The missing link: Bringing institutions and politics into energy future studies

Energy future studies can be a useful tool for learning about how to induce and manage technical, economic and policy change related to energy supply and use. The private sector has successfully deployed them for strategic planning, examining key parameters such as markets, competition and consumer trends. However in public policy, most energy future studies remain disconnected from policy making. One reason is that they often ignore the key political and institutional factors that underpin much of the anticipated, wished-for or otherwise explored energy systems developments. Still, we know that institutions and politics are critical enablers or constraints to technical and policy change. This paper examines how analytical insights into political and institutional dynamics can enhance energy future studies. It develops an approach that combines systems-technical change scenarios with political and institutional analysis. Using the example of a backcasting study dealing with the long term low-carbon transformation of a national energy system, it applies two levels of institutional and political analysis; at the level of international regimes and at the level of sectoral policy, and examines how future systems changes and policy paths are conditioned by institutional change processes. It finds that the systematic application of these variables significantly enhances and renders more useful backcasting studies of energy futures.     

中国纸制品消费趋势:城市化增长的效应分析和预测

基于对近期未来的人口—经济增长的预测,分析了城市化增长对未来纸制品消费的影响。用"自相关误差回归"的方法检验人口和城市化增长的不同发展路径对于纸制品消费的影响。中国的城市化过程对纸制品消费影响很大,更快的城市化进程,相应的影响会更强烈。比较人口变量和经济变量,城市家庭经济因素相对更加明显。在近期的未来,随着纸制品消费的增加,其对环境污染的压力也会增大。     

Country effect on firm performance: A multilevel approach

The debate about the impact of environmental constraints on firm performance in developing countries is relevant for business enterprises and governments. However, the academic literature offers limited empirical evidence comparing firm performance in emerging and developed countries. This paper performs a statistical analysis based on a sample of more than 10,000 firms in a 10-year span. A cross-classified 3-level hierarchical linear model allows the estimation of country, industry and country-industry interaction effects, which have roughly the same relative importance each. The analytical procedure is able to estimate the influence of each specific country on firm performance and produce a ranking of nations based on this effect. Country effects have a greater positive influence on firm performance in emerging countries than in more developed economies.     

Organizational culture and post-acquisition changes in management control systems: An analysis of a successful Brazilian case

This paper analyzes the effect of organizational culture on the post-acquisition management control system (MCS) of the Brazilian company Extrativa Metalquímica Inc. after its acquisition by the FASA Participações Group. The results herein reported add to discussions of the subject and contribute to reducing the research gap in this area in Brazil. The analysis supports two major conclusions: (1) changes in the acquired company's MCS were derived from the new financial results-oriented culture introduced by the acquirer; and (2) the implementation of this culture implied modifications in production, financial and quality controls.     

Urban bicycle tourism: path dependencies and innovation in Greater Copenhagen

Abstract

During the latest decade, a renaissance of bicycling in urban transportation has occurred in many Western European cities. This opens up for a development of bicycle tourism as a form of urban sustainable tourism, taking advantage of improved infrastructure and facilities for cycling tourists. The aim of this study is to conceptualise the dynamics behind the development of urban bicycle tourism. This development may be viewed as an innovative process based on incremental changes in local socio-technological mobility systems. An analytical framework is proposed, based on the following categories: urban planning, bicycle tourism services, communication, and place making. In the analysis, evidence from the Greater Copenhagen region is used to contextualise particularly these perspectives of the development of urban bicycle tourism. In each of the four categories, evidence of innovative services or procedures supporting bicycle tourism was found. However, the most important source of incremental innovation is likely to be found on a systemic level, between the actors in the destination. It is also argued that the development of urban bicycle tourism is highly path dependent, related to the local bicycle culture. Bicycle tourism should not be viewed as isolated from the locals’ everyday cycling.     

An approximate distribution of delta-hedging errors in a jump-diffusion model with discrete trading and transaction costs

We introduce a jump-diffusion model for asset returns with jumps drawn from a mixture of normal distributions and show that this model adequately fits the historical data of the S&P500 index. We consider a delta-hedging strategy (DHS) for vanilla options under the diffusion model (DM) and the proposed jump-diffusion model (JDM), assuming discrete trading intervals and transaction costs, and derive an approximation for the probability density function (PDF) of the profit-and-loss (P&L) of the DHS under both models. We find that, under the log-normal model of Black–Scholes–Merton, the actual PDF of the P&L can be well approximated by the chi-squared distribution with specific parameters. We derive an approximation for the P&L volatility in the DM and JDM. We show that, under both DM and JDM, the expected loss due to transaction costs is inversely proportional to the square root of the hedging frequency. We apply mean–variance analysis to find the optimal hedging frequency given the hedger's risk tolerance. Since under the JDM it is impossible to reduce the P&L volatility by increasing the hedging frequency, we consider an alternative hedging strategy, following which the P&L volatility can be reduced by increasing the hedging frequency.     

Power mapping with dynamical adjustment for improved portfolio optimization

For financial risk management it is of vital interest to have good estimates for the correlations between the stocks. It has been found that the correlations obtained from historical data are covered by a considerable amount of noise, which leads to a substantial error in the estimation of the portfolio risk. A method to suppress this noise is power mapping. It raises the absolute value of each matrix element to a power q while preserving the sign. In this paper we use the Markowitz portfolio optimization as a criterion for the optimal value of q and find a K/T dependence, where K is the portfolio size and T the length of the time series. Both in numerical simulations and for real market data we find that power mapping leads to portfolios with considerably reduced risk. It compares well with another noise reduction method based on spectral filtering. A combination of both methods yields the best results.     

Instability in cointegration regressions: a brief review with an application to money demand in Portugal

This study addresses some modelling questions related to the possibility of structural change in models with nonstationary variables. Focusing on cointegration issues, some methodological aspects are discussed, attempting to integrate coherently the several steps of the modelling strategy. These range from unit root to cointegration testing and to testing for instability in the cointegration vector. An empirical example with Portuguese data tries to illustrate the usefulness of this approach, where a simple money demand function is estimated using an error-correction model (ECM). If a break is explicitly allowed in the cointegration vector the forecasting performance of the ECM improves.     

On improving the least squares Monte Carlo option valuation method

This paper studies various possible approaches to improving the least squares Monte Carlo option valuation method. We test different regression algorithms and suggest a variation to estimating the option continuation value, which can reduce the execution time of the algorithm by one third. We test the choice of varying polynomial families with different number of basis functions. We compare several variance reduction techniques, and find that using low discrepancy sequences can improve the accuracy up to four times. We also extend our analysis to compound and mutually exclusive options. For the latter, we propose an improved algorithm which is faster and more accurate.