View source for Stock sampling

'''Stock sampling''' is [[Sampling (statistics)|sampling]] people in a certain state at the time of the survey.{{clarify |date=January 2018 |reason="the" survey? What survey? }} This is in contrast to [[Flow sampling|flow sampling]], where the relationship of interest deals with duration or [[Survival analysis|survival analysis]].<ref name="CameronTrivedi2005"/> In stock sampling, rather than focusing on transitions within a certain time interval, we only have observations at a certain point in time. This can lead to both left and right [[Censoring (statistics)|censoring]].<ref name="Wooldridge2002"/> Imposing the same model on data that have been generated under the two different sampling regimes can lead to research reaching fundamentally different conclusions if the joint distribution across the flow and stock samples differ sufficiently.<ref name="ChesherLancaster1981"/>

Stock sampling essentially leads to a [[Sampling bias|sample selection]] problem. This selection issue is akin to the [[Truncated regression model|truncated regression model]] where we face selection on the basis of a binary response variable, but the problem has been referred to as [[Medicine:Length time bias|length-biased sampling]] in this specific context.<ref name="Kiefer1988"/> Consider, for example, the figure below that plots some duration data. If a researcher would revert to stock sampling and only sample and survey individuals at the survey dates (i.e. the survey data, 12 months after the survey date, etc.), there is a high likelihood the short duration spells will be omitted from the sample, as some durations shorter than 12 months are necessarily omitted from the sample:<ref name="Wooldridge2002"/>

[[File:Stock sampling photo.png|center|frame|Source:  Cameron A. C. and P. K. Trivedi (2005): Microeconometrics: Methods and Applications. Cambridge University Press, New York.]]

A number of methods to adjust for these sampling issues have been proposed. One can appropriately adjust the [[Maximum likelihood estimation|maximum likelihood estimation]] for censored flow data for the sample selection, or use [[Nonparametric statistics|nonparametric estimation]] methods for censored flow data for the sample selection, or use nonparametric estimation methods for censored data.<ref name="LewbelLinton2002"/>

== References ==
{{Reflist|refs=
<ref name="CameronTrivedi2005">{{cite book |last1=Cameron |first1=A. C. |first2=P. K. |last2=Trivedi |year=2005 |title=Microeconometrics: Methods and Applications |publisher=Cambridge University Press |location=New York |isbn=978-0-521-84805-3 }}</ref>
<ref name="Wooldridge2002">{{cite book |last=Wooldridge |first=J. |year=2002 |title=Econometric Analysis of Cross Section and Panel Data |url=https://archive.org/details/econometricanaly0000wool |url-access=registration |publisher=MIT Press |location=Cambridge, Mass |isbn=978-0-262-23219-7 }}</ref>
<ref name="ChesherLancaster1981">{{cite journal |last1=Chesher |first1=A. |first2=T. |last2=Lancaster |year=1981 |title=Stock and Flow Sampling |journal=[[Finance:Economics Letters|Economics Letters]] |volume=8 |issue=1 |pages=63–65 |doi=10.1016/0165-1765(81)90094-X }}</ref>
<ref name="Kiefer1988">{{cite journal |last=Kiefer |first=N. M. |year=1988 |title=Economic Duration Data and Hazard Functions |journal=[[Finance:Journal of Economic Literature|Journal of Economic Literature]] |volume=26 |issue=2 |pages=646–679 |jstor=2726365 }}</ref>
<ref name="LewbelLinton2002">{{cite journal |last1=Lewbel |first1=A. |first2=O. |last2=Linton |year=2002 |title=Nonparametric Censored and Truncated Regression |journal=[[Finance:Econometrica|Econometrica]] |volume=70 |issue=2 |pages=765–779 |doi=10.1111/1468-0262.00304 |s2cid=120113700 |url=http://eprints.lse.ac.uk/2060/1/Nonparametric_Censored_and_Truncated_Regression.pdf }}</ref>
}}

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