Sinning in the basement: What are the rules? The ten commandments of applied econometrics

Journal of Economic Surveys

Volumn 16, Issue 4, 2002, Pages 569-589

  Kennedy, Peter E ^a  

^a SIMON FRASER UNIVERSITY   (Canada)

Author keywords

Applied econometrics; Data mining; Methodology

Indexed keywords

ECONOMETRICS;

EID: 0036351106     PISSN: 09500804     EISSN: None     Source Type: Journal    
DOI: 10.1111/1467-6419.00179     Document Type: Article

References (91)

1. Graphs in statistical analysis
2. Introduction: Is data mining a methodological problem?
3. Statistical practice and research: The essential interactions
4. A larger perspective
5. Modelling energy consumption - Using and abusing regression diagnostics
6. Economic history and econometrics: A cautionary note from the hyperinflation front
7. The initial examination of data
8. Avoiding statistical pitfalls
9. Model uncertainty, data mining and statistical inference
10. Introductory textbooks: A framework for evaluation
11. Mortgage lending to minorities: Where's the bias?
12. The ten commandments of statistical inference
13. Book review
14. Inflation, tax rules and investment: Some econometric evidence
15. Do old fallacies ever die?
16. Data and econometricians - The uneasy alliance
17. The craft of labormetrics
18. Data mining for fun and profit
19. Econometrics - Alchemy or science?
20. Encompassing
21. The ET dialogue: A conversation on econometric methodology
22. Procrustean econometrics: Or stretching and squeezing data
23. The econometric analysis of economic time series
24. In defense of data mining: Some preliminary thoughts
25. Data mining reconsidered: Encompassing and the general-to- specific approach to specification search
26. Three attitudes towards data mining
27. The teaching of statistics
28. Practicing statistics, or what they forgot to say in the classroom
29. Directional statistical decisions
30. Simplicity, scientific inference and econometreic modelling
31. On method of statistical research: Comment
32. Errors of the third kind in statistical consulting
33. Stocks and the weather: An exercise in data mining or yet another capital market anomaly
34. Things that bother me
35. Questions, theory and data
36. Revisiting Tobin's 1950 study of food expenditure
37. A sensitivity analysis of cross-country growth regressions
38. A picture is worth a thousand p values: On the irrelevance of hypothesis testing in the microcomputer age
39. The success of econometrics
40. Lessons from the tacit knowledge experiment
41. Introduction: Applied econometrics and design of two experiments
42. The M3 competition: Results, conclusions and implications
43. Comments
44. Statistical consulting: Reaction and comments
45. The standard error of regression
46. Uncertainty
47. An applied statistician's creed
48. Three econometric methodologies: A critical appraisal
49. The Tilburg experiments: Impressions of a drop-out
50. George Box: An interview
51. Statistical thinking and statistical practice: Themes gleaned from professional statisticians
52. Good statistical practice
53. The irregular economy and the quality of macroeconomic statistics
54. Statistical procedures and the justification of knowledge in psychological science
55. Quantitative methods in peace research
56. From homo economicus to homo sapiens
57. Comment
58. The future of data analysis
59. Analyzing data: Sanctification or detective work?
60. Consulting: Real problems, real interactions, real outcomes
61. Jolts as a synopsis of organizational studies
62. Comment
63. Comments
64. The construction of US consumption data: Some facts and their implications for empirical work
65. Embracing the 'wider view' of statistics
66. Statistical methods in psychology journals
67. Is progress in science possible?
68. Statistics, science and public policy
69. Keep it sophisticatedly simple