Economic Impacts of the Possible China–US Trade War

This article uses a multi-country global general equilibrium (GE) model to numerically simulate the effects of possible China–US trade wars. We introduce an endogenous trade imbalance structure with trade cost into the model which helps to explore both tariff and non-tariff trade war effects. Our simulation results show that China will be significantly hurt by the China–US trade war, but negative impacts are affordable. The US can gain under unilateral sanction measures to China, but will lose if China takes retaliation measures. Comparing the effects under mutual trade war, China will lose more than the US. Introducing non-tariff barrier trade wars will intensify the negative effects, and comparatively negative effects to China are larger than to the US. Mexico’s involvement in trade war with the US will strengthen the negative effects and comparatively hurt the US more. Under non-cooperative and cooperative Nash bargaining equilibrium, the US can gain more than China in trade war negotiation, which means the US has stronger bargaining power than China. Additionally, trade wars between China and the US will hurt most countries and the world especially in GDP and manufacturing employment, but benefit their welfare and trade.     

Magic mirror in my hand … How trade mirror statistics can help us detect illegal financial flows

Misreporting tricks of different sorts applied to the transfer of goods between different countries are typically exploited by criminals worldwide for money laundering ends. The main international anti‐money laundering organisations started paying attention to this phenomenon, dubbed “trade‐based money laundering” (TBML), a long time ago, but the failure to develop appropriate analytical tools has reportedly dogged preventive actions. Nonetheless, literature has widely advocated the possibility that the analysis of inconsistencies in mirrored bilateral trade data could provide some help. By building on previous contributions in the field, this work sets up a model factoring in the main structural determinants of discrepancies between mirrored data concerning Italy's 2010 to 2013 external trade at a highly detailed (6‐digit) level of goods classification for each partner country. Point estimates of freight costs are used to net each observation of the corresponding cif/fob discrepancy. The regression estimates are then deployed in order to compute TBML risk indicators at a country/4‐digit product level. Based on the indicators, rankings of countries and product lines can be compiled, which may be used for a risk‐driven search of potential illegal commercial transactions.     

Determinants of China's bilateral trade balance in global value chains

This paper identifies the determinants of China's bilateral trade balance using a new measure based on international input–output data, the so-called ‘trade in value-added’ (TiVA), which can prevent double counting in the estimation of bilateral trade balance. Our results show that using a measure based on gross exports, rather than TiVA, causes relatively large overestimation of the impact of the RMB exchange rate on China's bilateral trade balance. This overestimation is mainly because that the increasing production of exports may require increasing intermediate imports as a consequence of international fragmentation of production in global value chains. In addition, our results also show that the impact of FDI inflows on China's bilateral trade balances depends on the position and role of China and its trading partners in GVCs.     

Political Economy of Regional Integration: The Northeast Asian Model Revisited

It is found that the intra-regional trade share or functional integration plays an important role in the institutionalization of regional integration not only in the European Union (EU) but also in Northeast Asia. The crisis factor, which is measured by the regional economic growth rates, is empirically significant in Northeast Asia but not in the EU. This situation confirms the crisis model for Northeast Asia that emphasizes the stimulating role of crisis for the institutionalization of regional integration. However, the political leadership factor is not empirically significant in Northeast Asia and in the EU, and this finding does not support the political leadership model that emphasizes the facilitating role of political leadership for the institutionalization of regional integration.     

Interenterprise Credit and Adjustment during Financial Crises: The Role of Firm Size

Small and medium‐sized enterprises (SMEs) suffered a sharp contraction in their borrowing from banks during the Great Recession. Analyzing a large firm‐level database for European countries, the paper shows that trade credit amplified the liquidity squeeze on SMEs, with adverse effects on their real activity. SMEs sharply increased their net trade credit and thus transferred financial resources to larger firms. Given the large weight of SMEs in the economy of European countries, the liquidity squeeze of SMEs likely contributed to the depth of the output fall and the slow recovery in Europe during the Great Recession.     

省域尺度下不同时序景观指数集与粒度效应分析

[目的]景观格局变化是景观生态学中的热点问题。研究省域尺度下不同时序景观指数的粒度效应、选取计算景观指数所需的适宜粒度范围并筛选出代表性景观指数集对分析景观格局变化具有重要意义。[方法]以安徽省土地覆被为研究对象,以2000年、2005年、2010年的Landsat TM遥感影像为主要数据源,采用土地利用转移矩阵对安徽省土地覆被的转移数量与方向进行研究;通过设置不同的栅格大小研究景观指数的粒度效应并选取合适的粒度范围;基于相关性分析、因子分析与敏感性分析,筛选出代表性景观指数集。[结果](1) 2000—2010年安徽省的土地覆被始终以耕地为主,其次是林地与人工表面;人工表面的增加是建立在耕地面积减少基础之上的,在10年间共有超过3 200km2的耕地转化为人工表面;(2)景观指数存在粒度效应,粒度变化会对景观指数的计算结果产生影响;省域尺度下计算景观指数所需的合适粒度范围为100～125m;(3)研究安徽省景观格局变化的代表性景观指数有4个,分别为最大斑块指数、景观形状指数、平均斑块面积、香农多样性指数。[结论]计算安徽省景观指数的适宜粒度范围为100～125m,安徽省的代表性景观指数集为最大斑块指数、景观形状指数、平均斑块面积、香农多样性指数,为进一步研究景观格局变化及驱动机制提供了依据。     

Why you should use high frequency data to test the impact of exchange rate on trade

This study suggests that testing the impact of exchange rate on trade should be done using high-frequency data. Using different data frequencies for identical periods and specifications between the US and Canada, we show that low-frequency data might suppress and distort the evidence of the impact of exchange rate on trade in the short run and the long run.     

Protecting Innovation Through Patents and Trade Secrets: Evidence for Firms with a Single Innovation

Abstract

This paper analyzes the use and effectiveness of patents and trade secrets designed to protect innovation. While previous studies have usually considered patents and trade secrets as substitutes for one another, we investigate to what extent and in what situations the two protection methods are used jointly. We identify protection strategies for single innovation firms and hence overcome the assignment problem of existing empirical studies, that is, whether firms using both protection methods do so for the same innovation or for different innovations. Employing firm panel data from Germany, we find fairly few differences between the determinants for choosing secrecy and patenting. Single innovators that combine both strategies, 39% of the group, tend to aim at a higher level of innovation and act in a more uncertain technological environment. Firms combining both protection methods yield significantly higher sales with new-to-market innovations, providing some evidence for a complementarity of the two protection methods.     

The exchange regime and trade balance in Turkey

Over the last 15 years, high trade deficits have become a source of external vulnerability for the relatively stabilized Turkish economy. This corresponds to the period where authorities have been following a floating exchange rate regime. Thus, this study aims to empirically show whether the adopted exchange rate regime has an impact on the trade balance for the period of 1987 Q1 to 2015 Q2. Estimation results indicate that there is a long-run relationship between the real effective exchange rate and trade balance under both fixed and floating regimes in Turkey, but there is no evidence for the J-curve hypothesis.     

基于效应的随机灰规划模型和应用

为了解决同时含有随机因素和灰色因素的不确定规划问题,通过结合区间灰数所属区间两个端点的随机性,给出随机区间灰数和随机区间灰函数的定义,提出了随机灰规划模型。通过综合效应函数理论用随机变量期望值和方差综合量化表示灰数所属区间的两个端点值。应用该理论对综合量化后的两个端点值继续进行综合量化,从而将随机灰规划转化为确定型规划问题。应用遗传算法进行求解。通过综合效应函数的理念,综合随机变量的期望和方差,同时综合区间灰数的区间因素,将随机灰规划数学模型转化为确定型规划模型即基于效应的随机灰规划模型。通过选取不同的综合效应函数,得到了关于不同决策意识下的随机灰规划的最优解。这个方法可为决策者进行不确定决策提供参考。