This study examines the long-run relationship between carbon emissions and energy consumption, income and foreign trade in the case of China by employing time series data of 1975-2005. In particular the study aims at testing whether environmental Kuznets curve (EKC) relationship between CO2 emissions and per capita real GDP holds in the long run or not. Auto regressive distributed lag (ARDL) methodology is employed for empirical analysis. A quadratic relationship between income and CO2 emission has been found for the sample period, supporting EKC relationship. The results of Granger causality tests indicate one way causality runs through economic growth to CO2 emissions. The results of this study also indicate that the carbon emissions are mainly determined by income and energy consumption in the long run. Trade has a positive but statistically insignificant impact on CO2 emissions. © 2009 Elsevier Ltd. All rights reserved

The banking sector in Turkey has grown significantly over the last two decades of financial liberalization. One of the aims of the financial liberalization was to improve efficiency through restructuring programs including the privatization of state banks and the encouragement of mergers. In this paper we identify key factors determining the technical efficiency differentials among Turkish commercial banks in the pre-and post-liberalization periods, using the technical inefficiency effects model. We found that loan quality, size, ownership of the banks, and profitability have a positive and significant impact on the technical efficiencies of banks. The results warrant implementation of effective regulatory measures to improve the quality of the earning assets of commercial banks. Furthermore, steps by the government to encourage acquisitions or mergers for private banks and the privatization of state-owned banks seem to be consistent in improving the overall efficiency of commercial banking in Turkey.

In this study, non-parametric kernel estimation technique has been employed to estimate import and export price elasticities for six developed countries. Based on the estimates of these elasticities Marshall-Lerner condition has been examined. In general the condition is only partially satisfied in the sub-sample periods. The results also suggest that the condition is more likely to be satisfied under fixed exchange rate regime.

A survey of applications of the Technical Inefficiency Effects (TIE) model suggests that agro‐climatic and other environment variables are customarily omitted in the model specifications. The justification for such an omission is the assumption that these variables are beyond the control of the farmers and therefore should be treated as random variables. In this paper, we argue that in applications dealing with regional agricultural data, agro‐climatic variables should not be treated as pure random terms. Historical differences in agro‐climatic conditions are known with a reasonable degree of certainty across a larger region. Therefore, omission of such variables from the analysis may lead to inaccurate interregional technical inefficiency comparisons. In order to demonstrate the importance of agro‐climatic variables in such analyses, we estimate the TIE model for Turkey. A translog stochastic frontier production function with agro‐climatic variables such as rainfall and land quality is estimated, and it is shown not only that the agro‐climatic variables are statistically significant but also that their omission substantially affects mean output elasticities and relative technical efficiencies. Une étude sur les applications du modèle de l'effet d'inefficacité technique (EIT) laisse à supposer que les variables agro‐climatiques et les autres variables environnementales sont comme d'habitude omises dans les spécifications du modèle. Une telle omission est justifiée par l'hypothèse selon laquelle ces variables sont en dehors du contrôle des fermiers et devraient être considérées comme des variables aléatoires. Dans ce communiqué, nous affirmons que dans les applications concernant les données agricoles régionales, ces variables agro‐climatiques ne doivent pas être traitées comme de simples termes aléatoires. Les différences historiques dans les conditions agro‐climatiques sont connues avec un degré raisonnable de certitudes pour une grande région. Aussi l'omission de telles variables dans l'analyse peut‐elle donner lieu à de fausses comparaisons interrégionales d'inefficacité technique. Afin de démontrer l'importance des variables agro‐climatiques dans de telles analyses, nous considérons le modèle de l'effet d'inefficacité techniques de la Turquie. II s'agit d'une fonction de production frontalière translogue et stochastique avec des variables agro‐climatiques telles que la pluviosité, la qualité de sol et d'autres variables. Nous démontrons que les variables agro‐climatiques sont non seulement importantes statistiquement, mais que leur omission influence essentiellement les élasticités moyennes de production ainsi que les efficacités techniques relatives.