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Fuzzy information in venture capital can be well expressed by neutrosophic numbers, and TODIM method is an effective tool for multi-attribute decision-making. The distance measure is an essential step in TODIM method. The keystone of this paper is to define several new distance measures, in particular the improved interval neutrosophic Euclidean distance, and these measures are applied in the TODIM method for multi-attribute decision-making. Firstly, the normalized generalized interval neutrosophic Hausdorff distance is defined and proved to be valid in this paper. Secondly, we define a weighted parameter interval neutrosophic distance and discuss whether different weight parameters affect the decision result based on TODIM method. Thirdly, considering the preference perspective of decision-makers in behavioral economics, we define the improved interval neutrosophic Euclidean distance with the known parameter of risk preference. Finally, an application example is given to compare the effects of different parameters on the result and discuss the feasibility of these two distance measures in TODIM method.

In this paper, the TODIM method is used to solve the multi-attribute decision-making problem with unknown attribute weight in venture capital, and the decision information is given in the form of single-valued neutrosophic numbers. In order to consider the objectivity and subjectivity of decision-making problems reasonably, the optimal weight is obtained by combining subjective weights and objective weights. Subjective weights are given directly by decision makers. Objective weights are obtained by establishing a weight optimization model with known decision information, then this method will compare with entropy weight method. These simulation results also validate the effectiveness and reasonableness of this proposed method.

Monetary policy changes have an irreplaceable impact on economic activity. Considering the close linkage among economic policies, we employ a bi-directional Granger causality test to investigate the potential linkages between monetary policy uncertainty (MPU) and other categorical economic policy uncertainty (CEPU) in the time and frequency domains. We consider all news-based U.S. categorical economic policy uncertainty indices (CEPU). All monthly CEPU indicators, covering January 1986 to January 2022, can be obtained from the website of Economic Policy Uncertainty. On an average, causality running from each CEPU to MPU is not apparent, while MPU can significantly affect six policy-related uncertainties: taxes, government spending, health care, national security, entitlement programs and regulation. A further frequency-domain study showed the dynamic changes in the relationship between them. For instance, we capture mid- and long-run causality running from tax uncertainty to MPU, while MPU has an impact on taxes in the medium run. Our findings provide policymakers with a better understanding of the nexus between MPU and other CEPU for formulating appropriate economic policies. Particularly, if a sectional government considers the long- and short-term effects of different policies when formulating strategies, risk transmission may be curbed to some extent.

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