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The Neoclassical Growth Model Predicts That for Identical Savings Rates g6090^=β0^+β1^×RelProd60\widehat { g 6090 } = \widehat { \beta _ { 0 } } + \widehat { \beta _ { 1 } } \times \operatorname { RelProd } _ { 60 }

question 27

Essay

The neoclassical growth model predicts that for identical savings rates and population growth rates, countries should converge to the per capita income level. This is referred to as the convergence hypothesis. One way to test for the presence of convergence is to compare the growth rates over time to the initial starting level, i.e., to run the regression g6090^=β0^+β1^×RelProd60\widehat { g 6090 } = \widehat { \beta _ { 0 } } + \widehat { \beta _ { 1 } } \times \operatorname { RelProd } _ { 60 } , where g6090g 6090 is the average annual growth rate of GDP per worker for the 1960-1990 sample period, and RelProd60\operatorname { RelProd } _ { 60 } is GDP per worker relative to the United States in 1960. Under the null hypothesis of no convergence, β1=0;H1:β1<0\beta _ { 1 } = 0 ; H _ { 1 } : \beta _ { 1 } < 0 , implying ("beta") convergence. Using a standard regression package, you get the following output: Dependent Variable: G6090
Method: Least Squares
Date: 07/11/06 Time: 05:46
Sample: 1104
Included observations: 104
White Heteroskedasticity-Consistent Standard Errors & Covariance
 The neoclassical growth model predicts that for identical savings rates and population growth rates, countries should converge to the per capita income level. This is referred to as the convergence hypothesis. One way to test for the presence of convergence is to compare the growth rates over time to the initial starting level, i.e., to run the regression  \widehat { g 6090 } = \widehat { \beta _ { 0 } } + \widehat { \beta _ { 1 } } \times \operatorname { RelProd } _ { 60 } , where  g 6090  is the average annual growth rate of GDP per worker for the 1960-1990 sample period, and  \operatorname { RelProd } _ { 60 }  is GDP per worker relative to the United States in 1960. Under the null hypothesis of no convergence,  \beta _ { 1 } = 0 ; H _ { 1 } : \beta _ { 1 } < 0 , implying ( beta ) convergence. Using a standard regression package, you get the following output: Dependent Variable: G6090 Method: Least Squares Date: 07/11/06 Time: 05:46 Sample: 1104 Included observations: 104 White Heteroskedasticity-Consistent Standard Errors & Covariance    You are delighted to see that this program has already calculated p-values for you. However, a peer of yours points out that the correct p-value should be 0.4562. Who is right?
You are delighted to see that this program has already calculated p-values for you.
However, a peer of yours points out that the correct p-value should be 0.4562.
Who is right?


Definitions:

Hand Scoring

The process of manually calculating test scores or results, as opposed to using computerized scoring systems.

Error

A mistake or discrepancy that occurs in data, calculations, or actions, often leading to inaccuracies or deviations from expected results.

Diagnosis

The identification of the nature and cause of a certain phenomenon, often used in the context of medical conditions.

Screening

The process of evaluating individuals to identify potential problems or conditions, often before symptoms manifest.

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