Temptation and Taxation

We study optimal taxation when consumers have temptation and self‐control problems. Embedding the class of preferences developed by Gul and Pesendorfer into a standard macroeconomic setting, we first prove, in a two‐period model, that the optimal policy is to subsidize savings when consumers are tempted by “excessive” impatience. The savings subsidy improves welfare because it makes succumbing to temptation less attractive. We then study an economy with a long but finite horizon which nests, as a special case, the Phelps–Pollak–Laibson multiple‐selves model (thereby providing guidance on how to evaluate welfare in this model). We prove that when period utility is logarithmic, the optimal savings subsidies increase over time for any finite horizon. Moreover, as the horizon grows large, the optimal policy prescribes a constant subsidy, in contrast to the well known Chamley–Judd result.     

政府补偿下基于私人公平偏好的PPP项目投资决策分析

针对PPP （Private-Public Partnership）项目收益的不确定性,引入政府补偿契约问题。考虑私人投资者对政府补偿存在公平偏好倾向,借鉴BO模型的思想,将私人投资要求的特许收益作为其公平参考点,并通过对FS模型加以改进,构建私人公平偏好效用函数,从而给出私人在政府补偿下的投资决策模型。通过模型求最优解和概率分析,探讨私人公平偏好对其最优投资决策的影响,并借助数值分析给予检验。结果表明:当政府补偿使私人感知有利不公平时,私人将选择期望效用最大的最优投资,并随其感知程度的增加而增加;而当政府补偿使私人感知不利不公平时,私人最优投资及可能性将在有限公平偏好内随其感知程度的增加而减小。     

产业共性技术扩散中政府作用最优力度分析——基于变换的Bass模型

基于一定理论假设将Bass模型中技术扩散的内部影响因素和外部影响因素分别与市场作用和政府作用对应起来,并着眼于政府作用对市场作用的“挤出”效应建立起政府作用与市场作用之间的函数关系,以此来对Bass模型进行变换,使其能刻画政府作用对产业共性技术扩散速度和时间路径的影响。基于变换的Bass模型,以最大化技术扩散速度为目标构建最优化问题以求得政府作用最优力度,由最优化问题可知政府作用对市场作用的“挤出”效应越大,最优政府作用力度就应该越小。还基于相关数据进行了数值模拟分析,并且验证了模型的有效性。研究认为:由于存在政府干预对市场作用的“挤出”效应,在促进产业共性技术扩散中需要把握最优的干预力度即政府作用最优力度,在量化政府作用和市场作用的基础上,求解出来的政府作用最优力度系数可为政府有效和适当干预技术扩散提供理论上的一个尺量。     

Optimal designs for estimating a choice hierarchy by a general nested multinomial logit model

Abstract

In choice experiments the process of decision-making can be more complex than the proposed by the Multinomial Logit Model (MNL). In these scenarios, models such as the Nested Multinomial Logit Model (NMNL) are often employed to model a more complex decision-making. Understanding the decision-making process is important in some fields such as marketing. Achieving a precise estimation of the models is crucial to the understanding of this process. To do this, optimal experimental designs are required. To construct an optimal design, information matrix is key. A previous research by others has developed the expression for the information matrix of the two-level NMNL model with two nests: Alternatives nest (J alternatives) and No-Choice nest (1 alternative). In this paper, we developed the likelihood function for a two-stage NMNL model for M nests and we present the expression for the information matrix for 2 nests with any amount of alternatives in them. We also show alternative D-optimal designs for No-Choice scenarios with similar relative efficiency but with less complex alternatives which can help to obtain more reliable answers and one application of these designs.     

Use of the 21% rulf in experimental design

When the probabilities underlying a contingency table are assumed to be symmetric, it is advantageous to combine the frequencies of equiprobable cells (Haber, 1981, 1982).The present work introduces models, as well as exact and asymptotic methods, for analyzing such ‘intraclass’ contingency tables in several dimensions.     

A stepwise algorithm for selecting category boundaries for the chi-squared goodness-of-fit test

A stepwise algorithm for selecting categories for the chisquared goodness-of-fit test with completely specified continuous null and alternative distributions is described in this paper. The procedure's starting point is an initial partitioning of the sample space into a large number of categories. A second partition with one fewer category is constructed by combining two categories of the original partition. The procedure continues until there are only two categories; the partition in the sequence with the highest estimated power is the one chosen. For illustartive purposes, the performance of the algorithm is evaluated for several hypothesis tests of the from H₀: normal distribution vs. H₁: a specific mixed normal distribution. For each test considered, the partition identified by the algorithm was compared to several equiprobable partitions, including the equiprobable partition with the highest estimated power. In all cases but one, the algorithm identified a parttion with higher estimated power than the best equiprobable partition. Applciations of the procedure are discussed.     

Optimal spacing of quantiles for the estimation of the mixing parameters in a mixture of two exponential distributions

Methods for estimating the mixing parameters in a mixture of two exponential distributions are proposed. The estimators proposed are consistent and BAN(best asymptotically normal). The optimal spacings for estimating these mixture parameters are calculated.