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A test is considered to be objective if different independent researchers obtain the same results.

Source: SFB 504


If the organizational routines and structures have not been altered for a long time, the probability that these structures loose their fit with the environmental conditions increases when the environment is turbulent. This means, that these routines get obsolescent (Schulz, 1993). The consequence on the organizational level is that old organizations in a highly turbulent environment with obsolescent (core) routines should have a higher probability of dying than young ones (Barron, West and Hannan, 1994).

Source: SFB 504


An object's attribute of losing value because the outside world has changed. This is a source of price depreciation.

Source: econterms

ocular regression

A term, generally intended to be amusing, for the practice of looking at the data to estimate by eye how data variables are related. Contrast formal statistical regressions like OLS.

Source: econterms


Abbreviation for 'ordinary differential equation'.

Source: econterms


Organization of Economic Cooperation and Development; includes about 25 industrialized democracies.

Source: econterms

offer curve

Consider an agent in a general equilibrium (e.g., an Edgeworth box). Assume that agent has a fixed known budget and known preferences which predict what set (or possible sets) of quantities that agent will demand at various relative prices. The offer curve is the union of those sets, for all relative prices, and can be drawn in an Edgeworth box.

Source: econterms


Abbreviation for overlapping generations model, in which agents live a finite length of time long enough to live one period at least with the next generations of agents.

Source: econterms


The situation in which a few, possibly collusive, buyers are the only ones who buy a certain good.
Has the same relation to monopsony that oligopoly has to monopoly.

Source: econterms


Ordinary Least Squares, the standard linear regression procedure. One estimates a parameter from data and applying the linear model
y = Xb + e
where y is the dependent variable or vector, X is a matrix of independent variables, b is a vector of parameters to be estimated, and e is a vector of errors with mean zero that make the equations equal.
The estimator of b is: (X'X)-1X'y
A common derivation of this estimator from the model equation (1) is:
y = Xb + e
Multiply through by X'. X'y = X'Xb + X'e
Now take expectations. Since the e's are assumed to be uncorrelated to the X's the last term is zero, so that term drops. So now:
E[X'Xb] = E[X'y] Now multiply through by (X'X)-1 E[(X'X)-1X'Xb] = E[(X'X)-1X'y] E[b] = E[(X'X)-1X'y] Since the X's and y's are data the estimate of b can be calculated.

Source: econterms

omitted variable bias

There is a standard expression for the bias that appears in an estimate of a parameter if the regression run does not have the appropriate form and data for other parameters.

Define: y as a vector of N dependent variable observations, X1 as an (N by K1) matrix of regressors, X2 as an (N by K2 matrix of additional regressors), and e as an (N by 1) vector of disturbance terms with sample mean zero.
Suppose the true regression is:
y = X1b1 + X2b2 + e
for fixed values of b1 and b2. (If 'true regression' seems ambiguous, imagine for the rest of the description that the values of X1, X2, b1, and b2 were chosen in advance by the econometrician and e will be chosen by a random number generator with expectation zero, and y is determined by these choices; in this framework we can be certain what the true regression is and can study the behavior of possible estimators.)

Suppose given the data above one ran the OLS regression

y = X1c1 +errors

Would E[c1]=b1 despite the absence of X2b2? It will turn out in the following derivation that in most cases the answer is no and the difference between the two values is called the omitted variable bias.

The OLS estimator for c1 will be:

c1OLS = (X1'X1)-1X1'y
= (X1'X1)-1X1'(X1b 1 + X2b2 + e)
= (X1'X1)-1X1'X1b1 + (X1'X1)-1X1'X2b2 + (X1'X1)-1X1'e
= b1 + (X1'X1)-1X1'X2b2 + (X1'X1)-1X1'e

So since E[X1'e] = 0, taking expectations of both sides gives:

E[c1] = b1 + (X1'X1)-1X1'X2b2

In general c1OLS will be a biased estimator of b1. The omitted variables bias is (X1'X1)-1X1'X2b2 . An exception occurs if X1'X2=0. Then the estimator is unbiased.

There is more to be learned from the omitted variables bias expression. Leaving off the final b2, the expression (X1'X1)-1X1'X2b2 is the OLS estimator from a regression of X2 on X1.

Source: econterms


statistical abbreviation for "converges in distribution" or, equivalently, "the average is bounded in probability."
That is Xt/n is bounded in probability.

Source: econterms


An economy is said to be open if it has trade with other economies. (Implicitly these are usually assumed to be countries.)
One measure of a country's openness is the fraction of its GDP devoted to imports and exports.

Source: econterms


A contract that gives the holder the right, but not the duty, to make a specified transaction for a specified time.

The most common option contracts give the holder the right buy a specific number of shares of the underlying security (equity or index) at a fixed price (called the exercise price or strike price) for a given period of time. Other option contracts allow the holder to sell.

This is its most common practical business meaning, and the use in theoretical economics is analogous -- e.g. that owning a plant gives a firm the option to manufacture in it at any time or to sell it at any time.

Source: econterms

Options and hedging

Options are contracts, which give the owner the right, to buy (call option) or to sell (put option) a specific amount of an underlying asset for a specific price (exercise price) only at the end (european option) or at any time prior to the specified expiration date (american option). For this option right, the owner has to pay a premium, the option price, at the conclusion date. The opposition of the contract, the seller of the option, has the obligation, to sell (call option) or to buy (put option) the underlying asset at the exercise price if the owner exercises the option.

Source: SFB 504

order condition

In a econometric system of simultaneous equations, each equation may satisfy the order condition, or not do so. If it does not, its parameters are not all identified.

The order condition is often easy to verify. Often the econometrician verifies that the order condition is satisfied and assumes with this justification that the equation is identified, although formally a stronger requirement, the rank condition, must be satisfied. For each equation there must be enough instrumental variables available for the equation to have as many instruments as there are parameters.

The system can satisfy a form of the order condition: that there be as many exogenous variables in the reduced form of the system as there are parameters.

Source: econterms

order of a kernel

The order of a kernel function is defined as the first nonzero moment.

Source: econterms

order of a sequence

Two relevant concepts are denoted O() and o().

Let cn be a random sequence. Quoting from Greene, p 110: "cn is of order 1/n, denoted O(1/n), if plim ncn is a nonzero constant."
"cn is of order less than 1/n, denoted o(1/n), if plim ncn equals 0."

Source: econterms

order statistic

The first order statistic of a random sample is the smallest element of the sample. The second order statistic is the second smallest. And the nth order statistic in a sample of size n is the largest element. The pdf of the order statistics can be derived from the pdf from which the random sample was drawn.

Source: econterms

organizational capital

'whatever makes a collection of people and assets more productive together than apart. Firm-specific human capital (Becker 1962), management capital (Prescott and Visscher 1980), physical capital (Ramey and Schapiro 1996), and a cooperative disposition in the firm's workforce (Eeckhout 2000 and Rb and Zemsky 1997) are examples of organizational capital.' -- from Boyan Jovanovic and Peter L. Rousseau, Sept 20 2000, 'Technology and the Stock Market: 1885-1998' NYU and Vanderbilt University, working paper

Source: econterms

Organizational learning

The notion of Organizational Learning (OL) has become very prominent in the near past. Managers see OL as a powerful tool to improve the performance of an organization. Thus, it is not only the scholars of organization studies who are interested in the phenomenon of OL but also the practitioners who have to deal with the subject of OL.

Generally, one can distinguish between two different processes of organizational change that are associated with OL:
adaptive learning, i.e. changes that have been made in reaction to changed environmental conditions and
proactive learning, i.e organizational changes that have been made on a more willful basis. This is learning which goes beyond the simple reacting to environmental changes.

In general, it is assumed that adaptive learning comes along with a lower degree of organizational change. This means that adaptive learning is seen as a process of incremental changes. What is more, adaptive learning is also seen as more automatic and less cognitively induced than proactive learning. The inferiorities of adaptive learning compared to proactive learning are also expressed by the different labels which have been used to describe these two types of OL: ?Single-Loop versus Double-Loop Learning? (Argyris and Schön, 1978), ?Lower Level versus Higher Level Learning? (Fiol and Lyles, 1985), ?Tactical versus Strategic Learning? (Dodgson, 1991) ?Adaptive versus Generative Learning? (Senge, 1990).

Cyert and March (1963) started the discussion about OL. In their view OL is mainly an adaptive process in which goals, attention rules (or standard operating procedures), e.g. which parts of the environment the organization should listen to, and search rules that stir the organization in a particular way to find problem-solutions are adapted to the experiences that are made within the organization. Cyert and March did not concentrate on the question whether these experiences were made because of environmental changes. Rather they focus on the problem solving quality of the attention- and search rules. So even in stable environments, organizations can learn how to adjust their procedures in order to better perform.

Within the behavioral school of James March (e.g. Levitt and March, 1988; Levinthal and March, 1988; Levinthal and March, 1993) it was always emphasized that OL is executed on the basis of rules. Organizational decisions depend on certain rules. The experiences which have been made within the organization determine the contents of these rules. If the rules no longer fit the experiences they have to be altered. This process of rule change can be affected by different disturbances, e.g. false interpretation of events or the impediment of the realisation of personal insights (March and Olsen, 1975). These affections of the process of learning reveal that OL can only be regarded as a limited rational process.

Source: SFB 504

Organizational studies behavioral

Within the discussion about organizational learning the expression of behavioral is used in two different respects.

The approaches within the Carnegie School and later within the March School of organization studies are regarded as behavioral approaches that contrast the neo-classic concepts of organizing. The behavioral approaches are prominent for the notion that organizational actions are mainly rule based because the organizational members have only limited rational abilities. Therefore they need certain definite rules (or standard operating procedures) that relief them from the continuous task of creative problem solving. These rule based actions have only a satisficing outcome which contradicts the neoclassic view of a human who is able to willfully find the optimal decision by rational search.

The second meaning of behavioral within the discussion of organizational learning is quite similar to the meaning within the psychology of learning. In this respect behavioral is regarded as the opposite of cognitive, i.e. it is the automatic response to a stimulus of the environment. When there are some shifts in the environment of the organization the behavioral reaction to these shifts is the automatically changing of routines and strategies without reflecting cognitively what has happened and which reaction would be most appropriate (Fiol and Lyles, 1985).

Source: SFB 504

Organizational studies cognitive

The notion of cognitive activity has two different meanings within organization studies. The first meaning is the opposite of behavioral and means that decisions are made by reflective insights and not just by automatic response to certain stimuli.

The second meaning is prominent within the instititionalist debate. Herein, the expression cognitve denotes the tendency of humans within institutionalized settings to comply with the environment. Because humans have to create reliable frameworks in which they can repeatingly act in a stable way, the cognitive task of the human mind is to reassure the social structures they are living in. This has to be carried out actively, so that the categories of life are brought about by the actual human conduct. The result is a taken-for-granted world which is not reflectively questioned but which is actively constructed. An example would be a daily meeting of superiors which is seen as a basic element of organizing and is associated with many typical procedures which this meeting cannot do without. Otherwise it would not be the same essential part of organizing. However, organizational members have to actively dedicate themselves to the conduct of this meeting without questioning it in order to keep it as a stable element of the organization´s activities.

Source: SFB 504



Source: econterms

outside money

monetary base. Is held in net positive amounts in an economy. Is not a liability of anyone's. E.g., gold or cash. Contrast inside money.

Source: econterms


The concept of overconfidence is based on a large body of evidence from cognitive psychological experiments and surveys showing that individuals overestimate their own abilites or knowledge as well as the precision of their information.

Svenson (1981), Taylor & Brown (1988), Tiger (1979) and Weinstein (1980) provide empirical evidence for the first category of overconfidence: Most people rate themselves above the mean on almost every positive personal trait - including driving ability, a sense of humor, managerial risk taking, and expected longevity. For instance, when a sample of U.S. students assessed their own driving safety, 82% judged themselves to be in the top 30% of the group.

The sources of overconfidence can be indirect, like computational constraints and frictions which diminish the marginal benefits of additional iterations in judgment. Or they can be linked to a different cognition and decision process. For example, individuals may think that they can interpret information better than they really do.

In behavioral finance, the concept of overconfidence might help to explain the high volume of trade observed in financial markets. If one connects the phenomenon of overconfidence with the phenomenon of anchoring, one can see the origins of differences of opinion among investors, and one possible source of the high volume of trade among them.

Source: SFB 504


Describes "a situation where the initial reaction of a variable to a shock is greater than its long-run response."

Source: econterms


This word is used in a very particular way in the discussion of time series data. In the context of a discussion of a particular time series it refers to previous values of that time series. E.g. 'own temporal dependence' as in Bollerslev-Hodrick 92 p 8 refers to the question of whether values of the time series in question were detectably a function of previous values of that same time series.

Source: econterms


An object-oriented matrix language sometimes used for econometrics. Details are at .

Source: econterms

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