Wirtschaftswissenschaftliche Fakultät
http://edoc.hu-berlin.de/18452/85
2022-12-05T17:54:52ZIs Scientific Performance a Function of Funds?
http://edoc.hu-berlin.de/18452/19461
Is Scientific Performance a Function of Funds?
Zharova, Alona; Härdle, Wolfgang Karl; Lessmann, Stefan
The management of universities demands data on teaching and research performance. While teaching parameters can be measured via student performance and teacher evaluation programs, the connection of research outputs and their grant antecedents is much harder to check, test and understand. This paper elicits the interdependence structure between third-party expenses (TPE), publications, citations and academic age. To describe the relationship, we analyze individual level data from a sample of professorships from a leading research university and a Scopus database for the period 2001 to 2015. Using estimates from a PVARX model, impulse response functions and a forecast error variance decomposition, we show that analyzing on the high aggregation level of universities does not reflect the behavior of its faculties. We explain the differences in relationship structure between indicators for social sciences and humanities, life sciences and mathematical and natural sciences. For instance, for mathematics and some fields of social sciences and humanities the relationship between the TPE and the number of publications is insignificant, however, the influence of the TPE on the number of citation is significant and positive that indicates the difference between quality and quantity of research outputs. The paper also proposes a visualization of the cooperation between faculties and research interdisciplinarity via the co-authorship structure among publications. We discuss the implications for policy and decision making and suggest recommendations for research management of universities.
2017-11-06T00:00:00ZDynamic semi-parametric factor model for functional expectiles
http://edoc.hu-berlin.de/18452/19460
Dynamic semi-parametric factor model for functional expectiles
Burdejová, Petra; Härdle, Wolfgang Karl
High-frequency data can provide us with a quantity of informa- tion for forecasting, help to calculate and prevent the future risk based on extremes. This tail behaviour is very often driven by ex- ogenous components and may be modelled conditional on other vari- ables. However, many of these phenomena are observed over time, exhibiting non-trivial dynamics and dependencies. We propose a func- tional dynamic factor model to study the dynamics of expectile curves. The complexity of the model and the number of dependent variables are reduced by lasso penalization. The functional factors serve as a low-dimensional representation of the conditional tail event, while the time-variation is captured by factor loadings. We illustrate the model with an application to climatology, where daily data over years on temperature, rainfalls or strength of wind are available.
2017-11-06T00:00:00ZDynamic Semiparametric Factor Model with a Common Break
http://edoc.hu-berlin.de/18452/19459
Dynamic Semiparametric Factor Model with a Common Break
Chen, Likai; Wang, Weining; Wu, Wei Biao
For change-point analysis of high dimensional time series, we consider a semiparametric model with dynamic structural break factors. The observations are described by a few low dimensional factors with time-invariate loading functions of covariates. The unknown structural break in time models the regime switching e ects introduced by exogenous shocks. In particular, the factors are assumed to be nonstationary and follow a Vector Autoregression (VAR) process with a structural break. In addition, to account for the known spatial discrepancies, we introduce discrete loading functions. We study the theoretical properties of the estimates of the loading functions and the factors. Moreover, we provide both the consistency and the asymptotic convergence results for making inference on the common breakpoint in time. The estimation precision is evaluated via a simulation study. Finally we present two empirical illustrations on modeling the dynamics of the minimum wage policy in China and analyzing a limit order book dataset.
2017-11-06T00:00:00ZRealized volatility of CO2 futures
http://edoc.hu-berlin.de/18452/19458
Realized volatility of CO2 futures
Benschop, Thijs; López-Cabrera, Brenda
The EU Emission Trading System (EU ETS) was created to reduce the CO2 and other greenhouse gas emissions at the lowest economic cost. In reality market participants are faced with considerable uncertainty due to price changes and require price and volatility estimates and forecasts for appropriate risk management, asset allocation and volatility trading. Although the simplest approach to estimate volatility is to use the historical standard deviation, realized volatility is a more accurate measure for volatility, since it is based on intraday data. Besides the stylized facts commonly observed in financial time series, we observe long-memory properties in the realized volatility series, which motivates the use of Heterogeneous Autoregressive (HAR) class models. Therefore, we propose to model and forecast the realized volatility of the EU ETS futures with HAR class models. The HAR models outperform benchmark models such as the standard long-memory ARFIMA model in terms of model fit, in-sample and out-of-sample forecasting. The analysis is based on intraday data (May 2007-April 2012) for futures on CO2 certificates for the second EU-ETS trading period (expiry December 2008-2012). The estimation results of the models allow to explain the volatility drivers in the market and volatility structure, according to the Heterogeneous Market Hypothesis as well as the observed asymmetries. We see that both speculators with short investment horizons as well as traders taking long-term hedging positions are active in the market. In a simulation study we test the suitability of the HAR model for option pricing and conclude that the HAR model is capable of mimicking the long-term volatility structure in the futures market and can be used for short-term and long-term option pricing.
2017-11-06T00:00:00Z