1 / 13

Economics 105: Statistics

Economics 105: Statistics. Please practice your RAP, so you can keep it to 7 minutes. We have lots of them to do. please copy your Powerpoint file to your stats P:economicsEco 105 (Statistics) Foley userid lab space.

finola
Download Presentation

Economics 105: Statistics

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. Economics 105: Statistics Please practice your RAP, so you can keep it to 7 minutes. We have lots of them to do. please copy your Powerpoint file to your stats P:\economics\Eco 105 (Statistics) Foley\userid\ lab space. Tue Apr 24:  Thompson, Shanor, Nielsen, Moniz-Soares, Maher, Dugan, Burke, Adabayeri Thur Apr 26: Ryger-Wasserman, Lockwood, Gordon, Givens, Christ, Blasey, Bernert, Avinger Tue May 1: Yearwood, Swany, Ream, Polak, Pettiglio, Murray, Esposito, Bajaj Thur May 3: Yan, Tompkins, Mwangi, Mooney, Lockhart, Clune, Charles, Bourgeois Review #3 due Monday May 7, by 4:30 PM.

  2. Violations of GM Assumptions Assumption Violation Wrong functional form Omit Relevant Variable (Include Irrelevant Var) Errors in Variables Sample selection bias, Simultaneity bias “well-specified model” (1) & (5) constant, nonzero mean due to systematically +/- measurement error in Y can only assess theoretically zero conditional mean of errors (2) Homoskedastic errors (3) Heteroskedastic errors No serial correlation in errors (4) There exists serial correlation in errors

  3. Detection: The Durbin-Watson Test • Provides a way to test H0:  = 0 • It is a test for the presence of first-order serial correlation • The alternative hypothesis can be •   0 •  > 0: positive serial correlation • Most likely alternative in economics •  < 0: negative serial correlation • DW Test statistic is d

  4. Detection: The Durbin-Watson Test • To test for positive serial correlation with the Durbin-Watson statistic, under the null we expect d to be near 2 • The smaller d, the more likely the alternative hypothesis The sampling distribution of d depends on the values of the explanatory variables. Since every problem has a different set of explanatory variables, Durbin and Watson derived upper and lower limits for the critical value of the test.

  5. Detection: The Durbin-Watson Test • Durbin and Watson derived upper and lower limits such that d1d* du • They developed the following decision rule

  6. Detection: The Durbin-Watson Test • To test for negative serial correlation the decision rule is • Can use a two-tailed test if there is no strong prior belief about whether there is positive or negative serial correlation—the decision rule is

  7. Serial Correlation Table of critical values for Durbin-Watson statistic (table E11, page 833 in BLK textbook) http://hadm.sph.sc.edu/courses/J716/Dw.html

  8. Serial Correlation Example What is the effect of the price of oil on the number of wells drilled in the U.S.?

  9. Serial Correlation Example What is the effect of the price of oil on the number of wells drilled in the U.S.?

  10. Serial Correlation Example Analyze residual plots … but be careful …

  11. Serial Correlation Example Remember what serial correlation is … • This plot only “works” if obs number is in same order as the unit of time

  12. Serial Correlation Example Same graph when plot versus “year” • Graphical evidence of serial correlation

  13. Serial Correlation Example Calculate DW test statistic Compare to critical value at chosen sig level dlower or dupper for 1 X-var & n = 62 not in table dlower for 1 X-var & n = 60 is 1.55, dupper = 1.62 • Since .192 < 1.55, reject H0:  = 0 in favor of H1:  > 0 at α=5%

More Related