Demand: Per-capita demand deposits by state and year

In SASmixed: Data sets from "SAS System for Mixed Models"

Description

The Demand data frame has 77 rows and 8 columns of data on per-capita demand deposits by state and year.

Format

This data frame contains the following columns:

State

an ordered factor with levels WA < FL < CA < TX < IL < DC < NY

Year

an ordered factor with levels 1949 < ... < 1959

d

a numeric vector of per-capita demand deposits

y

a numeric vector of permanent per-capita personal income

rd

a numeric vector of service charges on demand deposits

rt

a numeric vector of interest rates on time deposits

rs

a numeric vector of interest rates on savings and loan association shares.

Source

Littel, R. C., Milliken, G. A., Stroup, W. W., and Wolfinger, R. D. (1996), SAS System for Mixed Models, SAS Institute (Data Set 1.2.4).

Feige, E. L. (1964), The Demand for Liquid Assets: A Temporal Cross-Sectional Analysis., Prentice Hall.

Examples

str(Demand)
if (require("lme4", quietly = TRUE, character = TRUE)) {
  ## compare to output 3.13, p. 132
  summary(fm1Demand <-
      lmer(log(d) ~ log(y) + log(rd) + log(rt) + log(rs) + (1|State) + (1|Year),
         Demand))
}

Example output

'data.frame':	77 obs. of  7 variables:
 $ State: Factor w/ 7 levels "CA","DC","FL",..: 1 1 1 1 1 1 1 1 1 1 ...
 $ Year : num  1949 1950 1951 1952 1953 ...
 $ d    : num  533 603 669 651 609 634 665 676 642 678 ...
 $ y    : num  1347 1464 1608 1636 1669 ...
 $ rd   : num  0.343 0.364 0.367 0.369 0.41 0.499 0.496 0.533 0.63 0.667 ...
 $ rt   : num  1.11 1.16 1.49 1.57 1.59 ...
 $ rs   : num  2.9 2.94 3.09 3.07 3.36 ...
 - attr(*, "ginfo")=List of 7
  ..$ formula     :Class 'formula'  language d ~ Year | State
  .. .. ..- attr(*, ".Environment")=<environment: R_GlobalEnv> 
  ..$ order.groups: logi TRUE
  ..$ FUN         :function (x)  
  ..$ outer       : NULL
  ..$ inner       : NULL
  ..$ labels      :List of 1
  .. ..$ d: chr "per capita demand deposits"
  ..$ units       : list()
Linear mixed model fit by REML ['lmerMod']
Formula: log(d) ~ log(y) + log(rd) + log(rt) + log(rs) + (1 | State) +  
    (1 | Year)
   Data: Demand

REML criterion at convergence: -240.2

Scaled residuals: 
     Min       1Q   Median       3Q      Max 
-2.13817 -0.59489  0.04588  0.47185  2.58156 

Random effects:
 Groups   Name        Variance  Std.Dev.
 Year     (Intercept) 0.0002646 0.01627 
 State    (Intercept) 0.0295052 0.17177 
 Residual             0.0011170 0.03342 
Number of obs: 77, groups:  Year, 11; State, 7

Fixed effects:
            Estimate Std. Error t value
(Intercept) -1.28384    0.72343  -1.775
log(y)       1.06978    0.10393  10.294
log(rd)     -0.29532    0.05246  -5.629
log(rt)      0.03988    0.02789   1.430
log(rs)     -0.32674    0.11438  -2.857

Correlation of Fixed Effects:
        (Intr) log(y) lg(rd) lg(rt)
log(y)  -0.976                     
log(rd)  0.383 -0.227              
log(rt)  0.077 -0.062 -0.337       
log(rs)  0.444 -0.600 -0.270 -0.323

SASmixed documentation built on May 1, 2019, 9:18 p.m.