The future of food production – a text-mining approach

ABSTRACT

The system of food production is facing grand challenges, such as a rising population, climate change, degrading bio-productivity of agricultural land and over-fishing. Agriculture and food production are becoming more innovative and implement new infrastructure, IT-platforms or biotechnologies, like gene editing or synthetic food production. A more advanced knowledge base about food innovations helps customers to build informed opinions of new technologies and provides policy makers and industry actors with better information for strategic decision-making. As the amount of available information exceeds expert knowledge or manual filtering of data outputs, this paper presents a text mining study on science and technology in food production based on more than 30 million documents. The proposed methodology which we demonstrate on the example of the future of food production can be applied each time new data becomes available and can serve as an early warning system for a changing technology landscape.     

Agreeing on generalized Darwinism: a response to Geoffrey Hodgson and Thorbj?rn Knudsen

I thank Geoffrey Hodgson and Thorbj?rn Knudsen for their thought-provoking response to my latest generalization of Darwinism, and welcome their proposal to cooperate, after many years of our independent searches. I agree with them that our searches contain more similarities than both they and I had previously seen, but consider our remaining differences—especially in the terms employed and in the definitions of the terms we both employ, including “information,” “instructions,” “programs,” and “Lamarckism”—more important than they do. Their response also exaggerates or distorts some of my arguments. All this needs to be clarified before our cooperation can start.     

The returns to training in Russia: a difference‐in‐differences analysis

The experience of developed countries – particularly member‐states of the OECD – has shown that employers are actively investing in developing the human capital of their employees. According to research conducted by the World Bank, more than half of the companies in developed countries provide their employees with training in one form or another. There is, however, reason to believe that the situation is quite different in Russia. Some studies have shown that the level of investment in training in Russia is much lower. This difference can be explained by the fact that employers do not see the point in such investment because it is much easier to lure employees with the required qualifications than to train their own staff. Moreover, Russia faces a problem with high employee mobility, meaning that companies are not sure that they will get a return on their investment. Given these circumstances, the present study examines whether investments in human capital in Russia are profitable. It investigates the wage return to job‐related training using a difference‐in‐differences estimator to control for unmeasured differences in ability and measured differences in past wages as a proxy for ability and motivation. Estimates use panel data from The Russia Longitudinal Monitoring Survey – Higher School of Economics from 2004 to 2011. As predicted, positive returns to training are identified and the returns increase absolutely with the level of past wages.     

Bringing institutions into evolutionary economics: another view with links to changes in physical and social technologies

Like Nelson (2002), I make a case for bringing institutions into evolutionary economics. But unlike Nelson, who defines institutions as social technologies consisting of rules-routines, I define them in agreement with North (1990) as humanly devised rules-constraints - such as formal law and informal social norms - but also view them, to accommodate most of Nelson's approach, as constraining the variety of rules-routines employable by agents. I show that this definition has advantages for communicating with modern institutional analysis, for clarifying how institutions can influence, and be influenced by, changes in physical and social technologies, and for producing policy implications.JEL Classification: B52, B15, N01, A10I thank Niclas Berggren, Thrainn Eggertsson, Gunnar Eliasson, Geoffrey Hodgson, Dan Johansson, Nils Karlson, Staffan Laestadius, Richard Nelson, Mark Perlman, Viktor Vanberg, Gerhard Wegner, the participants of seminars at the University of Jena and the Royal Institute of Technology in Stockholm, and two anonymous referees for valuable comments on earlier drafts.     

Is Violation of the Random Walk Assumption an Exception or a Rule in Capital Markets?

Both the efficient market hypothesis and modern portfolio theory rest on the assumptions of the Gaussian probability distribution and independence of consecutive returns. This paper provides a brief excursion into the history of capital market research. A measure of long-range dependence (Hurst exponent) was applied to daily returns of selected stock indices and individual firms. The Hurst exponent was estimated using rescaled range analysis. The estimates are based on an unusually large sample of empirical-time series from capital markets. This method distinguishes whether the data-generating process follows random walk or exhibits antipersistent or persistent behavior. Both the efficient market hypothesis and modern portfolio theory assume that the data-generating process has no memory, i.e. follows Brownian motion. The random walk process is characterized by a Hurst exponent value of 0.5. Values greater than 0.5 and less than 1 indicate a persistence of local trends. Values between 0 and 0.5 indicate a process that reverts to the mean more often than a random process (mean-reverting process). The results indicated that the series of daily returns exhibit predominantly persistent or antipersistent behavior. Therefore, Brownian motion cannot be perceived as the norm for describing stock market behavior. These findings challenge the assumption of a random walk in stock prices, valuation models and assessment of risk.

     

Dilatation monotone risk measures are law invariant

We prove that on an atomless probability space, every dilatation monotone convex risk measure is law invariant. This result, combined with the known ones, shows the equivalence between dilatation monotonicity and important properties of convex risk measures such as law invariance and second-order stochastic monotonicity. We would like to thank Johannes Leitner for helpful discussions. The second author made contributions to this paper while being affiliated to Heriot-Watt University and would like to express special thanks to Mark Owen, whose project (EPSRC grant no. GR/S80202/01) supported this research.     

Marxism and the structure of the future

A creative dialogue between Marxist and non-Marxist scholars, involving mutual criticism and due consideration of the consequences of their respective attitudes is needed to overcome the present crisis in futures studies. Within the framework of a new interpretation of Marxian dialectics, the structure of the future is seen as comprising a definite field of multiple possibilities. The meaning of propositions such as ‘the socialist future’ are examined in an attempt to think of the future in terms of probabilities and in the context of a system's view.     

Are structured products ‘fairly’ priced? An analysis of the German market for equity-linked instruments

Based on a unique data set, this paper examines the pricing of equity-linked structured products in the German market. The daily closing prices of a large variety of structured products are compared to theoretical values derived from the prices of options traded on the Eurex (European Exchange). For the majority of products, the study reveals large implicit premiums charged by the issuing banks in the primary market. A set of driving factors behind the issuers’ pricing policies is identified, for example, underlying and type of implicit derivative(s). For the secondary market, the product life cycle is found to be an important pricing parameter.