The effect of dynamic integrated resort experience on Croatian customer behavior

This paper aims to gain knowledge on customers’ experience toward integrated resorts in Croatia. Customer perception toward integrated resorts was collected via face‐to‐face survey. The multidimensional experiential values and behaviors of 354 customers were studied. The data were analyzed using structural equation modeling. Croatian customers are engaged with the integrated resort experience. This engagement influences their satisfaction and behavioral intention. Specifically, customers with high playfulness and service expectations tend to engage positive behavioral intention toward the integrated resort brand. This paper offers the first insight into the relationship between experiential value and behavioral intention in the integrated resort setting.     

Competition and Environmental Policy in the EU: Old Foes,New Friends?

European competition authorities consider environmental and competition policy to be complementary, as each has the objective of improving social welfare. Naturally, one would imagine that environmental considerations have already been accounted for in competition policy practice, but thus far, only in the case of voluntary environmental agreements. This paper analyzes the extent to which the two types of policy are complementary by examining the legal framework of competition policy, voluntary environmental agreements and three competition cases with equal relevance to the environment and then examines the basic theoretical economic observation that less competition implies lower pollution levels relative to more competition. This trade-off between the benefits of reduced emissions on the one side and increased competition on the other implies that disregarding environmental considerations in the implementation of competition policy entails a negative externality, which can be eliminated if environmental considerations are internalized in competition policy. The impact of the externality is found to depend on the emission level, the emission damage, and market size. Further, this implies that if competition authorities were to adopt a broad definition of the relevant market in competition cases, then environmental considerations would play a limited role in competition policy, whereas a narrow definition implies that environmental considerations should have a much more important place than competitive considerations in competition policy.     

Optimal Management of Environmental Externalities with Time Lags and Uncertainty

Many environmental externalities occur with time lags that can range from a few days to several centuries in length, and many of these externalities are also subject to uncertainty. In this paper, we examine the key features of an optimal policy to manage environmental externalities that are both lagged and stochastic. We develop a two-period, two-polluter model and obtain closed-form solutions for optimal emissions levels under different combinations of damage functions and stochastic processes. These solutions show that it is not obvious whether greater control should be exerted on polluters that generate externalities with longer lags or on polluters that generate externalities with shorter lags. We find that the optimal ranking of polluters with respect to the length of the time lag associated with their externality will depend on (a) the discount rate, (b) conditional expectations of future states of the polluted resource, (c) persistence of the pollutant, and (d) initial conditions.     

Markov decision processes under model uncertainty

We introduce a general framework for Markov decision problems under model uncertainty in a discrete-time infinite horizon setting. By providing a dynamic programming principle, we obtain a local-to-global paradigm, namely solving a local, that is, a one time-step robust optimization problem leads to an optimizer of the global (i.e., infinite time-steps) robust stochastic optimal control problem, as well as to a corresponding worst-case measure. Moreover, we apply this framework to portfolio optimization involving data of the . We present two different types of ambiguity sets; one is fully data-driven given by a Wasserstein-ball around the empirical measure, the second one is described by a parametric set of multivariate normal distributions, where the corresponding uncertainty sets of the parameters are estimated from the data. It turns out that in scenarios where the market is volatile or bearish, the optimal portfolio strategies from the corresponding robust optimization problem outperforms the ones without model uncertainty, showcasing the importance of taking model uncertainty into account.     

Forecasting high-frequency excess stock returns via data analytics and machine learning

Borsa Istanbul introduced data analytics to present additional information about its market conditions. We examine whether this product can be utilized via various machine learning methods to predict intraday excess returns. Accordingly, these analytics provide significant prediction ratios above 50% with ideal profit ratios that can reach up to 33%. Among all the methods considered, XGBoost (logistic regression) performs better in predicting excess returns in the long-term analysis (short-term analysis). Results provide evidence for the benefits of both the analytics and the machine learning methods and raise further discussion on the semistrong market efficiency.     

The role of satisfaction in labor diaspora dynamics: An analysis of BREXIT effects

In diaspora research, people's international mobility is often understood as a response to pull-push forces on an economic macro-level or as part of diasporic waves. However, labor diaspora formations are also influenced by micro-level (i.e., individual perceptions) drivers related to work per se, such as satisfaction. This explorative qualitative study takes a novel angle and focuses on the role of Portuguese nurses’ satisfaction with the evaluation of the Brexit scenario and its effects on this labor diaspora's mobility and stability. The findings illustrate that satisfaction, although affected by uncertainty, mainly relates to perceived working conditions and legislation and the possibilities to communicate with locals and other diasporans. This paper provides suggestions for future research and contributes to the development of theory on staying and human stickiness, explaining the dynamics of exit and entry in (re-)migration decision making.     

How Wealthy are the Rich?

Underreporting and undersampling biases in top tail wealth, although widely acknowledged, have not been statistically quantified so far, essentially because they are not readily observable. Here we exploit the functional form of power law-like regimes in top tail wealth to derive analytical expressions for these biases, and use German microdata from a popular survey and rich list to illustrate that tiny differences in non-response rates lead to tail wealth estimates that differ by an order of magnitude, in our case ranging from 1 to 9 trillion euros. Underreporting seriously compounds the problem, and we find that the estimation of totals in scale-free systems oftentimes tends to be spurious. Our findings also suggest that recent debates on the existence of scale- or type-dependence in returns to wealth are ill-posed because the available data cannot discriminate between scale- or type-dependence, on one hand, and statistical biases, on the other hand. Yet both economic theory and mathematical formalism indicate that sampling and reporting biases are more plausible explanations for the observed data than scale- or type-dependence.