Table 3: Weighted Least Squares meta regression results
|
(1) T-stat |
(2) T-stat |
(3) T-stat |
(4) T-stat |
(5) T-stat |
(6) T-stat |
(7) T-stat | |
|
Constant |
2.693*** |
1.932*** |
-0.253* |
-0.572*** |
-0.406*** |
-28.82*** |
-0.360*** |
|
(0.077) |
(0.079) |
(0.101) |
(0.097) |
(0.109) |
(0.001) |
(0.006) | |
|
no. of explanatory variables |
0.0422*** |
0.0416*** |
0.0416*** |
0.0416*** |
0.0425*** | ||
|
(0.000) |
(0.000) |
(0.000) |
(0.000) |
(0.000) | |||
|
N (in logs) |
0.0175*** |
0.000443 |
0.00515 |
-0.00195 |
-0.0162*** | ||
|
(0.000) |
(0.006) |
(0.005) |
(0.006) |
(0.000) | |||
|
No. of years used (log) |
0.0448*** |
-0.392* |
0.0198 |
-0.269 |
-0.378*** | ||
|
(0.002) |
(0.166) |
(0.086) |
(0.375) |
(0.025) | |||
|
No. of countries (log) |
0.384*** |
-0.0535*** |
-0.0642*** |
-0.0561*** |
-0.0285*** | ||
|
(0.003) |
(0.010) |
(0.010) |
(0.010) |
(0.000) | |||
|
annual = 1 |
1.241*** |
-2.880* |
1.092*** | ||||
|
(0.190) |
(1.214) |
(0.031) | |||||
|
selection correction = 1 |
-0.190*** |
-0.189*** |
-0.252*** | ||||
|
(0.049) |
(0.049) |
(0.004) | |||||
|
published = 1 |
0.0106 |
2.287* |
0.0117*** | ||||
|
(0.009) |
(0.977) |
(0.000) | |||||
|
country effects = 1 |
-0.283* |
0.384 |
-0.235*** | ||||
|
(0.115) |
(0.560) |
(0.016) | |||||
|
time effects = 1 |
0.00382 |
0.0105 |
-0.00122 | ||||
|
(0.046) |
(0.048) |
(0.004) | |||||
|
cross section = 1 |
-2.256*** |
-4.005 |
-2.485*** | ||||
|
(0.320) |
(4.257) |
(0.044) | |||||
|
other preferences included = 1 |
0.200*** |
0.699 |
0.151*** | ||||
|
(0.061) |
(3.553) |
(0.010) | |||||
|
gravity regression = 1 |
-0.466*** |
4.300** |
-0.379*** | ||||
|
(0.066) |
(1.514) |
(0.011) | |||||
|
agoa dummy = 1 |
-2.707*** |
-2.196*** |
-2.673*** | ||||
|
(0.262) |
(0.422) |
(0.103) | |||||
|
robust s.e. = 1 |
-0.144*** |
-0.139*** |
0.00619*** | ||||
|
(0.016) |
(0.017) |
(0.001) | |||||
|
product effects = 1 |
0.153** |
-0.864 |
0.391*** | ||||
|
(0.047) |
(0.570) |
(0.005) | |||||
|
single country analysis = 1 |
0.834*** |
0.972*** | |||||
|
(0.125) |
(0.015) | ||||||
|
logged dep. var. = 1 |
0.288*** |
-0.116 |
0.331*** | ||||
|
(0.041) |
(0.208) |
(0.005) | |||||
|
product group = ”All/Total” |
-0.00637 |
-0.0311 | |||||
|
(0.056) |
(0.068) | ||||||
|
product group = ”Apparel & Textiles” |
-0.0369 |
-0.0436 | |||||
|
(0.045) |
(0.045) | ||||||
|
product group = ”Agriculture” |
0.0609* |
0.0550* | |||||
|
(0.026) |
(0.026) | ||||||
|
regions included = AGOA countries |
-0.0514 |
-2.874 | |||||
|
(0.068) |
(3.493) | ||||||
|
regions included = AGOA + N. Africa |
-0.287*** |
-6.300** | |||||
|
(0.069) |
(2.054) | ||||||
|
definition of dep. var. = Exports |
-0.214 |
0.696 | |||||
|
(0.264) |
(3.502) | ||||||
|
definition of dep. var. = Imports |
0.156 |
1.813 | |||||
|
(0.245) |
(3.455) | ||||||
|
time frequency = Annual |
0.488** | ||||||
|
(0.157) | |||||||
|
time frequency = Monthly |
-0.0248 |
-2.959* | |||||
|
(0.134) |
(1.208) | ||||||
|
econometric method = GMM |
-0.00367 |
-0.657 | |||||
|
(0.057) |
(0.607) | ||||||
|
econometric method = Heckman/Tobit |
-0.873*** |
-2.552 | |||||
|
(0.121) |
(1.567) | ||||||
|
level of aggregation = Aggregate |
0.0686+ |
0.0712+ | |||||
|
(0.039) |
(0.040) | ||||||
|
level of aggregation = Less Aggregate |
0.0779* |
-2.206* | |||||
|
(0.040) |
(0.976) | ||||||
|
Precision |
0.00449*** |
-2.228*** |
2.584*** |
-0.258+ |
4.384*** |
0.0128*** |
2.489*** |
|
(0.000) |
(0.009) |
(0.342) |
(0.149) |
(1.056) |
(0.000) |
(0.107) | |
|
Observations |
173 |
173 |
173 |
173 |
173 |
173 |
173 |
|
goodness of fit-χ2 |
120496.0 |
7710.6 |
862.6 |
1074.5 |
836.8 |
1.31107e+10 |
316374.3 |
|
model χ2 |
1217.4 |
114002.8 |
120850.8 |
120639.0 |
120876.6 |
600194512.9 |
1.37106e+10 |
|
Standard errors in parentheses. All explanatory variables divided by standard error. |
The last two columns use the square of the standard error as weights | ||||||
+ p < 0.1, * p < 0.05, ** p < 0.01, *** p < 0.001
Multi-Level Meta-Regression
The final table, Table (4) below presents the multi-level MRA results. We include these results to check
the robustness of our earlier results given that that our coefficients are nested in the individual studies. The
intercept is the only random component included in the 2-level multi-level MRA. In column (2) in the table,
precision is negative and significant at the 1% level of significance. The number of explanatory variables,
product fixed effects and logged dependent variables contribute to higher to t-statistics holding all else con-
stant. The remaining significant variables in the final column of the table, number of years, cross-sectional
14
More intriguing information
1. A Brief Introduction to the Guidance Theory of Representation2. Labour Market Flexibility and Regional Unemployment Rate Dynamics: Spain (1980-1995)
3. The name is absent
4. The Role of State Trading Enterprises and Their Impact on Agricultural Development and Economic Growth in Developing Countries
5. Return Predictability and Stock Market Crashes in a Simple Rational Expectations Model
6. ESTIMATION OF EFFICIENT REGRESSION MODELS FOR APPLIED AGRICULTURAL ECONOMICS RESEARCH
7. PER UNIT COSTS TO OWN AND OPERATE FARM MACHINERY
8. Hemmnisse für die Vernetzungen von Wissenschaft und Wirtschaft abbauen
9. The name is absent
10. Experimental Evidence of Risk Aversion in Consumer Markets: The Case of Beef Tenderness