Economic Methodology: A Historical Introduction (Economics as Social Theory)
Harro Maas
Language: English
Pages: 202
ISBN: 0415858992
Format: PDF / Kindle (mobi) / ePub
Ever since the inception of economics over two hundred years ago, the tools at the discipline’s disposal have grown more and more more sophisticated. This book provides a historical introduction to the methodology of economics through the eyes of economists.
The story begins with John Stuart Mill's seminal essay from 1836 on the definition and method of political economy, which is then followed by an examination of how the actual practices of economists changed over time to such an extent that they not only altered their methods of enquiry, but also their self-perception as economists. Beginning as intellectuals and journalists operating to a large extent in the public sphere, they then transformed into experts who developed their tools of research increasingly behind the scenes. No longer did they try to influence policy agendas through public discourse; rather they targeted policymakers directly and with instruments that showed them as independent and objective policy advisors, the tools of the trade changing all the while.
In order to shed light on this evolution of economic methodology, this book takes carefully selected snapshots from the discipline’s history. It tracks the process of development through the nineteenth and twentieth centuries, analysing the growth of empirical and mathematical modelling. It also looks at the emergence of the experiment in economics, in addition to the similarities and differences between modelling and experimentation.
This book will be relevant reading for students and academics in the fields of economic methodology, history of economics, and history and philosophy of the social sciences.
Zombie Economics: How Dead Ideas Still Walk Among Us
Rigged: The True Story of an Ivy League Kid Who Changed the World of Oil, from Wall Street to Dubai
The Big Three in Economics: Adam Smith, Karl Marx, and John Maynard Keynes
Economics: Between Predictive Science and Moral Philosophy (Texas A&M University Economics Series)
Kameralismus at the University of Giessen in the state of Hessen-Darmstadt, arises out of a combination of these two aims. Figure 3.3 shows the absolute and relative size of the populations and state incomes of various European countries. The data used to produce such diagrams might sometimes be extremely politically sensitive, so it was not unusual for a prince to allow statistics to be compiled only under certain strict conditions, or only in secret. Deliberate distortions were quite common
the blind ambition of Allied politicians, Keynes placed his hopes in the science of economics, only to realize over time that the economic theory passed down to him did not provide the arguments that could give a more practical dimension to his outburst of rage. 64 John Maynard Keynes and Jan Tinbergen Skidelsky’s brief but apt description of the book enables us to understand how the mind of an economist such as Keynes actually worked. The Keynes who wrote it was not the economist he was to
R m ** to our scenario, the middle-aged are not .. . = R, our final equation becomes turning over to the young w hat the 0 =£[$,(*) . (80 young will later make good to them in retirement support. The budget equation (40 assures us that THE TWO-PERIOD CASE equation (80 has a solution: The paradox is delineated more clear „ 1 . ly if we suppose but two equal periods of R = — ;----or m = t. 1+ m life—work and retirement. Now it be comes impossible for any worker to find with 0 < Si (R ) = —RSz (
position of Milton Friedman (Chapter 6), who argues that the assumptions at the root of models are irrelevant, and positions that in one way or another support the notion that those assumptions are true, as in Chapter 9. In the former case, the value of models lies primarily in their predictive power, in the latter case in their capacity to simulate reality. Chapter 7 looks at the work of Paul Samuelson, showing that models can also facilitate thought experiments. In contrast to modelling
in his essay: how is knowledge of a complex world possible if that complexity cannot itself be controlled? Although admittedly a simplification of the world, a model is at least able not just to reflect complex processes but – if only to a certain level – to enable us to manipulate them. The next question that concerned economists and philosophers of science, one we still face today, was: where exactly does the power of models lie, in their equations or in their outcomes? Those who stress