On the Use of Two-Way Fixed Effects Regression Models for Causal Inference with Panel Data

The two-way linear fixed effects regression (2FE) has become a default method for estimating causal effects from panel data. Many applied researchers use the 2FE estimator to adjust for unobserved unit-specific and time-specific confounders at the same time. Unfortunately, we demonstrate that the ab...

Full description

Saved in:

Bibliographic Details
Published in:	Political analysis Vol. 29; no. 3; pp. 405 - 415
Main Authors:	Imai, Kosuke, Kim, In Song
Format:	Journal Article
Language:	English
Published:	New York, USA Cambridge University Press 01.07.2021
Subjects:	Applied research Causal models Causality Inference Justification Letter Letters Longitudinal studies Panel data Time periods difference-in-differences unobserved confounding weighted least squares longitudinal data matching
ISSN:	1047-1987, 1476-4989
Online Access:	Get full text
Tags:	Add Tag No Tags, Be the first to tag this record!

Abstract	The two-way linear fixed effects regression (2FE) has become a default method for estimating causal effects from panel data. Many applied researchers use the 2FE estimator to adjust for unobserved unit-specific and time-specific confounders at the same time. Unfortunately, we demonstrate that the ability of the 2FE model to simultaneously adjust for these two types of unobserved confounders critically relies upon the assumption of linear additive effects. Another common justification for the use of the 2FE estimator is based on its equivalence to the difference-in-differences estimator under the simplest setting with two groups and two time periods. We show that this equivalence does not hold under more general settings commonly encountered in applied research. Instead, we prove that the multi-period difference-in-differences estimator is equivalent to the weighted 2FE estimator with some observations having negative weights. These analytical results imply that in contrast to the popular belief, the 2FE estimator does not represent a design-based, nonparametric estimation strategy for causal inference. Instead, its validity fundamentally rests on the modeling assumptions.
AbstractList	The two-way linear fixed effects regression ( 2FE ) has become a default method for estimating causal effects from panel data. Many applied researchers use the 2FE estimator to adjust for unobserved unit-specific and time-specific confounders at the same time. Unfortunately, we demonstrate that the ability of the 2FE model to simultaneously adjust for these two types of unobserved confounders critically relies upon the assumption of linear additive effects. Another common justification for the use of the 2FE estimator is based on its equivalence to the difference-in-differences estimator under the simplest setting with two groups and two time periods. We show that this equivalence does not hold under more general settings commonly encountered in applied research. Instead, we prove that the multi-period difference-in-differences estimator is equivalent to the weighted 2FE estimator with some observations having negative weights. These analytical results imply that in contrast to the popular belief, the 2FE estimator does not represent a design-based, nonparametric estimation strategy for causal inference. Instead, its validity fundamentally rests on the modeling assumptions. The two-way linear fixed effects regression (2FE) has become a default method for estimating causal effects from panel data. Many applied researchers use the 2FE estimator to adjust for unobserved unit-specific and time-specific confounders at the same time. Unfortunately, we demonstrate that the ability of the 2FE model to simultaneously adjust for these two types of unobserved confounders critically relies upon the assumption of linear additive effects. Another common justification for the use of the 2FE estimator is based on its equivalence to the difference-in-differences estimator under the simplest setting with two groups and two time periods. We show that this equivalence does not hold under more general settings commonly encountered in applied research. Instead, we prove that the multi-period difference-in-differences estimator is equivalent to theweighted 2FE estimator with some observations having negative weights. These analytical results imply that in contrast to the popular belief, the 2FE estimator does not represent a design based, nonparametric estimation strategy for causal inference. Instead, its validity fundamentally rests on the modeling assumptions. The two-way linear fixed effects regression (2FE) has become a default method for estimating causal effects from panel data. Many applied researchers use the 2FE estimator to adjust for unobserved unit-specific and time-specific confounders at the same time. Unfortunately, we demonstrate that the ability of the 2FE model to simultaneously adjust for these two types of unobserved confounders critically relies upon the assumption of linear additive effects. Another common justification for the use of the 2FE estimator is based on its equivalence to the difference-in-differences estimator under the simplest setting with two groups and two time periods. We show that this equivalence does not hold under more general settings commonly encountered in applied research. Instead, we prove that the multi-period difference-in-differences estimator is equivalent to the weighted 2FE estimator with some observations having negative weights. These analytical results imply that in contrast to the popular belief, the 2FE estimator does not represent a design-based, nonparametric estimation strategy for causal inference. Instead, its validity fundamentally rests on the modeling assumptions.
Author	Kim, In Song Imai, Kosuke
Author_xml	– sequence: 1 givenname: Kosuke orcidid: 0000-0002-2748-1022 surname: Imai fullname: Imai, Kosuke email: Imai@Harvard.Edu organization: 1Professor, Department of Government and Department of Statistics, Harvard University, 1737 Cambridge Street, Institute for Quantitative Social Science, Cambridge, MA 02138, USA. E-mail: Imai@Harvard.Edu, URL: https://imai.fas.harvard.edu/ – sequence: 2 givenname: In Song orcidid: 0000-0002-5774-1585 surname: Kim fullname: Kim, In Song email: insong@mit.edu organization: 2Associate Professor, Department of Political Science, Massachusetts Institute of Technology, Cambridge, MA 02142, USA. E-mail: insong@mit.edu, URL: http://web.mit.edu/insong/www/
BookMark	eNp1kNFLwzAQxoMouE2ffBYCPkpn0rRN-yhz08FkIhuCLyVLL1tHl8wkY-6_N2NDQfTpjrvffXf3tdGpNhoQuqKkSwnld2uhuzGJSZexE9SiCc-ipMiL05CThEe0yPk5aju3JIHmRdFC72ON_QLw1AE2Ck-2JnoTOzyoP6HCfaVAeodfYW7Budpo_GwqaBxWxuKe2DjR4KFWYEFLwNvaL_CL0NDgB-HFBTpTonFweYwdNB30J72naDR-HPbuR5Fkae6jmZoVSlCSEpakaUgEZBVXPKsIpUrmgmSzmHCZkTiWjOaJjItQpAWInEDCWAfdHHTX1nxswPlyaTZWh5VlnLKUZyQ4Eih6oKQ1zllQpay98OEnb0XdlJSUewvLYGG5t7Bke-XbXzNrW6-E3f1DXx_opfPGfqMxpzRL0yT0o6OaWM1sXc3h59C_9L4AUhaLGw
CitedBy_id	crossref_primary_10_1016_j_ecolecon_2021_107318 crossref_primary_10_1111_ajps_12826 crossref_primary_10_1017_spq_2021_17 crossref_primary_10_1017_S0020818324000092 crossref_primary_10_1016_j_jeem_2023_102852 crossref_primary_10_1111_jifm_12207 crossref_primary_10_1002_rfe_1177 crossref_primary_10_1111_coep_12633 crossref_primary_10_3390_ijerph192214890 crossref_primary_10_1017_S0007123424000486 crossref_primary_10_1177_2212585X231213787 crossref_primary_10_1080_09692290_2023_2267051 crossref_primary_10_1016_j_eneco_2025_108827 crossref_primary_10_1177_00224294231206098 crossref_primary_10_1093_isq_sqae069 crossref_primary_10_1111_ajps_12820 crossref_primary_10_2139_ssrn_3773763 crossref_primary_10_1080_13547860_2022_2044658 crossref_primary_10_1108_PAR_10_2023_0137 crossref_primary_10_1177_00111287221083885 crossref_primary_10_1111_labr_12238 crossref_primary_10_1016_j_marpol_2024_106156 crossref_primary_10_3389_fpubh_2022_989625 crossref_primary_10_1177_10780874241241255 crossref_primary_10_1016_j_electstud_2025_102957 crossref_primary_10_1007_s11292_022_09508_y crossref_primary_10_1086_718210 crossref_primary_10_1162_glep_a_00710 crossref_primary_10_1017_pan_2022_23 crossref_primary_10_1287_inte_2023_0028 crossref_primary_10_1016_j_eneco_2023_106624 crossref_primary_10_1177_10659129221145938 crossref_primary_10_1093_ser_mwad034 crossref_primary_10_1177_00223433231200918 crossref_primary_10_3390_su16093585 crossref_primary_10_1177_00031224231156190 crossref_primary_10_1080_09692290_2025_2519189 crossref_primary_10_1111_obes_12673 crossref_primary_10_1016_j_eap_2025_05_027 crossref_primary_10_1098_rsos_221001 crossref_primary_10_1016_j_buildenv_2024_111618 crossref_primary_10_1016_j_jclepro_2024_141871 crossref_primary_10_1016_j_ssresearch_2024_103011 crossref_primary_10_1001_jamanetworkopen_2023_24018 crossref_primary_10_1080_13501763_2024_2390701 crossref_primary_10_1177_0095327X241277209 crossref_primary_10_1146_annurev_polisci_051120_014235 crossref_primary_10_26794_2587_5671_2026_30_4_1706_01 crossref_primary_10_2139_ssrn_4522039 crossref_primary_10_1016_j_eneco_2023_106770 crossref_primary_10_1086_723818 crossref_primary_10_1016_j_tra_2025_104649 crossref_primary_10_1021_envhealth_5c00033 crossref_primary_10_1111_ajps_12721 crossref_primary_10_1038_s43856_025_00757_2 crossref_primary_10_1111_1475_6773_14023 crossref_primary_10_2139_ssrn_5082905 crossref_primary_10_1007_s10668_025_06628_z crossref_primary_10_1007_s11127_023_01139_9 crossref_primary_10_1177_00104140231169018 crossref_primary_10_1016_j_electstud_2024_102878 crossref_primary_10_1038_s41467_024_49835_4 crossref_primary_10_3389_frsus_2025_1637126 crossref_primary_10_1093_sf_soaf102 crossref_primary_10_1111_coep_12645 crossref_primary_10_1111_poms_13863 crossref_primary_10_1016_j_jclepro_2023_139815 crossref_primary_10_1177_13691481251329774 crossref_primary_10_1007_s11187_024_00973_5 crossref_primary_10_1016_j_jdeveco_2025_103494 crossref_primary_10_1016_j_exis_2024_101442 crossref_primary_10_1016_j_labeco_2024_102547 crossref_primary_10_1080_17487870_2024_2326410 crossref_primary_10_1200_JCO_24_02121 crossref_primary_10_3390_rs16183407 crossref_primary_10_3389_fpubh_2024_1442304 crossref_primary_10_1080_07418825_2025_2557329 crossref_primary_10_1017_psrm_2021_45 crossref_primary_10_1215_00703370_11466849 crossref_primary_10_1186_s12992_025_01135_2 crossref_primary_10_3389_fsufs_2024_1460497 crossref_primary_10_1007_s10901_024_10115_8 crossref_primary_10_1016_j_socscimed_2021_114580 crossref_primary_10_1016_j_rssm_2024_100957 crossref_primary_10_1002_soej_12657 crossref_primary_10_1016_j_frl_2023_104599 crossref_primary_10_1371_journal_pone_0323565 crossref_primary_10_1016_j_eap_2021_12_020 crossref_primary_10_1111_lsq_70031 crossref_primary_10_1093_ser_mwac026 crossref_primary_10_17645_si_9638 crossref_primary_10_1007_s13132_025_02813_7 crossref_primary_10_3390_healthcare11030437 crossref_primary_10_1111_gove_12881 crossref_primary_10_1002_soej_12686 crossref_primary_10_1016_j_econlet_2025_112600 crossref_primary_10_1016_j_resourpol_2024_105091 crossref_primary_10_1017_S0022050723000359 crossref_primary_10_1038_s41558_024_02024_z crossref_primary_10_1002_soej_12682 crossref_primary_10_1016_j_electstud_2025_102968 crossref_primary_10_1016_j_jfineco_2022_01_004 crossref_primary_10_1016_j_jeem_2025_103161 crossref_primary_10_1016_j_adiac_2025_100816 crossref_primary_10_1093_geront_gnae151 crossref_primary_10_1017_ehs_2023_35 crossref_primary_10_1215_00703370_11680156 crossref_primary_10_1007_s10980_024_01926_9 crossref_primary_10_1515_em_2024_0025 crossref_primary_10_1080_00036846_2023_2165618 crossref_primary_10_2139_ssrn_3773825 crossref_primary_10_3390_su17167376 crossref_primary_10_1086_733370 crossref_primary_10_1177_00223433231214427 crossref_primary_10_1111_1540_6229_12507 crossref_primary_10_1007_s11162_023_09748_5 crossref_primary_10_1007_s10668_021_01971_3 crossref_primary_10_1017_S0007123422000564 crossref_primary_10_1016_j_labeco_2023_102492 crossref_primary_10_1111_ropr_12458 crossref_primary_10_2139_ssrn_5355231 crossref_primary_10_1016_j_habitatint_2024_103274 crossref_primary_10_1017_S0003055422001290 crossref_primary_10_3389_fsufs_2025_1595161 crossref_primary_10_1007_s00181_022_02253_1 crossref_primary_10_1016_j_jeconom_2021_03_014 crossref_primary_10_1017_S0003055420000556 crossref_primary_10_1111_caje_12549 crossref_primary_10_1186_s13063_024_08572_1 crossref_primary_10_1111_pops_13015 crossref_primary_10_1093_ectj_utae014 crossref_primary_10_1016_j_ssresearch_2025_103223 crossref_primary_10_1016_j_jdeveco_2022_102850 crossref_primary_10_1017_S0020818322000261 crossref_primary_10_1086_736996 crossref_primary_10_1016_j_jclepro_2023_136508 crossref_primary_10_1016_j_econedurev_2022_102328 crossref_primary_10_1016_j_ecolecon_2023_108078 crossref_primary_10_1038_s41598_025_92502_x crossref_primary_10_1016_j_ecolecon_2022_107367 crossref_primary_10_1016_j_jjie_2024_101338 crossref_primary_10_1002_soej_12742 crossref_primary_10_3102_00028312241275967 crossref_primary_10_1111_rssb_12448 crossref_primary_10_1108_IJESM_05_2023_0033 crossref_primary_10_1016_j_jeem_2024_102971 crossref_primary_10_1080_26395940_2024_2387682 crossref_primary_10_1093_ije_dyae137 crossref_primary_10_1080_01446193_2023_2291082 crossref_primary_10_1007_s11558_023_09510_7 crossref_primary_10_1016_j_jbef_2022_100719 crossref_primary_10_1371_journal_pwat_0000329 crossref_primary_10_1017_S0143814X25000121 crossref_primary_10_2139_ssrn_4487202 crossref_primary_10_1111_ele_70023 crossref_primary_10_1016_j_regsciurbeco_2024_104039 crossref_primary_10_1111_jofi_13412 crossref_primary_10_1080_09692290_2024_2442698 crossref_primary_10_1016_j_socscimed_2024_117252 crossref_primary_10_1093_isq_sqac047 crossref_primary_10_1007_s40797_023_00263_1 crossref_primary_10_1007_s10680_023_09687_y crossref_primary_10_1257_jep_20241406 crossref_primary_10_1177_10659129241268816 crossref_primary_10_1093_isq_sqab073 crossref_primary_10_1007_s10668_025_06246_9 crossref_primary_10_1016_j_ribaf_2023_102025 crossref_primary_10_1016_j_worlddev_2023_106418 crossref_primary_10_1111_1467_9566_13755 crossref_primary_10_1073_pnas_2414767122 crossref_primary_10_1093_jopart_muae014 crossref_primary_10_1108_IJHMA_05_2023_0064 crossref_primary_10_1007_s40750_023_00221_2 crossref_primary_10_1016_j_jimonfin_2024_103263 crossref_primary_10_1007_s40865_025_00271_y crossref_primary_10_1177_10591478251331095 crossref_primary_10_1016_j_socscimed_2023_116446 crossref_primary_10_1108_BPMJ_02_2024_0052 crossref_primary_10_1016_j_jenvman_2025_126286 crossref_primary_10_1007_s10101_022_00283_0 crossref_primary_10_1177_00323217241266029 crossref_primary_10_1016_j_eap_2024_10_056 crossref_primary_10_1001_jamanetworkopen_2020_36687 crossref_primary_10_1016_j_foodpol_2024_102626 crossref_primary_10_1214_25_AOAS2011 crossref_primary_10_1016_j_irfa_2024_103105 crossref_primary_10_1111_puar_13694 crossref_primary_10_1080_09638199_2024_2419406 crossref_primary_10_1111_ajps_12897 crossref_primary_10_1016_j_jinteco_2022_103685 crossref_primary_10_1017_psrm_2024_4 crossref_primary_10_1111_beer_12564 crossref_primary_10_1016_j_joclim_2025_100414 crossref_primary_10_1177_09589287251370494 crossref_primary_10_1007_s40750_024_00250_5 crossref_primary_10_1080_01402382_2025_2521582 crossref_primary_10_1093_poq_nfad052 crossref_primary_10_3390_su16198581 crossref_primary_10_1007_s11150_023_09657_7 crossref_primary_10_1111_ajae_12510 crossref_primary_10_1016_j_scs_2024_106097 crossref_primary_10_1093_isq_sqae126 crossref_primary_10_1093_isq_sqac067 crossref_primary_10_1177_10659129231205296 crossref_primary_10_1287_mnsc_2023_4811 crossref_primary_10_1111_ajes_12602 crossref_primary_10_1093_ser_mwae056 crossref_primary_10_1007_s11292_022_09527_9 crossref_primary_10_1111_ajps_12685 crossref_primary_10_1111_gove_12799 crossref_primary_10_1111_ecot_12436 crossref_primary_10_1111_1475_6773_13694 crossref_primary_10_1002_hec_4842 crossref_primary_10_1080_01900692_2022_2081177 crossref_primary_10_1111_jmcb_13244 crossref_primary_10_1016_j_jue_2024_103689 crossref_primary_10_1093_jrsssb_qkad136 crossref_primary_10_1002_smi_3216 crossref_primary_10_1007_s10668_024_05358_y crossref_primary_10_1016_j_ijhm_2024_103896 crossref_primary_10_3390_su16103986 crossref_primary_10_1177_10659129241252811 crossref_primary_10_1002_csr_2488 crossref_primary_10_1016_j_futures_2025_103566 crossref_primary_10_3390_app13085198 crossref_primary_10_1007_s12116_023_09390_3 crossref_primary_10_1016_j_rssm_2024_100889 crossref_primary_10_3790_staa_57_1_119 crossref_primary_10_1080_00220388_2023_2253977 crossref_primary_10_1016_j_jce_2025_01_003 crossref_primary_10_1111_ecot_12308 crossref_primary_10_1086_734538 crossref_primary_10_1080_15582159_2022_2135843 crossref_primary_10_3390_logistics9030121 crossref_primary_10_1017_S0003055422001010 crossref_primary_10_1080_15582159_2022_2135844 crossref_primary_10_1111_gove_12782 crossref_primary_10_1073_pnas_2217323120 crossref_primary_10_1097_EDE_0000000000001611 crossref_primary_10_17657_jcr_2024_10_31_6 crossref_primary_10_1002_sd_3063 crossref_primary_10_1016_j_jeconom_2023_03_008 crossref_primary_10_1080_10941665_2023_2174034 crossref_primary_10_1007_s11558_024_09553_4 crossref_primary_10_2139_ssrn_3992810 crossref_primary_10_3390_math11061531 crossref_primary_10_3390_su14127343 crossref_primary_10_3390_en17102411 crossref_primary_10_1007_s00148_025_01080_9 crossref_primary_10_1007_s10964_024_01986_9 crossref_primary_10_1177_20531680251320073 crossref_primary_10_18778_2391_6478_3_35_03 crossref_primary_10_1080_01900692_2024_2431976 crossref_primary_10_1177_00223433221128846 crossref_primary_10_1007_s11192_025_05400_4 crossref_primary_10_1093_jeg_lbad012 crossref_primary_10_1177_10848223221140502 crossref_primary_10_1177_10911421211064676 crossref_primary_10_1093_jopart_muaf021 crossref_primary_10_1016_j_ejpoleco_2024_102512 crossref_primary_10_1093_ectj_utac017 crossref_primary_10_1093_forsci_fxad042 crossref_primary_10_1080_01402382_2022_2089963 crossref_primary_10_1111_brv_70011 crossref_primary_10_1017_psrm_2024_28 crossref_primary_10_1007_s10666_025_10019_z crossref_primary_10_1016_j_eneco_2024_107776 crossref_primary_10_2139_ssrn_3794018 crossref_primary_10_1016_j_jeconom_2022_07_006 crossref_primary_10_1038_s41467_024_50630_4 crossref_primary_10_1016_j_eap_2025_07_025 crossref_primary_10_3790_staa_56_4_491 crossref_primary_10_1136_bmjph_2024_001595 crossref_primary_10_1016_j_worlddev_2024_106609 crossref_primary_10_1111_gove_12593 crossref_primary_10_1007_s43621_025_01783_9 crossref_primary_10_1177_10245294231221884 crossref_primary_10_1093_jnci_djae189 crossref_primary_10_1016_j_electstud_2023_102647 crossref_primary_10_1038_s41598_022_05482_7 crossref_primary_10_1080_01621459_2024_2395593 crossref_primary_10_1080_10242694_2025_2456798 crossref_primary_10_1016_j_eneco_2023_107028 crossref_primary_10_1016_j_jtrangeo_2025_104206 crossref_primary_10_1080_07350015_2020_1796395 crossref_primary_10_1080_13501763_2022_2061034 crossref_primary_10_1080_21565503_2023_2227438 crossref_primary_10_1017_S0003055420000957 crossref_primary_10_1016_j_isci_2024_110879 crossref_primary_10_1017_gov_2024_22 crossref_primary_10_1186_s12889_021_12474_1 crossref_primary_10_1186_s12913_024_11443_9 crossref_primary_10_1200_GO_20_00531 crossref_primary_10_1016_j_jenvman_2023_118213 crossref_primary_10_1080_09537325_2023_2196585 crossref_primary_10_1080_00036846_2024_2364119 crossref_primary_10_1371_journal_pone_0294453 crossref_primary_10_1007_s40974_024_00348_2 crossref_primary_10_1080_01402382_2021_1963139 crossref_primary_10_3390_rs17183208 crossref_primary_10_1177_00223433241279379 crossref_primary_10_1146_annurev_polisci_051120_104325 crossref_primary_10_1515_bejeap_2022_0241 crossref_primary_10_1017_pan_2022_8 crossref_primary_10_1080_1226508X_2023_2171458 crossref_primary_10_1177_17488958241276178 crossref_primary_10_1371_journal_pone_0297055
Cites_doi	10.1515/9781400829828 10.3386/w24963 10.3386/w25018 10.3386/w25904 10.1111/ajps.12417 10.2139/ssrn.2826228 10.1198/jasa.2009.ap08746 10.3368/jhr.50.2.301 10.2139/ssrn.3158747 10.1162/003355304772839588 10.1017/pan.2016.2 10.1111/ajps.12185 10.1080/07350015.2018.1546591
ContentType	Journal Article
Copyright	The Author(s) 2020. Published by Cambridge University Press on behalf of the Society for Political Methodology The Author(s) 2020
Copyright_xml	– notice: The Author(s) 2020. Published by Cambridge University Press on behalf of the Society for Political Methodology – notice: The Author(s) 2020
DBID	AAYXX CITATION 0-V 3V. 7UB 7XB 88F 88J 8FK 8G5 ABUWG AFKRA ALSLI AZQEC BENPR CCPQU DPSOV DWQXO GNUQQ GUQSH KC- M1Q M2L M2O M2R MBDVC PHGZM PHGZT PKEHL POGQB PQEST PQQKQ PQUKI PRINS PRQQA Q9U
DOI	10.1017/pan.2020.33
DatabaseName	CrossRef ProQuest Social Sciences Premium Collection【Remote access available】 ProQuest Central (Corporate) Worldwide Political Science Abstracts ProQuest Central (purchase pre-March 2016) Military Database (Alumni Edition) Social Science Database (Alumni Edition) ProQuest Central (Alumni) (purchase pre-March 2016) Research Library (Alumni) ProQuest Central (Alumni) ProQuest Central UK/Ireland Social Science Premium Collection ProQuest Central Essentials ProQuest Central ProQuest One Community College Politics Collection (OCUL) ProQuest Central ProQuest Central Student ProQuest Research Library ProQuest Politics Collection Military Database Political Science Database (OCUL) Research Library Social Science Database Research Library (Corporate) ProQuest Central Premium ProQuest One Academic (New) ProQuest One Academic Middle East (New) ProQuest Sociology & Social Sciences Collection ProQuest One Academic Eastern Edition (DO NOT USE) ProQuest One Academic (retired) ProQuest One Academic UKI Edition ProQuest Central China ProQuest One Social Sciences ProQuest Central Basic
DatabaseTitle	CrossRef Research Library Prep ProQuest Sociology & Social Sciences Collection ProQuest Central Student ProQuest One Academic Middle East (New) ProQuest Central Essentials ProQuest Social Science Journals (Alumni Edition) ProQuest Central (Alumni Edition) ProQuest One Community College Research Library (Alumni Edition) Politics Collection ProQuest Military Collection Sociology & Social Sciences Collection ProQuest Central China ProQuest Central ProQuest Central Korea ProQuest Research Library Worldwide Political Science Abstracts ProQuest Central (New) Social Science Premium Collection ProQuest Political Science ProQuest One Social Sciences ProQuest Central Basic ProQuest One Academic Eastern Edition ProQuest Military Collection (Alumni Edition) ProQuest Social Science Journals ProQuest Social Sciences Premium Collection ProQuest One Academic UKI Edition ProQuest Politics Collection ProQuest One Academic ProQuest One Academic (New) ProQuest Central (Alumni)
DatabaseTitleList	CrossRef Research Library Prep
Database_xml	– sequence: 1 dbid: BENPR name: ProQuest Central url: https://www.proquest.com/central sourceTypes: Aggregation Database
DeliveryMethod	fulltext_linktorsrc
Discipline	Political Science
EISSN	1476-4989
EndPage	415
ExternalDocumentID	10_1017_pan_2020_33 27116554
GroupedDBID	-~X .2P .I3 0-V 09C 09D 0R~ 123 1TH 29O 3V. 4.4 482 5VS 5WA 70D 8G5 8U8 9BT AABES AABWE AAEED AAFXQ AAGFV AAIYJ AAJKP AAKTX AALKF AAMVS AAOGV AAPYI AASVR AAUKB AAUQX AAXEK ABBGM ABBHK ABBXU ABIXL ABJNI ABJWI ABLIL ABMYL ABNKS ABQLI ABQTQ ABQWD ABROB ABSMQ ABUWG ABXAU ABXSQ ABYPY ABZBJ ABZCX ACCHT ACFCP ACGFS ACHQT ACMRT ACNCT ACPQN ACQFJ ACUFI ACUIJ ACUYZ ACWGA ACYPW ACYZP ACZBM ADACV ADEYI ADGEJ ADHZD ADKIL ADNBY ADOCK ADOCW ADOVH ADRIX ADTCA ADULT ADVJH ADZXQ AEBAK AEBPU AEFOJ AEGPL AEHGV AEJOX AEPUE AEUPB AEYYC AFFNX AFIYH AFKQG AFKRA AFKRZ AFKSM AFLVW AFVIK AGABE AGHGI AGJUD AGKEF AGOOT AGRIO AGSYK AHQXX AHRGI AHXPO AIGNW AIHIV AIJHB AJECE AJPFC AKZCZ ALMA_UNASSIGNED_HOLDINGS ALSLI ALUQC ANFVQ AOWSX APHTQ ARALO ARZZG ASPBG ATRLI ATUCA AUXHV AVDNQ AVWKF AWRMI AWSUU AYIQA AYLYT AZFZN AZNXF AZQEC BBAJS BBLKV BBQHK BENPR BJBOZ BMAJL BPHCQ CAG CCPQU CCQAD CCUQV CFAFE CFBFF CFLAC CHEAL CJCSC CKLRP COF CS3 CZ4 DDUBX DOHLZ DPSOV DU5 DWQXO D~K EBD EBS EE~ EGQIC EJD F5P F9B FEDTE GDOGT GKAIP GNUQQ GUQSH H5~ HAR HOVLH HVGLF HW0 HZ~ IH6 IOEEP IOO IOX IS6 J21 JAAYA JBMMH JENOY JHFFW JHPGK JKQEH JLEZI JLXEF JOSPZ JPL JPPIE JQKCU JRMXA JSODD JST KAFGG KAQDR KC- KC5 KSI LW7 M-Z M1Q M2L M2O M2R M49 N9A NGC NIKVX NU- O0~ O9- OYBOY O~Y P2P PB- PQQKQ PROAC Q1. Q5Y R44 RCA RD5 RIG RNI ROL ROX RW1 RXO RZF RZO S6U SA0 T9M TJJ TKY TSS UT1 WFFJZ X7H ZJOSE ZKX ZMEZD ZYDXJ ~91 ~D7 ~SN ABGDZ ABVKB ABXHF ACDLN AFZFC AGTDA AKMAY CBIIA IPSME PHGZM PHGZT AAGQS AAXMD AAYXX ABNGD ACUKT AEHUL AFFHD AGQPQ AHHGH CITATION H13 PRQQA 7UB 7XB 8FK MBDVC PKEHL POGQB PQEST PQUKI PRINS Q9U
ID	FETCH-LOGICAL-c358t-bfb9fa10503455a10ae6d7f76d011fc8a06b207c6022c3184c298a019ea80e433
IEDL.DBID	BENPR
ISICitedReferencesCount	365
ISICitedReferencesURI	http://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=Summon&SrcAuth=ProQuest&DestLinkType=CitingArticles&DestApp=WOS_CPL&KeyUT=000656899900008&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D
ISSN	1047-1987
IngestDate	Sun Nov 09 06:33:32 EST 2025 Sat Nov 29 03:06:28 EST 2025 Tue Nov 18 21:07:00 EST 2025 Thu Jul 03 21:36:54 EDT 2025 Wed Mar 13 05:59:21 EDT 2024
IsDoiOpenAccess	false
IsOpenAccess	true
IsPeerReviewed	true
IsScholarly	true
Issue	3
Keywords	difference-in-differences unobserved confounding weighted least squares longitudinal data matching
Language	English
License	https://www.cambridge.org/core/terms
LinkModel	DirectLink
MergedId	FETCHMERGED-LOGICAL-c358t-bfb9fa10503455a10ae6d7f76d011fc8a06b207c6022c3184c298a019ea80e433
Notes	ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14
ORCID	0000-0002-2748-1022 0000-0002-5774-1585
OpenAccessLink	https://www.cambridge.org/core/services/aop-cambridge-core/content/view/F10006D0210407C5F9C7CAC1EEE3EF0D/S1047198720000339a.pdf/div-class-title-on-the-use-of-two-way-fixed-effects-regression-models-for-causal-inference-with-panel-data-div.pdf
PQID	2535760020
PQPubID	51675
PageCount	11
ParticipantIDs	proquest_journals_2535760020 crossref_citationtrail_10_1017_pan_2020_33 crossref_primary_10_1017_pan_2020_33 jstor_primary_27116554 cambridge_journals_10_1017_pan_2020_33
PublicationCentury	2000
PublicationDate	20210700 20210701 2021-07-00
PublicationDateYYYYMMDD	2021-07-01
PublicationDate_xml	– month: 07 year: 2021 text: 20210700
PublicationDecade	2020
PublicationPlace	New York, USA
PublicationPlace_xml	– name: New York, USA – name: Oxford
PublicationTitle	Political analysis
PublicationTitleAlternate	Polit. Anal
PublicationYear	2021
Publisher	Cambridge University Press
Publisher_xml	– name: Cambridge University Press
References	2019; 38 2015; 60 2004; 119 2019; 63 2017; 25 2010; 105 2015; 50 S1047198720000339_r10 S1047198720000339_r11 S1047198720000339_r12 S1047198720000339_r13 S1047198720000339_r4 S1047198720000339_r14 S1047198720000339_r5 S1047198720000339_r2 S1047198720000339_r15 S1047198720000339_r3 S1047198720000339_r16 S1047198720000339_r17 S1047198720000339_r1 S1047198720000339_r18 S1047198720000339_r19 S1047198720000339_r8 S1047198720000339_r9 S1047198720000339_r6 S1047198720000339_r7
References_xml	– volume: 38 start-page: 613 year: 2019 end-page: 620 article-title: The Promise and Pitfalls of Differences-in-Differences: Reflections on 16 and Pregnant and Other Applications publication-title: Journal of Business & Economic Statistics – volume: 25 start-page: 57 issue: 1 year: 2017 end-page: 76 article-title: Generalized Synthetic Control Method: Causal Inference with Interactive Fixed Effects Models publication-title: Political Analysis – volume: 60 start-page: 250 issue: 1 year: 2015 end-page: 267 article-title: Does Regression Produce Representative Estimates of Causal Effects? publication-title: American Journal of Political Science – volume: 50 start-page: 301 issue: 2 year: 2015 end-page: 316 article-title: What are we weighting for? publication-title: Journal of Human Resources – volume: 105 start-page: 493 issue: 490 year: 2010 end-page: 505 article-title: Synthetic Control Methods for Comparative Case Studies: Estimating the Effect of California’s Tobacco Control Program publication-title: Journal of the American Statistical Association – volume: 119 start-page: 249 issue: 1 year: 2004 end-page: 275 article-title: How Much Should We Trust Differences-in-Differences Estimates? publication-title: Quarterly Journal of Economics – volume: 63 start-page: 467 issue: 2 year: 2019 end-page: 490 article-title: When should we use linear unit fixed effects regression models for causal inference with longitudinal data? publication-title: American Journal of Political Science – ident: S1047198720000339_r3 doi: 10.1515/9781400829828 – ident: S1047198720000339_r5 doi: 10.3386/w24963 – ident: S1047198720000339_r11 doi: 10.3386/w25018 – ident: S1047198720000339_r10 doi: 10.3386/w25904 – ident: S1047198720000339_r14 doi: 10.1111/ajps.12417 – ident: S1047198720000339_r9 doi: 10.2139/ssrn.2826228 – ident: S1047198720000339_r1 doi: 10.1198/jasa.2009.ap08746 – ident: S1047198720000339_r18 doi: 10.3368/jhr.50.2.301 – ident: S1047198720000339_r6 – ident: S1047198720000339_r8 – ident: S1047198720000339_r15 – ident: S1047198720000339_r2 doi: 10.2139/ssrn.3158747 – ident: S1047198720000339_r7 doi: 10.1162/003355304772839588 – ident: S1047198720000339_r19 doi: 10.1017/pan.2016.2 – ident: S1047198720000339_r17 – ident: S1047198720000339_r4 doi: 10.1111/ajps.12185 – ident: S1047198720000339_r16 doi: 10.1080/07350015.2018.1546591 – ident: S1047198720000339_r13 – ident: S1047198720000339_r12
SSID	ssj0017799
Score	2.6801355
Snippet	The two-way linear fixed effects regression (2FE) has become a default method for estimating causal effects from panel data. Many applied researchers use the... The two-way linear fixed effects regression ( 2FE ) has become a default method for estimating causal effects from panel data. Many applied researchers use the...
SourceID	proquest crossref jstor cambridge
SourceType	Aggregation Database Enrichment Source Index Database Publisher
StartPage	405
SubjectTerms	Applied research Causal models Causality Inference Justification Letter Letters Longitudinal studies Panel data Time periods
Title	On the Use of Two-Way Fixed Effects Regression Models for Causal Inference with Panel Data
URI	https://www.cambridge.org/core/product/identifier/S1047198720000339/type/journal_article https://www.jstor.org/stable/27116554 https://www.proquest.com/docview/2535760020
Volume	29
WOSCitedRecordID	wos000656899900008&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D
hasFullText	1
inHoldings	1
isFullTextHit
isPrint
journalDatabaseRights	– providerCode: PRVPQU databaseName: Military Database (ProQuest) customDbUrl: eissn: 1476-4989 dateEnd: 20241207 omitProxy: false ssIdentifier: ssj0017799 issn: 1047-1987 databaseCode: M1Q dateStart: 20170101 isFulltext: true titleUrlDefault: https://search.proquest.com/military providerName: ProQuest – providerCode: PRVPQU databaseName: Political Science Database (OCUL) customDbUrl: eissn: 1476-4989 dateEnd: 20241207 omitProxy: false ssIdentifier: ssj0017799 issn: 1047-1987 databaseCode: M2L dateStart: 20170101 isFulltext: true titleUrlDefault: https://www.proquest.com/politicalscience providerName: ProQuest – providerCode: PRVPQU databaseName: ProQuest Central customDbUrl: eissn: 1476-4989 dateEnd: 20241207 omitProxy: false ssIdentifier: ssj0017799 issn: 1047-1987 databaseCode: BENPR dateStart: 20170101 isFulltext: true titleUrlDefault: https://www.proquest.com/central providerName: ProQuest – providerCode: PRVPQU databaseName: Research Library customDbUrl: eissn: 1476-4989 dateEnd: 20241207 omitProxy: false ssIdentifier: ssj0017799 issn: 1047-1987 databaseCode: M2O dateStart: 20170101 isFulltext: true titleUrlDefault: https://search.proquest.com/pqrl providerName: ProQuest – providerCode: PRVPQU databaseName: Social Science Database customDbUrl: eissn: 1476-4989 dateEnd: 20241207 omitProxy: false ssIdentifier: ssj0017799 issn: 1047-1987 databaseCode: M2R dateStart: 20170101 isFulltext: true titleUrlDefault: https://search.proquest.com/socscijournals providerName: ProQuest
link	http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwpV1LS8QwEB509eDFt7i6Sg7iQSh200fak-jqoqDruiiKl5KmqQhLV-36-vfOpNlVUbx4CW0zlMAkk5nJl28AtsgN5ZlSjp8GGKAIHTtRSsC1PIxjHil8yUyxCdHpRDc3cdcm3EoLqxzZRGOos4GiHPkuD7zAHCK5ew-PDlWNotNVW0JjEqaIqcyvwdTBUafbG58jCGEqSBo-Agqv7Q09Io3GxYbhIceo1fvKq_Btf6ogij_MtNl72nP_HfU8zFqvk-1X02QBJnSxCPMW-4YddoUvwe15wdAlZFelZoOcXb4OnGv5ztr3bzpjFdNxyXr6rkLPFoxKqfVLhp4va8nnEn91MrpByCjFy7qy0H12KIdyGa7aR5etY8eWX3CUF0RDJ83TOJdNIozxgwAfpA4zkYswQ5uQq0i6YcpdoUJ0AxSaBl_xGD82Yy0jV_uetwK1YlDoVcJPadwIM4HOROoLiU6IjDTPUqlSrmI3r8P2WAGJXURlUgHQRIKaSkhTiefVYWeknURZEnOqpdH_XXhrLPxQcXf8LrZi1DyW4YI4iQK_Do2RUj8H9anRtb-712GGE_7FQHsbUBs-PesNmFYvw_vyadNO1E2YPGteUMtPTXtu2t4HDMvyHg
linkProvider	ProQuest
linkToHtml	http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMw1V1Lb9NAEB5FKRJcaCitCC2wh9BDJQtn_Vj7UCGUECVKmxaUioqLu16vUaTISeO0IX-K38jM2k5BVNx66M32jiw_vnntfjsD0KIwlCdKWW7sYYIidGgFMRHXUj8MeaDwJDHNJsRoFFxehuc1-FXthSFaZWUTjaFOZormyD9wz_HMIpL9cX5tUdcoWl2tWmgUsBjq9QpTtvx40MX_-57z3udxp2-VXQUs5XjB0orTOExlm-qguJ6HB1L7iUiFnyDUUxVI24-5LZSP3k0h4l3FQ7zYDrUMbO3SBCia_C0XIx3SqNP2l82qhRCmX6WpfkDJfLkfkEpUo2pjMsoxR3b-rOLwlzcsCJH_OAXj6Xrbj-0bNeB5GVOzT4USvICaznagUTL7cKC0Xy_h-1nGMOBlF7lms5SNVzPrm1yz3uSnTlhRxzlnX_WPghucMWoUN80ZxvWsI29yvNWg2h_JaAKbnctMT1lXLuUuXDzIK-5BPZtl-hWxwzS6-URgqBS7QmKIJQPNk1iqmKvQTptwuPnhUWki8qig14kIkRERMiLHacJRhYZIlSXaqVPI9H7h1kZ4XlQmuV9sz8BqI8MFVVzy3CYcVCC6e6g7BL3-__A7eNofn55EJ4PRcB-ecWL6GBLzAdSXixv9Bp6o2-UkX7w1KsLg6qHx9hvr00g3
linkToPdf	http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMw1V1LS8QwEB5ERbz4FtdnDupBKNb0kfYgIq6Li7ouoiheapqmIixdtevrr_nrnEnbVVG8efDWNtPSNl_mkXyZAVglN5QnSllu7GGAInRoBTER11I_DHmg8CQxxSZEqxVcXobtAXir9sIQrbLSiUZRJ11Fc-Sb3HM8s4hkb6YlLaJdb-zc3VtUQYpWWqtyGgVEDvXrM4Zv-Xazjn29xnlj_2zvwCorDFjK8YKeFadxmMotyonieh4eSO0nIhV-grBPVSBtP-a2UD5aOoXodxUP8eJWqGVga5cmQ1H9Dwm8mUbXMT_tr2AIYWpXmkwIFNiXewMpXTUOcwxMOcbLzueMDl8sY0GO_GYgjNVrjP_n_zUBY6WvzXaLwTEJAzqbgomS8YcNpV6bhquTjKEjzM5zzbopO3vuWhfylTVuX3TCivzOOTvVNwVnOGNUQK6TM_T32Z58zPFRzWrfJKOJbdaWme6wuuzJGTj_k0-chcGsm-k5Yo1pNP-JQBcqdoVE10sGmiexVDFXoZ3WYL3f-VGpOvKooN2JCFESEUoix6nBRoWMSJWp26mCSOdn4dW-8F2RseRnsVkDsb4MF5SJyXNrsFgB6uOlPtA0_3vzCowgzKKjZutwAUY5EYAMt3kRBnsPj3oJhtVT7zZ_WDajhcH1X8PtHXacUQE
openUrl	ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.atitle=On+the+Use+of+Two-Way+Fixed+Effects+Regression+Models+for+Causal+Inference+with+Panel+Data&rft.jtitle=Political+analysis&rft.au=Imai%2C+Kosuke&rft.au=In+Song+Kim&rft.date=2021-07-01&rft.pub=Cambridge+University+Press&rft.issn=1047-1987&rft.eissn=1476-4989&rft.volume=29&rft.issue=3&rft.spage=405&rft.epage=415&rft_id=info:doi/10.1017%2Fpan.2020.33&rft.externalDBID=HAS_PDF_LINK
thumbnail_l	http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=1047-1987&client=summon
thumbnail_m	http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=1047-1987&client=summon
thumbnail_s	http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=1047-1987&client=summon