
  library(AER)
  library(plm)
  data(Guns)
  model <- plm(log(violent) ~ law, data = Guns, index = c("state", "year"), model = "pooling")
  model_fe <- plm(log(violent) ~ law, data = Guns, index = c("state", "year"), model = "within")


  # estimate a model with state and time fixed effects using plm()
  model_sete <- 
  
  # print a summary using robust standard errors
  
  
  # test whether state and time fixed effects are jointly significant from zero


  # estimate a model with state and time fixed effects using plm()
  model_sete <- plm(log(violent) ~ law, data = Guns, index = c("state", "year"), model = "within", effect = "twoways")
  
  # print a summary using robust standard errors
  coeftest(model_sete, vcov. = vcovHC, type = "HC1")
  
  # test whether state and time fixed effects are jointly significant from zero
  pFtest(model_sete, model)


  ex() %>% check_function("plm") %>% {
    check_arg(., "formula") %>% check_equal()
    check_arg(., "data") %>% check_equal()
    check_arg(., "index") %>% check_equal()
    check_arg(., "model") %>% check_equal()
    check_arg(., "effect") %>% check_equal()
  }
  test_function("coeftest", args="x")
  test_student_typed("vcov. = vcovHC")
  ex() %>% check_function("pFtest") %>% {
    check_arg(., "x") %>% check_equal()
    check_arg(., "z") %>% check_equal()
  }
  success_msg("Correct! Including state and time effects results in a very small coefficient estimate which is not significantly different from zero at any common level. The F-test reveals that state and time fixed effects are jointly significantly different from zero.")