Augmenting short Cheap Talk scripts with a repeated Opt-Out Reminder in Choice Experiment surveys

Hypothetical bias remains a major problem when valuing non-market goods with stated preference methods. Originally developed for Contingent Valuation studies, Cheap Talk has been found to effectively reduce hypothetical bias in some applications, though empirical results are ambiguous. We discuss reasons why Cheap Talk may fail to effectively remove hypothetical bias, especially in Choice Experiments. In this light, we suggest augmenting Cheap Talk in Choice Experiments with a so-called Opt-Out Reminder. Prior to each single choice set, the Opt-Out Reminder explicitly instructs respondents to choose the opt-out alternative if they find the experimentally designed alternatives too expensive. In an empirical Choice Experiment survey we find the Opt-Out Reminder to significantly reduce total WTP and to some extent also marginal WTP beyond the capability of the Cheap Talk applied without the Opt-Out Reminder. This suggests that rather than merely adopting the Cheap Talk practice directly from Contingent Valuation, it should be adapted to fit the potentially different decision processes and repeated choices structure of the Choice Experiment format. Our results further suggest that augmenting Cheap Talk with a dynamic Opt-Out Reminder can be an effective and promising improvement in the ongoing effort to remedy the particular types of hypothetical bias that potentially continue to invalidate Choice Experiment surveys.Cheap talk, Opt-Out Reminder, Choice Experiments, hypothetical bias, stream re-establishment, opt-out effect

Overview Report: Measuring Media Development

An Interactive Timeline of Media Development Sankalpa Dashrath Research is a primary component of the Media Map project, and several papers will be published and distributed publicly as part of the effort through 2011 and 2012. They include: OVERVIEW PAPERSRethinking Media Development: A Report on The Media Map Project, Mark Nelson with Tara Susman-Peña This final report is intended as the beginning of a process of using Media Map research as a platform for action. Your feedback welcome. On Media Development: An Unorthodox Review (forthcoming) Daniel Kaufmann; Presentation to the Center for International Media Assistance based on this research available here. Healthy Media, Vibrant Societies: How Strengthening the Media Can Boost Development in Sub-Saharan Africa Tara Susman-Peña A synthesis report examining the policy implications of the relationships between media and economic development in Sub-Saharan Africa. Media Development and Political Stability: An Analysis of Sub-Saharan Africa, Sanjukta Roy An econometric study of the relationships between press freedom and access to information, and political stability in Sub-Saharan Africa. COUNTRY CASE STUDIES Edited by Mary Myers, Examining the impact of donor support to the media sector over the last two decades, to be released periodically throughout 2012. – Cambodia, Margarette Roberts– Democratic Republic of the Congo, Marie-Soleil Frère – Indonesia, Manfred Oepen– Kenya, Iginio Gagliardone and Katherine Reed Allen– Mali, Heather Gilberds– Peru, Gabriela Martínez, with Network Analysis, Erich Sommerfeldt; Participatory Photographic Mapping (PPM), and PPM Annex, Luisa Ryan and Gabriela Martínez– Ukraine, Katerina Tsetsura, with Network Analysis Erich Sommerfeldt, Katerina Tsetsura, and Anna Klyueva Design for Quantifying Donor Impact on the Media Sector Sanjukta Roy and Tara Susman-Peña MONITORING & EVALUATION AND MEDIA DEVELOPMENTMapping Donor Decision Making on Media Development: An Overview of Current Monitoring and Evaluation Practice Jason Alcorn, Amy Chen, Emma Gardner, and Hiro Matsumoto, A Capstone Masters’ thesis report at the School of International and Public Affairs, Columbia University; Anya Schiffrin, Faculty Advisor LITERATURE REVIEWS & BACKGROUND MATERIALSReview of Literature Amelia Arsenault and Shawn Powers A review of the literature that explores the intellectual history of media development Overview Report: Measuring Media Development Sanjukta Roy Explains the quantitative data available that measures media, and how it is incorporated in the Media Map Project Review of Literature on Quantitative Data (matrix) Sanjukta Ro

The Great Reset

This timely and insightful collection of essays written by economists from a range of academic and policy institutes explores the subject of public investment through two avenues. The first examines public investment trends and needs in Europe, addressing the initiatives taken by European governments to tackle the COVID-19 recession and to rebuild their economies. The second identifies key domains where European public investment is needed to build a more sustainable Europe, from climate change to human capital formation. Building on the 2020 edition, The Great Reset demonstrates the value of public capital both within European countries and as a European public good, shedding light on the impact that the NextGenerationEU’s Recovery and Resilience Facility will likely have on the macroeconomic structure of the European economy. The first part of the Outlook assesses the state of public investment in Europe at large, as well as focusing on five countries (France, Germany, Italy, Poland and Spain) as case studies. The second part focuses on the challenges posed by the pandemic and the pillars of the NextGenerationEU investment plan, with chapters ranging from education and digitalization, to territorial cohesion and green transition. This book is a must-read for economists, policymakers, and scholars interested in the impact and recovery of European countries during a time of extensive uncertainty

Designing an On-Demand Dynamic Crowdshipping Model and Evaluating its Ability to Serve Local Retail Delivery in New York City

Nowadays city mobility is challenging, mainly in populated metropolitan areas. Growing commute demands, increase in the number of for-hire vehicles, enormous escalation in several intra-city deliveries and limited infrastructure (road capacities), all contribute to mobility challenges. These challenges typically have significant impacts on residents’ quality-of-life particularly from an economic and environmental perspective. Decision-makers have to optimize transportation resources to minimize the system externalities (especially in large-scale metropolitan areas). This thesis focus on the intra-city mobility problems experienced by travelers (in the form of congestion and imbalance taxi resources) and businesses (in the form of last-mile delivery), while taking into consideration a measurement of potential adoption by citizens (in the form of a survey). To find solutions for this mobility problem this dissertation proposes three distinct and complementary methodological studies. First, taxi demand is predicted by employing a deep learning approach that leverages Long Short-Term Memory (LSTM) neural networks, trained over publicly available New York City taxi trip data. Taxi pickup data are binned based on geospatial and temporal informational tags, which are then clustered using a technique inspired by Principal Component Analysis. The spatiotemporal distribution of the taxi pickup demand is studied within short-term periods (for the next hour) as well as long-term periods (for the next 48 hours) within each data cluster. The performance and robustness of the LSTM model are evaluated through a comparison with Adaptive Boosting Regression and Decision Tree Regression models fitted to the same datasets. On the next study, an On-Demand Dynamic Crowdshipping system is designed to utilize excess transport capacity to serve parcel delivery tasks and passengers collectively. This method is general and could be expanded and used for all types of public transportation modes depending upon the availability of data. This system is evaluated for the case study of New York City and to assess the impacts of the crowdshipping system (by using taxis as carriers) on trip cost, vehicle miles traveled, and people travel behavior. Finally, a Stated Preference (SP) survey is presented, designed to collect information about people’s willingness to participate in a crowdshipping system. The survey is analyzed to determine the essential attributes and evaluate the likelihood of individuals participating in the service either as requesters or as carriers. The survey collects information on the preferences and important attributes of New York citizens, describing what segments of the population are willing to participate in a crowdshipping system. While the transportation problems are complex and approximations had to be done within the studies to achieve progress, this dissertation provides a comprehensive way to model and understand the potential impact of efficient utilization of existing resources on transportation systems. Generally, this study offer insights to decisions makers and academics about potential areas of opportunity and methodologies to optimize the transportation system of densely populated areas. This dissertation offers methods that can optimize taxi distribution based on the demand, optimize costs for retail delivery, while providing additional income for individuals. It also provides valuable insights for decision makers in terms of collecting population opinion about the service and analyzing the likelihood of participating in the service. The analysis provides an initial foundation for future modeling and assessment of crowdshipping