create a website

Econometric Inference for High Dimensional Predictive Regressions. (2024). Lee, Ji Hyung ; Mei, Ziwei ; Shi, Zhentao ; Gao, Zhan.
In: Papers.
RePEc:arx:papers:2409.10030.

Full description at Econpapers || Download paper

Cited: 0

Citations received by this document

Cites: 67

References cited by this document

Cocites: 41

Documents which have cited the same bibliography

Coauthors: 0

Authors who have wrote about the same topic

Citations

Citations received by this document

    This document has not been cited yet.

References

References cited by this document

  1. Adamek, R., Smeekes, S., and Wilms, I. (2023). Lasso inference for high-dimensional time series. Journal of Econometrics, 235(2), 1114–1143.

  2. Babii, A., Ghysels, E., and Striaukas, J. (2022). Machine learning time series regressions with an application to nowcasting.

  3. Belloni, A., Chen, D., Chernozhukov, V., and Hansen, C. (2012). Sparse models and methods for optimal instruments with an application to eminent domain. Econometrica, 80(6), 2369–2429.

  4. Benati, L. (2015). The long-run Phillips curve: A structural VAR investigation. Journal of Monetary Economics, 76, 15–28.

  5. Bickel, P. J., Ritov, Y., and Tsybakov, A. B. (2009). Simultaneous analysis of Lasso and Dantzig selector. The Annals of Statistics, 37(4), 1705–1732.
    Paper not yet in RePEc: Add citation now
  6. Bykhovskaya, A. and Gorin, V. (2022). Cointegration in large VARs. The Annals of Statistics, 50(3), 1593–1617.
    Paper not yet in RePEc: Add citation now

  7. Cai, Z. and Wang, Y. (2014). Testing predictive regression models with nonstationary regressors. Journal of Econometrics, 178, 4–14.

  8. Cai, Z., Chen, H., and Liao, X. (2023). A new robust inference for predictive quantile regression. Journal of Econometrics, 234(1), 227–250.

  9. Campbell, J. Y. and Yogo, M. (2006). Efficient tests of stock return predictability. Journal of Financial Economics, 81(1), 27–60.

  10. Caner, M. and Kock, A. B. (2018). Asymptotically honest confidence regions for high dimensional parameters by the desparsified conservative Lasso. Journal of Econometrics, 203(1), 143–168.

  11. Chernozhukov, V., Chetverikov, D., Demirer, M., Duflo, E., Hansen, C., Newey, W., and Robins, J. (2018). Double/debiased machine learning for treatment and structural parameters. The Econometrics Journal, 21(1), C1–C68.

  12. Chernozhukov, V., Escanciano, J. C., Ichimura, H., Newey, W. K., and Robins, J. M. (2022a). Locally robust semiparametric estimation. Econometrica, 90(4), 1501–1535.

  13. Chernozhukov, V., Newey, W. K., and Singh, R. (2022b). Automatic debiased machine learning of causal and structural effects. Econometrica, 90(3), 967–1027.

  14. Davydov, Y. A. (1968). Convergence of distributions generated by stationary stochastic processes. Theory of Probability & Its Applications, 13(4), 691–696.
    Paper not yet in RePEc: Add citation now

  15. Demetrescu, M., Georgiev, I., Rodrigues, P. M., and Taylor, A. R. (2023). Extensions to IVX methods of inference for return predictability. Journal of Econometrics, 237(2), 105271.

  16. Deshpande, Y., Javanmard, A., and Mehrabi, M. (2023). Online debiasing for adaptively collected high-dimensional data with applications to time series analysis. Journal of the American Statistical Association, 118(542), 1126–1139.

  17. Dimand, R. W. and Geanakoplos, J. (2005). Celebrating Irving Fisher: The legacy of a great economist. The American Journal of Economics and Sociology, 64(1), 3–vi.

  18. Dominguez, K. M., Fair, R. C., and Shapiro, M. D. (1988). Forecasting the depression: Harvard versus Yale. The American Economic Review, (pp. 595–612).

  19. Engemann, K. (2020). What is the Phillips curve (and why has it flattened)? Federal Reserve Bank of St. Louis, January, 14.
    Paper not yet in RePEc: Add citation now

  20. Fan, Q., Guo, Z., Mei, Z., and Zhang, C.-H. (2023). Uniform inference for nonlinear endogenous treatment effects with high-dimensional covariates. arXiv preprint arXiv:2310.08063.

  21. Fan, R. and Lee, J. H. (2019). Predictive quantile regressions under persistence and conditional heteroskedasticity. Journal of Econometrics, 213(1), 261–280.

  22. Fisher, I. (1925). Our unstable dollar and the so-called business cycle. Journal of the American Statistical Association, 20(150), 179–202.
    Paper not yet in RePEc: Add citation now
  23. Fisher, I. (1926). A statistical relation between unemployment and price changes. International Labour Review, 13, 785–792.
    Paper not yet in RePEc: Add citation now
  24. Fisher, I. (1973). I discovered the Phillips curve: ‘A statistical relation between unemployment and price changes’. Journal of Political Economy, 81(2, Part 1), 496–502.
    Paper not yet in RePEc: Add citation now
  25. Fu, W. and Knight, K. (2000). Asymptotics for Lasso-type estimators. The Annals of Statistics, 28(5), 1356–1378.
    Paper not yet in RePEc: Add citation now

  26. Giannone, D., Lenza, M., and Primiceri, G. E. (2021). Economic predictions with big data: The illusion of sparsity.

  27. Gold, D., Lederer, J., and Tao, J. (2020). Inference for high-dimensional instrumental variables regression. Journal of Econometrics, 217(1), 79–111.

  28. Granger, C. W. and Newbold, P. (1974). Spurious regressions in econometrics. Journal of Econometrics, 2(2), 111–120.

  29. Jansson, M. and Moreira, M. J. (2006). Optimal inference in regression models with nearly integrated regressors. Econometrica, 74(3), 681–714.

  30. Javanmard, A. and Montanari, A. (2014). Confidence intervals and hypothesis testing for high-dimensional regression.
    Paper not yet in RePEc: Add citation now

  31. Koo, B., Anderson, H. M., Seo, M. H., and Yao, W. (2020). High-dimensional predictive regression in the presence of cointegration. Journal of Econometrics, 219(2), 456–477.

  32. Kostakis, A., Magdalinos, T., and Stamatogiannis, M. P. (2015). Robust econometric inference for stock return predictability.

  33. Kostakis, A., Magdalinos, T., and Stamatogiannis, M. P. (2018). Taking stock of long-horizon predictability tests: Are factor returns predictable? Available at SSRN 3284149.
    Paper not yet in RePEc: Add citation now

  34. Lee, J. H. (2016). Predictive quantile regression with persistent covariates: IVX-QR approach. Journal of Econometrics, 192(1), 105–118.

  35. Lee, J. H., Shi, Z., and Gao, Z. (2022). On LASSO for predictive regression. Journal of Econometrics, 229(2), 322–349.
    Paper not yet in RePEc: Add citation now
  36. Lin, Z. and Lu, C. (1997). Limit theory for mixing dependent random variables, volume 378. Springer Science & Business Media.
    Paper not yet in RePEc: Add citation now
  37. Liu, X., Long, W., Peng, L., and Yang, B. (2023). A unified inference for predictive quantile regression. Journal of the American Statistical Association, (pp. 1–15).
    Paper not yet in RePEc: Add citation now

  38. Liu, X., Yang, B., Cai, Z., and Peng, L. (2019). A unified test for predictability of asset returns regardless of properties of predicting variables. Journal of Econometrics, 208(1), 141–159.

  39. Magdalinos, T. and Phillips, P. C. (2009). Limit theory for cointegrated systems with moderately integrated and moderately explosive regressors. Econometric Theory, 25(2), 482–526.

  40. Mankiw, N. G. (2024). Six beliefs I have about inflation: Remarks prepared for nber conference on “inflation in the covid era and beyond”. Journal of Monetary Economics, (pp. 103631).
    Paper not yet in RePEc: Add citation now

  41. McCracken, M. W. and Ng, S. (2016). FRED-MD: A monthly database for macroeconomic research. Journal of Business & Economic Statistics, 34(4), 574–589.

  42. Medeiros, M. C., Vasconcelos, G. F., Veiga, Á., and Zilberman, E. (2021). Forecasting inflation in a data-rich environment: the benefits of machine learning methods. Journal of Business & Economic Statistics, 39(1), 98–119.

  43. Mei, Z. and Shi, Z. (2024). On LASSO for high dimensional predictive regression. Journal of Econometrics, 242(2), 105809.

  44. Mei, Z., Phillips, P. C., and Shi, Z. (2024). The boosted hodrick-prescott filter is more general than you might think. Journal of Applied Econometrics.
    Paper not yet in RePEc: Add citation now

  45. Onatski, A. and Wang, C. (2018). Alternative asymptotics for cointegration tests in large VARs. Econometrica, 86(4), 1465–1478.

  46. Phillips, A. W. (1958). The relation between unemployment and the rate of change of money wage rates in the united kingdom, 1861-1957. Economica, 25(100), 283–299.

  47. Phillips, P. C. (2015). Halbert White Jr. memorial JFEC lecture: Pitfalls and possibilities in predictive regression. Journal of Financial Econometrics, 13(3), 521–555.

  48. Phillips, P. C. and Lee, J. H. (2013). Predictive regression under various degrees of persistence and robust long-horizon regression. Journal of Econometrics, 177(2), 250–264.

  49. Phillips, P. C. and Lee, J. H. (2016). Robust econometric inference with mixed integrated and mildly explosive regressors. Journal of Econometrics, 192(2), 433–450.

  50. Phillips, P. C. and Magdalinos, T. (2007). Limit theory for moderate deviations from a unit root. Journal of Econometrics, 136(1), 115–130.

  51. Phillips, P. C. and Magdalinos, T. (2009). Econometric inference in the vicinity of unity. Singapore Management University, CoFie Working Paper, 7.
    Paper not yet in RePEc: Add citation now

  52. Phillips, P. C. and Shi, Z. (2021). Boosting: Why you can use the HP filter. International Economic Review, 62(2), 521–570.

  53. Shi, Z. (2016). Estimation of sparse structural parameters with many endogenous variables. Econometric Reviews, 35(8-10), 1582–1608.

  54. Smeekes, S. and Wijler, E. (2018). Macroeconomic forecasting using penalized regression methods. International Journal of Forecasting, 34(3), 408–430.

  55. Smeekes, S. and Wijler, E. (2021). An automated approach towards sparse single-equation cointegration modelling. Journal of Econometrics, 221(1), 247–276.

  56. Stambaugh, R. F. (1999). Predictive regressions. Journal of Financial Economics, 54(3), 375–421.

  57. Step 2. Verifying (A.2). We use the strong Gaussian approximation from Lin and Lu (1997)’s Theorem 9.3.1. Specifically, define g(x) = exp(x). By the sub-exponential tail imposed by Assumption 1, the sub-exponential norm of εk,t, denoted as ∥εk,t∥g in Lin and Lu (1997), is uniformly bounded by an absolute constant. It then suffices to verify the following two conditions required in the aforementioned theorem: (i) Vk,t ≥ ct for some absolute constant c. (ii) P∞ d=1 α(d)1/4 log(1/α(d)) < ∞, where the parameter δ in Lin and Lu (1997, Theorem 9.3.1) is taken as 2.
    Paper not yet in RePEc: Add citation now
  58. Tibshirani, R. (1996). Regression shrinkage and selection via the lasso. Journal of the Royal Statistical Society Series B: Statistical Methodology, 58(1), 267–288.
    Paper not yet in RePEc: Add citation now

  59. Tu, Y. and Xie, X. (2023). Penetrating sporadic return predictability. Journal of Econometrics, 237(1), 105509.

  60. van de Geer, S., Bühlmann, P., Ritov, Y., and Dezeure, R. (2014). On asymptotically optimal confidence regions and tests for high-dimensional models. The Annals of Statistics, 42(3), 1166–1202.
    Paper not yet in RePEc: Add citation now

  61. Xu, K.-L. (2020). Testing for multiple-horizon predictability: Direct regression based versus implication based. The Review of Financial Studies, 33(9), 4403–4443.

  62. Yang, B., Liu, X., Peng, L., and Cai, Z. (2021). Unified tests for a dynamic predictive regression. Journal of Business & Economic Statistics, 39(3), 684–699.

  63. Yang, B., Long, W., Peng, L., and Cai, Z. (2020). Testing the predictability of us housing price index returns based on an IVX-AR model. Journal of the American Statistical Association, 115(532), 1598–1619.

  64. Zhang, C.-H. and Zhang, S. S. (2014). Confidence intervals for low dimensional parameters in high dimensional linear models. Journal of the Royal Statistical Society Series B: Statistical Methodology, 76(1), 217–242.

  65. Zhang, R., Robinson, P., and Yao, Q. (2019). Identifying cointegration by eigenanalysis. Journal of the American Statistical Association, 114(526), 916–927.

  66. Zhang, X. and Cheng, G. (2017). Simultaneous inference for high-dimensional linear models. Journal of the American Statistical Association, 112(518), 757–768.

  67. Zhu, F., Cai, Z., and Peng, L. (2014). Predictive regressions for macroeconomic data. The Annals of Applied Statistics, 8(1), 577 – 594.

Cocites

Documents in RePEc which have cited the same bibliography

  1. Exact Mixed-Frequency Data Sampling (eMIDAS). (2025). Quinlan, Stephen Snudden.
    In: LCERPA Working Papers.
    RePEc:wlu:lcerpa:jc0157.

    Full description at Econpapers || Download paper

  2. Brazilian Selic Rate Forecasting with Deep Neural Networks. (2025). Moreira, Rodrigo ; Rodrigues, Larissa Ferreira ; Silva, Flvio Oliveira.
    In: Computational Economics.
    RePEc:kap:compec:v:65:y:2025:i:3:d:10.1007_s10614-024-10597-2.

    Full description at Econpapers || Download paper

  3. Nowcasting Perus GDP with Machine Learning Methods. (2025). Tang, Juan ; Flores Audante, Jairo ; Ruelas-Huanca, Walter ; Gonzaga, Bruno.
    In: IHEID Working Papers.
    RePEc:gii:giihei:heidwp01-2025.

    Full description at Econpapers || Download paper

  4. Mixingale and physical dependence equality with applications. (2025). Hill, Jonathan B.
    In: Statistics & Probability Letters.
    RePEc:eee:stapro:v:221:y:2025:i:c:s0167715225000252.

    Full description at Econpapers || Download paper

  5. Information loss from perception alignment. (2025). Dalko, Viktoria ; Ardakani, Omid M ; Shim, Hyeeun.
    In: International Review of Economics & Finance.
    RePEc:eee:reveco:v:97:y:2025:i:c:s1059056024008220.

    Full description at Econpapers || Download paper

  6. Forecasting macroeconomic tail risk in real time: Do textual data add value?. (2025). Prser, Jan ; Admmer, Philipp ; Schssler, Rainer A.
    In: International Journal of Forecasting.
    RePEc:eee:intfor:v:41:y:2025:i:1:p:307-320.

    Full description at Econpapers || Download paper

  7. Forecast by mixed-frequency dynamic panel model. (2025). Hu, Mingming ; Chen, Yuxiu ; Liu, Han.
    In: Annals of Tourism Research.
    RePEc:eee:anture:v:110:y:2025:i:c:s0160738324001646.

    Full description at Econpapers || Download paper

  8. Enhancing GDP nowcasts with ChatGPT: a novel application of PMI news releases. (2025). de Bondt, Gabe ; Sun, Yiqiao.
    In: Working Paper Series.
    RePEc:ecb:ecbwps:20253063.

    Full description at Econpapers || Download paper

  9. Panel Machine Learning with Mixed-Frequency Data: Monitoring State-Level Fiscal Variables. (2025). Stevanovic, Dalibor ; Marcellino, Massimiliano ; Coulombe, Philippe Goulet.
    In: CIRANO Working Papers.
    RePEc:cir:cirwor:2025s-15.

    Full description at Econpapers || Download paper

  10. Panel Machine Learning with Mixed-Frequency Data: Monitoring State-Level Fiscal Variables. (2025). Stevanovic, Dalibor ; Marcellino, Massimiliano ; Coulombe, Philippe Goulet.
    In: Working Papers.
    RePEc:bbh:wpaper:25-04.

    Full description at Econpapers || Download paper

  11. Estimation of Latent Group Structures in Time-Varying Panel Data Models. (2025). Smeekes, Stephan ; Haimerl, Paul ; Wilms, Ines.
    In: Papers.
    RePEc:arx:papers:2503.23165.

    Full description at Econpapers || Download paper

  12. High-dimensional censored MIDAS logistic regression for corporate survival forecasting. (2025). van Keilegom, Ingrid ; Striaukas, Jonas ; Beyhum, Jad ; Miao, Wei.
    In: Papers.
    RePEc:arx:papers:2502.09740.

    Full description at Econpapers || Download paper

  13. The boosted Hodrick‐Prescott filter is more general than you might think. (2024). Phillips, Peter ; Mei, Ziwei ; Shi, Zhentao.
    In: Journal of Applied Econometrics.
    RePEc:wly:japmet:v:39:y:2024:i:7:p:1260-1281.

    Full description at Econpapers || Download paper

  14. Nowcasting Norwegian household consumption with debit card transaction data. (2024). Aastveit, Knut Are ; Fastb, Tuva Marie ; Granziera, Eleonora ; Paulsen, Kenneth Sterhagen ; Torstensen, Kjersti Nss.
    In: Journal of Applied Econometrics.
    RePEc:wly:japmet:v:39:y:2024:i:7:p:1220-1244.

    Full description at Econpapers || Download paper

  15. Nowcasting Euro area GDP with news sentiment: A tale of two crises. (2024). Saiz, Lorena ; Ashwin, Julian ; Kalamara, Eleni.
    In: Journal of Applied Econometrics.
    RePEc:wly:japmet:v:39:y:2024:i:5:p:887-905.

    Full description at Econpapers || Download paper

  16. Panel data nowcasting: The case of price–earnings ratios. (2024). Babii, Andrii ; Ball, Ryan T ; Striaukas, Jonas ; Ghysels, Eric.
    In: Journal of Applied Econometrics.
    RePEc:wly:japmet:v:39:y:2024:i:2:p:292-307.

    Full description at Econpapers || Download paper

  17. Influential assets in Large-Scale Vector AutoRegressive Models. (2024). Trimborn, Simon ; Zhang, Kexin.
    In: Tinbergen Institute Discussion Papers.
    RePEc:tin:wpaper:20240080.

    Full description at Econpapers || Download paper

  18. Benchmarking econometric and machine learning methodologies in nowcasting GDP. (2024). Hopp, Daniel.
    In: Empirical Economics.
    RePEc:spr:empeco:v:66:y:2024:i:5:d:10.1007_s00181-023-02515-6.

    Full description at Econpapers || Download paper

  19. Penalized Convex Estimation in Dynamic Location-Scale models. (2024). Chentoufi, Reda Alami.
    In: MPRA Paper.
    RePEc:pra:mprapa:123283.

    Full description at Econpapers || Download paper

  20. Forecasting Value-at-Risk Using Deep Neural Network Quantile Regression*. (2024). Raftapostolos, Aristeidis ; Kapetanios, George ; Chronopoulos, Ilias.
    In: Journal of Financial Econometrics.
    RePEc:oup:jfinec:v:22:y:2024:i:3:p:636-669..

    Full description at Econpapers || Download paper

  21. Reservoir computing for macroeconomic forecasting with mixed-frequency data. (2024). van Huellen, Sophie ; Dellaportas, Petros ; Hirt, Marcel ; Grigoryeva, Lyudmila ; Ortega, Juan-Pablo ; Ballarin, Giovanni.
    In: International Journal of Forecasting.
    RePEc:eee:intfor:v:40:y:2024:i:3:p:1206-1237.

    Full description at Econpapers || Download paper

  22. Forecasting oil futures returns with news. (2024). Wang, Yudong ; Pan, Zhiyuan ; Huang, Juan ; Zhong, Hao.
    In: Energy Economics.
    RePEc:eee:eneeco:v:134:y:2024:i:c:s0140988324003141.

    Full description at Econpapers || Download paper

  23. On LASSO for high dimensional predictive regression. (2024). Mei, Ziwei ; Shi, Zhentao.
    In: Journal of Econometrics.
    RePEc:eee:econom:v:242:y:2024:i:2:s0304407624001556.

    Full description at Econpapers || Download paper

  24. Nowcasting consumer price inflation using high-frequency scanner data: evidence from Germany. (2024). Wieland, Elisabeth ; Menz, Jan-Oliver ; Carstensen, Kai ; Schnorrenberger, Richard ; Beck, Gunter W.
    In: Working Paper Series.
    RePEc:ecb:ecbwps:20242930.

    Full description at Econpapers || Download paper

  25. CLARA and CARLSON: Combination of Ensemble and Neural Network Machine Learning Methods for GDP Forecasting. (2024). Bozhechkova, Alexandra ; Dzhunkeev, Urmat.
    In: Russian Journal of Money and Finance.
    RePEc:bkr:journl:v:83:y:2024:i:3:p:45-69.

    Full description at Econpapers || Download paper

  26. Nowcasting Italian GDP growth: a Factor MIDAS approach. (2024). Silvestrini, Andrea ; Prifti, Orest ; Ceci, Donato.
    In: Temi di discussione (Economic working papers).
    RePEc:bdi:wptemi:td_1446_24.

    Full description at Econpapers || Download paper

  27. Dual Interpretation of Machine Learning Forecasts. (2024). Goulet Coulombe, Philippe ; Goebel, Maximilian ; Klieber, Karin.
    In: Papers.
    RePEc:arx:papers:2412.13076.

    Full description at Econpapers || Download paper

  28. Sparse Interval-valued Time Series Modeling with Machine Learning. (2024). Wang, Shouyang ; Sun, Yuying ; Hong, Yongmiao ; Bao, Haowen.
    In: Papers.
    RePEc:arx:papers:2411.09452.

    Full description at Econpapers || Download paper

  29. Inference in High-Dimensional Linear Projections: Multi-Horizon Granger Causality and Network Connectedness. (2024). Wang, Endong ; Dettaa, Eugene.
    In: Papers.
    RePEc:arx:papers:2410.04330.

    Full description at Econpapers || Download paper

  30. Econometric Inference for High Dimensional Predictive Regressions. (2024). Lee, Ji Hyung ; Mei, Ziwei ; Shi, Zhentao ; Gao, Zhan.
    In: Papers.
    RePEc:arx:papers:2409.10030.

    Full description at Econpapers || Download paper

  31. Structural counterfactual analysis in macroeconomics: theory and inference. (2024). Wang, Endong.
    In: Papers.
    RePEc:arx:papers:2409.09577.

    Full description at Econpapers || Download paper

  32. Bayesian Bi-level Sparse Group Regressions for Macroeconomic Density Forecasting. (2024). Mogliani, Matteo ; Simoni, Anna.
    In: Papers.
    RePEc:arx:papers:2404.02671.

    Full description at Econpapers || Download paper

  33. Data-Driven Tuning Parameter Selection for High-Dimensional Vector Autoregressions. (2024). Kock, Anders ; Pedersen, Rasmus Sondergaard ; Sorensen, Jesper Riis-Vestergaard.
    In: Papers.
    RePEc:arx:papers:2403.06657.

    Full description at Econpapers || Download paper

  34. Expected Shortfall LASSO. (2024). Barendse, Sander.
    In: Papers.
    RePEc:arx:papers:2307.01033.

    Full description at Econpapers || Download paper

  35. Hierarchical Regularizers for Reverse Unrestricted Mixed Data Sampling Regressions. (2024). Wilms, Ines ; Hecq, Alain ; Ternes, Marie.
    In: Papers.
    RePEc:arx:papers:2301.10592.

    Full description at Econpapers || Download paper

  36. Reservoir Computing for Macroeconomic Forecasting with Mixed Frequency Data. (2024). van Huellen, Sophie ; Dellaportas, Petros ; Hirt, Marcel ; Grigoryeva, Lyudmila ; Ortega, Juan-Pablo ; Ballarin, Giovanni.
    In: Papers.
    RePEc:arx:papers:2211.00363.

    Full description at Econpapers || Download paper

  37. Nowcasting consumer price inflation using high-frequency scanner data: Evidence from Germany. (2023). Wieland, Elisabeth ; Schnorrenberger, Richard ; Menz, Jan-Oliver ; Carstensen, Kai ; Beck, Guenter.
    In: Discussion Papers.
    RePEc:zbw:bubdps:282982.

    Full description at Econpapers || Download paper

  38. Testing big data in a big crisis: Nowcasting under Covid-19. (2023). Tiozzo Pezzoli, Luca ; Ratto, Marco ; Pericoli, Filippo Maria ; onorante, luca ; Barbaglia, Luca ; Frattarolo, Lorenzo.
    In: International Journal of Forecasting.
    RePEc:eee:intfor:v:39:y:2023:i:4:p:1548-1563.

    Full description at Econpapers || Download paper

  39. Machine learning panel data regressions with heavy-tailed dependent data: Theory and application. (2023). Babii, Andrii ; Ball, Ryan T ; Striaukas, Jonas ; Ghysels, Eric.
    In: Journal of Econometrics.
    RePEc:eee:econom:v:237:y:2023:i:2:s0304407622001282.

    Full description at Econpapers || Download paper

  40. Flexible Bayesian MIDAS: time‑variation, group‑shrinkage and sparsity. (2023). Potjagailo, Galina ; Kohns, David.
    In: Bank of England working papers.
    RePEc:boe:boeewp:1025.

    Full description at Econpapers || Download paper

  41. High Dimensional Time Series Regression Models: Applications to Statistical Learning Methods. (2023). Katsouris, Christis.
    In: Papers.
    RePEc:arx:papers:2308.16192.

    Full description at Econpapers || Download paper

Coauthors

Authors registered in RePEc who have wrote about the same topic

Report date: 2025-09-07 19:18:29 || Missing content? Let us know

CitEc is a RePEc service, providing citation data for Economics since 2001. Last updated August, 3 2024. Contact: Jose Manuel Barrueco.