Exchange rate and transport cost sensitivities of bilateral freight flows between the US and China

This paper explores the long-run impacts of gross domestic product, exchange rate, and transport costs on bilateral air and ocean freight flows between the US and China. The study employs a cointegration framework by using export and import data over the period of 2003:Q1-2014:Q2. Results show that gross domestic product is the key determinant of bilateral freight flows, indicating that real income of a trading partner is a driving force of the bilateral freight flows between the US and China. In examining the sensitivities of the bilateral trade flows, air freight flows are found to be more responsive to a real income change than ocean freight flows. The bilateral exchange rate is a significant factor affecting the freight flows from China to the US, suggesting that a US dollar appreciation against the Chinese yuan increases the inflows of Chinese commodities to the US. The impacts of the bilateral exchange rate and transport cost are found to vary at industry and commodity levels. These findings support the importance of employing disaggregate data in the bilateral freight flow analysis.     

金融发展和城乡收入差距关系的实证分析

本文采用1990~2004年间的统计数据,通过协整分析和Granger因果检验法,对金融发展和城乡收入差距的关系作出实证研究。结果表明:金融发展与城乡收入差距正相关且前者是后者的Granger原因,中国现阶段的金融发展扩大了城乡收入差距。     

Nonlinear multivariate time–space threshold vector error correction model for short term traffic state prediction

We propose Time–Space Threshold Vector Error Correction (TS-TVEC) model for short term (hourly) traffic state prediction. The theory and method of cointegration with error correction mechanism is employed in the general design of the new statistical model TS-TVEC. An inherent connection between mathematical form of error correction model and traffic flow theory is revealed through the transformation of the well-known Fundamental Traffic Diagrams. A threshold regime switching framework is implemented to overcome any unknown structural changes in traffic time series. Spatial cross correlated information is incorporated with a piecewise linear vector error correction model. A Neural Network model is also constructed in parallel to comparatively test the effectiveness and robustness of the new statistical model. Our empirical study shows that the TS-TVEC model is an effective tool that is capable of modeling the complexity of stochastic traffic flow processes and potentially applicable to real time traffic state prediction.     

Estimating the effects of entry regulation in the Istanbul taxicab market

The economic literature shows that entry regulation in taxicab markets brings about a dramatic increase in medallion prices or license values of taxicabs. However, there is no study estimating what the effect of regulation is exactly on real medallion prices. We develop a model to estimate the effect of entry restrictions in the Istanbul taxicab market over real medallion prices and inflation. Our findings contribute that entry regulation in taxicab markets increases medallion prices. Moreover, we find that entry regulation in Istanbul pressures inflation rates as well.