Otwin Becker

Heuristic modeling of expectation formation in a complex experimental information environment

Abstract Academic subjects made judgmental forecasts of a graphically presented time series in a laboratory experiment. Besides the past realizations of the time series itself, the only available information for the forecasting task was provided by leading series, i.e. indicators with a constant lead period of one. The number and the quality of the leading series were varied systematically between seven versions of the experiment resulting in different levels of information complexity. We present a heuristic that explains the subjects’ average forecasting behavior better than the rational expectations hypothesis in all versions of the experiment. Furthermore, we find that the forecasting accuracy of the subjects increases with the number of reliable indicators but their efficiency declines with increasing complexity.

Educational effects in an experiment with the management game SINTO-Market

This paper examines how the educational background influences the performance of managers’ strategies. The research is based on data collected by an experiment with the management game SINTO-Market. This management game puts the players in a competitive situation in the branded food product sector, within which the subjects take over the role of the managers who have to find out the most successful strategy. From experimental research with this management game we will draw some interesting conclusions about human behavior in complex economic decision-making situations. To investigate educational effects the management game SINTO-Market was performed with students of different educational levels 17 times. The results show some significant differences between graduates and undergraduates.

Modeling Expectation Formation Involving Several Sources of Information

Abstract Experimental studies of expectation formation of subjects are predominantly limited to the prediction of one single time series despite the practical relevance of expectations in situations with multiple sources of information. In this paper, we report on an experiment in which subjects are given time series (indicators) as additional information for the judgemental forecast of a stationary time series. The quality and the number of these indicators are varied in three versions of a forecasting experiment. We explore the effects on forecasting accuracy and we test the average forecasts of the subjects for consistency with the rational expectations hypothesis. A simple heuristic is presented that explains the average forecasting behavior better than the rational expectations if indicators are presented to the subjects. It is demonstrated by a simulation study that this result is representative for the considered stationary stochastic processes.

Some New Lotka-Volterra-Experiments

The experiment described here has problems of economic stabilisation in mind, but, mainly for reasons of simplicity, it attacks the problem in the field of biology. A biotope consisting of two populations should be brought to a stationary fixpoint level by means of four different instruments. In each treatment of the experiment, however, only one instrument can be used to reach the two-dimensional goal.

Modelling Judgmental Forecasts under Tabular and Graphical Data Presentation Formats

The accuracy of statistical time series forecasts is a critical factor for the situationspecific application of a model. Makridakis and Hibon (1979) were the first to empirically explore the performance of various statistical models in forecasting competitions on a data set of thousands of real time series. It was found inter alia that simple procedures, such as exponential smoothing, perform equivalently to sophisticated models (Makridakis and Hibon, 2000) — a result supported by many other authors. Although statistical models were the initial interest of forecasting competitions probably the most common forecasting approach was incorporated soon: judgmental forecasting. Judgmental forecasts are based on subjective eyeballing of the past realizations of the time series without the support of statistical procedures — a technique which seems to be inferior to statistical procedures at first glance. Lawrence et al. (1985) applied 111 real-life time series of the Makridakis forecasting competition (Makridakis et al., 1982) in a forecasting experiment and compared the accuracy of judgmental forecasts to statistical models. Judgmental forecasts were at least as accurate as statistical models, and in some cases even superior to them. The authors also identified the influence of data presentation formats on the accuracy: Forecasts of time series presented in tables significantly outperformed graphs for annual time series (long run). They also found table forecasts to be more robust, i.e. smaller standard deviations of the forecasting errors. The authors attribute the differences to the inability of tabular forecasters to

Bounded Rational Strategies in Sequential Bargaining: An Experiment and a Learning by Evolution Strategy

In a sequential bargaining experiment the players had to choose strategies for a round of two-person games with different players. After each round the players had the possibility to revise their strategies for a new round. The final strategies formed a special kind of equilibrium which can be interpreted as bounded rational equilibrium. An attempt is made to identify bounded rational behavior with subsets of the set of all strategies. A parametric strategy which models some elements of bounded rational behavior is adapted in a process of learning from repeated games. The learning process is modeled by simulating a simple evolution process with successive steps of mutation and selection.

Encounters with Reinhard Selten: An Office Mate’s Report

In winter term 1960/1961 about 100 students applied for the economic seminar held by Professor Heinz Sauermann. As an economics student at the University of Frankfurt, I took part in that seminar. Among the students it had the reputation of being the most challenging course in the field of economic theory.

Forecasting Behavior in Instable Environments

In many economic situations periodically occurring changes in behavior of the involved agents can be observed. These changes have the characteristics of abrupt structural breaks. The behavior often seems to switch between regimes as if there were constant relationships between economic variables between these breaks. Examples are the alternating price determination of sellers and buyers on a market out of equilibrium or the periodical development of price cartels and the resulting switches in prices. In this study, we want to analyze the expectation formation of participants of a laboratory experiment subject to regime switches. Despite the practical relevance there is hardly any experimental contribution regarding the reaction of economic decision-makers to structural breaks. The only systematic experiment in this context was performed by [2]. The authors found inconsistent evidence on the performance of judgmental forecasts versus statistical procedures in the literature and therefore wanted to experimentally test the individual performance of subjects. The noise levels of the time series, the type of break (abrupt or creeping) and the direction of the break was systematically varied between 10 time series. The participants were told that the time series may contain structural changes. The judgmental forecasts were found to perform significantly worse than statistical procedures. The subjects were trying to read too much signal into the series and their forecasts contained excessive noise. In our experiment the forecasting performance will be analyzed but the main interest is the explanation of the average forecasts in order to understand how the subjects react on the break. The most simple casefor a structural break in our data generating process is a constant shift. Three time series are applied in the experiment subject to one break and two breaks respectively. Between the breaks the data generating process remains constant. By these means the behavior of the subjects in several regimes and their reactions on the breaks can be observed. Recently [1] presented a simple heuristic for the modeling of average forecasts of the subjects. The authors showed that the model forecasts the behavior of the subjects better than the Rational Expectations Hypothesis (REH) when indicators are in the information set of the participants. This heuristic is restricted to stable and stationary time series. We will apply a modified version of the model to the forecasts in the setting with the structural breaks. We find that the behavior of the subjects after the break is best described by a transition phase. When the new level of the series has established several periods after the break the information before the break (i.e. especially earlier turning points) is gradually ignored. We also find that the human performance compared to statistical procedures is rather poor.

The management game SINTO-Market — report on some recent experiments

The management game SINTO-Market which was originally developed and programmed by Otwin Beckerand Reinhard Selten was recently performed at the University of Kalmar/Sweden and University of Graz/Austria several times. The decisions were made by groups of students, each group representing one of the three firms. The electronic management game SINTO-Market puts the players in a competitive situation in the branded food product sector. We will give a short description of the structure of the game. The game runs via internet and can be seen at the web-page of our department. It is interesting to see that much can be learned about human behavior in complex economic decision situations from experimental research with management games. Surprisingly the results show some differences between genders

Bounds & likelihood procedure revisited.

In an experiment subjects are asked to predict the next value of an univariate time series on the basis of the past observations. The average forecasts of the subjects can be well described by a surprisingly simple rule, which is called the “Bounds and Likelihood procedure”(Becker/Leopold 1996). In a new series of the experiment, conducted 2002 in Graz with 72 participants, the behaviour and score of the subjects is further analysed with the Selective Attention Test (subset of D2, Brickenkamp 1962) and Intelligence Test for Reasoning (subset of PSB, Horn 1969).