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This paper aims to deepen the understanding of the relationship between global economic uncertainty and price volatility, specifically focusing on commodity, industrial materials and energy price indices as proxies for global inflation, analyzing data from 1997 to 2020.

The dynamic conditional correlation generalized autoregressive conditional heteroscedasticity model is used to study the dynamic relationship between variables over a while.

The results demonstrated a positive relationship between commodity prices and the global economic policy uncertainty (GEPU). Except for 1999–2000 and 2006–2008, the results of the energy price index model were very similar to those of the commodity price index. A predominant positive relationship is observed focusing on the connection between GEPU and the industrial material price index. The results of the pairwise Granger causality reveal a unidirectional relationship between the GEPU – the Global Commodity Price Index – and the GEPU – the Global Industrial Material Price Index. However, there is bidirectional causality between the GEPU – the Global Energy Price Index. In sum, changes in price indices can be driven by GEPU as a political factor indicating unfavorable economic conditions.

This paper provides a deeper understanding of the role of global uncertainty in the global inflation process. It fills the gap in the literature by empirically investigating the dynamic movements of global uncertainty and the three most important groups of prices.

The paper aims to propose a practical model for market segment selection and evaluation. The paper carries out a technique of order preference similarity to the ideal solution (TOPSIS) approach to make an operation systematic dealing with multi-criteria decision- making problem.

Introducing a multi-criteria decision-making problem based on TOPSIS approach. A new entropy and new similarity measure under neutrosopic environment are proposed to evaluate the weights of criteria and the relative closeness coefficient in TOPSIS model.

The outcomes show that the TOPSIS model based on new entropy and similarity measure is effective for evaluation and selection market segment. Profitability, growth of the market, the likelihood of sustainable differential advantages are the most important insights of criteria.

This paper put forward an effective multi-criteria decision-making dealing with uncertain information.

How did investors in the Swedish Premium Pension System (PPS) react to the stock market shock ignited by the COVID-19 pandemic?

The authors use fund-level data from the Swedish Pensions Agency on investment choices in the PPS. For each fund, the authors use monthly information on the number of investors and holdings' market value up to November 2020. The authors also use information on the total number of portfolio changes per day. For analyzing whether PPS investors reacted to the pandemic with claiming their pension, the authors use monthly data on the number of investors of a certain age group who initiate their public pension payment.

Trades more than doubled, and shifted capital from equity funds to low risk interest funds. In economic terms, however, trading stayed at low levels–less than two percent of investors traded in March 2020 and there was no effect on pension withdrawals. The increased trading during the market tumult was disproportionately concentrated among investors in the top of the pension capital distribution.

With fund-level data, the authors cannot investigate what in particular made retirement investors stay calm in the midst of a severe market decline. Either, those investors have a long-term investment horizon as they save for their pension or particular features of the system's choice architecture induce inertia and discourage from trading. The sub-group analyses are more consistent with the explanation that PPS-induced inertia is responsible for the relatively small increase in trading activity, but future research could exploit individual level data to explore this in more detail.

The often-criticized PPS choice architecture provided positive side effects in times of a severe market shock by shielding retail investors from committing trading mistakes when trying to outsmart the market.

The study complements previous evidence on the effects of COVID-19 on investor activity. The small response of PPS investors to COVID-19 is in line with earlier US findings on 401(k) accounts during the 2007 financial crisis (Tang et al., 2012) and industry reports about the COVID-19 period (see, e.g. Mitchell, 2020). The authors find no effects at all on public pension withdrawals in Sweden, while evidence from US 401(k) plans indicates a small share of workers taking COVID-related early withdrawals.

The authors show that there is a negative relationship between economic policy uncertainty (EPU) and firm overinvestment using Korean data from 2007 to 2016. Since Jensen (1986) shows that a firm's free cash flow is an important factor of overinvestment, the authors examine how free cash flow influences the sensitivity of overinvestment to EPU. The authors find that a high level of free cash flow attenuates the negative effect of EPU on overinvestment. The authors find that there is no significant difference in the effect of EPU on overinvestment between Chaebol (Korean family-run conglomerates) and non-Chaebol firms, which is consistent with the literature that the features of Chaebol are weakening.

The relevance of present consumption bias on personal finance has been confirmed in several studies and has important theoretical and practical implications. It has important, measurable implications when analyzing commitment or self-control, adherence to healthy habits (e.g. exercising or dieting), procrastination tendencies or savings. The purpose of this paper is to contribute to our understanding of these issues by postulating a model of income uncertainty within a hyperbolic discounting framework that measures the cost of financial intertemporal inconsistencies related to this bias. The emphasis is on the analysis of this cost. We also propose experimental designs and consistent estimation methods, as well as agent-based modelling extensions.

The authors develop a finite-horizon model with hyperbolic preferences. Individuals have a present bias distinct from their discount rate so their choices face intertemporal inconsistencies. The authors further extend the analysis with uncertainty about future incomes. Specifically, individuals live for three periods, and the authors find the optimal consumption levels in the perfect-information benchmark by backward induction. They then proceed to add biases and uncertainty to characterize their implications and measure the costs of the intertemporal inconsistencies they cause.

The authors measure how an agent's utility is greater when they “tie their hands” than when they are free to re-evaluate and change their consumption schedule. This “cost of being vulnerable to falling into temptation” only depends (increasingly) on the measure of the present bias and (decreasingly) on the discount factor. They analyze the varying effects on utility and consumption of changes in impatience and optimism. They conclude by discussing theoretical and practical implications; they also propose agent-based simulations, as well as empirical and experimental designs, to further test the relevance and applications of the results.

This model has important, measurable implications when analyzing commitment or self-control, adherence to healthy habits (e.g. exercising or dieting), procrastination tendencies or savings.

The results enhance the estimation of the costs of present biases such that employers can better identify the incentives required to acquire and retain human capital. The authors provide evidence that workers are vulnerable to contract renegotiations and about the need for a regulator that restores ex-ante efficiency. Similarly, in the private sector, firms could recognize the postulated consumer profiles and focus their resources on anxious, too-optimistic or potentially addictive consumers; this, again, provides some justification about the need for a regulator.

In traditional exponential discounting, the marginal rate of substitution of consumption between two points depends only on their distance; thus, it allows none of the intertemporal inconsistencies we often observe in real life. Therefore, hyperbolic discounting better fits the data. The authors model choice under uncertainty and focus on the costs caused when present biases (ex-post) push behaviour away from ex-ante optimality. They conclude by proposing experimental designs to further enhance the estimation and implications of these costs. The postulated refinements have the potential to improve previous analyses on commitment devices and commitment-related regulation.

The current paper aims to present a formal model illustrating how payoff imbalances among the members of a team of decision makers (DMs) who must undertake a project condition the final outcome obtained. This result builds on the fact that payoffs imbalances would lead to different performance levels among the employees and managers who compose a team. The analysis is applied to a strategic environment, where a project requiring coordination among the DMs within the team must be developed.

The intuition behind the strategic framework on which the results are based is twofold. The authors build on the literature on social comparisons and assume that employees and managers acquire information on the payoffs received by other members of the team while being affected by the resulting comparisons, and they follow the economic literature on firm boundaries determined via incomplete contracts. In this case, employees and managers may underperform if they feel aggrieved by the outcome of the contract giving place to deadweight losses when developing the project.

The authors illustrate how a team-based performance reward structure may lead to a coordinated equilibrium even when team managers and employees receive different payoffs and exhibit shading incentives based on the payoff differentials between them. The authors will also illustrate how identical shading intensities by both groups of DMs imply that shading by the managers imposes a lower cost on the profit structure of the firm because it leads to a lower decrease in the cooperation incentives of the other members of the team. Finally, the authors show how differences in shading intensity between both types of DMs trigger a strategic defect mechanism within the team that determines the outcome of the project.

The novel environment of team cooperation and defection through shading introduced in this paper is designed to deal with the strategic decisions taken by DMs when undertaking a project within a group. In particular, the intensity of shading applied by the DMs will be endogenously determined by the relative payoffs received, which allows to account for different scenarios, where relative payoff differentials among DMs determine the outcome of the project.

This paper aims to propose an integration of the analytic hierarchy process (AHP) and data envelopment analysis (DEA) methods in a multiattribute grey relational analysis (GRA) methodology in which the attribute weights are completely unknown and the attribute values take the form of fuzzy numbers.

This research has been organized to proceed along the following steps: computing the grey relational coefficients for alternatives with respect to each attribute using a fuzzy GRA methodology. Grey relational coefficients provide the required (output) data for additive DEA models; computing the priority weights of attributes using the AHP method to impose weight bounds on attribute weights in additive DEA models; computing grey relational grades using a pair of additive DEA models to assess the performance of each alternative from the optimistic and pessimistic perspectives; and combining the optimistic and pessimistic grey relational grades using a compromise grade to assess the overall performance of each alternative.

The proposed approach provides a more reasonable and encompassing measure of performance, based on which the overall ranking position of alternatives is obtained. An illustrated example of a nuclear waste dump site selection is used to highlight the usefulness of the proposed approach.

This research is a step forward to overcome the current shortcomings in the weighting schemes of attributes in a fuzzy multiattribute GRA methodology.

This study investigates the effect of global and domestic uncertainty on the dynamics of portfolio investment in 21 economies (mostly advanced and larger emerging economies) from 2001–2016.

Specifically, the evolution of the net portfolio equity investment inflows (FPI net inflows) and the evolution of net portfolio investment (FPI net) are investigated in a context in which the degree and the volatility of domestic economic policy uncertainty (EPU) and world uncertainty index (WUI) varied. The authors provide an empirical analysis through the sequential (two-stage) estimation of linear panel data models for unbalanced panel data.

An increase in the degree and volatility of domestic EPU has a significant negative influence on FPI net inflows, while an increase in WUI has a significant positive one. Notably, a simultaneous increase in the domestic EPU and WUI enhances the net inflows of FPI, whereas a simultaneous increase in the volatility of these indicators reduces the net inflows of FPI. An increase in the degree and volatility of both domestic EPU and WUI have a significant positive effect on the net portfolio investment, implying that a significant net portfolio investment is going out of the country.

The results of this study encourage international investors to consider uncertainty indicators (and, more specifically, their variations) in their portfolio strategy to optimize their position on the international markets. The findings of this study invite policy-makers from large countries to reduce the perceived domestic uncertainty since this parameter can influence international investors' sensitivity and willingness to diversify their position out of the country.

The authors' approach focuses on the variations of uncertainty (existing literature mainly works with the indicators). While the results confirm the role played by large markets in international portfolio investment management, it nuances the changes in the portfolio management behaviors toward other markets when facing a changing uncertainty.

This study aims to investigate the influences of global uncertainty indicators volatility on the domestic socioeconomic and environmental vulnerability in a sample of 54 developing countries.

The two-step system generalized method of moments estimator is recruited to deal with autoregression and endogeneity matter in our dynamic panel data. Seven different global uncertainty indicators (US trade uncertainty; world trade uncertainty; economic policy uncertainty; world commodities and oil prices; the geopolitical risk index and the world uncertainty index) have been mobilized and compared for their empirical impact on the economic (growth and GDP), social (the misery index and income inequality) and environmental (CO₂ emissions) vulnerabilities of nations.

Our empirical estimations suggest that the socioeconomic and environmental vulnerability cannot be solved through the same pattern: all decrease of a particular aspect will necessarily have a cost and an opposite influence on at least one of the other aspects of the nations' vulnerability.

The originality of this article is to combine these three dimensions of vulnerability in the same investigation. To our knowledge, our research is one of the few providing a joint analysis of the influence of global uncertainty on the economic and socioenvironmental countries' vulnerabilities – given the fact social, economic and environmental aspects are at the heart of the UN sustainable goals, our study can be seen as an investigation of the nations' capabilities to work proactively on meaningful sustainable goals in an increasingly uncertain world.

This study investigates the impact of uncertainty on the mean-variance relationship. We find that the stock market's expected excess return is positively related to the market's conditional variances and implied variance during low uncertainty periods but unrelated or negatively related to conditional variances and implied variance during high uncertainty periods. Our empirical evidence is consistent with investors' attitudes toward uncertainty and risk, firms' fundamentals and leverage effects varying with uncertainty. Additionally, we discover that the negative relationship between returns and contemporaneous innovations of conditional variance and the positive relationship between returns and contemporaneous innovations of implied variance are significant during low uncertainty periods. Furthermore, our results are robust to changing the base assets to mimic the uncertainty factor and removing the effect of investor sentiment.