economics, psychology, and interactive decision making - will the reign of reason rule on?

8/9/2019 Economics, Psychology, and Interactive Decision Making - Will the Reign of Reason Rule on?

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Economics, Psychology and

Interactive Decision Making:

Will the Reign of Reason Rule On?

Course Name: Applied Economics and Public Policy-2

Course No.: 214

An Assignment

Presented to the respected course teacher

Dr. Sayema Haque Bidisha

Assistant Professor

Department of Economics

University of Dhaka

Date of Submission: 10th April, Saturday, 2010.

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Identity of the Assignment Collaborators

(Names have been arranged according to their respective roll no.):

Group Name: Ark of Noah

No. of Group Members: 6

1. Md. Javed Hossain ( Roll No.: 13)

2. Nazmus Sakib (Roll.No: 14)

3. Safaeduzzaman Khan (Roll No.: 15)

4. Md. Al-Amin Parvez (Roll No.: 53)5. Md. Zayeed Hasan Talukdar (Roll No.: 75)

6. Md. Ohiul Islam (Roll No.: 79)

All are students of 2nd Year, 4th Semester

Session: 2007-2008

Department of EconomicsUniversity of Dhaka

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Table of Contents

Topicspage

1. Introduction.4

2. Research Question..7

3. Literature Review..7

4. Theoretical Background8

5. Econometric Specification.9

6. Methodology and Data..9

6.1 Methodology of the Study9

6.2 Description of the Data9

7. Analysis of the Study..11

8. Recommendation and Conclusions...28

8.1 Shortcomings of the Study...28

8.1.2 Directions for New Research29

8.2 Recommendations.29

8.3 Conclusions33

REFERRENCE..34

APPENDIX.35

Abstract:

In our paper we try to uncover the underlying philosophy of the sense of economic "rationality" and

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decision making under various cognitive and psychological problems emanated from economic

phenomena. The subjects were asked to respond to virtual decision and game situations at several

observations were collected and the results of their decisions along with ambient variables e.g. response

time were recorded. Furthermore, we analyze the psycho-economic behaviors such as preference, belief,

bias, and related cognitive and emotional factors. Consequentially our analyses draw to the manikin

model of economic behavior and propose further development of the model of a "rational" choice

assimilating the prevalent cognitive biases and choice errors of human beings.

1. Introduction:

1.1 Background:

Theoretical Characterization of Economic Rationality:

Economic theorists characterize an individual decision maker using three basic concepts:

1. A collection of objects: The manner in which a decision maker perceives an object does not have to be

objective. For example, one decision maker might think about a red triangle as a triangle while another

might think about it as a red object.

2. Mental preferences: These describe the mental attitude of an individual toward the objects. They can be

defined in contexts that do not involve actual choice. In particular, preferences can describe tastes (e.g., a

preference for one season over another) or can refer to situations that are only hypothetical (e.g., the

possible courses of action available to an individual were he to become emperor of Rome) or that the

individual does not fully control (e.g., a game situation in which a player has preferences over the entire

set of outcomes).

3. Choice: It is customary to describe a choice situation using a set of objects the individual can choose

from. A choice function spells out how the individual will respond to any choice situation he might face.

The standard economic approach assumes that a decision maker is rational in the sense that (i) in any

choice situation within the domain of his choice function he objectively identifies the set of objects, (ii)

his choice function is consistent with maximization of some preference relation that we will refer to as the

behavioral preferences, and (iii) the behavioral preferences are identical to the mental preferences.

But with the development of economics classical axioms and assumptions has been challenged

vigorously. As the world is not "perfect", consumers are not "know-all wizards" and events are not

"certain", the modeling of decisions has found several new directions and scopes of research and

authentication.

Approaches to the Frontiers of Rationality:

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There is growing interest among economists in the bounds on the rationality of economic agents.

Economists are increasingly abandoning the "economic man" paradigm and instead are using models that

reflect what they consider to be more realistic descriptions of the way in which human beings make

decisions. One can identify three approaches in the literature to "opening the black box" of decision

making

Bounded Rationality:

This approach is based on casual observations of the way in which people make decisions (and primarily

of our own decision-making processes). These are used to construct abstract models which are intended to

increase our understanding of the effect of certain decision-procedural elements on the outcome of an

economic interaction. Thus, for example, Rubinstein added an assumption to the standard model of the

repeated game such that players consider not only their standard game payoff but also the complexity of

their strategies. The inclusion of complexity considerations in these models is based on our intuition

about the meaning of complexity in long-term strategic situations. However, the choice of the actual

complexity measures has not been linked to any empirical findings.

Behavioral Economics

Daniel Kahneman and Amos Tversky carried out a study which not only refuted the standard use of the

economic man paradigm but also identified psychological elements which are systematically used by

decision makers. Their findings demonstrated the involvement of emotions and procedural elements

which were missing from the standard application of rationality in economics. The conclusions of the

Kahneman and Tversky school, as well as the feeling that traditional models had been exhausted, led in

the 1990s to the establishment of the field of Behavioral Economics. Researchers in this field usually

preserve the assumption that an agent is rational in the economic sense of maximizing a well-defined

target function; however, they do not feel obliged to define the target as material rewards. Agents in these

models maximize a utility function which also reflects psychological motives such as care, envy and

reciprocity. Note that for the most part behavioral economics does not relate to the procedural elements of

decision making but rather only to the incorporation of psychological elements in the utility function.

Game Theoretic Analysis of Psychological Phenomena:

Modeling the interaction between such agents could also be accomplished by applying the standard game

theoretical equilibrium concepts. However, once we do not require that economic agents behave as utility

maximizers the study of the interaction between agents requires the invention of new notions of

equilibrium. Notwithstanding, it is very successful method to judge the procedures of interpersonal

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decision-making with or without the introduction o risk and uncertainty.

1.2 Motivation:

In the above stance, we examine several theoretical concepts from game theory and preference and choice

theory which we transform into experiments and realize their practicality and practicability to gain

insights into the real-life economic decision making

In questions of preference and choice theory, we resort to the theoretical solution and then compare it

with the actual solutions suggested by our experimental "subjects". As preference and choice theory is

founded on the grounds of human psychological realities, we think the answers gathered from the data are

both necessary and sufficient to advocate our claims

In case of experiments concerning game theory, along with the theoretical and experimental answers, we

accompany it with the records of "response time" i.e. the time lapse between meeting and answering an

experimental question. In what follows, we present the more interesting results of the research. In most

cases, there were huge differences in the time response distributions of the various choices made. Often

one distribution lay completely to the right of another we will interpret such a configuration as evidence

that it requires more response time.

2. Research Questions and Objective of the Study:

What on earth are economists trying to accomplish? As we realize it, economics substantially deals with

minds; more specifically with "psychology", will it enable us to perform engineering with minds: the

most beautiful "machines" that we think of? Inspired by the questions posed by both economics and

psychology, our research addresses to the testing and rationalizing some standard theoretical economic

models in terms of psychological and behavioral experiments, comments in the light of the experimental

evidence and consequentially draws to some principle of the philosophy of economics and psychology. In

short, we search for answers to the following riddles:

The problem of the notions of rationality: How do we behave in our "real" lives: like a Homo

sapiens or a like a Homo economicus?

The problem of meaningless conclusions and propositions: Should we abandon an economic

model if it produces absurd conclusions?

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The problem of validity: Can we have a trend of "principles" which will be able to overtake and

assimilate all "patterns"?

The problem of responding to experimental evidence: Should our economic models be judged

according to experimental results?

The problem of limitations: Should we regard a model as a very limited set of assumptions that

will inevitably fail in some contexts? What are our scopes and boundaries?

The problem of modelless regularities and model-outside irregularities: Should models

provide the hypothesis for testing or are they simply exercises in logic that have no use in

identifying regularities?

The problem of reference: Does our sense of "fairness" match with the "solutions" referred by

the standard theories?

3. Literature Review:

As far as the interaction of economics and psychology is concerned, there exists a wealth of literature by

Kahneman and Tversky. As cognitive psychologists they began to compare their cognitive models of

decision making under risk and uncertainty to economic models of rational behavior. In mathematical

psychology, there is a longstanding interest in the transitivity of preference and what kind of

measurement scale utility constitutes.

An important paper in the development of the behavioral economics and finance fields was written by

Kahneman and Tversky in 1979. This paper, 'Prospect theory: An Analysis of Decision Under Risk', used

cognitive psychological techniques to explain a number of documented divergences of economic decision

making from neo-classical theory (Kahneman, 2003). However, 'Theory of Crime' written by Nobel

Laureate Gary Becker in 1967 was a seminal work that factored in psychological elements into economic

decision making; Becker, however, insisted on maintaining strict consistency of preferences. In tracing

the history of behavioral economics, reference should be made to the theory of Bounded Rationality by

Nobel Laureate Herbert Simon who explained how people irrationally tend to be satisfied, instead of

maximizing utility, as generally assumed. Other prominent forerunners of modern behavioral economics

include Maurice Allais, whose "Allais Paradox" represented a crucial early challenge to expected utility.

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Over time many other psychological effects have been incorporated into behavioral economics, such as

overconfidence, projection bias, and the effects of limited attention. We come now to what is probably the

mainstream of the newer work in bounded rationality, namely, the theoretical work that has been done

since the mid-eighties on automata and Turing machines playing repeated games. The work was

pioneered by A. Neyman(1985)and A. Rubinstein(1986), working independently and in very different

directions. Subsequently, the theme was taken up by many others, each of whom made significant new

contributions to the subject in various different directions. Different branches of this work have been

started by Lewis(1985)and Binmore(1987), (1988), who have also had their following. There is also

significant touch on the more recent work in this area, which has been very active lately.

Although the list is astronomical, what we, ourselves, tried to accomplish is to incorporate the flaws of

"trivial" modes of rationality and to piece-by-piece analyze its underlying philosophy. We state the

problems which constitutes the biases of human decisions and proposes new directions which not only

takes bounded rationality but also norms, beliefs and especially noisy variables like response time into

account. Though, as students, we are not able to provide a formal or mathematical model yet, we strongly

believe that the questions posed by our analysis can produce extremely meaningful application if

earnestly referred to further development.

4. Theoretical Background:

Our research constitutes of the experimentations of the following standard and well-known theories and

models:

From Game Theory:

1. The Travelers Dilemma

2. The Ultimatum Game (The Proposer version and the Responder Version)

3. The Centipede Game

4. The Bargaining Problem

From Preference and Choice Theory:

1. The Secretary Problem

2. The Hyperbolic Discounting Theory

3. The Expected Utility Theory

4. Decision and Judgment Under Uncertainty

5. Decision and Judgment Under Risk

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6. Risk-Aversion and Gain-Loving

7. Prospect Theory

8. The Wedding Ring Problem

9. The Allias Paradox

We don't present the formal treatments of the above theories and models rather we look forward to judge

their rationalizability, validity, nature and practicability in terms of indirect experiments

5. Econometric Specification:

Our research doesn't resort to any causal relationship so we specify no econometric variables. But to

judge the significance of our gathered data, we conduct the Wilcoxon Two-Sample Test and compute the

p-values of our experiments (see Appendix). We find our data to be sound and statistically significant.

6. Methodology:

6.1 Methodology of the Study:

The correspondence of the experiments was performed totally via e-mail as we approached to record such

noisy variables as rate of exposition, response time etc. Furthermore, to understand about the noise of our

experimental procedure some experiments was also conducted directly as a safety measure which is not

included into the defined population but rather to test the soundness and trustworthiness of our e-mail

approaches.

The experiment consisted of answering to various questions requiring both MCQs(Multiple Choice

Questions) and single-phrase/number written answers.

6.2 Description of Data:

We conducted the research with purely primary data. The population consisted of total 200 students from

various departments of the University of Dhaka.

We diversified the departments to get the variances efface within the variations and to homogenize the

answers. Furthermore, we concentrated the survey among the departments to possibly get the most

educated answers.

All the students are sophomores (2nd year students) or juniors (3rd year students) holding CGPAs from

3.25(lowest) to 4(highest)

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The students were asked to respond successively to 17 questions. They were told that some beautiful

wallpapers would be randomly awarded to each of six students who completed the questionnaire,

irrespective of what answers they gave. They were explicitly told that the questionnaire was not an exam

and that there were no

"right" answers.

Number of Departments: 20

Number of Students from Each Department: 10

Total Number of Subjects: 200

The Departments from where the subjects were chosen:

From Natural Science and Engineering Background:

1. Department of Pharmacy

2. Department of Applied Physics, Electronics and Telecommunication Engineering

3. Department of Computer Science

From Social Science and Arts Background:

4. Department of Economics

5. Department of Law

6. Department of English

From Business and Management Background:

7. Department of Finance

8. Department of Accounting Information Systems

9. Department of Marketing

10. Institute of Business Administration

7. Analysis of the Study:

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The Problem of Reference:

The ultimate goal of economics is to gain and ensure human welfare. But what is "fairness" actually?

When we say the value of pi is 3.1416 we do never say "it sounds unfair to me" but what about the

employers and the employees fighting in a never-ending combat for "fair wage" and "fair service"? What

is our ultimate reference point to which we measure our scale of fairness? We consider the following

experiments:

Experiment 1

Firstly, we consider the following experiment. We asked the subject to answer the following question:

Imagine that you have been given Tk. 1000 to "DIVIDE" it between TWO unknown candidates. Which of

the following method of division SEEMS TO YOU to be the "FAIREST" i.e. the most EQUITABLE?

(A) To give them Tk. 500 EACH

(B) To let them FREELY BARGAIN their share and to let them distribute it THEMSELVES

(C) To give them judging by their relative NEED

(D) To give them a FIXED portion INITIALLY (e.g. Tk. 100 each) and then to let them FREELY

BARGAIN over their share for the money LEFT (i.e. Tk. 900)

Which option would you choose?

Any economist can state it from the first look as it to be a two-person bargaining problem faced by a

mediator. If we analyze that

Option (A) provides the egalitarian solution

Option (B) provides the utilitarian solution

Option (C) provides the Kalai-Smorodinsky solution

Option (D) provides the Nash solution

The first two options are flawed from the "theoretical" view. The Kalai-Smorodinsky solution suffers

from the not meeting the "Independence from Irrelevant Alternatives" axiom. Furthermore, it can impose

a cost of considerable amount to "judge" peoples real "needs" that is triggered by not being IIR axiom.

Hence, the Nash bargaining solution is the only type of bargaining solution which is simultaneously

egalitarian, utilitarian and impendent of irrelevant alternatives. So, if people judge "fairness" or "justice"

according to the theory, most of the subject should make an unambiguous choice of option (D)

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Results:

The response of the subjects was as follows:

Option Population % Median Response Time

A 52% 17sec

B 9% 22sec

C 36% 35sec

D 3% 102sec

Explanations and Insights:

Evidently, there is an enormous deviation from the theoretical solution and actual perception of fairness.

That is, people may not perceive fairness by just by a theoretical calculation devoid of any kind of value

judgment. Here, also, the most educated answers take the maximum amount of response time where the

near-optimal solution takes the second-highest time. Option (A) and option (B) can be rationalized as

outcomes of random guessing taking the least track of time to be responded.

Judging by the response time we state that in general, we conclude that people are biased to be perceived

by others as just and compassionate. Likewise, here, the egalitarian and the Kalai-Smorodinsky can be

represented to be "just" and "compassionate" solutions respectively. By the response and response time

the ideal solution i.e. the Nash solution is simply the loner. This also supports some of our previous

evidence that people do not indulge into complex line of thought or calculation is there is a "bypass" way

which doesn't detect any forgeries.

Experiment 2

The subjects were asked to respond to the following problem:

Imagine that there are two payment schemes:

(A) A GAMBLE that offers 10% chance to WIN Tk. 950 and 90% chance to LOSE 50

(B) B LOTTERY that costs Tk. 50 to participate which offers 10% chance to WIN Tk. 1000 and 90%

chance to WIN nothing

Which scheme would you choose?

Here, both the options provide the same monetary outcome. If we calculate, these yields:

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(A) (0.1950) - (0.950) = 50

(B) -50+ (0.11000) + (0.90) = 50

If individuals are rational then there should be similar distribution of preferences over two same chances

of outcome. That is options (A) and (B) should represent a near-equal choice

Results:

The response was as follows

Option Population %

A 21

B 79

It states 79% i.e. majority of the population chose to enter a lottery rather "indulging" into a gamble.

Explanation and Insights:

The outcome of the experiment is difficult to be explained in economic terms rather it can be reasoned in

normative views. There are strong social traits against gambling as a "great evil" as it depicts games of

blind chance. But the same norms may permit lotteries which "doesn't look bad" by the members of the

economic agents. By the experiment, we claim that, people respond to problems with their previous

status-quo bias which affect their preference.

The Problem of Responding to Experimental Evidence:

The connection between the models in economic theory and reality is tricky. I do not think that many of

us take our models seriously enough to view them as platforms for producing accurate predictions in the

same way that models in the sciences are viewed. When comparing a model to real data, we hope at best

to find some evidence that something in reality is close to the models prediction. Experiments are used

to verify assumptions and conclusions. Should we change a model if one of its assumptions is

experimentally refuted? We consider the following experiments:

Experiment 3(A)


Imagine that you have to choose between the following options

(A) receiving Tk. 540 at 17th June, 2014

(B) receiving Tk. 690 at 17th June, 2015

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Results:

The subjects responded as follows:

Option Population %A 45

B 55

According to the standard utility theory, individuals should choose the outcome which is supposedly give

them higher return in between the time lag. So most of the subjects should choose (B)

Experiment 3(B)

The subjects were also asked to respond to the following problem:

Imagine that you have to choose between the following options:

(A) receiving Tk. 542 at 16th October , 2012

(B) receiving Tk. 543.89 at 17th October, 2012


Results:

The subjects responded as follows

Option Population %A 53

B 47

Here, the numerical data clearly violates the standard utility theory as most of the people prefer (A)


The response of the 1st problem abides by the trivial theory but the Problem 2 contradicts. This may be

realized as in the Problem 1 there is significantly higher monetary return but in the Problem 2 the increase

is too small to be taken notice of. In fact, the results demonstrate a tendency among the subjects to

consider Tk. 1.89 to be sufficiently meaningless to consider even a one-day delay. The two amounts in

the 2nd problem i.e. Tk. 542 and Tk. 543.89 are so similar that it is justifiable to hurry the receipt even a

day earlier. Whereas in the Problem 1, the trade-off between "amount" and "delay" is stronger

The Problem of Meaningless Conclusions and Propositions:

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Formal models have a number of functions. Sometimes they are simply used as a tool to paint a clear

picture of what we wish to express. As economic theorists, we use formal models to produce conclusions.

Should we be as concerned with an absurd conclusion reached from sound assumptions as we would be

by a contradiction in a mathematical model? Does an absurd conclusion require us to abandon an

economic model? We consider the following experiments:

Experiment 4

Subjects were requested to respond to the following problems

I

Imagine you have to choose one of the following two lotteries:

(A) Lottery A yields Tk.4,000 with probability 0.2 and Tk.0 with probability 0.8.

(B) Lottery B yields Tk.3,000 with probability 0.25 and Tk.0 with probability 0.75.

Which lottery would you choose?

II

Imagine you have to choose one of the following two lotteries:

(C) Lottery C yields Tk.4,000 with probability 0.8 and Tk.0 with probability 0.2.

(D) Lottery D yields Tk.3,000 with probability 1.

Which lottery would you choose?

The presented problem is a variant of the famous Allais Paradox concerning probabilistic choice. The

solution is a simple expected value calculation.

I

A =0.2[4000] + 0.8[0] = 800

B = 0.25[3000] + 0.75[0] = 750

II

C = 0.8[4000] + 0.2[0] = 3200

D = [3000] 74% 20 sec = 3000

So, in problem I majority should choose (A) and in Problem II majority should also choose (A) for

higher probabilistic value.

Results:

The responses were as follows

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Option Population % Median Response Time

A 62% 50sec

B 38% 36sec

C 26% 32sec

D 74% 20sec


The choice of lottery A clearly requires more time than the choice of B as does the choice of C relative to

D. The fact that the RTs of C and D are lower than those of A and B must be an outcome of the fact that

Problem II was presented after Problem I so that the subjects were already familiar with the problem. In

Problem II, the sure prize of 3000 seems to be the instinctive response while the choice of the risky

lottery 0.8[4000]+ 0.8[0] requires calculation and deliberation. Thus, the distinction between instinctive

and cognitive choices can explain the large differences in RT between the two choices. In Problem I, the

choice of 0.2[4000] + 0.2[0] is usually explained either by the comparison of the expectations or by the

procedure described in Rubinstein (1988) in which the decision maker finds the probabilities to be

similar and makes the choice according to the decisive difference in the size of the prizes. The choice of

0.25[3000]+ 0.75[0] is more difficult to interpret. The differences in response time seem to indicate that

the choice of 0.25[3000]+ 0.75[0] was for many an outcome of reasonless choice.

The Problem of Modeless Regularities and Model-Inside Irregularities:

Models in economic theory are also used to suggest regularities in human behavior and interaction. By

regularities we mean phenomena that appear repeatedly in similar environments at different points in time

and at different locations. We have the impression that as economic theorists, we hope that regularities

will miraculously emerge from the formulas we write leisurely at our desks. Applied economists often

feel the need for a model before they mine data for a pattern or regularity. Do we really need economic

theory to find these regularities? Would it not be better to go in the opposite direction by observing the

real world, whether through empirical or experimental data, to find unexpected regularities? We consider

the following experiments:

Experiment 5


Imagine YOU are one of the players in the following TWO-player game:

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EACH of the players CHOOSES an amount BETWEEN Tk.180 and Tk. 300.

BOTH players are paid the LOWER of the two chosen amounts.

Tk. 5 is transferred from the player who chose the LARGER amount to the player who chose the

SMALLER one.

In the case that both players choose the SAME amount, they BOTH receive that amount and NO transfer

is made.

What is your choice?

In the standard literature of game theory, the game above is known as the "Travelers Dilemma". This is a

beautiful example of a Static Prisoners Dilemma with complete information. Assuming that the players

care only about their final monetary payoff, the only equilibrium strategy in this game is Tk. 180.

Results:

The subjects responded as percentage of population as follows:

Amount Population % Median Response Time

180 13% 99sec

181-294 14% 79sec

295-299 17% 118sec

300 55% 280ec


Strikingly, the response time for the range 295299 is the longest while the response times for 300 and

the range 181294 were the shortest. The response 300 seems to be the instinctive action while the

choices involving more cognitive reasoning are in the range 295299 (following an argument of the type

'he will choose 300 and therefore I will choose 299' or 'he will choose 299 and therefore I will choose

298' etc.). The answers 181294 appear to be arbitrary and are probably the result of a random 'pick a

number' algorithm. The classification of the Nash equilibrium action, i.e. 180, is more difficult. For some

it might have been the outcome of a non-trivial reasoning process while for others it might have been the

result of prior knowledge of the game. The Nash equilibrium response of 180, lies between the cognitive

response and the instinctive response.

The Problem of Validity:

Will it be possible for us to have a trend of "principles" which will be able to overtake and assimilate all

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"patterns"? We consider the following experiments:

Experiment 6

Now we move on to our next experiment. The subjects were faced with the following problem:

YOU are playing the following game WITH an anonymous person. EACH of the players has an account

with an INITIAL BALANCE of Tk.0. At EACH stage, ONE of the players (in alternating order YOU

start) has the right to STOP the game.

If it is YOUR turn to STOP the game and YOU CHOOSE NOT to, YOUR account is DEBITED by Tk. 1

and your opponents is CREDITED by Tk. 3

EACH time your opponent has the opportunity to STOP the game and chooses NOT to, YOUR account is

CREDITED by Tk.3 and his is DEBITED by Tk. 1

If BOTH players choose NOT to stop the game for 100 turns, the game ENDS and EACH player

RECEIVES the balance in his account (WHICH is let Tk. 200).

At WHICH turn (BETWEEN 1 and 100) do YOU plan to STOP the game? (If you plan NOT to stop the

game at ANY point write 101)

What is your choice?

This game is known as the Centipede game by the standard game theoretic jargon. The Centipede Game

is another prime example of the tension between Nash equilibrium and the way in which games are

actually played. Assuming that the players care only about the amount in their own account, the only

Nash equilibrium strategy for player 1 is to stop the game at turn 1. However, this is a highly unintuitive

action. The response 101 seems to be the instinctive one. The cognitive actions are in the upper range of

the responses (98, 99, 100). A choice in the range 297 seems to be a reasonless one.

Results:

The subjects responded as follows:

Number Population % Median Response Time

1 12% 132 sec

2-97 11% 80sec

98-100 20% 189sec

101 57% 123sec

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The Centipede game also affirms the same nature of response with the Travelers dilemma. Here, also the

equilibrium of number 1 gets the 2nd lowest of population and takes the 2nd maximum response time to

be answered. Whereas, the instinctive choice 101 has the maximum share of population and the results of

random choice has taken the lowest median response time to be answered.

Insights:

Thus we see though Centipede game seems more of a complex nature; as far as it presents a same

strategic decision environment like the Traveler's Dilemma, the equilibrium result can be rationalized

distinctively by the response times.

Experiment 7:

Now we move on to our next experiment. The subjects were asked to respond to the following situation

Imagine that YOU are on a social networking website say FACEBOOK. Once you notice that:

There are 120 friendship requests for the position

The "want-to-be friends" can be RANKED from BEST to WORST with NO ties.

The "want-to-be friends" are FACED one-after-one in a RANDOM order, with each order being

EQUALLY LIKELY

You can ACCEPT or REJECT a "want-to-be friend" only ONCE but you CAN'T delay or "keep the

request aside"

Rejected "want-to-be friends" CANNOT be recalled.

The objective is to select the BEST "want-to-be-friends".

Your acceptance of friendship will AFFECT you in a sense that if you add people from the best group

they can be extremely GOOD friends but if you add from the worst group they can be extremely BAD

How many friends will you add in such a case?

This is a changed version of the celebrated "secretary problem" intensively studied in advanced industrial

organizations and also in operations research. The solution refers to solve a simple maximization problem

which is just a routine work if the variables and constraints can be identified properly. The answer is

unambiguously 44 i.e. the optimal number of friends that should be added is 44. It should be taken into

account that it was not our motive to check the mathematical abilities of our subjects but the aim was to

observe their judgment under "problems" that seems complex to them.

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Results:

The responses were as follows

Number of Friends Chosen to be Added Population %

0-10 32%

11-50 6%

51-60 58%

61-100 3%

101-120 1%


If the subjects (except the students from Law and English as they are not supposed to) used their

computational ability there should have been a regularity around the 40 range. But noticeably, the

maximum population gathers around the 51-60 limit with the second majority choosing 0-10 i.e. almost

no friends to add.

For the subject who chose at an "average" 51-60 range we think that if a person is subjected to immense

complexity but in a mild sense(which can affect them in an objective sense or indirectly), they tend to

refer to an "average" solution which will neither do good or bad to them in a direct sense. For the second

highest chosen range 0-10, we think that they constitute the people who are more loss-averse than they

are gain-lovers. In can also be explained as an instinctive choice resulting from "always be at safe-side"

reasoning.

The problem of the notions of rationality:

How do we behave in our "real" lives: like a Homo sapiens or a like a Homo economicus? We consider

the following experiments:

Experiment 8:

Now the subjects are requested to respond to the following notion of problem

Imagine that you are a princess. 5 princes of EQUAL age who are IDENTICALLY honest and handsome

have proposed to marry you. But you have decided that you will marry the BRAVEST prince among the

5. Their combat history is as follows:

(A) the 1st prince has taken part in 10 combats with 0.75 winning probability

(B) the 2nd prince has taken part in 20 combats with 0.33 winning probability

(C) the 3rd prince has taken part in 30 combats with 0.67 winning probability

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(D) the 4th prince has taken part in 40 combats with 0.25 winning probability

(E) the 5th prince has taken part in 50 combats with 0.41 winning probability

Which prince would you like to accept?

This is a famous version of the Wedding Ring Paradox. The problem assigns differently probabilities to

different set of histories to different alternatives. As the problem clearly refers the bravest prince so after

expected number of victories is the only factor that should affect outcome. If we calculate the expected

values of the number of victories of the above 5 princes, we get

Expected Values of Victory=Number of Combat*Winning Probability

1st prince= 100.75= 7.5

2nd prince= 200.33= 6.6

3rd prince= 300.67= 20.1

4th prince= 400.25= 10

5th prince= 500.41= 20.5

As the 5th prince has the highest expected value of victory and as he has taken part in the maximum

number of combats, a rational princess should choose the 5th prince without any doubt.

Results:

The nature of response from the subjects is as follows

Number Population %

1st prince 4%

2nd prince 1%

3rd prince 72%

4th prince 7%

5th prince 16%


From the data, we clearly observe that there is a tremendous majority in choosing the 3rd prince who is

the 2nd bravest. It can be rationalized that may be the subjects, at a first glance, looked to the higher

winning probability of the 3rd prince with a larger eye while ignoring the higher number of combats that

the 5th prince attended to. That is to say, most of the subjects had a tendency to give large weight to a

vivid observation whether its actual value is small or large.

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Experiment 9(A)

Now we analyze our next experiment where subjects were asked to respond to the following problem:

Imagine you have FINISHED a job and have to CHOOSE between two payment schemes:

(A) Receiving Tk.1000 in 8 months.

(B) Receiving Tk. 500 in 6 months and Tk. 500 in 10 months.


Receiving Tk. 1000 in 8 months is not much different from receiving Tk. 500 at 8 and Tk. 500 at 8+.

Thus, a reasonable application of the (hyperbolic) discounting approach in this case would imply that

advancing the receipt of Tk. 500 from t = 8 to t = 6 has more weight than postponing the receipt of Tk.

500 from

t = 8 to t = 10. Therefore, we would expect the vast majority of people to choose B.

Results:

The response asserts

Option Population %

A 54%

B 46%

However, 54% of the 354 participants in this experiment chose A and rest of the subjects that is 46%

chose B

Experiment 9(B)

Also we asked the subject to respond to the following problem in a recursive manner. Evidently,

Imagine you have bought a computer and have to choose between

two payment schemes:

(A) Paying Tk.1,000 in 8 months.

(B) Paying Tk.500 in 6 months and Tk.500 in 10 months.


Results:

The experiments yield the following numerical evidence

Option Population %

A 39%

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B 69%

While 54% of the subjects chose one installment when they had to choose between payments schemes for

earnings in Problem 1, only 39% of the 382 participants chose one installment in Problem 2, when they

had to choose between payment schemes for losses.


We believe that the phenomenon we see here is somewhat related to risk aversion: Given two alternatives,

there is a strong tendency to choose the one perceived as the average. In the context of decision making

under uncertainty, people tend to prefer the certain expectation of a lottery over the lottery itself. In the

context of streams of money, the averaging might be done on the time component. This consideration

leads an individual to prefer one installment. Apparently, for a majority of subjects the preference for the

average is stronger than the consideration underlying hyperbolic discounting (advancing the receipt ofTk.500 by two periods is a more significant than the loss from postponing the receipt of the same amount

for two periods) which, of course, we do not deny exists.

Experiment 10(A)

Now we tackle the following experiment where we asked the subject for their response to th following

problem:

Imagine that YOU and a person you do NOT know are to share Tk.100. YOU must make an offer as tohow to SPLIT the Tk.100 between the two of you and he MUST either ACCEPT or REJECT your offer.

In the case that he REJECTS the offer, NEITHER of you will get anything.

What is your offer?

In game theoretic literature, the above strategic situation can be referred as an "Proposer version"

Ultimatum Game. It is customary to assume that each player is only interested in attaining as much

money as possible. Applying the Sub-game Perfect Equilibrium concept, game theory "predicts" that the

proposer will offer either Tk.1 or nothing to the responder who will accept the offer. Of course, this is

unrealistic. In real life, the proposer often cares about the amount of money he offers to the other player,

perhaps due to feelings of guilt for exploiting his preferred status or perhaps out of fear that the responder

might be insulted by too low an offer and prefer to get nothing rather than agreeing to an "insultingly low

offer"

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Results:

The subjects responded as follows

Amount Population % Median Response Time

0-1 15% 55sec

2-25 9% 56sec

26-49 11% 52sec

50 47% 43sec

51-60 11% 55sec

61-100 7% 46sec


The distribution of responses across audiences was quite uniform. The results for subjects in this case,

distinguishing between the different actions is not straightforward. In particular, it is unclear whether the

instinctive action in this case is the 50:50 split or the one in which the proposer demands almost the entire

sum. We can look to response time for further clues. The MRT of those who offered less than Tk.50 was

25% higher than of those who offered an equal split, thus supporting the hypothesis that the equal split is

the instinctive action for many of the subjects.

There is a group of significant size within the audiences who offered the other player more than Tk.50.

The low MRT of those who offered 61 or more supports

the view that these choices were the outcome of a misunderstanding of the question. However, the MRT

of responses in the range 5160 (55 seconds) was even higher than that of responses in the range 4049

(51 seconds) and thus it is not clear whether these responses were intentional or an outcome of error.

Experiment 10(B)

Also, we presented to them the "Responder version" Ultimatum game; which is as follows:

Imagine that, YOU and someone you do NOT know are to share Tk.100. HE makes YOU an offer and

you can either ACCEPT it or REJECT it. If you REJECT it, NEITHER of you will get ANYTHING. He

offers you Tk.10 (if you ACCEPT, he will GET Tk.90).

Do you accept the offer?

Results

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The response was as follows:

Choice Population%

Yes 63%

No 37%


A surprisingly high proportion of subjects, 63%, "accepted" the offer. Remarkably, 95% of those who

offered 010 in the previous question accepted the Tk.10 as opposed to only 53% of those who offered an

equal split. Is there a difference in response time between those who accepted and those who rejected the

Tk.10? Remarkably, not only was the median of the two groups identical but, the RT distributions of

those who accepted and those who rejected the offer were almost identical. One would expect that the

response time of those who accepted the low offer would therefore be higher; however, the distributions

of those who accepted and those who rejected the offer are amazingly similar.

Experiment 11(A)


Imagine that Bangladesh is preparing for the outbreak of an unusual disease; which is expected to KILL

600 people. Two alternative programs to combat the disease have been proposed. Also assume that the

exact scientific consequences of the two programs are as follows:

(A) If Program A is adopted 200 people will be SAVED

(B) If Program B is adopted there is 1/3 rd probability that 600 people will be SAVED and 2/3 rd

probability that NO people will be SAVED

Which program would you choose?

Results:

The results were as follows:

Options Population%

A 72%

B 28%

Experiment 11(B)

The subjects were also asked to respond to the following problem:

If suppose two other Programs C and D are proposed such as:

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(C) If program C is adopted 400 people will DIE

(D) If Program D is adopted there is 1/3 rd probability that NOBODY will be DIE and 2/3 rd probability

that 600 people will DIE

Which program would you choose now?

Results:

The results were as follows

Options Population%

A 21%

B 79%


The formulation of problem I implicitly adopts as reference point a state of affairs in which the disease is

allowed to take its toll of 600 lives. The outcomes of the programs include the reference state and two

possible gains measured by the number of lives saved. As expected, preference are loss-averse: A clear

majority of respondents prefer saving 200 lives for sure over a gamble of that offers a one-third chance of

saving 600 lives

The second problem posed is virtually identical but varies in formulation. But the answer can be

interpreted as consistent with the above solutions presented.

Experiment 12(A)

The individuals were asked to respond to the following:

Imagine that you face the following tour schemes:

A: 50% chance to WIN a three-week tour of Cox's Bazar, Chittagong and Rangamati

B: A one-week tour of Cox's Bazar with CERTAINTY


Results:

The subjected provided the following outcomes:

Options Population%

A 24%

B 76%

Experiment 12(B)

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We formulated another version of the problem and presented to the audience; which was as follows:

Imagine that you face the following tour schemes


B: 10% chance to WIN A one-week tour of Cox's Bazar

Which scheme would you choose?(Please put a tick-mark on)---(A)---(B)

Results:

The subject responded as follows:

Options Population%

A 67%

B 33%


The numerical evidence shows a clear support toward an outcome which is certain rather than a risky

outcome which may be "alluring". As axiomatized by the standard utility theory, subjects put the majority

for option (B)

For problem 2, there exists clear majority for (A) which exhibits violation of the expected utility theory as

most of the subjects have respondent to the most risky outcome. But, the result can be rationalized in

terms of degree of uncertainty. As subjects notice that in problem 2, (B) provides an improvement of

chance only by 5% so they ignore this improvement and homogenize the risk for a greater outcome

8. Recommendations and Conclusions

8.1 Shortcomings of the Study:

(a) The method of data collection:

The data are a bit noisy and are blurred by the behavior of subjects who "choose" without serious

deliberation. There are also differences in server speed. Furthermore, subjects differ in how fast they read

and think. Indeed, this is the reason we do not advise conducting this kind of research using a sample of

less than several thousand. Here, the magic of a large sample gives us a clear picture of the relative time

responses. A standard criticism of survey experiments is that in the absence of monetary rewards behavior

is less realistic. However our experiment was conducted into our own acquainted groups. May be that

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have lessened some absence of deliberation in exchange of friendship. In any case, we are not interested

here in the absolute distribution of responses in real life problems (and note that even with real payments

the experiment is still far from a real life situation), but only in the relative response times of the different

choices. Thus, the absence of real rewards should not have any significant impact.

(b) Statistical tests

We believe that the results presented here are sufficiently persuasive that the performance of statistical

tests would not have any value beyond paying taxes to the orthodoxy. It is true that for certain problems

(not presented here) in which the results exhibited only slight differences in response time, statistical tests

are needed. However, we doubt that the results of such tests would be of much interest unless the

differences were large enough to make the tests redundant in any case. With that said, we yielded to the

pressure of readers of earlier drafts and conducted the standard Wilcoxon Two-Sample Test.

(c) The distinction between intuitive and cognitive choices

As mentioned earlier, the classification of choices was done intuitively. An alternative and more formal

approach would be to base classification on other sources of information such as the results of a survey in

which subjects were asked whether they consider a choice to be instinctive or not. Of course, such an

approach would have its own deficiencies. In any case, the distinction between intuitive and cognitive

responses was used here only as a suggestive explanation for the huge differences in time response

between actions. Overall, we believe that the methodology used in this article is a cheap and incisive tool

for understanding the process of reasoning involved in classical economic decision problems.

Furthermore, the results appear to be more clear-cut and less speculative than those obtained by

somewhat more "Formal (mathematical)" or on the other extreme more "Informal (behavioral)" studies.

8.1.2 Directions for Future Research:

Should We Continue to Ignore Psychological Research?

Economists have (until very recently) been fundamentally dismissive of laboratory evidence. A major

complaint has been that the stakes involved are generally too small to be used for predicting real-world

behavior; indeed, some psychological research consists of hypothetical choices in which subjects report

what they woulddo in particular situations, or of questionnaires where subjects are asked to give answers

without being provided with extrinsic incentives for correct answers. The stakes debate has, if anything,

been exacerbated by the advent of experimental economics, which has at times deemed the use of

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financial incentives a methodological imperative. The view that responses elicited from subjects will be

informative only if substantial financial stakes are involved is an empirical hypothesis. It is also a testable

hypothesis. And it is, by and large, a false hypothesis. By far the most comprehensive and integrated

review of psychological and economic experimental evidence on individual decision-making, finds some

instances where financial-stakes replications of psychological experiments have reversed the inferences

about theory drawn from those experiments. While there are some areas (e.g., departures from self

interest) where answers to hypothetical questions are likely to be misleading, our goal should be to

develop a psychologically sophisticated sense ofwhen facts about people can be accurately elicited in

low-stakes contexts, rather than putting forth a methodological proclamation that such elicitation

procedures are inadequate. As the list of examples (preference reversals, ultimatum-game sharing)

lengthens where psychological findings are robust to the scale of financial stakes, perhaps we can

converge to the point where in certain domains we accept the presumptive validity of low-stakes or

hypothetical-question evidence.

How can we use Psychological Findings:

Psychologists, and now experimental economists, often contend that controlled laboratory

experimentation is a more valid source of insights into human behavior than uncontrolled field studies.

Conversely, economists have traditionally contended that field evidence provides more insight than

laboratory evidence. Many of the tensions between the disciplines seem to come from these faiths in

different modes of empirical research. In some domains (e.g., departures from self interest) we must find

ways to test experimentally-generated hypotheses outside the laboratory. Indeed, the scale of monetary

and other stakes and the degree of experience involved in some economic situations cannot possibly be

replicated in the laboratory. Perhaps one of the most fruitful avenues for productive behavioral research is

for researchers to use the laboratory to generate hypotheses, and then to use field evidence to test these

hypotheses. For instance, many researchers, backed both by general analysis and specific laboratory

studies, have argued that fairness, equity, and related considerations are important for labor economics in

general, and unemployment in particular. Theories of unemployment cannot be adequately tested directly

in the laboratory. But armed with experimental evidence about what motivates people, economists can

test in the field the theories of unemployment implied by these motivations.

8.2 Recommendations:

Considering all the gist of the above experiments, we generalize the cognitive features and heuristic

biases of the subjects of our study can be broadly classified as follows:

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Exposition to Complexity:

If complexity arises people tend to give an average solution to the posed problem. On the other hand is

too much simplicity arises, most of the people tackle the problem with "extremal" answers

Loss-Aversion:

In general, people are more loss-averse than they are gain-lovers.

Incorrect Segregation and Aggregation:

People often wrongly perceive two similar outcomes as dissimilar and two dissimilar outcomes to be

similar.

Insensitivity to Final Outcome:

People tend to be more sensitive to momentary outcomes and ignore final outcomes

Offsetting Minor Improvement:

People have a marginal rate or threshold limit of sense to distinct the initial state and the changed state

Insensitivity to Sample Size:

People may be not serious about the total counterparts of a strategic action

Misconceptions of Chance:

People expect that a sequence of events generated by a random process will represent the essential

characteristics of that process even when the sequence is short.

The Illusion of Validity

As we have seen, people often predict by selecting the outcome (e.g., an occupation) that is most

representative of the input (e.g., the description of a person).

Biases Due to the Retrievability of Instances

When the frequency of a class is judged by the availability of its instances, a class whose instances are

easily retrieved will appear more numerous than a class of equal frequency whose instances are less

retrievable.

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Adjustment and Anchoring

In many situations, people make estimates by starting from an initial value which is adjusted to yield the

final answer.

Status Quo Bias:

People are biased by the characteristics of present state i.e. status quo. This may be referred as bias to

custom, culture, experience etc.

Prospect Bias:

People don't answer problems by their expositions but by their prospects that is how the problem is

presented by them

Representative Bias:

People judge different answers by matching by the representations triggered by their own minds. As

example; if it is said that someone is a doctor who drives a car, goes to shops and lives alone; we tend

conjure up a mental picture that the person should be a male.

Observation Bias:

People give more weight to a small number of vivid observations

Action-based Nature of Choice:

We classify choices as following

(1) Cognitive: an action which involves a reasoning process,

(2) Instinctive: an action which involves instinct, or driven by "animal spirit"

(3) Reasonless: an action which is likely to be the outcome of a random process with little or no reasoning

about the decision problem.

It is our claim from the evidence that choices which require more cognitive activity will result in longer

response times than choices which involve an instinctive response.

8.3 Conclusions:

In our study, we simply tried to explore the frontiers of economics and psychology. Our analysis is not to

provide an acid test which acts by proving or disproving or providing evidence or counterexamples rather

we tried to get hold of the flaws that prevails in the paradigm of a "rational" economic person. As students

of economics, we think that we must be aware of what are we studying economics for? What are

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economists trying to accomplish really? These are the only two questions that precipitated of the

outcome of this paper. Finally, we tackle the riddles that we put forward as our benchmarks

The problem of the notions of rationality: We pretend to be like Homo economicus but we are really

Homo sapiens.

The problem of meaningless conclusions and propositions: We should judge facts according to their

underlying logic, not by its conclusion outside its context or scope.

The problem of validity: For extremal situations we can find "principles" but for average cases we have

to be satisfied with "patterns".

The problem of responding to experimental evidence: In macro level Yes but in micro level may be!

The problem of limitations: A good model or theory can have an enormous influence on the real world,

not by providing advice or by predicting the future, but rather by influencing culture that is accepted

norms of activity.

The problem of modeless regularities and model-outside irregularities: The model which is too

regular i.e. accurate is bound to be too complex and a model which is too simple is bound to be too

irregular.

The problem of reference: Honestly, we tried our best but simply, we don't dare to know!

REFERRENCE:

[ I ] ACZEL, J.:Lectures on Functional Equations and Their Applications.New York: Academic Press, 1966.

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1'Ecole Americaine,"Econometrica, 21 (1953), 503-546.

[3] ANDERSON,N. H., AND J. C. SHANTEAU: "Information Integration in Risky Decision Making," Journal of

Experimental Psychology, 84 (1970), 441-451.

[4] ARROW, K.J.: Essays in the Theory of Risk-Bearing. Chicago: Markham, 1971. [5] BARNES,J . D., AND J.

E. REINMUTH: "Comparing Imputed and Actual Utility Functions in aCompetitive Bidding Setting,"Decision

Sciences, 7 (1976), 801-812.

[6] COOMBS,C. H.: "Portfolio Theory and the Measurement of Risk," inHuman Judgment and Decision

Processes. ed. bv M. F. Kaolan and S. Schwartz. New York: Academic Press. 1975.pp. 63-85.

[7] DAVIDSON, D., P. SUPPES, AND S. SIEGEL:Decision-making: An Experimental Approach.

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Stanford: Stanford University Press, 1957.

[8] DEBREU,G .: "T~p~logicMale thods in Cardinal Utility Theory," Mathematical Methods in the Social Sciences,

ed. by K. J. Arrow, S. Karlin, and P. Suppes. Stanford: Stanford UniversityPress, 1960,pp. 16-26.

[9] EDWARDS, W.: "Subjective Probabilities Inferred from Decisions,"Psychological Review, 69 119621. 109-

135. ~ ~ ,- --,, [lo] ELLSBERGD, .: "Risk, Ambiguity and the Savage Axior~s,"Q uarterly Journal ofEconomics, 75

(1961), 643-669.

[ll]FELLNER, W.: "Distortion of Subjective Probabilities as a Reaction to Uncertainty," Quarterly Journal of

Economics, 75 (1961), 670-690.

[I21 -:probability and Profit-A Study of Economic Behavior Along Bayesian Lines. Homewood, Illinois: Richard D.

Irwin, 1965.

[13] FISHBURN, P. C.: "Mean-Risk Analysis with Risk Associated with Below-Target Returns,"American

Economic Revrew, 67 (19771, 116-126.

[I41 FISHBURN, P. C., AND G. A. KOCHENBERGER: "Two-Piece von Neumann-Morgenstern Utility

Functions," forthcoming.[15] FRIEDMAN, M., AND L. J. SAVAGE: "The Utility Analysisof Choices Involving Risks,"Journal of Political

Economy, 56 (1948), 279-304.

[I61 F u c ~ s ,V. R.: "From Bismark to Woodcock: The "Irrational" Pursuit of National Health Insurance,"Journal

of Law and Economics, 19 (1976), 347-359.

1171 GALANTER, E., AND P. PLINER: "Cross-Modality Matching of Money Against Other Continua," in

Sensation and Measurement, ed. by H. R. Moskowitz et al. Dordrecht, Holland: Reidel, 1974,pp. 65-76.

Appendix

1. Sample Questionnaire Used in All Experiments

Thank you very much for your valuable time and patience.

The following is a hypothetical questionnaire involving and targeting to pure academic research.

You are earnestly requested to answer it with your kind and attentive response.

Please note that your response will never be disclosed with your identity in any manner or any form whatsoever

and hence will only be accounted in terms of anonymous attributions with utmost security.

Please kindly state your

Name:

Department:

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Semester/Year:

Number of Mathematics/ Statistics/Business Math/Applied Mathematics/Related Courses You Attended till Now:

Your CGPA/Class/Grade till Now:

1. Imagine YOU are one of the players in the following TWO-player game:

EACH of the players CHOOSES an amount BETWEEN Tk.180 and Tk. 300.

BOTH players are paid the LOWER of the two chosen amounts.

Tk. 5 are transferred from the player who chose the LARGER amount to

the player who chose the SMALLER one.

In the case that both players choose the SAME amount, they BOTH receive that

amount and NO transfer is made.

What is your choice?(Please write the amount) Tk.-----------------

2. Imagine that YOU and a person you do NOT know how to share Tk.100. YOU must make an offer as to how toSPLIT the Tk.100 between the two of you and he MUST either ACCEPT or REJECT your offer. In the case that he

REJECTS the offer, neither of you will get anything.

What is your offer?

(Please write)I offer the following amount to the other person (if he agrees I will get the rest):---------------

3. Imagine you have FINISHED a job and have to CHOOSE between


(A) Receiving Tk.1,000 in 8 months.

(B) Receiving Tk. 500 in 6 months and Tk. 500 in 10 months.


4. Imagine that YOU are on a social networking website say FACEBOOK. Once you notice that

There are 120 friendship requests for the position

The "want-to-be friends" can be RANKED from BEST to WORST with NO ties.

The "want-to-be friends" are FACED one-after-one in a RANDOM order, with each order being EQUALLY

LIKELY

You can ACCEPT or REJECT a "want-to-be friend" only ONCE but you CAN'T delay or "keep the request aside"

Rejected "want-to-be friends" CANNOT be recalled.

The objective is to select the BEST "want-to-be-friends".

Your acceptance of friendship will AFFECT you in a sense that if you add people from the best group they can be

extremely GOOD friends but if you add from the worst group they can be extremely BAD

How many friends will you add as a safe an optimal strategy?(Please write)-------------

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5. Imagine that Bangladesh is preparing for the outbreak of an unusual disease; which is expected to KILL 600

people. Two alternative program to combat the disease has been proposed. Also assume that the exact scientific

consequences of the two programs are as follows

(A) If Program A is adopted 200 people will be SAVED

(B) If Program B is adopted there is 1/3 rd probability that 600 people will be SAVED and 2/3 rd probability that

NO people will be SAVED

Which program would you choose?(Please put a tick-mark on)---(A)---(B)

If suppose two other Programs C and D are proposed such as

(C) If program C is adopted 400 people will DIE

(D) If Program D is adopted there is 1/3 rd probability that NOBODY will be DIE and 2/3 rd probability that 600

people will DIE

Which program would you choose?(Please put a tick-mark on)---(C)---(D)

6. Imagine that there are two payment schemes

(A) a GAMBLE that offers 10% chance to WIN Tk. 950 and 90% chance to LOSE 50

(B) a LOTTERY that costs Tk. 50 to participate which offers 10% chance to WIN Tk. 1000 and 90% chance to WIN

nothing


7. Imagine that you have to choose between the following options

(A) receiving Tk. 540 at 17th June, 2014

(B) receiving Tk. 690 at 17th June, 2015


8. Imagine that you face the following tour schemes:


B: A one-week tour of Cox's Bazar with CERTAINTY


9. YOU are playing the following game WITH an anonymous person. EACH of the players has an account with an

INITIAL BALANCE of Tk.0. At EACH stage, ONE of the players (in alternating order YOU start) has the right

to STOP the game.

If it is YOUR turn to STOP the game and YOU CHOOSE NOT to, YOUR account is DEBITED by Tk. 1 and your

opponents is CREDITED by Tk. 3

EACH time your opponent has the opportunity to STOP the game and chooses NOT to, YOUR account

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is CREDITED by Tk.3 and his is DEBITED by Tk. 1

If BOTH players choose NOT to stop the game for 100 turns, the game ENDS and EACH player RECEIVES

the balance in his account (WHICH is let Tk. 200).

At WHICH turn (BETWEEN 1 and 100) do YOU plan to STOP the game? (If you plan NOT to stop the

game at ANY point write 101)

What is your choice?(Please write the point)-----------------

10. YOU and someone you do NOT know how to share Tk.100. HE makes YOU an offer and you can either

ACCEPT it or REJECT it. If you REJECT it, NEITHER of you will get ANYTHING. He offers you Tk.10 (if you

ACCEPT, he will GET Tk.90).

Do you accept the offer?(Please put a tick-mark on)---Yes---No

11. Imagine that you have to choose between the following options

(A) receiving Tk. 542 at 16th October , 2012(B) receiving Tk. 543.89 at 17th October, 2012


12. Imagine that you have been given Tk. 1000 to "DIVIDE" it between TWO unknown candidates. Which of the

following method of division SEEMS TO YOU to be the "FAIREST" i.e. the most EQUITABLE division?

(A) To give them Tk. 500 EACH

(B) To let them FREELY BARGAIN their share and to let them distribute it THEMSELVES

(C) To give them judging by their relative NEED

(D) To give them a FIXED portion INITIALLY(e.g. Tk. 100 each) and then to let them FREELY BARGAIN over

their share for the money LEFT(i.e. Tk. 900)

Which scheme would you choose?(Please put a tick-mark on)---(A)---(B)---(C)---(D)

13. Imagine you have BOUGHT a computer and have to CHOOSE between


(A) Paying Tk.1,000 in 8 months.

(B) Paying Tk. 500 in 6 months and Tk. 500 in 10 months.


14. Imagine that you are a princess. 5 princes of EQUAL age who are IDENTICALLY honest and handsome have

proposed to marry you. But you have decided that you will marry the BRAVEST prince among the 5. Their combat

history are as follows:

(A) the 1st prince has taken part in 10 combats with 0.75 winning probability

36


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(B) the 2nd prince has taken part in 20 combats with 0.33 winning probability

(C) the 3rd prince has taken part in 30 combats with 0.67 winning probability

(D) the 4th prince has taken part in 40 combats with 0.25 winning probability

(E) the 5th prince has taken part in 50 combats with 0.41 winning probability

Which prince would you like to accept?(Please put a tick-mark on)---(A)---(B)---(C)---(D)---(E)

15. Imagine that you face the following tour schemes


B: 10% chance to WIN A one-week tour of Cox's Bazar


16. Imagine you have to choose one of the following two lotteries:

(A) Lottery A yields Tk.4,000 with probability 0.2 and Tk.0 with probability 0.8.

(B) Lottery B yields Tk.3,000 with probability 0.25 and Tk.0 with probability 0.75.Which lottery would you choose?(Please put a tick-mark on)---(A)---(B)

17. Imagine you have to choose one of the following two lotteries:

(C) Lottery C yields Tk.4,000 with probability 0.8 and Tk.0 with probability 0.2.

(D) Lottery D yields Tk.3,000 with probability 1.

Which lottery would you choose?(Please put a tick-mark on)---(A)---(B)

Table for p-Values:

Experiment Pair P-value

The Travelers Dilemma 180-295,

296-300

Significant

The Ultimatum Game (The

Proposer version and the

Responder Version)

0-50,

51-100

510-7

The Centipede Game 0-99,

100-101

310-7

The Bargaining Problem A-B,

C-D

210-7

The Secretary Problem 0-50,

51-120

310-7

37


38/38

The Wedding Ring Problem A-B,

C-E

410-7

economics, psychology, and interactive decision making - will the reign of reason rule on?

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