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Composite measure of industrial performance for cross-country analysis Shyam Upadhyaya UNIDO. The 59th World Statistics Congress Hong Kong, 25-30 August 2013. Outline of the presentation. Composite measures in international practice What is different in UNIDO’s CIP index

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Composite measure of industrial performance for cross country analysis shyam upadhyaya unido

Composite measure of industrial performance for cross-country analysisShyam UpadhyayaUNIDO

The 59th World Statistics Congress

Hong Kong, 25-30 August 2013


Outline of the presentation
Outline of the presentation cross-country analysis

Composite measures in international practice

What is different in UNIDO’s CIP index

Scope, dimensions and construction procedure

Sensitivity analysis

Some results and conclusion


Composite measures in international practice
Composite measures in international practice cross-country analysis

Jeder nach seinen Fähigkeiten, jedem nach seinen Bedürfnissen!

From each according to his ability, to each according to his need!

- Karl Marx (1875)

178 composite indices are compiled worldwide in different frequencies

Happiness index

Welfare Index

Global climate risk index

... ...

Political instability index

From each international agency at least one composite index according to their need ...


Why international agencies are so fond of composite index
Why international agencies are so fond of composite index? cross-country analysis

  • Single measure of indicating a country’s development performance

  • Easy for policymakers to understand

  • Benchmarking and country comparison

  • Ranking

  • Shift in the rank generates public debate

  • Media attraction (visibility)


What is risk
What is risk? cross-country analysis

  • Composite measure combines too many things into one, but precisely, it may not measure anything

  • To construct the index, one needs source data for all indicators; which may limit the country coverage

  • Or under temptation of getting larger coverage, the compiler may compromise the quality of estimates when underlying data are not readily available (HDI discussions)

  • Policymakers may actually not see the value of large amount of data that are produced behind the scene

Even when all underlying statistics are available … there is no way of capturing the entire wealth of knowledge embedded in a set of numbers in one real number.

- Amartya Sen, 1994


Unido s competitive industrial performance cip index
UNIDO’s Competitive Industrial Performance (CIP) Index cross-country analysis

  • UNIDO’s mandate on industrial development

  • Sectoral perspectives

  • Based on output measures to capture the production performance

  • Solely quantitative measures, no perception indicators

  • Reflects country’s capacity to produce and compete in the world market

Other similar indices:

Global Competitive Index (GCI)

by the World Economic Forum

World Competitiveness Scoreboard (WCS) by the Institute for Management Development

Doing Business Index (DBI) by the World Bank


Structure of cip index
Structure of CIP index cross-country analysis


Compilation procedure
Compilation procedure cross-country analysis

Normalization: conversion of real value of varying scale to obtain a common score between 0 to 1

Aggregation of individual scores to CIP value

Equal weights for three dimensions and aggregation through geometric mean

score obtained from k-th variable of i-th indicator and j-th country


Cip s fitness for its purpose as a performance index
CIP’s fitness for its purpose as a performance index cross-country analysis

A powerful tool for policy advice

Country comparator

Component indicators can be used for industrial diagnostics

Comparison with other composite measures

Rank correlation coefficient with HDI = 0.79



Sensitivity analysis
Sensitivity analysis cross-country analysis

  • Composite measures are compiled through several dilemmas

  • Often, there is no clear path to selection of one way against another

  • The main purpose of the sensitivity analysis is to examine the impact of methodological choices in the final results

  • Methodological choices in CIP construction:

  • Number of indicators and weights

  • Normalization method

  • Aggregation method


Results of sensitivity analysis
Results of sensitivity analysis cross-country analysis


Conclusion
Conclusion cross-country analysis

  • Composite index is a powerful tool to communicate with policy makers

  • Behind the single measure there is a vast amount of data and statistical work

  • CIP index depicts a country’s overall measure of industrial performance

  • Users should pay attention equally to its component indicators, which provide more specific measures of key aspects of industrial performance


Thank you s upadhyaya@unido org or stat@unido org
Thank you! cross-country [email protected]@unido.org


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