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  1. Book ; Online: On heterogeneous latent class models with applications to the analysis of rating scores/ Aurélie Bertrand; Christian M. Hafner

    Bertrand, Aurélie / Hafner, Christian M

    (SFB 649 discussion paper ; 2011-062)

    2011  

    Abstract: Discovering the preferences and the behaviour of consumers is a key challenge in marketing. Information about such topics can be gathered through surveys in which the respondents must assign a score to a number of items. In this article we suggest a ... ...

    Series title SFB 649 discussion paper ; 2011-062
    Abstract Discovering the preferences and the behaviour of consumers is a key challenge in marketing. Information about such topics can be gathered through surveys in which the respondents must assign a score to a number of items. In this article we suggest a strategy to analyze such data and achieve this objective: it consists in identifying groups of consumers whose response patterns are similar and characterizing them in terms of preferences and covariates. We use latent class models allowing for heterogeneity of both latent class and within-class probabilities across individuals. We illustrate the proposed methodology using data about the preferences of Belgian households for supermarkets. -- Latent class analysis

    rating scores

    heterogeneity

    EM algorithm

    marketing
    Keywords Belgien ; Konsumentenverhalten ; Befragung ; Präferenztheorie ; Multivariate Analyse ; Clusteranalyse ; Theorie ; Einkaufsverhalten ; Lebensmitteleinzelhandel ; Schätzung
    Language English
    Size Online-Ressource (PDF-Datei: 29 S., 511 KB)
    Publisher SFB 649, Economic Risk
    Publishing place Berlin
    Document type Book ; Online
    Note IMD-Felder maschinell generiert
    Database ECONomics Information System

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  2. Article ; Online: The Spread of the Covid-19 Pandemic in Time and Space.

    Hafner, Christian M

    International journal of environmental research and public health

    2020  Volume 17, Issue 11

    Abstract: As the COVID-19 pandemic has had a profound impact on public health and global economies in 2020; it is crucial to understand how it developed and spread in time and space. This paper contributes to the growing literature by considering the dynamics of ... ...

    Abstract As the COVID-19 pandemic has had a profound impact on public health and global economies in 2020; it is crucial to understand how it developed and spread in time and space. This paper contributes to the growing literature by considering the dynamics of country-wise growth rates of infection numbers. Low-order serial correlation of growth rates is predominantly negative with cycles of two to four days for most countries. The results of fitted spatial autoregressive models suggest that there is high degree of spillover between countries. Forecast variances of many countries, in particular those with a high absolute number of infections, can to a large extent be explained by structural innovations of other countries. A better understanding of the serial and spatial dynamics of the spread of the pandemic may contribute to an improved containment and risk management.
    MeSH term(s) Betacoronavirus ; COVID-19 ; Coronavirus Infections/epidemiology ; Global Health ; Humans ; Pandemics ; Pneumonia, Viral/epidemiology ; Public Health ; SARS-CoV-2 ; Spatio-Temporal Analysis
    Keywords covid19
    Language English
    Publishing date 2020-05-28
    Publishing country Switzerland
    Document type Journal Article
    ISSN 1660-4601
    ISSN (online) 1660-4601
    DOI 10.3390/ijerph17113827
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  3. Article: The Spread of the Covid-19 Pandemic in Time and Space

    Hafner, Christian M

    Int. j. environ. res. public health (Online)

    Abstract: As the COVID-19 pandemic has had a profound impact on public health and global economies in 2020; it is crucial to understand how it developed and spread in time and space. This paper contributes to the growing literature by considering the dynamics of ... ...

    Abstract As the COVID-19 pandemic has had a profound impact on public health and global economies in 2020; it is crucial to understand how it developed and spread in time and space. This paper contributes to the growing literature by considering the dynamics of country-wise growth rates of infection numbers. Low-order serial correlation of growth rates is predominantly negative with cycles of two to four days for most countries. The results of fitted spatial autoregressive models suggest that there is high degree of spillover between countries. Forecast variances of many countries, in particular those with a high absolute number of infections, can to a large extent be explained by structural innovations of other countries. A better understanding of the serial and spatial dynamics of the spread of the pandemic may contribute to an improved containment and risk management.
    Keywords covid19
    Publisher WHO
    Document type Article
    Note WHO #Covidence: #401771
    Database COVID19

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  4. Article ; Online: The Spread of the Covid-19 Pandemic in Time and Space

    Christian M. Hafner

    International Journal of Environmental Research and Public Health, Vol 17, Iss 3827, p

    2020  Volume 3827

    Abstract: As the COVID-19 pandemic has had a profound impact on public health and global economies in 2020; it is crucial to understand how it developed and spread in time and space. This paper contributes to the growing literature by considering the dynamics of ... ...

    Abstract As the COVID-19 pandemic has had a profound impact on public health and global economies in 2020; it is crucial to understand how it developed and spread in time and space. This paper contributes to the growing literature by considering the dynamics of country-wise growth rates of infection numbers. Low-order serial correlation of growth rates is predominantly negative with cycles of two to four days for most countries. The results of fitted spatial autoregressive models suggest that there is high degree of spillover between countries. Forecast variances of many countries, in particular those with a high absolute number of infections, can to a large extent be explained by structural innovations of other countries. A better understanding of the serial and spatial dynamics of the spread of the pandemic may contribute to an improved containment and risk management.
    Keywords corona virus ; spatial autoregressions ; stochastic cycles ; contagion ; LASSO ; networks ; Medicine ; R
    Subject code 339
    Language English
    Publishing date 2020-05-01T00:00:00Z
    Publisher MDPI AG
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

    Full text online

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  5. Article ; Online: A dynamic conditional score model for the log correlation matrix

    Hafner, Christian M. / Wang, Linqi

    Journal of Econometrics. 2021 Oct. 02, p.105176-

    2021  , Page(s) 105176–

    Abstract: This paper proposes a new model for the dynamics of correlation matrices, where the dynamics are driven by the likelihood score with respect to the matrix logarithm of the correlation matrix. In analogy to the exponential GARCH model for volatility, this ...

    Abstract This paper proposes a new model for the dynamics of correlation matrices, where the dynamics are driven by the likelihood score with respect to the matrix logarithm of the correlation matrix. In analogy to the exponential GARCH model for volatility, this transformation ensures that the correlation matrices remain positive definite, even in high dimensions. For the conditional distribution of returns, we assume a student-t copula to explain the dependence structure and univariate student-t for the marginals with potentially different degrees of freedom. The separation into volatility and correlation parts allows for a two-step estimation, which facilitates estimation in high dimensions. We derive estimation theory for one-step and two-step estimation. In an application to a set of six asset indices including financial and alternative assets we show that the model performs well in terms of diagnostics, specification tests, and out-of-sample forecasting.
    Keywords assets ; diagnostic techniques ; econometrics ; models ; C14 ; C43 ; Z11 ; Score ; Correlation ; Matrix logarithm ; Identification
    Language English
    Dates of publication 2021-1002
    Publishing place Elsevier B.V.
    Document type Article ; Online
    Note Pre-press version
    ZDB-ID 1460617-3
    ISSN 0304-4076
    ISSN 0304-4076
    DOI 10.1016/j.jeconom.2021.09.004
    Database NAL-Catalogue (AGRICOLA)

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  6. Article ; Online: Panel Stochastic Frontier Analysis with Dependent Error Terms

    Rachida El Mehdi / Christian M. Hafner

    International Econometric Review, Vol 13, Iss 2, Pp 24-

    2021  Volume 40

    Abstract: In presence of panel data, technical efficiency is used to compare the performances of Decision-Making Units (DMUs). The novelty of this paper is the consideration of the dependence between the two error terms in the case of panel data and the ... ...

    Abstract In presence of panel data, technical efficiency is used to compare the performances of Decision-Making Units (DMUs). The novelty of this paper is the consideration of the dependence between the two error terms in the case of panel data and the introduction of time effect models in the Stochastic Frontier Analysis (SFA). Hence, our SFA model considers the balanced panel case, several models describing the evolution of the inefficiency over time and the dependence between the two error terms. The inefficiency and noise terms being dependent, a copula function which reflects the dependence between them is included in their joint density. The model is estimated by maximum likelihood and the Akaike Information Criterion (AIC) is used for model selection. Moreover, a likelihood ratio test is performed for the nested models. A bootstrap algorithm is proposed for statistical inference on the Technical Efficiency (TE) measures. Results for Moroccan policy of the production and sales of drinking water from 2001 to 2007 identify the most and least efficient provinces, and a generally positive trend of estimated TE measures.
    Keywords bootstrap ; copulas ; efficiency ; panel data ; stochastic frontier analysis ; Economic theory. Demography ; HB1-3840 ; Economics as a science ; HB71-74
    Subject code 519
    Language English
    Publishing date 2021-12-01T00:00:00Z
    Publisher Econometric Research Association
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  7. Article ; Online: Looking Backward and Looking Forward

    Zhengyuan Gao / Christian M. Hafner

    Econometrics, Vol 7, Iss 2, p

    2019  Volume 27

    Abstract: Filtering has had a profound impact as a device of perceiving information and deriving agent expectations in dynamic economic models. For an abstract economic system, this paper shows that the foundation of applying the filtering method corresponds to ... ...

    Abstract Filtering has had a profound impact as a device of perceiving information and deriving agent expectations in dynamic economic models. For an abstract economic system, this paper shows that the foundation of applying the filtering method corresponds to the existence of a conditional expectation as an equilibrium process. Agent-based rational behavior of looking backward and looking forward is generalized to a conditional expectation process where the economic system is approximated by a class of models, which can be represented and estimated without information loss. The proposed framework elucidates the range of applications of a general filtering device and is not limited to a particular model class such as rational expectations.
    Keywords perception ; filter ; rational expectations ; estimation ; Economics as a science ; HB71-74
    Language English
    Publishing date 2019-06-01T00:00:00Z
    Publisher MDPI AG
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

    Full text online

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  8. Article: Identification of structural multivariate GARCH models

    Hafner, Christian M / Herwartz, Helmut / Maxand, Simone

    Journal of econometrics. 2020 July 01,

    2020  

    Abstract: The class of multivariate GARCH models is widely used to quantify and monitor volatility and correlation dynamics of financial time series. While many specifications have been proposed in the literature, these models are typically silent about the system ...

    Abstract The class of multivariate GARCH models is widely used to quantify and monitor volatility and correlation dynamics of financial time series. While many specifications have been proposed in the literature, these models are typically silent about the system inherent transmission of implied orthogonalized shocks to vector returns. In a framework of non-Gaussian independent structural shocks, this paper proposes a loss statistic, based on higher order co-moments, to discriminate in a data-driven way between alternative structural assumptions about the transmission scheme, and hence identify the structural model. Consistency of identification is shown theoretically and via a simulation study. In its structural form, a four dimensional system comprising US and Latin American stock market returns points to a substantial volatility transmission from the US to the Latin American markets. The identified structural model improves the estimation of classical measures of portfolio risk, as well as corresponding variations.
    Keywords econometric models ; economic analysis ; economic theory ; risk ; stock exchange ; time series analysis ; Latin America ; United States
    Language English
    Dates of publication 2020-0701
    Publishing place Elsevier B.V.
    Document type Article
    Note Pre-press version
    ZDB-ID 1460617-3
    ISSN 0304-4076
    ISSN 0304-4076
    DOI 10.1016/j.jeconom.2020.07.019
    Database NAL-Catalogue (AGRICOLA)

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  9. Article: Estimation of a multiplicative correlation structure in the large dimensional case

    Hafner, Christian M / Linton, Oliver B / Tang, Haihan

    Journal of econometrics. 2019,

    2019  

    Abstract: We propose a Kronecker product model for correlation or covariance matrices in the large dimensional case. The number of parameters of the model increases logarithmically with the dimension of the matrix. We propose a minimum distance (MD) estimator ... ...

    Abstract We propose a Kronecker product model for correlation or covariance matrices in the large dimensional case. The number of parameters of the model increases logarithmically with the dimension of the matrix. We propose a minimum distance (MD) estimator based on a log-linear property of the model, as well as a one-step estimator, which is a one-step approximation to the quasi-maximum likelihood estimator (QMLE). We establish rates of convergence and central limit theorems (CLT) for our estimators in the large dimensional case. A specification test and tools for Kronecker product model selection and inference are provided. In a Monte Carlo study where a Kronecker product model is correctly specified, our estimators exhibit superior performance. In an empirical application to portfolio choice for S&P500 daily returns, we demonstrate that certain Kronecker product models are good approximations to the general covariance matrix.
    Keywords Monte Carlo method ; econometric models ; economic analysis ; economic theory ; variance covariance matrix
    Language English
    Publishing place Elsevier B.V.
    Document type Article
    Note Pre-press version
    ZDB-ID 1460617-3
    ISSN 0304-4076
    ISSN 0304-4076
    DOI 10.1016/j.jeconom.2019.12.012
    Database NAL-Catalogue (AGRICOLA)

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  10. Article ; Online: Using Rapid Prototyping to Develop a Cell-Based Platform with Electrical Impedance Sensor Membranes for In Vitro RPMI2650 Nasal Nanotoxicology Monitoring.

    Vasconez Martinez, Mateo Gabriel / Reihs, Eva I / Stuetz, Helene M / Hafner, Astrid / Brandauer, Konstanze / Selinger, Florian / Schuller, Patrick / Bastus, Neus / Puntes, Victor / Frank, Johannes / Tomischko, Wolfgang / Frauenlob, Martin / Ertl, Peter / Resch, Christian / Bauer, Gerald / Povoden, Guenter / Rothbauer, Mario

    Biosensors

    2024  Volume 14, Issue 2

    Abstract: Due to advances in additive manufacturing and prototyping, affordable and rapid microfluidic sensor-integrated assays can be fabricated using additive manufacturing, xurography and electrode shadow masking to create versatile platform technologies aimed ... ...

    Abstract Due to advances in additive manufacturing and prototyping, affordable and rapid microfluidic sensor-integrated assays can be fabricated using additive manufacturing, xurography and electrode shadow masking to create versatile platform technologies aimed toward qualitative assessment of acute cytotoxic or cytolytic events using stand-alone biochip platforms in the context of environmental risk assessment. In the current study, we established a nasal mucosa biosensing platform using RPMI2650 mucosa cells inside a membrane-integrated impedance-sensing biochip using exclusively rapid prototyping technologies. In a final proof-of-concept, we applied this biosensing platform to create human cell models of nasal mucosa for monitoring the acute cytotoxic effect of zinc oxide reference nanoparticles. Our data generated with the biochip platform successfully monitored the acute toxicity and cytolytic activity of 6 mM zinc oxide nanoparticles, which was non-invasively monitored as a negative impedance slope on nasal epithelial models, demonstrating the feasibility of rapid prototyping technologies such as additive manufacturing and xurography for cell-based platform development.
    MeSH term(s) Humans ; Electric Impedance ; Zinc Oxide ; Microfluidics ; Biosensing Techniques
    Chemical Substances Zinc Oxide (SOI2LOH54Z)
    Language English
    Publishing date 2024-02-18
    Publishing country Switzerland
    Document type Journal Article
    ZDB-ID 2662125-3
    ISSN 2079-6374 ; 2079-6374
    ISSN (online) 2079-6374
    ISSN 2079-6374
    DOI 10.3390/bios14020107
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