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Glossary


A B C D E F G H I J K L M N O P Q R S T U V W X Y Z (Show all)

m-estimators

Estimators that maximize a sample average. The 'm' means 'maximum-likelihood-like'. (from Newey-McFadden)

The term was introduced by Huber (1967). "The class of M-estimators included the maximum likelihood estimator, the quasi-maximum likelihood estimator, multivariate nonlinear least squares" and others. (from Wooldridge, p 2649)

I think all m-estimators have scores.

Source: econterms

M1

A measure of total money supply. M1 includes only checkable demand deposits.

Source: econterms

M2

A measure of total money supply. M2 includes everything in M1 and also savings and other time deposits.

Source: econterms

MA

Stands for "moving average." Describes a stochastic process (here, et) that can be described by a weighted sum of a white noise error and the white noise error from previous periods. An MA(1) process is a first-order one, meaning that only the immediately previous value has a direct effect on the current value:
et = ut + put-1
where p is a constant (more often denoted q) that has absolute value less than one, and ut is drawn from a distribution with mean zero and finite variance, often a normal distribution.
An MA(2) would have the form:
et = ut + p1ut-1 + p2ut-2
and so on. In theory a process might be represented by an MA(infinity).

Source: econterms

MA(1)

A first-order moving average process. See MA for details.

Source: econterms

macro

macro

Source: econterms

MacroInstitutionalism


Generally, macroinstitutionalisation is seen as the tendency of organizations to arrange their formal structure not in response to the technical needs of the organizations but in accordance to certain widely accepted rules. This is done in order not to loose the legitimacy towards important stakeholders like banks, clients etc. (Scott, 1987, Scott, 1995, Zucker, 1991, Meyer & Rowan, 1977). Organizations are expected to conform to the institutionalized rules. So firms react to these expectations of good practice rather than looking for the most rational solutions. An example for this notion would be the implementation of computing facilities in organizational settings just because competing firms use computing facilities in similar settings too. "We arrive at the conclusion that formal organization, as it expands in a domain or society, becomes less explicitly rational in its structure. ... Every aspect of rationalized organizational structure comes under exogenous institutional control ..." (Meyer, 1992: 268). The consequence of this tendency is that within an organization the institutionalized routines might be decoupled from the actual practice of the organization. The formal rules signal to the environment that the organization complies with the institutionalized norms of organizing. However, the strict appliance of the rules would lead to inconsitencies. Therefore the organizational members (OM) have the freedom to arrange the tasks in a way which they consider most efficient - thereby violating the official rules (Meyer & Rowan, 1977: 357).

Source: SFB 504

Magic cards

" the Gathering game scenario, players assume the roles of dueling wizards, each with their own libraries of magic spells(represented by decks of cards) that may potentially be used against the player's opponent. Cards are sold in random assortments, just like baseball cards, at retail stores. Launched in August 1993, this product has already grossed hundreds of millions of retail dollars, and now has over a million players worldwide." - description from Reily (1999), " Using Field Experiments to Test Equivalence Between Auction Formats: Magic on the Internet." AER, 89

main effect

As contrasted to interaction effect.

In the regression

yi = aXi + bXZi + cZi + errors

The bXZi term measures the interaction effect. The main effect is cZi.

This term is usually used in an ANOVA context, where its meaning is presumably analogous but this editor has not verified that.

Source: econterms

maintained hypothesis

Synonym for 'alternative hypothesis'. "The hypothesis that the restriction or set of restrictions to be tested does NOT hold." Often denoted H1.

Source: econterms

Malmquist index

An index number enabling a productivity comparison between economy A and economy B. Imagine that we have an aggregate production function QAA=fA(KA,LA) that describes economy A and an aggregate production QBB=fB(KB,LB) that describes economy B. K and L stand for capital and labor inputs. We substitute the inputs of B into the production function of A to compute QAB=fA(KB,LB). We also compute QBA=fB(KA,LA) with the inputs from country A.

The Malmquist index of A with respect to B is the geometric mean of QAA/QAB and QBA/QBB. It will be greater than one if A's aggregate production technology is better than B's.

Source: econterms

mantissa

Fractional part of a real number.

Source: econterms

MAR

a rare abbreviation, for moving-average representation

Source: econterms

March CPS

Also known as the Annual Demographic File. Conducted in March of each year by the Census Bureau in the U.S. Gets the information from the regular monthly CPS survey, plus additional data on work experience, income, noncash benefits, and migration.

Source: econterms

marginal significance level

a synonym for 'P value'

Source: econterms

market

An organized exchange between buyers and sellers of a good or service.

Source: econterms

market capitalization

Total number of shares times the market price of each. May be said of a firm's shares, or of all the shares on an equity market.

Source: econterms

market failure

A situation, usually discussed in a model not in the real world, in which the behavior of optimizing agents in a market would not produce a Pareto optimal allocation. Sources of market failures:
-- monopoly. Monopoly or oligopoly producers have incentives to underproduce and to price above marginal cost, which then gives consumers incentives to buy less than the Pareto optimal allocation.
-- externalities

Source: econterms

market for corporate control

Shares of public firms are traded, and in large enough blocks this means control over corporations is traded. That puts some pressure on managers to perform, otherwise their corporation can be taken over.

Source: econterms

market power

Power held by a firm over price, and the power to subdue competitors.

Source: econterms

market power theory of advertising

That established firms use advertising as a barrier to entry through product differentiation. Such a firm's use of advertising differentiates its brand from other brands to a degree that consumers see its brand is a slightly different product, not perfectly substituted by existing or potential competitors. This makes it hard for new competitors to gain consumer acceptance.

Source: econterms

market price of risk

Synonym for Sharpe ratio.

Source: econterms

Markets

In a very abstract sense, a market is where private goods are exchanged. A good can be anything for which a well-defined property right exists. This abstract definition is related to the concepts of an allocation, the competitive market equilibrium, and an economic equilibrium in general.

More intuitively, the concept of a market describes the idea that the suppliers of a product (or a service) meet the demand side, and both sides negotiate over the price until an optimal combination of price and quantity is reached. Typically, the supply side offers a higher quantity the higher the price, whereas the demanded quantity falls the higher the price. In equilibrium, suppliers and consumers trade at a price at which the supplied quantity equals the demanded quantity.

Source: SFB 504

Markov chain

A stochastic process is a Markov chain if:
(1) time is discrete, meaning that the time index t has a finite or countably infinite number of values;
(2) the set of possible values of the process at each time is finite or countably infinite; and
(3) it has the Markov property of memorylessness.

Source: econterms

Markov perfect

A characteristic of some Nash equilibria. "A Markov perfect equilibrium (MPE) is a profile of Markov strategies that yields a Nash equilibrium in every proper subgame." A Markov strategy is one that does not depend at all on variables that are functions of the history of the game except those that affect payoffs.
A tiny change to payoffs can discontinuously change the set of Markov perfect equilibria, because a state variable with a tiny effect on payoffs can be part of a Markov perfect strategy, but if its effect drops to zero, it cannot be included in a strategy; that is, such a change makes many strategies disappear from the set of Markov perfect strategies.

Source: econterms

Markov process

A stochastic process where all the values are drawn from a discrete set. In a first-order Markov process only the most recent draw affects the distribution of the next one; all such processes can be represented by a Markov transition density matrix. That is,
Pr{xt+1 is in A | xt, xt-1,...} = Pr{xt+1 is in A | xt}
Example 1: xt+1 = a + bxt + et is a Markov process
For a=0, b=1 it is a martingale.


A Markov process can be periodic only if it is of higher than first order.

Source: econterms

Markov property

A property that a set of stochastic processes may have. The system has the Markov property if the present state predicts future states as well as the whole history of past and present states does -- that is, the process is memoryless.

Source: econterms

Markov strategy

In a game, a Markov strategy is one that does not depend at all on state variables that are functions of the history of the game except those that affect payoffs.
[Ed.: I believe random elements can be in a Markov strategy: e.g. a mixed strategy could be a Markov strategy.]

Source: econterms

Markov transition matrix

A square matrix describing the probabilities of moving from one state to another in a dynamic system. In each ?row? are the probabilities of moving from the state represented by that row, to the other states. Thus the rows of a Markov transition matrix each add to one. Sometimes such a matrix is denoted something like Q(x' | x) which can be understood this way: that Q is a matrix, x is the existing state, x' is a possible future state, and for any x and x' in the model, the probability of going to x' given that the existing state is x, are in Q. (An example would be good here)

Source: econterms

Markov's inequality

Quoting almost strictly from Goldberger, 1994, p 31:

If Y is a nonnegative random variable, that is, if Pr(Y<0)=0, and k is any positive constant, then E(Y) ≥ kPr(Y ≥ k).

The proof is amazingly quick. See Goldberger page 31 or Hogg and Craig page 68.

Source: econterms

markup

In macro, the ratio of price to marginal cost. Can be used as a measure of market power across firms, industries, or economies.

Source: econterms

Marshallian demand function

x(p,m) -- the amount of a factor of production that is demanded by a producer given that it costs p per unit and the budget limit that can be spent on all factors is m. p and x can be vectors.

Source: econterms

martingale

Same as martingale difference sequence.

Source: econterms

martingale difference sequence

** This definition is not usable as is ** A stochastic process {Xt} is a martingale (or, equivalently, martingale difference sequence) with respect to information {Yt} if and only if:
(i) E|Xt| < infinity
(ii) E[Xn+1 | Y0, Y1, ... , Yn] = Xn E(gt+1) = gt.

Martingale differences are uncorrelated but not necessarily independent.

Source: econterms

mass production

'A production system characterized by mechanization, high wages, low prices, and large-volume output.' (Hounshell, p.305) Usually refers to factory processes on metalwork, not to textiles or agriculture. The term came into use in the 1920s and referred to production approaches analogous to those of the Ford Motor Company in the US.

Source: econterms

Matching pennies

Extremely simplistic, symmetric, two player 2x2 game (which is said to be played by children), in which each player chooses either Head or Tail. If the choices differ, player 1 pays a dollar to player 2; if they are the same, player 2 pays player 1 a dollar. This game does not have an equilibrium in pure strategies, but the unique equilibrium involves each player selecting one of the two actions with equal probability. The game illustrates that interactively optimizing behavior may create the need to take actions randomly, in order not to be predictable by the opponent. For the exact determination of mixed equilibrium strategies, the assumption of expected utility is important. For a real-world situation closely resembling this game, think of penalty shooting in sports: both the goal-keeper and the player who shoots the ball play randomized strategies. They randomize their actions (left or right, upper corner or not) in a way such that the other player cannot improve by either action he takes, given the own probabilities of selecting the actions.

Source: SFB 504

Matching Pennies

Player Two
CD
Player One C1,-1 -1,1
D-1,1 1,-1
A zero-sum game with two players. Each shows either heads or tails from a coin. If both are heads or both are tails then player One wins, otherwise Two wins. The payoff matrix is at right.

There is no Nash equilibrium to this game.

Source: econterms

Matlab

A matrix programming language and programming environment. Used more by engineers but increasingly by economists. There's a very brief tutorial at Tutorial: Matlab.
The software is made by The Mathworks, Inc.

Source: econterms

maximin principle

A justice criterion proposed by the philosopher Rawls. A principle about the just design of social systems -- e.g., rights and duties. According to this principle the system should be designed to maximize the position of those who will be worst off in it.

"The basic structure is just throughout when the advantages of the more fortunate promote the well-being of the least fortunte, that is, when a decrease in their advantages would make the least fortunate even worse off than they are. The basic structure is perfectly just when the prospects ofthe least fortunate are as great as they can be." -- Rawls, 1973, p 328

Source: econterms

maximum score estimator

A nonparametric estimator of certain coefficients of a binary choice model. Avoids assumptions about the distribution of errors that would be made by a probit or logit model in the same circumstances.

In the econometric model: the dependent variable yi is either zero or one; the regressors Xi are multiplied by a parameter vector b. yi often represents which of two choices was selected by a respondent. b is estimated to maximize an objective function that is given by an expression: maxb sumi=1 to N [(yi-.5)sign(Xib)]

where i indexes observations, of which there are N, and the function sign() has value one if its argument is greater than or equal to zero, and has value zero otherwise.

b chosen this way has the property that it maximizes the correct prediction of yi given the information in X. Notice that although the maximum value of the maximand may be well defined, b is not usually uniquely estimated in a finite data set, because values of b near betahat would make the same predictions. Often, however, b is estimated within a narrow range.

Source: econterms

MBO

Stands for Management Buy-Out, the purchase of a company by its management. Sometimes means Management By Objectives, a goal-oriented personnel evaluation approach.

Source: econterms

mean square error

A criterion for an estimator: the choice is the one that minimizes the sum of squared errors due to bias and due to variance.

Source: econterms

mean squared error

The mean squared error of an estimator b of true parameter vector B is:
MSE(b) = E[(b - B)2]
which is also
MSE(b) = var(b) + (bias(b))(bias(b)')

Source: econterms

measurable

If (S, A) is a measurable space, elements of A are A-measurable.

Source: econterms

measurable space

(S, A) is a measurable space if S is a set and A is a sigma-algebra of S. Elements of A are said to be A-measurable.

Source: econterms

measure

A noun, in the mathematical language of measure theory: a measure is a function from sets to the real line. Probability is a common kind of measure in economic models. Other measures are the counting measure, which is the number of elements in the set, the length measure, the area measure, and the volume measure. Length, area, and volume are defined along lines, planes, and spaces just as one would expect, and they have the natural meanings.
Formally: a measure is a mapping m from a sigma algebra A to the extended real line such that
(i) m(null) = 0
(ii) m(B) >= 0 for all B in A
(iii) m(any countable union of disjoint sets in A) = the sum of m(each of those sets)
The third property is called the countable additivity property. An example: imagine probability mass distributed evenly on a unit square. Probability is then defined on any area within the square. The measure (probability, here) is the size (area) of the subset.
The kinds of subsets on which measures such as probability are defined are called sigma-algebras (which see).

Source: econterms

measure theory

measure theory

Source: econterms

measurement error

The data used in an econometric problem may have been measured with some error, and if so this violates a basic condition of the abstract environment in which OLS is validly derived. This turns out not to be seriously problematic if the dependent variable is affected by an iid mean-zero measurement error, but if the regressors have been measured with a mean-zero iid error the estimates can be biased. There are standard approaches to this problem, notably the use of instrumental variables. Paraphrasing from Schennach, 2000, p 1: In a linear econometric specification, a measurement error on the regressors can be viewed as a particular type of endogeneity problem causing the disturbance to be correlated with the regressors, which is precisely the problem addressed by standard IV techniques.

Source: econterms

mechanism design

A certain class of principal-agent problems are called mechanism design problems. In these, a principal would like to condition her own actions on the private information of agents. The principal must offer incentives for the agents to reveal information.
Examples from the theoretical literature are auction design, monopolistic price discrimination, and optimal taxation. In an auction the seller would like to set a price just below the highest valuation of a potential buyer, but does not know that price, and an auction is a mechanism to at least partially reveal it. In a price discrimination, the seller would like to offer the product at different prices to groups with different valuations but may not be able to identify which group an agent is a member of in advance.

Source: econterms

Mediator variable

In general, a given variable may be said to function as a mediator to the extend that it accounts for the relation between the predictor and the criterion. Mediators explain how external physical events take on internal psychological significance. Whereas moderator variables specify when certain effects will hold, mediators speak to how or why such effects occur (Baron & Kenny, 1986, p. 1176).

Path diagram:

IV = independent variable
OV = dependent (outcome) variable

The authors clarify the meaning of mediation, with introducing a path diagram as a model for depicting a causal chain. The basic causal chain involved in mediation is diagramed in the figure above. "This model assumes a three-variable system such that there are two causal paths feeding into the outcome variable: the direct impact of the independent variable (Path c) and the impact of the mediator (Path b). There is also a path from the independent variable to the mediator (Path a).

A variable functions as a mediator when it meets the following conditions:
(a) variations in levels of the independent variable significantly account for the variations in the presumed mediator (i.e., Path a),
(b) variations in the mediator significantly account for variations in the dependent variable (i.e., Path b), and (c) when Paths a and b are controlled, a previously significant relation between the independent and dependent variable is no longer significant, with the strongest demonstration of mediation occurring when Path c is zero.
In regard to the last condition we may envisage a continuum. When Path c is reduced to zero, we have strong evidence for a single, dominant mediator. If the residual Path c is not zero, this indicates the operation of multiple mediating factors. Because most areas of psychology, including social, treat phenomena that have multiple causes, a more realistic goal may be to seek mediators that significantly decrease Path c rather than eliminating the relation between the independent and the dependent variables altogether. From a theoretical perspective, a significant reduction demonstrates that a given mediator is indeed potent, albeit not both a necessary and a sufficient condition for an effect to occur (Baron & Kenny, 1986, p. 1176).

Source: SFB 504

medium of exchange

A distinguishing characteristic of money is that it is taken as a medium of exchange, that is, in the language of Wicksell (1935) p. 17, that it is "habitually, and without hesitation, taken by anybody in exchange for any commodity."

Source: econterms

meet

Given a space of possible events, the meet is the finest common coarsening of the information sets of all the players. The meet is the finest partition of the space of possible events such that all players have beliefs about the probabilities of the elements of the partition.

Source: econterms

mesokurtic

An adjective describing a distribution with kurtosis of 3, like the normal distribution. See by contrast leptokurtic and platykurtic.

Source: econterms

metaproduction function

Means best-practice production function -- depending on context, either the most efficient feasible practice, or most efficient actual practice of the existing entities converting inputs X into output y. Often in practice y is an agricultural output, and data from a sample of farms, and the meta-production function could be estimated by estimating production functions for the farms and choosing among the most efficient ones. In the (macro) context of the quote below, the entities are not farms but countries, producing GDP. 'The term 'meta-production function' is due to Hayami and Ruttan (1970, 1985). For an exposition of the meta-production function approach, see Lau and Yotopoulos (1989) and Boskin and Lau (1990).... The two most important maintained hypotheses [of this approach] are: (1) that the aggregate production functions of all countries are identical in terms of 'efficiency-equivalent' units of output and inputs; and (2) that technical progress in all countries can be represented in the commodity-augmentation form, with constant geometric augmentation factors....' The framework allows 'the researcher to consider and potentially to reject the maintained hypotheses of traditional growth accounting [such as] (1) constant returns to scale, (2) neutrality of technical progress; and (3) profit maximization.' (p66) An assumption related to the second maintained hypothesis above, which the theory depends on (p69) is that 'the measured outputs and inputs of the different countries may be converted into unobservable standardized, or 'efficiency-equivalent,' quantities of output and inputs by multiplicative country- and output- and input-specific time-varying augmentation factors....' (where 'time-varying' seems to conflict with the requirement, above, that the augmentation factors be 'constant'.) (p69) In this approach 'countries may differ in the quantities of their factor inputs and intensities and possibly in the qualities and efficiencies of their inputs and outputs, but they do not differ with regard to the technological opportunities .... [T]hey are assumed to have equal access to technologies.' From p66, 69, 73 of Lau (1996).

Source: econterms

metatheorem

An informal term for a proposition that can be proved in a class of economic model environments.

Source: econterms

method of moments

A way of generating estimators: set the distribution moments equal to the sample moments, and solve the resulting equations for the parameters of the distribution.

Source: econterms

MFP

Abbreviation for Multi-factor productivty.

Source: econterms

MGF

stands for 'moment generating function', which see.

Source: econterms

Microeconomics

Microeconomics is the analysis of individual economic units and their interactions. It includes the theories of the consumer (i.e., of households), the producer (i.e., firms), and the markets in which they interact. The tools of microeconomic analysis are also employed in other fields, such as the theory of optimal taxation in public economics. Microeconomics is often contrasted with macroeconomics which is concerned with economic aggregates, such as aggregate consumption and aggregate production, unemployment, or with economic growth in general.

Source: SFB 504

Minitab

Data analysis software, discussed at http://www.minitab.com.

Source: econterms

Mixed strategy

In contrast to pure strategies, mixed strategies are strategies that involve random draws. A mixed strategy is a probability distribution over a player's (pure) strategies. For example in penalty shooting, the goalgetter typically does not expect the goalkeeper to jump to the right corner for sure, but he regards the goalkeeper's behaviour as a mix between the pure strategies "jump to the right" and "jump to the left".

Source: SFB 504

mixing

In the context of stochastic processes, events A and B (that is, subsets of possible outcomes of the process) "are mixing" if they are asymptotically independent in the following way.

Let L be a lag operator that moves all time subscripts back by one (e.g. replacing t by t-1). Iff A and B are mixing, then taking the limit as h goes to infinity:
lim Pr(A intersected with LhB) = Pr(A)Pr(B).

The event Lh is the event B, but h periods ago; it's NOT some kind of stochastic ancestor of B.

If two events are independent, they are mixing.
If two events are mixing, they are ergodic.

I *believe* that a stochastic process is mixing iff all pairs of possible values it can take, taken as events, are mixing.

Source: econterms

MLE

maximum likelihood estimator

Source: econterms

MLRP

Abbreviation for monotone likelihood ratio property of a statistical distribution.

Source: econterms

models

Generally means theoretical or structural models. Can also mean econometric models which in this glossary are listed separately. models

Source: econterms

Models of microeconomic decisions

Economics proceeds by building models of behavior. These models are supposed to be simplified representations of reality which specify how variables in a system relate to each other. Economists use many techniques in the construction and analysis of economic models, but most of the techniques fall into the categories of optimization analysis and equilibrium analysis.

Nearly all models of individual behavior in microeconomics are models of optimizing behavior which can broadly be interpreted as rational behavior. In building a model of behavior, economists are naturally led to identify agents that make the choices, the kinds of choices that are feasible for them, how the choices of other agents constrain them, and so on. Once the economist is able to write down an optimizing problem describing an economic choice, he or she can apply the standard mathematical methods of microeconomic analysis.

Once we have understood the nature of the optimal choice problem facing individual agents, we can investigate how these choices fit together. In general, some of the variables that influence a given agent´s behavior ? such as prices ? will be determined, at least in part, by the behavior of other agents. An economic equilibrium is a situation of consistent optimal choices: No agent has an incentive to change any of his choices, given his perceptions of the behavior of other agents.

Source: SFB 504

Moderator variable

Moderator variables are important, because specific factors (e.g. context information) are often assumed to reduce or enhance the influence that specific independent variables have on specific responses in question (dependent variable).

Specifically within a correlational analysis framework, a moderator is a third variable that affects the zero-order correlation between two other variables. For example, Stern, McCants & Pettine (1982) found that the positivity of the relation between changing life events and severity of illness was considerably stronger for uncontrollable events (e.g., death of a spouse) than for controllable events (e.g., divorce). A moderator effect within a correlational framework may also be said to occur where the direction of the correlation changes. Such an effect would have occured in the Stern et al. study if controllable life changes had reduced the likelihood of illness, thereby changing the direction of the relation between life-event change and illness from positive to negative.

In the more familiar analysis of variance (ANOVA) terms, a basic moderator effect can be represented as an interaction between a focal independent variable and a factor that specifies the appropriate conditions for its operation" (Baron & Kenny, 1986, p. 1174).

Source: SFB 504

modernization

Quoting from Landes: "Modernization comprises such developments as urbanization (the concentration of the population in cities that serve as nodes of industrial production, administration, and intellectual and artistic activity); a sharp reduction in both death rates and birth rates from traditional levels (the so-called demographic transition); the establishment of an effective, fairly centralized bureaucratic government; the creation of an educational system capable of training and socializing the children of the society to a level compatible with their capacities and best contemporary knowledge; and, of course, the acquisition of the ability and means to use an up-to-date technology."

Source: econterms

Modigliani-Miller theorem

that the total value of the bonds and equities issued by a firm in a model is independent of the number of bonds outstanding or their interest rate.

The theorem was shown by Modigliani and Miller, 1958 in a particular context with no fixed costs, transactions costs, asymmetric information, and so forth. Analogous theorems are shown in various contexts. The assumptions made by such theorems offer a way of organizing what it would be that makes corporations choose to offer various levels of bonds. The choice of numbers and types of bonds and stocks a corporation offers is the choice of capital structure. Among the factors affecting the capital structure of a firm are taxes, bankruptcy costs, agency costs, signalling, bargaining position in litigation, and differences between firms and investors in access to capital markets.

Source: econterms

moment-generating function

Denoted M(t) or MX(t), and describes a probability distribution. A moment-generating function is defined for any random variable X with a pdf f(x). M(t) is defined to be E[etX], which is the integral from minus infinity to infinity of etXf(x). A use for these is that the tth moment of X is M(t)(0), that is the tth derivative of M() at zero.

Source: econterms

monetarism

The view that monetary policy is a prime source of the business cycle, and that the time path of the money stock is a good index of monetary policy. As presented by Milton Friedman and Anna Schwartz, monetarism emphasizes the relation between the level of the money stock and the level of output without a detailed theory of why changes in the money stock are not neutral in the short run. Later versions posed an explicit basis for noneutrality in the form of barriers to information flow about prices.

In policy terms monetarists, notably Friedman, advocated a monetary rule, that is, a steady growth in the money supply to match economic growth, without allowing central banks room for discretion. If the rule is credible, public expectations of inflation be low, and thus inflation itself, if high, would fall almost immediately.

Source: econterms

monetarist view

In extreme form: that only the quantity of money matters by way of aggregate demand policy. Relevant only in an overheated economy (Branson p 391).

Source: econterms

monetary base

In a modern industrialized monetary economy, the monetary base is made up of (1) the currency held by individuals and firms and (2) bank reserves kept within a bank or on deposit at the central bank.

Source: econterms

monetary regime

"A monetary regime can be thought of as a set of rules governing the objectives and the actions of the monetary authority."

Examples: (1) "A gold standard is one example of a monetary regime -- the monetary authority is obligated to maintain instant convertibility between its liabilities and the gold. Th monetary authority may have considerable room to maneuver in that monetary regime, but it can do nothing that would cause it to violate its commitment."
(2) "The same remarks would apply to a monetary regime obligating the monetary authority to maintain a fixed exchange rate between its own and another currency." (3) "A monetary regime of a very different sort could be based on a Monetarist rule specifying the rate of growth of some monetary aggregate. The basic distinction is between regimes based on a convertibility or redemption principle and those based on a quantity principle."

Source: econterms

monetary rule

See the policy discussion in monetarism.

Source: econterms

monetized economy

A model economy that has a medium of exchange: money

Source: econterms

money

A good that acts as a medium of exchange in transactions. Classically it is said that money acts as a unit of account, a store of value, and a medium of exchange. Most authors find that the first two are nonessential properties that follow from the third. In fact, other goods are often better than money at being intertemporal stores of value, since most monies degrade in value over time through inflation or the overthrow of governments.

Theory: Ostroy and Starr, 1990, p. 25, define money in certain models "as a commodity of positive price and zero transaction cost that does not directly enter in production or consumption."

History: See this Web site on the History of Money.

Related terms: money

Source: econterms

money illusion

'the belief that money [that is, a particular currency] represents a constant value'

Source: econterms

money-in-the-utility-function models

A modeling idea. In a basic Arrow-Debreu general equilibrium there is no need for money because exchanges are automatic, through a 'Walrasian auctioneer'. To study monetary phenomena, a class of models was made in which money was a good that brought direct utility to the agent holding it; e.g., a utility function took the form u(x,m) where x is a vector of other commodities, and m is a scalar quantity of real money held by the agent. Using this mechanism money can have a positive price in equilibrium and monetary effects can be seen in such models. Contrast 'cash-in-advance constraint' for an alternative approach.

Source: econterms

monopoly

If a certain firm is the only one that can produce a certain good, it has a monopoly in the market for that good.

Source: econterms

monopoly power

The degree of power held by the seller to set the price for a good. In U.S. antitrust law monopoly power is not measured by market share. (Salon magazine, 1998/11/11)

Source: econterms

monopsony

A state in which demand comes from one source. If there is only one customer for a certain good, that customer has a monopsony in the market for that good. Analogous to monopoly, but on the demand side not the supply side. A common theoretical implication is that the price of the good is pushed down near the cost of production. The price is not predicted to go to zero because if it went below where the suppliers are willing to produce, they won't produce. Market power is a continuum from perfectly competitive to monopsony and there's an extensive practice/industry/science of measuring the degree of market power.

Examples: For workers in an isolated company town, created by and dominated by one employer, that employer is a monopsonist for some kinds of employment. For some kinds of U.S. medical care, the government program Medicare is a monopsony.

Source: econterms

monotone likelihood ratio property

A property of a set of pdfs which is assumed in theoretical models to characterize risk and uncertainty because it makes more conclusions feasible and is often plausible.

Example: Let e ('effort') be an input variable into a stochastic production function, and y be the random variable that represent output. Let f(y | e) be the pdf of y for each e. Then the statement that f() has the monotone likelihood ratio property (MLRP) is the same as the statement that:
for e2>e1, f(y|e2)/f(y|e1) is increasing in y.
This says that output is positively related to effort, and something stronger, something like: of two outcomes or ranges of outcomes, the worse one will not become relatively more likely than the better one if effort were to rise. By relatively more likely is meant that the likelihood ratio, above, rises.

The set of pdfs for which the MLRP is assumed above is the set of f()'s indexed by values of e. Each holds that specified relationship to the others. In practice the MLRP assumption tends to rule out multimodal classes of distributions, and this is its main effect. (By multimodal we mean those with multiple-peaked pdfs.)

Normally e is scalar, taking on either discrete or continuous sets of values. An analogous definition, for a multidimensional (vector) e, is feasible. Whether it is used in existing models is not known to this author.

Source: econterms

monotone operator

An operator that preserves inequalities of its arguments. That is, if T is a monotone operator, then: (i) iff x>y, then Tx>Ty, and iff x<y, then Tx<Ty.

Same basic meaning as monotone transformation.

The most common monotone operator is the natural log function. For example in maximum likelihood estimation, one usually maximizes the log of the likelihood function, not the likelihood function itself, because this is more tractable and the log is a monotone operator so it doesn't change the answer.

Source: econterms

monotone transformation

A transformation that preserves inequalities of its arguments. That is, if T is a monotone transformation, then: (i) iff x>y, then Tx>Ty, and iff x<y, then Tx<Ty.

Same basic meaning as monotone operator.

Source: econterms

Monte Carlo simulations

These are data obtained by simulating a statistical model in which all parameters are numerically specified.

One might use Monte Carlo simulations to test how an estimation procedure would behave, for example under conditions when exact analytic descriptions of the performance of the estimation are not algebraically feasible, or when one wants to verify that one's analytic calculation for a confidence interval is correct.

Source: econterms

Moore-Penrose inverse

Same as pseudoinverse.

Source: econterms

morbidity

Incidence of ill health. It is measured in various ways, often by the probability that a randomly selected individual in a population at some date and location would become seriously ill in some period of time. Contrast to mortality.

Source: econterms

mortality

Incidence of death in a population. It is measured in various ways, often by the probability that a randomly selected individual in a population at some date and location would die in some period of time. Contrast to morbidity.

Source: econterms

MSA

Same as SMSA.

Source: econterms

MSE

mean squared error (which see)

Source: econterms

multi-factor productivity

Same as total factor productivity, a certain type of Solow residual.

MFP = d(ln f)/dt = d(ln Y)/dt - sLd(ln L)/dt - sKd(ln K)/dt where f is the global production function; Y is output; t is time; sL is the share of input costs attributable to labor expenses; sK is the share of input costs attributable to capital expenses; L is a dollar quantity of labor; K is a dollar quantity of capital.

Source: econterms

multinomial

In the context of discrete choice models, multinomial means there are more than two possible values of the dependent variable, the choice, which is a scalar.

For specific constructions see multinomial logit and multinomial probit.

Source: econterms

multinomial logit

Relatively easy to compute but has the problematic IIA property by construction. Multinomial probit with correlation between structural residuals does not suffer from the IIA problem but is computationally expensive. (Ed.: I don't know why the IIA problem gets sucked into this when the actual different between logit and probit is the functional form.) Multinomial logit is available in more software packages than is multinomial probit.

Source: econterms

multinomial probit

Multinomial probit with correlation between structural residuals does not suffer from the IIA problem but is computationally expensive. Multinomial logit which solves a similar problem is relatively easy to compute but has the problematic IIA property by construction. (Ed.: I don't know why the IIA problem gets sucked into this when the actual different between logit and probit is the functional form.) Multinomial logit is available in more software packages than is multinomial probit.

Source: econterms

multivariate

A discrete choice model in which the choice is made from a set with more than one dimension is said to be a multivariate discrete choice model.

Source: econterms

Mundell-Tobin effect

That nominal interest rates would rise less than one-for-one with inflation because in response to inflation the public would hold less in money balances and more in other assets, which would drive interest rates down.

Source: econterms

mutatis mutandis

"The necessary changes having been made; substituting new terms."

Source: econterms

MVN

An abbrevation for 'multivariate normal' distribution.

Source: econterms

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