Michael W. M. Roos

The importance of time series extrapolation for macroeconomic expectations

Abstract This article presents a simple experiment on how laypeople form macroeconomic expectations. Subjects have to forecast inflation and gross domestic product growth. By varying the information provided in different treatments, we can assess the importance of historical time-series information vs. information acquired outside the experimental setting such as knowledge of expert forecasts. It turns out that the availability of historical data has a dominant impact on expectations and wipes out the influence of outside-lab information completely. Consequently, backward-looking behavior can be identified unambiguously as a decisive factor in expectation formation.

Do people make strategic commitments? Experimental evidence on strategic information avoidance

Game theory predicts that players make strategic commitments that may appear counter-intuitive. We conducted an experiment to see if people make a counter-intuitive but strategically optimal decision to avoid information. The experiment is based on a sequential Nash demand game in which a responding player can commit ahead of the game not to see what a proposing player demanded. Our data show that subjects do, but only after substantial time, learn to make the optimal strategic commitment. We find only weak evidence of physical timing effects.

Information, Learning and Expectations in an Experimental Model Economy

The experimental ‘learning-to-forecast’ literature finds that subjects use simple linear backward-looking models when forecasting in environments with little to no inout the economic framework. We study the formation of expectations in a laboratory economy of monopolistic firms and labour unions with almost complete knowledge of the model. We observe simple backward-looking rules, but also a considerable share of model-based expectations using information on the economic structure. At least for some subjects, expectations are informed by theory. As in the previous literature, we find individual prediction rules to be heterogeneous.

Agglomeration and the public sector

Abstract I present a two-region model in which the actions of local governments can cause the agglomeration of population. A local public good is a centripetal force. The centrifugal force is competition among interregionally mobile workers for housing. In the model the supply of the local public good rises in the number of workers in a region. This creates incentives for immigration. Depending on the relative strength of the centrifugal force, full agglomeration of all workers in one region can result even with perfectly identical regions. This creates an incentive for the local governments in each region to provide the public good strategically leading to overprovision and suboptimal agglomeration.

The Macroeconomics of Radical Uncertainty

Macroeconomics must take radical uncertainty into account, if it aims at contributing to the solution of serious real-world problems such as climate change. Allowing for radical uncertainty must happen at two levels: the level of modeling and the level of the scientifi c discipline. I argue that the complexity approach which sees the economy as a complex adaptive system is better suited to deal with radical uncertainty than the mainstream DSGE approach. I review a number of agent-based models that are promising starting points to incorporate radical uncertainty into macroeconomics. Discussing the examples of the fi nancial crisis and climate change, I establish why methodological monism is dangerous and why macroeconomics needs more pluralism and openness towards other scientifi c approaches. Radical uncertainty and the complexity approach have important implications for macroeconomic policy and the advice that economists can give to policy makers. Under radical uncertainty it does not make sense to look for optimal policies.

Trust in a Network of Investors and Startup Entrepreneurs

We propose a simulation model of a stylized angel investor market in which the business relations are conditioned on the trust of the angel into the startup entrepreneur. Initial trust depends on social proximity between the angel and the entrepreneur and is later on updated depending on the returns an investor receives from an entrepreneur. We show that investors benefit most in terms of returns from an intermediate sensitivity of trust to returns. From an investor’s perspective, too much trust keeps too many unproductive firms in the market, while too little trust leads to the termination of profitable relations because of minor productivity drops. The proportion of entrepreneurs who reach the objective of leaving the market with enough capital, however, is higher if investors lose trust quickly and stop funding early. In this sense there is a conflict of interest between investors and entrepreneurs.

An Experiment on Consumption Responses to Future Prices and Interest Rates

We design an experiment to investigate the influence of announced future variations in interest rates and prices on consumption decisions. In an experimental implementation of the discounted utility model, the subjects learn the entire paths of inflation and interest rates prior to deciding on a consumption path. We decompose the total change in consumption that results from changes in either interest rates or inflation rates into anticipation and impact effects. While impact effects are of similar orders of magnitude as in the model, future changes in inflation or interest rates exert substantially smaller effects on current consumption than predicted by the model.

Price-Setting Behavior with Menu Costs – Experimental Evidence

We experimentally test the price-setting behavior of firms in the Rotemberg (1982) model in order to explain puzzles in the New Keynesian Phillips curve (NKPC). By constructing categories and a quantitative measure that compare behavior with optimum we find heterogeneous price-setting behavior by degree of information acquired about the future. Subjects rarely use past information, but overweight their own past price. We study the impact of heterogeneous price-setting behavior on estimated theoretically derived and hybrid Phillips curves. We find support for features of both NKPCs in our findings at the micro level. But the hybrid NKPC has a superior fit.

Real time tacit bargaining, payoff focality, and coordination complexity: Experimental evidence

We conduct a bargaining experiment where interaction is tacit and payoffs are earned and cumulated in real time. We test hypotheses about the interaction between the focal properties of payoffs and the complexity of coordinating on an intertemporal behavior that achieves them. The general finding is that when a payoff focal outcome requires a complicated coordination scheme bargainers tend to settle on a simpler and sometimes inefficient behavior.

Modeling Radical Uncertainty and Anticipating Uncertain Change with Models

AbstractIn this paper, I argue that agent-based modeling and simulation in a complexity framework can be useful scientific tools to think about the uncertain future. I will argue that the usefulness of this approach depends on its capability to generate surprise and discuss what conditions are needed for surprises to happen. The main value of agent-based models and simulations is to produce possible futures. This is the anticipation function of a model. It is important to emphasize that anticipating possible futures is different from predicting the most likely future evolution of some variables and requires a different understanding of what the science of economics can achieve. Therefore, I will discuss some epistemological thoughts related to the economic study of uncertain futures. Building on these foundations, the paper presents three methodological approaches of how agent-based models and simulations could be used to anticipate potential futures.