DATASET METADATA
Data Source:
UNIDO - Competitive Industrial Performance Index
The Competitive Industrial Performance (CIP) index considers countries' productive capacity, intensity of industrialization and impact on the world market as major components ofindustrial performance. The primary data source for the compilation of the CIP indexis UNIDO's database based on an underlying quality assurance framework for international comparability.
CIP index values represent a composite measure of a country's competitive industrial performance. The CIP index can be interpreted in time-series and across countries. A positive change in the CIP value of a given country over time indicates increased productive capacity and improved quality of products with a better chance of realization in international markets. A comparison of the CIP across countries indicates the comparative advantage of one economy over others.
The CIP's major distinction relates to its sector perspective. Industrial competitiveness is defined as the capacity of countries to increase their presence in international and domestic markets whilst developing industrial sectors and activities with higher value added and technological content (UNIDO, 2012). Industrial competitiveness necessitates innovation, technological sophistication, developed infrastructure and effective industrial policy directed at exploiting comparative advantage. CIP is based on output measures and thus captures a country's production performance.
Another important feature is that the CIP is fully based on statistical measures. While the uniformity of the computation methods and classification standards ensures the international comparability of statistical data, respondents' business perceptions are difficult to harmonize. Perception indicators are based on the respondent's individual understanding and are influenced by the time and context of the interview. As a performance indicator, CIP reflects a country's productivity, structural change and competitiveness. These concepts are taken as a departure point for the selection of indicators under the three major dimensions of the CIP.
Subsequently, the major part of the consistency check and imputation process is completed before the construction of the CIP. Nevertheless, the CIP as a composite measure requires figures to be available for all indicators in the given timeframe for target countries. To avoid the exclusion of a country due to missing data, additional imputation may also be necessary. After defining the indicators, the CIP index is constructed based on a standard data transformation process for the composite measure which involves the imputation of missing data, outlier cleaning and normalization. The purpose of normalization is to obtain a common measure from indicators with a value in varying scales. The CIP index follows the Min-Max normalization process, which is particularly useful for obtaining harmonized scores between 0 to 1.
Following normalization of each indicator, the best performing country is assigned a value of 1 and the weakest performing country is assigned a value of 0. The composite measure is subsequently calculated from the individual scores. At this stage, two methodological options are available weighting and aggregation. The general idea is to distribute equal weights to all indicators and to maintain the balance of the three dimensions. With respect to aggregation, the choice is based on the assumption that indicators are substitutable, i.e. poor performance of one indicator can be compensated for by higher values of other indicators. Aggregation using geometric means limits such compensation to some extent, and thus higher values for all indicators are necessary to achieve an improved CIP.
For more information on the CIP methodology, please see https://unstats.un.org/unsd/ccsa/isi/2013/Paper-UNIDO.pdf
For use guidelines, please consult United Nations Industrial Development Organization (http://www.unido.org/legal.html)
INDICATOR METADATA
Definition: Industrialization intensity index
Date range: 1990-2014
Periodicity: annually
Type of data: Value
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