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Mason, Kevin; Mason, Winter; Winsborough, Hal H.; Poole, W. Kenneth

doi:10.1097/00006199-197309000-00027

Cited by 2 publications

(3 citation statements)

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“…This model does not suffer from the complete confounding of age, period, and cohort effects discussed in Mason et al (1973) because relative cohort size, unlike cohort, is not completely determined by age and period. Further, in this analysis, age-group and period variables are orthogonal to one another.…”

Section: Discussionmentioning

confidence: 99%

Relative Cohort Size and Age‐specific Crime Rates: An Age‐period‐relative‐cohort‐size Model*

O’Brien

1989

Criminology

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The compositional effects of relatively large young-adult cohorts on the total rate of serious crimes is well established. The more subtle effect of relative cohort size on age-specij7c crime rates, suggested by Richard Easterlin, is more controversial. The literature contains no adequate test of Easterlin ' s hypothesis as it relates to crime. To provide an adequate test of Easterlin ' s theory, this study includes age-speciJc rates and measures of relative cohort size and controls for age and period in an age-period-relative-cohort-size model. Using arrest data from the Uniform Crime Reports (Part I crimes) for the years 1960, 1965, 1970, 1975, 1980, and 1985, the analysis provides support for Easterlin ' s theory for property crimes, that is, for robbery, burglary, and larceny (but not for motor vehicle theft). Though these relationships were small in comparison to those between age or period and age-spec@ crime rates, they were generally statistically signij7cant and were replicated with data from 1962, 1967, 1972, 1977, 1982, and 1987. The relationships between relative cohort size and assaultive crimes provided little consistent support for Easterlin 's theory.The dramatic increase in serious crime rates in the United States during the 1960s and 1970s needs little documentation. Homicide rates, for example, increased from 5.1 per 100,OOO in 1960, to 7.9 in 1970, to 10.2 in 1980, before declining to 7.9 in 1985. Similar increases occurred for the other part I crimes included in the Uniform Crime Report (UCR) crime index. 1Researchers attribute the increases in the overall rates of violent crimes to a number of factors, for example, increased urbanization (Ferdinand, 1970), increased unemployment rates (e.g., Cohen et al., 1980; Fleisher, 1963 Fleisher, , 1966, the consumer price index (Fox, 1976), the proportion of young black males in the population (Fox, 1976), and the residential population density ratio *This paper was motivated, in part, by a talk entitled, "A Test of Easterlin's Explanation of Trends in Political Alienation," given by William M. Mason. He, obviously, bears no responsibility for any errors in my own applications and modifications of his methods. I am indebted to Patricia Gwartney-Gibbs for suggestions and a careful reading of an earlier version of this paper.The UCR index includes murder and nonnegligent manslaughter, forcible rape, robbery, aggravated assault, burglary, larceny-theft, and motor vehicle theft. Arson was not added as a Part I crime until 1979.

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Section: Discussionmentioning

confidence: 99%

Relative Cohort Size and Age‐specific Crime Rates: An Age‐period‐relative‐cohort‐size Model*

O’Brien

1989

Criminology

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“…This is known as the "identification problem" in age-periodcohort analysis. Many previous studies attempt to overcome this problem by imposing some restraints on the identification model, usually by constraining two coefficients to be equal (Mason et al, 1973; or grouping one of the variables (Grasso, 2014(Grasso, , 2016Grasso et al, 2017). These restraints need to be based on theoretical assumptions about the likely effects of the three terms, although in reality, they are often undefended and risk producing arbitrary results (Tilley, 2002;Bell and Jones, 2013;Luo and Hodges, 2016).…”

Section: Analytical Approachmentioning

confidence: 99%

“…The above methods and debates are all ultimately based on the "APC accounting model" and the "multiple classification model", first explicated by Mason et al (1973) and Mason and Fienberg (1985), where age, period and cohort are modeled as three independent variables with some constraints to their coefficients (Yang et al, 2008;O'Brien, 2011;; see also Luo, 2013a). Recently, some prominent authors on both side of those debates have recently gravitated toward a different perspective: modeling cohort effects as cumulative, non-linear Respondents who chose "usually" or "many politicians" as opposed to "some", "few" or "none" are coded as trusting here.…”

Section: Analytical Approachmentioning

confidence: 99%

The recession generation? Age-period-cohort dynamics of political trust in six countries severely affected by the 2008 crisis

Valgarðsson

2024

Front. Polit. Sci.

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A potential puzzle has emerged in the study of political trust: recent studies indicate that individuals' trust judgements are remarkably stable over their life course, but many other studies have observed long-term declines of trust in the aggregate. In particular, trust clearly declined substantially during and following the 2008 economic (and political) crisis in many European countries severely affected by it: especially Greece, Iceland, Ireland, Italy, Portugal and Spain. In this study, I focus on these countries and ask to what extent the crisis may have resulted in a “recession generation” of citizens who were in their formative years at the time and may have adopted less trusting political orientations that have persisted since, more or less independent of life-cycle and period effects. To answer this question, I present descriptive visualizations of trust levels by citizens' age over time and conduct statistical age-period-cohort (APC) analysis of political trust levels using generalized additive models (GAMs) on data from the Eurobarometer (1997–2022) and the European Values Study/World Values Survey (EVS/WVS). The findings are inconclusive: descriptive comparisons of age-by-year diagonals suggest this cohort of citizens may indeed have lower levels of trust than older and younger cohorts, above and beyond the effects of life cycle and period—but the results from GAMs differ between countries and data sources and only show the expected cohort effect in three cases. These tentative results have implications for our understanding of the nature of political trust judgements and the potential socializing effects of major political events on citizens attitude-formation, but they await confirmation in future studies which will have the benefit of longer-term data and potentially further innovations in APC analysis.

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Cited by 2 publications

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Relative Cohort Size and Age‐specific Crime Rates: An Age‐period‐relative‐cohort‐size Model*

Relative Cohort Size and Age‐specific Crime Rates: An Age‐period‐relative‐cohort‐size Model*

The recession generation? Age-period-cohort dynamics of political trust in six countries severely affected by the 2008 crisis

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