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on Economic Design |
| By: | Haoge Chang |
| Abstract: | This paper considers the estimation of treatment effects in randomized experiments with complex experimental designs, including cases with interference between units. We develop a design-based estimation theory for arbitrary experimental designs. Our theory facilitates the analysis of many design-estimator pairs that researchers commonly employ in practice and provide procedures to consistently estimate asymptotic variance bounds. We propose new classes of estimators with favorable asymptotic properties from a design-based point of view. In addition, we propose a scalar measure of experimental complexity which can be linked to the design-based variance of the estimators. We demonstrate the performance of our estimators using simulated datasets based on an actual network experiment studying the effect of social networks on insurance adoptions. |
| Date: | 2023–11 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:2311.06891&r=des |
| By: | Minati Rath; Hema Date |
| Abstract: | In many real-world datasets, rows may have distinct characteristics and require different modeling approaches for accurate predictions. In this paper, we propose an adaptive modeling approach for row-type dependent predictive analysis(RTDPA). Our framework enables the development of models that can effectively handle diverse row types within a single dataset. Our dataset from XXX bank contains two different risk categories, personal loan and agriculture loan. each of them are categorised into four classes standard, sub-standard, doubtful and loss. We performed tailored data pre processing and feature engineering to different row types. We selected traditional machine learning predictive models and advanced ensemble techniques. Our findings indicate that all predictive approaches consistently achieve a precision rate of no less than 90%. For RTDPA, the algorithms are applied separately for each row type, allowing the models to capture the specific patterns and characteristics of each row type. This approach enables targeted predictions based on the row type, providing a more accurate and tailored classification for the given dataset.Additionally, the suggested model consistently offers decision makers valuable and enduring insights that are strategic in nature in banking sector. |
| Date: | 2023–11 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:2311.10799&r=des |
| By: | Jens Gudmundsson; Jens Leth Hougaard; Juan D. Moreno-Ternero; Lars Peter {\O}sterdal |
| Abstract: | We study the design of optimal incentives in sequential processes. To do so, we consider a basic and fundamental model in which an agent initiates a value-creating sequential process through costly investment with random success. If unsuccessful, the process stops. If successful, a new agent thereafter faces a similar investment decision, and so forth. For any outcome of the process, the total value is distributed among the agents using a reward rule. Reward rules thus induce a game among the agents. By design, the reward rule may lead to an asymmetric game, yet we are able to show equilibrium existence with optimal symmetric equilibria. We characterize optimal reward rules that yield the highest possible welfare created by the process, and the highest possible expected payoff for the initiator of the process. Our findings show that simple reward rules invoking short-run incentives are sufficient to meet long-run objectives. |
| Date: | 2023–11 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:2311.12494&r=des |
| By: | Fecho, Mariska; Zöll, Anne |
| Abstract: | Machine Learning (ML) systems have an enormous potential to improve medical care, but skepticism about their use persists. Their inscrutability is a major concern which can lead to negative attitudes reducing end users trust and resulting in rejection. Consequently, many ML systems in healthcare suffer from a lack of user-centricity. To overcome these challenges, we designed a user-centered, trustworthy ML system by applying design science research. The design includes meta-requirements and design principles instantiated by mockups. The design is grounded on our kernel theory, the Trustworthy Artificial Intelligence principles. In three design cycles, we refined the design through focus group discussions (N1=8), evaluation of existing applications, and an online survey (N2=40). Finally, an effectiveness test was conducted with end users (N3=80) to assess the perceived trustworthiness of our design. The results demonstrated that the end users did indeed perceive our design as more trustworthy. |
| Date: | 2023–12–10 |
| URL: | http://d.repec.org/n?u=RePEc:dar:wpaper:138903&r=des |
| By: | Syngjoo Choi; Bongseob Kim; Young-Sik Kim; Ohik Kwon |
| Abstract: | Privacy protection is among the key features to consider in the design of central bank digital currency (CBDC). Using a nationally representative sample of over 3, 500 participants, we conduct a randomized online survey experiment to examine how the willingness to use CBDC as a means of payment varies with the degree of privacy protection and information provision on the privacy benefits of using CBDC. We find that both factors significantly increase participants' willingness to use CBDC by up to 60% when purchasing privacy-sensitive products. Our findings provide useful insights regarding the design and the public's adoption of CBDC. |
| Keywords: | central bank digital currency (CBDC), privacy, randomized online survey experiment |
| JEL: | E40 E50 C90 |
| Date: | 2023–11 |
| URL: | http://d.repec.org/n?u=RePEc:bis:biswps:1147&r=des |
| By: | Marie Petitet; Amro Elshurafa; Frank Felder (King Abdullah Petroleum Studies and Research Center) |
| Abstract: | Energy prices in Europe have been soaring, and policymakers are trying to find solutions to immediately contain the energy prices for end-consumers and to enhance the market design in the longer term. This paper discusses some of the current events that are facing the power sector in Europe and some challenges that may face the industry more generally in the future. Then, we propose policy recommendations in the context of Gulf Cooperation Council (GCC) countries by contrasting the power sector design in place in this region with that in the European region. |
| Keywords: | Climate change, Carbon Market, Clean technology, Alternative fuels |
| Date: | 2023–10–24 |
| URL: | http://d.repec.org/n?u=RePEc:prc:dpaper:ks--2023-dp24&r=des |