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In jironghuang/shiftshare: Shift Share Analysis

Shift Share Analysis

During my career, I often have to deal with compositional & within group type of analysis. For instance, the employment rate fell by 3% across 2 period. How much of it is due to an increase in employment rate within the sub-group and how much of it is due to compositional shift (for example ageing population).

A formal way to explain these effects is known as shift-share analysis. It allows you to decompose percentage point change or absolute changes (WIP) into within group and across group effects.

A package currently used in the R community is REAT, but it doesn't allow you to decompose the effects into finer categories. Hence, I hope this package developed here is able to fill up the gap.

Some possible applications are the following,

• Employment rate
• Demographics rate
• Basketball field goal % for 2 point vs 3 point

To start using this package, you may first install the devtools package and execute the following command. install_github("jironghuang/shiftshare").

You may follow the example to better understand how this package works. Essentially, what the example does is to decompose the 29.7% point change into 3 effects. Within effect == 68.8%, Across_effect == -7.4% and Dynamic Effect == -31.8%

Quick example

emp1 = c(10, 20, 40, 50)
pop1 = c(40, 50, 60, 70)
emp2 = c(20, 30, 50, 60)
pop2 = c(50, 70, 20, 50)

ss_analysis <- shift_share(ap_grp_labels = c("grp1", "grp2", "grp3", "grp4"),
                           ap_numerator1 = emp1,
                           ap_numerator2 = emp2,
                           ap_denominator1 = pop1,
                           ap_denominator2 = pop2)

> ss_analysis$get_effects()
  grp_labels     prop1     prop2     rate1     rate2 within_effect across_effect dynamic_effect overall_effect
1       grp1 0.1818182 0.2631579 0.2500000 0.4000000   0.027272727    0.02033493    0.012200957     0.05980861
2       grp2 0.2272727 0.3684211 0.4000000 0.4285714   0.006493506    0.05645933    0.004032809     0.06698565
3       grp3 0.2727273 0.1052632 0.6666667 2.5000000   0.500000000   -0.11164274   -0.307017544     0.08133971
4       grp4 0.3181818 0.2631579 0.7142857 1.2000000   0.154545455   -0.03930280   -0.026725906     0.08851675  

> ss_analysis$get_agg_effects()
         Description within_effect across_effect dynamic_effect overall_effect
1 aggregated_effects     0.6883117   -0.07415129     -0.3175097      0.2966507

jironghuang/shiftshare documentation built on May 15, 2019, 1:16 p.m.