Decomposition of new venture growth into firm age,survey period and vintage effects

Firm data are accumulated on a yearly basis. In view of the linear relationship of firm age?+?foundation year?=?survey year, the fluctuations of firm data classified by age and period cannot be decomposed into age, period and cohort (foundation year) effects. Three decomposition methods are briefly reviewed and applied to Japanese data on new ventures founded since 1995. Regarding sales and employment growth, the age effect is the largest with a downward trend, and the cohort effect is negligible. Regarding labour productivity, the age effect indicates upward movements, and the cohort effect is negligible. The reason of the negligible cohort effect is discussed.     

Time-varying parameters in the almost ideal demand system and the Rotterdam model: will the best specification please stand up?

This article assesses the ability of the Rotterdam Model (RM) and of three versions of the Almost Ideal Demand System (AIDS) to recover the time-varying elasticities of a true demand system and to satisfy theoretical regularity. Using Monte Carlo simulations, we find that the RM performs better than the linear-approximate AIDS at recovering the signs of all the time-varying elasticities. More importantly, the RM has the ability to track the paths of time-varying income elasticities, even when the true values are very high. The linear-approximate AIDS, not only performs poorly at recovering the time-varying elasticities but also badly approximates the nonlinear AIDS.     

Evaluating the economy embedded in the Brazilian ethanol–gasoline flex-fuel car: a Real Options approach

The introduction of the flex-fuel cars in the Brazilian market in 2003 changed considerably the consumer decision-making process. Prior to this date, it was necessary to choose the automobile type only by gasoline or by ethanol fuel; today it is possible to choose a car type with both fuel options. This flexibility generates economic advantages for his owner, but what are the financial benefits of a flex-fuel car in comparison with a car using only gasoline? Geographically, where is the owner of the benefits from this flexibility located? This article presents an empirical application of the Real Options Theory in the analysis of the flex-fuel car option for five geographic Brazilian regions: Northern, Northeastern, Central-Western, Southeastern and Southern. The regional price differences as well as the consumer preferences of these regions were met. For this purpose, historical fuel prices were considered stochastic and following a Mean Reverting Stochastic process. The prediction and option values were generated by a Monte Carlo simulation. The results indicated that the option embedded on the Brazilian flex-fuel car adds considerable value to the owner in all regions and car models considered, with the Southeastern Region receiving most benefits by the flex option.     

股票资产组合VaR研究基于混合D藤Copula模型

本文在对上证市场五种股票资产组合的风险分析中以VaR作为风险度量指标,采用基于Pair Copula高维建模理论的混合D藤Copula模型,建立了反应多个资产组合相关结构的联合分布模型。该模型对传统D藤Copula建模方法作了进一步的改进,通过一定的选择标准,确定了D藤中每个Pair Copula函数的最优函数族,这样使得所建立的模型不仅考虑到了资产维数的影响,而且还能捕捉到组合内部因子间相关结构的差异性,从而改进后的模型能更好地描述资产组合的相关结构,并且能更精确地反映资产组合收益的实际分布。最后,以混合D藤Copula模型为基础,利用Monte Carlo方法计算了上证市场五种股票资产组合的VaR,并通过实证研究进一步证明了该模型的有效性。     

Understanding platform competition through simulation: a research outline

ABSTRACT

Platform competition shapes and is shaped by a constantly changing socioeconomic context. Three trends provide evidence for this: (i) the number of firm level relevant factors for platform success is steadily increasing, (ii) contemporary cases of platform competition take less time to unfold, and (iii) industries converge. These trends suggest that there is a change: in the time required for relevant factors to influence platform competition, and in the trade-offs managers face when they take actions in platform development and competition, to influence the market outcome of such processes. Current frameworks in the literature do not account explicitly for such timing issues. The use of modelling and simulation, along empirical cases, is a way to incorporate timing and strategic action delays in platform competition research. We explore the multi-level research agenda this opens up and develop nine research questions for platform competition research.     

Testing for negativity in a demand system: A Bayesian approach

The paper introduces Bayesian inference into a demand model. This allows us to test for the negativity condition of the substitution matrix which is difficult to handle directly in the traditional approach. To illustrate the Bayesian inference procedures, we estimate the Rotterdam model and test the demand properties using Japanese data. The empirical results show the importance of specifically considering negativity in demand analysis. First version received: September 1997/final version received: February 1998     

Bayesian inference in cointegrated systems

In this paper I deal with Bayesian methods for conducting inference on important features of (potentially) cointegrated VAR models involving I(1) variables. Firstly, (informal) inference is made on the cointegrating rank of the system. Secondly, posterior analysis is used to verify the validity of over-identifying restrictions on the cointegration parameters. Thirdly, posterior distributions are obtained for impulse response functions and predictive densities at different horizons. The relevant posterior distributions are obtained by means of Monte Carlo integration. The analysis is based on the use of simple weakly informative priors. Two applications on simulated data and on the Danish money demand data are presented.     

基于蒙特卡罗模拟的商业银行信用风险度量方法

通过与Matlab程序相结合的方式介绍了基于蒙特卡罗模拟的商业银行信用风险度量方法。该方法使在给定的置信水平下科学地估算国内商业银行的信用风险成为可能。     

Assessing the impact of cost optimization based on infrastructure modelling on CO2 emissions

Traditionally, logistics design is driven by a need to reduce costs and improve customer service. Recently, the environmental concerns from transport have been increasingly discussed. The traffic levels and associated energy consumption are influenced by supply chain structure, modal split and vehicle utilization. This paper aims to assess the impact of the traditional cost optimization approach to strategic modelling on overall logistics costs and CO₂ emissions by taking into account the supply chain structure (number of depots) and different freight vehicle utilization ratios (90%, 75% and 60%). The simulation model, based on a European case study from the automotive industry, considers strategic and operational level decisions simultaneously. The analysis shows that the optimum design based on costs does not necessary equate to an optimum solution for CO₂ emissions, therefore there is a need to address economical and environmental objectives explicitly as part of the logistics design.     

Workload control under continuous order release

Workload control is a production planning and control concept specifically designed for complex manufacturing environments. Past research on Workload control has been essentially focused on discrete order release. This means that release of orders to the shop floor takes places on a periodic basis. Continuous order release has been somehow neglected, in spite of its apparent potential for improving system performance, including the reduction of order flow times. This paper presents a simulation study of this order release approach. The study contributes for improving the basis for setting workload norms, selecting the workload control strategy and deciding upon routing alternatives under continuous order release.