| 1. |
- Andersson, Michael K., et al.
(författare)
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Bayesian forecast combination for VAR models
- 2008
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Ingår i: Bayesian Econometrics. - Bingley : Emerald. - 9781848553088 ; , s. 501-524
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Bokkapitel (övrigt vetenskapligt/konstnärligt)
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| 2. |
- Andersson, Michael K., et al.
(författare)
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Bootstrapping Error Component Models
- 2001
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Ingår i: Computational statistics (Zeitschrift). - : Physica Verlag. - 0943-4062 .- 1613-9658. ; 16:2, s. 221-231
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Tidskriftsartikel (refereegranskat)abstract
- This paper proposes several resampling algorithms suitable for error component models and evaluates them in the context of bootstrap testing. In short, all the algorithms work well and lead to tests with correct or close to correct size. There is thus little or no reason not to use the bootstrap with error component models.
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| 3. |
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| 4. |
- Andrén, Daniela, Associate Professor, 1968-, et al.
(författare)
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Individual wellbeing and cortisol
- 2024
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Ingår i: Encyclopedia of Happiness, Quality of Life and Subjective Wellbeing. - : Edward Elgar Publishing. - 9781800889668 - 9781800889675 ; , s. 125-133
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Bokkapitel (refereegranskat)abstract
- The variety and the number of ways of measuring individual wellbeing has increased over the past two decades. In addition to all self-reported measures, researchers also consider a wide variety of objectively-measured indicators of wellbeing (e.g., blood pressure, pulse rate, and the pattern of activity in different parts of the brain). However, it has not yet been established if the analysis of one only of these measurement concepts suffices, or rather whether more can be learnt from the joint analyses of both subjective and objective adult wellbeing indicators. This chapter briefly reviews this question, focussing on cortisol (as a potential objective measure) and life satisfaction (as a subjective measure), and suggests directions for future research.
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| 5. |
- Andrén, Daniela, 1968-, et al.
(författare)
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New ways to measure well-being? : A first joint analysis of subjective and objective measures
- 2018
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Rapport (övrigt vetenskapligt/konstnärligt)abstract
- Our study is, to our knowledge, the first joint analysis of subjective and objective measures of well-being. Using a rich longitudinal data from the mothers pregnancy until adulthood for a birth cohort of children who attended school in Örebro during the 1960s, we analyse in a first step how subjective (self-assessed) and objective (cortisol-based) measures of well-being are related to each other. In a second step, life-course models for these two measures are estimated and compared with each other. Despite the fact that our analysis is largely exploratory, our results suggest interesting possibilities to use objective measures to measure well-being, even though this may imply a greater degree of complexity.
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| 6. |
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| 7. |
- Andrén, Daniela, 1968-, et al.
(författare)
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Subjective and physiological measures of well-being : an exploratory analysis using birth-cohort data
- 2017
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Rapport (övrigt vetenskapligt/konstnärligt)abstract
- We use a rich longitudinal data set following a cohort of Swedish women from age 10 to 49 to analyse the effects of birth and early-life conditions on adulthood outcomes. These latter include both well-being and the stress hormone cortisol. Employment and marital status are important adult determinants of well-being. Log family income and absence from school also predict adult well-being, although their importance falls when controlling for adult and birth characteristics. Among the birth characteristics, we find that high birth weight (>4.3kg) affects adult well-being. We predict the level of adult cortisol only poorly, and suggest that the relationship between life satisfaction and cortisol is non-monotonic: both high and low cortisol are negatively correlated with life satisfaction. The results from an OLS life satisfaction regression and a multinomial logit of high or low cortisol (as compared to medium) are more similar to each other.
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| 8. |
- Berger, Helge, et al.
(författare)
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A note of caution on the relation between money growth and inflation
- 2023
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Ingår i: Scottish Journal of Political Economy. - : John Wiley & Sons. - 0036-9292 .- 1467-9485. ; 70:5, s. 479-496
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Tidskriftsartikel (refereegranskat)abstract
- We assess the bivariate relation between money growth and inflation in the euro area and the United States using hybrid time-varying parameter Bayesian VAR models. Model selection based on marginal likelihoods suggests that the relation is statistically unstable across time in both regions. The effect of money growth on inflation weakened notably after the 1980s before strengthening after 2020. There is evidence that this time variation is related to the pace of price changes, as we find that the maximum impact of money growth on inflation is increasing in the trend level of inflation. These results caution against asserting a simple, time-invariant relationship when modeling the joint dynamics of monetary aggregates and consumer prices.
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| 9. |
- Ding, Shutong, 1985-, et al.
(författare)
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Bayesian forecasting combination in VAR models with many predictors
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Annan publikation (övrigt vetenskapligt/konstnärligt)abstract
- This paper is motivated by the findings of our previous work, that is forecasting VAR models in the cases of small and medium-sized datasets, both marginalized marginal likelihood and predictive likelihood based averaging approaches tend to produce superior forecasts than the Bayesian VAR methods using shrinkage priors. With an efficient reversible-jump MCMC algorithm, We extend the forecast combination and model averaging of VAR models to the context of large datasets (more than hundred predictors), and consider a range of competitive alternative methods to compare and examine their forecast performance. Our empirical results show that the Bayesian model averaging approach outperforms the various alternatives.
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| 10. |
- Ding, Shutong, 1985-, et al.
(författare)
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Bayesian forecasting using reduced rank VARs
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Annan publikation (övrigt vetenskapligt/konstnärligt)abstract
- Reduced rank regression has a long tradition as a technique to achieve a parsimonious parameterization in multivariate regression models. Recently this has been applied in the Bayesian VAR framework where the rich parameterization is a common concern in applied work. We advocate a parameterization of the reduced rank VAR which leads to a natural interpretation in terms of a dynamic factor model. Without additional restrictions on the parameters the reduced rank model is unidentified and we consider two identification schemes. The traditional ad-hoc identification with the first rows of one of the reduced rank parameter matrices being the identity matrix and a semi-orthogonal identification originally proposed in the context of cointegrated VAR models with the advantage that it does not depend on the ordering of the variables. Borrowing from the cointegration literature, we propose efficient MCMC algorithms for the evaluation of the posterior distribution given the two identification schemes. The determination of the rank of the reduced rank VAR is an important practical issue and we study the performance of different criteria for determining the rank. Finally, the forecasting performance of the reduced rank VAR model is evaluated in comparison with other popular forecasting models for large data sets.
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