DOCSLIB.ORG

Regression Estimation for Survey Samples

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text
Regression Estimation for Survey Samples Catalogue no. 12-001-XIE Survey Methodology June 2002 How to obtain more information Specific inquiries about this product and related statistics or services should be directed to: Business Survey Methods Division, Statistics Canada, Ottawa, Ontario, K1A 0T6 (telephone: 1-800-263-1136). For information on the wide range of data available from Statistics Canada, you can contact us by calling one of our toll-free numbers. You can also contact us by e-mail or by visiting our website. National inquiries line 1-800-263-1136 National telecommunications device for the hearing impaired 1-800-363-7629 Depository Services Program inquiries 1-800-700-1033 Fax line for Depository Services Program 1-800-889-9734 E-mail inquiries [email protected] Website www.statcan.ca Information to access the product This product, catalogue no. 12-001-XIE, is available for free. To obtain a single issue, visit our website at www.statcan.ca and select Publications. Standards of service to the public Statistics Canada is committed to serving its clients in a prompt, reliable and courteous manner and in the official language of their choice. To this end, the Agency has developed standards of service that its employees observe in serving its clients. To obtain a copy of these service standards, please contact Statistics Canada toll free at 1 800 263-1136. The service standards are also published on www.statcan.ca under About us > Providing services to Canadians. Statistics Canada Business Survey Methods Division Survey Methodology June 2002 Published by authority of the Minister responsible for Statistics Canada © Minister of Industry, 2006 All rights reserved. The content of this electronic publication may be reproduced, in whole or in part, and by any means, without further permission from Statistics Canada, subject to the following conditions: that it be done solely for the purposes of private study, research, criticism, review or newspaper summary, and/or for non-commercial purposes; and that Statistics Canada be fully acknowledged as follows: Source (or “Adapted from”, if appropriate): Statistics Canada, year of publication, name of product, catalogue number, volume and issue numbers, reference period and page(s). Otherwise, no part of this publication may be reproduced, stored in a retrieval system or transmitted in any form, by any means—electronic, mechanical or photocopy—or for any purposes without prior written permission of Licensing Services, Client Services Division, Statistics Canada, Ottawa, Ontario, Canada K1A 0T6. October 2006 Catalogue no. 12-001-XIE ISSN 1492-0921 Frequency: semi-annual Ottawa Cette publication est disponible en français sur demande (no 12-001-XIF au catalogue). Note of appreciation Canada owes the success of its statistical system to a long-standing partnership between Statistics Canada, the citizens of Canada, its businesses, governments and other institutions. Accurate and timely statistical information could not be produced without their continued cooperation and goodwill. Survey Methodology, June 2002 5 Vol. 28, No. 1, pp. 5­23 Statistics Canada, Catalogue No. 12­001­XIE Regression Estimation for Survey Samples Wayne A. Fuller 1 Abstract Regression and regression related procedures have become common in survey estimation. We review the basic properties of regression estimators, discuss implementation of regression estimation, and investigate variance estimation for regression estimators. The role of models in constructing regression estimators and the use of regression in nonresponse adjustment are explored. Key Words: Auxiliary information; Calibration; Least squares; Design consistency; Linear prediction. 1. Introduction available to non governmental institutions selecting samples. Design and estimation in survey sampling involve the In the third situation, only the population mean of x is use of information about the study population to construct known, or known for a large sample. In this case, the efficient procedures. While design and estimation are auxiliary information cannot be used in design and the intimately related, with estimators depending on the design, estimation options are limited. For example the U.S. the two topics are often treated somewhat separately in the Department of Agriculture might release an estimate of the survey sampling literature. We follow tradition first total number of animals of a particular type on farms on a studying estimation treating the design as given. The particular date. Our discussion concentrates on this situation. estimation task is to combine the available information Two estimation situations can also be identified. In one, about the population, with the sample data to produce good a single variable and a parameter, or a very small number of representations of characteristics of interest. parameters, is under consideration. The analyst is willing to Regression estimation is one of the important procedures invest a great deal of effort in the analysis, has a well that use population information or information from a larger formulated population model, and is prepared to support the sample, to construct estimators with good efficiency. The estimation procedure on the basis of the reasonableness of information, sometimes called auxiliary information, may the model. In the second situation, a large number of have been used in the design or may not have been available analyses of a large number of variables is anticipated. No at the design stage. In surveys of the human population, the single model is judged adequate for all variables. The information often comes from official sources such as the prototypical example of the second situation is the case in national census. Similar sources may provide information which a data set is prepared by the survey sampler to be for other types of surveys. For example, in a survey of land analyzed by others. Because the person preparing the data use the total surface area, the area owned by the national set does not have knowledge of the analysis variables, government, and the area in permanent water bodies may be emphasis is placed on the use of estimators that can be available from national data archives. defended with minimal recourse to models. Three distinct situations can be identified with respect to Regression estimators fall in the class of linear esti­ the nature of the auxiliary information that is available. In mators. Linear estimators have a particular advantage in the first, the values of the auxiliary vector x are known for survey sampling because once the weights are calculated each element in the population at the time of sample they are appropriate for any analysis variable. Several selection. In this case the auxiliary variable can be used in properties of estimators will be examined in our discussion. designing the sample selection procedure. Given a model, we accept the classical goal of minimizing In the second situation all values of the vector x are the mean square error in a class of estimators. That class known, but a particular value cannot be associated with a may be the class of linear estimators that are unbiased under particular element until the sample is observed. In this case, the model, but the class may be further restricted. the auxiliary information cannot be used in design, but a Estimators that are scale and location invariant can be wide range of estimation options are available once the used in general settings. Mickey (1959) suggested that the observations are available. For example, the population term regression estimator be restricted to linear estimators census may give the age­sex distribution of the population, that are location and scale invariant. While we may not but a list of individuals and their characteristics is not adhere strictly to this definition, we support the distinction 1. Wayne Fuller, Emeritus Distinguished Professor, Iowa State University, 221 Snedecor Hall, Ames, IA 50011­1210, U.S.A. 6 Fuller: Regression Estimation for Survey Samples between estimators that are location and scale invariant and A great deal of research was conducted in the 1970’s and those that are not. We consider location invariance to be 1980’s on the general nature of the regression estimator in important for sampling designs where the unit of interest for survey samples and on the degree to which the model analysis is also the sampling unit. For cluster and two stage prediction approach can be reconciled with the design designs in which weights are constructed for primary perspective. Fuller (1973, 1975) gave the large sample sampling unit totals, location invariance is less important. properties of a vector of regression coefficients computed Models play an important role in the construction of from a survey sample. Isaki (1970) studied regression regression estimators. It is desirable that the estimators estimators and the results were published in expanded retain good properties if the model specification is not exact. versions in Isaki and Fuller (1982) and Fuller and Isaki Therefore properties conditional on the realized finite (1981). It was shown that a regression estimator constructed population, as well as properties under the model, are under a model is design consistent for the population mean if the model contains certain variables. Cassel, Särndal and important. Wretman (1976) considered both model and design Linear estimators that reproduce the known means of the principles in estimator construction and suggested the term auxiliary variables are said to be calibrated. This is a desir­ “generalized regression estimator” for design consistent able property in that, for example, the marginals of tables estimators of the total of the form with an auxiliary variable as an analysis variable agree with known totals. If the auxiliary variable is of no analytic Tˆ = Tˆ + (T - Tˆ ) βˆ , interest, then calibration is less important. y, GREG y, HT x, N x , HT ˆ ˆ where T y , HT and Tx , HT are the Horvitz­Thompson estimators of the totals of y and x, respectively, Tx , N is the 2. Background know population total of x and βˆ is an estimated regression coefficient.
Load more

Recommended publications
  • Time Series Econometrics and Commodity Price Analysis*
    TIME SERIES ECONOMETRICS AND COMMODITY PRICE ANALYSIS* by Robert J. Myers Department of Economics The University of Queensland February 1992 ... Invited paper at the 36th Annual Conference of the Australian Agricultural Economics Society, Australian National University, Canberra, February 10-12, 1992. 1. Introduction Econometric analysis of commodity prices has a long and distinguished history stretching back to the birth of econometrics itself as an emerging science in the 1920s and 1930s (Working, 1922; Schultz, 1938). Since then, a very large literature has developed focusing on estimating commodity supply and demand systems; forecasting commodity supplies and prices; and evaluating the effects of commodity pricing policies. Much of this research relies on a standard set of econometric methods, as outlined in books such as Theil (1971) and Johnston (1984). The goal in this paper is not to provide a detailed survey of the literature on econometric analysis of commodity prices. This has been done elsewhere (e.g. Tomek and Robinson, 1977) and, in any case, is well beyond the scope of what can be achieved in the limited time and space available here. Rather, the aims are to comment on some recent developments taking place in the time-series econometrics literature and discuss their implications for modelling the behaviour of commodity prices. The thesis of the paper is that developments in the time-series literature have important implications for modelling commodity prices, and that these implications often have not been fully appreciated by those undertaking commodity price analysis. The time-series developments that will be discussed include stochastic trends (unit roots) in economic time series; common stochastic trends driving multiple time series (cointegration); and time-varying volatility in the innovations of economic time series (conditional heteroscedasticity).
    [Show full text]
  • PDF File of the Newsletter Is Available on the IASS Web Site
    In This Issue No. 48, July 2003 1 Letter from the President 3 Charles Alexander, Jr. 4 Software Review 15 Country Reports 22 Articles 22 Training Needs for Survey Statisticians in Developed and Developing Countries 27 Special Articles: Censuses Conducted Around the World 27 – The Possible Impact of Question Changes on Data and Its Usage: A Case Study of Two South African Editors Censuses (1996 and 2001) Leyla Mohadjer Jairo Arrow 32 Discussion Corner: Substitution Section Editors 38 Announcements John Kovar — Country Reports James Lepkowski — Software Review 38 IASS General Assembly 38 IASS Elections Production Editor 38 Joint IMS-SRMS Mini Meeting Therese Kmieciak 38 IASS Program Committee for ISI, Sidney 2005 39 Publication Notice Circulation 40 Association for Survey Computing 2003 Claude Olivier 41 IASS Web Site Anne-Marie Vespa-Leyder 42 In Other Journals The Survey Statistician is published twice a year in English and French by the 42 Survey Methodology International Association of Survey 43 Journal of Official Statistics Statisticians and distributed to all its 45 Statistics in Transition members. Information for membership in 48 The Allgemeines Statistisches Archiv the Association or change of address for current members should be addressed to: Change of Address Form Secrétariat de l’AISE/IASS List of IASS Officers and Council Members c/o INSEE-CEFIL Att. Mme Claude Olivier List of Institutional Members 3, rue de la Cité 33500 Libourne - FRANCE E-mail: [email protected] Comments on the contents or suggestions for articles in The Survey Statistician should be sent via e-mail to [email protected] or mailed to: Leyla Mohadjer Westat 1650 Research Blvd., Room 466 Rockville, MD 20850 - USA Time goes by quickly—too quickly.
    [Show full text]
  • A Regression Composite Estimator with Application to the Canadian Labour Force Survey
    Survey Methodology, June 2001 45 Vol. 27, No. 1, pp. 45­51 Statistics Canada, Catalogue No. 12­001 A Regression Composite Estimator with Application to the Canadian Labour Force Survey Wayne A. Fuller and J.N.K. Rao 1 Abstract The Canadian Labour Force Survey is a monthly survey of households selected according to a stratified multistage design. The sample of households is divided into six panels (rotation groups). A panel remains in the sample for six consecutive months and is then dropped from the sample. In the past, a generalized regression estimator, based only on the current month’s data, has been implemented with a regression weights program. In this paper, we study regression composite estimation procedures that make use of sample information from previous periods and that can be implemented with a regression weights program. Singh (1996) proposed a composite estimator, called MR2, which can be computed by adding x­variables to the current regression weights program. Singh’s estimator is considerably more efficient than the generalized regression estimator for one­period change, but not for current level. Also, the estimator of level can deviate from that of the generalized regression estimator by a substantial amount and this deviation can persist over a long period. We propose a “compromise” estimator, using a regression weights program and the same number of x­variables as MR2, that is more efficient for both level and change than the generalized regression estimator based only on the current month data. The proposed estimator also addresses the drift problem and is applicable to other surveys that employ rotation sampling.
    [Show full text]
  • Newsletter Issue 17 July 2003
    Newsletter Issue 17 www.amstat.org/sections/srms July 2003 See You in San Francisco Cognitive Aspects of Web Survey Designs Report from the Program Chair (2003) (Elizabeth Stasny) Howard Hogan Calibration Estimation in Sample Surveys (Pat Cantwell) As I promised, and with due respect to last year’s SMRS Promise and Reality of Survey Automation (Dan program chair, Pat Cantwell, the 2003 ASA/JSM in San Cork) Francisco will be the best meetings ever. Was This the Best Census Ever? (Carolee Bush) Sampling in a Network (Steven K. Thompson) Very much at the heart of our meetings will be the Invited Memorial Session honoring Charles H. (Chip) Alexander. Small Area Estimation Using Information from We have scheduled this session for Monday at 10:30 and Multiple Surveys (William W Davis) worked with other sections to minimize conflicts. This is a Small Area Estimation Using Survey Weights session on the American Community Survey that Chip was in (Malay Ghosh) the process of organizing before his death. Very much like Small Area Estimation in Natural Resources Chip himself, we expect that this session will reflect both Management (Loveday Conquest) technical soundness and human warmth. How to Design a National Survey of the Homeless (David Marker) We also will have a memorial session on Survey Quality to honor Tore Dalenius, organized by Lars Lyberg. Issues Related to the Use of Administrative Records (Eloise Parker) In addition we are sponsoring or co-sponsoring invited Cross-Cultural Issues in Questionnaire Design sessions (with organizer) on: (Gordon Willis) Integration of Demographic, Survey, and Modeling Methods (Juanita Lott) Inside This Issue As is traditional, the incoming program chair, Partha Lahiri, has organized the Roundtable luncheons: Issues Involved in the Modeling of Complex Survey 1 See You in San Francisco Data with Danny Pfeffermann 2 Section News Statistical Confidentiality and Disclosure Limitation with Lawrence H.
    [Show full text]
  • October 2011 • Issue #412 AMSTATNEWS the Membership Magazine of the American Statistical Association •
    October 2011 • Issue #412 AMSTATNEWS The Membership Magazine of the American Statistical Association • http://magazine.amstat.org JSM 2011 Highlights & Trends Many Honored at Presidential Address, Awards Ceremony ALSO: ‘Reverse’ Time Capsule Kicks Off Preparations for 175th Anniversary Celebration The ASA Fellow Award—Revisited Publications Agreement No. 41544521 AMSTATNews OCTOBER 2011 • IssuE #412 Executive Director Ron Wasserstein: [email protected] Associate Executive Director and Director of Operations Stephen Porzio: [email protected] Director of Education Martha Aliaga: [email protected] Director of Science Policy features Steve Pierson: [email protected] 3 President’s Corner Managing Editor Megan Murphy: [email protected] 5 Highlights of the July 2011 ASA Board of Directors Meeting Production Coordinators/Graphic Designers Melissa Muko: [email protected] Kathryn Wright: [email protected] 7 ‘Reverse’ Time Capsule Kicks Off Preparations for 175th Anniversary Celebration Publications Coordinator Val Nirala: [email protected] 7 Papers Sought for Journal of Statistical Research Advertising Manager 9 ASA Accreditation Program Update Claudine Donovan: [email protected] 9 Call for Nominations: ASA President-elect and Contributing Staff Members Vice President Candidates Pam Craven • Amy Farris • Eric Sampson 10 Salary Survey of Business, Industry, and Amstat News welcomes news items and letters from readers on matters of interest to the association and the profession. Address correspondence to Government Statisticians Managing Editor, Amstat News, American Statistical Association, 732 North Washington Street, Alexandria VA 22314-1943 USA, or email amstat@ 14 JSM 2011 Highlights & Trends amstat.org. Items must be received by the first day of the preceding month to ensure appearance in the next issue (for example, June 1 for the July issue).
    [Show full text]
  • AMSTATNEWS the Membership Magazine of the American Statistical Association •
    January 2021 • Issue #523 AMSTATNEWS The Membership Magazine of the American Statistical Association • http://magazine.amstat.org Reaching for High-Impact Opportunities Pushes Profession Forward ALSO: My ASA Story: Sastry Pantula Meet Spiro Stefanou, Head of the Economic Research Service NOVEMBER.indd 2 10/21/20 4:08 PM AMSTATNEWS JANUARY 2021 • ISSUE #523 Executive Director Ron Wasserstein: [email protected] Associate Executive Director and Director of Operations Stephen Porzio: [email protected] features Senior Advisor for Statistics Communication and Media Innovation 3 2021: A Year of Hope and Helping Regina Nuzzo: [email protected] 5 Entries Invited for Statistical Significance Competition Director of Science Policy Steve Pierson: [email protected] 5 JSR to Publish Special Issue in Celebration of 50 Years Director of Strategic Initiatives and Outreach 6 Highlights of the November 18–20, 2020, ASA Board of Donna LaLonde: [email protected] Directors Meeting Director of Education Rebecca Nichols: [email protected] 8 Donor Spotlight: Mohamed Al Lawati Managing Editor 10 Meet Spiro Stefanou, Head of the Economic Research Service Megan Murphy: [email protected] 12 My ASA Story: Sastry Pantula, Dean Editor and Content Strategist Val Nirala: [email protected] 14 Reaching for High-Impact Opportunities Pushes Profession Forward Production Coordinators/Graphic Designers Olivia Brown: [email protected] 17 Nominate a Colleague for ASA Leadership Position Megan Ruyle: [email protected] 17 Webinar: Privacy Risk and Preservation Contributing Staff Members Rebecca Nichols • Amanda Malloy • Kim Gilliam Amstat News welcomes news items and letters from readers on matters of interest to the association and the profession. Address correspondence to Managing Editor, Amstat News, American Statistical Association, 732 North Washington Street, Alexandria VA 22314-1943 USA, or email amstat@ columns amstat.org.
    [Show full text]
  • Newsletter Issue 31 July 2010
    Newsletter Issue 31 July 2010 Inside this Newsletter Message from Section Chair ............................................................................................................1 Report from Education Officer ........................................................................................................2 Report from Council of Sections Representatives ...........................................................................4 JSM 2010: Report from Program Chair ...........................................................................................6 Feature Article: Two Decades of Survey Methods Research Pay Off for the Census ...................6 Announcements................................................................................................................................8 SRMS Mission Statement ..............................................................................................................12 ******************* Message From the Section Chair Howard Hogan How well is the section fulfilling its mission ―to promote the improvement of survey practice and the understanding of survey methods‖? Most of the news of the section is reported elsewhere in this newsletter, but let me highlight a few recent accomplishments. A major accomplishment has been our webinars that Mike Larsen has organized and reported on. These webinars accomplish three important goals for our section. First and most importantly, they directly promote the improvement of survey practice and understanding by bringing important
    [Show full text]
  • Survey Methodology December 2009
    Catalogue no. 12-001-X Survey Methodology December 2009 Statistics Statistique Canada Canada How to obtain more information For information about this product or the wide range of services and data available from Statistics Canada, visit our website at www.statcan.gc.ca, e-mail us at [email protected], or telephone us, Monday to Friday from 8:30 a.m. to 4:30 p.m., at the following numbers: Statistics Canada’s National Contact Centre Toll-free telephone (Canada and United States): Inquiries line 1-800-263-1136 National telecommunications device for the hearing impaired 1-800-363-7629 Fax line 1-877-287-4369 Local or international calls: Inquiries line 1-613-951-8116 Fax line 1-613-951-0581 Depository Services Program Inquiries line 1-800-635-7943 Fax line 1-800-565-7757 To access and order this product This product, Catalogue no. 12-001-X, is available free in electronic format. To obtain a single issue, visit our website at www.statcan.gc.ca and select “Publications.” This product, Catalogue no. 12-001-X, is also available as a standard printed publication at a price of CAN$30.00 per issue and CAN$58.00 for a one-year subscription. The following additional shipping charges apply for delivery outside Canada: Single issue Annual subscription United States CAN$6.00 CAN$12.00 Other countries CAN$10.00 CAN$20.00 All prices exclude sales taxes. The printed version of this publication can be ordered as follows: • Telephone (Canada and United States) 1-800-267-6677 • Fax (Canada and United States) 1-877-287-4369 • E-mail [email protected] • Mail Statistics Canada Finance R.H.
    [Show full text]
  • Department of Statistics Fall 2017 Newsletter
    Department of Statistics Fall 2017 Newsletter Department of Statistics What’s inside Letter from the chair...3 Faculty news...............4 Student news.............7 Alumni Updates..........10 Have a story? Email Kati at [email protected] Dear reader, The Department of Statistics newsletter is published for the alumni, friends, students, and faculty of the Department of Statistics, an academic department in the College of Liberal Arts and Sciences, and the College of Agricultural and Life Sciences at Iowa State University, It provides the latest news and achievements of the department and we are thrilled to share it. Kind regards, Department of Statistics Letter From The Chair Thank you for reading the 2017 newsletter of the Department of Statistics at Iowa State University. You may have heard that ISU President Stephen Leath left Ames during the summer to take the position of President at Auburn University. Since his departure, former ISU Provost Benjamin Allen has served as Interim President of the university. On October 23, a national search concluded with the announcement that ISU’s current Dean of the College of Agriculture and Life Sciences, Wendy Wintersteen, will be ISU’s 16th president. Wintersteen will officially begin her new position on November 20. Closer to home, we had three faculty retirements during the last academic year. Professors Song Chen, Dianne Cook, and Mervyn Marasinghe have joined the ranks of our emeritus faculty after having made major contributions to the department and its programs over many years. On the other side of the ledger, the department hired one new assistant professor this semester.
    [Show full text]
  • A. Ronald Gallant Office
    A. Ronald Gallant Office: 1-919-428-1130 The Pennsylvania State University Home: 1-919-932-4397 Department of Economics FAX: 1-814-863-4775 511 Kern Graduate Building e-mail: [email protected] University Park PA 16802 USA web: www.aronaldg.org EXPERIENCE Aug. 2013 The Pennsylvania State University, University Park, Pennsylvania to Professor of Economics and Liberal Arts Research Professor present Graduate teaching: econometric theory, computational econometrics; Undergraduate teach- ing: environmental economics Jan. 2003 Duke University, Durham, North Carolina to Hanes Corporation Foundation Professor of Business Administration, Fuqua School of Busi- July 2013 ness. MBA teaching: data mining, forecasting, environmental economics; Graduate teach- ing: computational econometrics. Jan. 2010 New York University, New York City, New York to Distinguished Scientist in Residence, Department of Economics Dec. 2013 Graduate teaching: computational econometrics. July 1993 University of North Carolina, Chapel Hill, North Carolina to Emeritus Professor of Economics. Adjunct Professor of Statistics and Henry A. Latan´e present Distinguished Professor of Economics previously. Graduate teaching: nonlinear and non- parametric econometrics, mathematical statistics. March 1983 Duke University, Durham, North Carolina to Professor of Economics (secondary appointment), Department of Economics, Research Pro- Aug. 2013 fessor previously. Graduate teaching: topics in econometrics. July 1971 North Carolina State University, Raleigh, North Carolina to Drexel Professor of Statistics and Economics. Assistant, Associate, and Full Professor pre- June 1993 viously. Graduate teaching: econometrics, linear models, multivariate linear and nonlinear models, time series analysis, statistical inference, statistical computing. Undergraduate teaching: mathematical statistics. Sept. 1987 University of Chicago, Chicago, Illinois to Visiting Professor of Econometrics, Graduate School of Business.
    [Show full text]
  • Journal of International Cooperation and Development Vol 3, No 1, May 2020
    Journal of International Cooperation and Development www.richtmann.org/journal Vol 3, No 1, May 2020 Does Unemployment Still Follow Hysteresis Hypothesis in Nigeria? Evidence from Linear and Nonlinear Unit Root Test Methods Isiaka Akande Raifu (MSc) Department of Economics, Faculty of Economics and Management Sciences University of Ibadan, Ibadan, Oyo State, Nigeria Temitope Titus Abodunde (MSc) Department of Economics, Faculty of Economics and Management Sciences, University of Ibadan, Ibadan, Oyo State, Nigeria Abstract In the face of persistent rise in unemployment figure in Nigeria, this study re-examines the unemployment hysteresis hypothesis by deploying both linear and nonlinear unit root estimation techniques. Using Nigerian unemployment rate data from 1970 to 2017, evidence from the adopted unit toot test techniques, except the quantile unit root test, showed that unemployment hysteresis hypothesis holds in Nigeria. This implies that when a shock that affects unemployment occurs, there is a high tendency that the effect would be permanent. However, the finding from the quantile unit root test sheds light on the need for a timely policy response. If the policy interventions such as fiscal policy and other forms of policies are taken regularly, especially at every quarter, the tendency for unemployment to revert to its pre-shock state is high. Keywords: Unemployment, Unemployment Hysteresis Hypothesis, Unit Root Tests 1. Introduction One of the fundamental macroeconomic problems facing Nigeria is the problem of unemployment. Figure 1 shows the trend of unemployment over time. The figure reveals that the unemployment rate has been rising over the years. Historically, the problem of unemployment began in the late 1970s after the discovery of crude oil at Oloibiri and its commercialisation.
    [Show full text]
  • Biographical Sketch
    Dickey, David A. Curriculum Vitae Education PhD; May 1976; Department of Statistics, Iowa State University Winner of Snedecor Award for outstanding statistics graduate student at ISU MS; May 1969; Math; Math; Miami University, Oxford, Ohio BA; July 1967; Math; Miami University, Oxford, Ohio Positions Held 6/2007 - Present Professor, Institute for Advanced Analytics, North Carolina State. 6/1976 - Present: Professor, Department of Statistics, North Carolina State University. Associate faculty, Economics. Financial Math faculty. 9/1971 - 6/1972: Instructor Randolph Macon College, Ashland, Virginia 9/1969 - 6/1971: Instructor College of William and Mary in Virginia 1968 Summer: Staff member Operations Research Division, Air Force Logistic Command, Wright Patterson AFB, Ohio 1968 - 1969: Math Instructor, Miami University, Oxford, Ohio Sabbatical Leaves and Scholarly Assignments 10/2001: Visiting Scholar, Federal Reserve Bank of St Louis 9/1982 - 6/1983: Scholarly Assignment, US Census Bureau Honors and Awards SAS Distinguished Professor award presented at SAS Global Forum 2014. Appointed William Neal Reynolds Distinguished Professor, 2008 Outstanding Extension Service Award 2007 Fellow, American Statistical Association, August 2000 D.D. Mason Faculty Award, 1986. Academy of Outstanding Teachers at North Carolina State University in Spring 1994 Member of Honor Societies: Phi Kappa Phi, Sigma Xi, Mu Sigma Rho, Pi Mu Epsilon (mathematics), Kappa Phi Kappa (education), Phi Mu Alpha(music) Areas of Research Time series analysis (unit roots and nonstationarity) Funded Grants Other Investi- Title Agency $ Amount Time Period PI/Co-PI gators StatisticalSupport for Project NCSU $98,999 2003-2006 D. Dickey M. OPEN subcontract L.Stefanski Williams Prognostic Capability for Coastal and Estuarine National Flooding Severe $17,000 2001-2006 D.
    [Show full text]