EconStor Collection:
https://hdl.handle.net/10419/107
2024-03-29T02:37:50ZA needs-based framework for approximating decisions and well-being
https://hdl.handle.net/10419/284393
Title: A needs-based framework for approximating decisions and well-being
Authors: Krecik, Markus
Abstract: Behavioral economics has so far largely avoided discussing the psychological origins of preferences, as well as their relation to needs. This has not only restricted interdisciplinary exchange, but also significantly limits the predictive capabilities of models. For example, the revealed preference approach can only reliably predict repeating choices, while needing large amounts of observations for calibration. In this paper, I show how unifying preferences with the psychological concept of needs strengthens economic models, by developing a decision-making framework for well-being assessment and choice prediction. To present the direct merit of this approach, I show how this framework yields a systematic approximation scheme, which is able to solve limitations of current approaches by describing new alternatives, non-repeating choices, or otherwise unobservable desires. Meanwhile, the approximation scheme requires less observations on an individual level than current approaches. I achieve this by constructing a hierarchical dependency between human motivations and preferences through the language of needs. I show the basic feasibility of the approximation scheme through simulations on random populations. In practice, the framework is applicable in situations where individuals exert choices only once and measuring preferences is expensive, like evaluating policy proposals or predicting decisions under technological change.2024-01-01T00:00:00ZPreference dynamics: A procedurally rational model of time and effort allocation
https://hdl.handle.net/10419/284389
Title: Preference dynamics: A procedurally rational model of time and effort allocation
Authors: Krecik, Markus
Abstract: Current time allocation and household production models face three major weaknesses: First, they only describe the average time allocation. Thus, information about the order of activities is lost. Therefore, it is impossible to describe the influence of activities on later ones. Such interactions are likely pervasive, and can significantly alter behavior. Second, they are unable to describe the effort allocation of individuals, although effort influences one's time allocation. Thereby, they are either unable or very limited in describing labor productivity or multitasking although individuals frequently multitask. Through the omission of interactions and effort allocation, current models yield biased descriptions of e.g. price and time elasticities. Third, they require strong assumptions, such as perfect foresight or periodic environments, and thus cannot describe behavior in unpredictable environments, like reactions to external shocks. In this paper, I provide a remedy for these shortcomings by developing a dynamical model of procedurally rational decision making. The basic idea of the model is a feedback loop between experienced utility, decision utility, and activities. In applications of the model, I show how introducing a work-leisure interaction and multitasking significantly changes elasticities and how nonmarginal external shocks cause short-term demand surges, none of which can be described by current time allocation models.2024-01-01T00:00:00ZMultidimensional tax compliance attitude
https://hdl.handle.net/10419/279435
Title: Multidimensional tax compliance attitude
Authors: Bruns, Christoffer; Fochmann, Martin; Mohr, Peter N. C.; Torgler, Benno
Abstract: Citizen tax compliance significantly dictates governmental fiscal capacities. Recognizing this, understanding the determinants of tax compliance remains paramount. While existing literature frequently isolates and tests individual determinants such as audit likelihood, penalty structures, tax morale, and perceived fairness, an integrative, bottom-up approach addressing the spectrum of tax compliance attitudes has largely been overlooked. Addressing this gap, our study constructs a multidimensional Tax Compliance Attitude Inventory (TCAI) by harmonizing real taxpayer responses with established theoretical underpinnings. Through factor analysis, we delineate four pivotal factors: (i) morale, (ii) monetary benefit, (iii) deterrence, and (iv) authority. Notably, morale and deterrence emerge as consistent influencers of tax compliance. Embracing this multidimensionality, our cluster analysis demarcates two distinct taxpayer personas: (a) moralists and (b) rationalists. Our findings underscore that moralists consistently exhibit higher tax compliance than their rationalist counterparts. We further present a streamlined classification algorithm to operationalize the TCAI in new datasets, minimizing item count. This work serves as a seminal contribution, offering both academia and tax authorities a robust, quantitative tool to gauge tax compliance attitudes.2023-01-01T00:00:00ZThe fade away effect of initial nonresponse bias in regression analysis
https://hdl.handle.net/10419/268486
Title: The fade away effect of initial nonresponse bias in regression analysis
Authors: Alho, Juha M.; Rendtel, Ulrich; Khan, Mursala
Abstract: High nonresponse rates have become a rule in survey sampling. In panel surveys there occur additional sample losses due to panel attrition, which are thought to worsen the bias resulting from initial nonresponse. However, under certain conditions an initial wave nonresponse bias may vanish in later panel waves. We study such a "Fade away" of an initial nonresponse bias in the context of regression analysis. By using a time series approach for the covariate and the error terms we derive the bias of cross-sectional OLS-estimates of the slope coefficient. In the case of no subsequent attrition and only serial correlation an initial bias converges to zero. If the nonresponse affects permanent components the initial bias will decrease to a limit which is determined by the size of the permanent components. Attrition is discussed here in a worst case scenario, where there is a steady selective drift into the same direction as in the initial panel wave. It is shown that the fade away effect dampens the attrition effect to a large extent depending on the temporal stability of the covariate and the dependent variable. The attrition effect may by further reduced by a weighted regression analysis, where the weights are estimated attrition probabilities on the basis of the lagged dependent variable. The results are discussed with respect to surveys with unsure selection procedures which are used in a longitudinal fashion, like access panels.2023-01-01T00:00:00Z