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The Individuals with Disabilities Education Act authorizes states to create early intervention (EI) programming to provide developmental and therapeutic services to infants and toddlers with a developmental condition; EI programs are mandated to report on child and family outcomes for purposes of accountability and quality improvement. For both purposes, there is critical need for research evidence on the adequacy of EI services. The researchers for this study partnered with a large urban EI program in Colorado that had recently transitioned to electronic data capture and was implementing a statewide initiative to facilitate function-focused care with individual families and paired collected electronic patient-reported outcomes (e-PRO) data with EI administrative data on child and family characteristics and service use to more fully examine EI service adequacy relative to patient-important outcomes. This study collected information from Young Children's Participation and Environment Measure (YC-PEM e-PRO) on home, environment, and community participation, involvement, and desired change. Measurements were also collected from the Pediatric Evaluation of Disability Inventory Computer Adaptive Test (PEDI-CAT e-PRO) on mobility, social cognitive, and daily activities domains. The Child Outcomes Summary (COS) was used to capture functional performance related to having positive social relationships, acquiring and using knowledge and skills, and taking appropriate action to meet needs. Early Intervention Service Use measured EI intensity, whether child received specific services including physical therapy (PT), occupational therapy (OT), speech therapy (ST), psychology, or developmental intervention (DI), and the total number of service hours received within each discipline. Demographic variables include reasons child received EI services, number of developmental delay conditions, age, race, and ethnicity; as well as caregiver's education, employment, number of children at home, income, and insurance type.,The first aim of this project involves using the data that early intervention (EI) programs currently capture electronically to examine EI service adequacy. The second aim of this project involves piloting the feasibility, acceptability, and value of implementing two psychometrically sound electronic patient-reported outcomes (e-PROs) within an EI workflow: 1) the Pediatric Evaluation of Disability Inventory - Computer Adaptive Test (PEDI-CAT e-PRO), evaluating children's discrete task performance; and 2) the Young Children's Participation and Environment Measure (YC-PEM e-PRO), evaluating the child's participation in valued home and community activities.,Researchers initially met with 22 early intervention (EI) service coordinators to finalize recruitment processes and materials. Service coordinators then approached eligible caregivers on their caseloads, when the child was within a month of their next annual review of progress. Eligible and interested caregivers were directed to a study website to confirm their study eligibility per the inclusion criteria. Caregivers who provided informed consent online proceeded to complete an online demographic questionnaire, followed by an electronic patient-reported outcome (e-PRO) assessment of their child's participation in home and community activities. After completion of the e-PRO assessment, participants were asked to indicate their availability for having a second e-PRO administered to them via iPad and over the telephone. Once they confirmed their availability, each caregiver received immediate access to an online report summarizing their responses to share with their child's EI team.,ICPSR data undergo a confidentiality review and are altered when necessary to limit the risk of disclosure. ICPSR also routinely creates ready-to-go data files along with setups in the major statistical software formats as well as standard codebooks to accompany the data. In addition to these procedures, ICPSR performed the following processing steps for this data collection: Checked for undocumented or out-of-range codes..,Presence of Common Scales: Young Children's Participation and Environment Measure (YC-PEM e-PRO); Pediatric Evaluation of Disability Inventory Computer Adaptive Test (PEDI-CAT e-PRO); Child Outcome Summary (COS);,Datasets: DS1: Early Intervention Colorado (EI-CO) Participant Characteristics, Service Use, and Patient-Reported Outcomes, Colorado, 2017-2018, Public-Use Data,audiovisual touch-screen computer-assisted self interview (AVT-CASI),record abstracts,web-based survey,Caregivers that were at least 18 years old; could read, write, and speak English or Spanish; had internet access; and had a child between 0-3 years old who was deemed early intervention service eligible for at least 3 months.,A total of 163 families were enrolled in the study between March 2017 and August 2018, with a final enrollment of 149 (139 English, 10 Spanish). Each caregiver confirmed his or her eligibility online by verifying that they fit the study inclusion criteria. For the Pediatric Evaluation of Disability Inventory - Computer Adaptive Test (PEDI-CAT e-PRO) measurement, 8 of the 139 families declined consent and 16 were lost to follow-up. Consequently, 115 families completed the PEDI-CAT e-PRO. Similarly, Child Outcomes Summary (COS) scores are not recorded for all early intervention (EI) enrolled children in this dataset. This is because the EI program did not routinely capture COS data electronically during the entire study period. The existing dataset is therefore available as either the whole sample or as the sub-sample of children with complete PEDI-CAT e-PRO and COS information.,
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In the United States, ambient air quality is regulated through National Ambient Air Quality standards (NAAQS). Enforcement of these standards is delegated to state and sub-state regulators who are also tasked with designing their own monitoring networks for ambient pollution. Past work has found evidence consistent with strategic behavior: local regulators strategically avoid pollution hotspots when siting monitors. This paper assesses whether income and race have historically played a role in monitor siting decisions.
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We examine the long-term impacts of California's state-based financial aid by tracking educational and labor force outcomes for up to 14 years after high school graduation. We identify program impacts by exploiting variation in eligibility rules using GPA and family income cutoffs that are ex ante unknown to applicants. Aid eligibility increases undergraduate and graduate degree completion, and for some subgroups, raises longer-run annual earnings and the likelihood that young adults reside in California. These findings suggest that the net cost of financial aid programs may frequently be overstated, though our results are too imprecise to provide exact cost-benefit estimates.
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  • Dataset
We present a framework for understanding the effects of automation and other types of technological changes on labor demand, and use it to interpret changes in US employment over the recent past. At the center of our framework is the allocation of tasks to capital and labor—the task content of production. Automation, which enables capital to replace labor in tasks it was previously engaged in, shifts the task content of production against labor because of a displacement effect. As a result, automation always reduces the labor share in value added and may reduce labor demand even as it raises productivity. The effects of automation are counterbalanced by the creation of new tasks in which labor has a comparative advantage. The introduction of new tasks changes the task content of production in favor of labor because of a reinstatement effect, and always raises the labor share and labor demand. We show how the role of changes in the task content of production—due to automation and new tasks—can be inferred from industry-level data. Our empirical decomposition suggests that the slower growth of employment over the last three decades is accounted for by an acceleration in the displacement effect, especially in manufacturing, a weaker reinstatement effect, and slower growth of productivity than in previous decades.
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The Cora data contains bibliographic records of machine learning papers that have been manually clustered into groups that refer to the same publication. Originally, Cora was prepared by Andrew McCallum, and his versions of this data set are available on his Data web page. The data is also hosted here. Note that various versions of the Cora data set have been used by many publications in record linkage and entity resolution over the years.
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These data are being released in BETA version to facilitate early access to the study for research purposes. This collection has not been fully processed by ICPSR at this time; the original materials provided by the principal investigator were minimally processed and converted to other file types for ease of use. As the study is further processed and given enhanced features by ICPSR, users will be able to access the updated versions of the study. Please report any data errors or problems to user support and we will work with you to resolve any data related issues. The Chinese Longitudinal Healthy Longevity Survey (CLHLS) provides information on health status and quality of life of the elderly aged 65 and older in 22 provinces of China in the period 2002 to 2005. The study was conducted to shed light on the determinants of healthy human longevity and advanced age mortality. To this end, data were collected on a large percentage of the oldest population, including centenarian and nonagenarian; the CLHLS provides information on the health, socioeconomic characteristics, family, lifestyle, and demographic profile of this aged population. Data are provided on respondents' health conditions, daily functioning, self-perceptions of health status and quality of life, life satisfaction, mental attitude, and feelings about aging. Respondents were asked about their diet and nutrition, use of medical services, and drinking and smoking habits, including how long ago they quit either or both. They were also asked about their physical activities, reading habits, television viewing, and religious activities, and were tested for motor skills, memory, and visual functioning. In order to ascertain their current state of health, respondents were asked if they suffered from such health conditions as hypertension, diabetes, heart disease, stroke, cancer, emphysema, asthma, tuberculosis, cataracts, glaucoma, gastric or duodenal ulcer, arthritis, Parkinson's disease, bedsores, or other chronic diseases. Respondents were further queried about assistance with bathing, dressing, toileting, or feeding, and who provided help in times of illness. Other questions focused on siblings, parents, and children, the frequency of family visits, and the distance lived from each other. Demographic and background variables include age, sex, ethnicity, place of birth, marital history and status, history of childbirth, living arrangements, education, main occupation before age 60, and sources of financial support.,The Chinese Longitudinal Healthy Longevity Study (CLHLS) collected the elderly participants' adult child's information, including level of education, income and occupation, marriage and family, kinship network, intergenerational interaction and the change of social values. The survey aims to explore the impact of adult child's status on the elderly's health and their support arrangement.,Face-to-face interviews were conducted using the same questionnaires used in the other study sites of the Chinese Longitudinal Healthy Longevity Survey.,Presence of Common Scales: The following scales were used in this collection: Mini-Mental State Examination (MMSE) and Activities of Daily Living (ADL).,Response Rates: The response rate was 88 percent.,Datasets: DS1: Dataset,Chinese Longitudinal Healthy Longevity Survey (CLHLS) Series,computer-assisted self interview (CASI),cognitive assessment test,face-to-face interview,self-enumerated questionnaire,The elderly population aged 65 and older and their adult-children aged 35-60 in the counties and cities of 22 provinces in China during the period 2002-2005. Smallest Geographic Unit: Province,All respondents from the 9 province areas in China who agreed to participate in the study were interviewed. The 9 province areas are as follows: Beijing; Liaoning; Shanghai; Jiangsu; Zhejiang; Fujian; Shandong; Guangdong; Guangxi; During the sampling process of CLHLS in 2002, either the single surviving child, or a randomly selected surviving child of the elderly participant acted as a valid sample. More specifically, for an elderly respondent with two children, if the birth month of the elderly falls into the first half-year (January to June), the elder child was selected as a valid sample, otherwise, the younger child was selected. One year is equally divided into three parts for the elderly with three surviving children. The child whose rank by age corresponds to the sequence of the division where the parent's birth month lies was selected as a valid sample. If the parent has four or more children, one year will be equally divided into four parts: the first three parts correspond to the three elder children, and the last part corresponds to the youngest child. The adult-child samples in 2005 came from the samples of adult-child dataset in 2002 with no newly added participants.,
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We use a choice experiment to examine public support for minimum wages. We first elicit respondents' moral assessment of two labor market systems: one with a minimum wage and one without. Then, we present four pairs of hypothetical employment outcomes and ask respondents to "vote." Our estimates suggest that the average respondent requires a 4.65 percentage point reduction in unemployment before they would support a system without a minimum wage. We also find that equity matters; respondents are 11.1 percentage points less likely to support a minimum wage if it disproportionately affects minorities and females.
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This collection consists of a repeated panel survey that explored attitudes and behaviors related to the emerging Zika virus in 2016-2017. The respondents consisted of women of child-bearing age, ages 18-45, residing in the United States. Three waves of data collection were conducted between July 25, 2016 and Dec 22, 2017. Demographic variables include questions related to age, race, highest level of education, household income, and political affiliation.,This study was designed to examine how one particularly high-risk population, women of child-bearing age, responded to an evolving threat.,Datasets: DS1: Dataset,web-based survey,Women of child-bearing age, ages 18-45, residing in the United States. Smallest Geographic Unit: Region,A convenience sample of women of child-bearing age was drawn from two sources: a representative survey sample of US residents (n=75 among 355 eligible to join the panel), and online national sampling frame (n=165 women). The representative survey sample consisted of women of child-bearing age who were US residents and who had participated in the baseline survey of a related study about perceptions of the Zika virus, funded by the National Science Foundation (grant number 1638545). This sample was constructed using a single-stage, random-digital-dialing sample of landline telephone households and randomly-generated cell phone numbers. The sample frame included an oversampling of women of child-bearing age (18-45) living in the states of Florida, Alabama, Mississippi, Louisiana, and Texas. These participants were supplemented with women of child-bearing age recruited from an online national sampling frame coordinated by Qualtrics Panels. Among the 240 sampled women, 226 completed the initial baseline survey.,
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The Pittsburgh Youth Study (PYS) is part of the larger "Program of Research on the Causes and Correlates of Delinquency" initiated by the Office of Juvenile Justice and Delinquency Prevention in 1986. PYS aims to document the development of antisocial and delinquent behavior from childhood to early adulthood, the risk factors that impinge on that development, and help seeking and service provision of boys' behavior problems. The study also focuses on boys' development of alcohol and drug use, and internalizing problems. PYS consists of three cohorts of boys who were in the first, fourth, and seventh grades in Pittsburgh, Pennsylvania public schools during the 1987-1988 academic year (called the youngest, middle, and oldest cohorts, respectively). Using a screening risk score that measured each boy's antisocial behavior, boys identified at the top 30 percent within each grade cohort on the screening risk measure (n=~250), as well as an equal number of boys randomly selected from the remainder (n=~250), were selected for follow-up. Consequently, the final sample for the study consisted of 1,517 total students selected for follow-up. 506 of these students were in the oldest sample, 508 were in the middle sample, and 503 were in the youngest sample. Assessments were conducted semiannually and then annually using multiple informants (i.e., boys, parents, and teachers) between 1987 and 2010. The youngest cohort was assessed from ages 6-19 and again at ages 25 and 28. The middle cohort was assessed from ages 9-13 and again at age 23. The oldest cohort was assessed from ages 13-25, with an additional assessment at age 35. Information has been collected on a broad range of risk and protective factors across multiple domains (e.g., individual, family, peer, school, and neighborhood). Measures of conduct problems, substance use/abuse, criminal behavior, mental health problems have been collected. This collection contains data and syntax files for demographic constructs. The datasets include constructs on repeated grade status, demographic information of participants, participants' biological mother, biological father, female caretaker, and male caretaker, change of caretaker since last phase, number of family members and other adults or children in the home, family structure, followup participation by youth, caretaker, and teacher, and housing characteristics. The demographic constructs were created by using the PYS raw data. The raw data are available at ICPSR in the following studies: Pittsburgh Youth Study Youngest Sample (1987 - 2001) [Pittsburgh, Pennsylvania], Pittsburgh Youth Study Middle Sample (1987 - 1991) [Pittsburgh, Pennsylvania], and Pittsburgh Youth Study Oldest Sample (1987 - 2000) [Pittsburgh, Pennsylvania].,The Pittsburgh Youth Study (PYS) is a part of the Program of Research on the Causes and Correlates of Delinquency (Causes and Correlates), initiated in 1986 by the United States Office of Juvenile Justice and Delinquency Prevention. Causes and Correlates is designed to improve the understanding of serious delinquency, violence, and drug use by examining how youth develop within the context of family, school, peers, and community. Specifically, PYS aims to document the development of antisocial and delinquent behavior from childhood to early adulthood, the risk factors that impinge on that development, and help seeking and service provision of boys' behavior problems. It also focuses on boys' development of alcohol and drug use, and internalizing problems. Additionally, the study provides an excellent real-life laboratory for advancing and testing hypothesized developmental pathways.,Variables for demographic constructs include constructs on repeated grade status, demographic information of participants, participants' biological mother, biological father, female caretaker, and male caretaker, change of caretaker since last phase, number of family members and other adults or children in the home, family structure, followup participation by youth, caretaker, and teacher, and housing characteristics.,ICPSR data undergo a confidentiality review and are altered when necessary to limit the risk of disclosure. ICPSR also routinely creates ready-to-go data files along with setups in the major statistical software formats as well as standard codebooks to accompany the data. In addition to these procedures, ICPSR performed the following processing steps for this data collection: Checked for undocumented or out-of-range codes..,Response Rates: Participant retention for the Pittsburgh Youth Study has historically been high (mean=91 percent), with 82 percent of living participants completing the most recent interview conducted in 2010.,Datasets: DS0: Study-Level Files DS1: Phase A All Samples Participant's Biological Parents Constructs - A3XBIOFM DS2: Phase A All Samples SES, Unemployment, Education, Income, Public Assistance, and Marital Status of Caretakers Constructs - A3XDEMO DS3: Phase A All Samples Family Structure and People Living in the Home Constructs - A3XFAMST DS4: Phase A All Samples Housing Quality, Size of House, and Crowded Home Constructs - A3XHOUSQ DS5: Phase AA Youngest Sample Biological Father Living Status and Biological Mother Living Status Constructs - AAYBIOFM DS6: Phase AA Youngest Sample SES, Employment, Education, Income, and Public Assistance of Participants Constructs - AAYDEMO DS7: Phase AA Youngest Sample Family Structure and People Living in the Home Constructs - AAYFAMST DS8: Phase AA Youngest Sample Followup Participation Constructs - AAYFOLLO DS9: Phase AA Youngest Sample Housing Quality Construct - AAYHOUSQ DS10: Phase B All Samples Repeated Grade Construct - B3XAGERP DS11: Phase B All Samples Participant's Biological Parents Constructs - B3XBIOFM DS12: Phase B All Samples SES, Employment, Education, and Marital Status of Caretakers Constructs - B3XDEMO DS13: Phase B All Samples Family Structure and People Living in the Home, Siblings, and Changes of Caretaker Constructs - B3XFAMST DS14: Phase B All Samples Followup Participation Constructs - B3XFOLLO DS15: Phase B All Samples Housing Quality Construct - B3XHOUSQ DS16: Phase C All Samples Participant's Biological Parents Constructs - C3XBIOFM DS17: Phase C All Samples SES, Employment, Education, Income, Public Assistance, and Marital Status of Caretakers Constructs - C3XDEMO DS18: Phase C All Samples Family Structure and People Living in the Home, Siblings, and Changes of Caretaker Constructs - C3XFAMST DS19: Phase C All Samples Followup Participation Constructs - C3XFOLLO DS20: Phase C All Samples Housing Quality, Size of House, and Crowded Home Constructs - C3XHOUSQ DS21: Phase D All Samples Repeated Grade Construct - D3XAGERP DS22: Phase D All Samples Participant's Biological Parents Constructs - D3XBIOFM DS23: Phase D All Samples SES, Employment, Education, and Marital Status of Caretakers Constructs - D3XDEMO DS24: Phase D All Samples Family Structure and People Living in the Home, Siblings, and Changes of Caretaker Constructs - D3XFAMST DS25: Phase D All Samples Followup Participation Constructs - D3XFOLLO DS26: Phase D All Samples Housing Quality Construct - D3XHOUSQ DS27: Phase E Oldest Sample Repeated Grade Construct - E3OAGERP DS28: Phase E All Samples Participant's Biological Parents Constructs - E3XBIOFM DS29: Phase E All Samples SES, Employment, Education, Income, Public Assistance, and Marital Status of Caretakers Constructs - E3XDEMO DS30: Phase E All Samples Family Structure and People Living in the Home, Siblings, and Changes of Caretaker Constructs - E3XFAMST DS31: Phase E All Samples Followup Participation Constructs - E3XFOLLO DS32: Phase E All Samples Housing Quality, Size of House, and Crowded Home Constructs - E3XHOUSQ DS33: Phase F Youngest and Middle Samples Repeated Grade Construct - F3NAGERP DS34: Phase F Youngest and Middle Samples Participant's Biological Parents Constructs - F3NBIOFM DS35: Phase F Youngest and Middle Samples SES, Employment, Education, and Marital Status of Caretakers Constructs - F3NDEMO DS36: Phase F Youngest and Middle Samples Family Structure and People Living in the Home, Siblings, and Changes of Caretaker Constructs - F3NFAMST DS37: Phase F Youngest and Middle Samples Followup Participation Constructs - F3NFOLLO DS38: Phase F Youngest and Middle Samples Housing Quality Construct - F3NHOUSQ DS39: Phase G Oldest Sample Repeated Grade Construct - G3OAGERP DS40: Phase G Youngest and Oldest Samples Participant's Biological Parents Constructs - G3WBIOFM DS41: Phase G Youngest and Oldest Samples SES, Employment, Education, Income, Public Assistance, and Marital Status of Caretakers Constructs - G3WDEMO DS42: Phase G Youngest and Oldest Samples Family Structure and People Living in the Home, Siblings, and Changes of Caretaker - G3WFAMST DS43: Phase G Youngest and Oldest Samples Followup Participation Constructs - G3WFOLLO DS44: Phase G Youngest and Oldest Samples Housing Quality, Size of House, and Crowded Home Constructs - G3WHOUSQ DS45: Phase H Youngest Sample Repeated Grade Construct - H3YAGERP DS46: Phase H Youngest Sample Participant's Biological Parents Constructs - H3YBIOFM DS47: Phase H Youngest Sample SES, Employment, Education, and Marital Status of Caretakers Constructs - H3YDEMO DS48: Phase H Youngest Sample Family Structure and People Living in the Home, Siblings, and Changes of Caretaker Constructs - H3YFAMST DS49: Phase H Youngest Sample Followup Participation Constructs - H3YFOLLO DS50: Phase H Youngest Sample Housing Quality Construct - H3YHOUSQ DS51: Phase I Oldest Sample Repeated Grade Construct - I3OAGERP DS52: Phase I Oldest Sample Participant's Biological Parents Constructs - I3OBIOFM DS53: Phase I Oldest Sample SES, Employment, Education, Income, Public Assistance, and Marital Status of Caretakers, and the Income of Participants - I3ODEMO DS54: Phase I Oldest Sample Family Structure and People Living in the Home, Siblings, and Changes of Caretaker Constructs - I3OFAMST DS55: Phase I Oldest Sample Followup Participation Constructs - I3OFOLLO DS56: Phase I Oldest Sample Housing Quality, Size of House, and Crowded Home Constructs - I3OHOUSQ DS57: Phase J Youngest Sample Repeated Grade Construct - J3YAGERP DS58: Phase J Youngest Sample Participant's Biological Parents Constructs - J3YBIOFM DS59: Phase J Youngest Sample SES, Employment, Education, Income, Public Assistance, and Marital Status of Caretakers Constructs - J3YDEMO DS60: Phase J Youngest Sample Family Structure and People Living in the Home, Siblings, and Changes of Caretaker Constructs - J3YFAMST DS61: Phase J Youngest Sample Followup Participation Constructs - J3YFOLLO DS62: Phase J Youngest Sample Housing Quality, Size of House, and Crowded Home Constructs - J3YHOUSQ DS63: Phase K Oldest Sample Biological Father Living Status and Biological Mother Living Status Constructs - K3OBIOFM DS64: Phase K Oldest Sample SES, Employment, Education, Income, and Public Assistance of Participants Constructs - K3ODEMO DS65: Phase K Oldest Sample Family Structure and People Living in the Home Constructs - K3OFAMST DS66: Phase K Oldest Sample Followup Participation Construct - K3OFOLLO DS67: Phase L Youngest Sample Repeated Grade Construct - L3YAGERP DS68: Phase L Youngest Sample Participant's Biological Parents Constructs - L3YBIOFM DS69: Phase L Youngest Sample SES, Employment, Education, Income, Public Assistance, and Marital Status of Caretakers - L3YDEMO DS70: Phase L Youngest Sample Family Structure and People Living in the Home, Siblings, and Changes of Caretaker Constructs - L3YFAMST DS71: Phase L Youngest Sample Followup Participation Constructs - L3YFOLLO DS72: Phase L Youngest Sample Housing Quality, Size of House, and Crowded Home Constructs - L3YHOUSQ DS73: Phase M Oldest Sample Biological Father Living Status and Biological Mother Living Status Constructs - M3OBIOFM DS74: Phase M Oldest Sample SES, Employment, Education, Income, and Public Assistance of Participants Constructs - M3ODEMO DS75: Phase M Oldest Sample Family Structure and People Living in the Home Constructs - M3OFAMST DS76: Phase M Oldest Sample Followup Participation Constructs - M3OFOLLO DS77: Phase N Youngest Sample Repeated Grade Construct - N3YAGERP DS78: Phase N Youngest Sample Participant's Biological Parents Constructs - N3YBIOFM DS79: Phase N Youngest Sample SES, Employment, Education, Income, Public Assistance, and Marital Status of Caretakers Constructs - N3YDEMO DS80: Phase N Youngest Sample Family Structure and People Living in the Home, Siblings, and Changes of Caretaker Constructs - N3YFAMST DS81: Phase N Youngest Sample Followup Participation Constructs - N3YFOLLO DS82: Phase N Youngest Sample Housing Quality, Size of House, and Crowded Home Constructs - N3YHOUSQ DS83: Phase O Oldest Sample Biological Father Living Status and Biological Mother Living Status Constructs - O3OBIOFM DS84: Phase O Oldest Sample SES, Employment, Education, Income, and Public Assistance of Participants Constructs - O3ODEMO DS85: Phase O Oldest Sample Family Structure and People Living in the Home Constructs - O3OFAMST DS86: Phase O Oldest Sample Followup Participation Constructs - O3OFOLLO DS87: Phase P Youngest Sample Repeated Grade Construct - P3YAGERP DS88: Phase P Youngest Sample Participant's Biological Parents Constructs - P3YBIOFM DS89: Phase P Youngest Sample SES, Employment, Education, Income, Public Assistance, and Marital Status of Caretakers and Employment and Income of the Participant Constructs - P3YDEMO DS90: Phase P Youngest Sample Family Structure and People Living in the Home, Siblings, and Changes of Caretaker Constructs - P3YFAMST DS91: Phase P Youngest Sample Followup Participation Constructs - P3YFOLLO DS92: Phase P Youngest Sample Housing Quality, Size of House, and Crowded Home Constructs - P3YHOUSQ DS93: Phase Q Oldest Sample Biological Father Living Status and Biological Mother Living Status constructs - Q3OBIOFM DS94: Phase Q Oldest Sample SES, Employment, Education, Income, and Public Assistance of Participants Constructs - Q3ODEMO DS95: Phase Q Oldest Sample Family Structure and People Living in the Home Constructs - Q3OFAMST DS96: Phase Q Oldest Sample Followup Participation Constructs - Q3OFOLLO DS97: Phase R Youngest Sample Repeated Grade Construct - R3YAGERP DS98: Phase R Youngest Sample Participant's Biological Parents Constructs - R3YBIOFM DS99: Phase R Youngest Sample SES, Employment, Education, Income, Public Assistance, and Marital Status of Caretakers and Employment and Income of the Participant Constructs - R3YDEMO DS100: Phase R Youngest Sample Family Structure and People Living in the Home, Siblings, and Changes of Caretaker Constructs - R3YFAMST DS101: Phase R Youngest Sample Followup Participation Constructs - R3YFOLLO DS102: Phase R Youngest Sample Housing Quality, Size of House, and Crowded Home Constructs - R3YHOUSQ DS103: Phase S All Samples On-Off Age For Grade Construct - S3XAGERP DS104: Phase S All Samples Participant's Biological Parents Constructs - S3XBIOFM DS105: Phase S All Samples SES, Education, Race/Ethnicity, and Marital Status of Caretakers, and Race/Ethnicity of Participant Constructs - S3XDEMO DS106: Phase S All Samples Family Structure and People Living in the Home and Siblings Constructs - S3XFAMST DS107: Phase SS Oldest Sample Biological Father Living Status and Biological Mother Living Status Constructs - SSOBIOFM DS108: Phase SS Oldest Sample SES, Employment, Education, Income, and Public Assistance of Participants Constructs - SSODEMO DS109: Phase SS Oldest Sample Family Structure and People Living in the Home Constructs - SSOFAMST DS110: Phase SS Oldest Sample Followup Participation Constructs - SSOFOLLO DS111: Phase T Youngest Sample Participant's Biological Parents Constructs - T3YBIOFM DS112: Phase T Youngest Sample SES, Employment, Education, Income, Public Assistance, and Marital Status of Caretakers and Employment and Income of the Participant Constructs - T3YDEMO DS113: Phase T Youngest Sample Family Structure and People Living in the Home, Siblings, and Changes of Caretaker Constructs - T3YFAMST DS114: Phase T Youngest Sample Followup Participation Constructs - T3YFOLLO DS115: Phase T Youngest Sample Housing Quality, Size of House, and Crowded Home Constructs - T3YHOUSQ DS116: Phase U Oldest Sample Biological Father Living Status and Biological Mother Living Status Constructs - U3OBIOFM DS117: Phase U Oldest Sample SES, Employment, Education, Income, and Public Assistance of Participants Constructs - U3ODEMO DS118: Phase U Oldest Sample Family Structure and People Living in the Home Constructs - U3OFAMST DS119: Phase U Oldest Sample Followup Participation Constructs - U3OFOLLO DS120: Phase V Youngest Sample Biological Father Living Status and Biological Mother Living Status Constructs - V3YBIOFM DS121: Phase V Youngest Sample SES, Employment, Education, Income, and Public Assistance of Participants Constructs - V3YDEMO DS122: Phase V Youngest Sample Family Structure and People Living in the Home Constructs - V3YFAMST DS123: Phase V Youngest Sample Followup Participation Constructs - V3YFOLLO DS124: Phase V Youngest Sample Housing Quality Construct - V3YHOUSQ DS125: Phase W Oldest Sample Biological Father Living Status and Biological Mother Living Status Constructs - W3OBIOFM DS126: Phase W Oldest Sample SES, Employment, Education, Income, and Public Assistance of Participants Constructs - W3ODEMO DS127: Phase W Oldest Sample Family Structure and People Living in the Home Constructs - W3OFAMST DS128: Phase W Oldest Sample Followup Participation Constructs - W3OFOLLO DS129: Phase W Oldest Sample Housing Quality Construct - W3OHOUSQ DS130: Phase Y Youngest Sample Biological Father Living Status and Biological Mother Living Status Constructs - Y3YBIOFM DS131: Phase Y Youngest Sample SES, Employment, Education, Income, and Public Assistance of Participants Constructs - Y3YDEMO DS132: Phase Y Youngest Sample Family Structure and People Living in the Home Constructs - Y3YFAMST DS133: Phase Y Youngest Sample Followup Participation Constructs - Y3YFOLLO DS134: Phase Y Youngest Sample Housing Quality Construct - Y3YHOUSQ DS135: Phase Z Oldest Sample Biological Father Living Status and Biological Mother Living Status Constructs - ZZOBIOFM DS136: Phase Z Oldest Sample SES, Employment, Education, Income, and Public Assistance of Participants Constructs - ZZODEMO DS137: Phase Z Oldest Sample Family Structure and People Living in the Home Constructs - ZZOFAMST DS138: Phase Z Oldest Sample Followup Participation Constructs - ZZOFOLLO DS139: Phase Z Oldest Sample Housing Quality Construct - ZZOHOUSQ,Program of Research on the Causes and Correlates of Delinquency Series,face-to-face interview,mail questionnaire,paper and pencil interview (PAPI),self-enumerated questionnaire,on-site questionnaire,telephone interview,This study collection contains those students, and their parents, who were in first, fourth, or seventh grade during the 1987-1988 school year.,The initial sample for the Pittsburgh Youth Study (PYS) was selected with the assistance of the Pittsburgh Board of Education in 1987. PYS researchers started out with comprehensive public school lists of the enrollment of 1,631, 1,432, and 1,419 male students in grades 1, 4, and 7 during the 1987-1988 school year respectively. From these lists, researchers randomly selected about 1,100 boys in each of the three grades to be contacted (1,165, 1,146, and 1,125 in grades 1, 4, and 7, respectively). However, a number of the children had moved out of the school district, proved to be girls, or were of incorrect age and were therefore not eligible participants. Eventually, 1,006, 1,004, and 998 families with eligible boys in grades 1, 4, and 7, respectively, were contacted. Boys in grade 1 became the "youngest" sample, boys in grade 4 became the "middle" sample, and boys in grade 7 became the "oldest" sample. From this contact, 84.6 percent, 86.3 percent, and 83.9 percent of the eligible boys in the youngest, middle, and oldest samples respectively chose to participate in PYS. In order to increase the number of high-risk males in the sample, researchers used a screening assessment on a subset of the boys during the first phase of the study, Phase S. Risk scores from this screening assessment measured each boy's antisocial behavior using parent, teacher, and self-report instruments. Within each grade-based sample, boys identified at the top 30 percent on the screening risk measure (n=~250), as well as an equal number of boys randomly selected from the remaining 70 percent (n=~250), were selected for follow-up in subsequent phases (Phase A- Phase DD). This resulted in the final samples of 503, 508, and 506 boys in grades 1, 4, and 7, respectively, who together with their parent were to be followed up. The youngest sample (N=503) and the oldest sample (N=506) have been assessed continuously since 1987, while the middle sample (N=508) was only assessed seven times from ages 10-13. Assessments of each of the cohorts were carried out initially half-yearly, and later yearly. When the assessment periods switched from six months to one year, the youngest sample was interviewed every spring and the oldest sample every fall. Each phase letter still represents a six-month period. Thus, all the phases from H through AA have data for only one sample.,
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I characterize the optimal financial regulation policy in an economy where financial intermediaries trade capital assets on behalf of households, but must retain an equity stake to align incentives. Financial regulation is necessary because intermediaries cannot be excluded from privately trading in capital markets. They don't internalize that high asset prices force everyone to bear more risk. The socially optimal allocation can be implemented with a tax on asset holdings. I derive a sufficient statistic for the externality in terms of observable variables, valid for heterogeneous intermediaries and asset classes, and arbitrary aggregate shocks. I use market data on leverage and volatility of intermediaries' equity to measure the externality, which co-moves with the business cycle.
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