Firms' Innovation,Public Financial Support,and Total Factor Productivity: The Case of Manufactures in Peru

Based upon an adjusted Crepon–Duguet–Mairesse (CDM) model, this paper analyzes the relationship between investment intensity, public financial support, innovation, and total factor productivity (TFP) for a sample of manufacturing firms of Peru with data obtained from the 2004 survey of science, technology, and innovation (STI) activities. The estimation of the model indicates that large firms are more likely to invest in STI activities and firms' size increases the probability of producing technological inovation (TI) and non‐technological innovation (NTI). STI firms' investment intensity and public financial support have also helped manufacturing firms to increase the probability of producing TI outcomes. Further, such support may have increased firms' investment on STI activities. The innovation effects on TFP, however, were statistically not clear or robust. Thus, whereas investment intensity did increase firms' TPF in low‐tech manufacturing firms, this is not the case for high‐tech firms. For this group of firms, relatively high capital–labor ratio and the availability of a high level of human capital seem to promote higher levels of TFP.     

FÜR SIE GELESEN

JOURNAL CLUB

FüR SIE GELESEN     

FÜR SIE GELESEN

JOURNAL CLUB

FüR SIE GELESEN     

What factors determine innovation performance in emerging economies? Evidence from China

Although the literatures on international trade, FDI and R&D have assisted significantly in improving our understanding regarding the determinants of innovation performance, there has been little research concerning the way in which each informs the other. Integrating theoretical developments from all three literatures, we propose and test a multidimensional conceptual framework that allows us to explain more fully what determines innovation performance in emerging economies. Testing the framework against a recently constructed industry-level dataset for China, the empirical analysis indicates that it has significant power in explaining variations in innovation performance. Nevertheless, our findings also show that factors such as international trade, FDI and R&D do not always have positive consequences. Rather, they indicate that their effects are moderated by technological opportunities and the level of foreign presence, implying that previous mixed findings regarding the role of international trade, FDI and R&D may be the result of incomplete theorizing about the factors that moderate the relationship between innovation performance and these factors.     

What is the optimal rate of R&D investment to maximize productivity growth?

Governments in modern economies devote much policy attention to enhancing productivity and continue to emphasize its drivers such as investment in R&D. This paper analyzes the relationship between productivity growth and levels of R&D investments. The econometric analysis shows that more than 65 per cent of productivity growth variance is due to its dependence on gross domestic expenditure on R&D expressed as percentage of GDP (GERD). Economic analysis shows that productivity growth = f(GERD) is a concave function downwards due to diminishing returns to research investments. In addition, the research shows that the range of GERD between 2.3 per cent and 2.6 per cent maximizes the long-run impact on productivity growth and it is the key to sustained productivity and technology improvements that are becoming more and more necessary to modern economic growth.     

The vicarious wisdom of crowds: toward a behavioral perspective on investor reactions to acquisition announcements

Although event‐study methodology is invaluable to strategic management research, we argue that the traditional financial economic rationale on which it is based has led scholars to assume away the behavioral mechanisms underlying investor reactions. Building on behavioral theory from management, psychology, and economics, we set out to develop a behavioral perspective on investor reactions to acquisition announcements—one that relaxes the assumption of investors making objective, rational‐deductive calculations. Given the information asymmetry they face, we theorize that investors (1) infer management's perception of an acquisition's synergistic potential from the premium it pays, and (2) draw on additional public information to assess the reliability of that perception. Using a multi‐industry sample of acquisitions by North American firms, we find considerable support for our behavioral framework. Copyright © 2012 John Wiley & Sons, Ltd.     

Multiple Internal Rate of Return Revisited: Frequency of Occurrences

Research in multiple internal rate of return (MROR) has mainly focused on three areas: uniqueness, conditions where MROR occur, and solutions to MROR. In an attempt to solve for MROR, researchers have assumed that the occurrence of MROR is prevalent and thus a solution is direly needed. This article examines the probability that positive MROR would occur when variation is incorporated into the cash flow and the probability of getting positive MROR when multiple sign-change cash flow is generated. Results show that the probability of positive MROR occurring in multiple sign-change cash flows is relatively low and potentially a rare event.     

A Comparison of Conjoint Analysis Response Formats

A split-sample design is used to evaluate the convergent validity of three response formats used in conjoint analysis experiments. We investigate whether recoding rating data to rankings and choose-one formats, and recoding ranking data to choose one, result in structural models and welfare estimates that are statistically indistinguishable from estimates based on ranking or choose-one questions. Our results indicate that convergent validity of ratings, ranks, and choose one is not established. In addition, we find that people frequently use "ties" in responses to rating questions, and that the option not to choose any of the alternatives ("opt-out") affects some preference estimates.     

Tourism demand for Italy and the business cycle

This study provides a strategy for modelling the effect of the business cycle on tourism demand under the rationale that tourism cycles are heavily influenced by lagged effects of the overall business cycle. Using quarterly data on overnight stays in Italian hotels, both domestic and inbound between 1985 and 2004, we adopt a structural time series approach to evaluate two alternative models, the first with a latent cycle component (LCC) and the second based on specific economic explanatory variables (XCV). The two models are compared in terms of explanatory power, best-fit, residual diagnostics and forecasting ability. The results show similar performances. The policy implication is that the XCV model can be used for calibrating countercyclical interventions in tourism policy.