Information and Knowledge as Antecedents of Consumer Attitudes and Intentions to Buy and Recommend Fair-Trade Products

The authors propose and empirically test a causal model to understand how the availability of fair-trade information and consumer knowledge about this issue affect consumers’ attitudes and intentions toward fair-trade products. The model is built upon the attitude-behavior paradigm and the premises of agency theory. It is tested through structural equation modeling with a sample of 292 Spanish consumers. The findings are that consumers do not have good knowledge about fair trade and that this is significantly determined by the lack of information about this in the market. It is also observed that consumers’ perceptions about the availability of fair-trade information have negative effects on their concern about this issue and that such information as is available is not effective in reducing consumer skepticism. The research represents an extension of previous fair-trade literature because the role of information and communication in improving consumer attitudes and buying intentions has rarely been explored in the case of ethical products.     

Competing for Good Immigrants

I analyze the competition among different countries for ‘desirable’ and ‘undesirable’ potential immigrants, using both an immigration quota and a level of (imperfect) ‘scrutiny’ that would‐be immigrants face. Scrutiny imposes costs on immigrants and therefore makes it less attractive to immigrate. The number of applying undesirable immigrants increases in immigration quota and decreases in the level of scrutiny. In contrast, the number of desirable applicants can go in either direction as scrutiny increases and is independent of the immigration quota, because an increase in the immigration quota is completely crowded out by more applications by undesirable immigrants.     

In Data We Trust? An Analysis of Indonesian Socioeconomic Survey Data

What if a popular dataset that has generated a large amount of literature has been misunderstood and has led to misleading inferences? This paper examines household expenditure data from the Indonesian National Socio-economic Survey (Susenas), which started more than 50 years ago. Appropriate use of Susenas data for policy analysis requires an understanding that the survey’s expenditure variable does not measure true out-of-pocket expenses, because it includes subsidies received by households when obtaining goods and services. We also highlight an abrupt change in the survey instrument that occurred in 2015, when the reference period for certain items was extended. For health items, this generated a change in the expenditure series that can be misinterpreted as being the result of a social health insurance reform introduced in 2014 to lower the health care burden on households. Accordingly, we propose a way to account for this artificial expenditure movement in Susenas.     

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.     

LEADERSHIP IN CLIMATE CHANGE MITIGATION: CONSEQUENCES AND INCENTIVES

Initiatives in favor of unilateral action on climate change are frequently challenged by concerns over free riding. Nevertheless, we observe an increasing number of unilateral efforts at different administrative levels and in different parts of the world. Previous academic literature described various individual mechanisms where emissions abroad may increase or decrease as a reaction to unilateral emission reductions. In this paper, we collect a comprehensive set of both positive and negative reactions and analyze them in stylized models. This allows us to identify the most important characteristics that determine the potential of a leader to boost mitigation efforts abroad. We find that this potential depends on (i) a strong ability to generate knowledge through leadership, (ii) a high degree of credibility in the international community, and (iii) a similar economic structure to the most important emitters. While most effects are difficult to quantify, this comprehensive assessment suggests that leakage effects resulting from unilateral mitigation may well be outweighed by positive reactions.     

Are China’s regional agricultural productivities converging: How and why?

This article tests the hypotheses of convergence to a single level of total factor productivity (TFP), and a steady state of TFP growth rate in China’s agricultural sector. Based on multilateral TFP estimates we found that China’s agricultural sector has rebounded in recent years from a slower TFP growth in the 2005–2007 period. While convergence test results confirm a “catch-up” effect that provinces with lower TFP levels tend to grow faster than others, estimated rates of β convergence are conditional on how we capture the heterogeneity effect across regions. The rates of β convergence range from 0.016 to 0.039 under different model specifications. Estimates show that higher growth rates of educational attainment, R&D, and intermediate goods density (per unit of labor) can enhance TFP growth. Unfortunately, there is no evidence of an overall σ convergence, indicating that TFP levels are not converging except in the South region. It implies that to catch up with leading provinces, it would require extra efforts for those lagging behind by increasing their region-specific research investment, promoting rural educational attainment, and enhancing embodied technical change.     

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.     

Interventions in Markets with Adverse Selection: Implications for Discount Window Stigma

I study the implications for central bank discount window stigma of a workhorse model of adverse selection in financial markets. In the model, firms (banks) need to borrow to finance a productive project. There is limited liability and firms have private information about their ability to repay their debts, which gives rise to the possibility of adverse selection. The central bank can ameliorate the impact of adverse selection by lending to firms. Discount window borrowing is observable and it may be taken as a signal of firms' credit worthiness. Under some conditions, firms borrowing from the discount window may pay higher interest rates to borrow in the market, a phenomenon often associated with the presence of stigma. I discuss these and other outcomes in detail and what they suggest about the relevance of stigma as an empirical phenomenon.     

新进入者如何在版权引进市场中有所作为

外版书引进在近现代中国出版史上具有非常重要的地位。我国版权贸易市场渐趋稳定的力量对比格局，给新进入者造成了不小的困惑：好版权抢不到，差版权没法要，夹缝中求生存异常艰难。新入者要改变这种困境就要精准定位，必须贴合本单位现有的资源基础，必须借助社会化分工并灵活创新。