A method for measuring treatment effects on the treated without randomization

This paper contributes to the literature on the estimation of causal effects by providing an analytical formula for individual specific treatment effects and an empirical methodology that allows us to estimate these effects. We derive the formula from a general model with minimal restrictions, unkno...
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Autor*in:	Swamy, Paravastu A. V. B. [verfasserIn] Hall, Stephen G. - 1953- [verfasserIn] Tavlas, George S. [verfasserIn] Chang, I-Lok [verfasserIn] Gibson, Heather D. - 1961- [verfasserIn] Greene, William - 1951- [verfasserIn] Mehta, Jatinder S. [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	June 2016

Übergeordnetes Werk:	Enthalten in: Econometrics - Basel : MDPI, 2013, 4(2016), 2 vom: Juni, Seite 1-23
Übergeordnetes Werk:	volume:4 ; year:2016 ; number:2 ; month:06 ; pages:1-23

Links:	Volltext Volltext

DOI / URN:	10.3390/econometrics4020019

Katalog-ID:	863513778

Internformat


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245	1	2	\|a A method for measuring treatment effects on the treated without randomization \|c P.A.V.B. Swamy, Stephen G. Hall, George S. Tavlas, I-Lok Chang, Heather D. Gibson, William H. Greene and Jatinder S. Mehta
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982			\|2 26 \|1 00 \|x DE-206 \|8 56 \|a non-experimental situation

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publishDate	2016
allfields	10.3390/econometrics4020019 doi 10419/171881 hdl (DE-627)863513778 (DE-576)9863513776 (DE-599)GBV863513778 DE-627 ger DE-627 rda eng C13 C51 jelc Swamy, Paravastu A. V. B. verfasserin (DE-588)170006409 (DE-627)060009284 (DE-576)130923478 aut A method for measuring treatment effects on the treated without randomization P.A.V.B. Swamy, Stephen G. Hall, George S. Tavlas, I-Lok Chang, Heather D. Gibson, William H. Greene and Jatinder S. Mehta June 2016 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier This paper contributes to the literature on the estimation of causal effects by providing an analytical formula for individual specific treatment effects and an empirical methodology that allows us to estimate these effects. We derive the formula from a general model with minimal restrictions, unknown functional form and true unobserved variables such that it is a credible model of the underlying real world relationship. Subsequently, we manipulate the model in order to put it in an estimable form. In contrast to other empirical methodologies, which derive average treatment effects, we derive an analytical formula that provides estimates of the treatment effects on each treated individual. We also provide an empirical example that illustrates our methodology. Hall, Stephen G. 1953- verfasserin (DE-588)124941907 (DE-627)368374475 (DE-576)168498510 aut Tavlas, George S. verfasserin (DE-588)12495202X (DE-627)368961532 (DE-576)294585931 aut Chang, I-Lok verfasserin (DE-588)171710320 (DE-627)061945315 (DE-576)132483556 aut Gibson, Heather D. 1961- verfasserin (DE-588)129664545 (DE-627)477109012 (DE-576)166309664 aut Greene, William 1951- verfasserin (DE-588)124700551 (DE-627)364372486 (DE-576)166603910 aut Mehta, Jatinder S. verfasserin aut Enthalten in Econometrics Basel : MDPI, 2013 4(2016), 2 vom: Juni, Seite 1-23 Online-Ressource (DE-627)74684042X (DE-600)2717594-7 (DE-576)382897196 2225-1146 nnns volume:4 year:2016 number:2 month:06 pages:1-23 http://hdl.handle.net/10419/171881 Resolving-System kostenfrei Volltext http://dx.doi.org/10.3390/econometrics4020019 Resolving-System Volltext GBV_USEFLAG_U GBV_ILN_26 ISIL_DE-206 SYSFLAG_1 GBV_KXP GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2009 GBV_ILN_2014 GBV_ILN_2034 GBV_ILN_2055 GBV_ILN_2108 GBV_ILN_2111 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 GBV_ILN_2403 GBV_ILN_2403 ISIL_DE-LFER zbwolc20160724 AR 4 2016 2 6 1-23 26 01 0206 1626477388 x1k 21-07-16 2403 01 DE-LFER 3495673385 00 --%%-- --%%-- n --%%-- l01 23-07-19 2403 01 DE-LFER http://hdl.handle.net/10419/171881 26 00 DE-206 56 causality 26 00 DE-206 56 real-world relationship 26 00 DE-206 56 unique error term 26 00 DE-206 56 treatment effect 26 00 DE-206 56 non-experimental situation
spelling	10.3390/econometrics4020019 doi 10419/171881 hdl (DE-627)863513778 (DE-576)9863513776 (DE-599)GBV863513778 DE-627 ger DE-627 rda eng C13 C51 jelc Swamy, Paravastu A. V. B. verfasserin (DE-588)170006409 (DE-627)060009284 (DE-576)130923478 aut A method for measuring treatment effects on the treated without randomization P.A.V.B. Swamy, Stephen G. Hall, George S. Tavlas, I-Lok Chang, Heather D. Gibson, William H. Greene and Jatinder S. Mehta June 2016 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier This paper contributes to the literature on the estimation of causal effects by providing an analytical formula for individual specific treatment effects and an empirical methodology that allows us to estimate these effects. We derive the formula from a general model with minimal restrictions, unknown functional form and true unobserved variables such that it is a credible model of the underlying real world relationship. Subsequently, we manipulate the model in order to put it in an estimable form. In contrast to other empirical methodologies, which derive average treatment effects, we derive an analytical formula that provides estimates of the treatment effects on each treated individual. We also provide an empirical example that illustrates our methodology. Hall, Stephen G. 1953- verfasserin (DE-588)124941907 (DE-627)368374475 (DE-576)168498510 aut Tavlas, George S. verfasserin (DE-588)12495202X (DE-627)368961532 (DE-576)294585931 aut Chang, I-Lok verfasserin (DE-588)171710320 (DE-627)061945315 (DE-576)132483556 aut Gibson, Heather D. 1961- verfasserin (DE-588)129664545 (DE-627)477109012 (DE-576)166309664 aut Greene, William 1951- verfasserin (DE-588)124700551 (DE-627)364372486 (DE-576)166603910 aut Mehta, Jatinder S. verfasserin aut Enthalten in Econometrics Basel : MDPI, 2013 4(2016), 2 vom: Juni, Seite 1-23 Online-Ressource (DE-627)74684042X (DE-600)2717594-7 (DE-576)382897196 2225-1146 nnns volume:4 year:2016 number:2 month:06 pages:1-23 http://hdl.handle.net/10419/171881 Resolving-System kostenfrei Volltext http://dx.doi.org/10.3390/econometrics4020019 Resolving-System Volltext GBV_USEFLAG_U GBV_ILN_26 ISIL_DE-206 SYSFLAG_1 GBV_KXP GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2009 GBV_ILN_2014 GBV_ILN_2034 GBV_ILN_2055 GBV_ILN_2108 GBV_ILN_2111 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 GBV_ILN_2403 GBV_ILN_2403 ISIL_DE-LFER zbwolc20160724 AR 4 2016 2 6 1-23 26 01 0206 1626477388 x1k 21-07-16 2403 01 DE-LFER 3495673385 00 --%%-- --%%-- n --%%-- l01 23-07-19 2403 01 DE-LFER http://hdl.handle.net/10419/171881 26 00 DE-206 56 causality 26 00 DE-206 56 real-world relationship 26 00 DE-206 56 unique error term 26 00 DE-206 56 treatment effect 26 00 DE-206 56 non-experimental situation
allfields_unstemmed	10.3390/econometrics4020019 doi 10419/171881 hdl (DE-627)863513778 (DE-576)9863513776 (DE-599)GBV863513778 DE-627 ger DE-627 rda eng C13 C51 jelc Swamy, Paravastu A. V. B. verfasserin (DE-588)170006409 (DE-627)060009284 (DE-576)130923478 aut A method for measuring treatment effects on the treated without randomization P.A.V.B. Swamy, Stephen G. Hall, George S. Tavlas, I-Lok Chang, Heather D. Gibson, William H. Greene and Jatinder S. Mehta June 2016 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier This paper contributes to the literature on the estimation of causal effects by providing an analytical formula for individual specific treatment effects and an empirical methodology that allows us to estimate these effects. We derive the formula from a general model with minimal restrictions, unknown functional form and true unobserved variables such that it is a credible model of the underlying real world relationship. Subsequently, we manipulate the model in order to put it in an estimable form. In contrast to other empirical methodologies, which derive average treatment effects, we derive an analytical formula that provides estimates of the treatment effects on each treated individual. We also provide an empirical example that illustrates our methodology. Hall, Stephen G. 1953- verfasserin (DE-588)124941907 (DE-627)368374475 (DE-576)168498510 aut Tavlas, George S. verfasserin (DE-588)12495202X (DE-627)368961532 (DE-576)294585931 aut Chang, I-Lok verfasserin (DE-588)171710320 (DE-627)061945315 (DE-576)132483556 aut Gibson, Heather D. 1961- verfasserin (DE-588)129664545 (DE-627)477109012 (DE-576)166309664 aut Greene, William 1951- verfasserin (DE-588)124700551 (DE-627)364372486 (DE-576)166603910 aut Mehta, Jatinder S. verfasserin aut Enthalten in Econometrics Basel : MDPI, 2013 4(2016), 2 vom: Juni, Seite 1-23 Online-Ressource (DE-627)74684042X (DE-600)2717594-7 (DE-576)382897196 2225-1146 nnns volume:4 year:2016 number:2 month:06 pages:1-23 http://hdl.handle.net/10419/171881 Resolving-System kostenfrei Volltext http://dx.doi.org/10.3390/econometrics4020019 Resolving-System Volltext GBV_USEFLAG_U GBV_ILN_26 ISIL_DE-206 SYSFLAG_1 GBV_KXP GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2009 GBV_ILN_2014 GBV_ILN_2034 GBV_ILN_2055 GBV_ILN_2108 GBV_ILN_2111 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 GBV_ILN_2403 GBV_ILN_2403 ISIL_DE-LFER zbwolc20160724 AR 4 2016 2 6 1-23 26 01 0206 1626477388 x1k 21-07-16 2403 01 DE-LFER 3495673385 00 --%%-- --%%-- n --%%-- l01 23-07-19 2403 01 DE-LFER http://hdl.handle.net/10419/171881 26 00 DE-206 56 causality 26 00 DE-206 56 real-world relationship 26 00 DE-206 56 unique error term 26 00 DE-206 56 treatment effect 26 00 DE-206 56 non-experimental situation
allfieldsGer	10.3390/econometrics4020019 doi 10419/171881 hdl (DE-627)863513778 (DE-576)9863513776 (DE-599)GBV863513778 DE-627 ger DE-627 rda eng C13 C51 jelc Swamy, Paravastu A. V. B. verfasserin (DE-588)170006409 (DE-627)060009284 (DE-576)130923478 aut A method for measuring treatment effects on the treated without randomization P.A.V.B. Swamy, Stephen G. Hall, George S. Tavlas, I-Lok Chang, Heather D. Gibson, William H. Greene and Jatinder S. Mehta June 2016 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier This paper contributes to the literature on the estimation of causal effects by providing an analytical formula for individual specific treatment effects and an empirical methodology that allows us to estimate these effects. We derive the formula from a general model with minimal restrictions, unknown functional form and true unobserved variables such that it is a credible model of the underlying real world relationship. Subsequently, we manipulate the model in order to put it in an estimable form. In contrast to other empirical methodologies, which derive average treatment effects, we derive an analytical formula that provides estimates of the treatment effects on each treated individual. We also provide an empirical example that illustrates our methodology. Hall, Stephen G. 1953- verfasserin (DE-588)124941907 (DE-627)368374475 (DE-576)168498510 aut Tavlas, George S. verfasserin (DE-588)12495202X (DE-627)368961532 (DE-576)294585931 aut Chang, I-Lok verfasserin (DE-588)171710320 (DE-627)061945315 (DE-576)132483556 aut Gibson, Heather D. 1961- verfasserin (DE-588)129664545 (DE-627)477109012 (DE-576)166309664 aut Greene, William 1951- verfasserin (DE-588)124700551 (DE-627)364372486 (DE-576)166603910 aut Mehta, Jatinder S. verfasserin aut Enthalten in Econometrics Basel : MDPI, 2013 4(2016), 2 vom: Juni, Seite 1-23 Online-Ressource (DE-627)74684042X (DE-600)2717594-7 (DE-576)382897196 2225-1146 nnns volume:4 year:2016 number:2 month:06 pages:1-23 http://hdl.handle.net/10419/171881 Resolving-System kostenfrei Volltext http://dx.doi.org/10.3390/econometrics4020019 Resolving-System Volltext GBV_USEFLAG_U GBV_ILN_26 ISIL_DE-206 SYSFLAG_1 GBV_KXP GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2009 GBV_ILN_2014 GBV_ILN_2034 GBV_ILN_2055 GBV_ILN_2108 GBV_ILN_2111 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 GBV_ILN_2403 GBV_ILN_2403 ISIL_DE-LFER zbwolc20160724 AR 4 2016 2 6 1-23 26 01 0206 1626477388 x1k 21-07-16 2403 01 DE-LFER 3495673385 00 --%%-- --%%-- n --%%-- l01 23-07-19 2403 01 DE-LFER http://hdl.handle.net/10419/171881 26 00 DE-206 56 causality 26 00 DE-206 56 real-world relationship 26 00 DE-206 56 unique error term 26 00 DE-206 56 treatment effect 26 00 DE-206 56 non-experimental situation
allfieldsSound	10.3390/econometrics4020019 doi 10419/171881 hdl (DE-627)863513778 (DE-576)9863513776 (DE-599)GBV863513778 DE-627 ger DE-627 rda eng C13 C51 jelc Swamy, Paravastu A. V. B. verfasserin (DE-588)170006409 (DE-627)060009284 (DE-576)130923478 aut A method for measuring treatment effects on the treated without randomization P.A.V.B. Swamy, Stephen G. Hall, George S. Tavlas, I-Lok Chang, Heather D. Gibson, William H. Greene and Jatinder S. Mehta June 2016 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier This paper contributes to the literature on the estimation of causal effects by providing an analytical formula for individual specific treatment effects and an empirical methodology that allows us to estimate these effects. We derive the formula from a general model with minimal restrictions, unknown functional form and true unobserved variables such that it is a credible model of the underlying real world relationship. Subsequently, we manipulate the model in order to put it in an estimable form. In contrast to other empirical methodologies, which derive average treatment effects, we derive an analytical formula that provides estimates of the treatment effects on each treated individual. We also provide an empirical example that illustrates our methodology. Hall, Stephen G. 1953- verfasserin (DE-588)124941907 (DE-627)368374475 (DE-576)168498510 aut Tavlas, George S. verfasserin (DE-588)12495202X (DE-627)368961532 (DE-576)294585931 aut Chang, I-Lok verfasserin (DE-588)171710320 (DE-627)061945315 (DE-576)132483556 aut Gibson, Heather D. 1961- verfasserin (DE-588)129664545 (DE-627)477109012 (DE-576)166309664 aut Greene, William 1951- verfasserin (DE-588)124700551 (DE-627)364372486 (DE-576)166603910 aut Mehta, Jatinder S. verfasserin aut Enthalten in Econometrics Basel : MDPI, 2013 4(2016), 2 vom: Juni, Seite 1-23 Online-Ressource (DE-627)74684042X (DE-600)2717594-7 (DE-576)382897196 2225-1146 nnns volume:4 year:2016 number:2 month:06 pages:1-23 http://hdl.handle.net/10419/171881 Resolving-System kostenfrei Volltext http://dx.doi.org/10.3390/econometrics4020019 Resolving-System Volltext GBV_USEFLAG_U GBV_ILN_26 ISIL_DE-206 SYSFLAG_1 GBV_KXP GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2009 GBV_ILN_2014 GBV_ILN_2034 GBV_ILN_2055 GBV_ILN_2108 GBV_ILN_2111 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 GBV_ILN_2403 GBV_ILN_2403 ISIL_DE-LFER zbwolc20160724 AR 4 2016 2 6 1-23 26 01 0206 1626477388 x1k 21-07-16 2403 01 DE-LFER 3495673385 00 --%%-- --%%-- n --%%-- l01 23-07-19 2403 01 DE-LFER http://hdl.handle.net/10419/171881 26 00 DE-206 56 causality 26 00 DE-206 56 real-world relationship 26 00 DE-206 56 unique error term 26 00 DE-206 56 treatment effect 26 00 DE-206 56 non-experimental situation
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source	Enthalten in Econometrics 4(2016), 2 vom: Juni, Seite 1-23 volume:4 year:2016 number:2 month:06 pages:1-23
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container_title	Econometrics
authorswithroles_txt_mv	Swamy, Paravastu A. V. B. @@aut@@ Hall, Stephen G. @@aut@@ Tavlas, George S. @@aut@@ Chang, I-Lok @@aut@@ Gibson, Heather D. @@aut@@ Greene, William @@aut@@ Mehta, Jatinder S. @@aut@@
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topic_title	C13 C51 jelc 26 00 DE-206 56 causality 26 00 DE-206 56 real-world relationship 26 00 DE-206 56 unique error term 26 00 DE-206 56 treatment effect 26 00 DE-206 56 non-experimental situation A method for measuring treatment effects on the treated without randomization P.A.V.B. Swamy, Stephen G. Hall, George S. Tavlas, I-Lok Chang, Heather D. Gibson, William H. Greene and Jatinder S. Mehta
topic	jelc C13 26 causality 26 real-world relationship 26 unique error term 26 treatment effect 26 non-experimental situation
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title	A method for measuring treatment effects on the treated without randomization
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title_full	A method for measuring treatment effects on the treated without randomization P.A.V.B. Swamy, Stephen G. Hall, George S. Tavlas, I-Lok Chang, Heather D. Gibson, William H. Greene and Jatinder S. Mehta
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title_sort	method for measuring treatment effects on the treated without randomization
title_auth	A method for measuring treatment effects on the treated without randomization
abstract	This paper contributes to the literature on the estimation of causal effects by providing an analytical formula for individual specific treatment effects and an empirical methodology that allows us to estimate these effects. We derive the formula from a general model with minimal restrictions, unknown functional form and true unobserved variables such that it is a credible model of the underlying real world relationship. Subsequently, we manipulate the model in order to put it in an estimable form. In contrast to other empirical methodologies, which derive average treatment effects, we derive an analytical formula that provides estimates of the treatment effects on each treated individual. We also provide an empirical example that illustrates our methodology.
abstractGer	This paper contributes to the literature on the estimation of causal effects by providing an analytical formula for individual specific treatment effects and an empirical methodology that allows us to estimate these effects. We derive the formula from a general model with minimal restrictions, unknown functional form and true unobserved variables such that it is a credible model of the underlying real world relationship. Subsequently, we manipulate the model in order to put it in an estimable form. In contrast to other empirical methodologies, which derive average treatment effects, we derive an analytical formula that provides estimates of the treatment effects on each treated individual. We also provide an empirical example that illustrates our methodology.
abstract_unstemmed	This paper contributes to the literature on the estimation of causal effects by providing an analytical formula for individual specific treatment effects and an empirical methodology that allows us to estimate these effects. We derive the formula from a general model with minimal restrictions, unknown functional form and true unobserved variables such that it is a credible model of the underlying real world relationship. Subsequently, we manipulate the model in order to put it in an estimable form. In contrast to other empirical methodologies, which derive average treatment effects, we derive an analytical formula that provides estimates of the treatment effects on each treated individual. We also provide an empirical example that illustrates our methodology.
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title_short	A method for measuring treatment effects on the treated without randomization
url	http://hdl.handle.net/10419/171881 http://dx.doi.org/10.3390/econometrics4020019
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A method for measuring treatment effects on the treated without randomization

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