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Srinivasulu Rajendran
 Centre for the Study of Regional Development (CSRD)


Jawaharlal Nehru University (JNU)
                      New Delhi
                        India
              r.srinivasulu@gmail.com
Objective of the session



        1. To measure probability
         distribution of wealth &
       inequality through Lorenz
       Curve and Gini Coefficient
1. What is the procedure to
measure wealth inequality
through Lorenz Curve & Gini
Coefficient?
2. How do we interpret results?
What is Lorenz Curve

 the Lorenz curve is a graphical representation of the
  cumulative distribution function of the empirical
  probability distribution of wealth
 To measure wealth inequality.
 The Lorenz curve can give a clear graphic
  interpretation of the Gini coefficient. Let’s make the
  Lorenz curve of per capita FOOD expenditure
  distribution of Bangladesh.
Step 1
 we draw a set of axes in which the cumulative
 percentage of wealth is measured along the y-axis
 while the cumulative percentage of households is
 measured along the x-axis. Usually, the graph’s axes are
 closed off to form a box
Step 2
 to order the distribution from the smallest through
 to the largest, thereby enabling us to answer the
 following sequential questions:

A. what proportion of wealth is owned by the poorest
   10 percent of the population?
B. what proportion of wealth is owned by the poorest
   20 percent of the population?
C. what proportion of wealth is owned by the poorest
   30 percent of the population?

   This process continues until we reach the
   point where 100 per cent of wealth is owned
   by 100 per cent of the population.
Step 3
Assume that we live in a truly
equal society
 If this were to be the case, the relationship would be
  such that as we move along the x-axis, each 10 per cent
  increment of households would own an additional 10
  per cent of wealth.
 In this case, the line we would draw would be a straight
  line emanating from the origin. This is known as the
  line of absolute equality and will have a slope of 45
  degrees.
Step 4
 Finally, we can insert a line that is based on the data
 set available to us. In this case, the line will bow away
 from the line of absolute equality. The more unequal
 society is, the further it will deviate away from the line
 of absolute equality. It is this line which is known as
 the Lorenz Curve.
Step 5
STATA Program
                           For District 1
glcurve pcmfx if district ==1, gl(gl2) p(p2) lorenz

twoway line gl2 p2 , sort || line p p , ///
xlabel(0(.1)1) ylabel(0(.1)1) ///
xline(0(.2)1) yline(0(.2)1)     ///
title("Lorenz curve") subtitle("Monthly Per Capita Food Expenditure - Manikganj")
    ///
legend(label(1 "Lorenz curve") label(2 "Line of perfect
  equality")) ///
plotregion(margin(zero)) aspectratio(1) scheme(economist)
1                                                      2
    Lorenz curve                                           Lorenz curve
    Monthly Per Capita Food Expenditure - Manikganj        Monthly Per Capita Food Expenditure - Mymensingh

          Lorenz curve      Line of perfect equality             Lorenz curve      Line of perfect equality
                                            1                                                      1
                                            .9
                                               A                                                   .9
                                                                                                       A
                                            .8                                                     .8
                                            .7                                                     .7
                                            .6                                                     .6
                                            .5                                                     .5
                                            .4                                                     .4
                                            .3                                                     .3
                                            .2                                                     .2
                                            .1                                                     .1
                                            0                                                      0
       O   0 .1 .2 .3 .4 .5 .6 .7 .8 .9 1
           Cumulative population proportion
                                                             O    0 .1 .2 .3 .4 .5 .6 .7 .8 .9 1
                                                                  Cumulative population proportion



3                                                      4
    Lorenz curve                                           Lorenz curve
    Monthly Per Capita Food Expenditure-Kishoreganj        Monthly Per Capita Food Expenditure-Jessore

          Lorenz curve      Line of perfect equality             Lorenz curve      Line of perfect equality
                                            1                                                      1
                                            .9   A                                                 .9   A
                                            .8                                                     .8
                                            .7                                                     .7
                                            .6                                                     .6
                                            .5                                                     .5
                                            .4                                                     .4
                                            .3                                                     .3
                                            .2                                                     .2
                                            .1                                                     .1
                                            0                                                      0
      O    0 .1 .2 .3 .4 .5 .6 .7 .8 .9 1
           Cumulative population proportion
                                                             O    0 .1 .2 .3 .4 .5 .6 .7 .8 .9 1
                                                                  Cumulative population proportion
Step 6
Interpretation

 In above figures, the line of absolute equality is
  labelled OA. However, the Lorenz curve assumes a
  different shape in the four diagrams. In Figure
  2, Mymensingh District, it can be seen that the poorest
  sections of society command a very small proportion
  of the country’s wealth.
 In Figure 4 Jessore District, societal wealth remains
  unevenly distributed, but the poorer households are
  (on average) better off as compare to Mymensingh
  District.
 One of the advantages of using the Lorenz Curve is
  that it provides a visual representation of the
  information we wish to consider, in this case the
  inequality of wealth prevailing in society.
 We could superimpose several Lorenz Curves onto the
  same diagram to show changes in the way in which
  wealth has been distributed across society at various
  points in time.
 Even if the shape of the Lorenz Curve is not changing
  significantly, poorer members of society may still be
  much better off in terms of what they can afford to
  buy.
 In other words, they are relatively no better off, but in
  terms of spending power, they have the opportunity to
  enjoy a wider range of luxury items. Commodities
  which were considered to be luxuries fifty years ago
  (for example, televisions and telephones) are now
  taken for granted by most people.
Hands-on exercises
 Now repeat this exercise based on per capita total
  expenditure for village adopted technology and not
  adopted technology and compare its Lorenz curve
  with the Lorenz curve for the whole area. What
  conclusions emerge?
 Now repeat this exercise per capita total expenditure
  for female head and male head household and
  compare its Lorenz curve with the Lorenz curve for the
  whole area. What conclusions emerge?
The Gini Coefficient
 The  Gini coefficient is to
                                     Lorenz curve
 measure      the    degree     of
                                     Monthly Per Capita Food Expenditure-Jessore
 concentration (inequality) of a
 variable in a distribution of its       Lorenz curve       Line of perfect equality
                                                                            1 A
 elements. It is the ratio of the                                           .9
 area between the Lorenz Curve                                              .8
 and the line of absolute                                                   .7
                                                                            .6
 equality (numerator) and the
                                                                            .5
 whole area under the line of                            C                  .4
 absolute                 equality                                          .3
 (denominator).      Based     on                                           .2
                                                                            .1
 Figure Four, it can be seen that                                           0
                                           0 .1 .2 .3 .4 .5 .6 .7 .8 .9 1       B
 the Gini Coefficient = C/0AB.       O     Cumulative population proportion
Interpretation for Gini Coefficient
 The extreme values of the Gini Coefficient are 0 and 1.
 These are often presented in statistical publications as
  percentages. Hence, the corresponding extreme values
  are 0% and 100%.
 The former implies perfect equality (in other words,
  everyone in society has exactly the same amount of
  wealth) whereas the latter implies total inequality in
  that one person has all the wealth and everyone else
  has nothing.
 Clearly, these two extremes are trivial;
The key thing to bear in mind is
that the lower the figure that
Gini Coefficient takes (between
0% and 100%), the greater the
degree of prevailing equality.
STATA Program
 Atkinson, inequal, lorenz, relsgini


 These four ado-files provide a variety of measures of
    inequality.
   atkinson computes the Atkinson inequality index using
    the inequality aversion para-meter(s) specified in the
    parameter list.
   inequal displays the following measures: relative mean
    deviation, coefficient of variation, standard deviation of
    logs, Gini index, Mehran index, Piesch index, Kakwani
    index, Theil entropy index, and mean log deviation.
   lorenz displays a Lorenz curve.
   relsgini computes the Donaldson-Weymark relative S-
    Gini using the distributional sensitivity parameters
    specified in the parameter list.
“inequal” command

   inequality measures of pcmfx

   relative mean deviation            .16517609
   coefficient of variation           .47881288
   standard deviation of logs         .41682198
   Gini coefficient                   .23579119
   Mehran measure                     .32276405
   Piesch measure                     .19230475
   Kakwani measure                    .05184636
   Theil entropy measure              .09620768
   Theil mean log deviation measure   .09104455

Hands-on Exercise
Let’s continue using the per capita total expenditure to
   calculate inequality measures:
i. Compute the Gini coefficient, the Theil index and the
   Atkinson index with inequality aversion
parameter equal to 1 for the four districts.
                     Gini         Theil        Atkinson
All regions          ________ ________        ________
District wise:       ________ ________         ________
Hands-Exercise
ii. Now repeat the above exercise using two
  decile dispersion ratios and the share of
  consumption of poorest 25%. STATA
  command xtile is good for dividing the
  sample by ranking. For example, to calculate
  the consumption expenditure ratio between
  richest 20% and poorest 20%, you need to
  identify those two groups.
Reference for inequality
 http://web.worldbank.org/WBSITE/EXTERNAL/TOPI
 CS/EXTPOVERTY/EXTPA/0,,contentMDK:20238991~
 menuPK:492138~pagePK:148956~piPK:216618~theSiteP
 K:430367,00.html

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Topic 19 inequality stata

  • 1. Srinivasulu Rajendran Centre for the Study of Regional Development (CSRD) Jawaharlal Nehru University (JNU) New Delhi India r.srinivasulu@gmail.com
  • 2. Objective of the session 1. To measure probability distribution of wealth & inequality through Lorenz Curve and Gini Coefficient
  • 3. 1. What is the procedure to measure wealth inequality through Lorenz Curve & Gini Coefficient? 2. How do we interpret results?
  • 4. What is Lorenz Curve  the Lorenz curve is a graphical representation of the cumulative distribution function of the empirical probability distribution of wealth  To measure wealth inequality.  The Lorenz curve can give a clear graphic interpretation of the Gini coefficient. Let’s make the Lorenz curve of per capita FOOD expenditure distribution of Bangladesh.
  • 6.  we draw a set of axes in which the cumulative percentage of wealth is measured along the y-axis while the cumulative percentage of households is measured along the x-axis. Usually, the graph’s axes are closed off to form a box
  • 8.  to order the distribution from the smallest through to the largest, thereby enabling us to answer the following sequential questions: A. what proportion of wealth is owned by the poorest 10 percent of the population? B. what proportion of wealth is owned by the poorest 20 percent of the population? C. what proportion of wealth is owned by the poorest 30 percent of the population? This process continues until we reach the point where 100 per cent of wealth is owned by 100 per cent of the population.
  • 10. Assume that we live in a truly equal society  If this were to be the case, the relationship would be such that as we move along the x-axis, each 10 per cent increment of households would own an additional 10 per cent of wealth.  In this case, the line we would draw would be a straight line emanating from the origin. This is known as the line of absolute equality and will have a slope of 45 degrees.
  • 12.  Finally, we can insert a line that is based on the data set available to us. In this case, the line will bow away from the line of absolute equality. The more unequal society is, the further it will deviate away from the line of absolute equality. It is this line which is known as the Lorenz Curve.
  • 14. STATA Program For District 1 glcurve pcmfx if district ==1, gl(gl2) p(p2) lorenz twoway line gl2 p2 , sort || line p p , /// xlabel(0(.1)1) ylabel(0(.1)1) /// xline(0(.2)1) yline(0(.2)1) /// title("Lorenz curve") subtitle("Monthly Per Capita Food Expenditure - Manikganj") /// legend(label(1 "Lorenz curve") label(2 "Line of perfect equality")) /// plotregion(margin(zero)) aspectratio(1) scheme(economist)
  • 15. 1 2 Lorenz curve Lorenz curve Monthly Per Capita Food Expenditure - Manikganj Monthly Per Capita Food Expenditure - Mymensingh Lorenz curve Line of perfect equality Lorenz curve Line of perfect equality 1 1 .9 A .9 A .8 .8 .7 .7 .6 .6 .5 .5 .4 .4 .3 .3 .2 .2 .1 .1 0 0 O 0 .1 .2 .3 .4 .5 .6 .7 .8 .9 1 Cumulative population proportion O 0 .1 .2 .3 .4 .5 .6 .7 .8 .9 1 Cumulative population proportion 3 4 Lorenz curve Lorenz curve Monthly Per Capita Food Expenditure-Kishoreganj Monthly Per Capita Food Expenditure-Jessore Lorenz curve Line of perfect equality Lorenz curve Line of perfect equality 1 1 .9 A .9 A .8 .8 .7 .7 .6 .6 .5 .5 .4 .4 .3 .3 .2 .2 .1 .1 0 0 O 0 .1 .2 .3 .4 .5 .6 .7 .8 .9 1 Cumulative population proportion O 0 .1 .2 .3 .4 .5 .6 .7 .8 .9 1 Cumulative population proportion
  • 17. Interpretation  In above figures, the line of absolute equality is labelled OA. However, the Lorenz curve assumes a different shape in the four diagrams. In Figure 2, Mymensingh District, it can be seen that the poorest sections of society command a very small proportion of the country’s wealth.  In Figure 4 Jessore District, societal wealth remains unevenly distributed, but the poorer households are (on average) better off as compare to Mymensingh District.
  • 18.  One of the advantages of using the Lorenz Curve is that it provides a visual representation of the information we wish to consider, in this case the inequality of wealth prevailing in society.  We could superimpose several Lorenz Curves onto the same diagram to show changes in the way in which wealth has been distributed across society at various points in time.  Even if the shape of the Lorenz Curve is not changing significantly, poorer members of society may still be much better off in terms of what they can afford to buy.
  • 19.  In other words, they are relatively no better off, but in terms of spending power, they have the opportunity to enjoy a wider range of luxury items. Commodities which were considered to be luxuries fifty years ago (for example, televisions and telephones) are now taken for granted by most people.
  • 20. Hands-on exercises  Now repeat this exercise based on per capita total expenditure for village adopted technology and not adopted technology and compare its Lorenz curve with the Lorenz curve for the whole area. What conclusions emerge?  Now repeat this exercise per capita total expenditure for female head and male head household and compare its Lorenz curve with the Lorenz curve for the whole area. What conclusions emerge?
  • 21. The Gini Coefficient  The Gini coefficient is to Lorenz curve measure the degree of Monthly Per Capita Food Expenditure-Jessore concentration (inequality) of a variable in a distribution of its Lorenz curve Line of perfect equality 1 A elements. It is the ratio of the .9 area between the Lorenz Curve .8 and the line of absolute .7 .6 equality (numerator) and the .5 whole area under the line of C .4 absolute equality .3 (denominator). Based on .2 .1 Figure Four, it can be seen that 0 0 .1 .2 .3 .4 .5 .6 .7 .8 .9 1 B the Gini Coefficient = C/0AB. O Cumulative population proportion
  • 22. Interpretation for Gini Coefficient  The extreme values of the Gini Coefficient are 0 and 1.  These are often presented in statistical publications as percentages. Hence, the corresponding extreme values are 0% and 100%.  The former implies perfect equality (in other words, everyone in society has exactly the same amount of wealth) whereas the latter implies total inequality in that one person has all the wealth and everyone else has nothing.  Clearly, these two extremes are trivial;
  • 23. The key thing to bear in mind is that the lower the figure that Gini Coefficient takes (between 0% and 100%), the greater the degree of prevailing equality.
  • 24. STATA Program  Atkinson, inequal, lorenz, relsgini  These four ado-files provide a variety of measures of inequality.  atkinson computes the Atkinson inequality index using the inequality aversion para-meter(s) specified in the parameter list.  inequal displays the following measures: relative mean deviation, coefficient of variation, standard deviation of logs, Gini index, Mehran index, Piesch index, Kakwani index, Theil entropy index, and mean log deviation.  lorenz displays a Lorenz curve.  relsgini computes the Donaldson-Weymark relative S- Gini using the distributional sensitivity parameters specified in the parameter list.
  • 25. “inequal” command  inequality measures of pcmfx   relative mean deviation .16517609  coefficient of variation .47881288  standard deviation of logs .41682198  Gini coefficient .23579119  Mehran measure .32276405  Piesch measure .19230475  Kakwani measure .05184636  Theil entropy measure .09620768  Theil mean log deviation measure .09104455 
  • 26. Hands-on Exercise Let’s continue using the per capita total expenditure to calculate inequality measures: i. Compute the Gini coefficient, the Theil index and the Atkinson index with inequality aversion parameter equal to 1 for the four districts. Gini Theil Atkinson All regions ________ ________ ________ District wise: ________ ________ ________
  • 27. Hands-Exercise ii. Now repeat the above exercise using two decile dispersion ratios and the share of consumption of poorest 25%. STATA command xtile is good for dividing the sample by ranking. For example, to calculate the consumption expenditure ratio between richest 20% and poorest 20%, you need to identify those two groups.
  • 28. Reference for inequality  http://web.worldbank.org/WBSITE/EXTERNAL/TOPI CS/EXTPOVERTY/EXTPA/0,,contentMDK:20238991~ menuPK:492138~pagePK:148956~piPK:216618~theSiteP K:430367,00.html