Stephen T. Ziliak (born October 17, 1963) is an American professor of economics whose research and essays span disciplines from statistics and beer brewing to medicine and poetry. He is currently a faculty member of the Angiogenesis Foundation, conjoint professor of business and law at the University of Newcastle in Australia, and professor of economics at Roosevelt University in Chicago, Illinois. He previously taught for the Georgia Institute of Technology, Emory University, and Bowling Green State University. Much of his work has focused on welfare and poverty, rhetoric, public policy, and the history and philosophy of science and statistics. [1] Most known for his works in the field of statistical significance, Ziliak gained notoriety from his 1996 article, "The Standard Error of Regressions", [2] from a sequel study in 2004 called "Size Matters", [3] and for his University of Michigan Press best-selling and critically acclaimed book The Cult of Statistical Significance: How the Standard Error Costs Us Jobs, Justice, and Lives (2008) [4] all coauthored with Deirdre McCloskey. [3] [5] [6] [7] [8]
Ziliak received a Bachelor of Arts in Economics from Indiana University Bloomington, a PhD in economics, and a PhD Certificate in the Rhetoric of the Human Sciences, both from the University of Iowa. While at University of Iowa, he served as resident scholar in the Project on Rhetoric of Inquiry, where he met among others Steve Fuller, Bruno Latour, and Wayne C. Booth, and co-authored the now-famous paper "The Standard Error of Regressions".
Following the completion of his PhD degrees, he has taught at Bowling Green State University, Emory University, Georgia Institute of Technology, and (currently) Roosevelt University, and he has been a visiting professor at more than a dozen other leading universities, law schools, and medical centers across the United States and Europe. In 2002 he won the Helen Potter Award for Best Article in Social Economics ("Pauper Fiction in Economic Science: `Paupers in Almshouses' and the Odd Fit of Oliver Twist"). [9] In that same year at Georgia Tech he won the "Faculty Member of the Year" award and in 2003 he was voted "Most Intellectual Professor". [10]
After college, but prior to his academic career, Ziliak served as county welfare caseworker and, following that, labor market analyst for the Indiana Department of Workforce Development, both in Indianapolis.
While at University of Iowa, Ziliak became friends with his dissertation adviser, Deirdre McCloskey. He and McCloskey shared an interest in the fields of rhetoric and statistical significance — namely how the two concepts merge in modern economics. Ziliak had discovered one big cost of the "significance mistake" early on in his job with Workforce Development, in 1987. By U.S. Department of Labor policy he learned he was not allowed to publish black youth unemployment rates for Indiana's labor markets: "not statistically significant," the Labor Department said, meaning the p-values exceeded 0.10 (p less than or equal to 0.10 was the Labor Department's bright line cut-off for publishing estimates). [11]
In their paper, "The Standard Error of Regressions," McCloskey and Ziliak argue that econometrics greatly over-values and vastly misuses statistical significance testing — Student's t-test. They claim econometricians rely too heavily on statistical significance, but too little on actual economic significance. Significance does not mean importance, and lack of significance does not mean unimportant. The paper also reviews and critiques over 40 years' worth of published papers in economic journals to see if and how ambiguity and misuse of statistical significance affect the author's article.
In a reply to critics, Ziliak and McCloskey did a follow-up study of the 1996 research and found that the significance problem had grown even larger, causing false inferences and decisions in from 70% in the 1980s to 80% of the 1990s articles published in the American Economic Review. "Size Matters: The Standard Error of Regressions in the American Economic Review" was presented by Ziliak at the 2004 meetings of the American Economic Association, in a standing-room only plenary session with over 350 economists and journalists, chaired by Nobel laureate Kenneth Arrow. [6] The article and a reply to critics ("Significance Redux") were published in a special issue of the Journal of Socio-Economics, with comments from Nobel laureate Clive Granger, Arnold Zellner, Edward Leamer, Gerd Gigerenzer, Jeffrey Wooldridge, Joel Horowitz and a half dozen others. [12] In 2004 "Size Matters" also inspired a comment from Nobel laureate Thomas Schelling. [13] Published cooperatively at the same time in Econ Journal Watch (2004), "Size Matters" maintains its rank as one of the top-most downloaded articles in that journal's history (over 25,000 complete downloads as of November 2015).
Ziliak was a lead author on the twenty-four statistician team which crafted in 2015-2016 the historic "American Statistical Association Statement on Statistical Significance and P-Values," edited by Ronald Wasserstein and Nicole Lazar. [14] [15] [16]
His article "How Large are Your G-values? Try Gosset's Guinnessometrics When a Little 'p' Is Not Enough" was published in a follow-up special issue of The American Statistician (2019 73 sup1), a major re-think of statistical testing, estimation, and reporting in "A world beyond p<0.05" for which Ziliak also served as associate editor.
His book, The Cult of Statistical Significance: How the Standard Error Costs Us Jobs, Justice, and Lives (2008) challenges the history, philosophy, and practice of all the testing sciences, from economics to medicine, and has been widely reviewed in journals and the media. [17] [18] [19] [20] [21] [22] [23] [24] [25] It was the beer-brewing Gosset aka "Student", Ziliak discovered in the archives, not the biologist R. A. Fisher, who provided the firmer foundation for modern statistics, decisions, and experimental design. The book featured in a 2011 U.S. Supreme Court case, Matrixx Initiatives v. Siracusano et al., wherein the justices unanimously decided against using statistical significance as a standard for adverse event reporting in U.S. securities law. [26] Ziliak and McCloskey were invited to submit to the court a brief of amici curiae ("friends of the court") wherein they explain the most important differences between economic, legal, and human significance versus mere statistical significance. Ziliak wrote about the case for Significance magazine, inspiring published letters from A.W.F. Edwards and Dennis Lindley, who later befriended Ziliak in correspondence over W.S. Gosset and R.A. Fisher. [26] [27]
In 2001, while teaching at Georgia Tech, Ziliak rediscovered his appreciation for haiku poetry. Haiku are short lyric verse with a budget constraint, conventionally arranged in three lines of 17 sounds (5-7-and-5). He had learned about the medieval Japanese art form back in the 1980s, from a friend in Indianapolis who happened to be the eminent African American poet Etheridge Knight. Teaching large-section courses to hundreds of students, Ziliak was at the same time seeking a low-cost way to help students connect their own observations and feelings to the economics textbook and economy itself. Economics and haiku overlap at the level of principles, he discovered, yet give something more in combination, such as feelings. [28] Students reacted positively. "Haiku economics" was born, and first published in 2002. [29] Ziliak's most famous haiku is:
Invisible hand;
mother of inflated hope,
mistress of despair! [30]
His invisible hand haiku has been erroneously credited to Etheridge Knight and Matsuo Basho. [31] (For example, in Kalle Lasn's Meme Wars: The Creative Destruction of Neoclassical Economics.) In 2008 and 2009 Ziliak's work on haiku economics gained international attention following a series of articles published in the Wall Street Journal, The Economist, The Chronicle of Higher Education, and National Public Radio. [32] [33] [34] [35] [36] In 2011 he published an essay in Poetry magazine, "Haiku Economics: On Money, Metaphor, and the Invisible Hand," [37] which the editors of Poetry cite as the most-read essay in 2011 and in the history of their non-fiction "The View from Here" column, which has featured essays by Richard Rorty, Christopher Hitchens, and many others. [38]
Ziliak's current projects include Guinnessometrics, [39] that is, a wholesale rethinking of experimental philosophy and econometric practice after William S. Gosset (1876-1937) aka "Student", [40] the inventor of "Student's" t and celebrated Head Brewer of Guinness. [39] [41] Ziliak's Guinnessometrics was twice featured on BBC Radio 4's "More or Less" program, hosted by Tim Harford, and later in many other media such as The Wall Street Journal Europe, Financial Times, Salon and The Washington Post. [42] Guinnessometrics argues that randomization plus statistical significance does not equal validity. Validity is proven by other means, including deliberately balanced and stratified experiments, small series of independent and repeated samples controlling for real not merely random error, and an economic approach to the logic of uncertainty.
His work showing the history and power of balanced over randomized controlled trials, [43] rival techniques which Ziliak traces back to the early 1900s and the Guinness Brewery in Dublin, has been noted by Tim Harford, Casey Mulligan, and others for its deep challenge to randomized field experiments after John List, Steve Levitt, Esther Duflo, and others. [44] [45] [46] [47] In July 2008 Ziliak was invited by the International Biometric Society and the Irish Statistical Association to present his work in Dublin on "Guinnessometrics: The Economic Foundation of Student's t," in celebration of the 100th anniversary of W.S. Gosset's aka "Student's" t-distribution and test. [48] Standing on stage with Sir David Cox and Stephen Senn, the biostatistician and president of the American Statistical Association Chicago Chapter Borko Jovanovic quipped that Ziliak "looked, at first, like a little kid walking around the British Museum. Then he began to speak, which he could probably do for two weeks straight". [49] In 2010 Ziliak and British statistician Stephen Senn exchanged views in The Lancet. [50] [51]
Ziliak's other contributions include a competitive learning game he calls renganomics. [52] Renganomics is a combination of economic science with an ancient Japanese poetic form called renga. The idea is to create a spontaneous, collaboratively written poem about the economy and economic science in the form of linked classical haiku poems (5-7-5 sound counts) followed by two lines of 7 sounds (14 sounds for the couplet). The renga form, which gained the attention of Octavio Paz, is created by writing a verse and then passing the poem on to the next person in the circle, given a predetermined time constraint and stakes. The genre challenges notions of the spontaneous order and central planning alike, while allowing both policies to air ideas, desires, and complaints.
In May 2015 Ziliak produced with his students at Roosevelt University an economics rap video, "Fear the Economics Textbook (Story of the Next Crook)". [52] The video, featured in Inside Higher Ed, The National Review, Rethinking Economics [53] and elsewhere, is in part a statement of Ziliak's pluralist and dialogical teaching philosophy and view of history, and at the same time a reply to the popular Keynes-Hayek rap videos. [54] [55] [56]
On the strength of his dissertation, "Essays on Self-Reliance: The United States in the Era of Scientific Charity," he was appointed associate editor for the millennial edition of Historical Statistics of the United States: Colonial Times to the Present (General Eds. S. Carter, R. Sutch, et al.) [57] [58] Ziliak argued in his dissertation and in a series of articles against the 1996 welfare reform act (PRWORA). He argued on the basis of novel econometric and social historical evidence he produced on previous, 19th century attempts to abolish welfare and to replace it with private charity ("scientific charity", so called). Economic theory of welfare is distorted, he argued, by a "Malthusian vice" and "Contradiction of compassion". Private charity expanded more than previous observers predicted. But labor market outcomes were about the same as one finds in late 20th century welfare programs. [59] [60] His comparative historical research has challenged left and right both, from Stephen Pimpare to the Cato Institute, and has featured in encyclopedias on social work. [61] [62] [63] [64] [65] [66] [67] [68] [69]
Ziliak's historical research on previous attempts to privatize welfare for the poor has questioned the virtue-ethical philosophies of Victorians, Old and New, from Herbert Spencer to Gertrude Himmelfarb. In The Bourgeois Virtues (2006, xviii) his former dissertation adviser and long-time coauthor Deirdre N. McCloskey thanks Ziliak (together with Arjo Klamer and Helen McCloskey, Deirdre's mother) for "disagreeing with me about the bourgeois virtues". The Cult of Statistical Significance drew attention to the ethics of statistical significance testing and the frequently large yet neglected consequences for human and other life when the test is misused and misinterpreted as Ziliak and McCloskey have documented it frequently is. Haiku economics is fundamentally an attempt to bring feelings and individual experience back inside the dismal science. In his 2011 essay on "Haiku Economics," published in Poetry magazine, Ziliak noted the influence of Adam Smith's The Theory of Moral Sentiments and John Stuart Mill's Autobiography. More recently, In a series of papers comparing Gosset's deliberately balanced experimental designs with Fisher's randomized, Ziliak argues that most randomized controlled trials lack both ethical and economic justification. His paper "The Unprincipled Randomization Principle in Economics and Medicine" (with Edward Teather-Posadas), published in the Oxford Handbook of Professional Economic Ethics (2015), argues that most randomized controlled trials (RCTs) fail every ethical code, from Smith's "impartial spectator" and Pareto efficiency to Rawls's difference principle, except possibly "vulgar utilitarianism" (page 436), an "ethic" which even most economists reject.
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: CS1 maint: DOI inactive as of January 2025 (link)Analysis of variance (ANOVA) is a collection of statistical models and their associated estimation procedures used to analyze the differences between groups. It uses F-test by comparing variance between groups and taking noise, or assumed normal distribution of group, into consideration by dividing by variance between elements in a group. ANOVA was developed by the statistician Ronald Fisher. ANOVA is based on the law of total variance, where the observed variance in a particular variable is partitioned into components attributable to different sources of variation. In its simplest form, ANOVA provides a statistical test of whether two or more population means are equal, and therefore generalizes the t-test beyond two means. In other words, the ANOVA is used to test the difference between two or more means.
Econometrics is an application of statistical methods to economic data in order to give empirical content to economic relationships. More precisely, it is "the quantitative analysis of actual economic phenomena based on the concurrent development of theory and observation, related by appropriate methods of inference." An introductory economics textbook describes econometrics as allowing economists "to sift through mountains of data to extract simple relationships." Jan Tinbergen is one of the two founding fathers of econometrics. The other, Ragnar Frisch, also coined the term in the sense in which it is used today.
Statistics is the discipline that concerns the collection, organization, analysis, interpretation, and presentation of data. In applying statistics to a scientific, industrial, or social problem, it is conventional to begin with a statistical population or a statistical model to be studied. Populations can be diverse groups of people or objects such as "all people living in a country" or "every atom composing a crystal". Statistics deals with every aspect of data, including the planning of data collection in terms of the design of surveys and experiments.
William Sealy Gosset was an English statistician, chemist and brewer who served as Head Brewer of Guinness and Head Experimental Brewer of Guinness and was a pioneer of modern statistics. He pioneered small sample experimental design and analysis with an economic approach to the logic of uncertainty. Gosset published under the pen name Student and developed most famously Student's t-distribution – originally called Student's "z" – and "Student's test of statistical significance".
In statistical hypothesis testing, a result has statistical significance when a result at least as "extreme" would be very infrequent if the null hypothesis were true. More precisely, a study's defined significance level, denoted by , is the probability of the study rejecting the null hypothesis, given that the null hypothesis is true; and the p-value of a result, , is the probability of obtaining a result at least as extreme, given that the null hypothesis is true. The result is statistically significant, by the standards of the study, when . The significance level for a study is chosen before data collection, and is typically set to 5% or much lower—depending on the field of study.
In statistics, self-selection bias arises in any situation in which individuals select themselves into a group, causing a biased sample with nonprobability sampling. It is commonly used to describe situations where the characteristics of the people which cause them to select themselves in the group create abnormal or undesirable conditions in the group. It is closely related to the non-response bias, describing when the group of people responding has different responses than the group of people not responding.
Student's t-test is a statistical test used to test whether the difference between the response of two groups is statistically significant or not. It is any statistical hypothesis test in which the test statistic follows a Student's t-distribution under the null hypothesis. It is most commonly applied when the test statistic would follow a normal distribution if the value of a scaling term in the test statistic were known. When the scaling term is estimated based on the data, the test statistic—under certain conditions—follows a Student's t distribution. The t-test's most common application is to test whether the means of two populations are significantly different. In many cases, a Z-test will yield very similar results to a t-test because the latter converges to the former as the size of the dataset increases.
The McCloskey critique refers to a critique of post-1940s "official modernist" methodology in economics, inherited from logical positivism in philosophy. The critique maintains that the methodology neglects how economics can be done, is done, and should be done to advance the subject. Its recommendations include use of good rhetorical devices for "disciplined conversation."
Deirdre Nansen McCloskey is an American economist and academic. Since 2023 she has been a Distinguished Scholar and holder of the Isaiah Berlin Chair in Liberal Thought at the Cato Institute in Washington, D.C. From 2000 to 2015, she taught at the University of Illinois at Chicago, where she was Distinguished Professor of Economics History, and Professor of English and Communication. During those years, she taught economic history at the University of Gothenburg, economics at the University of the Free State, and philosophy at Erasmus University Rotterdam.
Economic methodology is the study of methods, especially the scientific method, in relation to economics, including principles underlying economic reasoning. In contemporary English, 'methodology' may reference theoretical or systematic aspects of a method. Philosophy and economics also takes up methodology at the intersection of the two subjects.
Statistics, in the modern sense of the word, began evolving in the 18th century in response to the novel needs of industrializing sovereign states.
In statistical analysis, the rule of three states that if a certain event did not occur in a sample with n subjects, the interval from 0 to 3/n is a 95% confidence interval for the rate of occurrences in the population. When n is greater than 30, this is a good approximation of results from more sensitive tests. For example, a pain-relief drug is tested on 1500 human subjects, and no adverse event is recorded. From the rule of three, it can be concluded with 95% confidence that fewer than 1 person in 500 will experience an adverse event. By symmetry, for only successes, the 95% confidence interval is [1−3/n,1].
In statistics, the t-statistic is the ratio of the difference in a number’s estimated value from its assumed value to its standard error. It is used in hypothesis testing via Student's t-test. The t-statistic is used in a t-test to determine whether to support or reject the null hypothesis. It is very similar to the z-score but with the difference that t-statistic is used when the sample size is small or the population standard deviation is unknown. For example, the t-statistic is used in estimating the population mean from a sampling distribution of sample means if the population standard deviation is unknown. It is also used along with p-value when running hypothesis tests where the p-value tells us what the odds are of the results to have happened.
Anil K. Bera is an Indian-American econometrician. He is Professor of Economics at University of Illinois at Urbana–Champaign's Department of Economics. He is most noted for his work with Carlos Jarque on the Jarque–Bera test.
Meta-regression is a meta-analysis that uses regression analysis to combine, compare, and synthesize research findings from multiple studies while adjusting for the effects of available covariates on a response variable. A meta-regression analysis aims to reconcile conflicting studies or corroborate consistent ones; a meta-regression analysis is therefore characterized by the collated studies and their corresponding data sets—whether the response variable is study-level data or individual participant data. A data set is aggregate when it consists of summary statistics such as the sample mean, effect size, or odds ratio. On the other hand, individual participant data are in a sense raw in that all observations are reported with no abridgment and therefore no information loss. Aggregate data are easily compiled through internet search engines and therefore not expensive. However, individual participant data are usually confidential and are only accessible within the group or organization that performed the studies.
There have been many criticisms of econometrics' usefulness as a discipline and perceived widespread methodological shortcomings in econometric modelling practices.
Jack L. Amariglio is a North American heterodox economist. He is well known for his work on economic history, class analysis, and on economic methodology and postmodernism in economics.
Bourgeois Dignity: Why Economics Can’t Explain the Modern World is a 2010 book by economist and social theorist Deirdre McCloskey that is the second of a three-book series laying out the thesis that a change in the rhetoric surrounding the value of business, innovation, and entrepreneurship was the main factor responsible for the takeoff of economic growth in Northwest Europe in the late 18th century. Bourgeois Dignity focuses on arguing that there was a fairly significant and unprecedented takeoff of economic growth, and that existing explanations for this takeoff are inadequate. McCloskey provides a rough outline for why she thinks that the changes in rhetoric surrounding the dignity of business and markets were crucial, but leaves the elaborate case for later books in the series.
In statistics, a sequence of random variables is homoscedastic if all its random variables have the same finite variance; this is also known as homogeneity of variance. The complementary notion is called heteroscedasticity, also known as heterogeneity of variance. The spellings homoskedasticity and heteroskedasticity are also frequently used. “Skedasticity” comes from the Ancient Greek word “skedánnymi”, meaning “to scatter”. Assuming a variable is homoscedastic when in reality it is heteroscedastic results in unbiased but inefficient point estimates and in biased estimates of standard errors, and may result in overestimating the goodness of fit as measured by the Pearson coefficient.
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