The archive.

Assembled from roughly three hundred pre-war price series across England, Germany, the United States and beyond, this statistical study argues that the trade cycle cannot be read off any single index number. Published in Vienna by Springer with a foreword by Oskar Morgenstern and backing from the Austrian Institute for Trade Cycle Research and the London School of Economics, Tintner applies Anderson's Variate Difference Method and moving averages to decompose each series into trend, cyclical and seasonal components. His finding is that prices move unevenly — metals and interest rates on their own rhythm, textiles and foodstuffs on another — so that the notion of a general price level dissolves. He offers the results not as proof of causes but as ordered material for the theorist, cautiously favouring the monetary cycle theories of Wicksell, Mises and Hayek.

We consider time, on the contrary, only as a kind of auxiliary variable, which we must eliminate in order to bring out the economic relations.

For Gerhard Tintner, reliable confirmation can matter more than striking novelty. His 1936 review of Allen and Bowley’s Family Expenditure praises their use of household budgets to connect demand theory with statistical evidence, while questioning one simplifying assumption: a linear preference scale maintained throughout the investigation. Where that assumption appears to fail, he wants statistical tests, not merely a workable approximation. This brief review offers a concrete view of Tintner’s standards for econometric research: close knowledge of the data, explicit testing of theoretical assumptions, and economic interpretation of numerical results. His praise turns on what the calculations establish about household spending—not on mathematical sophistication alone.

What makes a mathematical model economically persuasive rather than merely tractable? In this review of Charles Frederick Roos’s Dynamic Economics, Gerhard Tintner welcomes new ways of analysing time lags and demand while questioning the assumptions that make their calculation possible. Linear demand curves and quadratic costs may be useful approximations, he argues, but conclusions drawn from them need explicit qualification. His sympathy for Roos’s methods sharpens rather than softens his criticism: analyses of particular markets cannot by themselves explain economy-wide employment, expectations, or cyclical fluctuations. The review offers a concrete encounter with the tension between mathematical innovation and economic justification, showing why Tintner values dynamic methods yet asks for stronger theoretical constraints and closer attention to systemic interdependence.

Economic statistics can guide governments and businesses without giving researchers a mandate to make policy. That distinction anchors Gerhard Tintner’s 1936 article on international business-cycle research, written in connection with a congress of research institutes in Vienna. Tintner treats these institutes as necessary responses to economies too complex to understand through personal experience alone, while insisting that their figures remain probabilistic and require economic interpretation. His account brings statistical methods into contact with the Austrian institute’s theoretical commitments, showing why neither data collection nor theory can suffice independently. Readers can discover a concrete conception of research cooperation: shared methods and comparable reports should improve the evidence available for international policy, while independence from state influence and private interests protects the institutes’ capacity to report objectively.

Government price fixing poses different problems depending on who competes with whom. In this brief review of Arnold Horwitz’s doctoral thesis, Gerhard Tintner values precisely that comparative approach: minimum prices, maximum prices, and direct price fixation examined across competitive and monopolistic markets. He places Horwitz’s analysis at the intersection of Mises’s work on price regulation and Stackelberg’s account of market organization, while noting its engagement with English and American scholarship. Tintner’s praise also marks a boundary: imperfect competition, selling costs, and price discrimination remain subjects for further investigation. The review offers a compact critical appraisal of what a differentiated theory of price controls should address, rather than an account of the effects of particular controls.

What mathematics should economists learn, and how should it be taught? In this 1939 review of R. G. D. Allen’s Mathematical Analysis for Economists, Gerhard Tintner values economic applications over the physical examples customary in calculus textbooks. Constrained optimization is his telling case: a technique central to economics receives the sustained attention economists need. His praise also draws a useful distinction between teaching mathematical tools through consumer choice, monopoly, and production, and presenting a continuous economic theory. Yet the book’s predominantly static approach leaves dynamic problems underrepresented. This brief review offers a concrete view of Tintner’s standards for graduate training: mathematical instruction should prepare economists to follow current research, while its omissions should guide their supplementary study.

Profit maximization need not settle a price when a sole buyer faces a sole seller. In this theoretical note, Gerhard Tintner makes that difficulty concrete through a steel producer purchasing iron ore from a monopolist supplier. His distinctive question is when buyer control, seller control, and joint profit maximization yield the same outcome. The conditions for their agreement prove exceptional: ordinarily, static analysis establishes a bargaining range rather than a unique input price. By tracing how price-setting authority changes the result, readers can distinguish the constraints imposed by demand and production costs from the distribution of gains between the parties. Tintner’s extension to union–employer wage bargaining sharpens the stakes: on his account, bargaining power, shaped especially by political forces, determines what profit-maximizing equations leave unresolved.

Discarding observations can make a statistical test more defensible. In this 1939 mathematical note, Gerhard Tintner confronts a difficulty in time-series analysis: successive differencing may remove a smooth trend, but it also creates correlations even when the original errors are independent. His response is to select differences built from disjoint observations, allowing their variances to be compared using familiar significance tests. He applies the same selection principle to lagged products in deriving a serial-covariance distribution. The note offers a precise encounter with the trade-off between retaining information and securing a tractable sampling distribution. Readers can see how the observations chosen determine which tests become available—and why the assumptions of normality, independence and a sufficiently smooth trend matter.

What makes consumer-credit exercises useful in teaching financial mathematics? In this brief review, Gerhard Tintner assesses Charles H. Mergendahl and Le Baron R. Foster’s pamphlet as a supplement to high-school and college textbooks. He distinguishes an adequate introduction to credit concepts and calculations from the exercises themselves, which he finds thoughtfully designed, interesting and stimulating. The review offers a concise curricular judgement: its interest lies in Tintner’s emphasis on the quality of practice problems, rather than merely their number or subject matter.

Can a demand curve measured across decades remain meaningful if the relationship it describes is itself changing? In this review essay on Henry Schultz’s 1938 treatise, Gerhard Tintner combines admiration for empirical demand research with a pointed challenge to its static assumptions. Dividing historical data into separate periods, he argues, yields successive snapshots without explaining how demand changes. His alternative allows both the position and slope of a demand curve to vary, ideally in response to economically meaningful factors such as population, expectations, and tastes. Equally crucial is testing whether the unexplained residuals are random before trusting statistical significance. The essay offers a concrete encounter with the tension between elegant estimation and economic change—and with Tintner’s insistence that economic theory and statistical diagnosis must develop together.

Gerhard Tintner’s brief review of S. Koller’s Graphische Tafeln zur Beurteilung statistischer Zahlen judges the book by its usefulness in statistical calculation. He identifies its nomograms—graphical aids covering several statistical distributions—and singles out the well-chosen practical examples as a help to users. The review offers a compact recommendation grounded in usability rather than theoretical novelty, showing precisely what Tintner valued in this medical statistician’s handbook.

A statistical pattern is not yet an economic explanation—and a plausible model fit is not yet a tested result. These distinctions sharpen Gerhard Tintner’s brief 1940 review of Herman Wold’s study of stationary time series. Tintner admires Wold’s mathematical framework but questions what its applications to wheat prices and Swedish living costs actually establish. His reservation is specific: without significance tests, the validity of the results cannot be assessed. The review offers a compact encounter with an economist’s demands on mathematical statistics, showing why theoretical advances in describing fluctuations still require methods of inference before they can support empirical conclusions.