Time Series Regression Model


I'm trying to create a simple regression model with a time series dataset.
The dataset includes 24 countries in the time period 2007-2020, and shows a country's Gini coefficient in the 1st sheet, and their GDP per capita in the 2nd.
I would like to find whether GDP per capita has a significant effect on the Gini coefficient, but I don't know how to start, unless the only option is to create 24 different regressions for each country.

Could someone help me proceed?

Many thanks

I'm thinking : 10.3 Fixed Effects Regression | Introduction to Econometrics with R (econometrics-with-r.org)

The first step is to get the data all into one dataframe using merge()--or better, use tidyverse and get the data into one tibble using left_join().

Next, lm(Ginie ~ GDPperCapita). After that, you might think about including the country identifier as a factor in the regression in order to create dummy variables for each country.

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