12 research outputs found
Optimal Taxation in a Simple Model of Human Capital Accumulation
This paper studies optimal taxation in dynamic economies with a simple form of human capital accumulation as considered in Bull (1993). We show that in a Ramsey equilibrium along any balanced growth path, the taxes on wage income and (physical) capital income must be zero. Under the assumption on preferences of Bull (1993), we extend his result by showing that along a balanced growth all optimal taxes are necessarily zero.
Sensitivity Analysis in Economic Simulations: A Systematic Approach
Sensitivity analysis studies how the variation in the numerical output of a model can be quantitatively apportioned to different sources of variation in basic input parameters. Thus, it serves to examine the robustness of numerical results with respect to input parameters, which is a prerequisite for deriving economic conclusions from them. In practice, modellers apply different methods, often chosen ad hoc, to do sensitivity analysis. This paper pursues a systematic approach. It formalizes deterministic and stochastic methods used for sensitivity analysis. Moreover, it presents the numerical algorithms to apply the methods, in particular, an improved version of a Gauss-Quadrature algorithm, applicable to one as well as multidimensional sensitivity analysis. The advantages and disadvantages of different methods and algorithms are discussed as well as their applicability. --Sensitivity Analysis,Computational Methods
Impact of Service Station Networks on Purchase Decisions of Alternative-fuel Vehicles
In this paper we analyze the impact of service station availability on the demand for alternative-fuel vehicles and the consumers' willingness to pay for an enlarged fueling infrastructure. We examine a stated preferences choice experiment conducted as a CAPI survey with about 600 interviews of potential car buyers in Germany and estimate the coefficients of a discrete choice model. We simulate different scenarios and analyze how individual choice probabilities for alternative fuel-types are changing with a modified fueling infrastructure. In our scenarios hybrids, LPG/CNG and hydrogen will be real alternatives to the existing conventional technologies. However, biofuels and electric power trains are well behind even in a situation where their infrastructure is equally developed. Moreover, on the basis of our model we compute what increases in fixed or variable costs consumers of different income groups are willing to accept for an increasing station density. --Fueling Infrastructure,Alternative Fuels,Automobile Market,Stated Preferences,Discrete Choice,Network Effects
Sensitivity analysis in economic simulations : a systematic approach
Sensitivity analysis studies how the variation in the numerical output of a model can be quantitatively apportioned to different sources of variation in basic input parameters. Thus, it serves to examine the robustness of numerical results with respect to input parameters, which is a prerequisite for deriving economic conclusions from them. In practice, modellers apply different methods, often chosen ad hoc, to do sensitivity analysis. This paper pursues a systematic approach. It formalizes deterministic and stochastic methods used for sensitivity analysis. Moreover, it presents the numerical algorithms to apply the methods, in particular, an improved version of a Gauss-Quadrature algorithm, applicable to one as well as multidimensional sensitivity analysis. The advantages and disadvantages of different methods and algorithms are discussed as well as their applicability
Impact of service station networks on purchase decisions of alternative-fuel vehicles
In this paper we analyze the impact of service station availability on the demand for alternative-fuel vehicles and the consumers’ willingness to pay for an enlarged fueling infrastructure. We examine a stated preferences choice experiment conducted as a CAPI survey with about 600 interviews of potential car buyers in Germany and estimate the coefficients of a discrete choice model. We simulate different scenarios and analyze how individual choice probabilities for alternative fuel-types are changing with a modified fueling infrastructure. In our scenarios hybrids, LPG/CNG and hydrogen will be real alternatives to the existing conventional technologies. However, biofuels and electric power trains are well behind even in a situation where their infrastructure is equally developed. Moreover, on the basis of our model we compute what increases in fixed or variable costs consumers of different income groups are willing to accept for an increasing station density
Impact of service station networks on purchase decisions of alternative-fuel vehicles
In this paper we analyze the impact of service station availability on the demand for alternative-fuel vehicles and the consumers’ willingness to pay for an enlarged fueling infrastructure. We examine a stated preferences choice experiment conducted as a CAPI survey with about 600 interviews of potential car buyers in Germany and estimate the coefficients of a discrete choice model. We simulate different scenarios and analyze how individual choice probabilities for alternative fuel-types are changing with a modified fueling infrastructure. In our scenarios hybrids, LPG/CNG and hydrogen will be real alternatives to the existing conventional technologies. However, biofuels and electric power trains are well behind even in a situation where their infrastructure is equally developed. Moreover, on the basis of our model we compute what increases in fixed or variable costs consumers of different income groups are willing to accept for an increasing station density
Sailing into a dilemma : an economic and legal analysis of an EU trading scheme for maritime emissions
On the basis of a joint economic and legal analysis, we evaluate the effects of a “regional” (European)
emission trading scheme aiming at reducing emissions of international shipping. The focus lies on the
question which share of emissions from maritime transport activities to and from the EU can and
should be included in such a system. Our findings suggest that the attempt to implement an EU
maritime ETS runs into a dilemma. It is not possible to design a system that achieves emission
reductions in a cost efficient manner and is compatible with international law
A thermodynamic analysis of the binding interaction between polysorbate 20 and 80 with human serum albumins and immunoglobulins: A contribution to understand colloidal protein stabilisation
Sensitivity Analysis in Economic Simulations - A Systematic Approach Sensitivity Analysis in Economic Simulations - A Systematic Approach Sensitivity analysis in economic simulations - a systematic approach
Die Dis cus si on Pape rs die nen einer mög lichst schnel len Ver brei tung von neue ren For schungs arbei ten des ZEW. Die Bei trä ge lie gen in allei ni ger Ver ant wor tung der Auto ren und stel len nicht not wen di ger wei se die Mei nung des ZEW dar. Dis cus si on Papers are inten ded to make results of ZEW research prompt ly avai la ble to other eco no mists in order to encou ra ge dis cus si on and sug gesti ons for revi si ons. The aut hors are sole ly respon si ble for the con tents which do not neces sa ri ly repre sent the opi ni on of the ZEW. Download this ZEW Discussion Paper from our ftp server: ftp://ftp.zew.de/pub/zew-docs/dp/dp08068.pdf Executive Summary This paper gives a systematic introduction to sensitivity analysis in economic simulations. Sensitivity analysis studies how the variation in the numerical output of a model can be quantitatively apportioned to different sources of variation in basic input parameters. It thus provides a check of robustness of the numerical results of a model. We present a formalisation of the deterministic and the stochastic approach to sensitivity analysis. The former assumes that the basic economic parameter stems from a known interval (in higher dimensions: a compact set) and quantifies the spread of the corresponding equilibrium output variables. The latter treats the parameter as a stochastic variable with known distribution and calculates mean and variance of output variables accordingly. Deterministic sensitivity analysis can be numerically implemented by peacemeal formulae. Stochastic sensitivity analysis is implemented by a Monte-Carlo or a Gauss-Quadrature algorithm. We develop an improved version of Gauss-Quadrature based on orthogonal polynomials. In an application of both algorithms to a CGE model we demonstrate its advantages: It significantly reduces the computational burden of sensitivity analysis and tends to be more stable numerically. Abstract Sensitivity analysis studies how the variation in the numerical output of a model can be quantitatively apportioned to different sources of variation in basic input parameters. Thus, it serves to examine the robustness of numerical results with respect to input parameters, which is a prerequisite for deriving economic conclusions from them. In practice, modellers apply different methods, often chosen ad hoc, to do sensitivity analysis. This paper pursues a systematic approach. It formalizes deterministic and stochastic methods used for sensitivity analysis. Moreover, it presents the numerical algorithms to apply the methods, in particular, an improved version of a Gauss-Quadrature algorithm, applicable to one as well as multidimensional sensitivity analysis. The advantages and disadvantages of different methods and algorithms are discussed as well as their applicability. Das Wichtigste in Kürz