Auditors' Fee Premiums and Low‐Quality Internal Controls*

We examine the relation between low‐quality internal controls and audit fee premiums. Using a novel data set of audit hours and audit fees we find, consistent with the audit risk model, that auditors increase their effort (hours) owing to low internal control quality. We find that auditors also charge a significant fee premium to clients with internal control weaknesses. This premium is observed for severe internal control weaknesses and companies with low‐quality alternative governance mechanisms. The results are robust to multiple methods to address endogeneity, including company fixed effects, difference‐in‐differences design, and a propensity score‐matched sample. Taken as a whole, low internal control quality leads to fee premiums, which are a deadweight loss to client companies.     

Explaining import quality: The role of the income distribution

We examine a generalized version of Flam and Helpman [Flam, H., Helpman, E., 1987. Vertical Product Differentiation and North-South Trade. American Economic Review, 77, 810-822.] in which consumption prices for quality differentiated goods are rising in household income. We provide propositions for aggregating this relationship across heterogenous households to map cross-country differences in income distributions to cross-country differences in import price distributions. The theoretical predictions are examined and confirmed using disaggregated data on prices of traded goods and micro data on household income from the Luxemburg Income Study. Country pairs with more similar income distributions have more similar import price distributions, whether similarity is measured by 1st-4th moment statistics, population and consumption shares within world income and product price quantiles, or income and price dis-similarity indices.     

ROBOT–BRAND FIT THE INFLUENCE OF BRAND PERSONALITY ON CONSUMER REACTIONS TO SERVICE ROBOT ADOPTION

Marketing Letters - Can every brand benefit from adopting service robots? To tackle this important question, we examined the interactive effects of brand personality (sincere vs. exciting) and...     

Temporal Orientation and Corporate Social Responsibility: Global Evidence

There has been a growing emphasis on the importance of a long-term perspective in academia and practice. Yet understanding of the interdependency of those factors – the temporal preferences embedded in organizations and in societal values as well as the influence of temporal orientation of investors – remains limited. We theorize whether and how a firm's corporate social responsibility (CSR) is affected by the societal temporal orientation, its time horizon, and its investors' time horizon. Using a global sample, we confirm that CSR activity is higher when a country has a long-term orientation culture, when the firm has a long-time horizon, and when the controlling institutional investor has a long-term investment horizon. We also find that the national culture's long-term orientation heightens the effect of a firm's long-time horizon on its CSR. Further, our results show that the effects of temporal orientation are more pronounced in environmental than in social CSR.     

Trade diversion effects of the US–China trade war on Vietnam

This paper empirically examines the US–China trade war that began in mid-2018, focusing on the impact on a third country, Vietnam. Using regression analysis, we found that while the trade war had a negative impact on US imports from China for all targeted products, there was a partial offset from increased imports from other countries. Notably, US imports from Vietnam experienced a sharp increase, particularly after the third round of US import tariffs on Chinese goods. Additionally, our research reveals that the four rounds of tariff escalation affected US imports from China differently depending on their end-use and technology intensity.     

Weak‐instrument robust inference for two‐sample instrumental variables regression

Instrumental variable (IV) methods for regression are well established. More recently, methods have been developed for statistical inference when the instruments are weakly correlated with the endogenous regressor, so that estimators are biased and no longer asymptotically normally distributed. This paper extends such inference to the case where two separate samples are used to implement instrumental variables estimation. We also relax the restrictive assumptions of homoskedastic error structure and equal moments of exogenous covariates across two samples commonly employed in the two‐sample IV literature for strong IV inference. Monte Carlo experiments show good size properties of the proposed tests regardless of the strength of the instruments. We apply the proposed methods to two seminal empirical studies that adopt the two‐sample IV framework.     

Corroborating social media echelon in cancer research

Worldwide medical facilities differ, and for this reason, the causes of death can vary. Cancer is considered the second leading cause of death after heart disease worldwide, and the same causes of death are observed in the United States (US). Therefore, the purposes of this study are to explore worldwide research levels in the field of cancer and the social collaboration of researchers and institutions in this field. This article examines the structural patterns of international co-authors and co-institutions in science citation index papers in cancer research. The study uses measures from the social network analysis method, including degree centrality, betweenness centrality, eigenvector centrality, and effectiveness, to investigate the effects of social networks in the area of cancer research. Empirical analysis results identify the US is the most central country, followed by Germany, Italy, France, and China, in terms of co-authored networks in this research field. Institutional analysis results indicate that the University of Milan is at the top in terms of degree centrality. The Gustave Roussy Cancer Campus in France and German University of Düsseldorf occupy the second and fourth positions, respectively. The University of California in Los Angeles and Harvard University, both in the US, are at third and fifth positions, respectively.     

Hyperbolic normal stochastic volatility model

For option pricing models and heavy-tailed distributions, this study proposes a continuous-time stochastic volatility model based on an arithmetic Brownian motion: a one-parameter extension of the normal stochastic alpha-beta-rho (SABR) model. Using two generalized Bougerol's identities in the literature, the study shows that our model has a closed-form Monte Carlo simulation scheme and that the transition probability for one special case follows Johnson's distribution—a popular heavy-tailed distribution originally proposed without stochastic process. It is argued that the distribution serves as an analytically superior alternative to the normal SABR model because the two distributions are empirically similar.     

Value at risk forecasting for volatility index

Forecasts of values at risk (VaRs) are made for volatility indices such as the VIX for the US S&P 500 index, the VKOSPI for the KOSPI (Korea Stock Price Index) and the OVX (oil volatility index) for crude oil funds, which is the first in the literature. In the forecasts, dominant features of the volatility indices are addressed: long memory, conditional heteroscedasticity, asymmetry and fat-tails. An out-of-sample comparison of the VaR forecasts is made in terms of violation probabilities, showing better performance of the proposed method than several competing methods which consider the features differently from ours. The proposed method is composed of heterogeneous autoregressive model for the mean, GARCH model for the volatility and skew-t distribution for the error.     

An SAO‐based text‐mining approach for technology roadmapping using patent information

A technology roadmap (TRM) links technologies with a company's strategic objectives and so supports acquisition of required technologies in advance of needs. It is a powerful tool for strategic planning and technology management. Because technology is changing rapidly and market competition is fierce, the role of a TRM is becoming increasingly important. To support the role of a TRM, many firms and governments that use roadmapping are becoming interested in reducing costs while retaining objectivity during TRM development. One suggestion to achieve these goals is to use the keyword‐based quantitative approach to creating a TRM, but the information provided by the approach is limited because of the characteristics of keyword information. To solve this limitation, this research uses the concept of ‘function’ to support quantitative analysis for developing a TRM. The concept of function can provide information on the uses and purposes of a technology. To represent a function, a subject–action–object structure is commonly used. The suggested approach allows research and development (R&D) managers to extend the views of product and technology during development of a TRM. In addition, by reducing the time required to develop a TRM, the proposed approach supports quick and accurate decision‐making by R&D managers.