INVESTIGATING THE IMPACT OF ATM AND POS TERMINALS ON MONEY DEMAND IN NINE EUROPEAN COUNTRIES IN THE CONTEXT OF A RANDOM EFFECT MODEL AS THE APPROPRIATE PANEL DATA MODEL

Payam MOHAMMAD ALIHA

Ph.D student, Universiti Kebangsaan Malaysia (UKM), Malaysia

payammaliha@gmail.com

Tamat SARMIDI

Associate Professor Dr. at Faculty of Economics and Management, Universiti Kebangsaan Malaysia (UKM), Malaysia

tamat@ukm.edu.my

Fathin FAIZAH SAID

Associate Professor Dr. at Faculty of Economics and Management, Universiti Kebangsaan Malaysia (UKM), Malaysia

fatin@ukm.edu.my

Abstract

This study investigates the effects of financial innovations on the demand for money using panel data for 9 European countries from 2014 to 2018. Such models assist in controlling for unobserved heterogeneity when this heterogeneity is constant over time and correlated (fixed effects) or uncorrelated (random effects) with independent variables. Hausman test and Breusch and Pagan Lagrangian multiplier test (LM) both indicate that the random effects model is appropriate. We use the conventional money demand that is enriched with the number of automated teller machines (ATM) and the number of point-of-sale (POS) terminals to proxy for the financial innovations. The estimation result of the chosen random effects regression indicate that the elasticity of the demand for real money to POS is about 10 percent meaning that money demand is not elastic with regard to POS. Also, the estimated coefficient of ATM is not significant.

Keywords: EU, money demand, random effects, fixed effects, financial innovation, panel data

JEL classification: C13, C40, C51, E40, E44

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THE IMPORTANCE OF SOUTHEAST MEDITERRANEAN NATURAL GAS RESERVES TO EU’S ENERGY SECURITY; A GEOPOLITICAL AND ECONOMIC APPROACH

Antonios STRATAKIS

PhD Candidate, University of Piraeus – Department of Maritime Studies,

stratakismaritime@gmail.com

Theodore PELAGIDIS

Professor of Economics, University of Piraeus – Department of Maritime Studies, Deputy Governor – Bank of Greece, pelagidi@unipi.gr

Tpelagidis@bankofgreece.gr

Abstract

It has been more than a decade since the Southeast Mediterranean region came to the forefront after the discovery of significant gas reserves in offshore fields located within the maritime territories of Egypt, Cyprus and Israel (Levantine Basin). Gradually, the region drew the attention of major oil companies (Total, Statoil, ENI, Exxon Mobil, BP, Rosneft Qatargas) which intensified their drilling operation activities; aiming to share the exploitation of the potential regional gas deposits with the involved countries in the future. Τhe aim of this paper is to investigate (a) the economic impact of these discoveries on the countries concerned, (b) what role can these discoveries play in EU’s energy plans, given the stated policy to reduce dependence on Russian supplies and (c) the implementation of a forthcoming energy hub in Southeast Mediterranean region, its viability and competitiveness towards other well-established or emerging gas producing areas. Finally, the paper examines the conflicted interests of European Union, Russia and USA in the energy equation of the region.

Keywords: Energy Corridors, Pipeline Networks, EastMed Project, LNG Terminals, Southeast Mediterranean

JEL classification: F10, F51, R41, R42, R48

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PATTERNS OF MAINLY TOURISM SECTORS AT LOCAL LEVEL BY EMPLOYEE’S CHARACTERISTICS USING GIS MULTIVARIATE CLUSTERING ANALYSIS – ROMANIA CASE STUDY

Cristina LINCARU

Dr, FeRSA, Department of Labour Market, National Scientific Research Institute for Labour and Social Protection, Bucharest, Romania ORCID ID: 0000-0001-6596-1820

cristina.lincaru@yahoo.de

Speranța PÎRCIOG

Dr, Scientific Director, National Scientific Research Institute for Labour and Social Protection, Bucharest, Romania ORCID ID: 0000-0003-0215-038X

pirciog@incsmps.ro

Draga ATANASIU

Senior Researcher, National Scientific Research Institute for Labour and Social Protection, Bucharest, Romania ORCID ID: 0000-0002-9695-8592

incsmps1@incsmps.ro

Cristina STROE

Senior Researcher, Department of Social Policies, National Scientific Research Institute for Labour and Social Protection, Bucharest, Romania ORCID ID: 0000-0001-8384-6084

cristinaradu@incsmps.ro

Vasilica CIUCĂ

Dr, Dr, General Director, National Scientific Research Institute for Labour and Social Protection, Bucharest, Romania ORCID ID: 0000-0003-4687-6377

silviaciuca@incsmps.ro

Adriana GRIGORESCU

Dr., Department of Public Management, National University of Political Studies and Public Administration,  Correspondent Member of Academy of Romanian Scientists, Bucharest, Romania ORCID ID: 0000-0003-4212-6974

adrianagrigorescu11@gmail.com

Abstract

The tourism sector, before the Corona Strikes, works as a inclusive development engine for many countries’ economies and labour markets. In a global world, with increasing travel opportunities, tourism offers both labours intensive and knowledge-intensive activities, across many economic sectors. Tourism is a spatially dependent sector and also a tradable one. The Methodology for tourism statistics (Eurostat 2014),  Tourism Satellite Accounts (TSA 2010) and The International Recommendations for Tourism Statistics 2008 (IRTS 2008) differentiate the “mainly tourism” industries at four digits. We identify the natural cluster by number and pattern, at 3189 local spatial units (NUTS 5) by eight attribute variable employees: gender (male, female), age (youth, adult and aged) and education detained level (low, medium and high). Sectors are detailed at two digits only (H51- Air transport, I55 – Hotels and other accommodation facilities and N79-Activities of tourist agencies and tour operators; other reservation services and tourist assistance). Romanian National Institute of Statistics provides 2011 Census data. We apply the Multivariate Clustering Analysis with K Means algorithm as a Spatial Statistical Tool in Arc Gis Pro 2.3, an unsupervised machine learning an Artificial Intelligence technique, appropriate for Big Data. Clusters resulted illustrates natural hidden patterns of local labour markets pooling in the sense of Urban& Jacobian economies, but also some insight regarding the Morettian externalities sources. These results are useful for Regions Smart Specialisation Strategies development of human resources & talents to increase innovation capabilities and inclusive job creation, but also for a prompt recovery post-Covid Pandemic.

Keywords: tourism, labour force characteristics, Multivariate Clustering Analysis, local labour markets, regional specialisation, education level, age and gender analysis

JEL classification: J210, C38, R23

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