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April 2, 2015 Probabilistic Voting in Models of Electoral Competition By
April 2, 2015 Probabilistic Voting in Models of Electoral Competition by Peter Coughlin Department of Economics University of Maryland College Park, MD 20742 Abstract The pioneering model of electoral competition was developed by Harold Hotelling and Anthony Downs. The model developed by Hotelling and Downs and many subsequent models in the literature about electoral competition have assumed that candidates embody policies and, if a voter is not indifferent between the policies embodied by two candidates, then the voter’s choices are fully determined by his preferences on possible polices. More specifically, those models have assumed that if a voter prefers the policies embodied by one candidate then the voter will definitely vote for that candidate. Various authors have argued that i) factors other than policy can affect a voter’s decision and ii) those other factors cause candidates to be uncertain about who a voter will vote for. These authors have modeled the candidates’ uncertainty by using a probabilistic description of the voters’ choice behavior. This paper provides a framework that is useful for discussing the model developed by Hotelling and Downs and for discussing other models of electoral competition. Using that framework, the paper discusses work that has been done on the implications of candidates being uncertain about whom the individual voters in the electorate will vote for. 1. An overview The initial step toward the development of the first model of electoral competition was taken by Hotelling (1929), who developed a model of duopolists in which each firm chooses a location for its store. Near the end of his paper, he briefly described how his duopoly model could be reinterpreted as a model of competition between two political parties. -
Harold Hotelling 1895–1973
NATIONAL ACADEMY OF SCIENCES HAROLD HOTELLING 1895–1973 A Biographical Memoir by K. J. ARROW AND E. L. LEHMANN Any opinions expressed in this memoir are those of the authors and do not necessarily reflect the views of the National Academy of Sciences. Biographical Memoirs, VOLUME 87 PUBLISHED 2005 BY THE NATIONAL ACADEMIES PRESS WASHINGTON, D.C. HAROLD HOTELLING September 29, 1895–December 26, 1973 BY K. J. ARROW AND E. L. LEHMANN AROLD HOTELLING WAS A man of many interests and talents. HAfter majoring in journalism at the University of Washington and obtaining his B.A in that field in 1919, he did his graduate work in mathematics at Princeton, where he received his Ph.D. in 1924 with a thesis on topology. Upon leaving Princeton, he took a position as research associate at the Food Research Institute of Stanford Univer- sity, from where he moved to the Stanford Mathematics Department as an associate professor in 1927. It was during his Stanford period that he began to focus on the two fields— statistics and economics—in which he would do his life’s work. He was one of the few Americans who in the 1920s realized the revolution that R. A. Fisher had brought about in statistics and he spent six months in 1929 at the Rothamstead (United Kingdom) agricultural research station to work with Fisher. In 1931 Hotelling accepted a professorship in the Eco- nomics Department of Columbia University. He taught a course in mathematical economics, but most of his energy during his 15 years there was spent developing the first program in the modern (Fisherian) theory of statistics. -
Principles of Communications ECS 332
Principles of Communications ECS 332 Asst. Prof. Dr. Prapun Suksompong (ผศ.ดร.ประพันธ ์ สขสมปองุ ) [email protected] 1. Intro to Communication Systems Office Hours: Check Google Calendar on the course website. Dr.Prapun’s Office: 6th floor of Sirindhralai building, 1 BKD 2 Remark 1 If the downloaded file crashed your device/browser, try another one posted on the course website: 3 Remark 2 There is also three more sections from the Appendices of the lecture notes: 4 Shannon's insight 5 “The fundamental problem of communication is that of reproducing at one point either exactly or approximately a message selected at another point.” Shannon, Claude. A Mathematical Theory Of Communication. (1948) 6 Shannon: Father of the Info. Age Documentary Co-produced by the Jacobs School, UCSD- TV, and the California Institute for Telecommunic ations and Information Technology 7 [http://www.uctv.tv/shows/Claude-Shannon-Father-of-the-Information-Age-6090] [http://www.youtube.com/watch?v=z2Whj_nL-x8] C. E. Shannon (1916-2001) Hello. I'm Claude Shannon a mathematician here at the Bell Telephone laboratories He didn't create the compact disc, the fax machine, digital wireless telephones Or mp3 files, but in 1948 Claude Shannon paved the way for all of them with the Basic theory underlying digital communications and storage he called it 8 information theory. C. E. Shannon (1916-2001) 9 https://www.youtube.com/watch?v=47ag2sXRDeU C. E. Shannon (1916-2001) One of the most influential minds of the 20th century yet when he died on February 24, 2001, Shannon was virtually unknown to the public at large 10 C. -
Arxiv:1306.1586V4 [Quant-Ph]
Strong converse for the classical capacity of entanglement-breaking and Hadamard channels via a sandwiched R´enyi relative entropy Mark M. Wilde∗ Andreas Winter†‡ Dong Yang†§ May 23, 2014 Abstract A strong converse theorem for the classical capacity of a quantum channel states that the probability of correctly decoding a classical message converges exponentially fast to zero in the limit of many channel uses if the rate of communication exceeds the classical capacity of the channel. Along with a corresponding achievability statement for rates below the capacity, such a strong converse theorem enhances our understanding of the capacity as a very sharp dividing line between achievable and unachievable rates of communication. Here, we show that such a strong converse theorem holds for the classical capacity of all entanglement-breaking channels and all Hadamard channels (the complementary channels of the former). These results follow by bounding the success probability in terms of a “sandwiched” R´enyi relative entropy, by showing that this quantity is subadditive for all entanglement-breaking and Hadamard channels, and by relating this quantity to the Holevo capacity. Prior results regarding strong converse theorems for particular covariant channels emerge as a special case of our results. 1 Introduction One of the most fundamental tasks in quantum information theory is the transmission of classical data over many independent uses of a quantum channel, such that, for a fixed rate of communica- tion, the error probability of the transmission decreases to zero in the limit of many channel uses. The maximum rate at which this is possible for a given channel is known as the classical capacity of the channel. -
Jacob Wolfowitz 1910–1981
NATIONAL ACADEMY OF SCIENCES JACOB WOLFOWITZ 1910–1981 A Biographical Memoir by SHELEMYAHU ZACKS Any opinions expressed in this memoir are those of the author and do not necessarily reflect the views of the National Academy of Sciences. Biographical Memoirs, VOLUME 82 PUBLISHED 2002 BY THE NATIONAL ACADEMY PRESS WASHINGTON, D.C. JACOB WOLFOWITZ March 19, 1910–July 16, 1981 BY SHELEMYAHU ZACKS ACOB WOLFOWITZ, A GIANT among the founders of modern Jstatistics, will always be remembered for his originality, deep thinking, clear mind, excellence in teaching, and vast contributions to statistical and information sciences. I met Wolfowitz for the first time in 1957, when he spent a sab- batical year at the Technion, Israel Institute of Technology. I was at the time a graduate student and a statistician at the building research station of the Technion. I had read papers of Wald and Wolfowitz before, and for me the meeting with Wolfowitz was a great opportunity to associate with a great scholar who was very kind to me and most helpful. I took his class at the Technion on statistical decision theory. Outside the classroom we used to spend time together over a cup of coffee or in his office discussing statistical problems. He gave me a lot of his time, as though I was his student. His advice on the correct approach to the theory of statistics accompanied my development as statistician for many years to come. Later we kept in touch, mostly by correspondence and in meetings of the Institute of Mathematical Statistics. I saw him the last time in his office at the University of Southern Florida in Tampa, where he spent the last years 3 4 BIOGRAPHICAL MEMOIRS of his life. -
Statistics Making an Impact
John Pullinger J. R. Statist. Soc. A (2013) 176, Part 4, pp. 819–839 Statistics making an impact John Pullinger House of Commons Library, London, UK [The address of the President, delivered to The Royal Statistical Society on Wednesday, June 26th, 2013] Summary. Statistics provides a special kind of understanding that enables well-informed deci- sions. As citizens and consumers we are faced with an array of choices. Statistics can help us to choose well. Our statistical brains need to be nurtured: we can all learn and practise some simple rules of statistical thinking. To understand how statistics can play a bigger part in our lives today we can draw inspiration from the founders of the Royal Statistical Society. Although in today’s world the information landscape is confused, there is an opportunity for statistics that is there to be seized.This calls for us to celebrate the discipline of statistics, to show confidence in our profession, to use statistics in the public interest and to champion statistical education. The Royal Statistical Society has a vital role to play. Keywords: Chartered Statistician; Citizenship; Economic growth; Evidence; ‘getstats’; Justice; Open data; Public good; The state; Wise choices 1. Introduction Dictionaries trace the source of the word statistics from the Latin ‘status’, the state, to the Italian ‘statista’, one skilled in statecraft, and on to the German ‘Statistik’, the science dealing with data about the condition of a state or community. The Oxford English Dictionary brings ‘statistics’ into English in 1787. Florence Nightingale held that ‘the thoughts and purpose of the Deity are only to be discovered by the statistical study of natural phenomena:::the application of the results of such study [is] the religious duty of man’ (Pearson, 1924). -
School of Social Sciences Economics Division University of Southampton Southampton SO17 1BJ, UK
School of Social Sciences Economics Division University of Southampton Southampton SO17 1BJ, UK Discussion Papers in Economics and Econometrics Professor A L Bowley’s Theory of the Representative Method John Aldrich No. 0801 This paper is available on our website http://www.socsci.soton.ac.uk/economics/Research/Discussion_Papers ISSN 0966-4246 Key names: Arthur L. Bowley, F. Y. Edgeworth, , R. A. Fisher, Adolph Jensen, J. M. Keynes, Jerzy Neyman, Karl Pearson, G. U. Yule. Keywords: History of Statistics, Sampling theory, Bayesian inference. Professor A. L. Bowley’s Theory of the Representative Method * John Aldrich Economics Division School of Social Sciences University of Southampton Southampton SO17 1BJ UK e-mail: [email protected] Abstract Arthur. L. Bowley (1869-1957) first advocated the use of surveys–the “representative method”–in 1906 and started to conduct surveys of economic and social conditions in 1912. Bowley’s 1926 memorandum for the International Statistical Institute on the “Measurement of the precision attained in sampling” was the first large-scale theoretical treatment of sample surveys as he conducted them. This paper examines Bowley’s arguments in the context of the statistical inference theory of the time. The great influence on Bowley’s conception of statistical inference was F. Y. Edgeworth but by 1926 R. A. Fisher was on the scene and was attacking Bayesian methods and promoting a replacement of his own. Bowley defended his Bayesian method against Fisher and against Jerzy Neyman when the latter put forward his concept of a confidence interval and applied it to the representative method. * Based on a talk given at the Sample Surveys and Bayesian Statistics Conference, Southampton, August 2008. -
An Experimental Investigation of the Hotelling Rule
Price Formation Of Exhaustible Resources: An Experimental Investigation of the Hotelling Rule Christoph Neumann1, Energy Economics, Energy Research Center of Lower Saxony, 38640 Goslar, Germany, +49 (5321) 3816 8067, [email protected] Mathias Erlei, Institute of Management and Economics, Clausthal University of Technology, 38678 Clausthal-Zellerfeld, Germany +49 (5323) 72 7625, [email protected] Keywords Non-renewable resource, Hotelling rule, Experiment, Continuous Double Auction Overview Although Germany has an ambitious energy strategy with the aim of a low carbon economy, around 87% of the primary energy consumption was based on the fossil energies oil, coal, gas and uranium in 2012, which all belong to the category of exhaustible resources (BMWi 2013). Harold Hotelling described in 1931 the economic theory of exhaustible resources (Hotelling 1931). The Hotelling rule states that the prices of exhaustible resources - more specifically the scarcity rent - will rise at the rate of interest, and consumption will decline over time. The equilibrium implies social optimality. However, empirical analysis shows that market prices of exhaustible resources rarely follow theoretical price paths. Nevertheless, Hotelling´s rule “continues to be a central feature of models of non-renewable resource markets” (Livernois 2009). We believe that there are difficulties in the (traditional) empirical verification but this should not lead to the invalidity of the theory in general. Our research, by using experimental methods, shows that the Hotelling rule has its justification. Furthermore, we think that the logic according to the Hotelling rule is one influencing factor among others in the price formation of exhaustible resources, therefore deviations are possible in real markets. -
Rakesh V. Vohra
Rakesh V. Vohra Department of Economics and the Department of Electrical and Systems Engineering University of Pennsylvania Philadelphia, PA 19104 Electronic mail: [email protected], [email protected] August 15th, 2020 Experience • (2013 to date) George A. Weiss and Lydia Bravo Weiss University Professor, Depart- ment of Economics and the Department of Electrical and Systems Engineering, University of Pennsylvania • (2013 to date) Secondary appointment, Department of Computer and Information Sciences, University of Pennsylvania. • (1999 to 2013) John L. and Helen Kellogg Professor of Managerial Economics and Decision Sciences, Kellogg School of Management, Northwestern University. • (2010 to 2013) Professor (Courtesy), Department of Economics, Weinberg College of Arts and Sciences, Northwestern University. • (2006 to 2013) Professor (Courtesy), Electrical Engineering and Computer Science, Mc- Cormick School, Northwestern University. • (1998 to 1999) Professor of Managerial Economics and Decision Sciences, Kellogg School of Management, Northwestern University. • (1991 to 1998) Associate Professor of Management Science and Industrial Engineering, Fisher College of Business, The Ohio State University. • (1985 to 1991) Assistant Professor of Management Science, Fisher College of Business, The Ohio State University. • (Summer 2011, 2012, 2014) Visiting Researcher, Microsoft Research, New England. • (Summer 2006) Visiting Researcher, Microsoft Research, Redmond. • (Winter 2005) Visiting Scholar, California Institute of Technology. • (Spring 2004, 2006, 2011, 2016) Visiting Professor, Indian School of Business. 1 • (Summer 2003) METEOR Fellow, Department of Quantitative Economics, University of Maas- tricht. • (September 2000) Cycle and Carriage Visiting Professor, Department of Decision Sciences, College of Business, National University of Singapore. • (1997-1998) Visiting Associate Professor, The Kellogg School of Management, Northwestern University. • (1992 -1993, Summer '96) Visiting Associate Professor, The Sloan School, MIT. -
IMS Presidential Address Teaching Statistics in the Age of Data Science
IMS Presidential Address Teaching Statistics in the Age of Data Science Jon A. Wellner University of Washington, Seattle IMS Annual Meeting, & JSM, Baltimore, July 31, 2017 IMS Annual Meeting and JSM Baltimore STATISTICS and DATA SCIENCE • What has happened and is happening? B Changes in degree structures: many new MS degree programs in Data Science. B Changes in Program and Department Names; 2+ programs with the name \Statistics and Data Science" Yale and Univ Texas at Austin. B New pathways in Data Science and Machine Learning at the PhD level: UW, CMU, and ::: • Changes (needed?) in curricula / teaching? IMS Presidential Address, Baltimore, 31 July 2017 1.2 ? Full Disclosure: 1. Task from my department chair: a. Review the theory course offerings in the Ph.D. program in Statistics at the UW. b. Recommend changes in the curriculum, if needed. 2. I will be teaching Statistics 581 and 582, Advanced Statistical Theory during Fall and Winter quarters 2017-2018. What should I be teaching? ? IMS Presidential Address, Baltimore, 31 July 2017 1.3 Exciting times for Statistics and Data Science: • Increasing demand! • Challenges of \big data": B challenges for computation B challenges for theory • Changes needed in statistical education? IMS Presidential Address, Baltimore, 31 July 2017 1.4 Exciting times for Statistics and Data Science: • Increasing demand! Projections, Bureau of Labor Statistics, 2014-24: Job Description Increase % • Statisticians 34% • Mathematicians 21% • Software Developer 17% • Computer and Information Research Scientists -
Asymptotic Theory for Canonical Correlation Analysis
Journal of Multivariate Analysis 70, 129 (1999) Article ID jmva.1999.1810, available online at http:ÂÂwww.idealibrary.com on Asymptotic Theory for Canonical Correlation Analysis T. W. Anderson Department of Statistics, Stanford University, Stanford, California 94305-4065 Received November 30, 1998 The asymptotic distribution of the sample canonical correlations and coefficients of the canonical variates is obtained when the nonzero population canonical correlations are distinct and sampling is from the normal distribution. The asymptotic distributions are also obtained for reduced rank regression when one set of variables is treated as independent (stochastic or nonstochastic) and the other set View metadata,as dependent. citation Earlier and similar work papers is corrected. at core.ac.uk 1999 Academic Press brought to you by CORE AMS 1991 subject classifications: 62H10, 62H20. provided by Elsevier - Publisher Connector Key Words: canonical variates; reduced rank regression; maximum likelihood estimators; test of rank. 1. INTRODUCTION Hotelling (1936) proposed canonical correlations as invariant measures of relationships between two sets of variates. Suppose that the two random vectors Y and X of p and q components ( pq), respectively, have the covariance matrix 7 7 7= YY YX (1.1) \7XY 7XX+ with 7YY and 7XX nonsingular. The first canonical correlation, say \1 ,is the maximum correlation between linear combinations U=:$Y and V=#$X. The maximizing linear combinations normalized so var U= var V=1 and denoted U1=:$1 Y and V1=#$1 X are the first canonical variates. The second canonical correlation \2 is the maximum correlation between linear combinations U=:$Y and V=#$X uncorrelated with U1 and V1 . -
Subsidies, Savings and Sustainable Technology Adoption: Field Experimental Evidence from Mozambique∗
Subsidies, Savings and Sustainable Technology Adoption: Field Experimental Evidence from Mozambique∗ Michael R. Carter University of California, Davis, NBER, BREAD and the Giannini Foundation Rachid Laajaj Universidad de los Andes Dean Yang University of Michigan, NBER and BREAD July 6, 2016 Abstract We conducted a randomized experiment in Mozambique exploring the inter- action of technology adoption subsidies with savings interventions. Theoretically, combining technology subsidies with savings interventions could either promote technology adoption (dynamic enhancement), or reduce adoption by encouraging savings accumulation for self-insurance and other purposes (dynamic substitution). Empirically, the latter possibility dominates. Subsidy-only recipients raised fertil- izer use in the subsidized season and for two subsequent unsubsidized seasons. Consumption rose, but was accompanied by higher consumption risk. By con- trast, when paired with savings interventions, subsidy impacts on fertilizer use disappear. Instead, households accumulate bank savings, which appear to serve as self-insurance. Keywords: Savings, subsidies, technology adoption, fertilizer, risk, agriculture, Mozam- bique JEL classification: C93, D24, D91, G21, O12, O13, O16, Q12, Q14 ∗Contacts: [email protected]; [email protected]; [email protected]. Acknowlegements: An- iceto Matias and Ines Vilela provided outstanding field management. This research was conducted in collabora- tion with the International Fertilizer Development Corporation (IFDC), and in particular we thank Alexander Fernando, Robert Groot, Erik Schmidt, and Marcel Vandenberg. We appreciate the feedback we received from seminar participants at Brown, PACDEV 2015, the University of Washington, Erasmus, the Institute for the Study of Labor (IZA), Development Economics Network Berlin (DENeB), the \Improving Productivity in De- veloping Countries" conference (Goodenough College London), UC Berkeley, Stanford, and Yale.