Macroeconomic forecasting and structural change

The aim of this paper is to assess whether modeling structural change can help improving the accuracy of macroeconomic forecasts. We conduct a simulated real‐time out‐of‐sample exercise using a time‐varying coefficients vector autoregression (VAR) with stochastic volatility to predict the inflation rate, unemployment rate and interest rate in the USA. The model generates accurate predictions for the three variables. In particular, the forecasts of inflation are much more accurate than those obtained with any other competing model, including fixed coefficients VARs, time‐varying autoregressions and the naïve random walk model. The results hold true also after the mid 1980s, a period in which forecasting inflation was particularly hard. Copyright © 2011 John Wiley & Sons, Ltd.     

Accounting students’ choice of blended learning format and its impact on performance and satisfaction

Using online platforms to deliver educational content, some institutions have developed blended courses that combine the advantages of online instruction with traditional face-to-face (F2F) teaching. This study compares accounting student performance and satisfaction in two blended formats with similar content and design, i.e. F2F+ vs. Online+ courses. It also assesses the characteristics of students who choose the latter option over F2F+ courses. Students in four advanced accounting subjects were surveyed and their course performance was obtained. Results indicate that the main determinants of students’ decision to register for an Online+ course are retaking the course, increased weekly work hours, and belief that this type of blended course facilitates learning. Results show that students in advanced accounting courses with equivalent content and design perform similarly and have the same level of course satisfaction across course delivery formats, as hypothesized under equivalency theory.     

Simultaneous Adjustment of Quantities and Prices: An Example of Hamiltonian Dynamics

In a well-known essay first published in 1953, Goodwin analyzed the dynamic adjustment of quantities and prices to long-run equilibrium values, in a set ofn ‘Walrasian’ markets. He treated the crossed adjustment of prices and quantities as a linear Hamiltonian vector field. In more recent work, Goodwin introduced non-linear perturbations in his multi-sectoral adjustment model. He assumed that real consumption depends non-linearly on relative prices. This paper shows the following: (1) Goodwin's behavioural hypotheses are compatible with the assumption that agents maximize; (2) if the dynamic process is Hamiltonian, then symplectic coordinate changes are essential tools of analysis; (3) if the real wage is rigid and returns to scale are not constant, then the Hamiltonian model can generate chaotic transients or, in extreme cases, pure chaotic motions.     

The effect of management incentives and cross-listing status on the accounting treatment of R&D spending

This paper investigates the effect of management incentives and cross-listing status on the accounting treatment of research and development (R&D) spending for a sample of Canadian hi-tech and biopharmaceutical firms. U.S. GAAP adopts an immediate expensing rule for all R&D spending except for software development costs for which technological feasibility has been established. Contrary to the U.S., Canadian and international standard setters recommend capitalization if development costs meet certain criteria. Because those criteria are largely based on management judgment, capitalization of R&D spending is an accounting choice that can be used for income manipulation or signaling.Using a logit model, we examine how the decision to capitalize R&D spending is influenced by the cross-listing status and several other key firm characteristics that are well documented in the accounting literature. We find that the probability of capitalizing R&D spending increases for cross-listed and non-cross-listed firms in the software industry. The probability of capitalizing R&D spending also increases for firms that are more leveraged, more mature, and have higher level of cash flows from operations. However, the probability of capitalizing R&D spending decreases for larger corporations, firms with more concentrated ownership and highly profitable firms. Overall our results indicate a preference for Canadian firms in the software industry to emulate U.S. accounting practices for R&D spending. They also suggest that firms use the decision to capitalize or expense R&D spending as an earning management tool to either meet debt covenants or to smooth income.     

Capturing the Evolution of Customer–Firm Relationships: How Customers Become More (or Less) Valuable Over Time

Few studies have examined the influence of marketing activities while accounting for customer dynamics over time. The authors contribute to this growing literature by extending the hurdle model to capture customer dynamics using a hidden Markov chain. We find our dynamic model performs better than static and latent class models. Our results suggest the customer base can be segmented into four segments: Deal-prone, Dependable, Active, and Event-driven. Each segment reacts differentially to marketing activities. Although catalogs influence both purchase incidence and the number of orders, this marketing activity has the largest impact on purchase incidence across all four segments. In contrast, retail promotions are more likely to influence the number of orders a customer will make for all of the segments except for the Deal-prone segment. For this segment, retail promotions have the strongest impact on purchase incidence.     

Comparing Alternative Predictors Based on Large‐Panel Factor Models

This article compares the predictive ability of the factor models of Stock and Watson (2002a) and Forni, Hallin, Lippi and Reichlin (2005) using a ‘large’ panel of macroeconomic variables of the United States. We propose a nesting procedure of comparison that clarifies and partially overturns the results of similar exercises in the literature. Our main conclusion is that with the dataset at hand the two methods have a similar performance and produce highly collinear forecasts.     

Internationalisation,Innovation and Productivity: How Do Firms Differ in Italy?

This paper addresses the issue of intra‐industry heterogeneity and internationalisation. We show that, after controlling for sector, location, firm age and size, Italian manufacturing companies exhibit different economic and innovative performance according to their involvement in foreign activities. In particular, exporters show intermediate innovative performance between non‐internationalised firms and those carrying out foreign production. Multinationals with a lower commitment to foreign markets, i.e. with non‐manufacturing activities abroad only, exhibit a higher productivity than exporters but they do not appear to innovate more than the latter. Heterogeneity in productivity is robust to controlling for innovation inputs and outputs, suggesting that the difference in economic performance cannot be entirely attributed to different innovative activities, and that the involvement in international operations can be a distinct channel of knowledge accumulation.     

On the time stability of the output–capital ratio

This paper is concerned with the role of the output–capital ratio in growth models. In the first part we highlight the behaviour of the output–capital ratio along the balanced growth path in the models of Solow [Q. J. Econ. 70 (1956) 65] and Romer [J. Polit. Econ. 94 (1986) 1002]. In the second part we assess the stability of the ratio for some industrial countries.     

Does host market regulation induce cross‐border environmental innovation?

This paper evaluates the effect of host‐country environmental policy stringency on the offshoring of green patents for 2000 top world R&D performers. It is shown that a more stringent environmental regulation triggers patent offshoring in the field of green technologies. Results are robust to various different specifications, to alternative definitions of innovation offshoring and of regulatory restrictions, to controls for firm and country‐level characteristics and to the consideration of possible endogeneity of regulation. We interpret these findings as evidence that MNEs can take advantage from their exposure to multiple institutional settings, reducing the costs of, and increasing the payoff from, green innovation offshoring. It is also suggested that R&D subsidies and non‐market‐based regulatory measures are more important than market‐based instruments as drivers of cross‐border environmental innovation.     

Who Trades with Whom? Exploring the Links between Firms' International Activities,Skills, and Wages

Using firm‐level data on the Italian manufacturing industry, we examine how trade activities are related to workforce composition and wages. We contribute to empirical research on these issues in three ways. First, we provide new evidence that is consistent with multi‐attribute models on firm heterogeneity and trade. We show that even after controlling for various company characteristics, including size and capital intensity, exporters still pay higher wages and employ more skilled workers than nonexporters. Second, we consider engagement in international transactions, either by means of exports, imports, or a combination of the two. We show that failing to control for importing activities may bias upward export premia. Third, we look at how the wage and the employment structures of trading firms change with the country of destination and origin of trade flows. We find that wage and skill premia are influenced by the characteristics of partner countries.