Zero-diagonality as a linear structure
Author
Abstract
Suggested Citation
DOI: 10.1016/j.econlet.2020.109513
Download full text from publisher
As the access to this document is restricted, you may want to look for a different version below or search for a different version of it.
Other versions of this item:
- Jan R. Magnus & Enrique Sentana, 2020. "Zero-Diagonality as a Linear Structure," Working Papers wp2020_2016, CEMFI.
- Jan R. Magnus & Enrique Sentana, 2020. "Zero-diagonality as a linear structure," Tinbergen Institute Discussion Papers 20-039/III, Tinbergen Institute.
References listed on IDEAS
- de Paula, Aureo & Rasul, Imran & Souza, Pedro, 2018.
"Identifying Network Ties from Panel Data: Theory and an Application to Tax Competition,"
CEPR Discussion Papers
12792, C.E.P.R. Discussion Papers.
- Áureo de Paula & Imran Rasul & Pedro CL Souza, 2019. "Identifying network ties from panel data: theory and an application to tax competition," CeMMAP working papers CWP55/19, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
- Áureo de Paula & Imran Rasul & Pedro CL Souza, 2023. "Identifying network ties from panel data: Theory and an application to tax competition," CeMMAP working papers 21/23, Institute for Fiscal Studies.
- Áureo de Paula & Imran Rasul & Pedro CL Souza, 2023. "Identifying network ties from panel data: theory and an application to tax competition," IFS Working Papers WCWP21/23, Institute for Fiscal Studies.
- Imran Rasul & Pedro Souza & Aureo de Paula, 2023. "Identifying Network Ties from Panel Data: Theory and an application to tax competition," POID Working Papers 081, Centre for Economic Performance, LSE.
- Áureo de Paula & Imran Rasul & Pedro CL Souza, 2023. "Identifying network ties from panel data: theory and an application to tax competition," CeMMAP working papers 02/23, Institute for Fiscal Studies.
- Aureo de Paula & Imran Rasul & Pedro Souza, 2019. "Identifying Network Ties from Panel Data: Theory and an Application to Tax Competition," Papers 1910.07452, arXiv.org, revised Oct 2023.
- Lanne, Markku & Meitz, Mika & Saikkonen, Pentti, 2017.
"Identification and estimation of non-Gaussian structural vector autoregressions,"
Journal of Econometrics, Elsevier, vol. 196(2), pages 288-304.
- Markku Lanne & Mika Meitz & Pentti Saikkonen, 2015. "Identification and estimation of non-Gaussian structural vector autoregressions," CREATES Research Papers 2015-16, Department of Economics and Business Economics, Aarhus University.
- Áureo de Paula & Imran Rasul & Pedro CL Souza, 2018.
"Recovering social networks from panel data: identification, simulations and an application,"
CeMMAP working papers
CWP58/18, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
- Ã ureo de Paula & Imran Rasul & Pedro Souza, 2018. "Recovering Social Networks from Panel Data: Identification, Simulations and an Application," Working Papers 2018-013, Human Capital and Economic Opportunity Working Group.
- Áureo de Paula & Imran Rasul & Pedro CL Souza, 2018. "Recovering social networks from panel data: identification, simulations and an application," CeMMAP working papers CWP17/18, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
- Aureo de Paula & Imran Rasul & Pedro CL Souza, 2018. "Recovering social networks from panel data: Identification, simulations and an application," Documentos de Trabajo 16173, The Latin American and Caribbean Economic Association (LACEA).
Citations
Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
Cited by:
- Dante Amengual & Gabriele Fiorentini & Enrique Sentana, 2022.
"Moment tests of independent components,"
SERIEs: Journal of the Spanish Economic Association, Springer;Spanish Economic Association, vol. 13(1), pages 429-474, May.
- Dante Amengual & Gabriele Fiorentini & Enrique Sentana, 2021. "Moment tests of independent components," Working Papers wp2021_2102, CEMFI.
- Fiorentini, Gabriele & Sentana, Enrique, 2023.
"Discrete mixtures of normals pseudo maximum likelihood estimators of structural vector autoregressions,"
Journal of Econometrics, Elsevier, vol. 235(2), pages 643-665.
- Sentana, Enrique & Fiorentini, Gabriele, 2020. "Discrete Mixtures of Normals Pseudo Maximum Likelihood Estimators of Structural Vector Autoregressions," CEPR Discussion Papers 15411, C.E.P.R. Discussion Papers.
- Gabriele Fiorentini & Enrique Sentana, 2020. "Discrete Mixtures of Normals Pseudo Maximum Likelihood Estimators of Structural Vector Autoregressions," Working Papers wp2020_2023, CEMFI.
Most related items
These are the items that most often cite the same works as this one and are cited by the same works as this one.- Marco Battaglini & Eleonora Patacchini & Edoardo Rainone, 2019.
"Endogenous Social Connections in Legislatures,"
NBER Working Papers
25988, National Bureau of Economic Research, Inc.
- Patacchini, Eleonora & Battaglini, Marco & Rainone, Edoardo, 2019. "Endogenous Social Connections in Legislatures," CEPR Discussion Papers 13845, C.E.P.R. Discussion Papers.
- Yann Bramoullé & Habiba Djebbari & Bernard Fortin, 2020.
"Peer Effects in Networks: A Survey,"
Annual Review of Economics, Annual Reviews, vol. 12(1), pages 603-629, August.
- Bramoullé, Yann & Djebbari, Habiba & Fortin, Bernard, 2019. "Peer Effects in Networks: a Survey," CEPR Discussion Papers 14260, C.E.P.R. Discussion Papers.
- Yann Bramoullé & Habiba Djebbari & Bernard Fortin, 2020. "Peer Effects in Networks: A Survey," CIRANO Working Papers 2020s-02, CIRANO.
- Yann Bramoullé & Habiba Djebbari & Bernard Fortin, 2019. "Peer Effects in Networks: a Survey," Working Papers halshs-02440709, HAL.
- Yann Bramoullé & Habiba Djebbari & Bernard Fortin, 2020. "Peer Effects in Networks: a Survey," AMSE Working Papers 1936, Aix-Marseille School of Economics, France.
- Bramoullé, Yann & Djebbari, Habiba & Fortin, Bernard, 2020. "Peer Effects in Networks: A Survey," IZA Discussion Papers 12947, Institute of Labor Economics (IZA).
- Yann Bramoullé & Habiba Djebbari & Bernard Fortin, 2020. "Peer Effects in Networks: A Survey," Post-Print hal-03072119, HAL.
- Luisa Corrado & Roberta Distante & Majlinda Joxhe, 2019.
"Body mass index and social interactions from adolescence to adulthood,"
Spatial Economic Analysis, Taylor & Francis Journals, vol. 14(4), pages 425-445, October.
- Luisa Corrado & Roberta Distante & Majlinda Joxhe, 2019. "Body Mass Index and Social Interactions from Adolescence to Adulthood," DEM Discussion Paper Series 19-06, Department of Economics at the University of Luxembourg.
- Zhou, Wenyu, 2019. "A network social interaction model with heterogeneous links," Economics Letters, Elsevier, vol. 180(C), pages 50-53.
- Hossein Alidaee & Eric Auerbach & Michael P. Leung, 2020. "Recovering Network Structure from Aggregated Relational Data using Penalized Regression," Papers 2001.06052, arXiv.org.
- Promit K. Chaudhuri & Sudipta Sarangi & Hector Tzavellas, 2023. "Games Under Network Uncertainty," Papers 2305.03124, arXiv.org, revised Jul 2023.
- Candelaria, Luis E. & Ura, Takuya, 2020. "Identification and Inference of Network Formation Games with Misclassified Links," The Warwick Economics Research Paper Series (TWERPS) 1258, University of Warwick, Department of Economics.
- Ayden Higgins & Federico Martellosio, 2019. "Shrinkage Estimation of Network Spillovers with Factor Structured Errors," Papers 1909.02823, arXiv.org, revised Nov 2021.
- Hsieh, Chih-Sheng & Hsu, Yu-Chin & Ko, Stanley I.M. & Kovářík, Jaromír & Logan, Trevon D., 2024. "Non-representative sampled networks: Estimation of network structural properties by weighting," Journal of Econometrics, Elsevier, vol. 240(1).
- Victor Chernozhukov & Chen Huang & Weining Wang, 2021. "Uniform Inference on High-dimensional Spatial Panel Networks," Papers 2105.07424, arXiv.org, revised Sep 2023.
- Michael Delgado & Meilin Ma & H. Holly Wang, 2021.
"Exploring Spatial Price Relationships: The Case of African Swine Fever in China,"
NBER Chapters, in: Risks in Agricultural Supply Chains,
National Bureau of Economic Research, Inc.
- Michael S. Delgado & Meilin Ma & H. Holly Wang, 2021. "Exploring Spatial Price Relationships: The Case of African Swine Fever in China," NBER Working Papers 29141, National Bureau of Economic Research, Inc.
- Chih-Sheng Hsieh & Stanley I. M. Ko & Jaromír Kovářík & Trevon Logan, 2018. "Non-Randomly Sampled Networks: Biases and Corrections," NBER Working Papers 25270, National Bureau of Economic Research, Inc.
- Boucher, Vincent, 2020. "Equilibrium homophily in networks," European Economic Review, Elsevier, vol. 123(C).
- Patacchini, Eleonora & Hsieh, Chih-Sheng & Lin, Xu, 2019. "Social Interaction Methods," CEPR Discussion Papers 14141, C.E.P.R. Discussion Papers.
- Francesca Parise & Asuman Ozdaglar, 2023. "Graphon Games: A Statistical Framework for Network Games and Interventions," Econometrica, Econometric Society, vol. 91(1), pages 191-225, January.
- Arthur Lewbel & Xi Qu & Xun Tang, 2021. "Social Networks with Mismeasured Links," Boston College Working Papers in Economics 1031, Boston College Department of Economics.
- Nail Kashaev & Natalia Lazzati, 2019. "Peer Effects in Random Consideration Sets," Papers 1904.06742, arXiv.org, revised May 2021.
- Arthur Lewbel & Xi Qu & Xun Tang, 2023.
"Social Networks with Unobserved Links,"
Journal of Political Economy, University of Chicago Press, vol. 131(4), pages 898-946.
- Arthur Lewbel & Xi Qu & Xun Tang, 2019. "Social Networks with Unobserved Links," Boston College Working Papers in Economics 1004, Boston College Department of Economics, revised 15 Jul 2022.
- Pol Antràs & David Zilberman, 2022. "Introduction to "Risks in Agricultural Supply Chains"," NBER Chapters, in: Risks in Agricultural Supply Chains, pages 1-12, National Bureau of Economic Research, Inc.
- Sentana, Enrique, 2024.
"Finite underidentification,"
Journal of Econometrics, Elsevier, vol. 240(1).
- Enrique Sentana, 2015. "Finite Underidentification," Working Papers wp2015_1508, CEMFI.
More about this item
Keywords
Diagonality; Networks; Restricted matrices; Spatial econometric models; Structural vector autoregressions;All these keywords.
JEL classification:
- C65 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Miscellaneous Mathematical Tools
- C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
- C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
Statistics
Access and download statisticsCorrections
All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:ecolet:v:196:y:2020:i:c:s016517652030313x. See general information about how to correct material in RePEc.
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/ecolet .
Please note that corrections may take a couple of weeks to filter through the various RePEc services.