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The green industrial performance (GIP) index provides a tool to analyse and compare the performance of economies in terms of green manufacturing. The demands for and expectations for sustainable development seem not matched with the existence of an analytical framework to measure how green the industrial sector of a given economy is. In this article, we introduce significant methodological improvements to the GIP index. In previous research, we developed and tested a set of indicators covering the various facets of the green industrial performance of economies. We also introduced a composite index to rank economies according to their green industrial performance. In this article, we address some limitations of the index. To improve the non-satisfactory data coverage, we investigate alternative imputation methods. We also refine our list of 'green' products; and test new outlier detection methods. [ABSTRACT FROM AUTHOR]

Manufacturing Value Added (MVA) is the key indicator of a country's industrial production. In order to facilitate international comparisons it is published in UNIDO's International Yearbook of Industrial Statistics for a large set of countries. Because of a time-gap of at least one year between the latest year for which data are available and the year for which MVA data must be reported in the Yearbook, nowcasting methods are used to fill in the missing data up to the current year. We propose a parsimonious methodology that exploits the relationship between MVA and GDP to produce reliable nowcasts of MVA. [ABSTRACT FROM AUTHOR]

A commonly used procedure for reduction of the number of variables in linear discriminant analysis is the stepwise method for variable selection. Although often criticized, when used carefully, this method can be a useful prelude to a further analysis. The contribution of a variable to the discriminatory power of the model is usually measured by the maximum likelihood ratio criterion, referred to as Wilks’ lambda. It is well known that the Wilks’ lambda statistic is extremely sensitive to the influence of outliers. In this work a robust version of the Wilks’ lambda statistic will be constructed based on the Minimum Covariance Discriminant (MCD) estimator and its reweighed version which has a higher efficiency. Taking advantage of the availability of a fast algorithm for computing the MCD a simulation study will be done to evaluate the performance of this statistic. [ABSTRACT FROM AUTHOR]