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In [[statistics]], '''truncation''' results in values that are limited above or below, resulting in a '''truncated sample'''.<ref>[[Yadolah Dodge|Dodge, Y.]] (2003) ''The Oxford Dictionary of Statistical Terms''. OUP. ISBN 0-19-920613-9</ref> Truncation is similar to but distinct from the concept of [[Censoring (statistics)|statistical censoring]]. A truncated sample can be thought of as being equivalent to an underlying sample with all values outside the bounds entirely omitted, with not even a count of those omitted being kept. If the sample had been censored, a record would be of those that were censored, consisting of a note of whether the lower or upper bound had been passed and the value of the bound.
{{TOCright}}
'''Gossen's Second “Law”''', named for [[Hermann Heinrich Gossen]] (1810–1858), is the assertion that an [[Economics|economic]] agent will allocate his or her expenditures such that the ratio of the [[marginal utility]] of each [[Good (economics)|good]] or [[Service (economics)|service]] to its price (the marginal expenditure necessary for its acquisition) is equal to that for every other good or service. Formally,
:<math>\frac{\partial U/\partial x_i}{p_i}=\frac{\partial U/\partial x_j}{p_j}~\forall\left(i,j\right)</math>
where
* <math>U</math> is [[utility]]
* <math>x_i</math> is quantity of the <math>i</math>-th good or service
* <math>p_i</math> is the price of the <math>i</math>-th good or service


==Applications==
== Informal derivation ==


Usually the values that [[insurance adjuster]]s receive are either left-truncated, right-censored or bothFor example, if policyholders are subject to a policy limit, u, then any loss amounts that are actually above u are reported to the insurance company as being exactly u because u is the amount the [[insurance company|insurance companies]] pay.  The insurance company knows that the actual loss is greater than ''u'' but they don't know what it is.  On the other hand, left truncation occurs when policyholders are subject to a deductibleIf policyholders are subject to a deductible d, any loss amount that is less than d will not even be reported to the insurance company.  If there is a claim on a policy limit of u and a deductible of d, any loss amount that is greater than u will be reported to the insurance company as a loss of u-d because that is the amount the insurance company has to pay.  Therefore insurance loss data is left-truncated because the insurance company doesn't know if there are values below the deductible d because policyholders won't make a claim.  The insurance loss is also right censored if the loss is greater than u because u is the most the insurance company will pay, so it only knows that your claim is greater than u, not what the claim amount is exactly.
Imagine that an agent has spent money on various sorts of goods or servicesIf the last unit of currency spent on goods or services of one sort bought a quantity with <em>less</em> marginal utility than that which would have been associated with the quantity of another sort that could have been bought with the money, then the agent would have been ''better off'' instead buying more of that other good or serviceAssuming that goods and services are continuously divisible, the only way that it is possible that the marginal expenditure on one good or service should not yield more utility than the marginal expenditure on the other (or ''vice versa'') is if the marginal expenditures yield ''equal'' utility.


==Probability distributions==
== Formal derivation ==
{{Main|Truncated distribution}}


Truncation can be applied to any [[probability distribution]] and will lead to a new distribution, not usually one within the same family. Thus, if a random variable ''X'' has ''F''(''x'') as its distribution function, the new random variable ''Y'' defined as having the distribution of ''X'' truncated to the semi-open interval (a,b] has the distribution function
Assume that utility, goods, and services have the requisite properties so that <math>\partial U/\partial x_i</math> is [[Well-defined|well defined]] for each good or service.  An agent then optimizes
:<math>U\left(x_1 ,x_2 ,\dots,x_n\right)</math>
subject to a [[budget constraint]]
:<math>W\geq\sum_{i=1}^n \left(p_i\cdot x_i \right)</math>
where
* <math>W</math> is the total available sum of money
Using the method of [[Lagrange multipliers]], one constructs the function
:<math>\mathcal{L}\left(x_1 ,x_2 ,\dots,x_n ,\lambda\right)=U\left(x_1 ,x_2 ,\dots,x_n\right)+\lambda\cdot\left[W-\sum_{i=1}^n \left(p_i\cdot x_i \right)\right]</math>
and finds the first-order conditions for optimization as
:<math>\frac{\partial\mathcal{L}}{\partial\lambda}=0</math>
(which simply implies that all of <math>W</math> will be spent) and
:<math>\frac{\partial\mathcal{L}}{\partial x_i}=0~~\forall i</math>
so that
:<math>\frac{\partial U}{\partial x_i}-\lambda\cdot p_i =0~~\forall i</math>
which is algebraically equivalent to
:<math>\frac{\partial U/\partial x_i}{p_i}=\lambda~~\forall i</math>
Since every such ratio is equal to <math>\lambda</math>, the ratios are all equal one to another:
:<math>\frac{\partial U/\partial x_i}{p_i}=\frac{\partial U/\partial x_j}{p_j}~\forall\left(i,j\right)</math>


:<math>F_Y(y)=\frac{F(y)-F(a)}{F(b)-F(a)} \,</math>
(Note that, as with any maximization using first-order conditions, the equations will hold only if the utility function satisfies specific concavity requirements and does not have maxima on the edges of the set over which one is maximizing.)


for ''y'' in the interval (''a'', ''b''], and 0 or 1 otherwise. If truncation were to the closed interval [a,b], the distribution function would be
== References ==


:<math>F_Y(y)=\frac{F(y)-F(a-)}{F(b)-F(a-)} \,</math>
* Gossen, Hermann Heinrich; ''Die Entwicklung der Gesetze des menschlichen Verkehrs und der daraus fließenden Regeln für menschliches Handeln'' (1854).  Translated into English as ''The Laws of Human Relations and the Rules of Human Action Derived Therefrom'' (1983) MIT Press, ISBN 0-262-07090-1.


for ''y'' in the interval [''a'', ''b''], and 0 or 1 otherwise.
== See also ==


==Data analysis==
* [[Gossen's laws]]
* [[Hermann Heinrich Gossen]]
* [[Marginal utility]]
* [[Marginalism]]


The analysis of data where observations are treated as being from truncated versions of standard distributions can be undertaken using a [[maximum likelihood]], where the likelihood would be derived from the distribution or density of the truncated distribution. This involves taking account of the factor <math>{F(b)-F(a)}</math> in the modified density function which will depend on the parameters of the original distribution.
{{DEFAULTSORT:Gossen's Second Law}}
[[Category:Marginal concepts]]
[[Category:Consumer theory]]
[[Category:Utility]]


In practice, if the fraction truncated is very small the effect of truncation might be ignored when analysing data. For example, it is common to use a [[normal distribution]] to model data whose values can only be positive but for which the typical range of values is well away from zero: in such cases a truncated or censored version of the normal distribution may formally be preferable (although there would be other alternatives also), but there would be very little change in results from the more complicated analysis. However, software is readily available for maximum likelihood estimation of even moderately complicated models, such as [[regression analysis|regression models]], for truncated data.<ref>Wolynetz, M.S. (1979) ''Maximum Likelihood estimation in a Linear model from Confined and Censored Normal Data''. J.Roy.Statist.Soc (Series C), 28(2), 195&ndash;206</ref>
[[nl:Tweede wet van Gossen]]
 
==See also==
*[[Censoring (statistics)]]
*[[Trimmed estimator]]
*[[Truncated (polyhedron)]]
*[[Truncated mean]]
*[[Truncated dependent variable]]
 
==References==
<references/>
 
[[Category:Statistical data types]]
[[Category:Theory of probability distributions]]

Revision as of 11:59, 17 August 2014

Template:TOCright Gossen's Second “Law”, named for Hermann Heinrich Gossen (1810–1858), is the assertion that an economic agent will allocate his or her expenditures such that the ratio of the marginal utility of each good or service to its price (the marginal expenditure necessary for its acquisition) is equal to that for every other good or service. Formally,

where

Informal derivation

Imagine that an agent has spent money on various sorts of goods or services. If the last unit of currency spent on goods or services of one sort bought a quantity with less marginal utility than that which would have been associated with the quantity of another sort that could have been bought with the money, then the agent would have been better off instead buying more of that other good or service. Assuming that goods and services are continuously divisible, the only way that it is possible that the marginal expenditure on one good or service should not yield more utility than the marginal expenditure on the other (or vice versa) is if the marginal expenditures yield equal utility.

Formal derivation

Assume that utility, goods, and services have the requisite properties so that is well defined for each good or service. An agent then optimizes

subject to a budget constraint

where

Using the method of Lagrange multipliers, one constructs the function

and finds the first-order conditions for optimization as

(which simply implies that all of will be spent) and

so that

which is algebraically equivalent to

Since every such ratio is equal to , the ratios are all equal one to another:

(Note that, as with any maximization using first-order conditions, the equations will hold only if the utility function satisfies specific concavity requirements and does not have maxima on the edges of the set over which one is maximizing.)

References

  • Gossen, Hermann Heinrich; Die Entwicklung der Gesetze des menschlichen Verkehrs und der daraus fließenden Regeln für menschliches Handeln (1854). Translated into English as The Laws of Human Relations and the Rules of Human Action Derived Therefrom (1983) MIT Press, ISBN 0-262-07090-1.

See also

nl:Tweede wet van Gossen