Economic forecast quality: information timeliness and data vintage effects

This paper investigates the impact of the timeliness of information releases and data vintage variation on economic forecast quality. Specifically, using a set of 63 key US economic series, we provide a concise measure of the forecast accuracy associated with use of economic activity indices with different publication lags. A forecasting model based on an economic activity index that is subject to a short publication lag (viz. the Aruoba-Diebold-Scotti index) is more efficient than competing models. Moreover, if this publication lag advantage is removed (by artificially imposing a publication lag restriction comparable to that of a competing indicator) this efficiency largely disappears. The final part of the analysis employs a novel (simulation-based) method of assessing the impact of data vintage variation on forecast accuracy, and finds that the results are somewhat sensitive to such variation.     

The impact of temporary uses on property prices: the example of food trucks

Food trucks represent a temporary use of vacant or underutilised land. They have been assumed to increase the livability, vibrancy and attractiveness of a neighbourhood. However, no previous study has investigated whether this effect is reflected in property prices within the surrounding neighbourhood. We investigate the impact of a food truck pod on the values of single-family homes nearby. Using a quasi-experimental design, transaction data from Portland, Oregon and a difference-in-difference specification of a spatial regression model, we find that food trucks actually represent a negative externality, and that proximity of a home to food trucks is penalised by homebuyers. The closer a home is to the food trucks, the lower is the sales price. Explanations for this effect include increased parking shortages and trash issues in a neighbourhood due to food truck visitors.     

PRICING DERIVATIVES ON MULTISCALE DIFFUSIONS: AN EIGENFUNCTION EXPANSION APPROACH

Using tools from spectral analysis, singular and regular perturbation theory, we develop a systematic method for analytically computing the approximate price of a large class of derivative‐assets. The payoff of the derivative‐assets may be path‐dependent. In addition, the process underlying the derivatives may exhibit killing (i.e., jump to default) as well as combined local/nonlocal stochastic volatility. The nonlocal component of volatility may be multiscale, in the sense that it may be driven by one fast‐varying and one slow‐varying factor. The flexibility of our modeling framework is contrasted by the simplicity of our method. We reduce the derivative pricing problem to that of solving a single eigenvalue equation. Once the eigenvalue equation is solved, the approximate price of a derivative can be calculated formulaically. To illustrate our method, we calculate the approximate price of three derivative‐assets: a vanilla option on a defaultable stock, a path‐dependent option on a nondefaultable stock, and a bond in a short‐rate model.     

The relationship between multinationality and performance: Knowledge-intensive vs. capital-intensive service micro-multinational enterprises

This research explores the relationship between multinationality and firm performance (M-P) in the context of micro-multinational enterprises (mMNEs) within the service sector. We examine the moderating effects of industry characteristics using a data set of 1082 Spanish service mMNEs over an eight-year period. The empirical results provide statistical evidence that knowledge-intensive service mMNEs exhibit an inverted U-shaped M-P relationship, while capital-intensive service mMNEs present a U-shaped relationship. Our findings demonstrate that knowledge-intensive service mMNEs increase their performance in the initial stage of multinationality, encounter a threshold of internationalization at relatively low levels of multinationality and have a propensity to over-internationalize. By comparison, capital-intensive service mMNEs experience negative performance effects at low levels of multinationality and positive ones as they further internationalize. Given that their operations are scale-sensitive, they tend to expand internationally by concentrating their operations in few foreign markets as a means to overcome the liabilities of internationalization and smallness. We contribute to the literatures on multinationality research in the service sector and on SME internationalization by showing that the effects of multinationality on the performance of mMNEs depend on industry characteristics and that such contextual factors provide a better understanding of the M-P relationship.     

Navigating compromise: How founder authenticity affects venture identification amidst organizational hybridity

Founders of hybrid ventures encounter organizational tensions that can compel compromise in both their organizations' and their own personal values. Such compromises may, in turn, undermine founders' identification with their ventures. In a multi-case study analysis we examine why social entrepreneurs differ in their responses to organizational tensions, both at the firm- and individual-level, and how such differences relate to their venture identification. Specifically, our findings reveal that strategic decisions made in the context of values-based complexity are often accompanied by concerns regarding founder authenticity—that is, judgments about the alignment between founders' actions and the commitments or responsibilities associated with their identities as entrepreneurs. Yet, because founders differ in the basis from which they seek to maintain such alignment, these differences shape both hybridity management and subsequent venture identification. By unpacking such differences, our findings contribute new theory, bridging recent scholarship on founder authenticity with longstanding research on organizational identification and hybrid organizing.     

On Emissions Trading and Market Structure: Cap-and-Trade versus Intensity Standards

This paper examines the interdependence between imperfect competition and emissions trading. We particularly analyze the long run equilibrium in a two-sector (‘clean’ and ‘dirty’) model with Cournot competition among firms who face a fixed cost of production. The clean sector is defined as the sector with the highest long run cost margin on emissions. We compare the welfare implications of a cap-and-trade scheme with an emissions trading scheme based on relative intensity standards. It is shown that a firm’s long run equilibrium output in the clean or dirty sector does not depend on the emissions trading format, but only depends on the fixed cost of producing in the respective sector. Intensity standards can result in clean firms selling allowances to dirty firms, or dirty firms selling to clean firms. The former outcome yields higher welfare. It is demonstrated that cap-and-trade outperforms the intensity-based trading scheme in terms of long run welfare with free entry and exit. With intensity standards the size of the clean sector is too large.     

The political economy of decarbonisation: from green energy ‘race’ to green ‘division of labour’

This paper aims to provide an addendum to the rapidly growing concept of a global ‘green energy race’ between major states. It argues that although this framing has been useful in underscoring important dynamics in the process of decarbonisation, its narrow focus on installed capacity obscures a much broader and more complex process at play. In particular, it overlooks the critical role played by states aggressively investing in R&D and export manufacturing in the renewable energy sector. The paper thus supplements the concept of a green ‘energy race’ with that of a green ‘global division of labour’, which sees the process of decarbonisation not exclusively as an effort by individual states to install renewables domestically, but rather as a collective and interdependent process by dozens of states, all striving in different ways to promote capital accumulation on their soil. The paper provides an overview of data covering innovation, manufacturing and deployment in the clean energy sector, and offers a theoretical analysis of the trends observed.