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Presentation on theme: " International Workshop on Industrial Statistics Dalian, China 21-25 June 2010 Shyam Upadhyaya UNIDO Use of IIP in other measures."— Presentation transcript:

1 International Workshop on Industrial Statistics Dalian, China June 2010 Shyam Upadhyaya UNIDO Use of IIP in other measures of industrial statistics- UNIDO experience

2 31/05/ 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

3 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: 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 31/05/2014 3

4 Use of IIP in estimation of recent year MVA Significant time-lag between reference year and data dissemination year – around 3 years Users demand for more recent year estimates Basic estimation method:(1) where - estimated value added for t th year - VA for base year t 0 - annual IIP for t th year compared to base year t 0 Data available for 159 countries at 2-digit level of ISIC

5 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 31/05/2014 5

6 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 31/05/2014 6

7 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) 31/05/2014

8 A snapshot from the Yearbook on world MVA distribution (row wise) 31/05/2014 8

9 Sector distribution of world MVA (column wise) 31/05/2014 9

10 Estimated VA for country ranking by sectors 31/05/

11 Major problems encountered Difference in valuation of VA: basic prices and producers 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 31/05/

12 IIP in UNIDO research Computation 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: 31/05/

13 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 31/05/

14 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 14

15 World manufacturing growth trends by country groups 31/05/ Quarterly indices of world industrial production (Base 2005=100)

16 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 31/05/

17 31/05/ Please send your comments to UNIDO Statistics

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