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Understanding short-term travel behavior under personal mobility credit allowance scheme using experimental economics

机译:使用实验经济学了解个人流动性信贷津贴计划下的短期旅行行为

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This study proposes personal mobility carbon allowance scheme, collects the data using an online experimental game, and analyzes data with econometric models. Personal mobility carbon allowance (PMCA) schemes allocate carbon credits to users at no cost based on the emissions reduction goal of the system. Users spend carbon credits for travel and a market place exists where users can buy or sell credits. To understand this process, a real-time experimental game tool is developed where players are asked to make travel decisions within the carbon budget set by PMCA and they are allowed to trade carbon credits in a market modeled as a double auction game. Results from estimated random parameter models show that medium and low income group users are highly sensitive to increase in carbon cost for grocery (non-work) trips. Further, the elasticity values show that high income group are less sensitive to carbon cost increase for work trips. The market dynamics such as number of total bids or asks are examined through count data models. The insights from the models can be used to effectively design the parameters of PMCA schemes. In addition, the experimental game tool and the analysis framework can be applied to understand other market based strategies such as carbon tax and tradable emissions permits. (C) 2015 Elsevier Ltd. All rights reserved.
机译:这项研究提出了个人流动性碳配额方案,使用在线实验游戏收集数据,并使用计量经济学模型进行数据分析。个人移动碳配额(PMCA)计划根据系统的减排目标免费向用户分配碳信用额。用户将碳信用额度用于旅行,并且存在一个可以购买或出售信用额度的市场。为了理解这一过程,开发了一种实时实验性游戏工具,要求玩家在PMCA设定的碳预算范围内做出旅行决定,并允许他们在以双向拍卖游戏为模型的市场中交易碳信用额。估计的随机参数模型的结果表明,中低收入群体的用户对食品杂货(非工作)旅行的碳成本增加高度敏感。此外,弹性值表明,高收入人群对工作旅行的碳成本增加不那么敏感。市场动态,例如总出价或要价数量,通过计数数据模型进行检查。这些模型的见解可用于有效设计PMCA方案的参数。此外,实验性游戏工具和分析框架可用于了解其他基于市场的策略,例如碳税和可交易的排放许可。 (C)2015 Elsevier Ltd.保留所有权利。

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