David Eric Kohns
Personal Details
First Name: | David |
Middle Name: | Eric |
Last Name: | Kohns |
Suffix: | |
RePEc Short-ID: | pko984 |
| |
https://sites.google.com/view/davidkohns/home | |
Affiliation
(50%) Centre for Energy Economics Research and Policy (CEERP)
Heriot-Watt University
Edinburgh, United Kingdomhttp://ceerp.hw.ac.uk/
RePEc:edi:ceehwuk (more details at EDIRC)
(50%) Department of Accountancy, Economics and Finance
Heriot-Watt University
Edinburgh, United Kingdomhttps://www.hw.ac.uk/uk/schools/social-sciences/accountancy-economics-finance.htm
RePEc:edi:dehwuuk (more details at EDIRC)
Research output
Jump to: Working papersWorking papers
- David Kohns & Tibor Szendrei, 2021. "Decoupling Shrinkage and Selection for the Bayesian Quantile Regression," Papers 2107.08498, arXiv.org.
- David Kohns & Arnab Bhattacharjee, 2020.
"Nowcasting Growth using Google Trends Data: A Bayesian Structural Time Series Model,"
Papers
2011.00938, arXiv.org, revised May 2022.
- Bhattacharjee, Arnab & Kohns, David, 2022. "Nowcasting Growth using Google Trends Data: A Bayesian Structural Time Series Model," National Institute of Economic and Social Research (NIESR) Discussion Papers 538, National Institute of Economic and Social Research.
- David Kohns & Tibor Szendrei, 2020. "Horseshoe Prior Bayesian Quantile Regression," Papers 2006.07655, arXiv.org, revised Mar 2021.
- David Kohns & Arnab Bhattacharjee, 2019. "Interpreting Big Data in the Macro Economy: A Bayesian Mixed Frequency Estimator," CEERP Working Paper Series 010, Centre for Energy Economics Research and Policy, Heriot-Watt University.
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
- David Kohns & Tibor Szendrei, 2021.
"Decoupling Shrinkage and Selection for the Bayesian Quantile Regression,"
Papers
2107.08498, arXiv.org.
Cited by:
- Jan Pruser & Florian Huber, 2023.
"Nonlinearities in Macroeconomic Tail Risk through the Lens of Big Data Quantile Regressions,"
Papers
2301.13604, arXiv.org, revised Sep 2023.
- Jan Prüser & Florian Huber, 2024. "Nonlinearities in macroeconomic tail risk through the lens of big data quantile regressions," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 39(2), pages 269-291, March.
- Szendrei, Tibor & Varga, Katalin, 2023. "Revisiting vulnerable growth in the Euro Area: Identifying the role of financial conditions in the distribution," Economics Letters, Elsevier, vol. 223(C).
- Jan Pruser & Florian Huber, 2023.
"Nonlinearities in Macroeconomic Tail Risk through the Lens of Big Data Quantile Regressions,"
Papers
2301.13604, arXiv.org, revised Sep 2023.
- David Kohns & Arnab Bhattacharjee, 2020.
"Nowcasting Growth using Google Trends Data: A Bayesian Structural Time Series Model,"
Papers
2011.00938, arXiv.org, revised May 2022.
- Bhattacharjee, Arnab & Kohns, David, 2022. "Nowcasting Growth using Google Trends Data: A Bayesian Structural Time Series Model," National Institute of Economic and Social Research (NIESR) Discussion Papers 538, National Institute of Economic and Social Research.
Cited by:
- David Kohns & Tibor Szendrei, 2021. "Decoupling Shrinkage and Selection for the Bayesian Quantile Regression," Papers 2107.08498, arXiv.org.
- Lolić, Ivana & Matošec, Marina & Sorić, Petar, 2024. "DIY google trends indicators in social sciences: A methodological note," Technology in Society, Elsevier, vol. 77(C).
- Kohns, David & Potjagailo, Galina, 2023. "Flexible Bayesian MIDAS: time‑variation, group‑shrinkage and sparsity," Bank of England working papers 1025, Bank of England.
- David Kohns & Tibor Szendrei, 2020.
"Horseshoe Prior Bayesian Quantile Regression,"
Papers
2006.07655, arXiv.org, revised Mar 2021.
Cited by:
- Andrea Carriero & Todd E. Clark & Massimiliano Marcellino, 2022.
"Specification Choices in Quantile Regression for Empirical Macroeconomics,"
Working Papers
22-25, Federal Reserve Bank of Cleveland.
- Carriero, Andrea & Clark, Todd & Marcellino, Massimiliano, 2024. "Specification Choices in Quantile Regression for Empirical Macroeconomics," CEPR Discussion Papers 18901, C.E.P.R. Discussion Papers.
- James Mitchell & Aubrey Poon & Dan Zhu, 2022.
"Constructing Density Forecasts from Quantile Regressions: Multimodality in Macro-Financial Dynamics,"
Working Papers
22-12R, Federal Reserve Bank of Cleveland, revised 11 Apr 2023.
- James Mitchell & Aubrey Poon & Dan Zhu, 2024. "Constructing density forecasts from quantile regressions: Multimodality in macrofinancial dynamics," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 39(5), pages 790-812, August.
- Michael Pfarrhofer, 2021.
"Modeling tail risks of inflation using unobserved component quantile regressions,"
Papers
2103.03632, arXiv.org, revised Oct 2021.
- Pfarrhofer, Michael, 2022. "Modeling tail risks of inflation using unobserved component quantile regressions," Journal of Economic Dynamics and Control, Elsevier, vol. 143(C).
- Andrea Carriero & Todd E. Clark & Massimiliano Marcellino, 2022.
"Specification Choices in Quantile Regression for Empirical Macroeconomics,"
Working Papers
22-25, Federal Reserve Bank of Cleveland.
- David Kohns & Arnab Bhattacharjee, 2019.
"Interpreting Big Data in the Macro Economy: A Bayesian Mixed Frequency Estimator,"
CEERP Working Paper Series
010, Centre for Energy Economics Research and Policy, Heriot-Watt University.
Cited by:
- Meyer-Gohde, Alexander & Shabalina, Ekaterina, 2022. "Estimation and forecasting using mixed-frequency DSGE models," IMFS Working Paper Series 175, Goethe University Frankfurt, Institute for Monetary and Financial Stability (IMFS).
- Cristea, R. G., 2020. "Can Alternative Data Improve the Accuracy of Dynamic Factor Model Nowcasts?," Cambridge Working Papers in Economics 20108, Faculty of Economics, University of Cambridge.
More information
Research fields, statistics, top rankings, if available.Statistics
Access and download statistics for all items
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.- NEP-ECM: Econometrics (3) 2020-07-20 2020-12-07 2021-08-09. Author is listed
- NEP-BIG: Big Data (1) 2020-12-07. Author is listed
- NEP-CMP: Computational Economics (1) 2020-12-07. Author is listed
- NEP-ETS: Econometric Time Series (1) 2020-11-23. Author is listed
- NEP-FDG: Financial Development and Growth (1) 2021-08-09. Author is listed
- NEP-FOR: Forecasting (1) 2020-12-07. Author is listed
- NEP-ICT: Information and Communication Technologies (1) 2020-11-23. Author is listed
- NEP-MAC: Macroeconomics (1) 2020-12-07. Author is listed
- NEP-RMG: Risk Management (1) 2021-08-09. Author is listed
Corrections
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