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This paper defends The Transformation of Values into Prices on the Basis of Random Systems, published in EIER, by answering to the Comments made in the same journal by Professors Mori, Morioka and Yamazaki. The clarifications mainly concern the justification of the randomness assumptions, the conditions needed to obtain the equality of total profit with total surplus value in the simplified one-industry system and the invariance of the results to changes in the units of measurement.
Sample-based longitudinal discrete choice experiments: preferences for electric vehicles over time
(2021)
Discrete choice experiments have emerged as the state-of-the-art method for measuring preferences, but they are mostly used in cross-sectional studies. In seeking to make them applicable for longitudinal studies, our study addresses two common challenges: working with different respondents and handling altering attributes. We propose a sample-based longitudinal discrete choice experiment in combination with a covariate-extended hierarchical Bayes logit estimator that allows one to test the statistical significance of changes. We showcase this method’s use in studies about preferences for electric vehicles over six years and empirically observe that preferences develop in an unpredictable, non-monotonous way. We also find that inspecting only the absolute differences in preferences between samples may result in misleading inferences. Moreover, surveying a new sample produced similar results as asking the same sample of respondents over time. Finally, we experimentally test how adding or removing an attribute affects preferences for the other attributes.
The modern tontine : an innovative instrument for longevity risk management in an aging society
(2020)
We investigate whether a historical pension concept, the tontine, yields enough innovative potential to extend and improve the prevailing privately funded pension solutions in a modern way. The tontine basically generates an age-increasing cash flow, which can help to match the increasing financing needs at old ages. In contrast to traditional pension products, however, the tontine generates volatile cash flows, which means that the insurance character of the tontine cannot be guaranteed in every situation. By employing Multi Cumulative Prospect Theory (MCPT) we answer the question to what extent tontines can be a complement to or a substitute for traditional annuities. We find that it is only optimal to invest in tontines for a certain range of initial wealth. In addition, we investigate in how far the tontine size, the volatility of individual liquidity needs and expected mortality rates contribute to the demand for tontines.
Crowdfunding platforms offer project initiators the opportunity to acquire funds from the Internet crowd and, therefore, have become a valuable alternative to traditional sources of funding. However, some processes on crowdfunding platforms cause undesirable external effects that influence the funding success of projects. In this context, we focus on the phenomenon of project overfunding. Massively overfunded projects have been discussed to overshadow other crowdfunding projects which in turn receive less funding. We propose a funding redistribution mechanism to internalize these overfunding externalities and to improve overall funding results. To evaluate this concept, we develop and deploy an agent-based model (ABM). This ABM is based on a multi-attribute decision-making approach and is suitable to simulate the dynamic funding processes on a crowdfunding platform. Our evaluation provides evidence that possible modifications of the crowdfunding mechanisms bear the chance to optimize funding results and to alleviate existing flaws.
Correction to: Computational Economics https://doi.org/10.1007/s10614-020-10061-x
The original publication has been updated. In the original publication of this article, under the Introduction heading section, the corrections to the second paragraph’s inline equation were not incorporated. The author’s additional corrections have also been incorporated. The publisher apologizes for the error made during production.
Vehicle registrations have been shown to strongly react to tax reforms aimed at reducing CO2 emissions from passengers’ cars, but are the effects equally strong for positive and negative tax changes? The literature on asymmetric reactions to price and tax changes has documented asymmetries for everyday goods but has not yet considered durables. We leverage multiple vehicle registration tax (VRT) reforms in Norway and estimate their impact on within car-model substitutions. We estimate stronger effects for cars receiving tax cuts and rebates than for those affected by tax increases. The corresponding estimated elasticity is − 1.99 for VRT decreases and 0.77 for increases. As consumers may also substitute across car models, our estimates represent a lower bound.
This paper uses historical monthly temperature level data for a panel of 114 countries to identify the effects of within year temperature level variability on productivity growth in five different macro regions, i.e., (1) Africa, (2) Asia, (3) Europe, (4) North America and (5) South America. We find two primary results. First, higher intra-annual temperature variability reduces (increases) productivity in Europe and North America (Asia). Second, higher intra-annual temperature variability has no significant effects on productivity in Africa and South America. Additional empirical tests indicate also the following: (1) rising intra-annual temperature variability reduces productivity (even thought less significantly)in both tropical and non-tropical regions, (2) inter-annual temperature variability reduces (increases) productivity in North America (Europe) and (3) winter and summer inter-annual temperature variability generates a drop in productivity in both Europe and North America. Taken together, these findings indicate that temperature variability shocks tend to have stronger adverse economic effects among richer economies. In a production economy featuring long-run productivity and temperature volatility shocks, we quantify these negative impacts and find welfare losses of 2.9% (1%) in Europe (North America).
Solving High-Dimensional Dynamic Portfolio Choice Models with Hierarchical B-Splines on Sparse Grids
(2021)
Discrete time dynamic programming to solve dynamic portfolio choice models has three immanent issues: firstly, the curse of dimensionality prohibits more than a handful of continuous states. Secondly, in higher dimensions, even regular sparse grid discretizations need too many grid points for sufficiently accurate approximations of the value function. Thirdly, the models usually require continuous control variables, and hence gradient-based optimization with smooth approximations of the value function is necessary to obtain accurate solutions to the optimization problem. For the first time, we enable accurate and fast numerical solutions with gradient-based optimization while still allowing for spatial adaptivity using hierarchical B-splines on sparse grids. When compared to the standard linear bases on sparse grids or finite difference approximations of the gradient, our approach saves an order of magnitude in total computational complexity for a representative dynamic portfolio choice model with varying state space dimensionality, stochastic sample space, and choice variables.
