GROSS JOB – CREATION AND GROSS JOB – DESTRUCTION DETERMINANTS: EMPIRICAL ANALYSE AT MICRO FIRMS DATA LEVEL

Tadeu LEONARDO

Faculty of Economy – Univercity Jos´e Eduardo dos Santos UJES-Angola

tad.eufeca@hotmail.com

Francisco DINIZ

Centre for Transdisciplinary Development Studies (CETRAD); Quinta dos Prados, 5000-801 Vila Real, Portugal, http://www.cetrad.info/

fdiniz@utad.pt

Abstract

This study analyses gross job-creation and gross job-destruction determinants at the firm level for a panel of Portuguese micro firms across four industry sectors, using the Ordinary Leat Square and Fixed Effect econometrics model to analyse a database consisting on 15.686 micro firms, for time period going from 2010 to 2017. It was found that laggard gross job-creation, assets tangibility, financial leverage, profits and the fact firms belong to the construction sector determines gross job-creation. Regarding gross job-destruction,  its was found that this variable is determined by its laggard variable, firm’s size, worker’s tenure and the fact the firm belongs to the hotels and restaurants sector. Finally, findings suggest that a resource-based approach explains gross job-creation and gross job-creation for micro firms by using microdata. This study contributes to the state of the art on the determinants of employment and firing at micro firms’ level as it investigates the importance of the independent variables in explaining micro firm’s labour demand in Portugal.

Keywords: Gross job-creation, gross job-destruction, micro firms, Portugal

JEL classification: M10, O14, O18, O44

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BALANCED SCORECARD AS A TOOL FOR EVALUATING THE INVESTMENT ATTRACTIVENESS OF REGIONS COMPRISING THE ARCTIC ZONE OF THE RUSSIAN FEDERATION

Vladimir MYAKSHIN

Professor,Northern (Arctic) Federal University,Russia,Arkhangelsk,Naberezhnaya Severnnoy Dviny17

mcshin@yandex.ru

Vladimir PETROV

Professor, St. Petersburg State Forestry University, Russia, St. Petersburg, Institutsky pereulok 5

wladimirpetrov@mail.ru

Abstract

Prerequisite to sound investment decision-making is the availability of reliable, objective information on earlier investments and which economic sectors they have benefitted, as well as methods allowing for multi-faceted analysis of investment performance. This study aims to elaborate a balanced scorecard to reflect the performance of and the trends in the investment activity ongoing in the regions that comprise the Arctic Zone of the Russian Federation. Methodologically, the study relies on a systemic, balanced approach; balanced scorecard concept; and foreign and domestic practices of estimating regional investment attractiveness. The study is novel in that it has achieved a customized balanced scorecard that allows for analyzing the RF Arctic regions’ investment attractiveness from various perspectives, while also allowing to identify these regions’ major investment-related challenges and promising investment opportunities. Further, the study contributes to the scientific soundness of strategies that seek better investment image. Among key outcomes of this study is the economic model that uses the said balanced scorecard to measure the RF Arctic regions’ investment attractiveness with regard to investment stakeholders (public authorities, investors, population). The outcomes of this study are expected to be used as guidance by the public authorities in the RF Arctic regions when shaping local investment policies. The prospects of this study lie in further improvement of the contents and the structure of the balanced scorecard as the Russian economy progresses in its development and, hence, improved models will be required for measuring its regions’ investment appeal.

Keywords: The Arctic Zone of the Russian Federation, investment activity, investment risks, investment climate, investment policy, investment attractiveness, important investment aspects, estimation of investment attractiveness, balanced scorecard, regional economic system.

JEL classification: D29, L50, L52, L90

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MODELING LOGISTIC ENTERPRISE RE-LOCATION DECISION BY A NESTED LOGIT MODEL

Y Nguyen CAO

Dr.Eng Vietnam-Japan Research and Development Center, Department of Transport Economics,University of Transport and Communications,Cau Giay, No.03 Lang Thuong, Dong Da, Ha Noi, Viet Nam

ynguyencao82@utc.edu.vn

Abstract

This paper develops a model to analyze decisions regarding the relocation process for logistics enterprise by using discrete choice models. In this framework, two decision points in the relocation process are assumed and maintained in the micro-simulation modeling. The first decision, move or non move, is modeled by using a binary logit form with outcome the probability of moving. The second decision, choosing the destination location, is modeled by a mixed logit model incorporating spatial effects with the outcome of the conditional probability of choosing a zone. This study also applied the relocation decision structure of each logistics enterprise by nested logit model to find out the best model. In case study, the logistics enterprise relocation decision model has acceptable performance by the nested logit model. However, the nested logit model has to follow the IID Gumbel distribution holds within each nest. Therefore, nested logit model cannot take into account the various tastes among alternatives in the random part of utility function to improve the implementation of the model. The proposed model also confirm again the important role of spatial interactions among individual logistics enterprise and among zones in the logistics enterprise relocation decision process. The results indicate that big logistics enterprises have a lower probability of relocating and the migrating enterprises are more attractive in the zone which has a high accessibility. Finally, the population density, number of employees and the average land prices of zone strongly affect on the relocation decision making process of individual logistics enterprises.

Keywords: Mixed Logit Model, Logistics Firm, Re-location Decision Model, Nested Logit Model

JEL classification:

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