# Morten Ørregaard Nielsen: Research

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My main research area is time series econometrics with focus on integration, cointegration, long memory, and fractional processes. I have also worked on applications, e.g. to electricity price dynamics, as well as financial econometrics and empirical finance (realized/implied volatility, high-frequency data, efficient markets hypothesis). Recently, I have also worked on cluster-robust inference and bootstrap methods for clustered data.

### Citations

### Research Interests

- Estimation and inference in fractional integration and cointegration models.
- Semiparametric analysis of long memory processes.
- Financial econometrics and high frequency data.
- Unit root and cointegration testing.
- Cluster-robust inference and bootstrap methods for clustered data.

### Current Working Papers

- Adaptive estimation in heteroskedastic fractional time series models (with G. Cavaliere and A.M.R. Taylor).

QED working paper 1390. Latest version 2018/12.

(Note: Data files and Ox programs that reproduce Tables 1-4 are available here.) - Bootstrap and asymptotic inference with multiway clustering (with J.G. MacKinnon and M.D. Webb.).

QED working paper 1386. Latest version 2017/08.

(Note: A Stata .do file to replicate Table 2 is available here. An R program and a Stata .ado file will be available soon.) - Asymptotic theory and wild bootstrap inference with clustered errors (with A.A. Djogbenou and J.G. MacKinnon).

QED working paper 1399. Latest version 2018/12.

(Note: Previously circulated under a slightly different title as QED working paper 1383.) - Truncated sum of squares estimation of fractional time series models with deterministic trends (with J. Hualde).

QED working paper 1376. Latest version 2018/09. - A Matlab program and user’s guide for the fractionally cointegrated VAR model (with M.K. Popiel).

QED working paper 1330. Latest version 2018/05.

(Note: The associated Matlab program can be downloaded here.) - The fractionally cointegrated VAR model with deterministic terms (with S. Johansen).

Work in progress. - A cointegrated model allowing for different fractional orders (with S. Johansen).

Work in progress.

### Articles in Journals

- Roodman, D., J.G. MacKinnon, M.Ø. Nielsen, & M.D. Webb (2019?) Fast and wild: bootstrap inference in Stata using boottest.

Forthcoming in*Stata Journal*.

(Note: A working paper version can be downloaded here and the latest version of boottest can be downloaded here.) - Johansen, S. & M.Ø. Nielsen (2019?) Nonstationary cointegration in the fractionally cointegrated VAR model.

Forthcoming in*Journal of Time Series Analysis*.

(Note: A working paper version can be downloaded here.) - Johansen, S. & M.Ø. Nielsen (2018) Testing the CVAR in the fractional CVAR model.
*Journal of Time Series Analysis*39, 836–849. - Johansen, S. & M.Ø. Nielsen (2018) The cointegrated vector autoregressive model with general deterministic terms.
*Journal of Econometrics*202, 214–229. - Dolatabadi, S., P.K. Narayan, M.Ø. Nielsen, & K. Xu (2018) Economic significance of commodity return forecasts from the fractionally cointegrated VAR model.
*Journal of Futures Markets*38, 219–242.

(Note: A working paper version that includes the weekly and monthly results corresponding to Table 4 as well as the supplementary results mentioned in footnotes 11 and 12 can be downloaded here.) - Nielsen, M.Ø. & S. Shibaev (2018) Forecasting daily political opinion polls using the fractionally cointegrated vector auto-regressive model.
*Journal of the Royal Statistical Society Series A*181, 3–33.

(Note: Computer programs and data for replication of the results can be downloaded here.) - Cavaliere, G., M.Ø. Nielsen, & A.M.R. Taylor (2017) Quasi-maximum likelihood estimation and bootstrap inference in fractional time series models with heteroskedasticity of unknown form.
*Journal of Econometrics*198, 165–188.

(Note: A working paper version that includes the supplementary appendix can be downloaded here.) - Johansen, S. & M.Ø. Nielsen (2016) The role of initial values in conditional sum-of-squares estimation of nonstationary fractional time series models.
*Econometric Theory*32, 1095–1139. - Dolatabadi, S., M.Ø. Nielsen, & K. Xu (2016) A fractionally cointegrated VAR model with deterministic trends and application to commodity futures markets.
*Journal of Empirical Finance*38B, 623–639. - Christensen, B.J., M.Ø. Nielsen, & J. Zhu (2015) The impact of financial crises on the risk-return tradeoff and the leverage effect.
*Economic Modelling*49, 407–418. - Cavaliere, G., M.Ø. Nielsen, & A.M.R. Taylor (2015) Bootstrap score tests for fractional integration in heteroskedastic ARFIMA models, with an application to price dynamics in commodity spot and futures markets.
*Journal of Econometrics*187, 557–579.

(Note: The working paper version cited in the paper can be downloaded here.) - Dolatabadi, S., M.Ø. Nielsen, & K. Xu (2015) A fractionally cointegrated VAR analysis of price discovery in commodity futures markets.
*Journal of Futures Markets*35, 339–356. - Nielsen, M.Ø. (2015) Asymptotics for the conditional-sum-of-squares estimator in multivariate fractional time-series models.
*Journal of Time Series Analysis*36, 154–188. - Boswijk, H.P., M. Jansson, & M.Ø. Nielsen (2015) Improved likelihood ratio tests for cointegration rank in the VAR model.
*Journal of Econometrics*184, 97–110. - Jones, M.E.C., M.Ø. Nielsen, & M.K. Popiel (2014) A fractionally cointegrated VAR analysis of economic voting and political support.
*Canadian Journal of Economics*47, 1078–1130.

(Note: Innis Lecture at 2014 Canadian Economics Association conference in Vancouver.) - Jensen, A.N. & M.Ø. Nielsen (2014) A fast fractional difference algorithm.
*Journal of Time Series Analysis*35, 428–436.

(Note: The associated fast fractional difference codes for Matlab, Ox, and R can be downloaded here.) - MacKinnon, J.G. & M.Ø. Nielsen (2014) Numerical distribution functions of fractional unit root and cointegration tests.
*Journal of Applied Econometrics*29, 161–171.

(Note: The computer programs to calculate critical values and*P*values can be downloaded here.) - Johansen, S. & M.Ø. Nielsen (2012) Likelihood inference for a fractionally cointegrated vector autoregressive model.
*Econometrica*80, 2667–2732.

(Note: A Matlab software package for estimation and testing in the fractionally cointegrated VAR model can be downloaded here and a computer program to calculate critical values and*P*values can be downloaded here.) - Jansson, M. & M.Ø. Nielsen (2012) Nearly efficient likelihood ratio tests of the unit root hypothesis.
*Econometrica*80, 2321–2332.

(Note: A working paper version which includes the supplemental material cited in the article can be downloaded here and a Matlab program can be downloaded here.) - Johansen, S. & M.Ø. Nielsen (2012) A necessary moment condition for the fractional functional central limit theorem.
*Econometric Theory*28, 671–679. - Frederiksen, P., F.S. Nielsen, & M.Ø. Nielsen (2012) Local polynomial Whittle estimation of perturbed fractional processes.
*Journal of Econometrics*167, 426–447. - Nielsen, M.Ø. & P. Frederiksen (2011) Fully modified narrow-band least squares estimation of weak fractional cointegration.
*Econometrics Journal*14, 77–120.

(Note: A zip file containing Ox programs to calculate the FMNBLS and other narrow-band estimators, and the data set to replicate the empirical IV-RV application, can be downloaded here. The programs are written in Ox.

A previous version of this paper was circulated as “Fully modified narrow-band least squares estimation of stationary fractional cointegration” and can be downloaded here.) - Jansson, M. & M.Ø. Nielsen (2011) Nearly efficient likelihood ratio tests for seasonal unit roots.
*Journal of Time Series Econometrics*3, issue 1, article 5. - Busch, T., B.J. Christensen, & M.Ø. Nielsen (2011) The role of implied volatility in forecasting future realized volatility and jumps in foreign exchange, stock, and bond markets.
*Journal of Econometrics*160, 48–57.

(Note: The three working papers cited in the article can be downloaded here:

The implied-realized volatility relation with jumps in underlying asset prices,

Forecasting exchange rate volatility in the presence of jumps, and

The information content of Treasury bond options concerning future volatility and price jumps.) - Haldrup, N., F.S. Nielsen, & M.Ø. Nielsen (2010) A vector autoregressive model for electricity prices subject to long memory and regime switching.
*Energy Economics*32, 1044–1058. - Johansen, S. & M.Ø. Nielsen (2010) Likelihood inference for a nonstationary fractional autoregressive model.
*Journal of Econometrics*158, 51–66. - Christensen, B.J., M.Ø. Nielsen, & J. Zhu (2010) Long memory in stock market volatility and the volatility-in-mean effect: the FIEGARCH-M model.
*Journal of Empirical Finance*17, 460–470. - Nielsen, M.Ø. (2010) Nonparametric cointegration analysis of fractional systems with unknown integration orders.
*Journal of Econometrics*155, 170–187.

(Note: A zip file containing the data set and a computer program to replicate the empirical application in the paper can be downloaded here. The program is written in Ox.) - Andersen, T.G., T. Bollerslev, P. Frederiksen, & M.Ø. Nielsen (2010) Continuous-time models, realized volatilities, and testable distributional implications for daily stock returns.
*Journal of Applied Econometrics*25, 233–261.

(Note: A working paper version which includes the separate appendix cited in the article can be downloaded here; this article was previously circulated as “Explorations into the distributional characteristics of common stock returns”.) - Nielsen, M.Ø. (2009) A powerful test of the autoregressive unit root hypothesis based on a tuning parameter free statistic.
*Econometric Theory*25, 1515–1544.

(Note: The working paper version “A powerful tuning parameter free test of the autoregressive unit root hypothesis” cited in the article can be downloaded here.) - Frederiksen, P. & M.Ø. Nielsen (2008) Bias-reduced estimation of long-memory stochastic volatility.
*Journal of Financial Econometrics*6, 496–512. - Nielsen, M.Ø. & P.H. Frederiksen (2008) Finite sample accuracy and choice of sampling frequency in integrated volatility estimation.
*Journal of Empirical Finance*15, 265–286.

(Note: This article was previously circulated as “Finite sample accuracy of integrated volatility estimators”.) - Zussman, A., N. Zussman, & M.Ø. Nielsen (2008) Asset market perspectives on the Israeli-Palestinian conflict.
*Economica*75, 84–115. - Nielsen, M.Ø. & K. Shimotsu (2007) Determining the cointegrating rank in nonstationary fractional systems by the exact local Whittle approach.
*Journal of Econometrics*141, 574–596.

(Note: A zip file containing Matlab programs to implement the ELW rank determination and the data set to replicate the empirical application in the paper can be downloaded here.) - Christensen, B.J. & M.Ø. Nielsen (2007) The effect of long memory in volatility on stock market fluctuations.
*Review of Economics and Statistics*89, 684–700. - Nielsen, M.Ø. (2007) Local Whittle analysis of stationary fractional cointegration and the implied-realized volatility relation.
*Journal of Business and Economic Statistics*25, 427–446. - Haldrup, N. & M.Ø. Nielsen (2007) Estimation of fractional integration in the presence of data noise.
*Computational Statistics & Data Analysis*51, 3100–3114. - Haldrup, N. & M.Ø. Nielsen (2006) Directional congestion and regime switching in a long memory model for electricity prices.
*Studies in Nonlinear Dynamics & Econometrics*10, issue 3, article 1. - Haldrup, N. & M.Ø. Nielsen (2006) A regime switching long memory model for electricity prices.
*Journal of Econometrics*135, 349–376. - Christensen, B.J. & M.Ø. Nielsen (2006) Asymptotic normality of narrow-band least squares in the stationary fractional cointegration model and volatility forecasting.
*Journal of Econometrics*133, 343–371.

(Note: A zip file containing Ox programs to calculate the NBLS and other narrow-band estimators can be downloaded here. The programs are written in Ox.

This article was previously circulated as “Semiparametric analysis of stationary fractional cointegration and the implied realized volatility relation”.) - Nielsen, M.Ø. & P.H. Frederiksen (2005) Finite sample comparison of parametric, semiparametric, and wavelet estimators of fractional integration.
*Econometric Reviews*24, 405–443.

(Note: A working paper version which includes the separate appendix cited in the article can be downloaded here.) - Nielsen, M.Ø. (2005) Multivariate Lagrange multiplier tests for fractional integration.
*Journal of Financial Econometrics*3, 372–398. - Nielsen, M.Ø. (2005) Semiparametric estimation in time-series regression with long-range dependence.
*Journal of Time Series Analysis*26, 279–304. - Nielsen, M.Ø. (2005) Noncontemporaneous cointegration and the importance of timing.
*Economics Letters*86, 113–119. - Nielsen, M.Ø. (2004) Optimal residual-based tests for fractional cointegration and exchange rate dynamics.
*Journal of Business and Economic Statistics*22, 331–345. - Brendstrup, B., S. Hylleberg, M.Ø. Nielsen, L. Skipper, & L. Stentoft (2004) Seasonality in economic models.
*Macroeconomic Dynamics*8, 362–394. - Nielsen, M.Ø. (2004) Efficient inference in multivariate fractionally integrated time series models.
*Econometrics Journal*7, 63–97. - Nielsen, M.Ø. (2004) Spectral analysis of fractionally cointegrated systems.
*Economics Letters*83, 225–231. - Nielsen, M.Ø. (2004) Local empirical spectral measure of multivariate processes with long range dependence.
*Stochastic Processes and their Applications*109, 145–166. - Nielsen, M.Ø. (2004) Efficient likelihood inference in nonstationary univariate models.
*Econometric Theory*20, 116–146.

### Editorials, comments, etc.

- Narayan, P.K. & M.Ø. Nielsen (2015) Guest editors’ introduction: Special issue of Journal of Banking and Finance on recent developments in financial econometrics and applications.
*Journal of Banking and Finance*61, S99–S100. - Andersen, T.G., T. Bollerslev, P.H. Frederiksen, & M.Ø. Nielsen (2006) Comment on P. R. Hansen and A. Lunde: “Realized variance and market microstructure noise”.
*Journal of Business and Economic Statistics*24, 173–179.