Iowa farmland values by county in 1925

data("wallace.iowaland")

Format

A data frame with 99 observations on the following 10 variables.

county: county factor, 99 levels
fips: FIPS code (state+county)
lat: latitude
long: longitude
yield: average corn yield per acre (bu)
corn: percent of land in corn
grain: percent of land in small grains
untillable: percent of land untillable
fedval: land value (excluding buildings) per acre, 1925 federal census
stval: land value (excluding buildings) per acre, 1925 state census

Details

None.

Source

H.A. Wallace (1926). Comparative Farm-Land Values in Iowa. The Journal of Land & Public Utility Economics, 2, 385-392. Page 387-388. https://doi.org/10.2307/3138610

References

Larry Winner. Spatial Data Analysis. https://www.stat.ufl.edu/~winner/data/iowaland.txt

Examples

# \dontrun{

library(agridat)
data(wallace.iowaland)
dat <- wallace.iowaland

# Interesting trends involving latitude
libs(lattice)
splom(~dat[,-c(1:2)], type=c('p','smooth'), lwd=2, main="wallace.iowaland")

# Means. Similar to Wallace table 1
apply(dat[, c('yield','corn','grain','untillable','fedval')], 2, mean)
#>      yield       corn      grain untillable     fedval 
#>   39.11111   32.47475   21.55556   18.84848  118.67677 

# Correlations.  Similar to Wallace table 2
round(cor(dat[, c('yield','corn','grain','untillable','fedval')]),2)
#>            yield  corn grain untillable fedval
#> yield       1.00  0.30  0.27      -0.16   0.61
#> corn        0.30  1.00  0.61      -0.82   0.81
#> grain       0.27  0.61  1.00      -0.59   0.62
#> untillable -0.16 -0.82 -0.59       1.00  -0.69
#> fedval      0.61  0.81  0.62      -0.69   1.00

m1 <- lm(fedval ~ yield + corn + grain + untillable, dat)
summary(m1) # estimates similar to Wallace, top of p. 389
#> 
#> Call:
#> lm(formula = fedval ~ yield + corn + grain + untillable, data = dat)
#> 
#> Residuals:
#>     Min      1Q  Median      3Q     Max 
#> -36.392  -7.797  -0.110   6.068  31.778 
#> 
#> Coefficients:
#>             Estimate Std. Error t value Pr(>|t|)    
#> (Intercept) -64.7071    17.3420  -3.731 0.000326 ***
#> yield         3.1488     0.3717   8.472 3.24e-13 ***
#> corn          1.8175     0.3090   5.881 6.20e-08 ***
#> grain         0.5394     0.2566   2.102 0.038229 *  
#> untillable   -0.5527     0.2697  -2.049 0.043270 *  
#> ---
#> Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
#> 
#> Residual standard error: 11.61 on 94 degrees of freedom
#> Multiple R-squared:  0.819,	Adjusted R-squared:  0.8113 
#> F-statistic: 106.3 on 4 and 94 DF,  p-value: < 2.2e-16
#> 

# Choropleth map
libs(maps)
data(county.fips)
dat <- transform(dat, polnm = paste0('iowa,',county)) # polnm example: iowa,adair

libs("latticeExtra") # for mapplot
redblue <- colorRampPalette(c("firebrick", "lightgray", "#375997"))
mapplot(polnm~fedval , data=dat, colramp=redblue,
        main="wallace.iowaland - Federal land values",
        xlab="Land value, dollars per acre",
        scales=list(draw=FALSE),
        map=map('county', 'iowa', plot=FALSE,
          fill=TRUE, projection="mercator"))
#> Warning: 6 unmatched regions: iowa,blackhawk, iowa,buenavista, iowa,cerrogordo, iowa,d....

# }