Unido.org/statistic s Statistical Indicators of Industrial performance Shyam Upadhyaya International workshop on industrial statistics 8 – 10 July, Beijing

unido.org/statistics

Statistical Indicators of Industrial performance

Shyam Upadhyaya

International workshop on industrial statistics 8 – 10 July, Beijing

unido.org/statisticsStatistics for policy

makers ...

Sir Roland Fisher (1890 – 1962)

In the original sense of the word, ‘Statistics’was the science of Statecraft: to the political arithmetrician of the eighteenth century, its function was to be the eyes and ears of the central government.

• We produce a lot of data, they need a few synthesized indicators

• We provide figures, they would like to read a story around the figures

• We should convert statistics into information and information into knowledge


Indicators of industrial performance are compiled to:

3

• Reflect the major policy relevant issues of industrial development

• Synthesize the large volume of data to some meaningful statistics

• Help to carry out the cross-country comparison

• Indicate the relative position of the country in industrial development


Construction of performance indicators by key policy issues

Performance indicators constructed in UNIDO mainly addresses the following three dimensions relevant to development strategy and monitoring of industrial performance

• Productivity

• Structural change

• Competitiveness

unido.org/statisticsProductivity

Generalized measure of industrial productivity of the whole population is measured by MVA per capita

Labour productivity

Value added per employee

Value added per worked hour

Capital productivity

Value added per unit of capital

Value added capital increment ratio

Multifactor productivity index

KKLL

QMF SISI

II

LK SS 1

LS - share of compensation of employees (as labour input) in value added

- share of other components (capital input) in valueIL and IK as defined in relation (4).

- Index of the number of employees and fixed assets (adjusted with price changes)

KL IandI

01

01

FAFA

VAVA

unido.org/statisticsTotal factor productivity from UNIDO

productivity database

6

http://www.unido.org/data1/wpd/Index.cfm


Structural change•Change in the share of sectords- difference of the share between two periods, 0 and 1.

si – share of i-th sector in total value

•Integral coefficient of structural changen – number of observations (sectors)The coefficient lies between 0 and 1. Its value more than 0.5 would

mean significant structural change, while less than 0.1 indicate the identical structure in both time points.

•Rank correlation of SpearmanLack of correlation of ranks in two periods would mean the presence

of structural change

•Coefficient of diversification It equals to 0 when the value is concentrated in one branch of industry, and to 1, when all the branches has equal value indicating a perfect diversification .

7

01 iis ssd

2

01

201

int

1

ii

ii

ss

ss

nd

)1(

61

2

2

nn

ds

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ssC ii

d ln

ln


18/04/238

Competitiveness

• Ability to sell the products in the market.

• International competitiveness is measured by the share of export in domestic output

• Share of resource-based and high-tech products in total manufactured export


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Analysis of demand supply data balanceOverall equilibrium

C – Apparent consumptionY – Domestic outputM – ImportX - Export

Relative variablesRatio of domestic output to consumption

Share of importin total consumption

Share of exportin total output

XMYC

C

YR

100C

M

100Y

X

When

R > 1 surplus

(export oriented)

R= 1 – self-sufficient

R < 1 – deficit

(import oriented)


Derived classification

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Create a smaller group of industrial sectors based on some policy relevant criteria •Resource based sectors

•Agro-based sectors

•Classification based on technological intensity

•Classification based on energy intensity

•ICT goods producing sectors

unido.org/statisticsShare of resource-based sectors in BRICS

countries in comparison with UK

11

Resource-based sectors account for a considerable part of manufacturing in emerging economies

So far, only China has succeeded in reducing its dependence on resource-based industries


Agro-based sectors

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Sub-set of resource-based industry, excluding the processing of mineral resources

Lower technological innovation, labour intensive

Share of agro-based sectors falls as industry diversifies and moves towards high-technology sectors


Classification by technological intensityBased on R&D expenditure per unit of value added

Medium-high and high technology industries by ISIC rev-3

24 Manufacture of chemicals and chemical products29 Manufacture of machinery and equipment n. e. c.30 Manufacture of office, accounting and computing machinery31 Manufacture of electrical machinery and apparatus n. e. c.32 Manufacture of radio, television and communication equipment33 Manufacture of medical, precision and optical instruments34 Manufacture of motor vehicles35 Manufacture of other transport equipment


Classification based on energy intensity

14

Classification is based on:iii i tEnergy

Input

nsobservatioofNo

x

nratioEnergyMean

cos_

.1

_

0.0

10.0

20.0

30.0

15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37ISIC

Energ

y c

ost

ratio in%

mjniZ

zi

ij

j ,1,1;max

Ranking of industries for sample countries

zij - rank score of j-th industry in i-th

sample

Z max – maximum value of z (m x n)


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Manufacturing branches by

intensity of energy

consumption

ISIC Description of activities

High energy-intensive 172123242627

Manufacture of textilesPaper and paper productsCoke and refined petroleum productsChemical productsNon-metallic mineral productsManufacture of basic metals

Moderate energy-intensive

15181920222528

Food products and beveragesWearing apparel; dressing and dyeingManufacture of leather productsWood and wood productsPrinting and publishingRubber and plastic productsFabricated metal products

Low energy-intensive 16293031323334353637

Tobacco productsMachinery and equipment n.e.c.Office, accounting and computing machineryElectrical machinery and apparatus n.e.c.Radio, TV and communication equipment Medical, precision and optical instrumentsMotor vehicles, trailers and semi‑trailersOther transport equipmentFurniture and other manufacturing n.e.c.Recycling

unido.org/statisticsA composite index

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• UNIDO constructs and disseminates data on a composite index - the Competitive industrial performance index (CIP Index)

• This is a consolidated measure of industrial performance based on a number of indicators capturing different dimensions

• CIP index is useful to benchmark and compare a country’s performance

• The index is used to rank countries and reveal their relative position. It serves as a tool for policy makers and attracts attention of public and media


Steps required in construction of a composite measure

• Dimensions and indicators

• Imputation and outlier

cleaning

• Normalization

• Weighting and aggregation

• Ranking

• Sensitivity analysis


CIP Components

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Dimensions IndicatorsCapacity to produce and export 1. Manufacturing value added per capita

2. Manufacturing export per capita

Technological upgrading and deepening

3. Share of MHT activities in total MVA 4. Share of MVA in GDP 5. Share of MHT manufactures exports 6. Share of manufactures export in total exports

Impact on world production and trade

7. Share of the country in world MVA8. Share of the country in world manufactures exports


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Construction of CIP index

• A normalized component index for i-th country, j-th year and k-th indicator is given by:

where x represents the actual value of the indicator

• CIP index is computed as the geometric mean of individual indices

10,I)Xmin()Xmax(

)Xmin(XS k

j,ikj,i

kj,i

kj,i

kj,ik

j,i

q

i

wijtjt

iSCIP1

unido.org/statisticsCIP ranking of selected Asian

countries

20

Global ranking


Indicators help to write a story...

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Performance indicators provide more synthesized and analytical information for policy makers

The process described here is more about the construction of indicators

Indicators help to write a story for communicating statistics to the policy makers

Writing story does not end in compilation of indicators, it only starts

Documents

Unido.org/statistic s Statistical Indicators of Industrial performance Shyam Upadhyaya International workshop on industrial statistics 8 – 10 July, Beijing