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Ph.D. in Political Science - Comparative and European Politics Academic year 2012-2013

Ph.D. in Political Science - Comparative and European Politics Academic year 2012-2013 Part 1 Laboratory Methods Experimental methods in political and social sciences Alessandro Innocenti alessandroinnocenti@live.it Outline Part 1 Laboratory Methods

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Ph.D. in Political Science - Comparative and European Politics Academic year 2012-2013

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  1. Ph.D. in Political Science - Comparative and EuropeanPolitics Academicyear 2012-2013 Part 1 LaboratoryMethods Experimental methods in political and social sciences Alessandro Innocenti alessandroinnocenti@live.it Outline Part 1 Laboratory Methods To provide a basic introduction to experimental methodology both from a theoretical and an empirical point of view. Part 2 Experimental Design To learn how to design an experiment and to understand that experiments in political sciences share many features from cognitive and experimental economics. Part 3 Applied Experiments To understand the differences between different kinds of experimental designs by discussing weaknesses and strengths of some experimental papers and the specificities of their designs.

  2. Course Programme Class Laboratory Experiment Experimental Gaming, Solution Concepts and Cognitive Biases Reference to very elementary concepts of game theory is required (see http://www.labsi.org/innocenti/introgt.pdf) Part 1 Laboratory Methods Outline: Purposes of Experiments (Why?). Experimental Methods (how?). Professional Subjects, Students or What? Experimental Topics. Internal and external validity. Virtual experiments. A laboratory experiment will be performed at the start of the course and discussed during the class Literature: *Davis, D.D. and C.A. Holt (1993) Experimental Economics, Princeton University Press, Princeton, Chapt. 1-2. *Friedman, D. and S. Sunder (1994)  Experimental methods. A primer for economists, Cambridge University Press, Cambridge, Chapt. 1-2 *Friedman, D and A. Cassar (2004) Economics Lab. An intensive course in experimental economics, Routledge, London and New York, Chapt. 2-3 *Smith, V. (1994) “Economics in the Laboratory”, Journal of Economic Perspectives, 8, 113-131.

  3. Part 2 Experimental Design Outline: Two illustrative experiments. Biases in judgment: the case of confirmation bias. Trust game. Oxytocinand trusting behavior. Literature: *Jones, M. and R. Sugden (2001) “Positive confirmation bias in the acquisition of information”, Theory and Decision, 50, 59-99. *Kosfeld, M., M. Heinrichs, P. J. Zak, U.Fischbacherand E. Fehr (2005) “Oxytocin increases trust in humans“, Nature, 435, 673-676. *Morton R.B and K.C. Williams (2010) Experimental Political Science and the Study of Causality. From Nature to the Lab, Cambridge University Press, New York, Ch. 13. Part 3 Applied Experiments Outline: Informational cascades and overconfident behavior. Voting by ballots and by feet. Travel mode choice and transportation policy. Literature: *Innocenti, A., A. Rufa and J. Semmoloni (2010) "Overconfident behavior in informational cascades: An eye-tracking study", Journal of Neuroscience, Psychology, and Economics, 3, 74-82. *Innocenti A. and C. Rapallini (2011) "VotingbyBallots and Feet in the Laboratory", Giornale degli Economisti e Annali di Economia, 70, 3-24. *Innocenti, A.,  P. Lattarulo and M.G. Pazienza (2013) "Car Stickiness: Heuristics and Biases in Travel Choice",Transport Policy, 25, 153-168.

  4. Part 1 Laboratory methods POINTS OF VIEW PROS “Would it not be better to leave laboratory experiments to psychologists who are trained to run them properly? Nobody doubts that we have a great deal to learn from psychologists about laboratory technique and learning theory, but recent history would nevertheless suggest that the answer is a resounding no. Our comparative advantage as economists is that we not only understand the formal statements of economic theory, but we are also sensitive to the economic environments and institutions within which the assumptions from which such statements are deduced are likely to be valid. Just as chemists know not to mix reagents in dirty test tubes, so we know that there is no point in testing economic propositions in circumstances to which they should not reasonably be expected to apply.” (Binmore 1999) “Once models, as opposed to economies, became the focus of research the simplicity of an experiment and perhaps even the absence of features of more complicated economies became an asset. The experiment should be judged by the lessons it teaches about theory and not by its similarity with what nature might happen to have created.” (Plott 1991)

  5. POINTS OF VIEW CONS The laboratory is not a socially neutral context, but is itself an institution with its own formal or informal, explicit or tacit, rules Human agency takes place within a socio-economic world that is structured in the sense that it consists of internally-related positions and systems Experimentation in economics is likely to be of limited value, save for situations – such as auctions – that exist in conditions of relative isolation and are characterized by low internal complexity (Siakantaris 2000) • experimental situations often project a game-like atmosphere in which a ‘subject’ may see himself as ‘matching wits’ against the experimenter • experimental subjects are cast in roles and they can act in accordance with his (mis)perceptions of these roles • experiments have too short horizons (real world lasts many years and many trials) • human beings are capable to control their behavior through the implementation of abstract rules (Cross 1994)

  6. PURPOSES OF EXPERIMENTS (WHY?) 1) Test of Behavioral Hypotheses. by constructing a laboratory environment that satisfies as many of the structural assumptions of a particular theory, it is possible to verify its behavioral implications 2) Theory Stress Tests to examine the sensitivity of a theory to violations of obviously unrealistic assumptions 3) Searching for Empirical Regularities heuristic experiments to discover and document stylized facts (Davis-Holt, Experimental Economics 1994) a) Speaking to Theorists b) Searching for Facts c) Whispering in the Ears of Princes (Roth 1986)

  7. EXPERIMENTAL METHODOLOGY (HOW?) 1. PROCEDURAL REGULARITY to permit replications that the researcher and observers would accept as being valid - instructions - subject pool and methods of recruiting subjects - experimental physical environment - computerized or manual 2. MOTIVATION - Induced-value theory: use of a reward medium allows to induce pre-specified characteristics in experimental subjects and to make subjects’ innate characteristics largely irrelevant - monotonicity: subjects prefer more reward medium to less and not become satiated - salience: rewards are explicitly and unambiguously connected to the decisions made - dominance: changes in subjects’ utility from the experiment come mainly from the reward medium and other subjective costs or benefits are rendered negligible by comparison, i.e. others’ reward

  8. 3. UNBIASEDNESS Experiments should be conducted in a manner that does not lead participants to perceive any particular behavioral pattern as being correct or expected, unless explicit suggestion is a treatment variable - double blind setting 4. CALIBRATION The design has to pre-specify and to cleanly separate the experimental predictions of alternative theories. 5. DESIGN PARALLELISM Results established in the lab hold in other, especially non-lab, real-world situations where similar ceteris paribus conditions hold Vernon Smith’s parallelism precept (1982): “Propositions about the behavior of individuals and the performance of institutions that have been tested in laboratory microeconomics apply also to non-laboratory micro economies where similar ceteris paribus conditions hold” Charles Plott (1982): “While laboratory processes are simple in comparison to naturally occurring processes, they are real processes in the sense that real people participate for real and substantial profits and follow real rules in doing so. It is precisely because they are real they are interesting” 

  9. PROFESSIONAL SUBJECTS, STUDENTS or WHAT? Main Subjects pool - Undergraduate students • readily accessible • low opportunity costs • steep learning curve • they do not know much about experimenter’s hypothesis PhD students unreliable subjects because they get interested in what are you doing and respond to their understanding of your topic rather than to incentives you have constructed Classes or friends dominance or salience at risk, conflicts between personal, teaching and scientific aims

  10. Professional subjects • comparisons show that students are more adept at maximizing their profits and learning in the lab • high opportunity costs • pre-specified and innate characteristics are too strong • when involved in laboratory markets they attempt to apply rules of thumb, which, valuable for dealing with uncertainty in the parallel natural market, are meaningless guides in the lab. Controversial evidence  Burns (1985): professional wool buyers and students in a progressive auction (professionals apply familiar rules and not adjust to design requirements)  Dyer, Kagel, and Levin (1985): bidding behavior of students and construction workers (no difference)  Dejong et al (1988): Businessmen and students in sealed-offer markets (same profits, but higher variance for businessmen) What about gender, age, risk attitude, experience?

  11. Kagel, John H. - Roth, Alvin E. The Handbook of Experimental Economics INDEX a) public goods cooperation vs. selfishness (social dilemmas, free-riding, institutions) what improves cooperation (thresholds, learning)  b) coordination problems experiments with overlapping generations coordination games with Pareto ranked equilibria decentralized matching environments  c) bargaining experiments agreements causes of disagreements and costly delays bargaining protocol and preplay communications

  12. d) industrial organization trading institutions centralized and decentralized monopoly regulation and potential entry market structure and market power collusion factors product differentiation and multiple markets e) experimental asset markets informational efficiency of markets state-contingent claims and bubbles learning and dynamics of adjustment paths investment and public policy  f) auctions symmetric independent private-values models common value auctions collusion g) individual choice behavior

  13. individual Choice Behavior • Judgment A. Calibration 1. Scoring Rules 2. Confidence Intervals B. Perception and Memory Biases C. Bayesian Updating and Representativeness 1. Underweighting on Likelihood Information (Conservatism) 2. The Law of Small Numbers and Misperceptions of Randomness D. Confirmation Bias and Obstacles to Learning E. Expectations Formation F. Iterated Expectations and the Curse of Knowledge 1. False Consensus and Hindsight Bias 2. Curse of Knowledge G. The Illusion of Control

  14. II. Choice under Risk and Uncertainty A. Mounting Evidence of Expected Utility Violation (1965-1986) 1. The Allais Paradoxes 2. Process Violations 3. Prospect Theory 4. Elicitation Biases B. Generalizations of Expected Utility and Recent Tests 1. Predictions of Generalized EU Theories 2. Empirical Studies Using Pair-wise Choices 3. Empirical Studies Measuring Indifference Curves 4. Empirical Studies Fitting Functions to Individuals 5. Cross-Species Robustness: Experiments with Animals C. Subjective Expected Utility 1. The Ellsberg Paradox 2. Conceptions of Ambiguity D. Choice over Time

  15. II. Choice under Risk and Uncertainty / II E. Description Invariance 1. Framing Effects 2. Lottery Correlation, Regret, and Display Effects 3. Compound Lottery Reduction F. Procedure Invariance 1. New Evidence of Preference Reversal 2. Arbitrage and Incentives 3. Reversals and Markets 4. Social Comparisons and Reversals G. Endowment Effects and Buying-Selling Price Gaps 1. Market Experiments 2. Endowment Effects: Some Psychology and Implications K. Search 1. Search for Wages and Prices 2. Search for Information

  16. VIRTUAL EXPERIMENTS Many experimental economists seem to view their enterprise as akin to silicon chip production. Subjects are removed from all familiar contextual cues. Like the characters 'thing one' and 'thing two' in Dr. Suess' Cat in the Hat, buyers and sellers become 'persons A and B', and all other information that might make the situation familiar and provide a clue about how to behave is removed. George Loewenstein (1999)

  17. The context free experiment • The context-free experiment is an elusive goal and not necessarily a good thing • Games in the laboratory are usually played without labels but subjects inevitably apply their own labels • A major discovery of cognitive psychology is how all forms of thinking and problem solving are context-dependent (language comprehension) • The laboratory is not a socially neutral context, but is itself an institution with its own formal or informal, explicit or tacit, rules

  18. Internal vs. External Validity • Internal validity - ability to draw confident causal conclusions from one's research • External validity - ability to generalise from the research context to the settings that the research is intended to approximate • Experiments have the reputation of being high in internal validity but low in external validity • Field studies of being low in internal validity but high in external validity

  19. Methodological Biases • One of the basic tenets of laboratory methodology is that the use of non-professional subjects and monetary incentives allows making subjects’ innate characteristics largely irrelevant • In some experiments, it is as if subjects take into the lab the preferences applied to real choices and stick to them with high probability • These biases or inclinations tend to override the incentives effect • Labels may give subjects clues to become less and not more rational

  20. The power of labels • Subjects’ behavior depends more on prior learning outside the laboratory than on expected gains in the laboratory • Labels have the power to increase external validity with a minimal sacrifice of the internal validity • To test learning and cognitive models, itisnecessarytoremindand toevokecontextswhichmayactivateemotions, association, similarities in the laboratory • The use of presentations with virtual reality (VR) visualisations can convey objectively this kind of information • A Virtual Experiment combines insights from virtual reality (VR) simulations in computer science, naturalistic decision making (NDM) and ecological rationality from psychology, and field and lab experiments from economics

  21. Virtual Experiments • The methodological objective of Virtual Experiments is to combine the strengths of the artificial controls of laboratory experiments with the naturalistic domain of field experiments or direct field studies • In a virtual experiment the internal validity of controlled lab experiments is joined with the external validity of field experiments

  22. Applications – Head Mounted Display

  23. Applications – Cave

  24. Applications – Virtual Simulations

  25. Applications – Risk Perception Fiore et al. 2009 • Virtual Experiment to elicit subjective risk perception from wild fires and the opportunity cost of public funds allocated to prescribed burns • Subjects experience four dynamic visual simulations of specific wild fires, with varying weather and fuel conditions. Simulations are selected to represent high and low risk of fire damage • Participants experience a sense of presence, a psychological state of “being there and take decisions closer to real behavior (with cognitive constraints )

  26. Applications – Risk Perception

  27. ALBO PROJECT– Workplace Risk ALBO PROJECT The ALBO project is funded by the Tuscany Region in the framework of PAR FAS 2007-2013 Linea diazione 1.1.a.3 in agreement with the University of Siena. http://www.progettoalbo.it/index.php?lang=en to elicit factor of risks and job related stress in the workplace • by making interactive the simulation of “L’enterprisevirtuelle” by Government of France http://www.travailler-mieux.gouv.fr/

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