Women, lifelong learning and transitions into employment

2006 ◽  
Vol 20 (2) ◽  
pp. 309-328 ◽  
Author(s):  
Andrew Jenkins
Keyword(s):  
Lifelong Learning ◽  
Event History Analysis ◽  
Labour Force ◽  
Full Range ◽  
Economic Effects ◽  
Event History ◽  
Formal Learning ◽  
Policy Makers ◽  
History Analysis ◽  
First Time

Policy makers place increasing emphasis on the importance of lifelong learning in enabling more people, not just the registered unemployed, who are out of the labour force to move back into employment, or even into employment for the first time. However, there is very little reliable evidence on the economic effects of formal learning undertaken by adults. This article reports research on a cohort of British women in their 30s who initially were not in employment, using event history analysis to examine the factors which influenced transitions into employment between 1991 and 2000.The key finding is that, in the presence of a full range of controls, lifelong learning, defined in terms of obtaining qualifications as an adult, substantially increases the likelihood that labour-market inactive women will make a transition to paid employment.

scholarly journals Using Event History Analysis in Historical Research: With Illustrations from a Study of the Passage of Women's Protective Legislation

1998 ◽  
Vol 43 (S6) ◽  
pp. 33-55 ◽  
Author(s):  
Holly J. McCammon
Keyword(s):  
Event History Analysis ◽  
Historical Research ◽  
Event History ◽  
Industrial Workers ◽  
Social Scientists ◽  
Policy Makers ◽  
History Analysis

Historians and social scientists often investigate the conditions that influence the occurrence of particular events. For instance, a researcher might be concerned with the causes of revolutionary action in some countries or the forces that unleash racial rioting in major cities. Or perhaps the researcher wishes to examine why industrial workers decide to strike or what prompts policy-makers to pass new legislation. In each of these examples, a qualitative shift occurs, from a circumstance without racial rioting in a particular city, for instance, to one with racial rioting. Event history analysis can aid researchers in uncovering the conditions that lead to such a shift.

scholarly journals Event History Analysis for Investigating the Likelihood and Timing of Changing Majors

2018 ◽  
Vol 38 (1) ◽  
pp. 47-60 ◽  
Author(s):  
Jeffrey C. Sklar
Keyword(s):  
Event History Analysis ◽  
Student Characteristics ◽  
Event History ◽  
First Year ◽  
First Year Students ◽  
History Analysis ◽  
Enrollment Data ◽  
First Time ◽  
The Relationship

Students change their majors for various reasons, and academic advisors often assume the role of facilitating that change through institutional agreements or contracts. Therefore, advisors need to identify time periods during enrollment with the greatest likelihood that students will seek to change majors. They must also examine the student characteristics associated with changing majors so that advisors can identify students to avoid delays to graduation. The relationship between student characteristics and the likelihood of changing majors over time was studied through event history analysis techniques applied to enrollment data for a cohort of first-time first-year students.

Event History Analysis of Antecedents to Running Away from Home and Being on the Street

2001 ◽  
Vol 45 (1) ◽  
pp. 51-65 ◽  
Author(s):  
KEVIN A. YODER ◽  
LES B. WHITBECK ◽  
DAN R. HOYT
Keyword(s):  
Sexual Abuse ◽  
Event History Analysis ◽  
Event History ◽  
Running Away ◽  
History Analysis ◽  
First Time ◽  
White Youths

Event history analysis was used to study the correlates of running away from home for the first time and spending time directly on the street (sleeping outside or in an abandoned building) for the first time in a sample of 602 homeless and runaway adolescents from four Midwestern states. The results indicated that age, neglect by an adult caretaker, and sexual abuse by an adult caretaker were associated with the likelihood of running away from home for the first time. Moreover, age at first run and the amount of time that elapsed since first running away from home were associated with the likelihood of spending time directly on the street for the first time. Finally, although males and White youths were no more likely than females and non-White youths, respectively, to run away initially, males and White youths were more likely than females and non-White youths, respectively, to spend time directly on the street.

Household Surveys as a Source of Data for Event History Analysis

2009 ◽  
Vol 24 (3) ◽  
pp. 430-456
Author(s):  
Benoît Laplante ◽  
María Marta Santillán ◽  
María Constanza Street
Keyword(s):  
Event History Analysis ◽  
Labour Force ◽  
Event History ◽  
Household Surveys ◽  
Panel Surveys ◽  
Independent Variables ◽  
Use Of Time ◽  
Use Of Data ◽  
History Analysis ◽  
Consensual Unions

The authors introduce a method that allows the use of data from rotating panel surveys, a design used in many household or labour force surveys, to realize statistical analyses similar to event history analysis. The method is illustrated with two examples, one on the dynamics of poverty — the effect of demographic and socioeconomic factors on the hazard of becoming poor in Argentina — and the other on family dynamics — the conversion of consensual unions into marriages. Both examples use data from the Argentinean Encuesta Permanente de Hogares, a national survey that is not designed to collect prospective or biographical data. The method allows for the use of time-varying independent variables and thus allows one to estimate the effect of an event on the hazard of another event, as in conventional event history analysis; several examples are provided.

The Adoption of Public Pre-Kindergarten among the American States: An Event History Analysis

2020 ◽  
pp. 089590482096100
Author(s):  
Lora Cohen-Vogel ◽  
James Sadler ◽  
Michael H. Little ◽  
Becca Merrill ◽  
F. Chris Curran
Keyword(s):  
Event History Analysis ◽  
The United States ◽  
Event History ◽  
Publicly Funded ◽  
Policy Makers ◽  
Legislative Action ◽  
History Analysis ◽  
Eligibility Requirements ◽  
Party Dominance ◽  
Combining Information

Over the past few decades, we have witnessed a surge in publicly funded pre-K programs in the United States. Today, policy makers in 45 states and the District of Columbia have adopted them. Combining information from twelve datasets, we use event history analysis (EHA) to examine the influence of a set of predictors on states’ decisions to adopt public pre-K. Findings indicate that party dominance in the legislature, legislative professionalism, and unemployment rates are associated with pre-K adoption; regional proximity to previously adopting states is also significant. The authors discuss implications for policy makers and advocates considering future legislative action in the early childhood education sector, including the expansion of pre-K eligibility requirements.

Migration to Urban and Rural Destinations in Post-Soviet Estonia: A Multilevel Event-History Analysis

2006 ◽  
Vol 38 (4) ◽  
pp. 749-764 ◽  
Author(s):  
Hill Kulu ◽  
Francesco C Billari
Keyword(s):  
Event History Analysis ◽  
Labour Force ◽  
Personal Characteristics ◽  
Event History ◽  
History Analysis ◽  
Socioeconomic Restructuring ◽  
Research Population ◽  
Western Market ◽  
Contextual Determinants ◽  
Rural Destinations

Researchers are divided on the trends and causes of internal migration in postsocialist Central and Eastern Europe. Theories run in opposite directions: some scholars argue that increasing similarities with Western market economies are explaining the migration processes, whereas others claim that specific developments during the postsocialist socioeconomic restructuring are playing a major role. In this paper we contribute to the existing discussion by providing an analysis of personal and contextual determinants of migration to urban and rural destinations in post-Soviet Estonia. We base our study on the data of the Estonian Labour Force Survey from 1995. Our research population consists of 8480 people aged 15 years to 68 years in early 1989. We analyze the intensity of urban-bound and rural-bound migration from January 1989 to December 1994, using the techniques of multilevel event-history analysis. We show that personal characteristics (age, marital status, employment status, education, and ethnicity) and contextual factors (unemployment level and the share of ethnic minorities) are both important in shaping the intensity of migration to urban and rural destinations in post-Soviet Estonia. Although the differences in migration behaviour by demographic characteristics in Estonia are in line with universalistic explanations, the regionally varying effect of socioeconomic status on migration is specific to developments in postsocialist countries, as a result of general economic hardship during the socioeconomic transition.

Event History Analysis in Demography

1995 ◽  
Vol 49 (2) ◽  
pp. 355-357
Author(s):  
Johannes Huinink
Keyword(s):  
Event History Analysis ◽  
Event History ◽  
History Analysis

From source-oriented databases to event-history data files: a twelve-step action plan for the analysis of individual and household life histories

1998 ◽  
Vol 10 (1-3) ◽  
pp. 1-9
Author(s):  
Onno Boonstra ◽  
Maarten Panhuysen
Keyword(s):  
Life Histories ◽  
Event History Analysis ◽  
Action Plan ◽  
Event History ◽  
Flat File ◽  
Event History Data ◽  
History Analysis ◽  
Good Technique ◽  
Data Files ◽  
The Way

Population registers are recognised to be a very important source for demographic research, because it enables us to study the lifecourse of individuals as well as households. A very good technique for lifecourse analysis is event history analysis. Unfortunately, there are marked differences in the way the data are available in population registers and the way event history analysis expects them to be. The source-oriented approach of computing historical data calls for a ‘five-file structure’, whereas event history analysis only can handle fiat files. In this article, we suggest a series of twelve steps with which population register data can be transposed from a five-file structured database into a ‘flat file’ event history analysis dataset.

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