LifeCycleSavings            package:base            R Documentation

_I_n_t_e_r_c_o_u_n_t_r_y _L_i_f_e-_C_y_c_l_e _S_a_v_i_n_g_s _D_a_t_a

_D_e_s_c_r_i_p_t_i_o_n:

     Data on the savings ratio 1960-1970.

_U_s_a_g_e:

     data(LifeCycleSavings)

_F_o_r_m_a_t:

     A data frame with 50 observations on 5 variables.

       [,1]  sr     numeric  aggregate personal savings
       [,2]  pop15  numeric  % of population under 15
       [,3]  pop75  numeric  % of population over 75
       [,4]  dpi    numeric  real per-capita disposable income
       [,5]  ddpi   numeric  % growth rate of dpi

_D_e_t_a_i_l_s:

     Under the life-cycle savings hypothesis as developed by Franco
     Modigliani, the savings ratio (aggregate personal saving divided
     by disposable income) is explained by per-capita disposable
     income, the percentage rate of change in per-capita disposable
     income, and two demographic variables: the percentage of
     population less than 15 years old and the percentage of the
     population over 75 years old. The data are averaged over the
     decade 1960-1970 to remove the business cycle or other short-term
     fluctuations.

_S_o_u_r_c_e:

     The data were obtained from Belsley, Kuh and Welsch (1980). They
     in turn obtained the data from Sterling (1977).

_R_e_f_e_r_e_n_c_e_s:

     Sterling, Arnie (1977) Unpublished BS Thesis. Massachusetts
     Institute of Technology.

     Belsley, D. A., Kuh. E. and Welsch, R. E. (1980) _Regression
     Diagnostics_. New York: Wiley.

_E_x_a_m_p_l_e_s:

     require(stats)
     data(LifeCycleSavings)
     pairs(LifeCycleSavings, panel = panel.smooth,
           main = "LifeCycleSavings data")
     fm1 <- lm(sr ~ pop15 + pop75 + dpi + ddpi, data = LifeCycleSavings)
     summary(fm1)

