Comparative Week 8
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The document discusses different ways to measure and compare welfare states beyond just spending levels. It examines micro-level input measures including spending by sub-function, packages of support for different family types, and non-expenditure measures. One study analyzed packages of support for 9 family types and 8 income levels across 22 countries. Non-expenditure measures like decommodification indices based on social insurance rules can also provide insights but data is limited. Comparing micro-level inputs provides a richer picture of how systems function but data availability remains a challenge.
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0008–4085 / 15 / 437–463 / © Canadian Economics Association
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Data for this study was accessed at the South Western Ontario Research Data Centre as part of
the Statistics Canada Research Data Centres Program. The opinions expressed herein do not
represent the opinions of Statistics Canada. The study benefited from a short-term research
grant provided by Wilfrid Laurier University. I would like to thank Kirill Savine for research
assistance. I would like to thank Hideki Ariizumi, Ana Ferrer, Nicole Fortin, David Green,
Stephen Jones, Shelly Lundberg, René Morissette, Arthur Sweetman, Michael Veall as well as
participants of the Laurier Economics Internal Seminar Series, the CRDCN 2012 National
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Corresponding author: Tammy Schirle, [email protected]
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Data for this study was accessed at the South Western Ontario Research Data Centre as part of
the Statistics Canada Research Data Centres Program. The opinions expressed herein do not
represent the opinions of Statistics Canada. The study benefited from a short-term research
grant provided by Wilfrid Laurier University. I would like to thank Kirill Savine for research
assistance. I would like to thank Hideki Ariizumi, Ana Ferrer, Nicole Fortin, David Green,
Stephen Jones, Shelly Lundberg, René Morissette, Arthur Sweetman, Michael Veall as well as
participants of the Laurier Economics Internal Seminar Series, the CRDCN 2012 National
Conference, the McMaster Economics Seminar Series, the CLSRN 2013 Annual Conference
and the University of Victoria Economics Seminar Series for their comments and suggestions.
I also thank two anonymous reviewers for their valuable suggestions.
Corresponding author: Tammy Schirle, [email protected]
438 T. Schirle
1. Introduction
The effect of child .
The Sandwich Generation and Working Caregivers: How HR Can Guide Employees Ca...
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The document discusses strategies that HR professionals can implement to support employees who are part of the "sandwich generation", caring for both children and aging parents. It defines the sandwich generation as middle-aged adults providing care to parents 65 or older while also raising children or financially supporting grown children. Some key challenges faced by these working caregivers include absenteeism, presenteeism, health declines, and financial stresses. The document provides examples of flexibility policies, benefits, resources, and education that employers can offer to help sandwich generation employees balance work and caregiving responsibilities.Defining the Eradication of Child Poverty in the Child Poverty Bill
The document discusses the Child Poverty Bill, which aims to eradicate child poverty in the UK within 20 years. It outlines the challenges of defining child poverty measures in legislation given limitations of existing data. Key measures included are relative low income, absolute low income, material deprivation, and persistent poverty. Significant effort was required to communicate technical definitions to stakeholders and address debates during the bill's passage through Parliament.
Professor Lynn McDonald, Middlesex University
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This research examines the stability of children's health insurance coverage using data from the Survey of Income and Program Participation (SIPP) from 1996-2005. The analysis finds:
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2) Measuring insurance at a single point in time fails to capture transitions and results in heterogeneous groups.
3) Having partial-year coverage or periods of uninsurance is associated with lower rates of physician visits compared to full-year coverage, even after accounting for individual characteristics. Policy designs should aim to minimize gaps and transitions in children's health insurance.Child related transfers and welfare
What are the welfare and macroeconomic effects of family policies? How do they depend on policy composition? I answer that questions in overlapping generations model calibrated to the US. I account for the idiosyncratic income risk, redistribution via social security, and tax and benefit system. I explicitly model child-related tax credit, child care subsidies, and child allowance. I show the expansion of the family policy yields higher welfare. The expenditure on the optimal policy accounts for approximately 3% of GDP. Even though the optimal family policy is three times bigger than the status quo policy, taxes decrease when the optimal policy is implemented. Therefore, reform is self- financing. The structure of family policy is crucial for welfare evaluation. Tax credit and child allowance generate higher welfare gains than child care.
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Key Findings and Programmatic Implications: OVC Program Evaluations in Kenya ...
Program exposure and coverage of key interventions was lower than expected based on registry data. Services targeting one domain, such as children's psychosocial well-being, had unintended effects on other domains. Exposure to multiple interventions showed additive benefits. While some programs improved children's outcomes, guardian outcomes were less consistently affected. Comprehensive HIV education, stigma reduction, and addressing guardians' psychological health and children's legal protection require more focus. Regular monitoring of coverage and participation is needed to improve program implementation and outcomes.
1RUNNING HEAD PROBLEM IDENTIFICATIONJohnston-Taylor.docx
1
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Problem Identification and Model Planning
Capella University
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In this paper, this writer, along with this writer’s project group, has identify a specific issue to focus on for our project and has plan how to use the data to examine it. We choose a problem from the scenario of the Homeless Teen Program run by the Riverbend City Community Action Center (CAC) and imply the identify problem to the linear regression model. We have decided to focus on the question/problem #6: “Is there a relationship between participation in individual mental health treatment and family tension?” (Riverbend City, 2020). It is important to learn more about teen mental health and family tension because mental health is important at every stage of life, from childhood to old age. But mental health treatment in young adult is extremely important and it can be examined as a very sensitive subject. Edidin et. al (2012) stated, youth homelessness is a growing concern in the United States. Despite the difficulty studying this particular population due to the inconsistent definitions of what it means to be homeless and a youth, the current body of research indicates disruptive family relationships, family breakdown, and abuse are all common contributing factors to youth homelessness.
According to EMC Educational Services (2015) stated data analytics lifestyle is the process used for incorporating data. It is also organized process that provides arrangement to the whole process of data analytics, which starts before the actual data is analyzed and connected. The data analytics lifestyle assist individuals to ensure there is an identified reason for collecting data, which data is available, and muse about the model using the data before collecting and analyzing the data. The lifecycle has six phases, and the project work can occur in several phases at once. The six phases are discovery, data preparation, model planning, model building, communicate results, and operationalize. Phase three of the data analytics is model planning, where the team has to determine the methods, techniques, and the workflow that tends to follow the subsequent model building phase (EMC Education Services, 2015). The best model chosen imply the identify problem is the linear regression model.
The linear regression model assumes that there is an immediate relationship between the outcome and input variables. As a group, we imply that an individual’s homelessness is can be expressed by two variables, which are family tension and mental health. Mental health and family tension is the input variables while homelessness is the outcome variable. We are focusing on the possible issue between family tension and mental health treatment, and analyze the data provided from the Homeless Teen Program scenario. This model is appropriate for this specific problem due.
1RUNNING HEAD PROBLEM IDENTIFICATIONJohnston-Taylor.docx
1
RUNNING HEAD: PROBLEM IDENTIFICATION Johnston-Taylor
Problem Identification and Model Planning
Capella University
HMSV5316: Effective Use of Analytics Human Services
In this paper, this writer, along with this writer’s project group, has identify a specific issue to focus on for our project and has plan how to use the data to examine it. We choose a problem from the scenario of the Homeless Teen Program run by the Riverbend City Community Action Center (CAC) and imply the identify problem to the linear regression model. We have decided to focus on the question/problem #6: “Is there a relationship between participation in individual mental health treatment and family tension?” (Riverbend City, 2020). It is important to learn more about teen mental health and family tension because mental health is important at every stage of life, from childhood to old age. But mental health treatment in young adult is extremely important and it can be examined as a very sensitive subject. Edidin et. al (2012) stated, youth homelessness is a growing concern in the United States. Despite the difficulty studying this particular population due to the inconsistent definitions of what it means to be homeless and a youth, the current body of research indicates disruptive family relationships, family breakdown, and abuse are all common contributing factors to youth homelessness.
According to EMC Educational Services (2015) stated data analytics lifestyle is the process used for incorporating data. It is also organized process that provides arrangement to the whole process of data analytics, which starts before the actual data is analyzed and connected. The data analytics lifestyle assist individuals to ensure there is an identified reason for collecting data, which data is available, and muse about the model using the data before collecting and analyzing the data. The lifecycle has six phases, and the project work can occur in several phases at once. The six phases are discovery, data preparation, model planning, model building, communicate results, and operationalize. Phase three of the data analytics is model planning, where the team has to determine the methods, techniques, and the workflow that tends to follow the subsequent model building phase (EMC Education Services, 2015). The best model chosen imply the identify problem is the linear regression model.
The linear regression model assumes that there is an immediate relationship between the outcome and input variables. As a group, we imply that an individual’s homelessness is can be expressed by two variables, which are family tension and mental health. Mental health and family tension is the input variables while homelessness is the outcome variable. We are focusing on the possible issue between family tension and mental health treatment, and analyze the data provided from the Homeless Teen Program scenario. This model is appropriate for this specific problem due.
Parental aspirations for children's education
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2) The study found that while the documentaries increased overall parental aspirations and investments in children's education, it did not reduce the pre-existing gender gap in aspirations and investments, which were on average lower for girls compared to boys.
3) Five years after the screenings, the positive impacts on aspirations and investments in education remained, but again the gender differences were not significantly impacted.
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3) Food support for households can reduce the probability of food insecurity by over 40% for just $0.74 per household.
5.7 From Research to Policy to Action (PPT)
The Homelessness Prevention and Rapid Re-Housing Program (HPRP) changed the way many communities think about and deliver housing services. Moving toward a more prevention-oriented approach to homelessness requires an understanding of the benefits and possible drawbacks. Recently, researchers have focused their efforts on the effectiveness of prevention initiatives. This workshop will highlight these studies and discuss the implications at the community-level.
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The Role of Welfare States in Making Global Cities Liveable: Reflections of L...
The document discusses the role of welfare states in making global cities like London liveable. It explores how global cities influence national welfare debates due to their economic power and differing social contexts. London faces special challenges as a global city, with issues like high income inequality, poverty rates, housing costs and lack of income protection that differ from the rest of the UK. While welfare services are important for London, its unique environment as a global city presents complex governance challenges for its welfare state.
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Policy transfer features prominently in the policy analysis literature, yet relatively little is known about how government officials seek to learn lessons from abroad in practice. This research, based on interviews with officials in government institutes in South Korea who were involved in a series of study visits to the United Kingdom, addresses this knowledge gap using Evans and Davies’ policy transfer network model and the recently developed notion of ‘policy tourism’. We conclude that policy tourism rarely leads directly to policy change but is a valuable part of on-going processes of policy learning.
* University of York, UK
** Yeungnam University, South Korea
Are Cultural Differences Between Nations a Barrier to Cross-National Policy L...
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Presentation by John Hudson*, Nam K. Jo** and Antonia Keung* to Second International Conference on Social Policy and Governance: Policy Learning and Policy Transfer, Hong Kong Institute of Education, Hong Kong, December 6-7 2013.
Abstract
Despite increasing attention recently paid to the role of culture within comparative welfare studies, empirical explorations of the impact of culture on social policy remain rare. One recent exception is Jo’s (2011) analysis of on an in-between level conception of culture based on the exploration of stable societal values using quantitative cross-national surveys of social values in high-income nations. In this paper we update and expand this framework by adding data from the most recent releases of the European Values Study and World Values Survey and by exploring a wider range of policy areas. Using this data along with data from international policy bodies such as the OECD we then move on to reflect how far cultural differences between nations not only explain policy differences, but may also be a barrier to cross-national policy learning.
Acknowledgements
This research is supported by ESRC award ES/J00460X/1
* = University of York, UK
** = Sungkonghoe University, South Korea
Exploring Culture and Welfare Regimes: Can the examination of cross-national ...
Exploring Culture and Welfare Regimes: can the examination of cross-national differences in societal values help us to understand differences in welfare state activity?
John Hudson*, Nam Jo** and Antonia Keung*
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Though culture is often suggested to be central to the understanding of cross-national differences in welfare state activity (Castles 1994, for instance, identified families of nations partly on this basis), there are few studies that have attempted to systematically analyse the influence of culture on welfare state types empirically. In part this is because both an absence of data and clear conceptions of culture have hampered such analyses. However, successive waves of both the European Values Survey and World Values Survey now provide us with detailed data on societal values stretching back over several decades. Moreover, recent debates about how this data might be used to identify stable societal values as a proxy measure of national culture (Jo, 2011) have provided us with the methodological and conceptual tools required to advance our understanding of the links between culture and welfare using cross-national quantitative data sets.
This paper reports on the second stage of a project that builds on these advances in order to further our understanding of the links between culture and welfare. The first stage of the project (the main results of which are summarised here) used successive waves of the EVS and WVS to identify stable societal values in a sample of 59 countries from 1981 to the present. Using principal components analysis 10 societal values were identified in this phase of the analysis. The second stage, which forms the core focus of this paper, explores how far these cross national differences in societal values can be used help us understand how culture relates to the different typologies of welfare that have been at the heart of comparative social policy analysis since the publication of Esping-Andersen's ground breaking work (1990). Using a mixture of quantitative and fuzzy set methods (Ragin, 2000), we explore whether culture can be usefully incorporated within typologies of welfare both as one key aspect differentiating welfare systems cross-nationally and as one of the causal factors underpinning the development of distinctive long run path dependent trajectories of welfare states.
Acknowledgement:
This research is supported by the UK Economic Social Research Council award ES/J00460X/1.
* = University of York, UK
** = Sungkonghoe University, South Korea
Does the Cultural Context Really Shape Welfare? A Comparative Analysis - pape...
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Presented to UK Social Policy Association Annual Conference 2013, Sheffield, July 9th
John Hudson*, Nam K. Jo* and Antonia Keung***
Abstract
Despite increasing attention recently paid to the role of culture within comparative welfare studies, empirical explorations of the impact of culture on social policy remain rare. One recent exception is Jo’s (2011) analysis of on an in-between level conception of culture based on the exploration of stable societal values using quantitative cross-national surveys of social values in high-income nations. In this paper we update and expand this framework by adding data from the most recent releases of the European Values Study and World Values Survey and by exploring a wider range of policy areas. In so doing, we address the underlining theoretical question of whether the cultural context really shapes welfare policies and conclude that there is strong evidence to support the ‘culture matters’ thesis.
Acknowledgements
This research is supported by ESRC award ES/J00460X/1
Author Contact Details
* Department of Social Policy and Social Work, University of York, UK. John Hudson: john.hudson@york.ac.uk.
** Department of Social Welfare, SungKongHoe University, South Korea. Nam K. Jo: namk.jo@skhu.ac.kr
*** Department of Social Policy and Social Work, University of York, UK. Antonia Keung: antonia.keung@york.ac.uk.
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New Brunswick, a picturesque province in eastern Canada, offers a plethora of unique and charming places to stay for every kind of traveler. From the historic allure of Fredericton and the vibrant culture of Saint John to the natural beauty of Fundy National Park and the serene coastal towns like St. Andrews by-the-Sea, there's something for everyone. Whether you prefer luxury resorts, cozy inns, rustic lodges, or budget-friendly options, the best places to stay in New Brunswick ensure a memorable stay, allowing you to fully immerse yourself in the province's rich history, stunning landscapes, and warm hospitality.
https://www.mmanor.ca/blog/best-5-bed-and-breakfast-new-brunswick-canada
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- 1. Comparative Social Structures and Welfare Week 8 Comparing Welfare Inputs - Beyond Spending
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