Purchasing power parity hypothesis postulates that nominal exchange rate growth (NER) in a country is positively related to domestic inflation rate (Π) and negatively related to foreign inflation rate (Π*): NERt = a0 + a1Πt + a2Π*t + ut where u is a disturbance term.  Under certain conditions, ER can be defined as a function of inflation differential ΠD = Π - Π*.  Some researchers often prefer to explain real exchange rate change which is defined as RER = ER – Π. Using a sample of 50 annual observations, a researcher estimates the following equations.    (1)           NERt = 0.19 + 0.96Πt  - 0.80Π*t                   R21 = 0.90, SSR1 = 900                                  (0.01)    (0.24)    (0.10)   (2)           NERt = 0.15 + 0.64ΠDt                                R22 = 0.89, SSR2 = 901                                    (0.03)  (0.10)   (3)           RERt = 0.05 – 0.95 Π*t                               R23 = 0.60, SSR3 = 905                                     (4)           NERt = b0 +  b1ΠD t + b2Π*t                                                    (0.02)  (0.03)    (0.24)   Compute the estimated standard error of the slope coefficient in Model 3.

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Purchasing power parity hypothesis postulates that nominal exchange rate growth (NER) in a country is positively related to domestic inflation rate (Π) and negatively related to foreign inflation rate (Π*):

NERt = a0 + a1Πt + a2Π*t + ut

where u is a disturbance term.  Under certain conditions, ER can be defined as a function of inflation differential ΠD = Π - Π*.  Some researchers often prefer to explain real exchange rate change which is defined as RER = ER – Π. Using a sample of 50 annual observations, a researcher estimates the following equations. 

 

(1)           NERt = 0.19 + 0.96Πt  - 0.80Π*t                   R21 = 0.90, SSR1 = 900

                                 (0.01)    (0.24)    (0.10)

 

(2)           NERt = 0.15 + 0.64ΠDt                                R22 = 0.89, SSR2 = 901

                                   (0.03)  (0.10)

 

(3)           RERt = 0.05 – 0.95 Π*t                               R23 = 0.60, SSR3 = 905

                                   

(4)           NERt = b0 +  b1ΠD t + b2Π*t                  

                                 (0.02)  (0.03)    (0.24)

 

Compute the estimated standard error of the slope coefficient in Model 3.

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