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182
Table 50: Regression Results -- Model 2
Dependent Variable
Days 1 Days 2 Days 3 Days 4
N 131 131 131 131
F (sig.) 3.830 (.000)* 2.914 (.001)* 7.020 (.000)* 5.682 (.000)*
R2 .280 .229 .417 .366
Constant 2313.973 (.000)* 2116.286 (.001)* 2474.666 (.000)* 2276.979 (.000)*
GDP82 0.087 (.799) -.131 (.693) 0.124 (.699) -0.094 (.760)
CGDP82 -.077 (.056)*** 0.005 (.901) -.097 (.011)** -0.016 (.667)
PartlyFree82 862.164 (.074)*** 794.391 (.090)*** 1510.478 (.001)* 1442.705 (.001)*
Free82 1625.446 (.002)* 1639.176 (.001)* 1726.467 (.001)* 1740.196 (.000)*
Previous RTA 247.076 (.509) 345.089 (.343) 619.963 (.079)*** 717.975 (.035)**
Comecon -1885.052 (.008)* -2312.822 (.001)* -2249.957 (.001)* -2677.728 (.000)*
Religion:
Middle
862.351 (.042)** 803.347 (.051)*** 1055.931 (.009)* 996.927 (.010)*
Religion: High 802.070 (.055)*** 728.158 (.072)*** 1183.736 (.003)* 1109.824 (.003)*
Language:
Middle
-522.302 (.229) -692.047 (.102) -685.949 (.093)*** -855.693 (.030)**
Language: High -563.576 (.291) -465.438 (.368) -873.580 (.082)*** -775.442 (.107)
Ethnic 377.841 (.385) 460.299 (.276) 377.129 (.356) 459.587 (.241)
Open 199.010 (.633) 129.443 (.749) 37.774 (.923) -31.793 (.932)
*Significant at the .01- level
** Significant at the .05-level
*** Significant at the .10- level
As with the previous analysis, the coefficient estimates for OPEN are not
statistically significant however, magnitude declines when the GSTP is included and
rises when it is excluded. The magnitudes of the coefficient estimates imply a
reduced duration ranging from -31.793 to 199.01 days compared to the base case,
states deemed closed. The high p-values generated when excluding the GSTP raise
doubts regarding the usefulness of these estimates. Relying on the estimates that
include the GSTP, it appears that an open trade policy shortens durations by 129 to
199 days compared to closed states.
The coefficient estimates for Comecon remain highly significant across all
four measures of the dependent variable. The values range from -2677.728 to -
1885.052. The range remains nearly constant compared to the regression containing
region dummies, however the magnitudes of the coefficient estimates are greater,
which reveals longer durations prior to adoption of an initial RTA. The higher
Object Description
| Title | Riding the wave: an interdisciplinary approach to understanding the popularity of RTA notifications to the GATT/WTO |
| Author | McClough, David Andrew |
| Author email | mcclough@usc.edu; dmcclou@bgsu.edu |
| Degree | Doctor of Philosophy |
| Document type | Dissertation |
| Degree program | Political Economy & Public Policy |
| School | College of Letters, Arts and Sciences |
| Date defended/completed | 2008-08-07 |
| Date submitted | 2008 |
| Restricted until | Unrestricted |
| Date published | 2008-10-18 |
| Advisor (committee chair) | Katada, Saori N. |
| Advisor (committee member) |
Nugent, Jeffrey B. Cartier, Carolyn |
| Abstract | The proliferation of Regional Trade Agreements (RTAs) notified to the GATT/WTO since the early 1980s deviates from the long-term trend and reflects participation of nearly every member of the United Nations. This dissertation seeks to explain the current wave of RTA notifications by supplementing the economic model of supply and demand with diffusion theory. Application of the supply and demand model is useful in distinguishing between changes in demand and changes insupply of RTAs. This distinction is seldom emphasized in the current literature examining RTAs. Recent applications of diffusion theory in the discipline of international relations offer a unique opportunity to include a dynamic force in the static analysis of the supply and demand model. Empirical analysis assesses the fit of the RTA diffusion pattern by comparing the RTA diffusion pattern to a cumulative standard normal distribution. The analysis indicates that the diffusion pattern of RTAs resembles the diffusion of an innovation through a social system.; The implication of this finding is that the adoption of an RTA as trade policy is not made independently of the decision by other states. Indeed, the analysis suggests interdependency between states. Further empirical analysis explores economic and political variables that may explain the decision to adopt the RTA as trade policy. The empirical analysis is unique in that survival analysis is utilized to assess the variation in duration to adopt an initial RTA since the early 1980s. A central discovery is that regional designation explains the variation in duration to adopt an initial RTA. Multiple regression analysis confirms the results generated using survival analysis and support the assertion that the proliferation of RTAs likely reflects changes in both the demand for RTAs and the supply of RTAs. This dissertation concludes by considering implications for the WTO resulting from the increase in RTA notifications. |
| Keyword | trade agreements |
| Coverage date | after 1980 |
| Language | English |
| Part of collection | University of Southern California dissertations and theses |
| Publisher (of the original version) | University of Southern California |
| Place of publication (of the original version) | Los Angeles, California |
| Publisher (of the digital version) | University of Southern California. Libraries |
| Provenance | Electronically uploaded by the author |
| Type | texts |
| Legacy record ID | usctheses-m1675 |
| Contributing entity | University of Southern California |
| Rights | McClough, David Andrew |
| Repository name | Libraries, University of Southern California |
| Repository address | Los Angeles, California |
| Repository email | cisadmin@lib.usc.edu |
| Filename | etd-McClough-2338 |
| Archival file | uscthesesreloadpub_Volume32/etd-McClough-2338.pdf |
Description
| Title | Page 191 |
| Contributing entity | University of Southern California |
| Repository email | cisadmin@lib.usc.edu |
| Full text | 182 Table 50: Regression Results -- Model 2 Dependent Variable Days 1 Days 2 Days 3 Days 4 N 131 131 131 131 F (sig.) 3.830 (.000)* 2.914 (.001)* 7.020 (.000)* 5.682 (.000)* R2 .280 .229 .417 .366 Constant 2313.973 (.000)* 2116.286 (.001)* 2474.666 (.000)* 2276.979 (.000)* GDP82 0.087 (.799) -.131 (.693) 0.124 (.699) -0.094 (.760) CGDP82 -.077 (.056)*** 0.005 (.901) -.097 (.011)** -0.016 (.667) PartlyFree82 862.164 (.074)*** 794.391 (.090)*** 1510.478 (.001)* 1442.705 (.001)* Free82 1625.446 (.002)* 1639.176 (.001)* 1726.467 (.001)* 1740.196 (.000)* Previous RTA 247.076 (.509) 345.089 (.343) 619.963 (.079)*** 717.975 (.035)** Comecon -1885.052 (.008)* -2312.822 (.001)* -2249.957 (.001)* -2677.728 (.000)* Religion: Middle 862.351 (.042)** 803.347 (.051)*** 1055.931 (.009)* 996.927 (.010)* Religion: High 802.070 (.055)*** 728.158 (.072)*** 1183.736 (.003)* 1109.824 (.003)* Language: Middle -522.302 (.229) -692.047 (.102) -685.949 (.093)*** -855.693 (.030)** Language: High -563.576 (.291) -465.438 (.368) -873.580 (.082)*** -775.442 (.107) Ethnic 377.841 (.385) 460.299 (.276) 377.129 (.356) 459.587 (.241) Open 199.010 (.633) 129.443 (.749) 37.774 (.923) -31.793 (.932) *Significant at the .01- level ** Significant at the .05-level *** Significant at the .10- level As with the previous analysis, the coefficient estimates for OPEN are not statistically significant however, magnitude declines when the GSTP is included and rises when it is excluded. The magnitudes of the coefficient estimates imply a reduced duration ranging from -31.793 to 199.01 days compared to the base case, states deemed closed. The high p-values generated when excluding the GSTP raise doubts regarding the usefulness of these estimates. Relying on the estimates that include the GSTP, it appears that an open trade policy shortens durations by 129 to 199 days compared to closed states. The coefficient estimates for Comecon remain highly significant across all four measures of the dependent variable. The values range from -2677.728 to - 1885.052. The range remains nearly constant compared to the regression containing region dummies, however the magnitudes of the coefficient estimates are greater, which reveals longer durations prior to adoption of an initial RTA. The higher |
