Persistence,mean reversion and non-linearities in the US housing prices over 1830–2013

The objective of this study is to provide a direct estimate of the degree of persistence of measures of nominal and real house prices for the US economy, covering the longest possible annual sample of data, namely 1830–2013. The estimation of the degree of persistence accommodates for non-linear (deterministic) trends using Chebyshev polynomials in time. In general, the results show a high degree of persistence in the series along with a component of non-linear behaviour. In general, if we assume uncorrelated errors, non-linearities are observed in both nominal and real prices, but this hypothesis is rejected in favour of linear models for the log-transformation of the data. However, if autocorrelated errors are permitted, non-linearities are observed in all cases, and mean reversion is found in the case of logged prices, though given the wide confidence intervals, the unit root null hypothesis cannot be rejected in these cases.     

Does Interindustry and Intraindustry Information Help Predict Financial Distress?

This study investigates whether and how the accounting ratios of peer firms within the same industry (the industry peers) or firms within the industry of their customers (the downstream peers) help improve the predictability of sample firm financial distress. We document that the Z‐score factors of the companies with high correlation in stock returns help predict financial distress. The results show that accounting‐based ratios of the industry peers and the downstream peers enhance the accuracy of early warnings of financial distress, especially when prior returns of peer firms are highly correlated with the sample firm.     

Crowdsourcing and work: individual factors and circumstances influencing employability

The development of a fast and reliable Internet, new technologies online payment systems, and changes in work structure that enable and demand flexible working patterns have driven a move to a new form of Internet‐enabled labour exchange called crowdsourcing. Evidence from an in‐depth qualitative study is presented, focusing on selected users' interactions and experiences of working on two UK‐based crowdsourcing platforms. The paper shows that workers engaged in this form of labour exchange need to deploy existing employability skills and networks to effectively meet the challenges, and take advantage of the opportunities, that crowdsourcing presents. Individual factors and circumstances emerge as paramount for workers' continued engagement in this form of employment. Using selected components from an employability framework, the findings suggest that crowdsourcing can offer new pathways to practising skills and enhancing employability for some workers.     

Making sense of new technology during organisational change

This article examines how employees interpret the use of various social media and web 2.0 technologies by managers of an organisation during a merger process. The article explores the way in which managers use technology to give sense to the merger process, the corresponding sensemaking of employees and also how employees make sense of the use of technology itself. The findings show that new media enables the sharing of emotional sense about organisational processes between managers and employees and places employees with different levels of involvement with the process and at different points in the organisational hierarchy on equal footing. In spite of this, employees view the use of technology negatively and feel mastered by the technology itself. In discussing these unintended consequences of the use of this technology, the article further discusses the paradoxes that emerge from using new technology to give sense during organisational change.     

R&D Partnerships and Innovation Performance: Can There Be too Much of a Good Thing?

R&D collaboration facilitates the pooling of complementary skills, learning from the partner as well as the sharing of risks and costs. Research therefore stresses the positive relationship between collaborative R&D and innovation performance. Fewer studies address the potential drawbacks of collaborative R&D. Collaborative R&D comes at the cost of coordination and monitoring, requires knowledge disclosure, and involves the risk of opportunistic behavior by the partners. Thus, while for lower collaboration intensities the net gains can be high, costs may start to outweigh benefits if firms perform a higher share of their innovation projects collaboratively. For a sample of 2735 firms located in Germany and active in a broad range of manufacturing and service sectors, this study finds that increasing the share of collaborative R&D projects in total R&D projects is associated with a higher probability of product innovation and with a higher market success of new products. While this confirms previous findings on the gains for innovation performance, the results also show that collaboration has decreasing and even negative returns on product innovation if its intensity increases above a certain threshold. Thus, the relationship between collaboration intensity and innovation follows an inverted‐U shape and, on average, costs start to outweigh benefits if a firm pursues more than about two‐thirds of its R&D projects in collaboration. This result is robust to conditioning market success to the introduction of new products and to accounting for the selection into collaborating. This threshold is, however, contingent on firm characteristics. Smaller and younger as well as resource‐constrained firms benefit from relatively higher collaboration intensities. For firms with higher collaboration complexities in terms of different partners and different stages of the R&D process at which collaboration takes place, returns start to decrease already at lower collaboration intensities.     

Bond Pricing with a Time‐Varying Price of Risk in an Estimated Medium‐Scale Bayesian DSGE Model

New Keynesian model in which households have Epstein–Zin preferences with time‐varying risk aversion and the central bank has a time‐varying inflation target can match the dynamics of nominal bond prices in the U.S. economy well. The model generates a large steady‐state term spread and its fitting errors for bond yields are comparable to those obtained from a nonstructural three‐factor model, and one‐third smaller than in models with a constant inflation target or risk aversion. Including data on interest rates has large effects on variance decompositions, making investment technology shocks much less important than found in other recent papers.     

Product Market Competition,Monetary Policy Regimes and Inflation Dynamics: Evidence from a Panel of OECD Countries

We empirically analyze the impact of product market competition on the responsiveness of inflation to macroeconomic imbalances. If competition is high the response of inflation to lagged inflation, unemployment and import prices is reduced, while inflation is more responsive to changes in productivity growth in countries in which competition is above the OECD average. Given the (‘good luck’) macroeconomic trajectories of the 1990s–2000s, the structural reforms that made goods markets more competitive improved the ability of OECD economies to smooth (dis)inflationary shocks, while changes in the monetary policy framework had a modest role in taming inflation during the Great Moderation.     

Financial Sector Volatility,Banking Market Structure and Exports

This paper assesses the impacts of financial sector volatility and banking market structure on industrial exports. By utilising the specification of Rajan and Zingales (American Economic Review 1998; 88 , 559) on the cross‐country, cross‐industry data from Manova (Journal of International Economics 2008; 76 , 33), we find that financial sector volatility, measured as the standard deviation of the growth of private credit, and banking market structure, measured as the share of the three largest banks’ assets in a country, respectively exert significantly negative and positive impacts on industrial exports, particularly for those industries that are more externally financially dependent. The findings are robust to a variety of kinds of sensitivity analysis and thus lend support to the notion that a more stable and concentrated banking system is important to the exports of those industries that rely more on external finance.