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Tobin's q [a] (or the q ratio, and Kaldor's v), is the ratio between a physical asset's market value and its replacement value. It was first introduced by Nicholas Kaldor in 1966 in his paper: Marginal Productivity and the Macro-Economic Theories of Distribution: Comment on Samuelson and Modigliani .
Mathematically, the markup rule can be derived for a firm with price-setting power by maximizing the following expression for profit: = () where Q = quantity sold, P(Q) = inverse demand function, and thereby the price at which Q can be sold given the existing demand C(Q) = total cost of producing Q.
However, at 95% confidence, Q = 0.455 < 0.466 = Q table 0.167 is not considered an outlier. McBane [ 1 ] notes: Dixon provided related tests intended to search for more than one outlier, but they are much less frequently used than the r 10 or Q version that is intended to eliminate a single outlier.
The index ranges from 0 to 1. A perfectly competitive firm charges P = MC, L = 0; such a firm has no market power. An oligopolist or monopolist charges P > MC, so its index is L > 0, but the extent of its markup depends on the elasticity (the price-sensitivity) of demand and strategic interaction with competing firms. The index rises to 1 if ...
All superlative indices produce similar results and are generally the favored formulas for calculating price indices. [14] A superlative index is defined technically as "an index that is exact for a flexible functional form that can provide a second-order approximation to other twice-differentiable functions around the same point." [15]
Markup is the difference between price and marginal cost. The formula states that markup as a percentage of price equals the negative (and hence the absolute value) of the inverse of the elasticity of demand. [33] A lower elasticity of demand implies a higher markup at the profit maximising equilibrium. [31]
After calculating your debt-to-income ratio (DTI), check the lender’s requirements. If your DTI is well below 43 percent or the lender’s threshold and you meet other eligibility criteria, you ...
The q-value can be interpreted as the false discovery rate (FDR): the proportion of false positives among all positive results. Given a set of test statistics and their associated q-values, rejecting the null hypothesis for all tests whose q-value is less than or equal to some threshold ensures that the expected value of the false discovery rate is .