Money and inflation in Germany: A cointegration analysis

This paper analyses the relation between money and inflation in Germany in a cost-push/demand-pull model of an open small economy by means of cointegration methods. The full-information-maximum-likelihood method of Johansen as well as structural methods are applied to datasubsets and the full data set. The focus of the paper is on tests for overidentifying restrictions and for weak and strong exogeneity within these data sets. The result of the paper is that the money stock, the price level and gross national product are endogenous whereas the interest rate and the real import price are both weakly and strongly exogenous. By means of the price cointegration relation we illustrate how monetary targeting should react to imported inflation.     

The efficiency of immunization of infants by local government

The paper makes use of data envelopment analysis (DEA) to measure the cost and production efficiency of local government programmemes for childhood immunization in urban and rural settings in Australia. Model specification is tested for validity, methods are used for ranking efficient units and advanced statistical methods are used to establish confidence intervals around the efficiency estimates. Given the small data set, the cost and production models are valid, and it is concluded that while neither urban nor rural programmes are particularly efficient, there is more room for improvement in rural programmes. Ways of changing methods of delivery are suggested which may increase efficiency.     

Institutional capacity to dynamically innovate: An application to the Portuguese case

The present paper addresses the dynamics of innovation, by extending the analysis beyond a static-economic perspective. It offers a dynamic-institutional mapping of relational capacities to dynamically innovate. Its main goal is to contribute to the above-mentioned research theme by presenting a new methodology able to pinpoint different trends in the relational capacities of institutions when they are innovative. Thereby, major characteristics in the networks of innovation are identified. This investigation uses an extended set of private institutions and public organizations located in Portugal, evaluated by their WebPage contents. To this data set a new combination of multivariate statistical methods is applied to detect group performances, to compare them, and to identify gradients of capacity to dynamically innovate. The results demonstrate that this method can provide extremely useful and tailor-made information for policy evaluation at regional or national levels.     

一种基于偏差熵的组合评价方法及其应用

传统组合评价方法的一般思路是使组合评价结果与基于各单一评价方法所得结果之间的偏差尽可能小,但该思路对相容方法集本身的质量却考虑较少。针对上述组合评价思路的不足,提出了偏差熵的概念,并在此基础上提出了基于偏差熵的组合评价方法。该方法对传统组合评价方法所做的改进在于,在考虑减小偏差的同时亦考虑了相容方法集本身的相容质量问题。最后,通过算例验证了用该方法得出的评价结果更加全面、合理,且该方法易于实现。     

Voting by Successive Elimination and Strategic Candidacy

We study the impact of strategic choices of self-interested candidates of whether or not to enter an election. We focus on strategic candidacy in the context of the tree and binary voting procedures used by small groups such as committees. We offer a comprehensive analysis for the special but important case of voting by successive elimination. Strategic candidacy slightly enlarges the set of candidates that can be equilibrium outcomes relative to the traditional analysis which takes the set of candidates as fixed. Pareto-dominated candidates can be elected in equilibrium under voting by successive elimination when strategic candidacy is considered, in contrast with a fixed set of candidates. Journal of Economic Litterature Classification Numbers: D71, D72.     

Efficient price and capacity choices under uncertain demand: An empirical analysis

Traditional economic analyses of the peak-load problem typically assume an unrealistic degree of regularity in demand during well-defined peak and off-peak periods. This issue is addressed through a comprehensive statistical model that separates demand into its systematic and stochastic components. This model is combined with a traditional economic model and applied to local telephone service, leading to substantive conclusions relevant for managerial decisions as well as further research, among them:

? Neglecting the systematicand stochastic structure of demand may lead to inefficient tariffs. Efficient measured service structures typically price individual callsbelow incremental capacity cost.

? Industry wide capacity decision rules that are exclusively driven by blockage probability targets during narrowly defined time periods may be economically inefficient.

? For telephone service, spot pricing, which sets high prices during periods ofactual congestion, has the potential to be considerably more efficient than traditional tariffs that set high prices during periods ofexpected congestion.

     

Feles: The functionalized extended linear expenditure system: Theory,estimation procedures and application to individual household consumption expenditures involving socioeconomic and sociodemographic characteristics

This article introduces the Functionalized Extended Linear Expenditure System, FELES, a new extension on Lluch's familiar Extended Linear Expenditure System. Household individual expenditures with respect to ‘subsistence expenditures’ and ‘partial marginal propensities to consume’ are made explicitly dependent on socioeconomic and sociodemographic characteristics in a system-wide approach. A restricted maximum likelihood estimator for relatively small systems with few explanatory variables and an iterative estimation procedure for larger systems with an extensive set of explanatory variables are proposed. The complete FELES then is applied to cross-sectional data with more than 47,000 German households. Stone's LES and Lluch's ELES are first quantified too on a German data base of this extent.     

Understanding the cell phone effect on vehicle fatalities: a Bayesian view

This article examines the potential effect of various factors on motor vehicle fatality rates using a rich set of panel data and classical regression analysis combined with Bayesian Extreme Bounds Analysis (EBA), Bayesian Model Averaging (BMA) and Stochastic Search Variable Selection (SSVS) procedures. The variables examined in the models include traditional motor vehicle and socioeconomic factors. In addition, the models address the effects of cell phone usage on such accidents. The use of both classical and Bayesian techniques diminish the model and parameter uncertainties which afflict more conventional modelling methods which rely on only one of the two methods.     

Bridging the gap between foresight and market research: Integrating methods to assess the economic potential of nanotechnology

This paper discusses how to bridge the gap between foresight research oriented to the long-term, and traditional market research oriented to the medium to short term, when applied to an early stage of a technology's life cycle. It proposes using an integrating approach, i.e. a combination of methods and both foresight and traditional market research. A mix of complementary methods for the acquisition and analysis of data is presented in a case study. This helps to overcome the deficits of some qualitative foresight methods and quantitative methods often used in traditional market research and allows us to examine research results from the different methods applied both on their own and as a group. In the absence of a single fully-fledged and accepted economic approach, this paper argues that combined market research and foresight modules are the best possible approach for analyzing the economic potential of emerging technologies like nanotechnology. In the future, similar applications of such market foresight modules may be useful, for example, as elements of foresight. They will also be useful in studies of emerging technologies (e.g. converging technologies, cognitive science and Web 2.0) where traditional market research does not produce a realistic market assessment.     

The combined estimator approach to model transferability and updating

The idea of transferability is to employ in model estimation, fitted model parameters computed from a different data set. Thecombined estimator approach to the transferability problem is expressed as a linear combination of the unbiased direct estimators on the two data sets. The major gain is in variance reduction. The combined estimator is shown to have superior accuracy, in a Mean Square Error sense, to a unbiased direct estimator whenever the transfer bias is relatively small. A test that indicates if the combined estimator is superior to the direct estimator is provided. Variances of the direct estimators are assumed to be known. Monte Carlo experiments are performed to assess the quality of the approximations. The results show that the approximations used are highly conservative. An empirical example of the combined estimator applied to a discrete choice problem is presented.     

Parity reversion persistence in real exchange rates: middle income country case

This article investigates purchasing power parity (PPP) in the specific context of middle income countries. To circumvent the low power of traditional stationarity tests (Augmented Dickey-Fuller and Phillips-Perron tests), it performs variance ratio and fractional integration tests in addition to Perron's test that accounts for potential structural changes in real exchange rate processes. Beyond estimating half-life shocks to PPP, this article attempts to explain these estimates using a set of country specific variables as suggested by economic theory. The evidence suggests that reversion to parity tends to be faster in high inflation countries and that productivity improvement leads to a higher level of persistence. Openness to trade tends to reduce the extent of deviations from parity but this result does not appear to be statistically robust. Evidence shows also that deviations are less persistent under a fixed exchange rate regime and under unrestricted capital mobility.     

A comparison of commodity price forecasting by Box-Jenkins and regression-based techniques

This article describes a study of forecasting methods performed for the corporate purchasing function, which required monthly forecasts of high-volume rubber-commodity prices as an aid to formulating its future purchasing strategy. Four mathematical forecasting procedures are applied to the same set of rubber-commodity price-index data. The forecasting techniques used are the Box-Jenkins time-series method, multiple linear regression analysis, and two new regression-based techniques, referred to as minimum relative error regressionanalysis and dynamic regression analysis.The rationale behind each method is briefly described. The forecast results generated by each algorithm are presented in graphic and numerical form. The accuracy of each method is evaluated by comparing forecasted versus actual values of the rubber-commodity price index. For this data, the new minimum relative error regression technique compares quite favorably with the powerful Box-Jenkins method, followed by standard multiple regression. The dynamic regression method is the least accurate of the four in this application.     

数字赋能企业商业生态系统跃迁升级的机理及路径研究

数字技术应用融合叠加商业模式创新催生商业生态新业态,实现跃迁升级。本文结合扎根理论与模糊集定性比较分析(FsQCA)方法,阐释数字赋能企业商业生态系统跃迁升级的机理,探究多重组态路径。从生态视角揭示了数字资源通过与传统要素资源融合释放数据价值,并驱动形成价值循环体系、实现价值共创、塑造商业群落,最终实现企业商业生态系统跃迁升级。基于FsQCA的多组态分析发现,数字赋能企业商业生态系统跃迁升级历经两个阶段分别为价值共创和商业群落生成。其中,价值共创实现有两条组态路径,即产品创新与要素融合相组合,技术融合同低产品创新、低数据资产相组合,且产品创新构成了价值共创的核心条件。商业群落生成的组态路径表现出以下特征：价值共创和价值链接协同下分别和网络组织、数据赋能相组合,网络组织和数据赋能互为替代,即在一方缺失时,分别与价值共创或价值链接组合实现商业群落构建。本研究为企业商业生态系统的结构与功能持续优化,实现数字商业生态资源的充分共享及最优利用,提供了关键方法和思路。     

Farming system modelling for agri-environmental policy design: The case of a spatially non-aggregated allocation of conservation measures

This paper addresses the issue of designing policies for habitat conservation on agricultural land. The case under study requires a non-aggregated spatial distribution of the fields to be enrolled in an agri-environmental programme. A spatially explicit mathematical programming farm-based model, which accounts for three spatial levels (field, farm and landscape), is coupled with a relevant spatial pattern index (the Ripley L-function) to analyse the design and implementation of an agri-environmental programme aimed to preserve the Tetrax tetrax in the Plaine de Niort, France. The model is run using a stylised map with heterogeneous soil types and both crop growing and mixed dairy farms. Results show that valuable insights into agri-environmental programme design are gained through a detailed representation of farming system management. The suitable, non-aggregated spatial pattern for T. tetrax conservation is more costly than less-suitable, more aggregated patterns, because it tends to require equal participation of all farms. The policy simulations reveal that the various spatial patterns can be obtained through relatively simple uniform contract structures. An effective contract structure entails a set of two degressive payments which encourages all farms to enrol at least a small share of their land in the program.     

Sustainable livelihoods in a Coptis-planting based rural community: a case study in Shizhu County, China

Coptis chinensis is a medicinal herb used in traditional Chinese medicine.This research features a case study in Shizhu County,China.Participatory Rural Appraisal（PRA） is used as the main tool for data collection.The study demonstrates that the current method of Coptis planting leads to forest destruction.Even with reforestation measures,it leads to the loss of biodiversity in the forest.It also shows that farmers cannot get satisfactory economic returns from Coptis planting,as the return is unstable and unpredictable.One alternative to the current Coptis planting mode is to incorporate it into the agroforestry system.Water shield planting also serves as a good alternative to Coptis planting itself.Improved methods of management,post-harvest processing,and marketing of Coptis are also proposed and analyzed.The intended contribution of this paper to the theoretical debate of sustainability shall be the provision of an example showing how agricultural production affects forest conservation.It also presents redressable measures to the negative consequences.Besides,one alternative livelihood pathway for the rural community in this case study is suggested.     

R&D activity in a dynamic factor demand model

The focus of this paper is an econometric analysis of the determinants of private firms' R&D activities in the context of a general dynamic factor demand model. Besides the traditional production factors we treat technological knowledge, endogenously determined by R&D expenditures, as a further input factor. While labour and materials are assumed to be variable, capital and know-how are considered as quasi-fixed. The dynamic demand equations for labour, capital investment and R&D which are derived from an intertemporal cost minimisation are estimated for a panel data set of small and medium size German firms. The data covers the period between 1978 and 1982 and includes 408 firms. It turns out that R&D activity depends on the underlying production structure as suggested by neoclassical theory. In addition, by introducing firm specific effects, we can show that firm size and market concentration influence innovative behaviour in accordance with the Schumpeterian hypotheses.Paper presented at the Industrial Organization Conference at the Annual Meeting of the Austrian Economic Association, Vienna, June 24–26, 1992, the 7th Annual Congress of the European Economic Association, Dublin, August 29–31, 1992, and the 19th Annual Conference of the EARIE, Stuttgart, September 4–6, 1992. Helpful suggestions and comments were received from participants of these conferences as well as from seminar participants at Temple University, at the University of Augsburg, and at the fourth DFG workshop Marktstruktur und gesamtwirtschaftliche Entwicklung in Munich. We are particularly indebted to an anonymous referee for very helpful specific comments. Finally, we would like to thank Horst Albach for providing us with the panel data set. Financial support of the DFG is gratefully acknowledged.     

On nonparametric estimation of the Schumpeterian link between innovation and firm size: Evidence from Belgium,France, and Germany

This paper analyses the Schumpeterian link between innovative activity and firm size by means of the nonparametric Nadaraya-Watson estimator and of the partially linear approach by Speckman. Four data sets referring to the manufacturing industries of three European countries are available for the analysis. We demonstrate how nonparametric methods can produce more reliable conclusions than conventional methods. For this purpose, the roles of bandwidth choice, wild bootstrap, density estimation and trimming are studied. For the German data set of 1984 and for the French data set we find that small firms and large firms are more innovative than firms of intermediate size while the relation is rather hump-shaped for Germany 1989 and decreasing for Belgium. Including an additional parametric component into the estimations based on the French data contributes considerably to the explanation of innovative activity without affecting the U-shaped link between innovation and firm size.     

新媒体的发展与广东文化创意产业的探究

新媒体与文化产业的结合，改变了传统文化产业的制作方式和传播平台，展现出文化创意产业的技术、文化、知识等创新要素，赋予了文化产业在数字化时代的新内涵。新媒体在文化产业中的作用是全方位的，创意产业中的动漫，文物交易、工艺品、设计、时装设计电影、互动休闲软件等内容形式、创作手段、传播媒介及产业经营思路发生根本的变化和迅猛的发展。经过改革开放近30年的快速发展，广州已进入全面推进现代化大都市建设的关键时期，在数字传媒时代中，广东如何抓住机遇，大力发展以人才资本为主的创意产业，从而引领产业向高端发展，对推动广州经济社会发展模式的转型和建设创新型城市具有十分重要的战略意义。     

Improving estimation of the fractionally differencing parameter in the SARFIMA model using tapered periodogram

This paper presents a new method to estimate the fractional differencing parameters in the SARFIMA model. A technique of split cosine bell tapering is suggested to improve the EGPH method. The simulation study shows that the optimal split proportion and bandwidth for the EGPH with split cosine bell tapering method respectively are p = 0.1 and b = 0.9. The new method with the optimal parameters outperforms the EGPH and EGPH with cosine bell tapering. We further applied the EGPH method to estimate intraday volume series and high-frequency absolute return data. The results show that the seasonal fractionally differencing parameters are all estimated to be large, while the nonseasonal fractionally differencing parameters are all very small. This indicates that their long memory property may be mainly caused by the structure of long-range dependence at the seasonal lags instead of dependence at the nonseasonal lags.     

Semiparametric and nonparametric testing for long memory: A Monte Carlo study

The finite sample properties of three semiparametric estimators, several versions of the modified rescaled range, MRR, and three versions of the GHURST estimator are investigated. Their power and size for testing for long memory under short-run effects, joint short and long-run effects, heteroscedasticity andt-distributions are given using Monte Carlo methods. The MRR with the Bartlett window is generally robust with the disadvantage of a relatively small power. The trimmed Whittle likelihood has high power in general and is robust except for large short-run effects. The tests are applied to changes in exchange rate series (daily data) of 6 major countries. The hypothesis of no fractional integration is rejected for none of the series.