World Inflation

Methodology for Calculating Regional and Global Estimates of Price Inflation

To satisfy an increasing need for global and regional estimates of price inflation, the International Labor Organization developed the following method for calculating them.

Basically the method calculates regional price changes as a weighted geometric average of the price changes that have been reported in each of the countries of the region, weighting each country's price changes by its share of GDP in the region. Inflation is then calculated as the percentage change in the average over some period, using one of two possible base periods. Either the same month of the previous year is used as the base period or the previous month is. There are many issues to deal with other than determining the basic method, such as what to do about gaps in data, and the approaches taken to these issues are described here as well.

Currently, the Cleveland Fed uses the ILO method to prepare inflation estimates for seven groups of countries: a global estimate and six regional ones.

Step 1. Gathering price data

Constructing the estimates begins with obtaining the consumer price index (general indices) of every country that prepares them. These data are gathered by the ILO and are available for download on the ILO website:

Step 2. Refine the dataset

After all the price series are gathered, there are some irregularities in the data that need to be dealt with. While most countries report monthly price data, a few report only quarterly, and two report semiannually. So for some months there will be "missing" data for the countries that don't report monthly data. Also, over the years some countries have changed the reference year on which their index is calculated but have not provided enough information to allow the entire series to be linked and rebased on one reference year. This leads to a "break" in the series when the inflation numbers are calculated (described in more detail below). Finally, most countries report only one consumer price index series, but some countries report more than one. For example, one country might report two or three general CPI series, each of which covers different geographical area or population group.

Step 2A. Adjust for different reporting frequencies

Some countries report CPI data only quarterly or semiannually (28 and 2, respectively, of the 200 total. Click here for a list). Instead of leaving these countries out of the monthly regional estimates, we include them by estimating (interpolating) values for the missing months. There are two estimation procedures for those countries reporting only quarterly or semiannually, one of which is used when the base period is the same month of the previous year, and one of which is used when the base period is the previous month.

Step 2.A.

i.When the base period is the same month of the previous year

In this case the procedure is to apply the quarterly estimate to each of the three months in a quarter, and likewise with semiannual data, to apply the semiannual estimate to each of the six months in the half-year. This procedure assumes that the price changes for the all months of the reporting period have the same price level as the one that was reported; because the number reported is the average for the period (the quarter or the half-year), this is reasonable.

ii.When the base period is the previous month

The method used for estimating missing months in the quarterly or semiannual series seems a little more complicated but is pretty straightforward.

To get the monthly index values

1. Take the CPI value from the current reporting period (quarter or half-year) and divide it by the CPI value from the previous reporting period.

2. Take the third root of this ratio for quarterly data, or the sixth root for semiannual data.

3. Multiply the index value from the previous reporting period by the resulting value from (a) to get the index value for the first month of the current period (note, it is really based on the final month of the previous period, not the previous month).

4. Multiply the previous period index value by the resulting value from (a) squared to get an index value for the second month of the current period.

5. Multiply the previous period index value by the resulting value from (a) cubed to get an index value for the third month of the current period.

Continue the process for semiannual data, multiplying the previous period index value by (a), but increasing the exponent by 1 for each successive month of the current period.

Here is an example.

Say there is a country that reports CPI data four times a year, in March, June, September, and December.

1995 fourth-quarter CPI is: 120.7

1996 first-quarter CPI is: 130.9

a. 130.9/120.7 = 1.084507. Third root of 1.084507 is 1.027411

b. 120.7 * 1.027411 = 124.0085 [The index for January 1996]

c. 120.7 * 1.027411 * 1.027411 = 127.4077 [The index for February 1996]

d. 120.7 * 1.027411 * 1.027411 * 1.027411 = 130.9 [The index for March 1996]

Note that the index values in (b), (c), and (d) above are really based on the previous quarter, but they will provide the correct inflation values. To check this, we can use the values computed with the previous-quarter base to calculate the index values for the months (Jan., Feb. and March 1996) that are based on the previous month:

Jan.1996: 124.0085/120.7 * 100 = 102.7411

Feb. 1996: 127.4077/124.0085 *100 = 102.7411

March 1996: 130.9/127.4077 * 100 = 102.7411

By multiplying these three indices (each one on base previous month):

102.7411*102.7411*102.7411/10000 =108.4507

we get the index for 1996IQ on base 1995IVQ.

Step 2.B. Adjust for "breaks" in the data

For those countries whose price series are not based on one single reference period, the calculation of month-to-month or month-over-the-same-month-of-the-previous-year inflation is problematic, In particular, it is not possible to calculate inflation values for any month that requires price data from both sets of numbers, that is, where one number is based on one reference year and the other number is based on another.

For example, a country X might have a consumer price series where the reference is 1990=100 for the years 1990 to 1995, but from 1996 to 2004 the reference is 2000=100. Calculating inflation will be a problem in each of the twelve months of 1996 when the same month from the previous year is used as the base period. When using the previous month as the base, there is a problem when calculating the inflation value in January 1996.

Because there are no reliable methods to estimate the missing data, the dataset must be adjusted so that the problem months are not included in the estimates. (Note that their inclusion will result in distorted estimates of period-to-period changes) Continuing with the example of country X, a value of "missing" has to be assigned to each of the months of 1995, when using the same month of the previous year as the base, so that no inflation values will be computed for that country in 1996. When using the previous month as the base, the value of "missing" is assigned to the final month of 1995 so that no inflation is calculated for that country in January 1996. These series thus will have breaks in them. Also, when GDP weights are calculated, the weights must be adjusted in the months where data are missing (see below). (Click here to view the list of countries that have breaks in their series.)

C. Adjust for countries reporting multiple price series

Some countries report multiple series. In these cases, all of the series are averaged together or one or a subset of series is selected and used. Preference is given to series having wider geographical coverage and relating to all income groups, provided they are no less current than more narrowly defined series. (Click here to view the list of countries reporting multiple series.)

Step 3. Preparing the weights

Another dataset is created with the GDP values for the countries that report GDP. The GDP values are from 1999, and to standardize the values across countries, they are deflated by purchasing power parity estimates (obtained from the World Bank*). It is difficult to be sure that an index based on weights that are seven years old and do not allow for the changing importance of a country within a region over time will provide a reliable and relevant measure of current inflation, but the 1999 GDP data were the most recent data available at the time this project started. A changing set of GDP weights will need to be introduced soon.

The relative weights of the countries in each regional estimate are then calculated. First the GDP totals for the various regional estimates are calculated, then the weights representing each country's share of the totals are calculated. As the same countries must be compared from one period to another, adjustments of weights are made each month for any changes in country coverage.

In calculating the total GDP and deriving the weights, only those countries that have price data available for both the starting month and the ending month of the calculation are included. That is, when using the same month of the previous year as the base to calculate inflation, only those countries that have price data available for the month in consideration and for the same month of the previous year are included in calculation of total GDP. Likewise, when calculating inflation using the previous month as the base, only those countries that have price data available for the month in consideration and for the previous month are included in the total GDP. This requirement means that countries that have missing price data are excluded from total GDP for that particular month. Separate sets of weights are calculated for each month.

GDP was chosen as the weighting variable over other some plausible alternatives, for example, population, because GDP seemed the most appropriate--a regional inflation estimate weighted by GDP indicates the general effect of inflation on the economy in the region. This weighting procedure is also similar to the one used to calculate national CPIs, which are expenditure-weighted indexes.

*World Bank estimates available at and are made each month for any changes in country coverage.

Step 4. Weighting the price data

The CPI data for each country that is included in a particular regional estimate is powered by its share of GDP in the region, expressed as percentage. These values, multiplied together, give the regional total. This is done for each month of data for each country that is part of a given regional estimate.

The calculation of regional totals and averages for the world takes account of the problem that data for some countries do not run through the end of the period for which world and regional data should be calculable. Regional totals are estimated by assuming that the rate of change in the unreported country data is the same as the rate of change in the weighted total or average of the reported country data for that region.

Step 5. Averaging

Regional price indexes are calculated as weighted geometric averages of the countries in the region. A geometric average is used because it is less affected than an arithmetic average by extreme values and is regarded as more suitable for groups where the dispersion of indices is considerable. (A geometric average is calculated as the nth root of the product of n observations or values. An arithmetic average is the result of the sum of n observations or values divided by n.)

Step 6. Calculating inflation estimates

Inflation is calculated from the series of index numbers as a percent change over some period. The 12-month rate of change is calculated as the percentage variation over 12 months for monthly series, over 4 quarters for quarterly series, and over 1 year for annual series.

Regional groupings

Researchers and analysts might be interested in any number of potential groupings, but initially countries were assigned into one of six categories. The first two categories are developed and transition economies, and countries not assigned to either of these are then grouped by geographical location. Standard UNSD Country and Region Classification was used as a starting point for making decisions on the major groupings. Modifications were made to account for the specificity of the CPI. For example, the transition countries from Central and Eastern Europe were grouped in a separate group from other transition countries because of the similar trends in the price inflation they experienced at the beginning of 1990s.

CPI estimates are produced for the following main country groupings:

  • Developed countries
  • Transition countries
  • Asia and Pacific
  • Latin America and the Caribbean
  • Sub-Saharian Africa
  • Middle East and North Africa

The country composition of the world is all countries for which the series are available.

Table 1. Countries contained in each regional aggregate

1. Developed (industrialized) countries
AT Austria
BE Belgium
CY Cyprus
DK Denmark
FO Faeroe Islands
FI Finland
FR France
D3 Germany
GI Gibraltar
GR Greece
IS Iceland
IE Ireland
IM Isle of Man
IT Italy
LU Luxembourg
MT Malta
MC Monaco
NL Netherlands
NO Norway
PT Portugal
SM San Marino
ES Spain
SE Sweden
CH Switzerland
TR Turkey
GB United Kingdom
AU Australia
CA Canada
GL Greenland
JP Japan
NZ New Zealand
US United States
IL Israel
2. Transition countries
AL Albania
BA Bosnia and Herzegovina
BG Bulgaria
HR Croatia
CZ Czech Republic
HU Hungary
MK Macedonia, The former Yugoslav Rep. of
PL Poland
RO Romania
SK Slovakia
SI Slovenia
YU Yugoslavia
EE Estonia
LV Latvia
LT Lithuania
AM Armenia
AZ Azerbaijan
BY Belarus
GE Georgia
KZ Kazakhstan
KG Kyrgyzstan
MD Moldova, Rep. of
RU Russian Federation
TJ Tajikistan
UA Ukraine
3. Asia and Pacific
HK Hong Kong, China
KR Korea, Republic of
MO Macau, China
MN Mongolia
TW Taiwan, China
AF Afghanistan
BD Bangladesh
BT Bhutan
IN India
MV Maldives
NP Nepal
PK Pakistan
LK Sri Lanka
BN Brunei Darussalam
KH Cambodia
ID Indonesia
LA Lao People's Dem. Rep.
MY Malaysia
MM Myanmar
PH Philippines
SG Singapore
TH Thailand
VN Viet Nam
FJ Fiji
NC New Caledonia
PG Papua New Guinea
SB Solomon Islands
VU Vanuatu
GU Guam
KI Kiribati
MD Micronesia (Federated States of)
MP Northern Mariana Islands
AS American Samoa
CK Cook Islands
PF French Polynesia
NU Niue
NF Norfolk Island
WS Samoa
TO Tonga
TV Tuvalu
4. Latin America and the Caribbean
AI Anguilla
AG Antigua and Barbuda
AW Aruba
BS Bahamas
BB Barbados
BZ Belize
BM Bermuda
KY Cayman Islands
DM Dominica
DO Dominican Republic
GD Grenada
GP Guadeloupe
HT Haiti
JM Jamaica
MQ Martinique
AN Netherlands Antilles
PR Puerto Rico
KN Saint Kitts and Nevis
LC Saint Lucia
PM Saint Pierre and Miquelon
VC Saint Vincent and the Grenadines
TT Trinidad and Tobago
VG Virgin Islands (British)
AR Argentina
BO Bolivia
BR Brazil
CL Chile
CO Colombia
CR Costa Rica
EC Ecuador
SV El Salvador
FK Falkland Is. (Malvinas)
GF French Guiana
GT Guatemala
GY Guyana
HN Honduras
MX Mexico
NI Nicaragua
PY Paraguay
PE Peru
SR Suriname
UY Uruguay
VE Venezuela
5. Sub-Saharian Africa
BI Burundi
ET Ethiopia
KE Kenya
MG Madagascar
MW Malawi
MU Mauritius
MZ Mozambique
RE Reunion
RW Rwanda
SC Seychelles
T1 Tanzania (Tanganyika)
T2 Tanzania (Zanzibar)
UG Uganda
ZM Zambia
ZW Zimbabwe
AO Angola
CM Cameroon
CF Central African Rep.
TD Chad
CG Congo
GA Gabon
BW Botswana
LS Lesotho
NA Namibia
ZA South Africa
SZ Swaziland
BJ Benin
BF Burkina Faso
CV Cape Verde
CI Cote d'Ivoire
GM Gambia
GH Ghana
GN Guinea
ML Mali
MR Mauritania
NE Niger
NG Nigeria
SH Saint Helena
SN Senegal
SL Sierra Leone
TG Togo
6. Middle East and North Africa
BH Bahrain
DJ Djibouti
IR Iran
IQ Iraq
JO Jordan
KW Kuwait
LB Lebanon
OM Oman
SA Saudi Arabia
SY Syrian Arab Republic
PS West Bank and Gaza Strip
Y2 Yemen, The former Democratic
DZ Algeria
EG Egypt
LY Libyan Arab Jamahiriya
MA Morocco
SD Sudan
TN Tunisia

Table 2. Countries reporting quarterly or semi-annually

Country Period Month of the quarter reported
LS, Lesotho 1990–2001 1st
SH, Saint Helena 1990–2001 2nd
T1, Tanzania (Tanganyika) 1990–1993 3rd
T2, Tanzania (Zanzibar) 1990–1998 2nd
AI, Anguilla 2001–2004 3rd
BZ, Belize 1990–2004 2nd
KY, Cayman Islands 1990–2003 3rd
FK, Falkland Is. (Malvinas) 1990–2002 2nd
PM, Saint Pierre and Miquelon 1990–2001 3rd
OM, Oman 1990–2001 2nd
FO, Faeroe Islands 1990–2003 1st
GI, Gibraltar 1990–2004 1st
IE, Ireland 1990–1996 2nd
JE, Jersey 1990–2003 3rd
AS, American Samoa 1990–2004 2nd
AU, Australia 1990–2004 3rd
CK, Cook Islands 1990–2004 2nd
GU, Guam 1990–2003 2nd
KI, Kiribati 1990–2003 2nd
MH, Marshall Islands 1991–2004 2nd
NZ, New Zealand 1990–2004 2nd
NU, Niue 1990–2003 2nd
NF, Norfolk Island 1990–2004 3rd
MP, Northern Mariana Island 1990–2004 2nd
PG, Papua New Guinea 1990–2004 2nd
WS, Samoa 1999–2003 3rd
TV, Tuvalu 1990–2003 2nd
VU, Vanuatu 1990–2003 2nd
GL, Greenland 1990–2004 Half yearly, 1st
BT, Bhutan 1990–2003 Half yearly 6th

Table 3. Countries reporting multiple series

Country Available series Series used
Cape Verde
  • CV–Cape Verde
  • CV1–Cape Verde (Praia)
  • ET–Ethiopia
  • ET1–Ethiopia (Addis Ababa))
  • MG–Madagascar
  • MG1–Madagascar (Antananarivo, Madagascar)
  • MG2–Madagascar (Antananarivo, Europe)
  • MG1 (1990–2000)
  • MG(>2000)
  • MZ –Mozambique
  • MZ1–Mozambique (Maputo)
  • SZ–Swaziland
  • SZ1–Swaziland (Mbabane-Manzini)
  • SZ1 (1994)
  • SZ (all years except 1994)
  • ZM–Zambia
  • ZM2–Zambia (low-income group)
  • BR–Brazil
  • BR1–Brazil (Sao Paulo)
French Guiana
  • GF–French Guiana
  • GF1–French Guiana (Cayenne)
  • GF1 (1990–1992)
  • GF(>1992)
  • NI–Nicaragua
  • NI1–Nicaragua (Managua)
  • IN4–India (Agricultural workers)
  • IN5–India (Industrial workers)
  • IN6–India (Urban, nonmanual employees)
  • IN7 –India (Delhi, industrial workers)
Lao People’s Dem. Rep.
  • LA–Lao People’s Dem. Rep.
  • LA1–Lao People’s Dem. Rep. (Vientiane)
  • LA1 (1990–1996)
  • LA(>1996)
  • MM–Myanmar
  • MM1–Myanmar (Yangon)
  • MM1 (1990–1998)
  • MM(>1998)
Saudi Arabia
  • SA–Saudi Arabia (All cities)
  • SA1–Saudi Arabia (middle-income group)

Table 4. Countries that have breaks in their series

Country Period of break
MA, Morocco


GA, Gabon


BN, Brunei Darussalam


DM, Dominica


FI, Finland


BH, Bahrain


HT, Haiti


ET, Ethiopia


CI, Cote d’Ivoire


GQ, Equatorial Guinea