Econometric Demand and Welfare Analysis

政府的市场干预在真实的生活中无处不在，包括对产品和服务的税收和补贴、行业监管和市场力量的适度、扩大学校选择的覆盖范围、行为推动和补贴，以引导信息不足的决策者选择最佳的保险产品，等等。拟议项目旨在开发新的计量经济学工具，利用微观数据对这些干预措施进行实际成本效益分析。这种计算的主要挑战是通过消费者福利来衡量利益，消费者福利等于政策干预所产生的变化对消费者的货币价值，而研究人员通常无法观察到这种变化。此外，当消费者的偏好不同时，收益和成本是不均匀的，因此需要进行统计分析，以确定整个人口的福利分配情况。拟议的项目旨在开发计量经济学工具，以便进行这种分析。这些工具将有助于（1）从观察到的选择行为中了解消费者偏好的性质，以及（2）应用这些知识来评估现有和潜在的公共政策对各种重要现实生活背景下的社会福利的影响，如教育，住房，医疗保健，通勤旅行和度假住宿。该提案包括四个部分，解决以下具体问题：（A）如何将社会福利总额纳入计量经济学项目评估和政策的最佳目标;现有文献通常将个人结果作为研究对象，而不是特定结果对个人本身有多大价值。(B)如何在享乐环境中衡量消费者福利，在享乐环境中有许多可能的选择，每一种选择都具有个人偏好的几个特征，例如住房选择中的当地设施和犯罪，以及学校选择中的学生-教师比例和学术成果。(C)如何测试最优的个人选择的保险计划和福利潜力的推动在保险市场上，使用微观数据的选择覆盖和随后的索赔。(D)如何使用从网上房源中收集的“大数据”，分析传统和网上供应商市场的需求模式和消费者福利，并应用于计算共享住宿服务Airbnb的福利影响。这些子项目的共同主题是开发新的计量经济学方法，用于分析建立在严格经济理论基础上的实际福利计算的横截面数据。最终目标是通过对研究人员未观察到的个人偏好异质性施加最小或不施加假设来获得可信的经验结果。这是在现有的计量经济学文献中的福利分析，依赖于分析方便，但在经济上未经证实的特设假设消费者的偏好和异质性的实证工具。因此，拟议的项目将建立在由PI启动的研究计划的基础上，该计划由欧洲研究理事会在2016-21年期间提供的5年整合补助金资助，并将其边界扩展到以前未探索的背景和技术上分析新类型的数据，以便为与这些背景相关的基本政策问题提供可靠的答案。

Market-interventions by the government are ubiquitous in real life and include taxes and subsidies on products and services, regulation of industries and moderation of market-power, expansion of catchment areas for school-choice, behavioral nudges and subsidies to steer under-informed decision-makers towards their optimal choice of insurance products, and so forth. The proposed project aims to develop novel econometric tools for practical cost-benefit analysis of such interventions using micro-level data. The key challenge of such calculations is the measurement of the benefits via consumer welfare, which equals the monetary value to the consumer of the change resulting from the policy intervention, that is typically unobserved by a researcher. Further, when consumers differ in preferences, the benefits and costs are heterogeneous, hence statistical analysis is required to characterize the distribution of welfare across the population. The proposed project aims to develop econometric tools to enable such analysis. These tools will be useful for (1) understanding the nature of consumer preferences from observed choice behavior, and (2) for applying that knowledge to evaluate existing and potential public policies in terms of their impact on social welfare in a variety of important real-life contexts such as education, housing, healthcare, commuter travel and holiday accommodation. The proposal consists of four parts addressing the following specific questions:(A) How to incorporate aggregate social welfare in econometric program evaluation and the optimal targeting of policies; the existing literature typically foucuses on an individual outcome as its object of study, as opposed to how much that particular outcome is worth to the individual herself.(B) how to measure consumer welfare in hedonic settings where there are many possible alternatives, each characterized by a few features that individuals have preference over, such as local amenities and crime in housing choice and student-teacher ratio and academic outcomes in school-choice.(C) how to test optimality of individuals' choice of insurance-plans and the welfare potential of nudges in insurance markets, using micro-data on choice of cover and subsequent claims.(D) how to use `big data' collected from online listings to analyze demand patterns and consumer welfare in markets with both traditional and online providers, with an application to calculating the welfare impact of the shared accommodation service Airbnb. The common theme of these sub-projects is the development of novel econometric methods for analyzing cross-sectional data for practical welfare calculations that are founded on rigorous economic theory. The ultimate goal is to obtain credible empirical results by imposing minimal or no assumptions on heterogeneity in individual preferences unobserved by researchers. This is in contrast to available empirical tools for welfare analysis in the existing econometric literature which rely on analytically convenient but economically unsubstantiated ad-hoc assumptions on consumer preferences and their heterogeneity. As such, the proposed project will build on the research programme started by the PI that was funded by a 5-year Consolidator grant by the European Research Council between 2016-21, and expand its boundaries both substantively to previously unexplored contexts and technically to analyzing new types of data in order to provide credible answers to fundamental policy questions relevant to these contexts.