Econometrics assignment

Econometrics assignment The followin" rel="nofollow">in" rel="nofollow">in" rel="nofollow">ing are two macro production functions; the first is a static model, the second a dynamic model with a lagged dependent variable: Static Model: Ln(yt) = β0 + β1 Ln kt + λ year + ut Dynamic Model: Ln(yt) = β0 + β1 Ln (kt) + ρ Ln(yt-1) + λ year + vt log(y) is the natural log of GDP per capita and log(k) is the natural log of capital per capita, Year is the trend variable. The data for this exercise can be found in" rel="nofollow">in" rel="nofollow">in" rel="nofollow">in ‘Macro_PEBLIF’ (attached). This macro data set is a merged file with data from PENN6.1, Barro and Lee (2000), the IMF Fin" rel="nofollow">in" rel="nofollow">in" rel="nofollow">inancial Statistics and measures of political and civil rights from the Freedom House annual ‘Freedom in" rel="nofollow">in" rel="nofollow">in" rel="nofollow">in the World’ survey over the period 1950 to 2000. Answer the followin" rel="nofollow">in" rel="nofollow">in" rel="nofollow">ing in" rel="nofollow">in" rel="nofollow">in" rel="nofollow">in 2 pages: 1. Estimate both the static and dynamic models usin" rel="nofollow">in" rel="nofollow">in" rel="nofollow">ing the time-series data over the period from 1950 to 2000 from ‘Macro_PEBLIF’ for Ghana, Argentin" rel="nofollow">in" rel="nofollow">in" rel="nofollow">ina, South Korea and Australia. 2. What are the assumptions that ensure the OLS estimates are unbiased and consistent and how can they be tested? 3. What are the short- and long-run coefficients on capital and technical progress for both South Korea and Ghana? 4. Establish the time-series properties of the arguments for the production function. 5. Estimate the constant returns to scale production function and assess if the variables are coin" rel="nofollow">in" rel="nofollow">in" rel="nofollow">integrated. 6. The implications of variables havin" rel="nofollow">in" rel="nofollow">in" rel="nofollow">ing a unit root