Vocab Words

Positive - factual statement about what is. A hypothesis or theory about how things work. Does not make any value judgements. http://ingrimayne.com/econ/Introduction/Normativ.html

Normative - Statement about how things SHOULD be. Expresses whether a situation is desirable or undesirable. http://ingrimayne.com/econ/Introduction/Normativ.html

Tractable - easily managed, controlled.

Parsimonious -
Parsimony is also a factor in statistics: in general, mathematical models with the smallest number of parameters are preferred as each parameter introduced into the model adds some uncertainty to it. Additionally, adding too many parameters leads to "connect-the-dots" curve-fitting which has little predictive power. In general terms, it may be said that applied statisticians (such as process control engineers) value parsimony quite highly, whereas mathematicians prefer to have a more predictive model even if a large number of parameters are required.

Pareto Optimality - Given a set of alternative allocations of, say, goods or income for a set of individuals, a movement from one allocation to another that can make at least one individual better off without making any other individual worse off is called a Pareto improvement. An allocation is Pareto efficient or Pareto optimal when no further Pareto improvements can be made. This is often called a Strong Pareto Optimum (SPO). http://en.wikipedia.org/wiki/Pareto_efficiency

Monotonic - In calculus, a function f defined on a subset of the real numbers with real values is called monotonic (also monotonically increasing, increasing, or non-decreasing), if for all x and y such that x ≤ y one has f(x) ≤ f(y), so f preserves the order. Likewise, a function is called monotonically decreasing (also decreasing, or non-increasing) if, whenever x ≤ y, then f(x) ≥ f(y), so it reverses the order. http://en.wikipedia.org/wiki/Monotonic#Monotonic_logic

Endogenous - The word endogenous means "arising from within", the opposite of exogenous.

Exogenous - Exogenous (or exogeneous) (from the Greek words "exo" and "gen", meaning "outside" and "production") refers to an action or object coming from outside a system. It is the opposite of endogenous, something generated from within the system.

Stochastic - to·chas·tic (st-kstk)

adj.

1. Of, relating to, or characterized by conjecture; conjectural.

2. Statistics

a. Involving or containing a random variable or variables: stochastic calculus.

b. Involving chance or probability: a stochastic stimulation.

The Time Horizon Problem

I have a lot of research ideas and such that I need to catch up on posting, but I wanted to jot down this one quote/thought while it is just fresh. I just read a paragraph of an agency theory paper that made me think of the environmental problem:

"The Shorter time horizon for the agent and the superior information of the agent set up the classic tradeoff in accounting: we would like accounting reports to reflect information that is forward looking, but forward-looking information is less reliable and more manipulable. In particular, the short time horizon for the agent makes it more important that the principal have a forward-looking performance measure in order to motivate the agent to be 'long term' in his thinking. However, the short time horizon for the agent also means he has greater opportunities to avoid having to settle up if he misleads the principal about future prospects." (Lambert, JAE 2001)

This is a big part of what leads to environmental and social externalities. There is no way to tie management compensation to long-term thinking. Therefore, CEOs are essentially getting paid to maximize the short term at the expense of the long-term. Externalizing short-term costs to long-term resources like the environment is the rational decision for the agent because his performance is evaluated using short-term measures. This is probably not the optimal solution for the agent in the presence of a long-term performance measure that is not manipulable, but in current models, long-term performance measures are too easily manipulated to allow for optimal contracts based on long-term measures.

I don't know how to solve this problem, but, i do know that it is related to other problems that I am thinking about. I want to keep that in mind.

Research Ideas

Ok, I think it might help me decide what I want to do if I scribble down some of my many wild ideas for research topics and see if any sense comes out of this.

1. I think that climate change is one of, if not the most, important problems of our generation. It is possibly one of the biggest and most direct ways that I can see myself bringing positive change to the world through accounting. Financial markets are one of the largest driving forces behind the destruction of our planet's climate and natural resources. This is because financial markets do not incorporate natural resources into financial information. They are treated as externalities. When a company pollutes or uses up natural resources, these costs do no show up as expenses on the company's financial statements. If these costs were taken into account, investors would have more of the necessary information needed to allocate resources towards sustainable activities instead of investing in business activities that create profit by externalizing costs onto the environment. In short, if companies were to internalize environmental externalities, they would then manage these costs. In order to internalize these costs, we must be able to measure, analyze, and report what these costs are.

- Strenghs: Very important. Growing field with lots of room for potential. Becoming a more relevant area as global warming gets worse.

- Weakness: I know very little about this. I have no previous competitive advantage. This is not an established area of research. Will be hard to get published and also to find traction among ASU faculty.

2. I guess that, if I step back and take a big picture view, one of the most interesting aspects of accounting for me is that accounting is a snapshot of reality. Without stepping into the realm of non-financial/environmental issues, there are many areas of financial reporting that may not currently represent economic reality very accurately. There are two areas, one a balance sheet measure, and one an income statement measure, that are of interest to me. On the balance sheet, I think that increasingly intellectual capital and intangibles are major sources of future economic value that are not captured in the financial statements. Perhaps of even more importance to investors, it also appears that earnings do not capture very much of the information that explains stock price movements. Based on the paper that we read by Lev, earnings only explains a very very small amount of the R-squared in stock price variability. I think that investors might be able to make more efficient resource allocations if they had more accurate/relevant earnings information to base their investment decisions on. I also find it interesting that both of these issues are issues that Prof. Lev is interested in. I should read more of his research. As far as the earnings question, i think I am most interested in how investors use earnings information to make decisions (e.g. what adjustments do they make?) and also what affect differences in accounting methods have on the usefulness of earnings information (e.g. is one method more useful to investors than the other? are there better methods that we are not using that could be more useful?)

Strengths - Very mainstream. Especially the earnings question. Very interesting problem. I understand at least a little bit about it from my background. I have a fair amount of institutional knowledge of US GAAP if I want to research GAAP alternatives. I am also interested in standard setting and I think it would be great if I could help develop useful standards. Prof. Lev is already interested in many of the things I am interested in. I could contact him and possibly have a mentor in my pursuit.

Weaknesses - Very crowded field. It would be hard to stand out. Do I have any new ideas to bring to the table that people have not already tried? Might necessitate learning a lot of quantitative and finance skills that may not be my strong suit. There is a chance to get bogged down in the details of the market and end up doing research that is not interesting or helpful. Does not have as direct of an impact for creating positive change as trying to save the environment from climate change.


3. Methodological interests: Axelrod's "evolution of cooperation," and computer/Monte Carlo simulations. I really like Axelrod's approach to game theory and cooperation. I wonder if there are any applications of his model in accounting settings. This is related in my mind to the Monte Carlo methodology. Axelrod uses a agent-based computer simulation to conduct his research on cooperation and show how cooperation can evolve in competitive settings. Monte Carlo methods are also computer simulations.

Strengths- I have a computer science degree. I like programming. I almost became a programmer instead of an accountant. Maybe I can use that competitive advantage to approach accounting problems from a different angle than other people. I also like the evolution aspect of Axelrod's research. It seems that evolution is a very powerful mechanism that shows up as a plausible explanation for a lot of phenomena in the world. Maybe there are accounting/market phenomena that have evolutionary explanations also. If other people have approached my topical interests from traditional points of view already, maybe no one has taken these methodological approaches yet and I can bring something new to the table. Another advantage to these methods is that they do not require running experiments using people, which can be unreliable.

Weaknesses - I enjoyed programming in college, but I have no evidence that I really do have a competitive advantage in this method. It seems that many accounting PhDs know how to program. Many of them may be far better programmers than I am. I also do not know much about these methods, especially monte carlo methods. There is so so much to learn. There are many books and classes just about these methods. While I think i would be fairly strong in simulation design, I might struggle a lot with the mathematics and quantitative mechanics of developing these simulations. My weak quant skills might actually make this a terrible path for me to pursue.

Ok, very tired for now, but i think that was a good start.

Questions:
- Is there a simple mission statement that links all of these things together?
- Are there any good ideas from these topics that I could use for my literature review or event study this semester?