Computing, the bootstrap and economics
Bibliographic Data
| ID | 19063058 |
|---|---|
| Authors | Russell Davidson (0000-0003-4214-5198, Department of Economics and CIREQ McGill University; AMSE–GREQAM, corresponding author) |
| Year | 2015 |
| Volume | 48 |
| Issue | 4 |
| Pages | 1195-1214 |
| Publication date | 2015-11-01 |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Canadian Journal of Economics/Revue canadienne d économique (JOURNAL) |
| Journal identifiers | ISSN: 0008-4085 • E-ISSN: 1540-5982 |
| Publisher | Wiley (PUBLISHER • GB) |
| DOI | 10.1111/caje.12158 |
| OpenAlex | W2406035511 |
| Language | EN |
| References cited | 15 |
A major contention in this paper is that scientific models can be viewed as virtual realities, implemented, or rendered, by mathematical equations or by computer simulations. Their purpose is to help us understand the external reality that they model. In economics, particularly in econometrics, models make use of random elements, so as to provide quantitatively for phenomena that we cannot or do not wish to model explicitly. By varying the realizations of the random elements in a simulation, it is possible to study counterfactual outcomes, which are necessary for any discussion of causality. The bootstrap is virtual reality within an outer reality. The principle of the bootstrap is that, if its virtual reality mimics as closely as possible the reality that contains it, it can be used to study aspects of that outer reality. The idea of bootstrap iteration is explored, and a discrete model discussed that allows investigators to perform iteration to any desired level
Counterfactual thinking · Epistemology · Virtual reality · Complex Systems and Time Series Analysis · Computer Science · Economic theories and models · Financial Markets and Investment Strategies · Artificial Intelligence
The general theory of employment, interest, and money
Bootstrap Methods and their Application
Identification and Inference in Nonlinear Difference-in-Differences Models
Investigating Causal Relations by Econometric Models and Cross-spectral Methods
Using the Longitudinal Structure of Earnings to Estimate the Effect of Training Programs
A discrete model for bootstrap iteration
| Highly cited | No |
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