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41.
We analyze a dynamic and stochastic ecological-economic model of grazing management in semi-arid rangelands. The ecosystem is driven by stochastic precipitation. A risk averse farmer chooses a grazing management strategy under uncertainty such as to maximize expected utility from farming income. Grazing management strategies are rules about which share of the rangeland is given rest depending on the actual rainfall in that year. In a first step we determine a myopic farmer's optimal grazing management strategy and show that a risk averse farmer chooses a strategy such as to obtain insurance from the ecosystem: the optimal strategy reduces income variability, but yields less mean income than possible. In a second step we analyze the long-run ecological and economic impact of different strategies. We conclude that a myopic farmer, if he is sufficiently risk averse, will choose a sustainable grazing management strategy, even if he does not take into account long-term ecological and economic benefits of conservative strategies. 相似文献
42.
Exploring the boundaries of the framing effect: The moderating roles of disparate expected values and perceived costs of judgmental errors 总被引:1,自引:1,他引:0
Framing effects on retail store choice decisions were investigated in four experiments. Subjects preferred the store that guaranteed (a sure option) good prices (experiment 1), product availability (experiment 2), or a rebate (experiment 3) when consequences were framed in terms of gains; subjects preferred the risky option when consequences were framed in terms of losses. Consistent with fuzzy-trace theory, framing effects were reduced when the expected values of options were disparate in a direction that disfavored sure gain or probabilistic loss options (experiment 2) and when the perceived costs of committing a judgmental error were high (experiment 3). Experiment 4 shows that the moderating effects of disparate expected values and costs of judgment errors generalize to within-subject designs. 相似文献
43.
Trade-off Model of Debt Maturity Structure 总被引:3,自引:0,他引:3
In this paper, we suggest the trade-off model to explain the choice of debt maturity. This model is based on balancing between risk and reward of using shorter-term loans. Shorter-term loans have cost advantage over, but incur higher refinancing and interest rate risk than longer-term loans. Using the Compustat data, we show that the principal components of financial attributes are financial flexibility and financial strength. Therefore, only firms with greater financial flexibility and financial strength can use proportionately more short-term loans. We also document that financially strong firms take advantage of lower interest rates of short-term debt. They use proportionately more short-term loans when the term premium is high. The results of our study also provide evidence supporting the agency cost hypothesis, which is strongly supported by current literature. 相似文献
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We examine the determinants of the new issue maturity of corporate bonds. As credit rating decreases, new bond issues have longer maturities, but substantial variation in maturity within each rating class remains. We seek to explain the variation of new issue maturity within credit classes. We find that asset maturity, security covenants, and macroeconomic conditions influence the new issue maturity of bonds within rating categories. 相似文献
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Central bank credit has expanded dramatically in some of the Euro Area member countries since the beginning of the financial crisis. This paper makes two contributions to understand this stylized fact. First, we discuss a simple model of monetary policy that includes (i) a credit channel and (ii) a common pool problem in a monetary union. We illustrate that the interaction of the two elements leads to an inflation bias that is independent of the standard time-inconsistency bias. Secondly, we present an institutional analysis that is consistent with the view of fragmented monetary policy and empirical evidence that illustrates the heterogeneity of central bank credit expansion. 相似文献
50.
Salim Lahmiri Stelios Bekiros Anastasia Giakoumelou Frank Bezzina 《International Journal of Intelligent Systems in Accounting, Finance & Management》2020,27(1):3-9
Financial data classification plays an important role in investment and banking industry with the purpose to control default risk, improve cash and select the best customers. Ensemble learning and classification systems are becoming gradually more applied to classify financial data where outputs from different classification systems are combined. The objective of this research is to assess the relative performance of existing state‐of‐the‐art ensemble learning and classification systems with applications to corporate bankruptcy prediction and credit scoring. The considered ensemble systems include AdaBoost, LogitBoost, RUSBoost, subspace, and bagging ensemble system. The experimental results from three datasets: one is composed of quantitative attributes, one encompasses qualitative data, and another one combines both quantitative and qualitative attributes. By using ten‐fold cross‐validation method, the experimental results show that AdaBoost is effective in terms of low classification error, limited complexity, and short time processing of the data. In addition, the experimental results show that ensemble classification systems outperform existing models that were recently validated on the same databases. Therefore, ensemble classification system can be employed to increase the reliability and consistency of financial data classification task. 相似文献