Dynamic Functional Principal Components for Testing Causality

In this paper, we investigate the causality in the sense of Granger for functional time series. The concept of causality for functional time series is defined, and a statistical procedure of testing the hypothesis of non-causality is proposed. The procedure is based on projections on dynamic functional principal components and the use of a multivariate Granger test. A comparative study with existing procedures shows the good results of our test. An illustration on a real dataset is provided to attest the performance of the proposed procedure.

Granger causality between cardiovascular diseases and some macroeconomic indicators: Azerbaijan case

Objective: Statistical assessment of the interdependence of CVD indicators on macroeconomic indicators on the example of Azerbaijan. Design: Research design is to test statistical hypotheses about the presence of direct and inverse causal relationships between CDV-indicators and macroeconomic indicators. Baseline and estimated data cover the period from 1991 to 2018 and are based on data from the SSCRA (2019) report. We use paired linear regression in which macroeconomic indicators are independent and CDV indicators are dependent variables. The stationarity of the time series was checked using the ADF test. To investigate the causal relationship between time series, the Granger test was used. Main Outcome Measures: p-level < 0.05; time lags are 1, 2 and 3 years. Results: Absence of direct and inverse causal relationship between CVD indicators and macroeconomic indicators GDP per capita, average annual income households per capita and average annual income households per capita. Conclusions: In the period from 1991 to 2018, the number of CDV deaths in Azerbaijan increased by 1.54. There is a steady increase in CDV diseases by 2.23 times. Despite GDP growth, there is no direct and inverse causal relationship between CVD indicators and macroeconomic indicators in the sense of the Granger test.

Granger Causality Analysis of Geophysical, Geodetic and Geochemical Observations during Volcanic Unrest: A Case Study in the Campi Flegrei Caldera (Italy)

The recent signs of reawakening at Campi Flegrei caldera (Southern Italy) received a great deal of attention due to the issues related to the volcanic risk management in a densely populated area. This paper explores relations between ground deformations, seismicity and geochemical time series in the time span 2004–2016. The aim is to unravel primary processes of unrest and the related indicators which may change in time. Data structure and interactions among variables were examined applying the clustering analysis, the correlations and the Granger causality test. The hierarchical agglomerative clustering detected two sub-periods which were further investigated. In both sub-period causal links were observed between variables while correlations did not appear and vice versa. Thus, well established formal approaches are required to study causal relations. Granger test results indicate that during 2004–2011 the awakening unrest could be mainly ascribed to hydrothermal system pressure fluctuations, probably induced by deep-rooted fluids injection, and that ground deformation together with CO2/H2O appears the most suitable geo-indicators. The 2011–2016 sub-period is characterized by enhanced dynamical connectivity. Granger test results suggest that the unrest is driven by a more localized and shallower thermohydromechanical engine. CO/CO2, He/CH4 and ground deformation velocity are mutually interacting appearing the most suitable geo-indicators.

Inter-Relationship between Global Competitiveness and Human Development- Analytical Study of Selected Countries

The research aims to study the inter-relationship between global competitiveness indicators and human development indicators for selected countries (low, middle, and high income)by using Granger Test, and VAR Test. The results of the causality test showed that there is a causality relation between international competitiveness and human development. We found global competitiveness indicators has a clear effect on human development indicators in the low, middle, and high-income countries.

Information Management: the Key Driver of the Economic System’s Development

In the scientific article, an information management model was developed for assessing the influence of regulatory tools on business processes on the example of the insurance market of Ukraine. The main purpose of the research is to determine the role of information management as a key driver of business process development in economic systems (on the example of the Ukrainian insurance market). Systematization literary sources and approaches for solving the problem indicates that the development of innovative tools of public governance for the assessment of the regulatory influence of the state regulatory body on the business processes of insurance market is not completed and requires a more in-depth study. The formation of a system of indicators characterizing the business processes of insurance market, which take into account the influence of the Regulator's tools, is proposed to be implemented in the following sequence: to find out the causal links between the indicators of business processes of insurance market and the measures; to determine the existence of the reaction of business processes’ indicators of insurance market to the Regulator’s measures, taking into account the time gap, which determines the presence of lags in the process of applying the Regulator's measures; to define and formalize the variability of the business processes’ indicators of insurance market under the influence of the Regulator's measures. Then the scale of the state of insurance market was built: firstly, check for normality the distribution of the indicators’ values of these markets; secondly, in compliance with the distribution law to construct the scale of indicators according to the «three-sigma rule»; thirdly, in the case of nonconformance with the normal distribution law and presence of skewness, the method of «three sigma» may be used, but either the arithmetic mean, or the mode of the variation series, or its median, is taken as the reference point. The relevance of the decision of this scientific problem is that a set of models is developed for establishing causal relationships between the indicators characterizing the business processes of the insurance market and government regulation instruments, which are quantitatively determined, are theoretical and practical basis for their possible application for solving universal modeling problems of causal processes of estimating the influence of the taken decisions at any regulation of business processes. To solve the problem the Granger-test, the expanded Dickey-Fuller test, the Phillips-Perron test and the Kwiatkowski-Phillips-Schmidt-Shin test were applied. Time series distribution on stationarity and construction of vector autoregression models are implemented. In order to evaluate the adequacy of the models, a comparison of values of Fisher's, Student's criteria, determination coefficient and adjusted determination coefficient is used. Jarque-Bera criteria are used to test the model for stationarity, stability. The formalization of cause-and-effect relationships through the postulate of the theory of measurements and the construction of scales is performed. The built interval scales are based on the application of the three sigma rule, which made possible to specify the allowable boundary values of the indicators. The obtained results testify the influence of regulatory tools on the business processes of insurance market, which confirms the correctness of the use of this complex of models for the solution of weakly formalized problems of causal nature of universal type. The proposed innovative model can be used as a methodology for developing a set of rational methods for assessing informational influences of management decisions in production systems or marketing research. The results of the research can be used to evaluate the business processes of any market or system. Keywords: business processes, Granger test, informational management, informational model, insurance key driver, services market, regulation tools, scaling, vector autoregression.

UJI KAUSALITAS GRANGER: INFLASI DAN PENGANGGURAN DI INDONESIA

Inflation and unemployment in Indonesia are specific problems which need government attention. To overcome inflation, we must understand first some factors causing the rise of inflation, before making a policy. In relation to inflation, the number of unemployment can be influenced via company where the employees where the employees work or via manpower market.In this article the writer carried out a causality test of the relation between inflation (I) and unemployment (11) using Granger test model. In this test the writer formulated that the current inflation variable value (It) connected to past inflation and past unemployment level. The writer also tested the variable of current employment level (Ut) where current employment level is influenced by past inflation and employment levels