Spillovers from Multinationals to Heterogeneous Domestic Firms: Evidence from Hungary

Firms cluster their economic activities to exploit technological and informational spillovers from other firms. Spillovers from multinational firms can be particularly beneficial to firms in less developed economies, because technological superiority and management expertise of foreign multinational firms yield various opportunities for learning. Yet, the importance of foreign firms’ spillovers might vary with respect to two key features of domestic firms: their productivity level and their export status. In line with theories on the absorptive capacity of firms, we argue on the basis of an empirical analysis of Hungarian firms that larger and more productive firms are more able than smaller firms to reap spillovers from multinationals. However, the export status is found to be of minor importance once higher productivity is controlled for.     

COMPOSITE CORPORATE INCOME TAX

The federal, state, and local income tax rates can be combined into a single composite income tax rate. Such a composite tax rate significantly simplifies the consideration of income taxes in economic analyses. The composite tax rate can vary by as much as 6 percent from one state to another. Thus, managers should carefully consider the state and local income tax laws in their economic studies.     

The diffusion of technological innovation in the commercial banking industry

This paper examines the propensity of organizations to adopt technological innovations. Technological innovations evolve from the stock of skills which organizations have accumulated over time. Linkages with extramural sources of technology are presumed to be important as well. Hypotheses are tested on a sample of commercial banks. Findings show that prior experience in information technology, in tandem with a variety of interfirm linkages, will affect the banks' decision to adopt this innovation.     

Forecasting Inflation Using Constant Gain Least Squares

This paper assesses the usefulness of constant gain least squares when forecasting inflation. An out‐of‐sample forecast exercise is conducted, in which univariate autoregressive models for inflation in Australia, Sweden, the United Kingdom and the United States are used. The results suggest that it is possible to improve the forecast accuracy by employing constant gain least squares instead of ordinary least squares. In particular, when using a gain of 0.05, constant gain least squares generally outperforms the corresponding autoregressive model estimated with ordinary least squares. In fact, at longer forecast horizons, the root mean square forecast error is reliably lowered for all four countries and for all lag lengths considered in the study.     

Meta-analysis selection bias in marketing research

The tendency of meta-analytic authors to select particular studies is called selection bias. Selection bias can affect the strength of the meta-analytic estimate and the attention that scholars devote to the results. This research is, in effect, a meta-analysis of the effect sizes reported or calculated from 94 meta-analysis studies of various topics in marketing research. The analysis reveals that estimates depend on the publication status of the included studies. The greater the percentage of studies that were published in academic journals vs. non-published studies, the greater is the size of the meta-effects, and the more published studies from leading journals the meta-analysis includes, the stronger the effect size. The meta-analytic effect size is a mediator for the influence of both the ratio of unpublished studies and the ratio of studies from leading journals on the probability of a meta-analysis to be published in a leading journal, which increases the number of citations to a meta-analysis. The findings of this study have several implications for meta-analysts, editors, reviewers and the marketing community on how to conduct and read current and future meta-analysis in marketing research.     

Intellectual property rights,product complexity and the organization of multinational firms

This paper studies how the intellectual property right (IPR) regime in destination countries influences the decision of firms between procurement from related parties and from independent suppliers while the latter may involve technology sharing or not. Using firm‐level data on the mode choice for each transaction and a new product complexity measure, results confirm that firms are generally reluctant to source complex goods from outside firm boundaries. However, when technology is shared, IPRs promote outsourcing of more complex goods whereas without technology sharing, IPRs promote outsourcing of less complex products that are prone to reverse engineering and simpler to imitate.     

Customers’ Preferences for Different Processed Tomato Categories in Food Service

Hypothetical discrete choice experiments were conducted to elicit food-service professionals’ preferences and willingness-to-pay for different attributes of processed tomatoes. A sample of 110 food-service professionals were surveyed in Italy, Russia, Eastern Europe, and South Korea in 2012. Data were analyzed by using multinomial logit and random parameter logit models. Results suggest that food-service professionals preferred peeled tomatoes to chopped pulp, tomato purée, and tomato paste. However, their preferences were heterogeneous. They would pay a premium price for products labeled with Italian origin. Types of cuisine sold by practitioners, numbers of points of sale, and nationalities also influence practitioners’ WTP. Factors affecting their purchasing decision were freshness of product, followed by convenience, cooking time, price, origin of product, and brand. This study shows that the research method is suitable for evaluating the preferences of food-service professionals. The preferences of industry operators resemble those of consumers.     

Market Moods and Network Dynamics of Stock Returns: The Bipolar Behavior

The authors show that a simple mood-separable preference in a network study of stock returns captures a variety of stylized facts regarding stocks’ provisional (ab)normal behavior. These behaviors are articulated in a multistate complete Euclidean network model that specifies the existence, direction, and magnitude of a self-organized dynamics for each individual stock during abnormal market moods. In the empirical setting, the authors apply suggested model along with 2 established visual approaches (multidimensional scaling and agglomerative hierarchical clustering) for benchmark purposes. Results reveal different levels of erratic return dynamics for each stock and the entire market in different abnormal market moods. The authors model and interpret these self-organized dynamics as evidence of stocks’ and market’s bipolar behavior.     

Nonparametric estimates of productivity and efficiency change in Australian Broadacre Agriculture

This paper computes and decomposes Färe‐Primont indexes of total factor productivity of Australian broadacre agriculture by estimating distance functions. Using state‐level data from 1990 to 2011, the empirical results show that TFP grew at an average rate of 1.36 per cent per annum in the broadacre agriculture over the period 1990–2011. There are variations of total factor productivity (TFP) growth across states and fluctuations over time within each state and territory. However, overall, there is a clear movement towards slower TFP growth across the sample period. Further decomposition of TFP growth shows that it is declining growth in technical possibilities (technological progress) that is the main driver of the declining trend in productivity growth in broadacre agriculture in Australia.     

Chief executive officer attributes,sustainable performance,environmental performance,and environmental reporting: New insights from upper echelons perspective

This study examines the impact of chief executive officer (CEO) attributes on sustainable performance, environmental performance, and environmental reporting, which are motivated by institutionally driven environmental policies, regulations, and management in the context of Chinese listed firms. With the use of a comprehensive dataset of 2,854 Chinese listed firms over the 2010–2017 period (i.e., making over 16,000 individual firm‐year observations), our findings are fourfold. First, our overall findings reveal that CEOs with research background tend to engage more in activities that improve sustainable performance, environmental performance, and environmental reporting than do those without research background. Second, CEOs with financial expertise are positively linked with increased sustainable performance and environmental reporting. Third, CEOs with foreign exposure are more eager to engage in activities that enhance sustainable and environmental performance than do those without foreign exposure. Fourth, young CEOs tend to take actions that reduce both sustainable and environmental performance than do their older counterparts. We interpret our results within upper echelons theoretical perspective. The results are robust to alternative measures, potential endogeneities, and sample selection problems.