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Analysis of demand in steel and iron industry – latent variables model

100%
Barska M.
Przegląd Statystyczny
|
2019
|
vol. 66
|
issue 4
247-269
EN
Demand in the steel and iron industry is influenced by multiple factors. Not all of them can be identified and measured. The paper presents the results of the analysis of the levels of demand achieved by a selected enterprise from this sector in the years 2010–2014. The aim of the study is to build a hidden Markov model which would reflect the turning points of this demand, thus making it possible to forecast its future levels. The model’s forecasting properties and stability have been examined. A simulation has been carried out that involved generating a high number of series for selected model parameters and checking their properties. This demonstrated that a three-state second order hidden Markov model was most relevant to the purpose of the study. Thanks to the model’s application, it was possible to describe states which could potentially shape the demand. Moreover, taking the transition state into consideration allowed spotting the signal about the upcoming replacement of the growth phase with the decline phase, and vice versa. The presented second order hidden Markov model can serve as an alternative to the traditional methods of the analysis of time series. The forecast generated by the model informs about the shaping of a trend in demand and serves as an indication of the shifts in economic cycles.
2
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Analysis of latent class models in economic research

100%
Brzezińska J.
Econometrics. Ekonometria. Advances in Applied Data Analytics
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2016
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issue 4 (54)
36-47
EN
Latent variable models are used and applied in many areas of the social and behavioral sciences. The increasing availability of computer packages for fitting such models makes latent variable models popular, known and applied in many scientific areas. Latent variable models have a very wide range of applications, especially in the presence of repeated observations, longitudinal data, and multilevel data. The basic model postulates an underlying categorical latent variable; within any category of the latent variable the manifest or observed categorical variables are assumed independent of one another (the axiom of conditional independence). The observed relationships between the manifest variables are thus assumed to result from the underlying classification of the data produced by the categorical latent variable. In this paper we present the theoretical and methodological aspects of latent variable models, as well as their application in R software in the field of economic research.
3
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Identification and Estimation of Initial Conditions in Non-Minimal State-Space Models

88%
Bystrov V.
Central European Journal of Economic Modelling and Econometrics
|
2020
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issue 4
4
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Bayesian DEJD Model and Detection of Asymmetry in Jump Sizes

75%
Kostrzewski M.
Central European Journal of Economic Modelling and Econometrics
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2015
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issue 1
5
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A Bayesian Analysis of Exogeneity in Models with Latent Variables

75%
Pajor A.
Central European Journal of Economic Modelling and Econometrics
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2011
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issue 2
6

Model czynnikowy ze zmiennymi dychotomicznymi w analizie ukrytej struktury zjawisk rynkowych

63%
Tarka P.
Zeszyty Naukowe Uniwersytetu Ekonomicznego w Krakowie
|
2013
|
issue 916
47-58
PL
W artykule przedstawiono teoretyczne założenia konstrukcji wraz z praktycznymi implikacjami modelu czynnikowego w kontekście badań marketingowych. W pierwszej części zwrócono uwagę na zależność badań marketingowych od rozwoju teorii pomiaru w ramach analizy zjawisk rynkowych o charakterze ukrytym. Następnie omówiono proces konstrukcji modelu czynnikowego do analizy zmiennych dychotomicznych. Napodstawie przeprowadzonych badań empirycznych zaprezentowano funkcjonalność jednoczynnikowego modelu w sferze pomiaru postaw młodzieży (młodych konsumentów) wobec hedonistyczno-konsumpcyjnego stylu życia.
EN
The article describes a number of theoretical and practical issues pertaining to the factor analysis model and its application in the field of marketing research. The first part discusses the dependence of marketing research on the theory of measurement e.g., the course of research development in the sphere of latent events analysis. The next part looks at factorial modeling in research on consumer attitudes and opinions, followed by a discussion of the possibilities for binary data analysis using the latent trait model. Finally, using empirical data, the author presents a one-factor model to measure youth (young consumers) attitudes towards a hedonistic-consumer lifestyle.
7
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Hierarchiczny model pomiaru jakości życia

51%
Panek T.
Wiadomości Statystyczne. The Polish Statistician
|
2015
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issue 6
1-22
RU
В статье были представлены концепции иерархической модели обсле-дования качества жизни в отношении к целям социальной политики, а также инструменты позволяющие проводить это измерение. Качество жизни в этом подходе определяется на основе теории потребностей, которая отождествляется с уровнем удовлетворения социальных потре-бностей. Кроме того была представлена связь понятия качества жизни с социальной интеграцией и сбалансированным развитием.
PL
W artykule przedstawiono koncepcje hierarchicznego modelu badania jakości życia w kontekście celów polityki społecznej oraz narzędzia umożliwiające ten pomiar. Jakość życia w tym ujęciu zdefiniowana jest na gruncie teorii potrzeb, czyli utożsamiana jest z poziomem zaspokojenia potrzeb społecznych. Ponadto przedstawiono powiązania pojęcia jakości życia z integracją społeczną i zrównoważonym rozwojem.
EN
The study presents the concept of the hierarchical model of quality of life investigation in the context of social policy objectives and tools for the life quality measurement. Quality of life in the context of social policy is defined on the ground of the theory of needs, which is identified with the level of satisfaction of social needs. Moreover, the links of the concept of quality of life with social integration and sustainable development were presented.
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