldenwachstum und die kommunalen Ausgaben unter Verwendung eines Panel-Datensatzes, der 604 Baden-Württembergische Kommunen für den Zeitraum von 1994-2014 umfasst. Da der Regierungstyp generell nicht zufällig ist, können Studien, die herkömmliche Regressionsmethoden verwenden, den kausalen Effekt nicht identifizieren. Ich verwende ein Regressions-Diskontinuitäts-Design, das die quasi-zufällige Variation knapper Wahlausgänge ausnutzt, und trage zur neuen quasi-experimentellen Literatur bei, indem ich die GFH im Kontext einer Bürgermeisterverfassung analysiere. Entgegen der theoretischen Vorhersage erhöhen Koalitionsregierungen weder die Steuersätze noch die Verschuldung. Koalitionsregierungen haben einen nichtrobusten, negativen Effekt auf die Bruttoausgaben, der im Wesentlichen von den Verwaltungsausgaben und dem Laufenden Sachaufwand getrieben ist.

Climate change poses large economic costs to governments and societies. Reducing individuals' CO2 footprints is central in mitigating climate change. In a new paper, we show that providing information on combating climate change motivates individuals to take costly actions to offset CO2 emissions. Presenting the information as the result of scientific research is as effective as framing it as the behaviour of other people. Individuals' responses vary depending on their socio-demographic characteristics and attitudes towards climate change. Furthermore, individuals choose information that aligns with their views. Individuals who actively gather information about climate change have a higher willingness to pay for carbon offsets.

Beim PHF Scientific Use File (SUF) Welle 3 Version 2.0 handelt es sich um die erste aktualisierte Version des PHF Datensatzes der dritten Welle. Er besteht aus den folgenden fünf Sata-Dateien: PHF_h_wave3_v2_0.dta, PHF_p_wave3_v2_0.dta, PHF_m_wave3_v2_0.dta, PHF_d_wave3_v2_0.dta und PHF_w_wave3_v2_0.dta.
Die wichtigsten Änderungen im PHF SUF Welle 3 Version 2.0 im Vergleich zur Vorgängerversion PHF SUF Welle 3 Version 1.0 sind:

Editieren und Korrektur einiger Werte.
Der Datensatz enthält zusätzliche Variablen.
Die Definition der Derived Variables wurde soweit möglich über alle Wellen vereinheitlicht.

Weiter Informationen finden Sie im PHF User Guide auf den Webseiten der Deutsche Bundesbank.

The PHF scientific use file Wave 3 Version 1.0 data set is the first version of the wave 3 PHF data set and consists of the following five Stata files: PHF_h_wave3_v1_0.dta, PHF_p_wave3_v1_0.dta, PHF_m_wave3_v1_0.dta, PHF_d_wave3_v1_0.dta and PHF_w_wave3_v1_0.dta.
For more details, see the PHF User Guide on website of the Deutsche Bundesbank.

While high risk of failure is an inherent part of developing innovative therapies, it can be reduced by adherence to evidence-based rigorous research practices. Numerous analyses conducted to date have clearly identified measures that need to be taken to improve research rigor. Supported through the European Union's Innovative Medicines Initiative, the EQIPD consortium has developed a novel preclinical research quality system that can be applied in both public and private sectors and is free for anyone to use. The EQIPD Quality System was designed to be suited to boost innovation by ensuring the generation of robust and reliable preclinical data while being lean, effective and not becoming a burden that could negatively impact the freedom to explore scientific questions. EQIPD defines research quality as the extent to which research data are fit for their intended use. Fitness, in this context, is defined by the stakeholders, who are the scientists directly involved in the research, but also their funders, sponsors, publishers, research tool manufacturers and collaboration partners such as peers in a multi-site research project. The essence of the EQIPD Quality System is the set of 18 core requirements that can be addressed flexibly, according to user-specific needs and following a user-defined trajectory. The EQIPD Quality System proposes guidance on expectations for quality-related measures, defines criteria for adequate processes (i.e., performance standards) and provides examples of how such measures can be developed and implemented. However, it does not prescribe any pre-determined solutions. EQIPD has also developed tools (for optional use) to support users in implementing the system and assessment services for those research units that successfully implement the quality system and seek formal accreditation. Building upon the feedback from users and continuous improvement, a sustainable EQIPD Quality System will ultimately serve the entire community of scientists conducting non-regulated preclinical research, by helping them generate reliable data that are fit for their intended use.

While high risk of failure is an inherent part of developing innovative therapies, it can be reduced by adherence to evidence-based rigorous research practices. Supported through the European Union's Innovative Medicines Initiative, the EQIPD consortium has developed a novel preclinical research quality system that can be applied in both public and private sectors and is free for anyone to use. The EQIPD Quality System was designed to be suited to boost innovation by ensuring the generation of robust and reliable preclinical data while being lean, effective and not becoming a burden that could negatively impact the freedom to explore scientific questions. EQIPD defines research quality as the extent to which research data are fit for their intended use. Fitness, in this context, is defined by the stakeholders, who are the scientists directly involved in the research, but also their funders, sponsors, publishers, research tool manufacturers, and collaboration partners such as peers in a multi-site research project. The essence of the EQIPD Quality System is the set of 18 core requirements that can be addressed flexibly, according to user-specific needs and following a user-defined trajectory. The EQIPD Quality System proposes guidance on expectations for quality-related measures, defines criteria for adequate processes (i.e. performance standards) and provides examples of how such measures can be developed and implemented. However, it does not prescribe any pre-determined solutions. EQIPD has also developed tools (for optional use) to support users in implementing the system and assessment services for those research units that successfully implement the quality system and seek formal accreditation. Building upon the feedback from users and continuous improvement, a sustainable EQIPD Quality System will ultimately serve the entire community of scientists conducting non-regulated preclinical research, by helping them generate reliable data that are fit for their intended use.

While high risk of failure is an inherent part of developing innovative therapies, it can be reduced by adherence to evidence-based rigorous research practices. Numerous analyses conducted to date have clearly identified measures that need to be taken to improve research rigor. Supported through the European Union's Innovative Medicines Initiative, the EQIPD consortium has developed a novel preclinical research quality system that can be applied in both public and private sectors and is free for anyone to use. The EQIPD Quality System was designed to be suited to boost innovation by ensuring the generation of robust and reliable preclinical data while being lean, effective and not becoming a burden that could negatively impact the freedom to explore scientific questions. EQIPD defines research quality as the extent to which research data are fit for their intended use. Fitness, in this context, is defined by the stakeholders, who are the scientists directly involved in the research, but also their funders, sponsors, publishers, research tool manufacturers and collaboration partners such as peers in a multi-site research project. The essence of the EQIPD Quality System is the set of 18 core requirements that can be addressed flexibly, according to user-specific needs and following a user-defined trajectory. The EQIPD Quality System proposes guidance on expectations for quality-related measures, defines criteria for adequate processes (i.e., performance standards) and provides examples of how such measures can be developed and implemented. However, it does not prescribe any pre-determined solutions. EQIPD has also developed tools (for optional use) to support users in implementing the system and assessment services for those research units that successfully implement the quality system and seek formal accreditation. Building upon the feedback from users and continuous improvement, a sustainable EQIPD Quality System will ultimately serve the entire community of scientists conducting non-regulated preclinical ...