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Maarten Vanhoof, Fernando Reis, Thomas Ploetz and Zbigniew Smoreda

Abstract

Mobile phone data are an interesting new data source for official statistics. However, multiple problems and uncertainties need to be solved before these data can inform, support or even become an integral part of statistical production processes. In this article, we focus on arguably the most important problem hindering the application of mobile phone data in official statistics: detecting home locations. We argue that current efforts to detect home locations suffer from a blind deployment of criteria to define a place of residence and from limited validation possibilities. We support our argument by analysing the performance of five home detection algorithms (HDAs) that have been applied to a large, French, Call Detailed Record (CDR) data set (~18 million users, five months). Our results show that criteria choice in HDAs influences the detection of home locations for up to about 40% of users, that HDAs perform poorly when compared with a validation data set (resulting in 358-gap), and that their performance is sensitive to the time period and the duration of observation. Based on our findings and experiences, we offer several recommendations for official statistics. If adopted, our recommendations would help ensure more reliable use of mobile phone data vis-à-vis official statistics.

Open access

Anderson Cristiano Neisse, Jhessica Letícia Kirch and Kuang Hongyu

Summary

The presence of genotype-environment interaction (GEI) influences production making the selection of cultivars in a complex process. The two most used methods to analyze GEI and evaluate genotypes are AMMI and GGE Biplot, being used for the analysis of multi environment trials data (MET). Despite their different approaches, both models complement each other in order to strengthen decision making. However, both models are based on biplots, consequently, biplot-based interpretation doesn’t scale well beyond two-dimensional plots, which happens whenever the first two components don’t capture enough variation. This paper proposes an approach to such cases based on cluster analysis combined with the concept of medoids. It also applies AMMI and GGE Biplot to the adjusted data in order to compare both models. The data is provided by the International Maize and Wheat Improvement Center (CIMMYT) and comes from the 14th Semi-Arid Wheat Yield Trial (SAWYT), an experiment concerning 50 genotypes of spring bread wheat (Triticum aestivum) germplasm adapted to low rainfall. It was performed in 36 environments across 14 countries. The analysis provided 25 genotypes clusters and 6 environments clusters. Both models were equivalent for the data’s evaluation, permitting increased reliability in the selection of superior cultivars and test environments.

Open access

Abbas Pak

Abstract

Fisher information is of key importance in estimation theory. It is used as a tool for characterizing complex signals or systems, with applications, e.g. in biology, geophysics and signal processing. The problem of minimizing Fisher information in a set of distributions has been studied by many researchers. In this paper, based on some rather simple statistical reasoning, we provide an alternative proof for the fact that Gaussian distribution with finite variance minimizes the Fisher information over all distributions with the same variance.

Open access

Mirosława Wesołowska-Janczarek and Monika Różańska-Boczula

Summary

This paper presents an application of Hellwig’s method for selecting concomitant variables under a growth curve model, where the values of the concomitant variables change over time and are the same for all experimental units. The authors present a simple adaptation of the growth curve model to the multiple regression model for which Hellwig’s method applies. The theoretical considerations are applied to the selection of significant concomitant variables for raspberry fruiting.

Open access

Fahir Kanlić and Ademir Abdić

Abstract

National Statistical Institutes (NSIs) strive to produce short-term business statistics (STS) indicators with the high quality estimates in a timely manner. NSIs are usually faced with the challenges, such as differences in definitions, incompleteness of administrative data, periodicity and timeliness, coverage issues, etc. Administrative Value Added Tax (VAT) turnover data can be used to partially or completely replace survey data for the estimation of short-term business turnover indicators. In this paper, main characteristics of administrative VAT turnover data in Bosnia and Herzegovina will be examined through cleaning of VAT turnover data and matching them with survey data. Hence, the main objective of this study is to investigate the relationship between VAT turnover data and survey data in in Bosnia and Herzegovina. The Monthly Retail Trade Turnover Indices (RTI) for in Bosnia and Herzegovina will be estimated by using administrative VAT turnover data. Spearman’s correlation coefficients are used to examine the presence of a linear relationship between VAT turnover data and survey data. Results gained by using survey and administrative VAT turnover data will be compared. Based on the results of the analysis, future challenges and perspectives for expansion of using administrative VAT turnover data will be identified.

Open access

Rudi Seljak, Lea Bregar, Sanda Colić and Maja Dozet

Abstract

In spite of theoretical inferiority, a large majority of statistical institutes use non-probabilistic sampling techniques in price surveys. The main disadvantage of non-probabilistic sample design is that the risk of biased results is increased. Attempting to handle this risk in the domain of service producer price indices (SPPI) of professional services, the Croatian Bureau of Statistics (CBS) developed an innovative methodology and implemented it relying on the probability proportional to size (PPS) sample design. The purpose of the paper is to evaluate the impact of the probabilistic sampling strategy on the quality of price indices as shown in the case of SPPI for professional services at the CBS. The paper outlines respective methodological upgrading of SPPI compilation at the CBS, including also the method for variance estimation. The effect of the probabilistic sampling on SPPI is analysed by comparison with traditional purposive sampling surveys. The quality of SPPI based on the probabilistic sample approach is examined by coefficients of variation and confidence intervals.

Open access

Berislav Žmuk and Iris Mihajlović

Abstract

The expansion of the Internet has radically changed the way in which citizens travel, book and organise travel arrangements. Since innovation and new information technologies have become crucial determinants to encourage competitiveness in the tourism sector in Europe, this article investigates how selected development indicators influence the Percentage of individuals that use Internet for travel and accommodation services. Eurostat data for 34 European, European Union (EU-28) and selected EU candidates, countries for 2017 were analysed. It has been presented that (1) Gross Domestic Product per capita in Purchasing Power Standards; (2) Percentage of population aged 15 to 64, by tertiary education; as well as (3) Percentage of individuals aged 16 to 74, who have basic or above basic overall digital skills, all correlate positively and strongly with the main variable under study. The conducted regression analysis has shown that variable digital skills has the greatest impact on the main variable under the study. The K-mean clustering of countries resulted with four clusters. The Western Balkan countries can be found in a cluster which has in average the lowest values of all four variables in compare to the averages of other three clusters.

Open access

Gloria Gheno

Abstract

If there are no heavy sanctions in place to prevent it, the problem of the cancellation of appointments can lead to huge economic losses and can have a significant impact on underutilized resources of healthcare facilities. A good model to predict the appointment cancellations could be an effective solution to this problem. Therefore, a new Bayesian method is proposed to estimate accurately the probability of the cancellation of visits to healthcare institutions based on specific factors such as age. This model uses the regression for binary variables, linking the explanatory variables to the probability of appearance at a previously made appointment with a new weighted function and estimating the parameters with the Bayesian method. The goodness of the new method is demonstrated by applying it to a real case and by comparing it to other methodologies. Therefore, the advantages of the proposed method are exposed and possible real-world applications are described.

Open access

Martin Noveski

Abstract

Although a decade has passed since the global financial and economic crisis of 2008, the expansionary fiscal policy in Macedonia can still be felt, primarily through an increased level of public expenditures aimed at stimulation of the economic growth. From 2008 onwards, the Republic of Macedonia has continuously recorded a negative budget balance, which affects the resources allocation and the overall economic situation. The question that arises is whether such interference by the Government in the functioning of the market economy is necessary, especially having in mind the EU regulation in this area. Using a multiple regression model for the period 1996-2015, this paper examines the impact of the budget deficit on Gross Domestic Product (GDP) per capita in Macedonia. Results show that the budget deficit is not a statistically significant determinant of GDP per capita, supporting thus the Ricardian equivalence theory. The analysis is conducted on the basis of statistical data from the World Bank’s database, as well as data from the National Bank of the Republic of Macedonia. Household final consumption expenditure, the unemployment rate and the official exchange rate of the Macedonian Denar against the U.S. Dollar are also taken into consideration as controlling variables. GDP per capita and household final consumption expenditures are in current prices, with natural logarithms applied, whereas the other variables are in nominal terms. The purpose of this paper is to provide an insight into the empirical relationship between the two main variables of interest and to initiate further discussion and analysis.

Open access

Vesna Bucevska and Goran Mojanoski

Abstract

This paper aims to evaluate the relationship of real exchange rates of domestic currencies with macroeconomic variables in Macedonia, Croatia and Serbia by using econometric approaches. Macedonia is characterized by the regime of a fixed exchange rate, Croatia is characterized by a managed floating exchange rate, while Serbia is characterized by the regime of a floating exchange rate. The choice of an exchange rate regime is an important aspect of economic management, in order to ensure competitiveness, macroeconomic stability and development. Evaluation of the relationship of Croatian, Macedonian and Serbian real exchange rates is performed by employing the consistent methodology of vector error correction modelling (VECM). According to the results of the analyses of the real exchange rates on the long run, the selected independent variables have long-run causality in case of the real exchange rate of Croatian Kuna. In case of Macedonian Denar and Serbian Dinar the VECM is inappropriate.