Accounting Policies in the Extractive Industry: A Global and a Turkish Perspective

This paper investigates the influence of accounting standards on financial reporting for companies in the extractive industry. In Turkey, listed firms have prepared their financial reports according to the International Accounting Standards and the International Financial Reporting Standards (IAS/IFRS) since 2005, as has the European Union. The aim of this study is to determine the degree of compliance with IFRS 6, comparing global and Turkish extractive entities. We find that the entities reporting in accordance with IFRS 6 in Turkey are more likely to fail to declare their accounting policies, whereas global companies are more likely to be compliant with IFRS 6.     

Selecting container port via a fuzzy ANP-based approach: A case study in the Marmara Region,Turkey

In this case study, a real world problem of a production firm in the Marmara Region, Turkey was considered. In the current situation, the firm works with different third-party logistics firms and uses different ports each time. However, they have some quality problems and decided to work with a logistics firm by using the most convenient port alternative. A number of conflicting qualitative and quantitative criteria exist for evaluating alternative ports. Qualitative criteria are often accompanied by ambiguities and vagueness. To cope with this problem, the fuzzy analytic network process (FANP) method is used in this study. First, we defined the region specific criteria consisting of the twenty sub-criteria under the six main criteria clusters that influence the selection of container port. Then seven alternative container ports located in the Marmara Sea were determined. The results showed that the most convenient district for the container port is Istanbul District, which is one of the biggest economical centers in Eastern Europe.     

INTERGENERATIONAL INCOME MOBILITY IN SWEDEN: WHAT DO TAX‐DATA SHOW?

The aim of this paper is to investigate intergenerational income mobility in Sweden by means of a representative sample drawn from tax-data files. Longitudinal data on actual parent-child pairs spanning 1978–92 are employed. Regression and correlation coefficients are analyzed and transition matrices calculated in order to investigate income mobility over generations. The results achieved show high intergenerational income mobility in Sweden between fathers and sons in comparison to estimations performed in most other countries and more especially compared to the U.S. This indicates that Sweden does not only have lower cross-sectional income inequality, but also higher intergenerational income mobility than those countries. The mother's earnings influence children's earnings less than the father's. However, the mother's earnings correlate more strongly with a daughter's earnings than they do with that of a son. The major indication of immobility across generations is found in the upper income deciles.     

Commodity market risk from 1995 to 2013: an extreme value theory approach

In this article we examine whether extreme risk has increased in the agricultural commodity market during the period 1995–2013. We add to the literature on food price volatility by analysing the tail segment of futures price return distributions. Food price variability is a concern for governments and regulators worldwide, as most nations trade in food. High food price variability can contribute to poverty and malnourishment, in particular for people in less economically developed economies. We find no indications of systematically increasing tail-risk for the commodities in our sample. Analysis of estimated shape-parameters of the Generalized Extreme Value distribution further supports the conclusion that there is no general systematic change in the extreme risk associated with these commodity investments.     

Dual long memory property in returns and volatility: Evidence from the CEE countries' stock markets

This paper investigates the presence of long memory in the eight Central and Eastern European (CEE) countries' stock market, using the ARFIMA, GPH, FIGARCH and HYGARCH models. The data set consists of daily returns, and long memory tests are carried out both for the returns and volatilities of these series. The results of the ARFIMA and GPH models indicate the existence of long memory in five of eight return series. The results also suggest that long memory dynamics in the returns and volatility might be modeled by using the ARFIMA–FIGARCH and ARFIMA–HYGARCH models. The results of these models indicate strong evidence of long memory both in conditional mean and conditional variance. Moreover, the ARFIMA–FIGARCH model provides the better out-of-sample forecast for the sampled stock markets.