WWW.DISSERTATION.XLIBX.INFO
FREE ELECTRONIC LIBRARY - Dissertations, online materials
 
<< HOME
CONTACTS



Pages:     | 1 |   ...   | 9 | 10 || 12 | 13 |

«THE EFFECT OF SCHOOL FINANCE REFORMS ON THE DISTRIBUTION OF SPENDING, ACADEMIC ACHIEVEMENT, AND ADULT OUTCOMES C. Kirabo Jackson Rucker Johnson ...»

-- [ Page 11 ] --

Model: These plots present the estimated coefficients of a regression on per-pupil spending at the district level on year fixed effects, district fixed effects, and the percentile group of the district in the state distribution of median income interacted with a full set of event time indicator variables from 10 years prior to 19 years after reforms (for equity based court-mandated reforms, adequacy based court-mandated reforms, and legislative reforms simultaneously). Standard errors are adjusted for clustering at the state level.  

–  –  –

  Data: The sample includes all school districts in the United States between the years of 1967 and 2010 (unless stated otherwise). The sample is made up of 483,047 district-year observations.

Model: These plots present the estimated coefficients of a regression on per-pupil spending at the district level on year fixed effects, district fixed effects, and the percentile group of the district in the state distribution of median income interacted with a full set of event-time indicator variables from 10 years prior to 19 years after reforms (for court-mandated reforms and legislative reforms simultaneously). Standard errors are adjusted for clustering at the state level.           

–  –  –

  Data: The sample includes all school districts in the United States between the years of 1967 and 2010 (unless stated otherwise). The sample is made up of 483,047 district-year observations.

Model: These plots present the estimated coefficients of a regression on per-pupil spending at the district level on year fixed effects, district fixed effects, and the percentile group of the district in the state distribution of median income interacted with a full set of event-time indicator variables from 10 years prior to 19 years after reforms (for reforms that impose spending limits and reward for effort plans simultaneously). Standard errors are adjusted for clustering at the state level.    

–  –  –

Data: The sample includes all school districts in the United States between the years of 1967 and 2010 (unless stated otherwise). The sample is made up of 483,047 district-year observations.

Model: These plots present the estimated coefficients of a regression on per-pupil spending at the district level on year fixed effects, district fixed effects, and the percentile group of the district in the state distribution of median income interacted with a full set of event-time indicator variables from 10 years prior to 19 years after reforms (for reforms that impose spending limits and reward for effort plans simultaneously). Standard errors are adjusted for clustering at the state level.    

–  –  –

Data: The sample includes all school districts in the United States between the years of 1967 and 2010 (unless stated otherwise). The sample is made up of 483,047 district-year observations.  Model: These plots present the estimated coefficients of a regression on per-pupil spending at the district level on year fixed effects, district fixed effects, and the percentile group of the district in the state distribution of median income interacted with a full set of event-time indicator variables from 10 years prior to 19 years after reforms (for equalization plans, foundation plans and flat grant plans, simultaneously). Standard errors are adjusted for clustering at the state level.              

–  –  –

.3.3.2.2.1.1 0 0

–  –  –

Data: PSID geocode Data (1968-2011), matched with childhood school and neighborhood characteristics. Analysis sample includes all PSID individuals born 1955-1985, followed into adulthood through 2011, (N=15,353 individuals (9,035 poor kids; 6,318 non-poor kids) from 1,409 school districts (1,031 child counties, 50 states).

Models: Results are based on non-parametric event-study models that include: school district fixed effects, race-specific year of birth fixed effects, race*census division-specific linear cohort trends, controls at the county-level for the timing of school desegregation*race, hospital desegregation*race, roll-out of "War on Poverty" & related safety-net programs (community health centers, county expenditures on Head Start (at age 4), food stamps, medicaid, AFDC, UI, Title-I (average during childhood years), timing of state-funded Kindergarten), controls for 1960 county characteristics (poverty rate, percent black, education, percent urban, population size, percent voted for Strom Thurmond in 1948 Presidential election*race (proxy for segregationist preferences)) each interacted with linear cohort trends, and controls for childhood family characteristics (parental income/education/occupation, mother's marital status at birth, birth weight, gender). Standard errors are clustered at the childhood county level. Main school finance reform variables allowed to affect outcomes through both the amount of induced school spending changes and the duration of school-age years of exposure to reform-induced spending changes (i.e., models include intercept and slope terms of intensity of treatment (district spending change) and interaction terms of "school spending change*exposure years" in order to capture dose of treatment in terms of both an individual's school-age years of exposure to school finance reform and the district's change in per-pupil spending induced by reform). Results for non-poor kids not statistically significantly different from zero.





 

–  –  –

2 2 1.5 1.5 1 1.5.5 0 0

-.5 -.5

–  –  –

  Data: PSID geocode Data (1968-2011), matched with childhood school and neighborhood characteristics. Analysis sample includes all PSID individuals born 1955-1985, followed into adulthood through 2011. (N=15,353 individuals (9,035 poor kids; 6,318 non-poor kids) from 1,409 school districts (1,031 child counties, 50 states).

Models: Results are based on non-parametric event-study models that include: school district fixed effects, race-specific year of birth fixed effects, race*census division-specific linear cohort trends, controls at the county-level for the timing of school desegregation*race, hospital desegregation*race, roll-out of "War on Poverty" & related safety-net programs (community health centers, county expenditures on Head Start (at age 4), food stamps, medicaid, AFDC, UI, Title-I (average during childhood years), timing of state-funded Kindergarten), controls for 1960 county characteristics (poverty rate, percent black, education, percent urban, population size, percent voted for Strom Thurmond in 1948 Presidential election*race (proxy for segregationist preferences)) each interacted with linear cohort trends, and controls for childhood family characteristics (parental income/education/occupation, mother's marital status at birth, birth weight, gender). Standard errors are clustered at the childhood county level. Main school finance reform variables allowed to affect outcomes through both the amount of induced school spending changes and the duration of school-age years of exposure to reform-induced spending changes (i.e., models include intercept and slope terms of intensity of treatment (district spending change) and interaction terms of "school spending change*exposure years" in order to capture dose of treatment in terms of both an individual's school-age years of exposure to school finance reform and the district's change in per-pupil spending induced by reform). Results for non-poor kids not statistically significantly different from zero.

–  –  –

.5.5 0 0

-.5 -.5

–  –  –

  Data: PSID geocode Data (1968-2011), matched with childhood school and neighborhood characteristics. Analysis sample includes all PSID individuals born 1955-1985, followed into adulthood through 2011. (N=15,353 individuals (9,035 poor kids; 6,318 non-poor kids) from 1,409 school districts (1,031 child counties, 50 states).

Models: Results are based on non-parametric event-study models that include: school district fixed effects, race-specific year of birth fixed effects, race*census division-specific linear cohort trends, controls at the county-level for the timing of school desegregation*race, hospital desegregation*race, roll-out of "War on Poverty" & related safety-net programs (community health centers, county expenditures on Head Start (at age 4), food stamps, medicaid, AFDC, UI, Title-I (average during childhood years), timing of state-funded Kindergarten), controls for 1960 county characteristics (poverty rate, percent black, education, percent urban, population size, percent voted for Strom Thurmond in 1948 Presidential election*race (proxy for segregationist preferences)) each interacted with linear cohort trends, and controls for childhood family characteristics (parental income/education/occupation, mother's marital status at birth, birth weight, gender). Standard errors are clustered at the childhood county level. Main school finance reform variables allowed to affect outcomes through both the amount of induced school spending changes and the duration of school-age years of exposure to reform-induced spending changes (i.e., models include intercept and slope terms of intensity of treatment (district spending change) and interaction terms of "school spending change*exposure years" in order to capture dose of treatment in terms of both an individual's school-age years of exposure to school finance reform and the district's change in per-pupil spending induced by reform). Results for non-poor kids not statistically significantly different from zero.

–  –  –

1.5 1.5 1 1.5.5 0 0

-.5 -.5

–  –  –

    Data: PSID geocode Data (1968-2011), matched with childhood school and neighborhood characteristics. Analysis sample includes all PSID individuals born 1955-1985, followed into adulthood through 2011. (N=15,353 individuals (9,035 poor kids; 6,318 non-poor kids) from 1,409 school districts (1,031 child counties, 50 states).

Models: Results are based on non-parametric event-study models that include: school district fixed effects, race-specific year of birth fixed effects, race*census division-specific linear cohort trends, controls at the county-level for the timing of school desegregation*race, hospital desegregation*race, roll-out of "War on Poverty" & related safety-net programs (community health centers, county expenditures on Head Start (at age 4), food stamps, medicaid, AFDC, UI, Title-I (average during childhood years), timing of state-funded Kindergarten), controls for 1960 county characteristics (poverty rate, percent black, education, percent urban, population size, percent voted for Strom Thurmond in 1948 Presidential election*race (proxy for segregationist preferences)) each interacted with linear cohort trends, and controls for childhood family characteristics (parental income/education/occupation, mother's marital status at birth, birth weight, gender). Standard errors are clustered at the childhood county level. Main school finance reform variables allowed to affect outcomes through both the amount of induced school spending changes and the duration of school-age years of exposure to reform-induced spending changes (i.e., models include intercept and slope terms of intensity of treatment (district spending change) and interaction terms of "school spending change*exposure years" in order to capture dose of treatment in terms of both an individual's school-age years of exposure to school finance reform and the district's change in per-pupil spending induced by reform). Results for non-poor kids not statistically significantly different from zero.

 

–  –  –

   Data: PSID geocode Data (1968-2011), matched with childhood school and neighborhood characteristics. Analysis sample includes all PSID individuals born 1955-1985, followed into adulthood through 2011. (N=15,353 individuals (9,035 poor kids; 6,318 non-poor kids) from 1,409 school districts (1,031 child counties, 50 states).

Models: Results are based on non-parametric event-study models that include: school district fixed effects, race-specific year of birth fixed effects, race*census division-specific linear cohort trends, controls at the county-level for the timing of school desegregation*race, hospital desegregation*race, roll-out of "War on Poverty" & related safety-net programs (community health centers, county expenditures on Head Start (at age 4), food stamps, medicaid, AFDC, UI, Title-I (average during childhood years), timing of state-funded Kindergarten), controls for 1960 county characteristics (poverty rate, percent black, education, percent urban, population size, percent voted for Strom Thurmond in 1948 Presidential election*race (proxy for segregationist preferences)) each interacted with linear cohort trends, and controls for childhood family characteristics (parental income/education/occupation, mother's marital status at birth, birth weight, gender). Standard errors are clustered at the childhood county level. Main school finance reform variables allowed to affect outcomes through both the amount of induced school spending changes and the duration of school-age years of exposure to reform-induced spending changes (i.e., models include intercept and slope terms of intensity of treatment (district spending change) and interaction terms of "school spending change*exposure years" in order to capture dose of treatment in terms of both an individual's school-age years of exposure to school finance reform and the district's change in per-pupil spending induced by reform). Results for non-poor kids not statistically significantly different from zero.

–  –  –

Number of Individuals 14,670 14,670 8,639 8,639 6,031 6,031 Number of School Districts 1,288 1,288 918 918 978 978 *** p0.01, ** p0.05, * p0.10 Robust standard errors in parentheses (clustered at school district level) Data: PSID geocode Data (1968-2011), matched with childhood school and neighborhood characteristics. Analysis sample includes all PSID individuals born 1955-1985, followed into adulthood through 2011.



Pages:     | 1 |   ...   | 9 | 10 || 12 | 13 |


Similar works:

«PODER JUDICIÁRIO DE NOVA JERSEY NEW JERSEY JUDICIARY COBRANÇA DE SENTENÇA MONETÁRIA Collecting a Money Judgment – Portuguese Tribunal de Justiça de Nova Jersey Divisão Jurídica Seção Especial Cível Superior Court of New Jersey Law Division Special Civil Part Cobrança de sentença monetária página 1 Se você ganhou uma causa na Seção Especial Cível cuja sentença estipulou um valor monetário, você é o credor. Você deverá contatar a pessoa que lhe deve o dinheiro (o...»

«COMMENTS RECEIVED ON PUBLIC DISCUSSION DRAFT BEPS ACTION 1: ADDRESS THE TAX CHALLENGES OF THE DIGITAL ECONOMY 16 April 2014 Summary/Action This note contains compilation of comments received the public discussion draft on BEPS Action 1 (Address the Tax Challenges of the Digital Economy). An invitation for comments was published on the OECD Website on 24 March 2014, with a deadline of 14 April 2014. TABLE OF CONTENTS A3F 5 AFME BBA 12 AmCham EU 16 Association of British Insurers (ABI) 21...»

«Paper Faith in The Market Religion, Secularisation, and Economics, David Joseph Deutch Lay er3 Lay er2 Abstract The underlying premise of this work is that to use the terms ‘secular’ and ‘religion’ without proper definitions and methodological insight is an academic mistake of the highest order. In light of such an assertion, this dissertation provides a clear definition of both the term ‘secular’, and therefore ‘secularisation’, and ‘religion’. In regards to...»

«Financial services sector report Opportunities for Standards in Investment and Asset Management A joint study from BSI and Long Finance – 2014 Prepared by Z/Yen Group for BSI Opportunities for Standards in Investment and Asset Management About the Publishers BSI (British Standards Institution) is the business standards company that equips businesses with the necessary solutions to turn standards of best practice into habits of excellence. Formed in 1901, BSI was the world’s first National...»

«Institutional Investors and the Information Production Theory of Stock Splits Thomas J. Chemmanur† Gang Hu‡ Jiekun Huang§ Boston College Babson College National University of Singapore This Version: October 2012 † Professor of Finance, Fulton Hall 330, Carroll School of Management, Boston College, Chestnut Hill, MA 02467. Phone: 617-552-3980. Fax: 617-552-0431. E-mail: chemmanu@bc.edu. ‡ Associate Professor of Finance, Babson College, 223 Tomasso Hall, Babson Park, MA 02457. Phone:...»

«Chapter 4 Protecting Indigenous Rights and Interests in Water David H. Getches and Sarah B. Van de Wetering With assistance from David Farrier, University of Wollongong (Australia), Robyn Stein, Bowman Gilfillan Inc. (South Africa), Wang Xi (and colleagues), Wuhan University (China); and Marcos Terena, Coordinator General of Indigenous Rights, Mato Grosso do Sul (Brazil) Access to water is fundamental to the right of indigenous people to use and enjoy their lands and maintain the integrity of...»

«Federal Reserve Bank of New York Staff Reports The Federal Reserve’s Commercial Paper Funding Facility Tobias Adrian Karin Kimbrough Dina Marchioni Staff Report no. 423 January 2010 Revised June 2010 This paper presents preliminary findings and is being distributed to economists and other interested readers solely to stimulate discussion and elicit comments. The views expressed in the paper are those of the authors and are not necessarily reflective of views at the Federal Reserve Bank of New...»

«MEMORANDUM To: The Honorable Orrin Hatch, Chairman, Finance Committee The Honorable Kevin Brady, Chairman, Ways and Means Committee The Honorable Peter Roskam, Chairman, House Oversight Subcommittee, Ways and Means Committee From: Office of Federal Relations, on behalf of Harvard University Re: Request for Information on Endowment Date: March 31, 2016 Harvard University is pleased to provide the following information in response to the inquiry of the Senate Committee on Finance and the House...»

«Second ENA/Florida International University Dialogue on Public Administration Public Sector Leadership: The French and U.S. Experiences March 3, 2014 Biographical elements on the speakers Shahed Al-Tammar Shahed is a Ph.D. student in Public Affairs at FIU. She is originally from Kuwait. She obtained her MPA from the University of Pennsylvania and has worked in an investment advisory firm in New York. Her professional work as an assistant to some of the Members of Kuwait’s National Assembly...»

«Adam S. Yore Department of Finance Home Address: 425 Cornell Hall 3100 Wisteria Ln. University of Missouri Columbia, MO 65203 Columbia, MO 65211 (813) 786-1966 (573) 884-1446 yorea@missouri.edu Research Interests: Corporate Governance, Mergers & Acquisitions, Corporate Investment Teaching Interests: Corporate Finance Education: LeBow College of Business, Drexel University Ph.D., Finance, 2009 Dissertation Title: Three Essays in Corporate Governance Dissertation Advisor: Dr. Ralph A. Walkling...»

«REPUBLIC OF GHANA THE BUDGET SPEECH of the BUDGET STATEMENT AND ECONOMIC POLICY of the GOVERNMENT OF GHANA for the 2016 FINANCIAL YEAR presented to PARLIAMENT on FRIDAY, 13TH NOVEMBER 2015 By SETH E. TERKPER Minister for Finance on the Authority of HIS EXCELLENCY PRESIDENT JOHN DRAMANI MAHAMA Progress towards a Brighter Medium Term” THEME: “Consolidating INTRODUCTION 1. Rt. Hon. Speaker and Honourable Members of Parliament, on the authority of His Excellency John Dramani Mahama, President...»

«Matias Damian Cattaneo November 2016 Contact Information Address: Department of Economics Office: 734–763–1306 University of Michigan Cell: 510–207–7865 238 Lorch Hall 611 Tappan Ave. Email: cattaneo@umich.edu Ann Arbor, MI 48109-1220 Web: http://www.umich.edu/∼cattaneo Education Ph.D. in Economics, University of California at Berkeley, 2003 – 2008. M.A. in Statistics, University of California at Berkeley, 2004 – 2005. Master in Economics, Universidad Torcuato Di Tella, Argentina,...»





 
<<  HOME   |    CONTACTS
2016 www.dissertation.xlibx.info - Dissertations, online materials

Materials of this site are available for review, all rights belong to their respective owners.
If you do not agree with the fact that your material is placed on this site, please, email us, we will within 1-2 business days delete him.