Assessing information integration processes: a comparison of findings obtained with between-subjects designs versus within-subjects designs

Quality & Quantity - Within-subject designs (WSDs) remain unpopular in psychology. Social psychologists have argued that they create “demand” and “order” effects....     

Capital gains lock-in and governance choices

Differences in accrued gains and investors’ tax-sensitivity induce variation in a capital gains lock-in effect across mutual funds even for the same stock at the same time. Exploiting this variation, we show this effect influences funds’ governance decisions: higher capital gains decrease the likelihood a fund exits prior to contentious votes and increase the likelihood a fund votes against management. Consistent with tax motivation, these findings are concentrated among funds with tax-sensitive investors. Further, high aggregate capital gains across funds holding a stock predict a higher likelihood management loses a vote and a lower likelihood a contentious vote is proposed.     

Testing Part of a DSGE Model by Indirect Inference

We propose a way of testing a subset of equations of a DSGE model. The test draws on statistical inference for limited information models and the use of indirect inference to test DSGE models. Using the numerical small sample distribution of our test for two subsets of equations of the Smets–Wouters model we show that the test has accurate size and good power in small samples, and better power than using asymptotic distribution theory. In a test of the Smets–Wouters model on US Great Moderation data, we reject the specification of the wage‐price but not the expenditure sector. This points to the wage‐price sector as the source of overall model rejection.     

Co-movement in Stock Prices in Emerging Economies: The Case of the Caricom Region

The Grand Anse Declaration of 1989 recognised the need for financial integration within the emerging economies that comprise the CARICOM region, as a way of furthering the wider process of economic integration and, indeed, economic development in that region. Using co-movement as a measure of financial integration, this paper investigates the co-movement in stock prices among the Barbados, the Jamaica and the Trinidad and Tobago Stock Exchanges, the three major exchanges within the CARICOM region. It also examines how integrated these exchanges are with the New York Stock Exchange. The GARCH-Copula methodology and, to a lesser extent, estimated correlation coefficients, are used to attain this objective. There appears to be co-movement in stock prices and returns within the CARICOM stock markets and significant dependence structures between the returns of the three CARICOM stock markets. However, there is considerably less evidence of integration between the CARICOM markets and the New York Stock Exchange.     

Environmental Policy,Sustainable Development,Governance Mechanisms and Environmental Performance

We investigate the effects of environmental policy (Climate Change Act – CCA), sustainable development frameworks (Global Reporting Initiative – GRI; UN Global Compact – UNGC) and corporate governance (CG) mechanisms on environmental performance (carbon reduction initiatives – CRIs; actual carbon performance – GHG emissions) of UK listed firms. We use the generalized method of moments (GMM) estimation technique to analyse data consisting of 2245 UK firm‐year observations over the 2002–2014 period. First, we find that the CCA has a positive effect on CRIs, and this effect is stronger in better‐governed firms. Second, we find that the GRI‐based framework is positively associated with CRIs. Third, we find that firms with poor CG structures have lower actual carbon performance compared with their better‐governed counterparts. Overall, our evidence suggests that firms can symbolically conform to environmental policy (CCA) and sustainable development frameworks (GRI, UNGC) by engaging in CRIs without necessarily improving actual environmental performance (GHG emissions) substantively. Copyright © 2017 John Wiley & Sons, Ltd and ERP Environment     

Blockchain in Additive Manufacturing and its Impact on Supply Chains

Additive manufacturing (AM) appears to be a particularly attractive use case for blockchain. This research combines inductive in‐depth interviews with the Delphi method to explore what potentials blockchain technology in AM creates, which adoption barriers firms need to overcome, and how supply chains will be affected by the integration of these two potentially disruptive technologies. The results suggest opportunities that are related to intellectual property (IP) rights management, the monitoring of printed parts throughout their lifecycle, process improvements, and data security. The most important barriers for blockchain adoption in AM are an absence of blockchain‐skilled specialists on the labor market, missing governance mechanisms, and a lack of firm‐internal technical expertise. By addressing important limitations of AM, blockchain is expected to improve the competitiveness of AM in parts’ production, catalyzing the trend toward more decentralized manufacturing resulting in more agile, resilient, and flexible supply chains and reduced logistics costs. Beyond that, blockchain‐based AM platforms are expected to enhance supply chain visibility, drive supply chain digitalization, support supply chain finance, and contribute to the emergence of shared factory systems.     

Outward foreign direct investment by Polish state-owned multinational enterprises: is ‘stateness’ an asset or a burden?

State-owned enterprises (SOEs) are commonly associated with undue advantages due to preferential treatment by the state. Simultaneously they are often quoted as handicapped given the notorious state interference, management problems and agency tensions. They used to be regarded as a mainly domestic issue but in the context of globalisation and the fact that states enter treaties with new obligations, SOEs’ performance ceased to be solely a domestic problem, increasingly so as state-owned multinational enterprises (SOMNEs) emerge. This article presents the results of research on Polish SOEs’ outward foreign direct investment (OFDI). It offers an overview of overseas activities of nine major Polish firms with a state stake and aims to contribute to the conceptual literature on foreign investments conducted by SOMNEs. We distinguish between FDI by SOMNEs as specific – privileged (facilitated) or discriminated (hampered) – investments subject to the home country’s state power and the host country’s state perception.     

The Politics of Inequality as Organised Spectacle: Why the Swiss Do Not Want to Tax the Rich

In 2015, Swiss voters had the opportunity to impose a tax on the super rich in a popular vote and thereby fund a redistributive policy. However, a large majority voted against its seemingly obvious self-interest and rejected the tax. We propose an explanation for this puzzling outcome, bridging the usually separate behavioralist and institutionalist perspectives on the politics of inequality. We start from the observation that political economy tends to neglect processes of preference formation. Theorising preferences as socially constructed, we show that interest groups played a major role in shaping the outcome of the vote. Business frames were multiplied through allied parties and the media and had a major impact on individual voting behaviour. In addition, we demonstrate that interest groups representing business interests derive the content of their communication from business’s structurally privileged position in the capitalist economy. Specifically, creating uncertainty about possible perverse effects of government policies on jobs and growth is a powerful tool to undermine popular support. Frames based on this structural power ultimately explain why the Swiss refrained from ‘soaking the rich.’     

A multivariate distance nonlinear causality test based on partial distance correlation: a machine learning application to energy futures

This paper proposes a multivariate distance nonlinear causality test (MDNC) using the partial distance correlation in a time series framework. Partial distance correlation as an extension of the Brownian distance correlation calculates the distance correlation between random vectors X and Y controlling for a random vector Z. Our test can detect nonlinear lagged relationships between time series, and when integrated with machine learning methods it can improve the forecasting power. We apply our method as a feature selection procedure and combine it with the support vector machine and random forests algorithms to study the forecast of the main energy financial time series (oil, coal, and natural gas futures). It shows substantial improvement in forecasting the fuel energy time series in comparison to the classical Granger causality method in time series.