LASSO Regression using Panel Data
$begingroup$
I have panel data for 3 countries, ranging over 3 years. The dataset is called CarProduction
Country Year cars Fuel_price PPP Manufact PublicTransport
USA 2015 500 5 10000 9 2
USA 2016 700 5.2 10500 8.75 2.2
USA 2017 780 5.4 11000 8.6 1.9
China 2015 150 9 4000 11 3
China 2016 200 8.6 4500 11.5 4
China 2017 340 9.4 6000 15.6 5
Italy 2015 200 9 4000 11 5
Italy 2016 300 8.6 4500 11.5 6.2
Italy 2017 440 9.4 6000 15.6 6.7
I know that the glmnet
package can be used in R to run a LASSO regression.
Considering that I have panel data, how do I run LASSO regression on panel data?
I will be implementing OLS for comparison purposes. This is the regression I would ordinarily run, accounting for fixed effects:
ans <- plm(cars ~ Fuel_price+PPP+Manufact+PublicTransport, data=CarProduction, model="within")
machine-learning r glm
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$endgroup$
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$begingroup$
I have panel data for 3 countries, ranging over 3 years. The dataset is called CarProduction
Country Year cars Fuel_price PPP Manufact PublicTransport
USA 2015 500 5 10000 9 2
USA 2016 700 5.2 10500 8.75 2.2
USA 2017 780 5.4 11000 8.6 1.9
China 2015 150 9 4000 11 3
China 2016 200 8.6 4500 11.5 4
China 2017 340 9.4 6000 15.6 5
Italy 2015 200 9 4000 11 5
Italy 2016 300 8.6 4500 11.5 6.2
Italy 2017 440 9.4 6000 15.6 6.7
I know that the glmnet
package can be used in R to run a LASSO regression.
Considering that I have panel data, how do I run LASSO regression on panel data?
I will be implementing OLS for comparison purposes. This is the regression I would ordinarily run, accounting for fixed effects:
ans <- plm(cars ~ Fuel_price+PPP+Manufact+PublicTransport, data=CarProduction, model="within")
machine-learning r glm
New contributor
$endgroup$
add a comment |
$begingroup$
I have panel data for 3 countries, ranging over 3 years. The dataset is called CarProduction
Country Year cars Fuel_price PPP Manufact PublicTransport
USA 2015 500 5 10000 9 2
USA 2016 700 5.2 10500 8.75 2.2
USA 2017 780 5.4 11000 8.6 1.9
China 2015 150 9 4000 11 3
China 2016 200 8.6 4500 11.5 4
China 2017 340 9.4 6000 15.6 5
Italy 2015 200 9 4000 11 5
Italy 2016 300 8.6 4500 11.5 6.2
Italy 2017 440 9.4 6000 15.6 6.7
I know that the glmnet
package can be used in R to run a LASSO regression.
Considering that I have panel data, how do I run LASSO regression on panel data?
I will be implementing OLS for comparison purposes. This is the regression I would ordinarily run, accounting for fixed effects:
ans <- plm(cars ~ Fuel_price+PPP+Manufact+PublicTransport, data=CarProduction, model="within")
machine-learning r glm
New contributor
$endgroup$
I have panel data for 3 countries, ranging over 3 years. The dataset is called CarProduction
Country Year cars Fuel_price PPP Manufact PublicTransport
USA 2015 500 5 10000 9 2
USA 2016 700 5.2 10500 8.75 2.2
USA 2017 780 5.4 11000 8.6 1.9
China 2015 150 9 4000 11 3
China 2016 200 8.6 4500 11.5 4
China 2017 340 9.4 6000 15.6 5
Italy 2015 200 9 4000 11 5
Italy 2016 300 8.6 4500 11.5 6.2
Italy 2017 440 9.4 6000 15.6 6.7
I know that the glmnet
package can be used in R to run a LASSO regression.
Considering that I have panel data, how do I run LASSO regression on panel data?
I will be implementing OLS for comparison purposes. This is the regression I would ordinarily run, accounting for fixed effects:
ans <- plm(cars ~ Fuel_price+PPP+Manufact+PublicTransport, data=CarProduction, model="within")
machine-learning r glm
machine-learning r glm
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asked 47 secs ago
Jyothsna HarithsaJyothsna Harithsa
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