Analysis of the Efficacy of Public Spending on Research and Development in State Programs

This paper presents an approach to assessing the efficacy of public spending on research and development in state programs. At present, there is a need to develop a unified approach to the analysis and evaluation of the efficacy of such spending from the perspective of participants in state programs (federal executive bodies). The proposed approach does not allow evaluating the efficacy of public spending on the development of research areas assigned to the authors.     

Introduction to the policy articles on Trump to Biden: Implications for Canadian Agriculture

President Biden was sworn in on January 20, 2021 after a 4‐year term by President Trump. Certainly, Trump's norm breaking presidency impacted Canada in significant ways and the agricultural sector was no exception. In this issue, we have a set of four short articles discussing the possible implications on Canadian agriculture of transitioning from a Trump to Biden presidency. Issues related to Canada‐U.S. agricultural trade, political norms and uncertainty, U.S. domestic support, participation in trade agreements, and U.S.‐China relations are all considered.     

Interorganisational project dynamics: A longitudinal study of perceptual distance and client-contractor collaborative relationships

Despite the importance of good collaborative relationships in interorganisational projects, clients and contractors often develop adversarial relationships due to perceptual distance about key project issues. In this case study research, we investigated how perceptual distance emerges and changes over time, and how the collaborative relationship between client and contractor develops alongside these dynamics. In this exploration, we built upon agency theory and stewardship theory as complementary perspectives for understanding client-contractor collaborative relationships. We gathered quantitative and qualitative data in two projects, conducting three assessments in about one year. We found that perceptual distance increased and decreased over time, and that a reduction was typically associated with the collaborative relationship being characterized by stewardship rather than agency. These findings suggest that a regular assessment and evaluation of partners’ perceptions of critical project issues is warranted to timely detect and counteract perceptual distance. Moreover, partners would best adopt a stewardship orientation to reduce perceptual distance, although this may take considerable effort given the distributive nature of many pre-project negotiations.     

Shareholder Activism and Voluntary Disclosure Initiation: The Case of Political Spending

Demand for disclosures on environmental, social, and governance (ESG) issues has increased dramatically. Using corporate political spending disclosures as our setting, we conduct a detailed inquiry of 541 political spending‐related shareholder proposals from 2004 to 2012 to highlight the role of shareholder activism as a mechanism to motivate ESG disclosure. Unlike earlier studies, we examine both proposals that went to a vote and proposals that were withdrawn by the activist, allowing us to assess more comprehensively the success of shareholder activism. We find that 20 percent of firms targeted by disclosure proposals begin disclosing in the subsequent year, although implementation rates vary by proposal type—8 percent for proposals subject to a vote versus 56 percent for proposals withdrawn. The sponsor is also important: unions and public pension funds are less likely than other activists to target firms with agency problems and are less successful in having proposals withdrawn, and the implementations they obtain are viewed more negatively by the broader investor base. Our findings highlight shareholder proposals as one mechanism through which investors can successfully express their preferences for corporate disclosure policies. Given activists' long‐standing interest in environmental and social disclosure policies, we believe our findings generalize to a broader set of ESG disclosures.     

Machine learning for financial transaction classification across companies using character-level word embeddings of text fields

An important initial step in accounting is mapping financial transfers to the corresponding accounts. We devised machine-learning-based systems that automate this process. They use word embeddings with character-level features to process transaction texts. When considering 473 companies independently, our approach achieved an average top-1 accuracy of 80.50%, outperforming baselines that exclude the transaction texts or rely on a lexical bag-of-words text representation. We extended the approach to generalizes across companies and even across different corporate sectors. After standardization of the account structures and careful feature engineering, a single classifier trained on 44 companies from 28 sectors achieved a test accuracy of more than 80%. When trained on 43 companies and tested on the remaining one, the system achieved an average performance of 64.62%. This rate increased to nearly 70% when considering only the largest sector.     

Stock market volatility forecasting: Do we need high-frequency data?

The general consensus in the volatility forecasting literature is that high-frequency volatility models outperform low-frequency volatility models. However, such a conclusion is reached when low-frequency volatility models are estimated from daily returns. Instead, we study this question considering daily, low-frequency volatility estimators based on open, high, low, and close daily prices. Our data sample consists of 18 stock market indices. We find that high-frequency volatility models tend to outperform low-frequency volatility models only for short-term forecasts. As the forecast horizon increases (up to one month), the difference in forecast accuracy becomes statistically indistinguishable for most market indices. To evaluate the practical implications of our results, we study a simple asset allocation problem. The results reveal that asset allocation based on high-frequency volatility model forecasts does not outperform asset allocation based on low-frequency volatility model forecasts.     

Demographics,personality, contact,and universal‐diverse orientation: An exploratory examination

This study explores relationships between race, gender, agreeableness, openness to experience, contact, and a measure of attitudes toward diversity—universal‐diverse orientation (UDO). UDO consists of three attitudinal components: realistic appreciation (a cognition), comfort with difference (a feeling), and diversity of contact (a behavior). Results suggest that race, agreeableness, and openness relate to UDO attitudes, primarily due to the relationships of these variables with the behavioral component—diversity of contact. Identifying characteristics of tolerant people (e.g., agreeableness) and training managers in skills related to those characteristics may improve contextual performance and make managers better role models within the organizational context. © 2003 Wiley Periodicals, Inc.     

Self‐help in housing and chengzhongcun in China's urbanization

This article focuses on the housing issues of rural migrants arising from urbanization, with particular reference to chengzhongcun, a topic with considerable impact on policymaking. An attempt is made to understand the underlying rationale of self‐help in housing and the important role of chengzhongcun in sheltering rural migrants in the context of China's rural‐urban dichotomy. As demonstrated in this study, chengzhongcun accommodate, with little in the way of government resources and assistance, millions of rural migrants because of their social accessibility and affordability. While not denying their social problems, we argue that chengzhongcun in fact act as an innovative and positive agent to promote urbanization in present day China by housing massive numbers of rural migrants and assimilating them into cities. Current government policies towards chengzhongcun have generated a wide range of interest conflicts and confrontations. The consequences of such conflicts show that the government policies were problematic and unworkable, as they violated basic market principles as well as citizen rights. Policy strategy towards the redevelopment of chengzhongcun must acknowledge their credibility in the Chinese road to urbanization and requires more thoughtful and prudent consideration of migrants' demands for affordable housing.     

Density estimation in the uniform deconvolution model

We consider the problem of estimating a probability density function based on data that are corrupted by noise from a uniform distribution. The (nonparametric) maximum likelihood estimator for the corresponding distribution function is well defined. For the density function this is not the case. We study two nonparametric estimators for this density. The first is a type of kernel density estimate based on the empirical distribution function of the observable data. The second is a kernel density estimate based on the MLE of the distribution function of the unobservable (uncorrupted) data.