A STOCHASTIC MODEL OF MIGRANT RESCUE IN THE MEDITERRANEAN SEA

Amitrajeet A. BATABYAL

Department of Economics, Rochester Institute of Technology, 92 Lomb Memorial Drive, Rochester, NY 14623-5604, USA.
aabgsh@rit.edu

Hamid BELADI

Department of Economics, University of Texas at San Antonio, One UTSA Circle, San Antonio, TX 78249-0631, USA.
Hamid.Beladi@utsa.edu

Abstract
We theoretically study the rescue of destitute migrants seeking to reach Europe on boats across the Mediterranean Sea. To this end, we first construct a discrete-time Markov chain (DTMC) model of a stylized rescue process. Second, we specify the one-step transition probabilities of the DTMC. Third, we delineate a recursive algorithm that can be used to compute the limiting or steady-state probabilities of our DTMC model. Finally, we use these limiting probabilities to compute the average throughput. This metric is an efficiency measure and it tells us the long run expected number of migrants that are rescued by the stylized rescue process under study.
Keywords: Markov Chain, Mediterranean Sea, Migrant, Rescue, Uncertainty
JEL classification: J61, D81
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SPATIAL VARIATIONS OF EMPLOYMENT CHANGE IN GREECE OVER THE EARLY-CRISIS PERIOD (2008-2011)

Dimitris KALLIORAS

University of Thessaly, Department of Planning and Regional Development, Pedion Areos, 38334 Volos, tel: 0030 24210 74484
dkallior@uth.gr
(Corresponding author)

Maria TSIAPA

University of Thessaly, Department of Planning and Regional Development
mtsiapa@uth.gr

Spyridon ZAPANTIS

University of Thessaly, Department of Planning and Regional Development
szapantis@uth.gr

Abstract

Towards conceptualizing and understanding the spatial impact of the contemporary economic crisis, the paper scrutinizes the spatial variations of employment change in Greece. To this end, the paper employs a trade-adjusted shift-share analysis; a shift-share formulation accounting for employment changes resulting from changes in exports, imports and domestic demand. Trade-adjusted shift-share analysis is employed against the backdrop of the world economy, on the basis of employment data that refer to NACE Rev. 2 aggregation sectoral levels and to NUTS II spatial level, and covers the early-crisis period (2008-2011). The results obtained highlight the negative national effect component as an outcome of the shocks and the upsets that the Greek economy has suffered. The industry mix component and the competitive shift component are positive only for specific regions and sectors. Particularly, for the industry mix component it comes that all Greek regions specialize in sectors that, at the national level, are export-declining and import-declining and experience labor productivity losses.

Keywords: economic crisis, employment change, Greek regions, trade-adjusted shift-share analysis

JEL classification: C10, F10, L16, R11, R12
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ZIPF’S LAW APPEARANCE IN THE RUSSIAN CITIES

Svetlana RASTVORTSEVA

World Economy Chair – Belgorod State National Research University, Russia, http://www.bsu.edu.ru
SRastvortseva@gmail.com

Inna MANAEVA

World Economy Chair – Belgorod State National Research University, Russia, http://www.bsu.edu.ru
in.manaeva@yandex.ru

Abstract

The understanding of concentration processes about resources, population, enterprises in some regions and in the cities is very significant for economists and policy-makers. It’s caused by the worldwide urbanization trend and local trend of economic activity agglomeration that increase the regional development differentiation within the country. Issues of economic activity locations and space distribution are solved by scientists over the past two centuries. Recent works show the increasing interest of economists to the Zipf’s law testing in the regional system and the rank-size distribution of the cities. Research aims are to test the Zipf’s law in the Russian cities and to test the hypothesis that the Russian Zipf coefficients depends on the size of the geographical territory of the Federal District.Methodology. In the paper it’s used least square method for tasting the Zipf’s law in Russian cities in general and separately for the federal districts. There is 1,123 Russian cities panel (cities with over 1,000 people population in 2014).Results. The Zipf’s law is confirmed in the territory of Russia in general. According to the Federal Districts the Zipf coefficients range from -0.65 (Far Eastern Federal District) to -0.9 (the Urals and the North Caucasian Federal Districts). Equitability of cities hierarchy in the Ural and the North Caucasus Federal Districts dues to the fact that there are 139 cities located in the 1,789 thous. km2 in the Urals and 56 cities in the 170 thous. km2 in the Caucasus. In the Far East the city location is very disperse – 66 cities in the area of 6000 thous. km2 (Zipf coefficient – 0.65). Conclusions. Testing of the Zipf’s law for the Russian cities in general shows that it’s valid for the small (8,600 – 15,300 peoples) and large cities (66,700 – 331,000 peoples). For cities panel with population exceeds 100 thous. people. The Zipf’s law is not valid for cities of more than 1 million people. (exception – the city of St. Petersburg). The result of the study is the confirmation of the hypothesis that the Zipf coefficient depends on the size of the Federal District.

Keywords: location theories, the Zipf’s law, the city, the rank-size distribution, the cities of Russia

JEL classification: R12
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