On the structure and estimation of hierarchical Archimedean copulas

In this paper we provide a method for estimating multivariate distributions defined through hierarchical Archimedean copulas. In general, the true structure of the hierarchy is unknown, but we develop a computationally efficient technique to determine it from the data. For this purpose we introduce a hierarchical estimation procedure for the parameters and provide an asymptotic analysis. We consider both parametric and nonparametric estimation of the marginal distributions. A simulation study and an empirical application show the effectiveness of the grouping procedure in the sense of structure selection.     

Asymptotic behavior of the estimated weights and of the estimated performance measures of the minimum VaR and the minimum CVaR optimal portfolios for dependent data

In this paper we derive the asymptotic distributions of the estimated weights and of estimated performance measures of the minimum value-at-risk portfolio and of the minimum conditional value-at-risk portfolio assuming that the asset returns follow a strictly stationary process. It is proved that the estimated weights as well as the estimated performance measures are asymptotically multivariate normally distributed. We also present an asymptotic test for the weights and a joint test for the characteristics of both portfolios. Moreover, the asymptotic densities of the estimated performance measures are compared with the corresponding exact densities. It is shown that the asymptotic approximation performs well even for the moderate sample size.     

Model-independent bounds for option prices—a mass transport approach

In this paper we investigate model-independent bounds for exotic options written on a risky asset using infinite-dimensional linear programming methods. Based on arguments from the theory of Monge–Kantorovich mass transport, we establish a dual version of the problem that has a natural financial interpretation in terms of semi-static hedging. In particular we prove that there is no duality gap.     

Optimal Harvesting of an Age-Structured Schooling Fishery

Biologists have criticized traditional biomass models in fishery economics for being oversimplified. Biological stock assessment models are more sophisticated with regard to biological content, but rarely account for economic objectives. This study includes a full age-structured population model for studying schooling fisheries and extends the delayed difference approach used in earlier studies. We take the total harvest as the choice variable, resulting in a simple analytical structure. The model produces optimal steady states that may be higher or lower compared to the delayed-difference formulation. The model is applied to the Baltic sprat fishery. Both ecological and harvesting cost data support specifying Baltic sprat as a schooling fishery. Given nonlinear harvesting costs, the optimal solution is a path toward a steady state with smooth annual harvest and population age structure. Sensitivity analysis shows that the optimal solution is highly dependent on the population level of the sprat’s main predator Baltic cod. A linear cost function and an interest rate below 9 % imply pulse fishing instead of smooth continuous harvesting. Given nonlinear harvesting cost, the optimal steady state yield is rather insensitive to changes in the interest rate. However, under a high cod scenario, interest rates of 10 % or higher implies that no optimal steady state exists.     

Corruption and the shadow economy: like oil and vinegar, like water and fire?

From a theoretical point of view, the relationship between corruption and the shadow economy is ambiguous: They can either be substitutes or complements. This paper contributes to this debate by using a structural equation model with two latent variables to extract information on various dimensions of corruption and the shadow economy. Analyzing a sample of 51 countries around the world over the period 2000 to 2005, we present empirical evidence for a complementary (positive) relationship of corruption and the shadow economy.     

Tax avoidance versus tax evasion: on some determinants of the shadow economy

In this paper we investigate how the possibility of (legal) tax avoidance affects the extent of (illegal) tax evasion and hence the shadow economy. We formulate a theoretical microeconomic model of household behavior in which households can participate in the official and in the shadow economy. Using comparative statics, we show that the complexity of the tax system affects participation in the shadow economy negatively, i.e. a more complex tax system with more possibilities of legal tax avoidance implies, ceteris paribus, a smaller labor supply in the shadow economy. In addition, we show that a reduction in the maximum admissible number of working hours in the official economy increases the labor supply in the shadow economy.     

Rentenreform — mit welchem Fokus?

The demographic imbalance is aggravating, and by 2060 the old-age dependency ratio will double to approximately 70%. This development has consequences for the state pension system: growing contribution rates to social security coupled with lower pension levels, but at the same time a higher retirement age. The German pension scheme is mandatory for all wage and salary earners, but since 2001, no reasonable indicator for measuring the pension level exists any more. As a consequence of this, old-age pension has lost its traditional function as a replacement for earnings. The recent pension reforms have dropped the pension level sharply. Further reductions have been announced with the consequence of increasing old age poverty. Against this background it is proposed to raise the pension level so that the pensioners can maintain their standard of living. But any pension reform involves issues of distribution between and often also within generations, which cannot be addressed without explicit equity criteria. Some authors consider the past reforms as a mistake, others suggest adjustments.     

Confident expectations, rational expectations and the optimal conduct of monetary policy

Under what conditions central banks can afford to deviate from announced targets without losing their reputation is analyzed. For this, the public must have something like ‘confident expectations' vis-a-vis monetary policy and central banks have to behave accordingly. The paper shows that it can be rational for the public and welfare-increasing for the society to retain ‘confident expectations' instead of switching to rational expectations, when central banks have gained long-run reputation. At the end of the paper, alternative optimal money supply rules are compared in a dynamic optimization framework. © 1998 Elsevier Science B.V. All rights reserved.     

Tracing the Pathways from Research to Innovation: Evidence from Case Studies

The complex process through which agricultural research stimulates innovation and achieves policy goals has commonly been treated as a ‘black box’ in the scientific literature. Statistical correlations between measured expenditure and impacts, where satisfactorily established, have mostly led to details of the research and innovation system being ignored. However, identifying and exploring causal chains of impact propagation can strengthen agricultural innovation. IMPRESA investigated impact mechanisms for research‐based innovations in six case studies using a Participatory Impact Pathway Assessment approach. Several suggestions result for improving performance and public support for agricultural research. Planning for impact is needed at the design phase of research so that expected advances in technology and their consequences can be explored. At that stage and throughout the research process, soft social skills are required to promote uptake. Greater impact can be achieved through the close involvement of key public and private sector stakeholders, using stakeholder mapping as a supporting tool. There is a strong argument for the close involvement of relevant social scientists and professional facilitators from the design phase of research through to its ultimate impacts. Funding frameworks and the specification of calls for tenders would function more effectively by giving more flexibility for stakeholder engagement.     

Robust Small Area Estimation under Spatial Non‐stationarity

The effective use of spatial information in a regression‐based approach to small area estimation is an important practical issue. One approach to account for geographic information is by extending the linear mixed model to allow for spatially correlated random area effects. An alternative is to include the spatial information by a non‐parametric mixed models. Another option is geographic weighted regression where the model coefficients vary spatially across the geography of interest. Although these approaches are useful for estimating small area means efficiently under strict parametric assumptions, they can be sensitive to outliers. In this paper, we propose robust extensions of the geographically weighted empirical best linear unbiased predictor. In particular, we introduce robust projective and predictive estimators under spatial non‐stationarity. Mean squared error estimation is performed by two analytic approaches that account for the spatial structure in the data. Model‐based simulations show that the methodology proposed often leads to more efficient estimators. Furthermore, the analytic mean squared error estimators introduced have appealing properties in terms of stability and bias. Finally, we demonstrate in the application that the new methodology is a good choice for producing estimates for average rent prices of apartments in urban planning areas in Berlin.