help: index dialog:

Title

index: Price, Quantity, and Value Index Numbers

Table of Contents

Syntax

Options

Description

*** Index Applications

*** Examples

Authors

Syntax

index LHS = RHS [if] [in] , [ lhs(str) rhs(str) base(#)
year(#) panel id(#) it(#) chain list summ
simple save(file_name)]

Options

lhs( ) LHS: Left Hand Side = Price - Quantity [ LHS( P, Q ) ]; default (p)

rhs( ) RHS: Right Hand Side = Quantity - Value [ RHS( Q, V ) ]; default (q)

base(#) Base Time Period; default (1)

year(#) Starting Year Period; default (1)

id(var) Cross Sections ID variable name}}

it(var) Time Series ID variable name

simple Display Simple Price, Quantity, and Value Index Numbers

chain Print Main Price & Quantity Index Numbers with chain

summ Report Summary Statistics

list Add Index Numbers Variables to Data File

save(file_name) Save Results in File (*.txt)

Description

index estimates Quantity, and Value Index Numbers, i.e., Divisia (Tornqvist–Theil), Paasche, Laspeyres, Fisher, Marshall-Edgeworth, Walsh, Bowley, Mitchell, Geometric Laspeyres, Harmonic Mean, and Simple Index Numbers.

An index number measures the relative change in price, quantity, value, or some other item of interest from one time period to another.

A simple index number measures the relative change in just one variable.

An index is a convenient way to express a change in a diverse group of items.
Converting data to indexes also makes it easier to assess the trend in a series composed of exceptionally large numbers.

* Unweighted Indexes
1- Simple Average of the Price Indexes
2- Simple Aggregate Index
* Weighted Indexes
1- Lespeyres Price Index
2- Paasche Price Index
3- Fisher’s Price Index

Laspeyres’ index tends to overweight goods whose prices have increased.

Paasche’s index tends to overweight goods whose prices have have decreased.

Fisher’s ideal index was developed in an attempt to offset these shortcomings.
It is the geometric mean of the Laspeyres and Paasche indexes.

* Comparison of the Laspeyres, Paasche and Fisher

If price and quantity changes (weighted by values) are negatively correlated, then Laspeyres index exceeds Paasche index.

if weighted price and quantity changes are positively correlated, then Paasche index exceeds Laspeyres index. Because consumers are usually pricetakers, they typically react to price changes by substituting goods or services that have become relatively cheaper for those that have
become relatively more expensive.; the substitution effect.

Geometric Laspeyres index: A weighted geometric average of the price relatives using the expenditure shares of the price reference period as weights. Also called Logarithmic Laspeyres index

Bowley Index: The arithmetic average of the Laspeyres price index and the Paasche price index.

* Laspeyres versus Paasche Index:

When is Laspeyres most appropriate and when is Paasche the better choice?

* Laspeyres
* Advantages
1- Requires quantity data from only the base period.
2- This allows a more meaningful comparison over time.
3- The changes in the index can be attributed to changes in the price.
* Disadvantages:
1- Does not reflect changes in buying patterns over time.
2- it may overweight goods whose prices increase.

* Paasche
* Advantages:
1- Because it uses quantities from the current period.
2- it reflects current buying habits.

* Disadvantages:
1- It requires quantity data for the current year.
2- Because different quantities are used each year
3- impossible to attribute changes in index to changes in price alone.
4- tends to overweight the goods whose prices have declined.
5- It requires the prices to be recomputed each year.

* Chained vs non-chained calculations[edit]

we have always had our price indices relative to some fixed base period.
An alternative is to take the base period for each time period to be the immediately
preceding time period. This can be done with any of the above indices.

Index Applications:

====================================================
*** Price, Quantity, and Value Index Numbers ***
----------------------------------------------------
* (1) Divisia (Tornqvist–Theil) Index *
* (2) Paasche Index *
* (3) Laspeyres Index *
* (4) Fisher Index *
* (5) Marshall-Edgeworth Index *
* (6) Walsh Index *
* (7) Bowley Index *
* (8) Mitchell Index *
* (9) Geometric Laspeyres Index *
* (10) Harmonic Mean Index *
----------------------------------------------------

* Definition:
* Po = Price at base time
* Qo = Quantity at base time
* Pt = Price at time t
* Qt = Quantity at time t
* Yo = ALL Values at base time
* Yt = ALL Values at time t
* Wo = (Po*Qo) / Yo
* Wt = (Pt*Qt) / Yt

--------------------------------------------------
(1) Divisia (Tornqvist–Theil Index):

* TT_P = Sum{ 0.5 * (Wo+Wt) * [ln(Pt)-ln(Po)] }
* TT_Q = Sum{ 0.5 * (Wo+Wt) * [ln(Qt)-ln(Qo)] }

+-----------------------------------------------------------+
| _Year | _TT_P | _TT_Q | _TT_Pc | _TT_Qc |
|-----------+-----------+-----------+-----------+-----------|
1. | 1 | 100 | 100 | 100 | 100 |
2. | 2 | 121.6498 | 114.4852 | 121.6498 | 114.4852 |
3. | 3 | 171.3751 | 150 | 173.2402 | 148.4146 |
4. | 4 | 213.9295 | 166.9038 | 216.5502 | 164.9051 |
5. | 5 | 270.3362 | 184.9538 | 275.1124 | 181.739 |
6. | 6 | 318.0049 | 218.9944 | 323.7102 | 215.1335 |
+-----------------------------------------------------------+
* _TT_P = Divisia Price Index
* _TT_Q = Divisia Quantity Index
* _TT_Pc = Divisia Chained Price Index
* _TT_Qc = Divisia Chained Quantity Index

---------------------------------------------------------------------------------
T P1 Q1 P2 Q2 P1tQ1t P2tQ2t Y W1 W2 D1 D2 _TT_P
(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)
---------------------------------------------------------------------------------
(1) (2) (3) (4) (1*2) (3*4) (5+6) (5/7) (6/7) (10/11*100)
---------------------------------------------------------------------------------
1 6 10 4 20 60 80 140 0.43 0.57 0.00 0.00 100.00
2 7 10 5 25 70 125 195 0.36 0.64 0.06 0.14 121.65
3 8 15 8 30 120 240 360 0.33 0.67 0.11 0.43 171.38
4 10 17 10 33 170 330 500 0.34 0.66 0.20 0.56 213.93
5 14 20 12 35 280 420 700 0.40 0.60 0.35 0.64 270.34
6 15 25 15 40 375 600 975 0.38 0.62 0.37 0.78 318.00
---------------------------------------------------------------------------------
D1 = 10 = 0.5*(8 + 8_1)*(ln(1) - ln(1_1))
D2 = 11 = 0.5*(9 + 9_1)*(ln(3) - ln(3_1))
_TT_P = exp(D1+D2)*100

* Divisia (Tornqvist–Theil Index) (another method):
---------------------------------------------------------------------------------
T P1 Q1 P2 Q2 RP1 W1 Ws1 D1 RP2 W2 Ws2 D2 _TT_P
---------------------------------------------------------------------------------
1 6 10 4 1.00 1.00 0.43 0.43 1.00 1.00 0.57 0.57 1.00 100.00
2 7 10 5 1.17 1.17 0.36 0.39 1.06 1.25 0.64 0.61 1.14 121.65
3 8 15 8 1.33 1.33 0.33 0.38 1.12 2.00 0.67 0.62 1.54 171.38
4 10 17 10 1.67 1.67 0.34 0.38 1.22 2.50 0.66 0.62 1.76 213.93
5 14 20 12 2.33 2.33 0.40 0.41 1.42 3.00 0.60 0.59 1.90 270.34
6 15 25 15 2.50 2.50 0.38 0.41 1.45 3.75 0.62 0.59 2.19 318.00
---------------------------------------------------------------------------------
RP1 = P1t/P1o RP2 = P2t/P2o
W1 = P1t*Q1t/Y W2 = P2t*Q2t/Y
Ws1 = (W1t+W1o)/2 =	Ws2 = (W2t+W2o)/2 =
D1 = Q1t ^ Ws1 D2 = Q2t ^ Ws2
_TT_P = D1*D2*100

* Chaind Divisia (Tornqvist–Theil Index):
------------------------------------------------------------------------------------
T P1 Q1 P2 Q2 P1tQ1t P2tQ2t Y W1 W2 D1 D2 X Y
(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) (13)
------------------------------------------------------------------------------------
(1) (2) (3) (4) (1*2) (3*4) (5+6) (5/7) (6/7) (10/11*100) T
------------------------------------------------------------------------------------
1 6 10 4 20 60 80 140 0.43 0.57 0.00 0.00 100.0 100.0
2 7 10 5 25 70 125 195 0.36 0.64 0.06 0.14 121.6 121.6
3 8 15 8 30 120 240 360 0.33 0.67 0.05 0.31 142.4 173.2
4 10 17 10 33 170 330 500 0.34 0.66 0.08 0.15 125.0 216.6
5 14 20 12 35 280 420 700 0.40 0.60 0.12 0.11 127.0 275.1
6 15 25 15 40 375 600 975 0.38 0.62 0.03 0.14 117.7 323.7
------------------------------------------------------------------------------------
D1 = 10 = 0.5*(W1t + W1t_1)*(ln(P1t) - ln(P1t_1))
D2 = 11 = 0.5*(W2t + W2t_1)*(ln(P2t) - ln(21t_1))
_TT_Pc (1) = X:1 = 100.0
_TT_Pc (2) = X:2 * Y:1 / 100 = 121.6 * 100.0 / 100 = 121.6
_TT_Pc (3) = X:3 * Y:2 / 100 = 142.4 * 121.6 / 100 = 173.2
_TT_Pc (4) = X:4 * Y:3 / 100 = 125.0 * 173.2 / 100 = 216.6
_TT_Pc (5) = X:5 * Y:4 / 100 = 127.0 * 216.6 / 100 = 275.1
_TT_Pc (6) = X:6 * Y:5 / 100 = 117.7 * 275.1 / 100 = 323.7

--------------------------------------------------
(2) Paasche Index:

* P_P = Sum[Pt*Qt] / Sum(Po*Qt]
* P_Q = Sum[Pt*Qt] / Sum(Pt*Qo]

+-----------------------------------------------------------+
| _Year | _P_P | _P_Q | _P_Pc | _P_Qc |
|-----------+-----------+-----------+-----------+-----------|
1. | 1 | 100 | 100 | 100 | 100 |
2. | 2 | 121.875 | 114.7059 | 121.875 | 114.7059 |
3. | 3 | 171.4286 | 150 | 172.0588 | 147.479 |
4. | 4 | 213.6752 | 166.6667 | 215.0735 | 163.8656 |
5. | 5 | 269.2308 | 184.2105 | 273.7299 | 180.9241 |
6. | 6 | 314.5161 | 216.6667 | 321.5502 | 213.8194 |
+-----------------------------------------------------------+
* _P_P = Paasche Price Index
* _P_Q = Paasche Quantity Index
* _P_Pc = Paasche Chained Price Index
* _P_Qc = Paasche Chained Quantity Index

---------------------------------------------------------------------------------
T P1 Q1 P2 Q2 P1tQ1t P2tQ2t PtQt P1oQ1t P2oQ2 PoQt _P_P
---------------------------------------------------------------------------------
(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11)
---------------------------------------------------------------------------------
1 2 3 4 1*2 3*4 5+6 1*2 3*4 8+9 7/10*100
---------------------------------------------------------------------------------
1 6 10 4 20 60 80 140 60 80 140 100.00
2 7 10 5 25 70 125 195 60 100 160 121.88
3 8 15 8 30 120 240 360 90 120 210 171.43
4 10 17 10 33 170 330 500 102 132 234 213.68
5 14 20 12 35 280 420 700 120 140 260 269.23
6 15 25 15 40 375 600 975 150 160 310 314.52
---------------------------------------------------------------------------------

* Chaind Paasche Index:
------------------------------------------------------------------------------------
T P1 Q1 P2 Q2 P1tQ1t P2tQ2t D1 P1oQ1t P2oQ2 D2 X Y
(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)
------------------------------------------------------------------------------------
1 2 3 4 1*2 3*4 5+6 1*2 3*4 8+9 7/10*100
------------------------------------------------------------------------------------
1 6 10 4 20 60 80 140 60 80 140 100.0 100.0
2 7 10 5 25 70 125 195 60 100 160 121.9 121.9
3 8 15 8 30 120 240 360 105 150 255 141.2 172.1
4 10 17 10 33 170 330 500 136 264 400 125.0 215.1
5 14 20 12 35 280 420 700 200 350 550 127.3 273.7
6 15 25 15 40 375 600 975 350 480 830 117.5 321.6
------------------------------------------------------------------------------------
D1 = P1t * Q1t + P2t * Q2t
D1 = P1t-1 * Q1t + P2t-1 * Q2t
_P_Pc (1) = X:1 = 100.0
_P_Pc (2) = X:2 * Y:1 / 100 = 121.9 * 100.0 / 100 = 121.9
_P_Pc (3) = X:3 * Y:2 / 100 = 141.2 * 121.9 / 100 = 172.1
_P_Pc (4) = X:4 * Y:3 / 100 = 125.0 * 172.1 / 100 = 215.1
_P_Pc (5) = X:5 * Y:4 / 100 = 127.3 * 215.1 / 100 = 273.7
_P_Pc (6) = X:6 * Y:5 / 100 = 117.5 * 273.7 / 100 = 321.6

--------------------------------------------------
(3) Laspeyres Index:

* L_P = Sum[Pt*Qo] / Sum[Po*Qo]
* L_Q = Sum[Pt*Qt] / Sum[Po*Qo]

+-----------------------------------------------------------+
| _Year | _P_P | _P_Q | _P_Pc | _P_Qc |
|-----------+-----------+-----------+-----------+-----------|
1. | 1 | 100 | 100 | 100 | 100 |
2. | 2 | 121.875 | 114.7059 | 121.875 | 114.7059 |
3. | 3 | 171.4286 | 150 | 172.0588 | 147.479 |
4. | 4 | 213.6752 | 166.6667 | 215.0735 | 163.8656 |
5. | 5 | 269.2308 | 184.2105 | 273.7299 | 180.9241 |
6. | 6 | 314.5161 | 216.6667 | 321.5502 | 213.8194 |
+-----------------------------------------------------------+
* _P_P = Paasche Price Index
* _P_Q = Paasche Quantity Index
* _P_Pc = Paasche Chained Price Index
* _P_Qc = Paasche Chained Quantity Index

---------------------------------------------------------------------------------
T P1 Q1 P2 Q2 P1tQ1o P2tQ2o P1Q1 P1oQ1o P2oQ2o PoQo _L_P
(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11)
---------------------------------------------------------------------------------
1 2 3 4 1*2 3*4 5+6 1*2 3*4 8+9 7/10*100
---------------------------------------------------------------------------------
1 6 10 4 20 60 80 140 60 80 140 100.00
2 7 10 5 25 70 100 170 60 80 140 121.43
3 8 15 8 30 80 160 240 60 80 140 171.43
4 10 17 10 33 100 200 300 60 80 140 214.29
5 14 20 12 35 140 240 380 60 80 140 271.43
6 15 25 15 40 150 300 450 60 80 140 321.43
---------------------------------------------------------------------------------

--------------------------------------------------
(4) Fisher Index:

* F_P = Sum[ sqrt(Laspeyres_P * Paasche_P) ]
* F_Q = Sum[ sqrt(Laspeyres_Q * Paasche_Q) ]

+-----------------------------------------------------------+
| _Year | _F_P | _F_Q | _F_Pc | _F_Qc |
|-----------+-----------+-----------+-----------+-----------|
1. | 1 | 100 | 100 | 100 | 100 |
2. | 2 | 121.6516 | 114.4956 | 121.6516 | 114.4956 |
3. | 3 | 171.4286 | 150 | 173.2051 | 148.4615 |
4. | 4 | 213.9803 | 166.9046 | 216.5063 | 164.9572 |
5. | 5 | 270.3274 | 184.9609 | 275.0413 | 181.7909 |
6. | 6 | 317.9536 | 219.0347 | 323.6229 | 215.1976 |
+-----------------------------------------------------------+
* _F_P = Fisher Price Index
* _F_Q = Fisher Quantity Index
* _F_Pc = Fisher Chained Price Index
* _F_Qc = Fisher Chained Quantity Index

---------------------------------------------------------------------
T	P1	Q1	P2	Q2	Pach	Lasp	_F_P
(1)	(2)	(3)	(4)	(5)	(6)	(7)
---------------------------------------------------------------------
1	2	3	4 sqrt(5*6)*100
---------------------------------------------------------------------
1	6	10	4	20	100	100	100.00
2	7	10	5	25	122	121	121.65
3	8	15	8	30	171	171	171.43
4	10	17	10	33	214	214	213.98
5	14	20	12	35	269	271	270.33
6	15	25	15	40	315	321	317.95
---------------------------------------------------------------------

--------------------------------------------------
(5) Marshall-Edgeworth Index:

* ME_P = Sum[Pt*(Qo+Qt)] / Sum[(Po*Qo)+(Po*Qt)]
* ME_Q = Sum[Qt*(Po+Pt)] / Sum[(Po*Qo)+(Pt*Qo)]

+-----------------------------------+
| _Year | _ME_P | _ME_Q |
|-----------+-----------+-----------|
1. | 1 | 100 | 100 |
2. | 2 | 121.6667 | 114.5161 |
3. | 3 | 171.4286 | 150 |
4. | 4 | 213.9037 | 166.8182 |
5. | 5 | 270 | 184.6154 |
6. | 6 | 316.6667 | 217.7966 |
+-----------------------------------+
* _ME_P = Marshall-Edgeworth Price Index
* _ME_Q = Marshall-Edgeworth Quantity Index

-------------------------------------------------------------------------
T P1 Q1 P2 Q2 M1 M2 D1 P1Q1 P2Q2 D2 _ME_P
(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11)
-------------------------------------------------------------------------
1 2 3 4 5+6 8+9 7/10*100
-------------------------------------------------------------------------
1 6 10 4 20 120 160 280 120 160 280 100.00
2 7 10 5 25 140 225 365 120 180 300 121.67
3 8 15 8 30 200 400 600 150 200 350 171.43
4 10 17 10 33 270 530 800 162 212 374 213.90
5 14 20 12 35 420 660 1080 180 220 400 270.00
6 15 25 15 40 525 900 1425 210 240 450 316.67
-------------------------------------------------------------------------

M1 = P1t*(Q1o+Q1t) = 1 * (2_1 + 2)
M2 = P2o*(Q2o+Q2t) = 3_1 * (4_1 + 4)
P1Q1 = P1tQ1t = (1_1 * 2_1) + (1_1 + 2)
P2Q2 = P2oQ2o = (3_1 * 4_1) + (3_1 + 4)

--------------------------------------------------
(6) Walsh Index:

* W_P = Sum[Pt*sqrt(Qo*Qt)] / Sum[Po*sqrt(Qo*Qt)]
* W_Q = Sum[Qt*sqrt(Po*Pt)] / Sum[Qo*sqrt(Po*Pt)]

+-----------------------------------+
| _Year | _W_P | _W_Q |
|-----------+-----------+-----------|
1. | 1 | 100 | 100 |
2. | 2 | 121.6542 | 114.4964 |
3. | 3 | 171.4286 | 150 |
4. | 4 | 213.9808 | 166.899 |
5. | 5 | 270.3337 | 184.9528 |
6. | 6 | 317.9893 | 218.9898 |
+-----------------------------------+
* _W_P = Walsh Price Index
* _W_Q = Walsh Quantity Index

-------------------------------------------------------------------------
T P1 Q1 P2 Q2 M1 M2 D1 P1Q1 P2Q2 D2 _ME_P
(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11)
-------------------------------------------------------------------------
1 2 3 4 5+6 8+9 7/10*100
------------------------------------------------------------------------
1 6 10 4 20 60 80 140 60 80 140 100.00
2 7 10 5 25 70 112 182 60 89 149 121.65
3 8 15 8 30 98 196 294 73 98 171 171.43
4 10 17 10 33 130 257 387 78 103 181 213.98
5 14 20 12 35 198 317 515 85 106 191 270.33
6 15 25 15 40 237 424 661 95 113 208 317.99
-------------------------------------------------------------------------
M1 = P1t*(Q1o*Q1t)^0.5 = 1 * (2_1 * 2)^0.5
M2 = P2t*(Q2o+Q2t)^0.5 = 3 * (4_1 * 4)^0.5
P1Q1 = P1tQ1t = 1_1*(2_1 * 2)^0.5
P2Q2 = P2oQ2o = 3_1*(4_1 * 4)^0.5

--------------------------------------------------
(7) Bowley Index:

* B_P = Sum[ 0.5*(Laspeyres_P + Paasche_P) ]
* B_Q = Sum[ 0.5*(Laspeyres_Q + Paasche_Q) ]

+-----------------------------------------------------------+
| _Year | _B_P | _B_Q | _B_Pc | _B_Qc |
|-----------+-----------+-----------+-----------+-----------|
1. | 1 | 100 | 100 | 100 | 100 |
2. | 2 | 121.6518 | 114.4958 | 121.6518 | 114.4958 |
3. | 3 | 171.4286 | 150 | 173.2116 | 148.4671 |
4. | 4 | 213.9805 | 166.9048 | 216.5145 | 164.9634 |
5. | 5 | 270.3297 | 184.9624 | 275.0522 | 181.798 |
6. | 6 | 317.9724 | 219.0476 | 323.636 | 215.2064 |
+-----------------------------------------------------------+
* _B_P = Bowley Price Index
* _B_Q = Bowley Quantity Index
* _B_Pc = Bowley Chained Price Index
* _B_Qc = Bowley Chained Quantity Index

---------------------------------------------------------------------
T	P1	Q1	P2	Q2	Pach	Lasp	_F_P
(1)	(2)	(3)	(4)	(5)	(6)	(7)
---------------------------------------------------------------------
1	2	3	4 0.5(5+6)*100
---------------------------------------------------------------------
1	6	10	4	20	100	100	100.00
2	7	10	5	25	122	121	121.65
3	8	15	8	30	171	171	171.43
4	10	17	10	33	214	214	213.98
5	14	20	12	35	269	271	270.33
6	15	25	15	40	315	321	317.97
---------------------------------------------------------------------

--------------------------------------------------
(8) Mitchell Index:

* WtP = 0.5 * (Po+ Pt)
* WtQ = 0.5 * (Qo+ Qt)
* M_P = Sum[Pt*WtQ] / Sum[Po*WtQ]
* M_Q = Sum[Qt*WtP] / Sum[Qo*WtP]
* M_Pw = Sum[(Pt*WtQ/Po)] / Sum[WtQ]
* M_Qw = Sum[(Qt*WtP/Qo)] / Sum[WtP]

+-----------------------------------------------------------+
| _Year | _M_P | _M_Q | _M_Pw | _M_Qw |
|-----------+-----------+-----------+-----------+-----------|
1. | 1 | 100 | 100 | 100 | 100 |
2. | 2 | 121.6667 | 114.5161 | 122.4359 | 110.2273 |
3. | 3 | 171.4286 | 150 | 177.7778 | 150 |
4. | 4 | 213.9037 | 166.8182 | 221.875 | 167.6667 |
5. | 5 | 270 | 184.6154 | 276.4706 | 188.8889 |
6. | 6 | 316.6667 | 217.7966 | 328.9474 | 226.25 |
+-----------------------------------------------------------+
* _M_P = Mitchell Price Index
* _M_Q = Mitchell Quantity Index

--------------------------------------------------------------------------------------
T P1 Q1 P2 Q2 W1 W2 P1tW1 P2tW2 D1 P1oW1 P2oW2 D2 _M_P
(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) (13)
--------------------------------------------------------------------------------------
1 2 3 4 1*5 3*6 7+8 1*5 3*6 10+11 10/11*100
--------------------------------------------------------------------------------------
1 6 10 4 20 10.0 20.0 60.0 80 140 60 80 140 100.00
2 7 10 5 25 10.0 22.5 70.0 113 183 60 90 150 121.67
3 8 15 8 30 12.5 25.0 100.0 200 300 75 100 175 171.43
4 10 17 10 33 13.5 26.5 135.0 265 400 81 106 187 213.90
5 14 20 12 35 15.0 27.5 210.0 330 540 90 110 200 270.00
6 15 25 15 40 17.5 30.0 262.5 450 713 105 120 225 316.67
--------------------------------------------------------------------------------------
* W1 = 0.5 * (P1o+ P1t)
* W2 = 0.5 * (P2o+ P2t)

-----------------------------------------------------------------------
T P1 Q1 P2 Q2 W1 W2 P1W P2W D1 D2 _M_Pw
(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11)
-----------------------------------------------------------------------
1 2 3 4 1*5 3*6 7+8 5+6 9/10*100
-----------------------------------------------------------------------
1 6 10 4 20 10.0 20.0 10.0 20.0 30 30 100.00
2 7 10 5 25 10.0 22.5 11.7 28.1 40 33 122.44
3 8 15 8 30 12.5 25.0 16.7 50.0 67 38 177.78
4 10 17 10 33 13.5 26.5 22.5 66.3 89 40 221.88
5 14 20 12 35 15.0 27.5 35.0 82.5 118 43 276.47
6 15 25 15 40 17.5 30.0 43.8 112.5 156 48 328.95
-----------------------------------------------------------------------
P1W = P1t * W1 / P1o
P2W = P2t * W2 / P2o

--------------------------------------------------
(9) Geometric Laspeyres Index:

* GL_P = Sum{ (Wo) * [ln(Pt)-ln(Po)] }
* GL_Q = Sum{ (Wo) * [ln(Qt)-ln(Qo)] }

+-----------------------------------+
| _Year | _GL_P | _GL_Q |
|-----------+-----------+-----------|
1. | 1 | 100 | 100 |
2. | 2 | 121.3581 | 113.5997 |
3. | 3 | 168.0979 | 150 |
4. | 4 | 210.1224 | 167.1246 |
5. | 5 | 269.3674 | 185.307 |
6. | 6 | 315.1836 | 220.071 |
+-----------------------------------+
* _GL_P = Geometric Mean Price Index
* _GL_Q = Geometric Mean Quantity Index

------------------------------------------------------------------
T P1 Q1 P2 Q2 Wo1 Wo2 D1 D2 _GL_P
(1) (2) (3) (4) (5) (6) (7) (8) (9)
------------------------------------------------------------------
1 6 10 4 20 0.43 0.57 0.00 0.00 100.00
2 7 10 5 25 0.43 0.57 0.07 0.13 121.36
3 8 15 8 30 0.43 0.57 0.12 0.40 168.10
4 10 17 10 33 0.43 0.57 0.22 0.52 210.12
5 14 20 12 35 0.43 0.57 0.36 0.63 269.37
6 15 25 15 40 0.43 0.57 0.39 0.76 315.18
------------------------------------------------------------------
Wo1 = P1o * Q1o / Yo
Wo2 = P2o * Q2o / Yo
D1 = W1o * [ln(P1t) - ln(P1o)]
D2 = W2o * [ln(P2t) - ln(P2o)]
_GL_P = exp(D1+D2)*100

--------------------------------------------------
(10) Harmonic Mean Index:

* HM_P = Sum[Po*Qo] / Sum[(Po^2)*Qo/Pt]
* HM_Q = Sum[Po*Qo] / Sum[(Qo^2)*Po/Qt]

+-----------------------------------+
| _Year | _HM_P | _HM_Q |
|-----------+-----------+-----------|
1. | 1 | 100 | 100 |
2. | 2 | 121.2871 | 112.9032 |
3. | 3 | 164.7059 | 150 |
4. | 4 | 205.8824 | 167.1064 |
5. | 5 | 267.2727 | 184.9057 |
6. | 6 | 308.8235 | 218.75 |
+-----------------------------------+
* _HM_P = Harmonic Mean Price Index
* _HM_Q = Harmonic Mean Quantity Index

------------------------------------------------------------------------------------
T P1 Q1 P2 Q2 P1oQ1o P2oQ2o D1 P1oQ1oP1 P2oQ2oP2 D2 _H_P
(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11)
------------------------------------------------------------------------------------
1 2 3 4 1*2 3*4 5+6 1*2/1 3*4/3 8+9 7/10*100
------------------------------------------------------------------------------------
1 6 10 4 20 60 80 140 60 80 140 100.00
2 7 10 5 25 60 80 140 51 64 115 121.29
3 8 15 8 30 60 80 140 45 40 85 164.71
4 10 17 10 33 60 80 140 36 32 68 205.88
5 14 20 12 35 60 80 140 26 27 52 267.27
6 15 25 15 40 60 80 140 24 21 45 308.82
------------------------------------------------------------------------------------

--------------------------------------------------
*** Simple Price, Quantity,and Value Index Numbers ***

+-----------------------------------------------------------------------------------+
| _Year | _P_1 | _IP_1 | _Q_1 | _IQ_1 | _V_1 | _IV_1 |
|-----------+-----------+-----------+-----------+-----------+-----------+-----------|
| 1 | 6 | 100 | 10 | 100 | 60 | 100 |
| 2 | 7 | 116.6667 | 10 | 100 | 70 | 116.6667 |
| 3 | 8 | 133.3333 | 15 | 150 | 120 | 200 |
| 4 | 10 | 166.6667 | 17 | 170 | 170 | 283.3333 |
| 5 | 14 | 233.3333 | 20 | 200 | 280 | 466.6667 |
| 6 | 15 | 250 | 25 | 250 | 375 | 625 |
+-----------------------------------------------------------------------------------+
* _IP = Simple Price Index [ Pt / Po * 100 ]
* _IQ = Simple Quantity Index [ Qt / Qo * 100 ]
* _IV = Simple Value Index [ Vt / Vo * 100 ]

Examples

clear all

sysuse index.dta, clear

index p1 p2 = q1 q2 , summ list chain simple

index p1 p2 = q1 q2 , lhs(p) rhs(q) base(1) summ list chain year(2000) simple save(Index)

index p1 p2 = q1 q2 , panel id(id) it(t) lhs(p) rhs(q) base(1) summ list chain year(2000) simple

index p1 p2 = q1 q2 , lhs(p) rhs(q) simple

index p1 p2 = v1 v2 , lhs(p) rhs(v) simple

index q1 q2 = v1 v2 , lhs(q) rhs(v) simple

. clear all
. sysuse index.dta, clear
. index p1 p2 = q1 q2 , lhs(p) rhs(q) base(1) summ list chain year(2000) simple save(Index)

==================================================
*** Price, Quantity, and Value Index Numbers ***
--------------------------------------------------
* (1) Divisia Index (Tornqvist–Theil) *
* (2) Paasche Index *
* (3) Laspeyres Index *
* (4) Fisher Index *
* (5) Marshall-Edgeworth Index *
* (6) Walsh Index *
* (7) Bowley Index *
* (8) Mitchell Index *
* (9) Geometric Laspeyres Index *
* (10) Harmonic Mean Index *
--------------------------------------------------
* LHS: Left Hand Side = Price [ LHS( P ) ]
* RHS: Right Hand Side = Quantity [ RHS( Q ) ]

* Po = Price at base time * Pt = Price at time t
* Qo = Quantity at base time * Qt = Quantity at time t
* Yo = ALL Values at base time * Yt = ALL Values at time t

--------------------------------------------------
*** (1) Divisia Index (Tornqvist–Theil) ***

* Wo = (Po*Qo) / Yo
* Wt = (Pt*Qt) / Yt
* TT_P = Sum{ 0.5 * (Wo+Wt) * [ln(Pt)-ln(Po)] }
* TT_Q = Sum{ 0.5 * (Wo+Wt) * [ln(Qt)-ln(Qo)] }

+-----------------------------------------------------------+
| _Year | _TT_P | _TT_Q | _TT_Pc | _TT_Qc |
|-----------+-----------+-----------+-----------+-----------|
1. | 2000 | 100 | 100 | 100 | 100 |
2. | 2001 | 121.6498 | 114.4852 | 121.6498 | 114.4852 |
3. | 2002 | 171.3751 | 150 | 173.2402 | 148.4146 |
4. | 2003 | 213.9295 | 166.9038 | 216.5502 | 164.9051 |
5. | 2004 | 270.3362 | 184.9538 | 275.1124 | 181.739 |
6. | 2005 | 318.0049 | 218.9944 | 323.7102 | 215.1335 |
+-----------------------------------------------------------+
* _TT_P = Divisia Price Index
* _TT_Q = Divisia Quantity Index
* _TT_Pc = Divisia Chained Price Index
* _TT_Qc = Divisia Chained Quantity Index

--------------------------------------------------
*** (2) Paasche Index ***

* P_P = Sum[Pt*Qt] / Sum(Po*Qt]
* P_Q = Sum[Pt*Qt] / Sum(Pt*Qo]

+-----------------------------------------------------------+
| _Year | _P_P | _P_Q | _P_Pc | _P_Qc |
|-----------+-----------+-----------+-----------+-----------|
1. | 2000 | 100 | 100 | 100 | 100 |
2. | 2001 | 121.875 | 114.7059 | 121.875 | 114.7059 |
3. | 2002 | 171.4286 | 150 | 172.0588 | 147.479 |
4. | 2003 | 213.6752 | 166.6667 | 215.0735 | 163.8656 |
5. | 2004 | 269.2308 | 184.2105 | 273.7299 | 180.9241 |
6. | 2005 | 314.5161 | 216.6667 | 321.5502 | 213.8194 |
+-----------------------------------------------------------+
* _P_P = Paasche Price Index
* _P_Q = Paasche Quantity Index
* _P_Pc = Paasche Chained Price Index
* _P_Qc = Paasche Chained Quantity Index

--------------------------------------------------
*** (3) Laspeyres Index ***

* L_P = Sum[Pt*Qo] / Sum[Po*Qo]
* L_Q = Sum[Pt*Qt] / Sum[Po*Qo]

+-----------------------------------------------------------+
| _Year | _L_P | _L_Q | _L_Pc | _L_Qc |
|-----------+-----------+-----------+-----------+-----------|
1. | 2000 | 100 | 100 | 100 | 100 |
2. | 2001 | 121.4286 | 114.2857 | 121.4286 | 114.2857 |
3. | 2002 | 171.4286 | 150 | 174.359 | 149.4505 |
4. | 2003 | 214.2857 | 167.1429 | 217.9487 | 166.0562 |
5. | 2004 | 271.4286 | 185.7143 | 276.359 | 182.6618 |
6. | 2005 | 321.4286 | 221.4286 | 325.7088 | 216.5847 |
+-----------------------------------------------------------+
* _L_P = Laspeyres Price Index
* _L_Q = Laspeyres Quantity Index
* _L_Pc = Laspeyres Chained Price Index
* _L_Qc = Laspeyres Chained Quantity Index

--------------------------------------------------
*** (4) Fisher Index ***

* F_P = Sum[ sqrt(Laspeyres_P * Paasche_P) ]
* F_Q = Sum[ sqrt(Laspeyres_Q * Paasche_Q) ]

+-----------------------------------------------------------+
| _Year | _F_P | _F_Q | _F_Pc | _F_Qc |
|-----------+-----------+-----------+-----------+-----------|
1. | 2000 | 100 | 100 | 100 | 100 |
2. | 2001 | 121.6516 | 114.4956 | 121.6516 | 114.4956 |
3. | 2002 | 171.4286 | 150 | 173.2051 | 148.4615 |
4. | 2003 | 213.9803 | 166.9046 | 216.5063 | 164.9572 |
5. | 2004 | 270.3274 | 184.9609 | 275.0413 | 181.7909 |
6. | 2005 | 317.9536 | 219.0347 | 323.6229 | 215.1976 |
+-----------------------------------------------------------+
* _F_P = Fisher Price Index
* _F_Q = Fisher Quantity Index
* _F_Pc = Fisher Chained Price Index
* _F_Qc = Fisher Chained Quantity Index

--------------------------------------------------
*** (5) Marshall-Edgeworth Index ***

* ME_P = Sum[Pt*(Qo+Qt)] / Sum[(Po*Qo)+(Po*Qt)]
* ME_Q = Sum[Qt*(Po+Pt)] / Sum[(Po*Qo)+(Pt*Qo)]

+-----------------------------------+
| _Year | _ME_P | _ME_Q |
|-----------+-----------+-----------|
1. | 2000 | 100 | 100 |
2. | 2001 | 121.6667 | 114.5161 |
3. | 2002 | 171.4286 | 150 |
4. | 2003 | 213.9037 | 166.8182 |
5. | 2004 | 270 | 184.6154 |
6. | 2005 | 316.6667 | 217.7966 |
+-----------------------------------+
* _ME_P = Marshall-Edgeworth Price Index
* _ME_Q = Marshall-Edgeworth Quantity Index

--------------------------------------------------
*** (6) Walsh Index ***

* W_P = Sum[Pt*sqrt(Qo*Qt)] / Sum[Po*sqrt(Qo*Qt)]
* W_Q = Sum[Qt*sqrt(Po*Pt)] / Sum[Qo*sqrt(Po*Pt)]

+-----------------------------------+
| _Year | _W_P | _W_Q |
|-----------+-----------+-----------|
1. | 2000 | 100 | 100 |
2. | 2001 | 121.6542 | 114.4964 |
3. | 2002 | 171.4286 | 150 |
4. | 2003 | 213.9808 | 166.899 |
5. | 2004 | 270.3337 | 184.9528 |
6. | 2005 | 317.9893 | 218.9898 |
+-----------------------------------+
* _W_P = Walsh Price Index
* _W_Q = Walsh Quantity Index

--------------------------------------------------
*** (7) Bowley Index ***

* B_P = Sum[ 0.5*(Laspeyres_P + Paasche_P) ]
* B_Q = Sum[ 0.5*(Laspeyres_Q + Paasche_Q) ]

+-----------------------------------------------------------+
| _Year | _B_P | _B_Q | _B_Pc | _B_Qc |
|-----------+-----------+-----------+-----------+-----------|
1. | 2000 | 100 | 100 | 100 | 100 |
2. | 2001 | 121.6518 | 114.4958 | 121.6518 | 114.4958 |
3. | 2002 | 171.4286 | 150 | 173.2116 | 148.4671 |
4. | 2003 | 213.9805 | 166.9048 | 216.5145 | 164.9634 |
5. | 2004 | 270.3297 | 184.9624 | 275.0522 | 181.798 |
6. | 2005 | 317.9724 | 219.0476 | 323.636 | 215.2064 |
+-----------------------------------------------------------+
* _B_P = Bowley Price Index
* _B_Q = Bowley Quantity Index
* _B_Pc = Bowley Chained Price Index
* _B_Qc = Bowley Chained Quantity Index

--------------------------------------------------
*** (8) Mitchell Index ***

* WtP = 0.5 * (Po+ Pt)
* WtQ = 0.5 * (Qo+ Qt)
* M_P = Sum[Pt*WtQ] / Sum[Po*WtQ]
* M_Q = Sum[Qt*WtP] / Sum[Qo*WtP]
* M_Pw = Sum[(Pt*WtQ/Po)] / Sum[WtQ]
* M_Qw = Sum[(Qt*WtP/Qo)] / Sum[WtP]

+-----------------------------------------------------------+
| _Year | _M_P | _M_Q | _M_Pw | _M_Qw |
|-----------+-----------+-----------+-----------+-----------|
1. | 2000 | 100 | 100 | 100 | 100 |
2. | 2001 | 121.6667 | 114.5161 | 122.4359 | 110.2273 |
3. | 2002 | 171.4286 | 150 | 177.7778 | 150 |
4. | 2003 | 213.9037 | 166.8182 | 221.875 | 167.6667 |
5. | 2004 | 270 | 184.6154 | 276.4706 | 188.8889 |
6. | 2005 | 316.6667 | 217.7966 | 328.9474 | 226.25 |
+-----------------------------------------------------------+
* _M_P = Mitchell Price Index
* _M_Q = Mitchell Quantity Index

--------------------------------------------------
*** (9) Geometric Laspeyres Index ***

* GL_P = Sum{ Wo * [ln(Pt)-ln(Po)] }
* GL_Q = Sum{ Wo * [ln(Qt)-ln(Qo)] }

+-----------------------------------+
| _Year | _GL_P | _GL_Q |
|-----------+-----------+-----------|
1. | 2000 | 100 | 100 |
2. | 2001 | 121.3581 | 113.5997 |
3. | 2002 | 168.0979 | 150 |
4. | 2003 | 210.1224 | 167.1246 |
5. | 2004 | 269.3674 | 185.307 |
6. | 2005 | 315.1836 | 220.071 |
+-----------------------------------+
* _GL_P = Geometric Laspeyres Price Index
* _GL_Q = Geometric Laspeyres Quantity Index

--------------------------------------------------
*** (10) Harmonic Mean Index ***

* HM_P = Sum[Po*Qo] / Sum[(Po^2)*Qo/Pt]
* HM_Q = Sum[Po*Qo] / Sum[(Qo^2)*Po/Qt]

+-----------------------------------+
| _Year | _HM_P | _HM_Q |
|-----------+-----------+-----------|
1. | 2000 | 100 | 100 |
2. | 2001 | 121.2871 | 112.9032 |
3. | 2002 | 164.7059 | 150 |
4. | 2003 | 205.8824 | 167.1064 |
5. | 2004 | 267.2727 | 184.9057 |
6. | 2005 | 308.8235 | 218.75 |
+-----------------------------------+
* _HM_P = Harmonic Mean Price Index
* _HM_Q = Harmonic Mean Quantity Index

-------------------------------------------------------
*** Simple Price, Quantity, and Value Index Numbers ***

* Simple Index Number for Commodity: q1

+-----------------------------------------------------------------------------------+
| _Year | _P_1 | _IP_1 | _Q_1 | _IQ_1 | _V_1 | _IV_1 |
|-----------+-----------+-----------+-----------+-----------+-----------+-----------|
| 2000 | 6 | 100 | 10 | 100 | 60 | 100 |
| 2001 | 7 | 116.6667 | 10 | 100 | 70 | 116.6667 |
| 2002 | 8 | 133.3333 | 15 | 150 | 120 | 200 |
| 2003 | 10 | 166.6667 | 17 | 170 | 170 | 283.3333 |
| 2004 | 14 | 233.3333 | 20 | 200 | 280 | 466.6667 |
| 2005 | 15 | 250 | 25 | 250 | 375 | 625 |
+-----------------------------------------------------------------------------------+

* Simple Index Number for Commodity: q2

+-----------------------------------------------------------------------------------+
| _Year | _P_2 | _IP_2 | _Q_2 | _IQ_2 | _V_2 | _IV_2 |
|-----------+-----------+-----------+-----------+-----------+-----------+-----------|
| 2000 | 4 | 100 | 20 | 100 | 80 | 100 |
| 2001 | 5 | 125 | 25 | 125 | 125 | 156.25 |
| 2002 | 8 | 200 | 30 | 150 | 240 | 300 |
| 2003 | 10 | 250 | 33 | 165 | 330 | 412.5 |
| 2004 | 12 | 300 | 35 | 175 | 420 | 525 |
| 2005 | 15 | 375 | 40 | 200 | 600 | 750 |
+-----------------------------------------------------------------------------------+
* _IP = Price Simple Index Number [ Pt / Po * 100 ]
* _IQ = Quantity Simple Index Number [ Qt / Qo * 100 ]
* _IV = Value Simple Index Number [ Vt / Vo * 100 ]

---------------------------------------------------------------------------
*** Report Summary Statistics ***
----------------------------------------------------------------------

* (1) Summary Statistics for Price Index Numbers:

Variable | Obs Mean Std. Dev. Min Max
-------------+--------------------------------------------------------
_TT_P | 6 199.2159 84.87735 100 318.0049
_P_P | 6 198.4543 83.66524 100 314.5161
_L_P | 6 200 86.07068 100 321.4286
_F_P | 6 199.2236 84.85943 100 317.9536
_ME_P | 6 198.9443 84.43953 100 316.6667
_W_P | 6 199.2311 84.87001 100 317.9893
_B_P | 6 199.2271 84.86504 100 317.9724
_M_P | 6 198.9443 84.43953 100 316.6667
_M_Pw | 6 204.5844 88.69904 100 328.9474
_GL_P | 6 197.3549 84.07363 100 315.1836
_HM_P | 6 194.6619 82.06486 100 308.8235
_TT_Pc | 6 201.7105 87.24368 100 323.7102
_P_Pc | 6 200.7146 86.39321 100 321.5502
_L_Pc | 6 202.634 88.02825 100 325.7088
_F_Pc | 6 201.6712 87.20775 100 323.6229
_B_Pc | 6 201.6777 87.21306 100 323.636

----------------------------------------------------------------------
* (2) Summary Statistics for Quantity Index Numbers:

Variable | Obs Mean Std. Dev. Min Max
-------------+--------------------------------------------------------
_TT_Q | 6 155.8895 44.3191 100 218.9944
_P_Q | 6 155.375 43.50843 100 216.6667
_L_Q | 6 156.4286 45.1641 100 221.4286
_F_Q | 6 155.8993 44.3296 100 219.0347
_ME_Q | 6 155.6244 43.92439 100 217.7966
_W_Q | 6 155.8897 44.31533 100 218.9898
_B_Q | 6 155.9018 44.33346 100 219.0476
_M_Q | 6 155.6244 43.92439 100 217.7966
_M_Qw | 6 157.1721 47.77395 100 226.25
_GL_Q | 6 156.017 44.84983 100 220.071
_HM_Q | 6 155.6109 44.55306 100 218.75
_TT_Qc | 6 154.1129 42.74157 100 215.1335
_P_Qc | 6 153.4657 42.19345 100 213.8194
_L_Qc | 6 154.8398 43.3437 100 216.5847
_F_Qc | 6 154.1505 42.76605 100 215.1976
_B_Qc | 6 154.1551 42.76961 100 215.2064
------------------------------------------------------------------------------

------------------------------------------------------------------------------
*** Main Price & Quantity Index Numbers with CHAIN ***

* (1) (Divisia - Paasche - Laspeyres - Fisher) Index Numbers *

+---------------------------------------------------------------------------------------+
| _TT_P | _P_P | _L_P | _F_P | _TT_Q | _P_Q | _L_Q | _F_Q |
|----------+----------+----------+----------+----------+----------+----------+----------|
1. | 100 | 100 | 100 | 100 | 100 | 100 | 100 | 100 |
2. | 121.6498 | 121.875 | 121.4286 | 121.6516 | 114.4852 | 114.7059 | 114.2857 | 114.4956 |
3. | 171.3751 | 171.4286 | 171.4286 | 171.4286 | 150 | 150 | 150 | 150 |
4. | 213.9295 | 213.6752 | 214.2857 | 213.9803 | 166.9038 | 166.6667 | 167.1429 | 166.9046 |
5. | 270.3362 | 269.2308 | 271.4286 | 270.3274 | 184.9538 | 184.2105 | 185.7143 | 184.9609 |
6. | 318.0049 | 314.5161 | 321.4286 | 317.9536 | 218.9944 | 216.6667 | 221.4286 | 219.0347 |
+---------------------------------------------------------------------------------------+
* _TT_P = Divisia Price Index * _TT_Q = Divisia Quantity Index
* _P_P = Paasche Price Index * _P_Q = Paasche Quantity Index
* _L_P = Laspeyres Price Index * _L_Q = Laspeyres Quantity Index
* _F_P = Fisher Price Index * _F_Q = Fisher Quantity Index
--------------------------------------------------------------------------------

* (2) (Divisia - Paasche - Laspeyres - Fisher) Chained Index Numbers *

+---------------------------------------------------------------------------------------+
| _TT_Pc | _P_Pc | _L_Pc | _F_Pc | _TT_Qc | _P_Qc | _L_Qc | _F_Qc |
|----------+----------+----------+----------+----------+----------+----------+----------|
1. | 100 | 100 | 100 | 100 | 100 | 100 | 100 | 100 |
2. | 121.6498 | 121.875 | 121.4286 | 121.6516 | 114.4852 | 114.7059 | 114.2857 | 114.4956 |
3. | 173.2402 | 172.0588 | 174.359 | 173.2051 | 148.4146 | 147.479 | 149.4505 | 148.4615 |
4. | 216.5502 | 215.0735 | 217.9487 | 216.5063 | 164.9051 | 163.8656 | 166.0562 | 164.9572 |
5. | 275.1124 | 273.7299 | 276.359 | 275.0413 | 181.739 | 180.9241 | 182.6618 | 181.7909 |
6. | 323.7102 | 321.5502 | 325.7088 | 323.6229 | 215.1335 | 213.8194 | 216.5847 | 215.1976 |
+---------------------------------------------------------------------------------------+
* _TT_P = Divisia Chained Price Index * _TT_Q = Divisia Chained Quantity Index
* _P_P = Paasche Chained Price Index * _P_Q = Paasche Chained Quantity Index
* _L_P = Laspeyres Chained Price Index * _L_Q = Laspeyres Chained Quantity Index
* _F_P = Fisher Chained Price Index * _F_Q = Fisher Chained Quantity Index
--------------------------------------------------------------------------------

* Price Index Results File Has Been saved in:
Data Directory: D:\Stata
Open File: Index.txt
--------------------------------------------------

Authors

- Emad Abd Elmessih Shehata
Professor (PhD Economics)
Agricultural Research Center - Agricultural Economics Research Institute - Egypt
Email: emadstat@hotmail.com
WebPage at IDEAS: http://ideas.repec.org/f/psh494.html
WebPage at EconPapers: http://econpapers.repec.org/RAS/psh494.htm

- Sahra Khaleel A. Mickaiel
Professor (PhD Economics)
Cairo University - Faculty of Agriculture - Department of Economics - Egypt
Email: sahra_atta@hotmail.com
WebPage at IDEAS: http://ideas.repec.org/f/pmi520.html
WebPage at EconPapers: http://econpapers.repec.org/RAS/pmi520.htm

INDEX Citation

Emad Abd Elmessih Shehata & Mickaiel, Sahra Khaleel A. (2015)

INDEX: "Stata Module to Estimate Price, Quantity, and Value Index Numbers"

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