The evaluation of generic cross-impact models

The first cross-impact models were developed ten years ago. Since then, many versions of this technique have been developed. This article proposes criteria for evaluating generic cross-impact models and demonstrates the use of these criteria. It distinguishes carefully between generic cross-impact models and application models. Generic models consist of mathematical definitions and computational procedures; application models consist of a generic model plus appropriately expressed data relevant to the topic being analysed. Four criteria are proposed for evaluating generic cross-impact models: internal consistency, robustness, generality, and clarity.     

Cross-impact analysis and classical probability: The question of consistency

A great deal of confusion has surrounded the basic definitions and concepts in the various versions of cross-impact analysis. The purpose of this article is to clarify the meaning of one of the fundamental concepts-conditional probability-as used in a cross-impact analysis. The authors begin by illustrating two versions of conditional probability, one based on correlation and one based on causation, and show that the latter is much better suited to the study of alternative futures. One of the main sources of past misunderstanding is the attempt to apply the correlative conditions of Bayes' theorem to a causative cross-impact analysis. They demonstrate that there is no inconsistency between Bayes' theorem and cross-impact analysis; the confusion results from the use of Bayes' theorem when the basic analysis involves causation.     

Events and economic forecasting models

In the June 1972 issue of Futures, Olaf Helmer developed the idea of cross-impact analysis to include both events (singular occurrences) and trends (gradual developments).¹ The present article pursues further this idea, using an econometric forecasting model to represent the economic trends in an economy, and a sequential cross-impact method to analyse the events which could change its course. The application of this idea, also described in the article, suggests a procedure for improving the communication between model builders and final users.     

A gross-impact case study: The Dutch construction sector

The authors advocate the use of cross-impact models for scenario generation and describe a calibration technique which reduces problems of scaling. In a study of the Netherlands construction sector to 1990, aggressive interviewing of experts produced quantified trends. After cross-impact analysis, an input-output table for 1990 was estimated from that for 1975. A number of scenarios were also developed, by adding events to the matrix. The authors review the strengths and weaknesses of the methods used and summarise the results of the study.     

Cross-impact and no-dynamic-arbitrage

We extend the ‘No-dynamic-arbitrage and market impact’-framework of Gatheral [Quant. Finance, 2010, 10(7), 749–759] to the multi-dimensional case where trading in one asset has a cross-impact on the price of other assets. From the condition of absence of dynamical arbitrage we derive theoretical limits for the size and form of cross-impact that can be directly verified on data. For bounded decay kernels we find that cross-impact must be an odd and linear function of trading intensity and cross-impact from asset i to asset j must be equal to the one from j to i. To test these constraints we estimate cross-impact among sovereign bonds traded on the electronic platform MOT. While we find significant violations of the above symmetry condition of cross-impact, we show that these are not arbitrageable with simple strategies because of the presence of the bid-ask spread.     

Exploring long-term business climates and strategies with interax

A major objective of corporate strategic planning is to minimize the surprises the future may bring, and INTERAX (developed at the Center for Futures Research with industrial sponsorship) draws on cross-impact matrices and scenario generation to allow alternative futures to be explored. This paper outlines the method, and summarizes part of the present database—a Delphi study of possible social, economic, and political developments, internationally and within the USA.     

Cross-impact analysis using group decision support systems: an application to the future of Hong Kong

When several interdependent events affect the future of an organization, an industry, or a society, it is often useful to know how these events may affect each other. Determining the impact of external events on other such events, called a cross-impact analysis, is usually accomplished by asking knowledgeable people to (1) discuss any relationships among the events and (2) provide subjective estimates of conditional probabilities relating the events. However, there are two possible problems. First, in some political environments people may be reluctant to discuss the events openly. Second, the subjective probability estimates may violate the laws of probability theory, such as Bayes' theorem. We present a simple method, using group decision support systems (GDSS), for eliciting anonymous comments and preparing consistent probability estimates concerning interdependent events. We then illustrate our method by using it to perform a cross-impact analysis concerning the future of Hong Kong.     

Economic perspectives of technological progress: New dimensions for forecasting technology

The environment of technology is changing, research and development budgets are no longer growing rapidly, and the objectives of research and development are increasingly directed to solving environmental problems and the pressure on natural resources. The causal relationship between the allocation of finance and technological growth is discussed. The author suggests that financial cross-impact, previously ignored by most forecasters, is becoming an important determinant of technological progress. Technology-forecasting techniques must be modified to incorporate economic constraints. Current technological scenarios which ignore the financial dimension are likely to prove over-optimistic.     

Cross-impact analysis: Extended KSIM

The authors present an extension of Kane's cross-impact simulation model (ksim) that allows the inclusion of events and trends, and discuss the basic issues of forecasting and compatibility of forecasts.     

Judgement research in policy analysis

A primary purpose of futures research is to assist the formulation of policy; as such, futures research is an instrument of policy analysis. A parallel field of research in the behavioural sciences-judgement research-is also potentially an important instrument of policy analysis. Practitioners and consumers frequently overlook both the extent to which futures research is based heavily on judgements, and, therefore, the extent to which it would benefit from incorporating the principles and techniques of judgement research. This article explores the relationships between futures research and judgement research (and their links with policy analysis, and planning) and discusses the gains to policy analysis and formation-notably in the creative aspect of policy invention -from a linking of, and interaction between, the two areas. Two recent developments in applied research, symmetrical linkage systems (judgement research) and interactive cross-impact modelling (futures research), are used as vehicles for the discussion ; and the practical value of the behavioural sciences approach is indicated in a discussion of group decision making.     

Scenario generation: limitations and developments in cross-impact analysis

Informed subjective judgement has a place in decision making, and cross-impact analysis may be useful in providing this information. The authors focus on the art of scenario generation, reviewing a number of existing procedures and noting their limitations. The information needs of decision makers are discussed and three alternative approaches are outlined and compared in terms of their relative efficiency.     

The Akropong approach to multi-sector project planning

We introduce an approach to cross-sector project planning developed in the context of a climate change adaptation strategy being carried out in Ghana. The approach, which uses a simplified cross-impact approach, should be applicable in many cross-sector or cross-disciplinary studies in which the work is carried out by sector or discipline-specific teams.     

The impact of inflation on ROE,growth and stock prices

Using the constant growth dividend discount model (DDM), it can be shown that the critical factor which determines whether common stocks will be able to be an inflation hedge is the growth rate of dividends. In turn, the growth of dividends is mainly impacted by the aggregate return on equity (ROE). Using the DuPont formula, it is clear that the main variable that drives the aggregate ROE in an inflationary environment is the profit margin.Following from this background, this article updates and extends an earlier analysis that involves an analysis of ROE and its components for the 40-year period 1956–1995. The analysis demonstrates that the aggregate ROE is currently at about the same level as in the 1960's, but the components have changed, that is, there has been a decline in total asset turnover and profit margin, but a significant increase in financial leverage that has compensated for the declines in turnover and profit margin. It is further shown that there have been periods of high and low inflation since 1956, and the negative impact of inflation of the implied growth rate is confirmed, which helps explain why investigators find consistent empirical results that common stocks are poor inflation hedges.     

Two complementary cross-impact models: MIP1 and MIP2

The postulates on which probabilistic cross-impact models are built have progressed considerably and still vary today from author to author. The author reviews the characteristics of these models and the objectives that their users can hope to achieve. Two new models, MIP₁ and MIP₂, designed to minimise the disadvantages of existing models, are proposed.     

SMIC 74—A method for constructing and ranking scenarios

A valid concept of what the future could be implies the existence of an overall conjectural framework which makes full allowance for the dynamics and complexity of the various systems involved. Such a framework must integrate the variable factors which determine the behaviour of all the economic and other agents contributing to the shape of the future, even when these variables are of a qualitative, subjective nature. A new method based on the cross-impact analysis is proposed to improve decision-making processes. A simple example is given to illustrate how this method can be used in forecasting studies and scenarios.     

Reassessment of cross-impact analysis

Five problems in cross-impact methodology are discussed, solutions are proposed, and a simple illustrative case is provided. The problems are lack of commutativity, probabilistic imbalances, double counting of impacts, linearity, and two-dimensionality.     

The evolution of the Australian life insurance industry

The life insurance industry in Australia has traditionally been an important source of long term finance for both the public and private sector. However, very little historical analysis has been undertaken into an industry that constitutes a fundamental part of the economy's financial sector. The present climate of deregulation has initiated an irrevocable process of change within the industry. To comprehend the full implications of this change it is necessary to have an understanding of how the industry has evolved. This paper seeks to provide a background account of the growth of the life insurance industry in Australia highlighting the influences that have determined the structure of the industry.     

我国开征不动产税与增强地方政府公共服务能力的思考

在物质生活基本得到满足的情况下．老百姓对医疗、教育、社会保障、公共安全以及环境保护等公共产品和公共服务的需求越来越突出，对地方政府的目标要求也不再是发展经济这一单一目标，而是更加强调其公共服务的能力。地方政府的公共服务能力在很大程度上取决于其收入能力。本文将探讨不动产税改革将如何在增强地方政府公共服务能力中发挥作用，并针对开征不动产税过程可能遇到的难点问题，提出相关对策建议。     

A Markovian cross-impact model

The author describes a cross-impact method which is based on Markov-chain theory. This allows scenarios to be derived which explicitly include the time dimension. An example of the use of the method is included which deals with the installation of nuclear reactors for energy production.     

Did expected returns fall? Evidence from UK size portfolios

Ex post equity returns were extremely high during the latter part of the twentieth century and in particular during the 1990s. Many observers suggest ex post returns have been higher than expected returns. This article suggests, in the case of the UK, that the largest firms primarily cause the appearance of a shift in expected returns during the 1990s. The article presents some novel evidence consistent with an earlier shift in expected returns for small- and medium-sized firms in the early 1980s. However, evidence from structural break tests on valuation ratios is consistent with either moderate changes in long-term expected fundamental growth or long-term expected returns; it is difficult to distinguish statistically between these two competing explanations.