US 1960 used car prices

The used.cars data frame has 48 rows and 2 columns. The data set includes a neighbours list for the 48 states excluding DC from poly2nb().

used.cars

Format

This data frame contains the following columns:

• tax.charges: taxes and delivery charges for 1955-9 new cars

• price.1960: 1960 used car prices by state

Source

Hanna, F. A. 1966 Effects of regional differences in taxes and transport charges on automobile consumption, in Ostry, S., Rhymes, J. K. (eds) Papers on regional statistical studies, Toronto: Toronto University Press, pp. 199-223.

References

Hepple, L. W. 1976 A maximum likelihood model for econometric estimation with spatial series, in Masser, I (ed) Theory and practice in regional science, London: Pion, pp. 90-104.

Examples

if (requireNamespace("spdep", quietly = TRUE)) {
  library(spdep)
  data(used.cars)
  moran.test(used.cars$price.1960, nb2listw(usa48.nb))
  moran.plot(used.cars$price.1960, nb2listw(usa48.nb),
           labels=rownames(used.cars))
  uc.lm <- lm(price.1960 ~ tax.charges, data=used.cars)
  summary(uc.lm)

  lm.morantest(uc.lm, nb2listw(usa48.nb))
  lm.morantest.sad(uc.lm, nb2listw(usa48.nb))
  lm.LMtests(uc.lm, nb2listw(usa48.nb))
# \donttest{
  if (requireNamespace("spatialreg", quietly = TRUE)) {
    library(spatialreg)
    uc.err <- errorsarlm(price.1960 ~ tax.charges, data=used.cars,
                       nb2listw(usa48.nb), tol.solve=1.0e-13, 
                       control=list(tol.opt=.Machine$double.eps^0.3))
    summary(uc.err)
    uc.lag <- lagsarlm(price.1960 ~ tax.charges, data=used.cars,
                     nb2listw(usa48.nb), tol.solve=1.0e-13, 
                     control=list(tol.opt=.Machine$double.eps^0.3))
    summary(uc.lag)
    uc.lag1 <- lagsarlm(price.1960 ~ 1, data=used.cars,
                      nb2listw(usa48.nb), tol.solve=1.0e-13, 
                      control=list(tol.opt=.Machine$double.eps^0.3))
    summary(uc.lag1)
    uc.err1 <- errorsarlm(price.1960 ~ 1, data=used.cars,
                        nb2listw(usa48.nb), tol.solve=1.0e-13, 
                        control=list(tol.opt=.Machine$double.eps^0.3),
                        Durbin=FALSE)
    summary(uc.err1)
  }
# }
}
#> Please update scripts to use lm.RStests in place of lm.LMtests
#> Loading required package: Matrix
#> 
#> Attaching package: ‘spatialreg’
#> The following objects are masked from ‘package:spdep’:
#> 
#>     get.ClusterOption, get.VerboseOption, get.ZeroPolicyOption,
#>     get.coresOption, get.mcOption, set.ClusterOption,
#>     set.VerboseOption, set.ZeroPolicyOption, set.coresOption,
#>     set.mcOption

#> 
#> Call:
#> errorsarlm(formula = price.1960 ~ 1, data = used.cars, listw = nb2listw(usa48.nb), 
#>     Durbin = FALSE, tol.solve = 1e-13, control = list(tol.opt = .Machine$double.eps^0.3))
#> 
#> Residuals:
#>      Min       1Q   Median       3Q      Max 
#> -76.1518 -18.2214   5.2489  21.6309  63.4983 
#> 
#> Type: error 
#> Coefficients: (asymptotic standard errors) 
#>             Estimate Std. Error z value  Pr(>|z|)
#> (Intercept) 1542.607     27.321  56.462 < 2.2e-16
#> 
#> Lambda: 0.82919, LR test value: 54.202, p-value: 1.8086e-13
#> Asymptotic standard error: 0.070993
#>     z-value: 11.68, p-value: < 2.22e-16
#> Wald statistic: 136.42, p-value: < 2.22e-16
#> 
#> Log likelihood: -240.977 for error model
#> ML residual variance (sigma squared): 1045.4, (sigma: 32.333)
#> Number of observations: 48 
#> Number of parameters estimated: 3 
#> AIC: 487.95, (AIC for lm: 540.16)
#>