Adonis Diaries

Posts Tagged ‘econometrics

 

Micro-economics freak, Freakonomics…: Who is Steven Levitt

Note: updated this review book of 2011

Seven  D. Levitt made himself famous by focusing on micro-economics phenomena that macro-economics scholars would not touch with a long pole.

The macro-economists theorize about mathematical monetary issues, but Levitt says: “I don’t pretend to know very much about the field of economics, I am poor in econometrics (mathematical set of equations with an objective equation and a set of constraint equations, like in operation research field), I don’t know how to do theory. It would be a total fake on my part if I claim that I know how the stock market moves, or if the economy is shrinking, or if deflation is bad or good…”

Levitt’s point of view is that economics is a science with excellent tools for gaining insights, but it lacks and is short on interesting questions to ponder upon.

Steven loves to ask freaky questions and get on with the task of torturing data-bases in order to discover trends and correlations among the various factors.

For example, you ask a question that interest you, and you discover the story behind the problem, such as:

1) Why most drug dealers still live with their mothers?

2) Which is more dangerous: Having a gun at home or a private swimming pool?

3) Why crime rate plunged dramatically in the last two decades and is still witnessing a steady decline, though population increased and the economy has its feet flailing up?

4) Why your real estate agent sells his own home at a higher price and stay longer on the market?

5) Does your stock broker has your best interest in mind?

6) Why black parents give their children names that they know may hurt their career prospects…?

7) Do school teacher cheat to meet high-stakes testing standards?

8) Why police departments distort crime data and eliminate cases from the records…?

Do you believe that the problems of this modern world are not impenetrable, and can be resolved, if the right questions are asked, and people are dedicated in uncovering the real story?

Are you curious in divulging the real stories behind cheating, corruption, and criminal behaviors and activities?

Levitt just loves to play the economist investigator to questions that are related to criminal behaviors.

Levitt drives an aging green Chevy Cavalier with a window that does not shut close, and the car produces a dull roar at highway speed. Levitt notices a homeless guy and says: “He had nice headphones, nicer than mines. Otherwise, it doesn’t look like he has many assets…”

Levitt had an interview for the Society of Fellows, a Harvard clubhouse that pays young scholars to do their own work, for three years, with no commitments attached. Levitt was on fire and his wit crackled. A scholar member asked Steven:

“Do you have a unifying theme of your work? I’m having hard time seeing one underlying theme…”

The scholars volunteered offering what they thought could be a unifying theme, and Steven found himself agreeing with every alternative theme.

Finally, philosopher Robert Nozick interrupted saying: “He is 26 year-old. Why does Steven need to have a unifying theme at such a young age? A talented person take a question and he’ll just answer it, and he’ll be fine.”  Steven was awarded the grant.

Steven Levitt has contributed in giving micro-economics and edge over macro-economics or “homo economics” and this behavioral perspective has called into doubt many claims of mankind rational decision-making tendencies.

Real world problems demand to get immersed into various fields of knowledge such as psychology, criminology, sociology, neurology… in order to overcome mathematical theoretical shortcoming.

At 36 of age, Levitt is a full professor at the Univ. of Chicago’s economics department, and received tenure two years after starting to teach. He is an editor of “The Journal of Political Economy

Note 1Stephen J. Dubner, co-author of “Freakonomics”, covered the biography of Steven D. Levitt in a special chapter called “Bonus matter”

Note 2:  I have published 5 posts on chapters of Freakonomics and you may have a head start with https://adonis49.wordpress.com/2011/10/26/how-to-convert-conventional-wisdoms-into-success-freakonomics-discoveries/

Micro-economics freak, Freakonomics…: Who is Steven Levitt

Seven  D. Levitt made himself famous by focusing on micro-economics phenomena that macro-economics scholars would not touch with a long pole.

The macro-economists theorize about mathematical monetary issues, but Levitt says: “I don’t pretend to know very much about the field of economics, I am poor in econometrics (mathematical set of equations with an objective equation and a set of constraint equations), I don’t know how to do theory. It would be a total fake on my part if I claim that I know how the stock market moves, or if the economy is shrinking, or if deflation is bad or good…”

Levitt’s point of view is that economics is a science with excellent tools for gaining insights, but it lacks  and is short on interesting questions to ponder upon.

Steven love to ask freaky questions and get on with the task of torturing data-bases in order to discovering trends and correlations among the various factors.

For example, you ask a question that interest you, and you discover the story behind the problem, such as:

1) Why most drug dealers still live with their mothers?

2) Which is more dangerous: Having a gun at home or a private swimming pool?

3) Why crime rate plunged dramatically in the last two decades and is still witnessing a steady decline, though population increased and the economy has its feet flailing up?

4) Why your real estate agent sells his own home at a higher price and stay longer on the market?

5) Does your stock broker has your best interest in mind?

6) Why black parents give their children names that they know may hurt their career prospects…?

7) Do school teacher cheat to meet high-stakes testing standards?

8) Why police departments distort crime data and eliminate cases from the records…?

Do you believe that the problems of this modern world are not impenetrable, and can be resolved, if the right questions are asked, and people are dedicated in uncovering the real story?

Are you curious in divulging the real stories behind cheating, corruption, and criminal behaviors and activities? Levitt just love to play the economist investigator to questions that are related to criminal behaviors.

Levitt drives an aging green Chevy Cavalier with a window that does not shut close, and the car produces a dull roar at highway speed. Levitt notices a homeless guy and says: “He had nice headphones, nicer than mines. Otherwise, it doesn’t look like he has many assets…”

Levitt had an interview for the Society of Fellows, a Harvard clubhouse that pays young scholars to do their own work, for three years, with no commitments attached. Levitt was on fire and his wit crackled. A scholar member asked Steven:

“Do you have a unifying theme of your work? I’m having hard time seeing one underlying theme…” The scholars volunteered offering what they thought could be a unifying theme, and Steven found himself agreeing with every alternative theme.

Finally, philosopher Robert Nozick interrupted saying: “He is 26 year-old. Why does Steven need to have a unifying theme at such a young age? A talented person take a question and he’ll just answer it, and he’ll be fine.”  Steven was awarded the grant.

Steven Levitt has contributed in giving micro-economics and edge over macro-economics or “homo economics” and this behavioral perspective has called into doubt many claims of mankind rational decision-making tendencies.

Real world problems demand to get immersed into various fields of knowledge such as psychology, criminology, sociology, neurology… in order to overcome mathematical theoretical shortcoming.

At 36 of age, Levitt is a full professor at the Univ. of Chicago’s economics department, and received tenure two years after starting to teach. He is an editor of “The Journal of Political Economy”

Note 1: Stephen J. Dubner, co-author of “Freakonomics”, covered the biography of Steven D. Levitt in a special chapter called “Bonus matter”

Note 2:  I have published 5 posts on chapters of Freakonomics and you may have a head start with https://adonis49.wordpress.com/2011/10/26/how-to-convert-conventional-wisdoms-into-success-freakonomics-discoveries/

Article #29, December 1st, 2005

“How objective and scientific are research?”

Would you please give me a minute to set the foundations first? Friend, allow me just a side explanation on experimentation.  Psychologists, sociologists and marketing graduates are trained to apply various experimentation methods and not just cause and effects designs.  There are many statistical packages oriented to providing dimensions and models to the set of data dumped into the experiment so that a preliminary understanding of the system behavior is comprehended qualitatively.

Every applied science has gone through many qualitative models or schemas, using various qualitative methods, before attempting to quantify their models. However, many chairmen of engineering departments, especially those who have no understanding of the disciple of Human Factors or were never exposed to designing experiments, have a conception that this field is mostly qualitative in nature and would ask me to concentrate in my courses on the quantitative aspects such as the environmental factors of lighting, noise, heat and any topic that requires computation or has well defined physics equations.

We have three concepts in the title: objectivity, scientific and research that are related in people’s mind as connoting the same concept.  However, the opposite meanings for these concepts are hard to come by without philosophical divergences or assumptions.  If we define science as a set of historical paradigms, a set of concepts, truths, facts and methods that most of them keep changing as new technologies and new methodologies enlarge the boundaries of knowledge then you might be more inclined to discuss notions with a freer mind.

Could subjectivity be accepted as the opposite of objectivity without agreeing on a number of axioms and assumptions that are not tenable in many cases?  Any agreement in the meanings of objectivity in scientific research procedures and results are basically consensual among the professionals in a discipline, for a period, until the advent of a new paradigm that changes the meaning or orientation of the previous consensus among the professionals.

Could opinions, personal experiences, recalled facts or events not be accepted in the domain of research even if they could be found in written documents but not thoroughly investigated by a researcher?  So what if you refer to an accredited research article and then it turned out that the article was fraught with errors, misleading facts with borderline results and untenable interpretations?  Would the research be thrown in the dust bin as unscientific or non objective and thus not worth further investigations?

Research in Physics, Chemistry and engineering deal with objects and are related to studying the behavior of the physical nature; these kind of research can arrive to well establish mathematical models because the factors are countable, could be well controlled in experimental settings and the variability in errors are connected to the technology of the measuring instruments once the procedure is well defined and established according to experimental standards.  It is when research has to deal with the variability in the human nature such as in psychology, psychometric, sociology, marketing, business management and econometrics that the notions of objectivity, research and science become complex and confusing.

The main problem is to boldly discriminate among research and admit that not every research is necessarily scientific or objective and that a research has an intrinsic value if the investigator is candid about the purpose and nature of his research.  We need to admit that every research is subjective in nature because it is the responsibility of the investigator to select his topic, his intentions, his structured theory, references, fund providers, the hypotheses, the design, the methodology, the sample size, the populations, the data collection techniques, the statistical package, emphasis on either error type I or error type II, the interpretation of results and so on. 

By admitting prior subjective environment to a research endeavor then we can proffer the qualitative term of objectivity to the research only and only when the investigators provide full rationales to every subjective choices in the research process.

Every step in the research process is a variation on an accepted paradigm at one point in the history of science and the mixing of paradigms with no conscious realization of the mixing process should set a warning alarm on the validity of the research and the many pitfalls it is running through.  

Acknowledging the role of subjectivity in the methodology, the data and its interpretation could open the way for more accurate and flexible judgments as to the extent of objectivity and scientific tendencies of the research.

 “An exercise for taxonomy of methods”

Article #14 in Human Factors

I am going to let you have a hand at classifying methods by providing a list of various methods that could be used in Industrial engineering, Human Factors, Ergonomics, and Industrial Psychology.

This first list of methods is organized in the sequence used to analyzing part of a system or a mission;

The second list is not necessarily randomized though thrown in without much order; otherwise it will not be an excellent exercise.

First, let us agree that a method is a procedure or a set of step by step process that our for runners of geniuses and scholars have tested, found it good, agreed on it on consensus basis and offered it for you to use for the benefit of progress and science.

Many of you will still try hard to find short cuts to anything, including methods, for the petty argument that the best criterion to discriminating among clever people is who waste time on methods and who are nerds.

Actually, the main reason I don’t try to teach many new methods in this course is that students might smack run into a real occupational stress which they are not immune of, especially that methods in human factors are complex and time consuming.

Here is this famous list of a few methods and you are to decide which ones are still in the conceptual phases and which have been “operationalized“.

The first list contains the following methods: operational analysis, activity analysis, critical incidents, function flow, decision/action, action/information analyses, functional allocation, task, fault tree, failure modes and effects analyses, time line, link analyses, simulation, controlled experimentation  operational sequence analysis, and workload assessment.

The second list is constituted of methods that human factors are trained to utilize if need be such as: verbal protocol, neural network, utility theory, preference judgments, psycho-physical methods, operational research, prototyping, information theory, cost/benefit methods, various statistical modeling packages, and expert systems.

Just wait, let me resume.

There are those that are intrinsic to artificial intelligence methodology such as: fuzzy logic, robotics, discrimination nets, pattern matching, knowledge representation, frames, schemata, semantic network, relational databases, searching methods, zero-sum games theory, logical reasoning methods, probabilistic reasoning, learning methods, natural language understanding, image formation and acquisition, connectedness, cellular logic, problem solving techniques, means-end analysis, geometric reasoning system, algebraic reasoning system.

If your education is multidisciplinary you may catalog the above methods according to specialty disciplines such as: artificial intelligence, robotics, econometrics, marketing, human factors, industrial engineering, other engineering majors, psychology or mathematics.

The most logical grouping is along the purpose, input, process/procedure, and output/product of the method, otherwise it would be impossible to define and understand any method.

Methods could be used to analyze systems, provide heuristic data about human performance, make predictions, generate subjective data, discover the cause and effects of the main factors, or evaluate the human-machine performance of products or systems.

The inputs could be qualitative or quantitative such as declarative data, categorical, or numerical generated from structured observations, records, interviews, questionnaires, computer generated or outputs from prior methods.

The outputs could be point data, behavioral trends, graphical in nature, context specific, generic, or reduction in alternatives.

The process could be a creative graphical or pictorial model, logical hierarchy or in network alternative, operational, empirical, informal, or systematic.

You may also group these methods according to their mathematical branches such as algebraic, probabilistic, or geometric.

You may collect them as to their deterministic, statistical sampling methods and probabilistic characters.

You may differentiate the methods as belonging to categorical, ordinal, discrete or continuous measurements.

You may wish to investigate the methods as parametric, non parametric, distribution free population or normally distributed.

You may separate them on their representation forms such as verbal, graphical, pictorial, or in table.

You may discriminate them on heuristic, observational, or experimental scientific values.

You may bundle these methods on qualitative or quantitative values.

You may as well separate them on their historical values or modern techniques based on newer technologies.

You may select them as to their state of the art methods such as ancient methods that new information and new paradigms have refuted their validity or recently developed.

You may define the methods as those digitally or analytically amenable for solving problems.

You may choose to draw several lists of those methods that are economically sounds, esoteric, or just plainly fuzzy sounding.

You may opt to differentiate these methods on requiring high level of mathematical reasoning that are out of your capability and those that can be comprehended through persistent efforts.

You could as well sort them according to which ones fit nicely into the courses that you have already taken, but failed to recollect that they were indeed methods worth acquiring for your career.

You may use any of these taxonomies to answer an optional exam question with no guarantees that you might get a substantial grade.

It would be interesting to collect statistics on how often these methods are being used, by whom, for what rational and by which line of business and by which universities.

It would be interesting to translate these methods into Arabic, Chinese, Japanese, Hindu, or Russian.

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