LA

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LA KLEMS ProjectMexico

• Francisco Guillén Martín
• Deputy General Directorate for National Accounts
• INEGI-Mexico

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LA KLEMS Mexico Project Implementation

• SUMMARY
• A). Offices of the System of National Accounts -
  Mexico which are linked to the project.
• B). Main challenges to the construction of annual
  statistical series.
• 1. Inter-sector accounts
• 2. Labor accounts
• 3. Capital accounts
• C). ITs measurement and its role in
  productivity.
• D). Some Preliminary Results

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A). Offices of the SNA Mexico which are linked
to the project
NATIONAL INSTITUTE FOR STATISTICS AND GEOGRAPHY (INEGI) NATIONAL INSTITUTE FOR STATISTICS AND GEOGRAPHY (INEGI) NATIONAL INSTITUTE FOR STATISTICS AND GEOGRAPHY (INEGI) NATIONAL INSTITUTE FOR STATISTICS AND GEOGRAPHY (INEGI) NATIONAL INSTITUTE FOR STATISTICS AND GEOGRAPHY (INEGI)

GENERAL DIRECTORATE FOR ECONOMIC STATISTICS GENERAL DIRECTORATE FOR ECONOMIC STATISTICS GENERAL DIRECTORATE FOR ECONOMIC STATISTICS GENERAL DIRECTORATE FOR ECONOMIC STATISTICS
DEPUTY GENERAL DIRECTORATE FOR NATIONAL ACCOUNTS DEPUTY GENERAL DIRECTORATE FOR NATIONAL ACCOUNTS DEPUTY GENERAL DIRECTORATE FOR NATIONAL ACCOUNTS
DIRECTORATE FOR NATIONAL ACCOUNTING DIRECTORATE FOR NATIONAL ACCOUNTING
DEPUTY DIRECTORATE FOR INTEGRATION OF GOODS AND SERVICES ACCOUNTS
DEPUTY DIRECTORATE FOR MANUFACTURING INDUSTRIES
DEPUTY DIRECTORATE FOR SERVICES
DEPUTY DIRECTORATE FOR INTEGRATION OF INSTITUTIONAL SECTORS ACCOUNTS
DIRECTORATE FOR INPUT-OUTPUT TABLES DIRECTORATE FOR INPUT-OUTPUT TABLES
DEPUTY DIRECTORATE FOR MINING AND INDUSTRIAL NON MANUFACTURING SECTORS
DEPUTY DIRECTORATE FOR FARMING, FORESTRY, FISHING AND PROCESSED FOODS
DEPUTY DIRECTORATE FOR NON FINANCIAL AND ECONOMICS REFERENCES SERVICES
DEPUTY GENERAL DIRECTORATE FOR ECONOMIC POLLS AND ADMINISTRATIVE RECORDS DEPUTY GENERAL DIRECTORATE FOR ECONOMIC POLLS AND ADMINISTRATIVE RECORDS DEPUTY GENERAL DIRECTORATE FOR ECONOMIC POLLS AND ADMINISTRATIVE RECORDS
DIRECTORATE FOR SECONDARY SECTOR POLLS DIRECTORATE FOR SECONDARY SECTOR POLLS
DIRECTORATE FOR SCIENCE AND TECHNOLOGY STATISTICS DIRECTORATE FOR SCIENCE AND TECHNOLOGY STATISTICS
DEPUTY DIRECTORATE FOR INFORMATION TECHNOLOGIES AND COMMUNICATIONS
DEPUTY GENERAL DIRECTORATE FOR ECONOMIC AND FARMING CENSUSES DEPUTY GENERAL DIRECTORATE FOR ECONOMIC AND FARMING CENSUSES DEPUTY GENERAL DIRECTORATE FOR ECONOMIC AND FARMING CENSUSES

GENERAL DIRECTORATE FOR DEMOGRAPHIC STATISTICS GENERAL DIRECTORATE FOR DEMOGRAPHIC STATISTICS GENERAL DIRECTORATE FOR DEMOGRAPHIC STATISTICS GENERAL DIRECTORATE FOR DEMOGRAPHIC STATISTICS
DEPUTY GENERAL DIRECTORATE FOR DEMOGRAPHIC STATISTICS AND ADMINISTRATIVE RECORDS DEPUTY GENERAL DIRECTORATE FOR DEMOGRAPHIC STATISTICS AND ADMINISTRATIVE RECORDS DEPUTY GENERAL DIRECTORATE FOR DEMOGRAPHIC STATISTICS AND ADMINISTRATIVE RECORDS
DIRECTORATE FOR CONCEPTUAL DESIGN OF REGULAR AND SPECIAL POLLS DIRECTORATE FOR CONCEPTUAL DESIGN OF REGULAR AND SPECIAL POLLS
DEPUTY DIRECTORATE FOR CONCEPTUAL DESIGN OF REGULAR POLLS
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B) Main challenges to the construction of annual
statistical series

• 1. Inter-sectorial Accounts
• KLEMS economic activities classification requires
  a wide sectorial breakdown, so it was needed to
  harmonize the economic classification for
  censuses and polls, the NAICS 02 and the SNA
  Mexico for the series 1990-2008.
• In order to get data for the components of
  intermediate consumption by activity, it was
  required the use of all economic censuses and
  polls available for the referred period.
• A particular challenge resides in determining the
  technology output for own use at business, homes
  and other economic agents.

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B) Main challenges to the construction of annual
statistical series

• 2. Labor Accounts
• IT specification on labor data set out a strong
  conceptual and methodological requirement (there
  is not a clear definition on the relationship of
  people with ITs) that is hard to achieve for the
  complete series. Thus, available data from polls
  and administrative records is being gathered, in
  order to estimate it.
• Another challenge is to conceptually determining
  data from employment polls for its KLEMS
  classification as well as for its breakdown by
  sex, age, education (high, medium, low) on this
  very last issue there is not a clear definition.
  What must be understood for each of these
  educational levels?

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B) Main challenges to the construction of annual
statistical series

• If this definition of educational levels is leave
  up to each country, thera is a loss in
  comparability. Nevertheless, the data from
  employment tables which have generated from the
  ENE and the ENOE, in order to satisfy the LA
  KLEMS requirement, using some statistical-mathemat
  ic procedure that does not distort the original
  demographic basic data trend.

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B) Main challenges to the construction of annual
statistical series

• 3. Capital Accounts
• For fulfillment of the objective of this project,
  SNA Mexico data on gross capital stocks and net
  stocks at acquisition costs and at replacement
  value through the Perpetual Inventory Method
  (PIM) was used for the 1990-2008 Annual Series.
• The challenged that is now being undertaken is
  the calculation of the time series, with the
  economic activity breakdown required for the
  LA-KLEMS this task is being developed through
  statistical and mathematic methods supported on
  data from the Economic Polls and Census, which
  allows to obtain product-capital elasticity
  coefficients by economic activity.

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C) ITs measurement and its role in productivity

• Information Technologies measurement and its role
  in productivity
• The quantification on stocks, employment an input
  is made through total supply of ITs sectors and
  through statistical data available for these
  economic sectors, as well as with the calculation
  of technical coefficients on the use of this
  technology, obtained through the Supply and
  Demand Tables, Economic Censuses, annual polls
  and administrative records, which will allow to
  identify their contribution in each ITs related
  factor (KLEMS)
• Computer equipment.
• Communication equipment.
• Software.

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D) Some preliminary results.

• The next table shows the economic variables which
  have been calculated to date, for the 1900-2008
  series, at both current and 1995 constant prices.

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D) Some preliminary results.

• Inter-sectorial Accounts
• Intermediate Consumption Value
• Taking into account that the sum of its three
  required components equals total intermediate
  value for the referred economic activity, its
  composition at current values was obtained from
  1993, 1998 and 2003 census data, as well as
  manufacturing polls and administrative records
  for energy, transportation and all other
  services. The resulting values were adjusted to
  the intermediate consumption value registered in
  the output accounts of each activity.
• Intermediate Consumption Value at constant values
• For calculation of these aggregates, the
  intermediate consumption for each activity was
  taken as constant, and its composition was
  obtained through deflecting its three components
  with price indexes calculated from energy rates,
  producer and consumer prices and implicit IC
  prices.

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D) Some preliminary results.
Intermediate Consumption Value (IC) at current and constant values Intermediate Consumption Value (IC) at current and constant values Intermediate Consumption Value (IC) at current and constant values Intermediate Consumption Value (IC) at current and constant values Intermediate Consumption Value (IC) at current and constant values Intermediate Consumption Value (IC) at current and constant values Intermediate Consumption Value (IC) at current and constant values Intermediate Consumption Value (IC) at current and constant values
  Current Values Current Values Current Values Current Values Constant Values Constant Values Constant Values Constant Values
YEAR IC Energy Raw Materials Services IC Energy Raw Materials Services
1990 576,415,997 11,825,890 306,152,055 258,438,052 1,412,890,299 28,280,390 708,389,932 676,219,977
1995 1,636,945,587 32,765,077 820,725,978 783,454,532 1,636,945,587 32,765,077 820,725,978 783,454,532
2000 4,544,613,987 109,955,353 2,435,534,703 1,999,123,931 2,462,732,857 49,289,432 1,234,756,273 1,178,687,152
2003 5,262,301,986 258,301,123 3,474,139,082 1,529,861,781 2,499,114,083 62,973,725 1,252,996,963 1,183,143,395
2004 6,016,322,085 186,922,882 4,048,225,958 1,781,173,245 2,675,299,076 68,332,594 1,341,331,971 1,265,634,511
2005 6,670,809,932 207,098,575 4,459,620,105 2,004,091,252 2,855,230,822 74,147,486 1,431,545,512 1,349,537,824
2006 7,503,531,005 236,335,208 5,025,377,851 2,241,817,946 3,148,379,520 80,457,207 1,578,523,368 1,489,398,946
2007 8,098,293,133 252,241,235 5,392,316,850 2,453,735,048 3,351,939,937 87,303,866 1,680,583,768 1,584,052,303
2008 8,877,075,275 301,197,586 5,933,088,465 2,642,789,224 3,397,662,611 94,733,154 1,703,508,041 1,599,421,416
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D) Some preliminary results.

• WP2 and WP3 Labor Account and Capital Account
• We have a considerable progress in the analysis
  and conciliation of basic data available for the
  labor account and the capital account, so we
  expect to deliver the results in time and on the
  required format .
• Data related to job posts and worked hours, by
  sex, age and education are available to NAICS
  sub-sector levels, for the 1900-2008 period, as a
  result of the ENE-ENOE data re-processing.

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D) Some preliminary results.

• Labor Account Progress.
• For the 1990-2008 series, technical coefficient
  were calculated with the following data sources.

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D) Some preliminary results.
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Thank you