Lopsided inclusion: The impact of multi-employer bargaining and class-based unionism on non-regular employment in South Korea

This study examines the impact of multi-employer bargaining on non-regular workers across different unions and types of non-regular employment. Using national representative survey data from South Korea, I find that multi-employer bargaining increases the likelihood that a workplace union would address a pay increase for non-regular workers when the union was affiliated with a confederation espousing class-based as opposed to business-unionism. However, such a relationship was weaker for temporary agency workers and subcontractors than for direct-hire fixed-term workers. This mechanism is further illustrated through a second round of data collection and analysis, namely in-depth interviews. I identify two factors that characterize the class-based confederation: (1) centralized pressure from the union and (2) activists and their identity work. Altogether, these results further an understanding of how the identities of national union confederations can influence local representatives’ approach to representing non-regular workers and how those influences are manifested through workplace-level collective bargaining.     

Asymmetric Loss and the Rationality of Inflation Forecasts: Evidence from South Korea

We examine asymmetry in the loss functions of South Korean consumers' and the Bank of Korea's (BOK) inflation forecasts, and test the rationality of these forecasts under the assumption of a possible asymmetric loss function. Under an asymmetric loss function, we find evidence of asymmetry and support for rationality. We also examine whether the BOK's forecasts incorporate respective forecasts and consensus forecasts efficiently. They broadly use available information efficiently, and their results are robust to inflation‐targeting measures and the recent global financial crisis. However, our results suggest that the information efficiency of the BOK's forecasts for consumers was affected during the period 2007–2008.     

Environmental regulations in private and mixed duopolies: Taxes on emissions versus green R&D subsidies

In this article, we compare two kinds of environmental regulations—emissions taxes and green R&D subsidies—in private and mixed-duopoly markets in the presence of R&D spillovers. We show that a green R&D subsidy is better (worse) than an emissions tax when the green R&D is efficient (inefficient), irrespective of R&D spillovers, whereas the existence of a publicly owned firm encourages the government to adopt a subsidy policy. We also show that the optimal policy choice depends on R&D efficiency and spillovers. In particular, when green R&D is inefficient and the spillover rate is low (high), the government should choose an emissions tax and (not) privatize the state-owned firm. When green R&D is efficient, however, an R&D subsidy is better, but a privatization policy is not desirable for society, irrespective of spillovers.     

Household Determinants of the Adoption of Improved Cassava Varieties using DNA Fingerprinting to Identify Varieties in Farmer Fields: A Case Study in Colombia

We examine factors affecting the adoption of improved cassava varieties of 217 households in the Cauca Department in southwest Colombia. Using DNA fingerprinting through Single Nucleotide Polymorphisms (SNPs), we identified different cultivars in farmers fields. We also used this information to remove possible bias in the adoption model that could have resulted from a misclassification of improved varieties (IVs). As a result, we found that farmers substantially overestimate their use of IVs and there are important differences in the determinants of adoption between farmer self‐identification and DNA fingerprinting. This finding implies that the incorporation of DNA fingerprinting in IV adoption studies is important to ensure the accuracy of future agricultural economic research and the relevance of subsequent policy recommendations.     

Building relationship innovation in global collaborative partnerships: big data analytics and traditional organizational powers

This study examines how relationship innovation can be developed in global collaborative partnerships (alliances, joint ventures, mergers, and acquisitions). The recently emerging theory of big data analytics linked with traditional organizational powers has attracted a growing interest, but surprisingly little research has been devoted to this important and complex topic. Therefore, after developing the theoretical foundations, our study empirically quantifies the links between the theoretical constructs based on the data collected from chief executive officers, managing directors, and heads of departments who work in contemporary global data‐and‐information driven collaborative partnerships. The results from structural equation modeling indicate that the relationship innovation depends on the power of big data analytics and non‐mediated powers (NMP, expert and referent). The power of big data analytics also mediates the correlation between NMP and relationship innovation. However, mediated powers (coercive and manipulative) negatively affect the power of big data analytics and relationship innovation. The interaction effects further depict that analytically powered partnerships have better relationship innovation compared with those which focus less on the analytical power. Consequently, the contributions of this study provide a deeper understanding of mechanisms of how modern collaborative partnerships can use big data analytics and traditional organizational powers to co‐create relationship innovation.     

Policy Uncertainty and the Dual Role of Corporate Political Strategies

Firms use active political strategies not only to mitigate uncertainty emanating from legislative activity, but also to enhance their growth opportunities. We find that a firm's systematic risk (beta) can be hedged away by employing various political strategies involving the presence of former politicians on corporate boards of directors, contributions to political campaigns, and corporate lobbying activities. The hedging effect is greater when firms operate in more uncertain industries. In addition, active political strategies are associated with greater firm heterogeneity and make real options more value relevant as potential drivers of competitive advantages in uncertain environments.     

Target‐Setting,Pay for Performance,and Quality Improvement: A Case Study of Ontario Hospitals’ Quality‐Improvement Plans

This study examines whether difficult targets and quality indicators in executives' pay‐for‐performance (P4P) plans affect performance. The impact of target‐setting and P4P plans on quality improvement in the public sector is unclear. The Ontario government initiated the Quality Improvement Plan (QIP), which requires hospitals to set targets for quality indicators annually and link executive pay to target achievement since 2011. Analyzing Health Quality Ontario's database and hospitals' 2012–2013 QIPs, this study shows greater quality improvement in hospitals with difficult targets than hospitals with easy targets or without assigned targets; however, the positive impact disappears for high‐performance hospitals relative to their peers. We find no significant effect of the use of quality indicators in executives' P4P plans on quality improvement. Copyright © 2018 ASAC. Published by John Wiley & Sons, Ltd.     

Does Institutional Blockholder Short‐Termism Lead to Managerial Myopia? Evidence from Income Smoothing

We examine institutional blockholders’ influence on income‐smoothing practices in the Korean market, which provides an interesting setting where family‐oriented chaebols dictate the corporate landscape and impede shareholder activism. The empirical results reveal that institutional shareholders with a short‐term (long‐term) investment horizon facilitate (constrain) managerial myopia. This positive (negative) association is most evident among firms with domestic institutional investors. Therefore, we argue that the presence of domestic institutional investors with transient investment goals incentivizes firms’ management to smooth out earnings.     

Time series copulas for heteroskedastic data

We propose parametric copulas that capture serial dependence in stationary heteroskedastic time series. We suggest copulas for first‐order Markov series, and then extend them to higher orders and multivariate series. We derive the copula of a volatility proxy, based on which we propose new measures of volatility dependence, including co‐movement and spillover in multivariate series. In general, these depend upon the marginal distributions of the series. Using exchange rate returns, we show that the resulting copula models can capture their marginal distributions more accurately than univariate and multivariate generalized autoregressive conditional heteroskedasticity models, and produce more accurate value‐at‐risk forecasts.