Editing Price elasticity of demand (section)

==Selected price elasticities==
Various research methods are used to calculate the price elasticities in real life, including analysis of historic sales data, both public and private, and use of present-day surveys of customers' preferences to build up [[marketing research|test markets]] capable of modelling such changes.<ref>{{cite web|url=https://www.economicsdiscussion.net/demand/empirical-estimation-of-demand-top-10-techniques/19772|title=Empirical Estimation of Demand: Top 10 Techniques|access-date=11 December 2020|author=Samia Rekhi|work=economicsdiscussion.net|date=16 May 2016}}</ref>  Alternatively, [[conjoint analysis]] (a ranking of users' preferences which can then be statistically analysed) may be used.<ref>Png, Ivan (1999). pp.&nbsp;79–80.</ref> Approximate estimates of price elasticity can be calculated from the [[income elasticity of demand]], under conditions of preference independence. This approach has been empirically validated using bundles of goods (e.g. food, healthcare, education, recreation, etc.).<ref>{{Cite journal|last=Sabatelli|first=Lorenzo|date=2016-03-21|title=Relationship between the Uncompensated Price Elasticity and the Income Elasticity of Demand under Conditions of Additive Preferences|journal=PLOS ONE|volume=11|issue=3|pages=e0151390|doi=10.1371/journal.pone.0151390|issn=1932-6203|pmc=4801373|pmid=26999511|bibcode=2016PLoSO..1151390S|arxiv=1602.08644|doi-access=free}}</ref>

Though elasticities for most demand schedules vary depending on price, they can be modeled assuming constant elasticity.<ref>{{cite web|url=http://wpscms.pearsoncmg.com/aw_perloff_microecon_3/9/2365/605606.cw/index.html|title=Constant Elasticity Demand and Supply Curves (Q=A*P^c)|access-date=26 April 2010|url-status=dead|archive-url=https://web.archive.org/web/20110113151547/http://wpscms.pearsoncmg.com/aw_perloff_microecon_3/9/2365/605606.cw/index.html|archive-date=13 January 2011}}</ref>  Using this method, the elasticities for various goods—intended to act as examples of the theory described above—are as follows. For suggestions on why these goods and services may have the elasticity shown, see the above section on determinants of price elasticity.

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* Cigarettes (US)<ref name="ReferenceB">Perloff, J. (2008). p.&nbsp;97.</ref>
** −0.3 to −0.6 (general)
** −0.6 to −0.7 (youth)
* [[Alcohol tax|Alcoholic beverages]] (US)<ref>Chaloupka, Frank J.; Grossman, Michael; Saffer, Henry (2002); Hogarty and Elzinga (1972) cited by Douglas 
 (1993).</ref>
**−0.3 or −0.7 to −0.9 as of 1972 (beer)
**−1.0 (wine)
**−1.5 (spirits)
* Airline travel (US)<ref name=PindyckRubinfeldPage381>Pindyck; Rubinfeld (2001). p.&nbsp;381.; Steven Morrison in Duetsch (1993), p.&nbsp;231.</ref>
**−0.3 (first class)
**−0.9 (discount)
**−1.5 (for pleasure travelers)
* Livestock
** −0.5 to −0.6  ([[broiler chicken]]s)<ref>Richard T. Rogers in Duetsch (1993), p.&nbsp;6.</ref>
* Oil (World)
**−0.4
* Car fuel<ref>{{cite journal|title=Demand for gasoline is more price-inelastic than commonly thought|journal=Energy Economics|doi=10.1016/j.eneco.2011.09.003 | volume=34|pages=201–207|year=2012|last1=Havranek|first1=Tomas|last2=Irsova|first2=Zuzana|last3=Janda|first3=Karel|bibcode=2012EneEc..34..201H |s2cid=55215422 |url=https://cloudfront.escholarship.org/dist/prd/content/qt0m94j50t/qt0m94j50t.pdf}}</ref>
**−0.09 (short run)
**−0.31 (long run)
**−0.085 to −0.13 (non-linear with price change in the <br />short-run for Saudi Arabia in 2013}<ref>{{cite journal|title=The responsiveness of fuel demand to gasoline price change in passenger transport: a case study of Saudi Arabia|journal=Energy Efficiency|doi=10.1007/s12053-018-9628-6 | volume=11|issue=6|pages=1341–1358|year=2018|last1=Algunaibet|first1=Ibrahim|last2=Matar|first2=Walid|bibcode=2018EnEff..11.1341A |s2cid=157328882}}</ref>
* Cinema visits (US)
**−0.87 (general)<ref name="Samuelson 2001"/>
* live performing arts (theater, etc.)
** −0.4 to −0.9<ref>Heilbrun and Gray (1993, p.&nbsp;94) cited in Vogel (2001)</ref>
* Medicine (US)
**−0.31 (medical insurance)<ref name="Samuelson 2001">Samuelson; Nordhaus (2001).</ref>
**−0.03 to −0.06 ([[Pediatrics|pediatric]] visits)<ref>Goldman and Grossman (1978) cited in Feldstein (1999), p.&nbsp;99</ref>
* Patents
**−0.45 <ref name="de Rassenfosse and van Pottelsberghe">{{Cite journal|last1=de Rassenfosse|first1=Gaétan|last2=van Pottelsberghe de la Potterie|first2=Bruno|year=2007|title=Per un pugno di dollari: A first look at the price elasticity of patents|journal=Oxford Review of Economic Policy|volume=23|doi=10.2139/ssrn.1743840 |s2cid=219337939 |url=https://dx.doi.org/10.2139/ssrn.1743840|author-link=Gaétan de Rassenfosse}}</ref>
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* Rice<ref name="Perloff, Microeconomics Theory 2008">Perloff, J. (2008).</ref>
**−0.47 (Austria)
**−0.8{{0}} (Bangladesh)
**−0.8{{0}} (China)
**−0.25 (Japan)
**−0.55 (US)
* Trademarks
**−0.25 to −0.40 (international market) <ref>{{Cite journal|last=de Rassenfosse |first=Gaétan |title=On the price elasticity of demand for trademarks|date=2020|journal=Industry and Innovation|volume=27|issue=1–2 |pages=11–24 |doi=10.1080/13662716.2019.1591939 |url=https://doi.org/10.1080/13662716.2019.1591939|author-link=Gaétan de Rassenfosse}}</ref>
* Transport
** −0.20 (bus travel US)<ref name="Samuelson 2001"/>
** −2.8{{0}} (Ford compact automobile)<ref>Goodwin; Nelson; Ackerman; Weisskopf (2009). p.&nbsp;124.</ref>
** −0.52 (commuter parking)<ref>Lehner, S.; Peer, S. (2019), The price elasticity of parking: A meta-analysis, Transportation Research Part A: Policy and Practice, Volume 121, March 2019, pages 177−191" web|url=https://doi.org/10.1016/j.tra.2019.01.014</ref>
*Cannabis (US)<ref>Davis, A.; Nichols, M. (2013), The Price Elasticity of Marijuana Demand"</ref>
**−0.655 
* Soft drinks
**−0.8 to −1.0 (general)<ref>Brownell, Kelly D.; Farley, Thomas; Willett, Walter C. et al. (2009).</ref>
**−3.8 ([[Coca-Cola]])<ref name="ayers120">Ayers; Collinge (2003). p.&nbsp;120.</ref>
**−4.4 ([[Mountain Dew]])<ref name="ayers120"/>
* Steel
**−0.2 to −0.3<ref name="Duetsch 1993 p.&nbsp;147">Barnett and Crandall in Duetsch (1993), p.&nbsp;147</ref>
* Telecommunications
**−0.405 (mobile)<ref>{{cite web|url=https://www.brookings.edu/wp-content/uploads/1997/01/1997_bpeamicro_hausman.pdf|title=Valuing the Effect of Regulation on New Services in Telecommunications|publisher=Jerry A. Hausman|access-date=29 September 2016}}</ref>
**−0.434 (broadband)<ref>{{cite web|url=http://spcnetwork.eu/uploads/Broadband_Elasticity_Paper_2008.pdf|title=Price and Income Elasticity of Demand for Broadband Subscriptions: A Cross-Sectional Model of OECD Countries|publisher=SPC Network|access-date=29 September 2016}}</ref>
*Eggs
**−0.1 (US: household only)<ref>Krugman and Wells (2009) p.&nbsp;147.</ref>
**−0.35 (Canada)<ref>{{cite web|url=http://www.agr.gc.ca/poultry/prinde3_eng.htm#sec312|archive-url=https://web.archive.org/web/20110708130337/http://www.agr.gc.ca/poultry/prinde3_eng.htm#sec312|url-status=dead|archive-date=8 July 2011|title=Profile of The Canadian Egg Industry|publisher=Agriculture and Agri-Food Canada|access-date=9 September 2010}}</ref>
**−0.55 (South Africa)<ref>{{cite journal |title=Demand Analysis of Eggs in South Africa |first1=R. C. G. |last1=Cleasby |first2=G. F. |last2=Ortmann |journal=Agrekon |volume=30 |issue=1 |year=1991 |pages=34–36 |doi=10.1080/03031853.1991.9524200 }}</ref>
*Golf
**−0.3 to −0.7<ref name="Duetsch 1993 p.&nbsp;147"/>
*University education
** near 0<ref>{{Cite journal|title=Tuition Fees and University Enrolment: A Meta-Regression Analysis|journal=Oxford Bulletin of Economics and Statistics|volume=80|issue=6|pages=1145–1184|doi=10.1111/obes.12240|year=2018|last1=Havranek|first1=Tomas|last2=Irsova|first2=Zuzana|last3=Zeynalova|first3=Olesia|s2cid=158193395|doi-access=free}}</ref>

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