Prof. Dr. Matei Demetrescu

Former Bonn Junior Fellow
Current position: Professor (W3), University of Kiel

E-mail: mdeme(at)
Institute: Department of Economics
Research Area: Research Area H
Date of birth: 16.Dec 1976
Mathscinet-Number: 776612

Academic Career


Diploma (Engineering and Business Administration), Politehnica University, Bucharest, Romania

2001 - 2006

Assistant, TU Darmstadt and University of Frankfurt


Dr. rer. pol., University of Frankfurt

2007 - 2008

Max Weber Postdoc Fellow, European University Institute, Florence, Italy

2008 - 2010

Junior Professor (W1), University of Frankfurt


PhD (Industrial Engineering), Politehnica University, Bucharest, Romania

2010 - 2014

Professor (W2, Bonn Junior Fellow), University of Bonn

Since 2014

Professor (W3), University of Kiel

Research Profile

My research focusses on two related aspects of time series econometrics: the analysis of persistent (fractionally integrated) time series, and exploiting the persistence to forecast time series.

Not knowing the shape of the deterministic component when testing for (co)integration poses problems; in [1], the evidence from two cointegration tests, one accounting for a deterministic linear trend in the cointegrating relations, and one without trend, is combined to obtain robust inference about the cointegration rank, which is shown to be a better procedure that pretesting or always accounting for the possible trend. The analysis of fractionally cointegrated series often presupposes knowledge of the exact degree of fractional integration. A test for the fractional integration parameter which is entirely regression based and allows for conditional and unconditional heteroskedasticity is proposed in [2].

When it comes to forecasts based on stochastic time series models, modeling the dynamics of the series is only one aspect; the other important issue is to provide the optimal forecast. Given the inherent uncertainty of forecasts, optimality is delivered from a decision-theoretic point of view by the point forecast minimizing the expected cost, or loss, caused by forecast errors. A numerical method tailored for minimization of sample counterparts of such loss functionals is put forward in [3], a method that can also be used for estimation under the relevant loss function. Moving on to forecast intervals, often used as a measure of forecast precision, it is argued in [4] that the usual, \mu \pm 2\sigma, are not compatible with point forecasts that are optimal under loss functions different from the squared-error loss (they may not even contain the point forecast); a coherent optimality principle for forecast intervals is proposed. The issue of optimality of multivariate forecasts and of multivariate loss functions is discussed in [5].

Research Projects and Activities

“Approximation and aggregation in modeling and forecasting persistent time series”
Project leader, jointly with Uwe Hassler, Goethe University Frankfurt, 2011 - 2014

Contribution to Research Areas

Research Area H
Heteroskedasticity or time-varying variance leads to severe distortions of the asymptotic distribution of test statistics if the statistics involve highly persistent series. A first goal of mine within research Area H is thus to obtain robustness to heteroskedasticity of test statistics whose distribution can be written as functionals of time-transformed Wiener processes.

Another continued research direction fitting the program of Area H is inference with highly persistent series in heterogeneous panels, e.g. the identification of structural breaks in the presence of long memory.

Selected Publications

[1] Matei Demetrescu, Helmut Lütkepohl, Pentti Saikkonen
Testing for the cointegrating rank of a vector autoregressive process with uncertain deterministic trend term
Econom. J. , 12: (3): 414--435
DOI: 10.1111/j.1368-423X.2009.00297.x
[2] Matei Demetrescu, Vladimir Kuzin, Uwe Hassler
Long memory testing in the time domain
Econometric Theory , 24: (1): 176--215
DOI: 10.1017/S0266466608080092
[3] Matei Demetrescu
An extension of the Gauss-Newton algorithm for estimation under asymmetric loss
Comput. Statist. Data Anal. , 50: (2): 379--401
DOI: 10.1016/j.csda.2004.08.007
[4] Matei Demetrescu
Optimal forecast intervals under asymmetric loss
J. Forecast. , 26: (4): 227--238
DOI: 10.1002/for.1019
[7] Matei Demetrescu, Uwe Hassler
Effect of neglected deterministic seasonality on unit root tests
Statist. Papers , 48: (3): 385--402
DOI: 10.1007/s00362-006-0343-6

Publication List

Supervised Theses

  • Master theses: 2
  • Diplom theses: 1
Download Profile