Akanksha Negi

Personal Details

First Name:	Akanksha
Middle Name:
Last Name:	Negi
Suffix:
RePEc Short-ID:	pne376
	[This author has chosen not to make the email address public]
	https://www.anegi.net/

Affiliation

Department of Econometrics and Business Statistics
Monash Business School
Monash University

Melbourne, Australia
http://business.monash.edu/econometrics-and-business-statistics
RePEc:edi:dxmonau (more details at EDIRC)

Citations

Many of the citations below have been collected in an experimental project, CitEc, where a more detailed citation analysis can be found. These are citations from works listed in RePEc that could be analyzed mechanically. So far, only a minority of all works could be analyzed. See under "Corrections" how you can help improve the citation analysis.

Working papers

1. Akanksha Negi & Digvijay Singh Negi, 2022. "Difference-in-Differences with a Misclassified Treatment," Papers 2208.02412, arXiv.org.

   Cited by:

   1. Justin Contat & William M. Doerner & Robert N. Renner & Malcolm J. Rogers, 2024. "Measuring Price Effects from Disasters using Public Data: A Case Study of Hurricane Ian," FHFA Staff Working Papers 24-04, Federal Housing Finance Agency.

2. Akanksha Negi & Jeffrey M. Wooldridge, 2020. "Robust and Efficient Estimation of Potential Outcome Means under Random Assignment," Papers 2010.01800, arXiv.org, revised Aug 2024.

   Cited by:

   1. John List & Ian Muir & Gregory Sun, 2022. "Using Machine Learning for Efficient Flexible Regression Adjustment in Economic Experiments," Natural Field Experiments 00763, The Field Experiments Website.
      • John A. List & Ian Muir & Gregory K. Sun, 2022. "Using Machine Learning for Efficient Flexible Regression Adjustment in Economic Experiments," NBER Working Papers 30756, National Bureau of Economic Research, Inc.

3. Akanksha Negi, 2020. "Doubly weighted M-estimation for nonrandom assignment and missing outcomes," Papers 2011.11485, arXiv.org.

   Cited by:

   1. Rahul Singh, 2021. "Generalized Kernel Ridge Regression for Causal Inference with Missing-at-Random Sample Selection," Papers 2111.05277, arXiv.org.

4. Negi, Akanksha & Roy, Devesh, 2015. "The cooling effect of pulse imports on price: The case of the pigeon pea in India:," IFPRI discussion papers 1439, International Food Policy Research Institute (IFPRI).

   Cited by:

   1. Joshi, Pramod Kumar & Kishore, Avinash & Roy, Devesh, 2016. "Making pulses affordable again: Policy options from the farm to retail in India:," IFPRI discussion papers 1555, International Food Policy Research Institute (IFPRI).
      • P.K. Joshi & Avinash Kishore & Devesh Roy, 2016. "Making Pulses Affordable Again: Policy Options from the Farm to Retail in India," Working Papers id:11327, eSocialSciences.
   2. Vijay Laxmi Pandey & S. Mahendra Dev & Ranjeeta Mishra, 2019. "Pulses in eastern India: production barriers and consumption coping strategies," Food Security: The Science, Sociology and Economics of Food Production and Access to Food, Springer;The International Society for Plant Pathology, vol. 11(3), pages 609-622, June.
   3. Ranjit Kumar & K. V. Raju, 2018. "Leveraging Policies for Self Sufficiency in Pulses in India," Journal of Development Policy and Practice, , vol. 3(2), pages 155-178, July.
   4. Joshi, Pramod Kumar & Rao, P. Parthasarathy, 2016. "Global and regional pulse economies: Current trends and outlook:," IFPRI discussion papers 1544, International Food Policy Research Institute (IFPRI).

Articles

1. Akanksha Negi & Jeffrey M. Wooldridge, 2021. "Revisiting regression adjustment in experiments with heterogeneous treatment effects," Econometric Reviews, Taylor & Francis Journals, vol. 40(5), pages 504-534, April.

   Cited by:

   1. Negi Akanksha, 2024. "Doubly weighted M-estimation for nonrandom assignment and missing outcomes," Journal of Causal Inference, De Gruyter, vol. 12(1), pages 1-25.
   2. Stanislao Maldonado & Deborah Martinez & Lina Diaz, 2024. "Building a shield together: Addressing low vaccine uptake against cancer through social norms," Working Papers 202, Peruvian Economic Association.
   3. Joao M.C. Santos Silva & Rainer Winkelmann, 2024. "MisspecifiÂ…ed Exponential Regressions: Estimation, Interpretation, and Average Marginal Effects," School of Economics Discussion Papers 0124, School of Economics, University of Surrey.
   4. Jiang, Liang & Phillips, Peter C.B. & Tao, Yubo & Zhang, Yichong, 2023. "Regression-adjusted estimation of quantile treatment effects under covariate-adaptive randomizations," Journal of Econometrics, Elsevier, vol. 234(2), pages 758-776.
      • Liang Jiang & Peter C. B. Phillips & Yubo Tao & Yichong Zhang, 2021. "Regression-Adjusted Estimation of Quantile Treatment Effects under Covariate-Adaptive Randomizations," Papers 2105.14752, arXiv.org, revised Sep 2022.
      • Liang Jiang & Xiaobin Liu & Peter C.B. Phillips & Yichong Zhang, 2021. "Regression-Adjusted Estimation of Quantile Treatment Effects under Covariate-Adaptive Randomizations," Cowles Foundation Discussion Papers 2288, Cowles Foundation for Research in Economics, Yale University.
   5. John List & Ian Muir & Gregory Sun, 2022. "Using Machine Learning for Efficient Flexible Regression Adjustment in Economic Experiments," Natural Field Experiments 00763, The Field Experiments Website.
      • John A. List & Ian Muir & Gregory K. Sun, 2022. "Using Machine Learning for Efficient Flexible Regression Adjustment in Economic Experiments," NBER Working Papers 30756, National Bureau of Economic Research, Inc.
   6. Tymon Sloczynski, 2020. "Interpreting OLS Estimands When Treatment Effects Are Heterogeneous: Smaller Groups Get Larger Weights," CESifo Working Paper Series 8331, CESifo.
      • Tymon SÅ‚oczyÅ„ski, 2022. "Interpreting OLS Estimands When Treatment Effects Are Heterogeneous: Smaller Groups Get Larger Weights," The Review of Economics and Statistics, MIT Press, vol. 104(3), pages 501-509, May.
      • Sloczynski, Tymon, 2020. "Interpreting OLS Estimands When Treatment Effects Are Heterogeneous: Smaller Groups Get Larger Weights," IZA Discussion Papers 13283, Institute of Labor Economics (IZA).
   7. Tatsushi Oka & Shota Yasui & Yuta Hayakawa & Undral Byambadalai, 2024. "Regression Adjustment for Estimating Distributional Treatment Effects in Randomized Controlled Trials," Papers 2407.14074, arXiv.org.
   8. Undral Byambadalai & Tatsushi Oka & Shota Yasui, 2024. "Estimating Distributional Treatment Effects in Randomized Experiments: Machine Learning for Variance Reduction," Papers 2407.16037, arXiv.org.
   9. Zhao, Anqi & Ding, Peng, 2021. "Covariate-adjusted Fisher randomization tests for the average treatment effect," Journal of Econometrics, Elsevier, vol. 225(2), pages 278-294.
   10. Zhao, Anqi & Ding, Peng, 2024. "No star is good news: A unified look at rerandomization based on p-values from covariate balance tests," Journal of Econometrics, Elsevier, vol. 241(1).
   11. Haoge Chang, 2023. "Design-based Estimation Theory for Complex Experiments," Papers 2311.06891, arXiv.org.
   12. Andrews Doeh Agblobi & Anthony Kofi Osei-Fosu & Hadrat Yusif, 2020. "Poverty Response to the Household Type of Elderly and Old-Age Pension," Business and Management Research, Business and Management Research, Sciedu Press, vol. 9(4), pages 1-20, December.
   13. Jeffrey M Wooldridge, 2023. "Simple approaches to nonlinear difference-in-differences with panel data," The Econometrics Journal, Royal Economic Society, vol. 26(3), pages 31-66.
   14. Yuehao Bai & Azeem M. Shaikh & Max Tabord-Meehan, 2024. "A Primer on the Analysis of Randomized Experiments and a Survey of some Recent Advances," Papers 2405.03910, arXiv.org.
   15. Siddik, Abu Bakkar & Khan, Samiha & Khan, Uzma & Yong, Li & Murshed, Muntasir, 2023. "The role of renewable energy finance in achieving low-carbon growth: contextual evidence from leading renewable energy-investing countries," Energy, Elsevier, vol. 270(C).
   16. Murshed, Muntasir & Apergis, Nicholas & Alam, Md Shabbir & Khan, Uzma & Mahmud, Sakib, 2022. "The impacts of renewable energy, financial inclusivity, globalization, economic growth, and urbanization on carbon productivity: Evidence from net moderation and mediation effects of energy efficiency," Renewable Energy, Elsevier, vol. 196(C), pages 824-838.
   17. Max Cytrynbaum, 2023. "Covariate Adjustment in Stratified Experiments," Papers 2302.03687, arXiv.org, revised Jul 2024.
   18. Bai, Yuehao & Jiang, Liang & Romano, Joseph P. & Shaikh, Azeem M. & Zhang, Yichong, 2024. "Covariate adjustment in experiments with matched pairs," Journal of Econometrics, Elsevier, vol. 241(1).
       • Yuehao Bai & Liang Jiang & Joseph P. Romano & Azeem M. Shaikh & Yichong Zhang, 2023. "Covariate Adjustment in Experiments with Matched Pairs," Papers 2302.04380, arXiv.org, revised Oct 2023.
   19. Liang Jiang & Oliver B. Linton & Haihan Tang & Yichong Zhang, 2022. "Improving Estimation Efficiency via Regression-Adjustment in Covariate-Adaptive Randomizations with Imperfect Compliance," Papers 2201.13004, arXiv.org, revised Jun 2023.
   20. Lihua Lei, 2024. "Causal Interpretation of Regressions With Ranks," Papers 2406.05548, arXiv.org.
   21. Sebastian Schongen, 2023. "Digitalisation as a Prospect for Work–Life Balance and Inclusion: A Natural Experiment in German Hospitals," Social Inclusion, Cogitatio Press, vol. 11(4), pages 225-238.

Chapters

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More information

Research fields, statistics, top rankings, if available.

Statistics

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Co-authorship network on CollEc

NEP Fields

NEP is an announcement service for new working papers, with a weekly report in each of many fields. This author has had 4 papers announced in NEP. These are the fields, ordered by number of announcements, along with their dates. If the author is listed in the directory of specialists for this field, a link is also provided.

1. NEP-ECM: Econometrics (3) 2020-10-19 2020-12-14 2022-09-12. Author is listed
2. NEP-NET: Network Economics (1) 2022-06-27. Author is listed
3. NEP-RMG: Risk Management (1) 2022-06-27. Author is listed

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