scholarly journals The Analysis and the Measurement of Poverty: An Interval Based Composite Indicator Approach

2020 ◽  
Author(s):  
Carlo Drago
Keyword(s):  
Monte Carlo Simulation ◽  
Composite Indicator ◽  
Composite Indicators ◽  
Crucial Issue ◽  
Distinct Factor ◽  
Indicator Approach ◽  
Statistical Indicators ◽  
Consistent Measurement ◽  
Random Configuration ◽  
Measurement Of Poverty

The analysis and measurement of poverty is a crucial issue in the field of social science. Poverty is a multidimensional notion that can be measured using composite indicators relevant to synthesizing statistical indicators. Subjective choices could, however, affect these indicators. We propose interval-based composite indicators to avoid the problem, enabling us in this context to obtain robust and reliable measures. Based on a relevant conceptual model of poverty we have identified, we will consider all the various factors identified. Then, considering a different random configuration of the various factors, we will compute a different composite indicator. We can obtain a different interval for each region based on the distinct factor choices on the different assumptions for constructing the composite indicator. So we will create an interval-based composite indicator based on the results obtained by the Monte-Carlo simulation of all the different assumptions. The different intervals can be compared, and various rankings for poverty can be obtained. For their parameters, such as center, minimum, maximum, and range, the poverty interval composite indicator can be considered and compared. The results demonstrate a relevant and consistent measurement of the indicator and the shadow sector's relevant impact on the final measures.

Adjustment of enterprises to the requirements of the fourth industrial revolution – regional approach

2021 ◽  
Vol 66 (1) ◽  
pp. 32-48
Author(s):  
Andrzej Sokołowski ◽  
Małgorzata Markowska
Keyword(s):  
Experimental Research ◽  
Industry 4.0 ◽  
Industrial Revolution ◽  
Composite Indicator ◽  
Composite Indicators ◽  
Regional Approach ◽  
Fourth Industrial Revolution ◽  
The Future

The aim of the paper is to propose a composite indicator characterising the level of development of Polish NUTS 2 regions with respect to the implementation and results of the changes the fourth industrial revolution (Industry 4.0) entails, and to present a ranking of regions illustrating the degree to which enterprises have adjusted to the requirements of Industry 4.0. Data used for the calculations have been based on the results of an experimental research conducted by Statistics Poland (GUS) in 2019. Two methods for constructing the composite indicators have been used – classical and iterative which is to assess the indicator’s resilience to the influence of any potential outliers. 10 sub-criteria, covered by 21 variables have been taken into account. Opolskie region appeared to be the best NUTS 2 region in Poland in terms of the implementation of the requirements outlined by Industry 4.0. The evaluation of the proposed composite indicator will be possible when comparing it with the results of similar surveys carried out by GUS in the future.

A Quantile Composite-Indicator Approach for the Measurement of Equitable and Sustainable Well-Being: A Case Study of the Italian Provinces

2016 ◽  
Vol 136 (3) ◽  
pp. 999-1029 ◽  
Author(s):  
Cristina Davino ◽  
Pasquale Dolce ◽  
Stefania Taralli ◽  
Vincenzo Esposito Vinzi
Keyword(s):  
Well Being ◽  
Composite Indicator ◽  
Indicator Approach ◽  
Italian Provinces

scholarly journals Forecasting Tourism Demand with Composite Indicator Approach for Fiji

2019 ◽  
Vol 9 (4) ◽  
pp. 12
Author(s):  
Ann-Ni Soh ◽  
Chin-Hong Puah ◽  
M. Affendy Arip
Keyword(s):  
Composite Indicator ◽  
Economic Research ◽  
Seasonal Adjustment ◽  
National Bureau ◽  
Tourism Demand ◽  
Monthly Basis ◽  
Significance Level ◽  
Indicator Approach ◽  
Market Outlook ◽  
Average Lead

This study attempts to scrutinize the fluctuations of the Fijian tourism market and forecast the early warning signals of tourism market vulnerability using the tourism composite indicator (TCI). The data employed on a monthly basis from 2000M01 to 2017M12 and the indicator construction steps were adopted from the ideology of the National Bureau of Economic Research (NBER). A parsimonious macroeconomic and non-economic fundamental determinant are included for the construction of TCI. Subsequently, the procedure then employed the seasonal adjustment using Census X-12, Christiano-Fitzgerald filtering approach, and Bry-Boschan dating algorithm. Empirical evidence highlighted the signalling attributes against Fijian tourism demand with an average lead time of 2.75 months and around 54 percent of directional accuracy rate, which is significant at 5 percent significance level. Thus, the non-parametric technique can forecast the tourism market outlook and the constructed TCI can provide information content from a macroeconomic perspective for policymakers, tourism market players and investors.

scholarly journals Building a Composite Indicator to Measure Environmental Sustainability Using Alternative Weighting Methods

2020 ◽  
Vol 12 (11) ◽  
pp. 4398 ◽  
Author(s):  
José Gómez-Limón ◽  
Manuel Arriaza ◽  
M. Guerrero-Baena
Keyword(s):  
Environmental Sustainability ◽  
Environmental Performance ◽  
Composite Indicator ◽  
Composite Indicators ◽  
Alternative Methods ◽  
Analytic Hierarchy ◽  
The Individual ◽  
Hierarchy Process ◽  
Weighting Methods

Environmental sustainability in agriculture can be measured through the construction of composite indicators. However, this is a challenging task because these indexes are heavily dependent on how the individual base indicators are weighted. The main aim of this paper is to contribute to the existing literature regarding the robustness of subjective (based on experts’ opinions) weighting methods when constructing a composite indicator for measuring environmental sustainability at the farm level. In particular, the study analyzes two multi-criteria techniques, the analytic hierarchy process and the recently developed best-worst method, as well as the more straightforward point allocation method. These alternative methods have been implemented to empirically assess the environmental performance of irrigated olive farms in Spain. Data for this case study were collected from a panel of 22 experts and a survey of 99 farms. The results obtained suggest that there are no statistically significant differences in the weights of the individual base indicators derived from the three weighting methods considered. Moreover, the ranking of the sampled farms, in terms of their level of environmental sustainability measured through the composite indicators proposed, is not dependent on the use of the different weighting methods. Thus, the results support the robustness of the three weighting methods considered.

La costruzione di un indicatore sintetico ponderato. Un'applicazione della procedura Benefit of the Doubt al caso della dotazione infrastrutturale in Italia

2009 ◽  
pp. 35-69
Author(s):  
Claudia Mazziotta ◽  
Francesco Vidoli
Keyword(s):  
Data Envelopment Analysis ◽  
Maximum Level ◽  
Jel Classification ◽  
Composite Indicator ◽  
Composite Indicators ◽  
Data Envelopment ◽  
Synthesis Procedure ◽  
Italian Province ◽  
Simple Indicator ◽  
Keywords Composite

- (Paper first received, October 2007; in final form, febbraio 2008) This paper provides a review of a methodology for constructing composite indicators who constitute the synthesis of a series of simple indicators and, above all, characterize a system of weights to use in the synthesis procedure. We apply the Benefit of the Doubt (BoD) approach, an application of the technique of linear programming Data Envelopment Analysis (DEA). In our formulation, however, weights constraints are endogenously determined, differently to BoD usual applications, analyzing variability of every simple indicator. Our methodology allows to find a matrix of the weights characterizing not only the simple indicators, but also the territorial units involved, obtaining, for every unit, the system of weights more favourable and, consequently, a composite indicator with maximum level. BoD approach has been applied to construction of a composite indicator of the Italian infrastructural endowment, whose elementary indicators were available to level of Italian province and infrastructural categories. Keywords: Composite Indicators; Data Envelopment Analysis; Infrastructure Endowment JEL classification: H54. C43. C61

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