scholarly journals Trends in Childbearing, Marriage and Divorce in Sweden: An Update with Data up to 2012

2016 ◽  
Vol 50 ◽  
pp. 21-30 ◽  
Author(s):  
Gunnar Andersson ◽  
Martin Kolk
Keyword(s):  
Time Series ◽  
Family Dynamics ◽  
Turn Of The Century ◽  
Population Research ◽  
Marriage And Divorce ◽  
Relative Risks ◽  
Demographic Behavior ◽  
Swedish Family ◽  
Trend Reversal

We present an update of the main and parity-specific trends in vital family-demographic behavior in Sweden presented in Finnish Yearbook of Population Research 2011. Based on Swedish register data, previous time series of relative risks of childbearing, marriage, and divorce by calendar year are updated with another five years of observation. We demonstrate that more than a decade of increasing fertility levels turned into moderate fertility declines in 2011. This trend reversal pertains to all main birth orders. Marriage propensities continued to increase for mothers but stagnated for the childless. Since the turn of the century, trends in divorce risks seem to have leveled off, altogether reflecting a more prevalent role of marriage in recent Swedish family dynamics.

scholarly journals Trends in Childbearing and Nuptiality in Sweden: An Update with Data up to 2007

2011 ◽  
pp. 21-29 ◽  
Author(s):  
Gunnar Andersson ◽  
Martin Kolk
Keyword(s):  
Time Series ◽  
21St Century ◽  
Upward Trend ◽  
Marriage Rates ◽  
Marriage And Divorce ◽  
Relative Risks ◽  
Demographic Behavior ◽  
Recent Trends ◽  
Trend Reversal

We present an update of the main features of recent trends in vital family-demographic behavior in Sweden. For this purpose, time series of relative risks of childbearing, marriage, and divorce by calendar year are updated with another five years of observation added to previously published series. We demonstrate that fertility in Sweden continued its upward trend during much of the first decade of the 21st century. The rise pertains to all birth orders. It is driven by the halt in postponement of first childbearing at the younger ages and the continued fertility recuperation at higher ages. Marriage propensities increased as well, reversing a decades-long trend of decreasing marriage rates. The trend reversal comprises first marriages and remarriages alike. Interestingly, the increased popularity of marriage and childbearing is accompanied with a slight decline in divorce risks during the first decade of the new century.

The role of parental self-regulation and household chaos in parent-toddler interactions: A time-series study.

2020 ◽  
Author(s):  
Sanne B. Geeraerts ◽  
Joyce Endendijk ◽  
Kirby Deater-Deckard ◽  
Jorg Huijding ◽  
Marike H. F. Deutz ◽  
...  
Keyword(s):  
Time Series ◽  
Self Regulation ◽  
Household Chaos ◽  
Time Series Study ◽  
Series Study

scholarly journals The Role of Assumptions in Ohlson Model Performance: Lessons for Improving Equity-Value Modeling

Mathematics ◽  
2021 ◽  
Vol 9 (5) ◽  
pp. 513
Author(s):  
Olga Fullana ◽  
Mariano González ◽  
David Toscano
Keyword(s):  
Time Series ◽  
Model Performance ◽  
Listed Firms ◽  
Valuation Model ◽  
Residual Income Valuation ◽  
Equity Value ◽  
Short Run ◽  
Time Series Approach ◽  
Linear Information

In this paper, we test whether the short-run econometric conditions for the basic assumptions of the Ohlson valuation model hold, and then we relate these results with the fulfillment of the short-run econometric conditions for this model to be effective. Better future modeling motivated us to analyze to what extent the assumptions involved in this seminal model are not good enough approximations to solve the firm valuation problem, causing poor model performance. The model is based on the well-known dividend discount model and the residual income valuation model, and it adds a linear information model, which is a time series model by nature. Therefore, we adopt the time series approach. In the presence of non-stationary variables, we focus our research on US-listed firms for which more than forty years of data with the required cointegration properties to use error correction models are available. The results show that the clean surplus relation assumption has no impact on model performance, while the unbiased accounting property assumption has an important effect on it. The results also emphasize the uselessness of forcing valuation models to match the value displacement property of dividends.

scholarly journals Calibrating the CreditRisk+ Model at Different Time Scales and in Presence of Temporal Autocorrelation †

Mathematics ◽  
2021 ◽  
Vol 9 (14) ◽  
pp. 1679
Author(s):  
Jacopo Giacomelli ◽  
Luca Passalacqua
Keyword(s):  
Time Series ◽  
Default Risk ◽  
Real Life ◽  
Statistical Error ◽  
Real Data ◽  
Sampling Period ◽  
Calibration Procedure ◽  
Industry Standards ◽  
Default Rate

The CreditRisk+ model is one of the industry standards for the valuation of default risk in credit loans portfolios. The calibration of CreditRisk+ requires, inter alia, the specification of the parameters describing the structure of dependence among default events. This work addresses the calibration of these parameters. In particular, we study the dependence of the calibration procedure on the sampling period of the default rate time series, that might be different from the time horizon onto which the model is used for forecasting, as it is often the case in real life applications. The case of autocorrelated time series and the role of the statistical error as a function of the time series period are also discussed. The findings of the proposed calibration technique are illustrated with the support of an application to real data.

scholarly journals Seasonality in extra-pulmonary tuberculosis notifications in Germany 2004-2014- a time series analysis

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Tanja Charles ◽  
Matthias Eckardt ◽  
Basel Karo ◽  
Walter Haas ◽  
Stefan Kröger
Keyword(s):  
Time Series ◽  
Time Series Analysis ◽  
Disease Onset ◽  
Age Groups ◽  
Age Group ◽  
Pulmonary Tb ◽  
Series Analysis ◽  
Disease Site ◽  
Extra Pulmonary

Abstract Background Seasonality in tuberculosis (TB) has been found in different parts of the world, showing a peak in spring/summer and a trough in autumn/winter. The evidence is less clear which factors drive seasonality. It was our aim to identify and evaluate seasonality in the notifications of TB in Germany, additionally investigating the possible variance of seasonality by disease site, sex and age group. Methods We conducted an integer-valued time series analysis using national surveillance data. We analysed the reported monthly numbers of started treatments between 2004 and 2014 for all notified TB cases and stratified by disease site, sex and age group. Results We detected seasonality in the extra-pulmonary TB cases (N = 11,219), with peaks in late spring/summer and troughs in fall/winter. For all TB notifications together (N = 51,090) and for pulmonary TB only (N = 39,714) we did not find a distinct seasonality. Additional stratified analyses did not reveal any clear differences between age groups, the sexes, or between active and passive case finding. Conclusion We found seasonality in extra-pulmonary TB only, indicating that seasonality of disease onset might be specific to the disease site. This could point towards differences in disease progression between the different clinical disease manifestations. Sex appears not to be an important driver of seasonality, whereas the role of age remains unclear as this could not be sufficiently investigated.

scholarly journals Mapping Forest Fuels through Vegetation Phenology: The Role of Coarse-Resolution Satellite Time-Series

PLoS ONE ◽  
2015 ◽  
Vol 10 (3) ◽  
pp. e0119811 ◽  
Author(s):  
Sofia Bajocco ◽  
Eleni Dragoz ◽  
Ioannis Gitas ◽  
Daniela Smiraglia ◽  
Luca Salvati ◽  
...  
Keyword(s):  
Time Series ◽  
Vegetation Phenology ◽  
Forest Fuels ◽  
Coarse Resolution

TIME SERIES MODELLING OF EPIDEMICS: LEADING INDICATORS, CONTROL GROUPS AND POLICY ASSESSMENT

2021 ◽  
Vol 257 ◽  
pp. 83-100
Author(s):  
Andrew Harvey
Keyword(s):  
Time Series ◽  
Data Science ◽  
Leading Indicators ◽  
Control Groups ◽  
Balanced Growth ◽  
Time Series Modelling ◽  
Key Variables ◽  
The Uk ◽  
The Relationship

This article shows how new time series models can be used to track the progress of an epidemic, forecast key variables and evaluate the effects of policies. The univariate framework of Harvey and Kattuman (2020, Harvard Data Science Review, Special Issue 1—COVID-19, https://hdsr.mitpress.mit.edu/pub/ozgjx0yn) is extended to model the relationship between two or more series and the role of common trends is discussed. Data on daily deaths from COVID-19 in Italy and the UK provides an example of leading indicators when there is a balanced growth. When growth is not balanced, the model can be extended by including a non-stationary component in one of the series. The viability of this model is investigated by examining the relationship between new cases and deaths in the Florida second wave of summer 2020. The balanced growth framework is then used as the basis for policy evaluation by showing how some variables can serve as control groups for a target variable. This approach is used to investigate the consequences of Sweden’s soft lockdown coronavirus policy in the spring of 2020.

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