Permit markets,carbon prices and the creation of innovation clusters

Innovation clusters combining public and private effort to develop breakthrough technologies promise greater technological advances to slow down climate change. We use a multi-country model with an emission trading system to examine whether and how international climate policy can incentivize countries to create such innovation clusters. We find that a minimal carbon price is needed to attract applied research firms, but countries may nevertheless fail to invest in complementary research infrastructure. We construct a mechanism that leads to innovation clusters when emissions targets are set before uncertainty surrounding technological developments is resolved. It is a combination of low permit endowments for the country with the lowest costs to build the needed infrastructure, compensation for this country by profits from permit trade, and maximal possible permit endowments for the remaining countries. We outline how the EU-ETS can be further refined according to this mechanism.     

The impact of research collaboration on academic performance: An empirical analysis for some European countries

The aim of this paper is to investigate the impact of internal and external research collaborations on the scientific performance of academic institutions. The data are derived from the international SCOPUS database. We consider both quantity (the number of publications) and quality indicators (the field-weighted citation impact and the share of publications in the 10% most-cited articles) to evaluate universities' performance in some European countries (Germany, France, Italy, the UK and Russia). To this end, we develop a non-overlapping generations model to evidence the theoretical idea of research externalities between academic institutions. Moreover, we implement an empirical model to determine the extent to which the impact of internal and external collaborations on universities' performance is sensitive to the geographical dimension of the data.     

Volatility spillovers between WTI and Brent spot crude oil prices: an analysis of granger causality in variance patterns over time

There has been an increase in price volatility in oil prices during and since the global financial crisis (GFC). This study investigates the Granger causality patterns in volatility spillovers between West Texas International (WTI) and Brent crude oil spot prices using daily data. We use Hafner and Herwartz’s (2006) test and employ a rolling sample approach to investigate the changes in the dynamics of volatility spillovers between WTI and Brent oil prices over time. Volatility spillovers from Brent to WTI prices are found to be more pronounced at the beginning of the analysis period, around the GFC, and more recently in 2020. Between 2015 and 2019, the direction of volatility spillovers runs unidirectionally from WTI to Brent oil prices. In 2020, however, a Granger-causal feedback relation between the volatility of WTI and Brent crude oil prices is again detected. This is due to the uncertainty surrounding how the COVID-19 pandemic will evolve and how long the economies and financial markets will be affected. In this uncertain environment, commodities markets participants could be reacting to prices and volatility signals on both WTI and Brent, leading to the detection of a feedback relation.     

Is it U.S. GAAP or IFRS? Understanding how R&D costs affect ratio analysis

While financial reporting standards under U.S. GAAP and IFRS are fundamentally similar, differences do exist that may affect our analysis of company financial statements. This is particularly true when comparing a U.S. company following U.S. GAAP to a firm that uses IFRS. To illustrate, we compare research and development (R&D) accounting methods under both sets of standards and illustrate how they affect the analysis of financial results of firms in a specific industry—automotive manufacturers. Our results provide insight into settings in which differences in R&D accounting may have the greatest impact on financial analysis.     

Machine Learning and Expert Judgement: Analyzing Emerging Topics in Accounting and Finance Research in the Asia–Pacific

In this paper, we focus on the question to what extent machine learning (ML) tools can be used to support systematic literature reviews. We apply a ML approach for topic detection to analyze emerging topics in the literature—our context is accounting and finance research in the Asia–Pacific region. To evaluate the robustness of the approach, we compare findings from the automated ML approach with the results from a manual analysis of the literature. The automated approach uses a keyword algorithm detection mechanism whereby the manual analysis uses common techniques for qualitative data analysis, that is, triangulation between researchers (expert judgement). From our paper, we conclude that both methods have strengths and weaknesses. The automated analysis works well for large corpora of text and provides a very standardized and non-biased way of analyzing the literature. However, the human researcher is potentially better equipped to evaluate current issues and future trends in the literature. Overall, the best results might be achieved when a variety of tools are used together.     

跨国公司技术联盟:动因、效应及启示

跨国公司技术联盟是在经济全球化与一体化的国际背景下发展起来的，它被愈来愈多的人认为是一种知识联盟，是一种独立的组织形式。跨国公司进行技术联盟的动因在于：获取与企业核心技术相关的上下游技术、适应网络竞争的需要及促进研究与开发等。跨国公司技术联盟既给合作方带来一定的积极效应，同时也产生相当的负面影响。在当前，跨国公司技术联盟对我国企业进行技术联盟与合作有积极的借鉴意义。     

International Economies of Scale and the Gains from Trade

In this paper, we present a two-country trade model with external economies of scale that emerge on an international level but are partially localized in each country. First, we show that the larger country exports the good produced in an industry with external economies of scale in the trading equilibrium. Second, we investigate the welfare effects of trade for the following two cases: (I) the case where external economies are completely localized in autarky; (II) the case where external economies are internationally effective in autarky. In case (II), it is shown that trade can be welfare-decreasing for both countries.     

Researching with whom? Stability and manipulation

This paper explores the existence of stable research teams, when the preferences of each agent depend on the set of researchers who are collaborating. We introduce a property over researchers’ preferences, called top responsiveness, guaranteeing the existence of stable research teams configurations. We also provide a stable mechanism, induced by the so-called top covering algorithm, which is strategy-proof when researchers preferences satisfy top responsiveness. Furthermore, we find that, in this framework, the top covering mechanism is the only strategy-proof mechanism that always selects stable allocations.     

Multinational Companies,Technology Spillovers and Plant Survival*

How does the presence of multinational companies affect plant survival in the host country? We postulate that multinational companies can impact positively on plant survival through technology spillovers. We examine the nature of the effect of multinationals using a Cox proportional hazard model, which we estimate using plant‐level data for Irish manufacturing industries. Our results show that the presence of multinationals has a life‐enhancing effect only on indigenous plants in high‐tech industries, suggesting the presence of technology spillovers. In contrast, multinationals compete with each other in low‐tech sectors in the host country.     

A Cross‐national Comparison of R&D Expenditure Decisions: Tax Incentives and Financial Constraints*

We provide evidence on the impact of tax incentives and financial constraints on corporate R&D expenditure decisions. We contribute to extant research by comparing R&D expenditures in the United States and Canada, thereby exploiting the differences in the two countries' R&D tax credit mechanisms and generally accepted accounting principles. The two tax incentive mechanism designs are consistent with differing views of the degree of financial constraints faced by firms in these economies. Our sample also allows us to explore the effects of capitalizing R&D on Canadian firms. Employing a matched design, we document relations between tax credit incentives and R&D spending consistent with both Canadian and U.S. public companies responding as though they are not financially constrained. We estimate that the Canadian credit system induces, on average, $1.30 of additional R&D spending per dollar of taxes forgone while the U.S. system induces, on average, $2.96 of additional spending. We also find that firms that capitalize R&D costs in Canada spend, on average, 18 percent more on R&D. Collectively, this evidence is important to the ongoing debates in both countries concerning the appropriate design of incentives for R&D and is consistent with the assumptions found in the U.S. tax credit system, but not those found in the Canadian system.