Conditional distributions of generalized order statistics and some characterizations

Generalized order statistics have been introduced in Kamps (1995a). They enable a unified approach to several models of ordered random variables, e.g. (ordinary) order statistics, record values, sequential order statistics, record values from non-identical distributions. The purpose of this paper is to develop conditional distributions of one generalized order statistic given another and to characterize the underlying continuous distribution by different conditional expectations. Well-known results for ordinary order statistics and record values are extended to generalized order statistics. Received: July 1997     

Social-ecological factors influencing tourist satisfaction in three ecotourism lodges in the southeastern Peruvian Amazon

Analysing the factors that influence visitor satisfaction is critical for the appropriate management of tourism, particularly in nature tourism enterprises, which are expected to contribute to biodiversity conservation and the development of local people. In this paper, we investigate the effect of different socio-economic and ecological variables, as well as tourist-operation related factors, on the overall satisfaction of tourists visiting three Amazonian lodges in Peru. We found three typologies of tourists, differing by several socio-economic and cultural factors, and by their motivations. The quality of the lodge was the factor that had the largest influence on overall satisfaction. Only one type of tourists (“true ecotourists”) showed a positive relation between their overall satisfaction and ecological features such as the species observed or cultural features such as operation of the lodge by native communities using local guides. Implications for management are discussed in terms of the potential of nature tourism to contribute to sustainable development in the Peruvian Amazon.     

Comparison of farmers’ mental models of the present and the future: A case study of pesticide use

Farmers in developing countries will in the future be confronted with major changes. The ability to cope with these challenges rests on their capability to relate future problems to current behavior. Our approach investigates this capability and consists in comparing mental models of the present and future. The approach moreover enables us to explore whether and how farmers are able to imagine a future differing from the perceived present.Data from previous studies investigating present and future pesticide application were used. In the datasets the mental models of farmers’ livelihood were structured into livelihood capitals (human, health, natural and financial capital), causal relations among the livelihood capitals were derived, and present and future causal relations were compared.The comparison of these causal relations led to six cases, each representing a different degree of dependence of future on present causal relations. The dependence was found to vary among farmers and analyzed livelihood capital. Three types of farmers with differing dependence patterns were identified.The differences found lead to new insights for policy recommendations, depending on farmers focus in their causal relations. We therefore expect that interventions focusing either more on the causes or effects of causal relations will result in a better uptake of knowledge by farmers.     

Interest rate pass-through,monetary policy rules and macroeconomic stability

In this paper we analyze equilibrium determinacy in a sticky price model in which the pass-through from policy rates to retail interest rates is sluggish and potentially incomplete. In addition, we empirically characterize and compare the interest rate pass-through process in the euro area and the U.S. We find that if the pass-through is incomplete in the long run, the standard Taylor principle is insufficient to guarantee equilibrium determinacy. Our empirical analysis indicates that this result might be particularly relevant for bank-based financial systems as for instance that in the euro area.     

Factors affecting farmers’ acceptance of conservation measures—A case study from north-eastern Germany

Intensive forms of agriculture have been proven to cause severe environmental effects, such as soil erosion by water and wind, or the pollution of ground and surface water with nutrients and pesticides contributing to the deterioration of natural habitats and the loss in biodiversity. In order to avoid or mitigate these detrimental environmental effects, a number of conservation measures can be undertaken by farmers. However, the adoption of these measures is highly dependent on the assumed benefits and risks attached as well as the personal perception and attitude of the individual farmer.This paper presents the outcome of a survey conducted in north-eastern Germany aimed at analysing farmers’ acceptance of different conservation measures. Eleven farmers, managing more than 80% (about 13,000 ha) of the agricultural land in the chosen case study region were interviewed. Respondents were asked about their personal experiences with different environmental measures and requested to assess these measures, e.g., regarding costs, time and labour demands, attached risks, or effectiveness. They also ranked these factors in terms of importance for decision making on adoption or rejection of a new measure. The findings show that, despite of the general assumption that farmers’ decisions are mostly driven by economic rationality, costs were not the most important factor. Other factors, like associated risks, effectiveness, or time and effort necessary to implement a certain measure were equally or even more important depending on the specific situation.     

Using low frequency information for predicting high frequency variables

We analyze ways of incorporating low frequency information into models for the prediction of high frequency variables. In doing so, we consider the two existing versions of the mixed frequency VAR, with a focus on the forecasts for the high frequency variables. Furthermore, we introduce new models, namely the reverse unrestricted MIDAS (RU-MIDAS) and reverse MIDAS (R-MIDAS), which can be used for producing forecasts of high frequency variables that also incorporate low frequency information. We then conduct several empirical applications for assessing the relevance of quarterly survey data for forecasting a set of monthly macroeconomic indicators. Overall, it turns out that low frequency information is important, particularly when it has just been released.     

Financial instruments with sports betting components: Marketing gimmick or a domain for behavioral finance?

We examine theoretically and experimentally a certain class of new financial instruments which are designed as lotteries on the outcome of prominent sports events like the Soccer World Cup 2006. From a theoretical point of view, sports betting products may be superior to a fixed rate investment because of heterogeneous expectations, risk-loving behavior of investors or additional non-monetary utility components. In comparison to the direct placement of bets at bookmakers’, sports betting products may be preferable in cases of hedonic framing. Our experimental section, however, reveals the limited practical relevance of these theoretical arguments for “average” decision makers. Despite this, financial instruments with sports betting components offer a certain profit potential due to the diversity of preferences across individuals. Summarizing, the issuance of sports betting products may actually be mainly driven by marketing aspects, nevertheless sports betting products may be considered to be “viable” niche products with low cost of capital for banks.     

MIXED‐FREQUENCY STRUCTURAL MODELS: IDENTIFICATION,ESTIMATION, AND POLICY ANALYSIS

The mismatch between the timescale of DSGE (dynamic stochastic general equilibrium) models and the data used in their estimation translates into identification problems, estimation bias, and distortions in policy analysis. We propose an estimation strategy based on mixed‐frequency data to alleviate these shortcomings. The virtues of our approach are explored for two monetary policy models. Copyright © 2014 John Wiley & Sons, Ltd.