3 resultados para Blue Chip Economic Indicators

em Helda - Digital Repository of University of Helsinki


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Adverse health behaviors as well as obesity are key risk factors for chronic diseases. Working conditions also contribute to health outcomes. It is possible that the effects of psychosocially strenuous working conditions and other work-related factors on health are, to some extent, explained by adverse behaviors. Previous studies about the associations between several working conditions and behavioral outcomes are, however, inconclusive. Moreover, the results are derived mostly from male populations, one national setting only, and with limited information about working conditions and behavioral risk factors. Thus, with an interest in employee health, this study was set to focus on behavioral risk factors among middle-aged employees. More specifically, the main aim was to shed light on the associations of various working conditions with health behaviors, weight gain, obesity, and symptoms of angina pectoris. In addition to national focus, international comparisons were included to test the associations across countries thereby aiming to produce a more comprehensive picture. Furthermore, a special emphasis was on gaining new evidence in these areas among women. The data derived from the Helsinki Health Study, and from collaborative partners at the Whitehall II Study, University College London, UK, and the Toyama University, Japan. In Helsinki, the postal questionnaires were mailed in 2000-2002 to employees of the City of Helsinki, aged 40 60 years (n=8960). The questionnaire data covered e.g., socio-economic indicators and working conditions such as Karasek s job demands and job control, work fatigue, working overtime, work-home interface, and social support. The outcome measures consisted of smoking, drinking, physical activity, food habits, weight gain, obesity, and symptoms of angina pectoris. The international cohorts included comparable data. Logistic regression analysis was used. The models were adjusted for potential confounders such as age, education, occupational class, and marital status subject to specific aims. The results showed that working conditions were mostly unassociated with health behaviors, albeit some associations were found. Low job strain was associated with healthy food habits and non-smoking among women in Helsinki. Work fatigue, in turn, was related to drinking among men and physical inactivity among women. Work fatigue and working overtime were associated with weight gain in Helsinki among both women and men. Finally, work fatigue, low job control, working overtime, and physically strenuous work were associated with symptoms of angina pectoris among women in Helsinki. Cross-country comparisons confirmed mostly non-existent associations. High job strain was associated with physical inactivity and smoking, and passive work with physical inactivity and less drinking. Working overtime, in turn, related to non-smoking and obesity. All these associations were, however, inconsistent between cohorts and genders. In conclusion, the associations of the studied working conditions with the behavioral risk factors lacked general patters, and were, overall, weak considering the prevalence of psychosocially strenuous work and overtime hours. Thus, based on this study, the health effects of working conditions are likely to be mediated by adverse behaviors only to a minor extent. The associations of work fatigue and working overtime with weight gain and symptoms of angina pectoris are, however, of potential importance to the subsequent health and work ability of employees.

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In recent years, thanks to developments in information technology, large-dimensional datasets have been increasingly available. Researchers now have access to thousands of economic series and the information contained in them can be used to create accurate forecasts and to test economic theories. To exploit this large amount of information, researchers and policymakers need an appropriate econometric model.Usual time series models, vector autoregression for example, cannot incorporate more than a few variables. There are two ways to solve this problem: use variable selection procedures or gather the information contained in the series to create an index model. This thesis focuses on one of the most widespread index model, the dynamic factor model (the theory behind this model, based on previous literature, is the core of the first part of this study), and its use in forecasting Finnish macroeconomic indicators (which is the focus of the second part of the thesis). In particular, I forecast economic activity indicators (e.g. GDP) and price indicators (e.g. consumer price index), from 3 large Finnish datasets. The first dataset contains a large series of aggregated data obtained from the Statistics Finland database. The second dataset is composed by economic indicators from Bank of Finland. The last dataset is formed by disaggregated data from Statistic Finland, which I call micro dataset. The forecasts are computed following a two steps procedure: in the first step I estimate a set of common factors from the original dataset. The second step consists in formulating forecasting equations including the factors extracted previously. The predictions are evaluated using relative mean squared forecast error, where the benchmark model is a univariate autoregressive model. The results are dataset-dependent. The forecasts based on factor models are very accurate for the first dataset (the Statistics Finland one), while they are considerably worse for the Bank of Finland dataset. The forecasts derived from the micro dataset are still good, but less accurate than the ones obtained in the first case. This work leads to multiple research developments. The results here obtained can be replicated for longer datasets. The non-aggregated data can be represented in an even more disaggregated form (firm level). Finally, the use of the micro data, one of the major contributions of this thesis, can be useful in the imputation of missing values and the creation of flash estimates of macroeconomic indicator (nowcasting).

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Väitöskirjatutkimuksen tavoitteena oli selvittää, miten aviopuolisoiden sosioekonominen asema vaikuttaa avioeroriskiin Suomessa. Tutkimuksessa käytettiin Tilastokeskuksen rekistereistä koottua aineistoa, joka koskee suomalaisten ensimmäisiä avioliittoja vuoden 1990 lopussa ja avioeroja vuosina 1991−93. Väitöskirjaan sisältyy kolme osatutkimusta. Ensimmäinen osatutkimus käsitteli avioeroriskin vaihtelua aviopuolisoiden sosioekonomisen aseman eri osatekijöiden (koulutusaste, sosiaaliryhmä, pääasiallinen toiminta, tulotaso, asunnon omistaminen ja asumisahtaus) mukaan. Kaiken kaikkiaan avioeroriski oli sitä pienempi, mitä paremmassa taloudellisessa ja sosiaalisessa asemassa aviopuolisot olivat. Esimerkiksi miehen ja vaimon korkea koulutusaste, toimihenkilöammatti, työssäkäynti (etenkin verrattuna työttömyyteen) sekä omistusasunnossa asuminen liittyivät pienentyneeseen avioeroriskiin. Vaimon sosioekonomisen aseman yhteys avioeroriskiin oli paljolti samanlainen kuin miehen aseman yhteys. Huomattavin poikkeus tähän oli, että vaimon suuret tulot lisäsivät avioeroriskiä, vaikka miehen suurilla tuloilla oli päinvastainen vaikutus. Lisäksi kotitaloustyötä pääasiallisena toimintanaan tekevillä naisilla (pääasiallisen toiminnan luokka ”muut”) oli vielä pienempi avioeroriski kuin työssäkäyvillä naisilla. Toisessa osatutkimuksessa keskityttiin aviomiehen ja vaimon aseman yhdistettyyn vaikutukseen. Selviä viitteitä siitä, että puolisoiden koulutustasojen erilaisuus lisäisi eroriskiä, ei saatu. Pareilla, joissa molemmilla oli enintään perusasteen koulutus, oli kuitenkin odotettua pienempi avioeroriski. Eroriski oli suhteellisen alhainen pareilla, joissa vaimo oli työssäkäyvä tai kotitaloustyötä tekevä ja aviomies työssäkäyvä. Eroriskiä kasvatti se, että aviomies, vaimo tai molemmat puolisot olivat työttömiä. Vaimon korkea tulotaso lisäsi eroriskiä miehen kaikilla tulotasoilla mutta erityisen voimakkaasti silloin, kun miehen tulotaso oli alhainen. Kolmanneksi selvitettiin, vaikuttaako puolisoiden sosioekonominen asema avioeroriskiin eri tavalla riippuen siitä, kauanko avioliitto on kestänyt. Tällöin havaittiin, että vähän koulutettujen ja työntekijäammateissa toimivien puolisoiden suuri eroriski rajoittuu paljolti nuorimpiin avioliittoihin. Sen sijaan esim. puolisoiden työttömyys, vaimon korkea tulotaso ja vuokra-asunnossa asuminen kasvattivat eroriskiä riippumatta siitä, kuinka kauan avioliitto oli kestänyt. Kaiken kaikkiaan eroriski oli siis sitä pienempi, mitä paremmassa taloudellisessa ja sosiaalisessa asemassa puolisot olivat. Vaimon taloudellisilla ja sosiaalisilla resursseilla näyttää kuitenkin olevan myös joitakin avioeroriskiä lisääviä vaikutuksia.