Www.unido.org/statistics International Workshop on Industrial Statistics Dalian, China 21-25 June...

www.unido.org/statistics

International Workshop on Industrial StatisticsDalian, China

21-25 June 2010

Shyam UpadhyayaUNIDO

Use of IIP in other measures of industrial statistics- UNIDO experience


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Outline

IIP in UNIDO Statistical products

Estimation of recent year MVA using base weights and annual IIP

Nowcasting of IIP for recent years and estimation of missing values using econometric models

Use of IIP in deriving deflators for time-series analysis of production data

Estimation of world growth trends of industrial production using quarterly index data


IIP in UNIDO statistical products

UNIDO maintains international industrial statistical databases: INDSTAT, IDSB, World MVA database and MinSTAT (new)

Statistical products: International Yearbook of Industrial Statistics; Databases in CD ROM – INDSTAT2, INDSTAT4, IDSB, Statistical country brief (SCB) -online data portal available in: www.unido.org/statistics

Yearbook , INDSTAT2 and SCB presents Index numbers or/and data derived from the index numbers

Index numbers are collected from UNSD and OECD (for OECD countries) and supplemented with other sources or own estimates

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Use of IIP in estimation of recent year MVA

Significant time-lag between reference year and data dissemination year – around 3 years

User’s demand for more recent year estimates

Basic estimation method: (1)where - estimated value added for tth year

- VA for base year t0 -

annual IIP for tth year compared to base year t0

Data available for 159 countries at 2-digit level of ISIC


Base weights and IIP

Base weights – MVA for base year at current prices

Preferable valuation method - basic prices

IIP – fixed base annual indices (2000)

Deviations:Valuation method is not always at basic prices or it is not always

reported

there is no unique base year for all countries; so indices are chained to link to a common base year

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Problems for imputation and forecasting

Base weights are pre-set, thus they are same every year so data are always available

IIP data naturally vary over periods, but they might also be trending indicating the uncertainty in changing pattern, which makes imputation and forecasting difficult

Trends can be non-linear; they might be different from one to another ISIC groups within a country

There might be extreme cases too, which are not easily explained

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Nowcasting model for IIP

Nowcasting – estimation of index numbers up to the recent year

The parameters of models allow also to estimate the missing value

Dependent variable – IIP for an industry group (ISIC 2-digit)Explanatory variable - MVA (available in UNIDO database)

The model: (2)

suffix i, j, t stands for - industry country and year

Log model helped to reduce the effect of erratic changes on results

Computation is performed by SAS. When index numbers are ready VA is estimated using equation (1)

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A snapshot from the Yearbook on world MVA distribution(row wise)

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Sector distribution of world MVA (column wise)

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Estimated VA for country ranking by sectors

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Major problems encountered

Difference in valuation of VA: basic prices and producer’s prices

Difference of base years across the countries

Not regularly updated weights, do not reflect the recent structure and growth of manufacturing sectors

Regional aggregation for some areas (especially Africa) based on few countries

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IIP in UNIDO researchComputation of deflators using index

UNIDO gets VA data from NSOs at current prices- These data are fit for cross-country business structural analysis

- Users also need data for time-series analysis, but no deflator or PPI data are available by ISIC

An implicit deflator can be derived from the relation of current price data and IIP Change of VA at current prices and IIP are given as;

And their ratio gives an implicit deflator as given below:

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00

00 ∑

∑

Q

QIIP;

QP

QP

V

V tt.

o

ttt ==

t,t

t, IIP/V

VDeflator 0

00 =


Use of deflated data

Deflated data are not directly used for production growth analysis due to the nature of their approximation

However, data were found quite reliable for structural change and labour productivity analysis

Problems related to price change within a country can be solved through different methods; but the measurement of price variation across the countries is more complicated

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Aggregated quarterly indices for the world MVA

The main objective is to monitor the world industrial growth trend

The data covers 40 sample countries which accounts for 90% of the world MVA

Weights are computed at the country level

Index numbers are obtained from the secondary data sources; mainly websites UNSD monthly bulletin, STAN database OECD and national web-sites

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World manufacturing growth trends by country groups

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Quarterly indices of world industrial production (Base 2005=100)


Concluding remarks

IIP are widely used in international statistical system not only for monitoring growth but also as an important supplementary data for estimation of level and structure indicators

Major quality issues are international comparability in terms of classification, methods of compilation and timeliness, especially in terms of weight updating

During the implementation stage of new recommendations differences may arise due to change in method of computation (e.g. from Lespeyres to chained Lespeyres). It is expected from NSOs that they revise the past series too when new method is introduced

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Please send your comments to UNIDO Statistics

[email protected]

Www.unido.org/statistics International Workshop on Industrial Statistics Dalian, China 21-25 June...

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