Herman K. van Dijk is affiliated with the Faculty of Economics and Business Administration, VU University Amsterdam, as professor of econometrics, and also as professor emeritus with the Econometric Institute, Erasmus University Rotterdam. He has been director of the Tinbergen Institute, Director of the Econometric Institute, and professor of Econometrics with a Personal Chair at Erasmus University Rotterdam. He has also been a visiting Fellow and a visiting professor at Cambridge University, the Catholic University of Louvain, Harvard University, Duke University, Cornell University, and the University of New South Wales. He is Fellow of the International Society of Bayesian Analysis, Senior Fellow at the Rimini Center for Economic Analysis, and Honorary Fellow of the Tinbergen Institute. He received the Savage Prize for his PhD dissertation and is listed in the Journal Econometric Theory in the Econometricians Hall of Fame amongst the top ten European econometricians. His research interests cover a range of topics in econometrics with a common theme: Simulation-based Bayesian Econometric Techniques for Inference, Forecasting and Decision analysis. For more information about the author and his research activities you can visit [[not sure if this is too informal]] his website: http://people.few.eur.nl/hkvandijk/ Jan Tinbergen (1903-1994) was awarded the first Nobel Prize in Economics in 1969 together with Ragnar Frisch: “for having developed and applied dynamic models for the analysis of economic processes”.
Tinbergen’s motivation and basic approach to econometrics The desire to combat the socio-economic consequences of the Great Depression of the 1930s was Tinbergen's motivation for using econometric modeling. His approach towards studying periodic economic upswings and downswings contrasted with previous approaches to business cycle research. After a 19th-century undertaking by Juglar (1862) ascribing the recurrent business crises in Europe and North America to credit crises, and Jevons's (1884) study pointing to agricultural production cycles connected with sunspot numbers, several research projects in the early 20th century were devoted to the construction of so-called business cycle barometers. The purpose was to measure economic fluctuations through a particular index (or set of indices) with the aim of giving warning signals for turning points that would lead to a depression. An example was the Harvard Index of Business Conditions, known as the Harvard Barometer, constructed by a team led by Persons (1919). Another well-known descriptive approach to the business cycle during this period was initiated by Mitchell (1913). Mitchell’s work was followed by that of Yule (1927) and Slutzky (1927), who suggested that the cumulative effect of random shocks could be the cause of cyclical patterns in economic variables. Frisch (1933) applied these ideas, introducing econometric models in which impulse propagation mechanisms led to business cycles. However useful it could be as a starting point, Tinbergen criticized descriptive analysis as being too vague for use in policy preparation, and started a quantitatively oriented research program to explore the possible economic causes of the periodic upswings and downswings in economic activity. In an earlier theoretical study, Aftalion (1927) had argued that lags in an economic model could generate cyclical variation in economic activity. Following this argument, Tinbergen specified a first simple case using a system of difference equations to express lagged responses of supply to price changes in a market for a single good. He noted that the systematic fluctuations that could arise in such a system had been observed in an empirical study of the pork market by the German economist Hanau (1928), a phenomenon that became known as the ‘cobweb model’. Tinbergen subsequently generalized the specification of dynamic equations with lagged adjustment processes to macroeconomic settings, arguing that fluctuations in components of national product, such as investment and consumption expenditures, would lead to business cycle fluctuations in general economic activity. In 1936 he published the first applied macroeconometric model for the Netherlands. It was a dynamic model consisting of 22 equations in 31 variables. Employing what we now see as basic statistical techniques like correlation and regression analysis, it was to be used for the analysis of the particularly pressing unemployment problem. The specification of consumption and employment in this model anticipated elements of Keynes's theory (1936). This modeling exercise resulted in a strong policy recommendation in favour of a devaluation of the Dutch guilder to tackle unemployment. But its importance for the economics profession was far more profound: for the first time, the economic-policy debate had been based on empirically tested, quantitative economic analysis and not on rather informally stated economic theory, the so-called verbal approach. Thus, according to Solow (2004, p. 159), Tinbergen's work during this period ‘was a major force in the transformation of economics from a discursive discipline into a model-building discipline’. The Keynes-Tinbergen Debate The formulation of certain relations in Tinbergen's 1936 model showed some resemblance to Keynes's theory. Nevertheless, in an article in the Economic Journal of 1939, Keynes was remarkably skeptical of Tinbergen's work. Keynes labeled Tinbergen's method of estimating the parameters of an econometric model and computing quantitative policy scenarios as ‘statistical alchemy’, arguing that this approach ‘… is a means of giving quantitative precision to what, in qualitative terms, we know already as the result of a complete theoretical analysis’ (Keynes, 1939, p. 560). Their widely diverging views on the relevance of quantitative economic analysis were also illustrated by Keynes's reaction to Tinbergen's estimate of the price elasticity of demand for exports. When, in 1919, Keynes had strongly criticized the excessive war indemnity payments enforced upon Germany after the First World War, his argument had depended critically on the value of this elasticity. Tinbergen empirically found this value to be minus 2, precisely the value that Keynes had assumed a priori in his study. When informed about this Keynes replied: ‘How nice that you found the correct figure’. Keynes' critical attitude towards macroeconometric modeling and analysis originated from his view that the underlying economic theory should be complete in the sense that it should include all relevant variables and set out in detail its causal and dynamic structure. Econometrics could be used only for measuring relations (‘curve fitting’ was the term used); it could not refute economic hypotheses or evaluate economic models. Tinbergen, on the other hand, argued that economic theories cannot be complete. Econometric research could be useful for scrutinizing elements of economic theories and for examining whether one theory describes reality better than another. Further, it could provide the numerical values of the coefficients in dynamic models that determine the cyclical and stability properties of the model, and, by applying a testing procedure of trial and error, it could yield suggestions for an improved specification of dynamic lags. The debate still goes on In this controversy Tinbergen's approach soon gained the upper hand as increasing numbers of economists, especially in the United States, noted its practical results in terms of model construction and verification, including forecasting and policy recommendation in particular for monetary policy. However, Keynes's comments on the role of expectations and uncertainty in macro-econometrics and on specification and simultaneous equation biases remained relevant. Haavelmo (1943) advocated the use of probability theory in bridging the gap between theory and data in business cycle analysis. Later these issues would become the subject of intensive debate and research. The pioneering work by Thomas Sargent and Christopher Sims, Nobel Laureates in Economics in 2011, to construct models that both fit the data and can be used for forecasting and policy is a clear example of the continuing debate. Discussing their contributions is beyond the scope of the present note. I only mention that forecast and policy implications based on their modeling and inference techniques are studied and used by almost all econometricians at the US Federal Reserve System and at European Central Banks. Personal note I met Jan Tinbergen late in his life when I was director of the Tinbergen Institute, www.tinbergen.nl , from 1992-1998 and after his death from 2008-2010. A brief story of my personal experience with Tinbergen shows his interest in that empirical econometric work which may have enormous potential policy implications. In 1994, just a few months before he died, he read my paper on the bimodal distribution of the World’s Income and the very low estimates of the catch-up probability of poor countries with the rich ones, see Paap and Van Dijk (EER, 1998). He saw it as a testimony to his efforts to make development programming of poor countries an important area of theoretical and practical research and he invited me (with my wife) to discuss in more detail my paper on a Saturday afternoon in the Spring of 1994. Regrettably he passed away on the Monday before our meeting, but it shows how actively involved he was in following empirical econometric research that has substantial policy implications until the very last days of his life. This note is an adjusted excerpt from the paper: “Tinbergen, Jan (1903–1994)." By Cornelisse, Peter A. and Herman K. van Dijk, in The New Palgrave Dictionary of Economics. Second Edition. Eds. Steven N. Durlauf and Lawrence E. Blume. Palgrave Macmillan, 2008. The New Palgrave Dictionary of Economics Online. Palgrave Macmillan. 25 March 2008 <http://www.dictionaryofeconomics.com/article?id=pde2008_T000065> doi:10.1057/9780230226203.1710. References can be found in that paper. Selected papers Keynes, J.M. 1939. Professor Tinbergen's method. Economic Journal 49, 558–68. Keynes, J.M. 1940. Comment. Economic Journal 50, 154–6. Tinbergen J., 1939. Statistical Testing of Business Cycle Theories. I: A Method and Its Application to Investment Activity. II: Business Cycles in the United States of America,1919–1932. Geneva: League of Nations. Tinbergen J., 1940. On a method of statistical business cycle research. A reply. Economic Journal 50, 141–54.
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