发帖
雷达卡
Theories and Models in Economics An Empirical Approach to Methodology.pdf
(2.26 MB, 需要: RMB 13 元)
2024年底上线，2026放出的新资料。
130多页内容丰富的资料！
全部矢量文字，方便翻译学习！特别适合投喂给大模型，生成自己的资料知识库！
Contents of Theories and Models in Economics An Empirical Approach to Methodology
1 Introduction and background to the empirical approach to
methodology 1
2 What characterizes the object that Economics studies? 7
3 What economists do: (1) path-breaking contributions 24
4 What economists do: (2) contributions in “normal science” 41
5 How Economics develops over time: Kuhn versus Laudan 61
6 On theory in Economics 67
7 On models in Economics 77
8 How to make an idea credible: a case study of Krugman’s
New Trade Theory 96
9 Summary and implications 107
Appendix: Information about the empirical studies 116
References 122
Index 126
This resource is written with two specific audiences in mind. The resource should be of interest to those both inside and outside Economics who wants to understand how economists work and especially learn about the use of theories and models in Economics. As I see it, there are both criticisms and defences of Economics that are not based on systematic knowledge of what economists really do and really claim in their research. The resource should also be suitable for courses in the methodology of economics as a more empirical complement to the existing methodology resources that typically start from various philosophical theories and positions and try to relate what economists do and claim to these theories. There are, for example, a number of classical methodology resources that look at economics from the perspective of positivism, Kuhn’s theory of paradigms, Popperian falsificationism or the Lakatos theory of research programmes. The structure of the resource is as follows. In order to understand what economists do, it is important to think about the characteristics of the object that economics studies. In Chapter 2, I formulate the hypothesis that this object has a chaos-like structure. This hypothesis is tested by deriving a number of implications about what we should find if we compare motivations for Nobel 5Introduction and background to the empirical approach to methodology Prizes in Economics and Physics. The tests showed that there were statistically significant differences supporting the hypothesis about a chaos-like object. The subsequent two chapters describe what economists do in their research. Chapter 3 is based on the study of Nobel Prize motivations and categorizes path-breaking contributions – contributions that motivate a Nobel Prize. Six different types of contributions were found. Chapter 4 focuses on what Kuhn calls normal science and categorizes articles published in American Economic Review, 1990 and 2020. Three types of articles were found: those where the core was an analysis of relations in a mathematical model, those that presented an empirical study without any explicit “theoretical” model, and a third group that included both such a model and an empirical study. Over time the first group has shrunk while the second group has increased and also included more experimental and quasi-experimental studies. In Chapter 5, I compare two views of how science develops over time. Kuhn’s model of scientific revolutions and Laudan’s more incremental model where important elements can be replaced, but where the rest of a research tradition is kept intact. The data from the Nobel Prize motivations strongly support Laudan’s view. Mathematical methods were, for example, introduced without changing behavioural assumptions, and new behavioural assumptions were later introduced but without changing the methods used. Chapter 6 focuses on theory in economics. After looking at how theory is defined in some advanced dictionaries, I investigate how theory is used in AER-articles. It is, for example, found that the word theory/theoretical is used rather sparsely. One issue studied is the relation between theory (theoretical models) and empirical studies, and it is found that this relation is rather weak. There is also a section about the meaning and use of theoretical frameworks. Chapter 7 is about models, and while the word theory/theoretical is used rather sparsely, the word model/modelling is used about ten times more often. Here, I also start with the meaning of models according to some advanced dictionaries and with an investigation of how the words are used in the AER-articles. Two main interpretations are mathematical models that are studied in “theoretical” articles, and empirical models that are the base for statistical estimation. The focus in the rest of the chapter is on the first type of model analysis and some views from the methodological literature are presented. I argue that a Bayesian framework can be used to evaluate the empirical value of the mathematical models: the result in the mathematical model can be seen as “new information” and the questions is then how much it is rational to change the probability of specific empirical assertions. Realism in assumptions, robustness of the results and lack of competing hypotheses are then important aspects, besides the result being supported by “common sense”. 6 Theories and models in economics In Chapter 8, a case study of Krugman’s New trade theory illustrates how a new idea can be established through a combination of simple general equilibrium models, empirical studies and common sense. Chapter 9 summarizes the main points of the earlier chapter and presents some concluding reflections. If the final aim of science is to evaluate how probable various empirical statements are, then a Bayesian framework seems interesting. All kinds of studies produce new information, and the question is how much it is rational to change the probability of specific empirical statements given this new information. The new information can be anything from a result that a certain relation holds in a mathematical model to statements in an interview with someone working in the field. My final hypothesis is that there is diminishing marginal utility of each specific kind of information in relation to a specific empirical issue. If a lot of mathematical models have been built, then maybe interviews or case studies can change the probabilities of empirical statements more. And the other way around, if a lot of information from interviews and case-studies is available, then analysing sufficient conditions for a certain relation in a mathematical model could increase our knowledge more. An implication of this is that it is not rational to have a general opinion about what is the best method in economics or about “the role of mathematical models” in economics
京公网安备 11010802022788号
