Ladislaus von Bortkiewicz—Statistician,Economist and a European Intellectual

Ladislaus von Bortkiewicz (1868–1931) was a European statistician. His scientific work covered theoretical economics, stochastics, mathematical statistics and radiology; today, we would call him a cross‐disciplinary scientist. With his clear views on mathematical principles with their applications in these fields, he stood in conflict with the mainstream economic schools in Germany at the dawn of the 20th century. He had many prominent students (Gumbel, Leontief and Freudenberg among them), and he carved out the path of modern statistical thinking. He was a true European intellectual with a career path from St. Petersburg via Göttingen to Straßburg and finally the Berliner Universität, now Humboldt‐Universität zu Berlin. He is known for the precise calibration of insurance claims applying the—at that time hardly known—Poisson distribution to Prussian horse kick and child suicide data. He proposed a simple solution to the Marxian transformation problem and wrote numerous articles and books on the mathematical treatment of statistical (including radiological physical) data. In this article, we sketch his life and work and point out the prominent role that he has in today's statistical thinking.     

Factors Related to the Academic Performance of Students in the Statistics Course in Psychology

Many studies have examined the factors that influence academic performance in primary and secondary education as well as at university, with the purpose of enhancing learning at these stages and reducing drop-out rates. It is within this research framework that we want to emphasise the deficient performance of students enrolled on the statistics course in the Faculty of Psychology at the University of Barcelona. Consequently, this paper attempts to determine the factors that affect student performance in this subject by undertaking an analysis of a structural equation model and determining its stability over time. In order to accomplish our objective, we worked with two samples of students enrolled statistics classes. The first group comprised 211 students enrolled in the academic year 2000–2001, while the second comprised 287 students enrolled in the academic year 2001–2002. By administering a questionnaire, we obtained information concerning such variables as demographic data, previous academic record, information related to the subject and the degree of satisfaction with it, and the final mark obtained by the students in the subject. The parameters for each group of students were estimated separately and the goodness of fit of the proposed structural model was assessed. The data analysis showed a good fit with both data bases, but the set of estimated parameters differed in the two academic years under consideration.     

Statistics by Gender: Measures to Reduce Gender Bias in Agricultural Surveys

Statistics by gender has been the concern of policy makers in the recent past years. The demand on data disaggregated by gender has led the survey statistician to collect data and tabulate statistics by gender. In this paper, some measures will be suggested to avoid and reduce gender bias for data collection and tabulation in agricultural surveys.     

湖南省大学生体育课选课动因探析

本文采用问卷调查、数理统计、文献资料等研究方法,从心理学的角度,在调查大学生体育课选课现状的基础上,详细分析了大学生体育课选课中的外部诱因和内部动因,并针对其存在的问题,提出了几点相应对策。     

Multivariate likelihood ratio orderings between spacings of heterogeneous exponential random variables

Let X ₁, X ₂, ..., X _n be independent exponential random variables such that X _i has failure rate λ for i = 1, ..., p and X _j has failure rate λ^* for j = p + 1, ..., n, where p ≥ 1 and q = n − p ≥ 1. Denote by D _i:n (p,q) = X _i:n −X _i-1:n the ith spacing of the order statistics X _1:n ≤ X _2:n ≤ ... ≤ X _n:n , i = 1, ..., n, where X _0:n ≡ 0. The purpose of this paper is to investigate multivariate likelihood ratio orderings between spacings D _i:n (p,q), generalizing univariate comparison results in Wen et al.(J Multivariate Anal 98:743–756, 2007). We also point out that such multivariate likelihood ratio orderings do not hold for order statistics instead of spacings. Supported by National Natural Science Foundation of China, the Program for New Century Excellent Talents in University (No.: NCET-04-0569), and by the Knowledge Innovation Program of the Chinese Academy of Sciences (No.: KJCX3-SYW-S02).     

De bewerking van veldproeven volgens de methode van Knut Vik

Summary  (The treatment of field experiments by Knut Vik's method).
Agriculturists and statisticians have studied the problem, how to free the yields in a field experiment from the inequality of the soil. The method of the analysis of variance, due to the English statistician R. A. Fisher has taken an important place in the study of field experiments, so that other methods fell in the background.
The Norwegian agriculturist Knut Vik has suggested a method, which leads to good results without complicated calculations and without the knowledge of a great part of the mathematical statistics.
The mathematical foundation of this method is discussed in this article, which concludes, that the method of Knut Vik is of great importance for agriculturists, who don't want to perform intricate calculations.     

A Special Gen(d)re of Statistics: Roots,Development and Methodological Prospects of Gender Statistics

The very expression Gender Statistics calls for a double interpretation. It accounts for the popular mix‐up of statistical methodology with its typical products such as indexes, tables and graphs. At the same time it implies a broader and forward‐looking perspective, which is inspired by the increasing demand of gender sensitive statistical information coming from society, official agencies, economy. Gender statistics stands as a proper independent field of statistics with its own objectives and a variety of applications in social, human and life science. Concurrently an emerging necessity of appropriate equipment of methods and dissemination tools is noticeable. The paper tracks the roots and the historical development of gender statistics, reviews critically the existing indexes and practice and outlines methodological needs and research prospects.     

Downdating: Interdisciplinary Research Between Statistics and Computing

The purpose of this paper is to define and explain the meaning behind the term 'downdating' which has recently been introduced in the statistics literature from the computing sciences. We give a review of the historical background and describe the main statistical application areas which make reference to the terminology. Extensive references are provided to the very active current research effort on downdating in both the statistical and computing sciences and opportunities for development in statistical science are outlined.     

Karl Pearson's Influence in the United States

Karl Pearson, the founder of mathematical statistics, was the leading statistical researcher from the 1890s up to about 1920. His interests were wide-ranging and so his impact on statistics in the United States was also wide-ranging. Many American researchers came to University College London to study with him. Others studied his work from afar. In the United States, Pearsonian statistics first penetrated the academic landscape in biology. This was soon followed by the fields of economics and psychology. It was not until relatively late in Pearson's career that several American mathematicians took up statistics as a serious research topic.     

My Chancy Life as a Statistician

In this short article, I will attempt to provide some highlights of my chancy life as a statistician in chronological order spanning over 60 years, 1954 to present.     

On Becoming a Statistician—A Qualitative View

In this paper, we highlight some qualitative facets of the discipline of statistics and argue that a qualitative approach, in particular a qualitative methodology known as phenomenography, allows us to research important aspects of statistics pedagogy. We summarize several components of our recent research into students' conceptions of statistics, their learning of statistics, our teaching of statistics, and their perceptions of their future professional work. We have obtained this information on the basis of analyses of several series of interviews with students studying statistics, both as statistics majors and as service students. In each of these cases, the broadest views relate in some way to personal connection, growth, and change. In other words, they contain a strong ontological component—focusing on being or becoming a statistician—above and beyond the standard epistemological component—focusing on the knowledge required to do statistics. We discuss the importance of personal change in becoming a statistician, or an informed professional user of statistics, and investigate the pedagogical conditions under which such change is likely to occur.     

Karl Pearson in Russian Contexts

The confluence of statistics and probability into mathematical statistics in the Russian Empire through the interaction, 1910–1917, of A.A. Chuprov and A.A. Markov was influenced by the writings of the English Biometric School, especially those of Karl Pearson. The appearance of the Russian-language exposition of Pearsonian ideas by E. E. Slutsky in 1912 was instrumental in this confluence. Slutsky's predecessors in such writings (Lakhtin, Orzhentskii, and Leontovich) were variously of mathematical, political economy, and biological backgrounds. Work emanating from the interpolational nature of Pearson's system of frequency curves was continued subsequently through the work of Markov, Bernstein, Romanovsky, and Kravchuk (Krawtchouk), who laid a solid probabilistic foundation. The correlational nature in the interpolational early work of Chebyshev, and work of the English Biometric School in the guise of linear least-squares fitting exposited as the main component of Slutsky's book, was developed in population as well as sample context by Chuprov. He also championed the expectation operation in providing exact relations between sample and population moments, in direct interaction with Karl Pearson. Romanovsky emerges as the most adaptive and modern mathematical statistician.     

A Conversation with Jean‐Louis Bodin

Jean‐Louis Bodin has had a distinguished career as an official statistician in the French and European statistical systems, where he has been working for 40 years. Born in 1941 in Bordeaux, the capital city of one of the most famous vineyards in the world, he became graduate of two French prestigious schools, the Ecole Polytechnique in 1963, then the ENSAE (Ecole Nationale de la Statistique et de l'Administration Economique) in 1966. After having spent 20 years in different positions in the French Statistical System, he dedicated the last 20 years of his career to international relations in official statistics and cooperation for strengthening statistical capacities of transition and developing countries. In particular, he was one of the main drafters of the UN Resolution on Fundamental Principles for Official Statistics and of the African Statistical Charter. He is also known for having created AFRISTAT, the Economic and Statistical Observatory of Sub‐Saharan African countries. He was also during years one of the French representatives in the UN Statistical Commission, the UN Conference of European Statisticians and the Statistical Committee Programme of the European Union. Jean‐Louis Bodin has played for 40 years a very active role in national and international statistical societies. He served on many disparate positions in the ISI family: executive director of the International Association of Survey Statisticians from 1981 to 1985 under the successive chairmanships of Gérard Théodore and Leslie Kish, founding member in 1985 with Vera Nyitrai of the International Association for Official Statistics and president of the Association from 1989 to 1991, secretary‐general of the National Organizing Committee of the 47th ISI Session held in Paris in August 1989, Chair of the Programme Coordinating Committee of the 50th ISI Session held in Beijing in August 1995, ISI president‐elect then president from 1997 to 2001, president of the Jury of the Mahalanobis Prize from 2002 to 2005. He was also president of the Société de Statistique de Paris in 1994. He received the certificate of Fellow of the American Statistical Association in 1996 and was a member of the ASA Committee for International Relations in Statistics from 1993 to 1997. He was bestowed in 2006 as a Chevalier de la Légion d'Honneur (Knight of the Legion of Honour) in France and in 1997 as a Kawaleski Orderu Zas?ugi(Knight of the Order of Merit) in Poland. He received the Medal of Statistical Merit in Vietnam in 2003 and the African Statistical Award bestowed by the UN Economic Conference for Africa in 2012. This conversation was held in June 2013 with Gilbert Saporta in Paris. Gilbert Saporta: Welcome to this interview, Jean‐Louis. I'm delighted that you could spend some time with me to discuss your career, your achievements and your views on some aspects of official statistics. It appears that your professional career as a French official statistician and your participation in ISI activities were tightly linked.

     

An Interview with Chris Skinner

Chris Skinner was born in London on 12 March 1953. He completed a BA in mathematics in 1975 at the University of Cambridge. He then obtained an MSc degree in statistics from the London School of Economics and Political Science (LSE) in 1976 and worked as an assistant statistician in the Central Statistical Office for 1 year. After working as a research assistant in LSE from 1977 to 1978, he joined the University of Southampton as a lecturer in 1978, where he earned a PhD in social statistics in 1982. He remained at the University of Southampton, where he became a senior lecturer in 1989 and professor of statistics in 1994. While serving as the head of his department from 1997 to 2000, he played a crucial role in the creation of an MSc programme in official statistics in 1999. In 2011, he returned to the LSE, where he currently holds the position of professor of statistics. Chris is the author of over 80 peer‐reviewed articles in statistical journals and the co‐editor of two influential books on the analysis of survey data. He made significant research contributions covering areas that include the analysis of survey data, inference in the presence of non‐response and measurement errors and statistical disclosure control. He served on several advisory committees, including the Statistical Methods Advisory Committee at Statistics Canada (from 2000 to 2011) and the National Statistics Methodology Advisory Committee in the United Kingdom (from 2001 to 2010). He has received numerous awards and honors for his outstanding contributions to survey sampling and social statistics. He is a Fellow of the American Statistical Association, Fellow of the British Academy and a Fellow of the Academy of Social Sciences. In 2009, he received the West Medal from the Royal Statistical Society for contributions to social statistics, and in 2010, he was made a Commander of the Most Excellent Order of the British Empire. In 2019, he also received the Waksberg award to recognize his contributions to survey methodology. The following conversation took place at LSE on 21 May 2019.     

International Comparisons of Public Sector Performance

Abstract

Measuring and comparing the overall performance of countries' public sectors requires agreement on definitions and objectives of government. I argue that such an agreement is about finding a consensus rather than about finding better definitions. Measuring government requires a number of leaps of faith, where certain definitions, assumptions and statistics are accepted as good enough for measurement and comparison. The political science and economic research community have a different tradition of dealing with such agreements and leaps of faith, and this is reflected in their approaches to measuring and comparing the performance of public sectors. The implications of these traditions are particularly visible in the usefulness of measurement and indicators for policy makers.     

General‐to‐Specific Model Selection Procedures for Structural Vector Autoregressions*

Structural vector autoregressive (SVAR) models have emerged as a dominant research strategy in empirical macroeconomics, but suffer from the large number of parameters employed and the resulting estimation uncertainty associated with their impulse responses. In this paper, we propose general‐to‐specific (Gets) model selection procedures to overcome these limitations. It is shown that single‐equation procedures are generally efficient for the reduction of recursive SVAR models. The small‐sample properties of the proposed reduction procedure (as implemented using PcGets) are evaluated in a realistic Monte Carlo experiment. The impulse responses generated by the selected SVAR are found to be more precise and accurate than those of the unrestricted VAR. The proposed reduction strategy is then applied to the US monetary system considered by Christiano, Eichenbaum and Evans (Review of Economics and Statistics, Vol. 78, pp. 16–34, 1996) . The results are consistent with the Monte Carlo and question the validity of the impulse responses generated by the full system.     

Segmenting the Belgian charitable sector: The impact of environmental factors on households' generosity

Research on charitable giving has known a renewed interest over the last years. Despite a recent evolution, the literature remains predominantly Anglo‐Saxon, and studies are consequently conducted in societies marked by a strong charitable giving culture. In that respect, donors are generally considered as isolated individuals, and the impact of social and environmental factors such as public policies, institutional specificities, and punctual events is often underestimated. Moreover, research on generosity often suffers from the absence of reliable data, free of desirability bias. Based on fiscal data of tax returns and gift tax returns provided by the official Belgian statistics bureau, this research investigates individual donating behaviors while considering the influence of environmental determinants on generosity. More specifically, we empirically assess the generosity of Belgian households over a period of 8 years marked by natural disasters, massive calls for public generosity, and changes in tax policies. Among other things, we qualify the results of previous research on the role of age and open the debate on the role of household composition as a variable for segmenting donors. Finally, we propose leads for future research in order to stimulate further academic effort on the topic.     

Estimation of the parameters of log-gamma distribution using order statistics

In this work we propose a technique of estimating the location parameter μ and scale parameter σ of log-gamma distribution by U-statistics constructed by taking best linear functions of order statistics as kernels. The efficiency comparison of the proposed estimators with respect to maximum likelihood estimators is also made.     

Regression‐based Tests for a Change in Persistence*

We show that the minimal forward (reverse) recursive unit tests of Banerjee, Lumsdaine and Stock [Journal of Business and Economics Statistics (1992) Vol. 10, pp. 271–288] are consistent against the alternative of a change in persistence from I(0) to I(1) [I(1) to I(0)]. However, these statistics are also shown to diverge for series which are I(0) throughout. Consequently, a rejection by these tests does not necessarily imply a change in persistence. We propose a further test, based on the ratio of these statistics, which is consistent against changes either from I(0) to I(1), or vice versa, yet does not over‐reject against constant I(0) series. Consistent breakpoint estimators are proposed.