Coffee export booms and monetary disequilibrium: some evidence for Colombia

The theoretical models that analyse the monetary consequences of export booms show that under a regime of fixed exchange rates, they affect not only the demand for money, via real income, but also the money supply via foreign exchange accumulation. Within this theoretical framework, this study proposes an empirical approach to determine whether the coffee booms of the second half of the 1970s and mid–1980s led to excess money supply in the Colombian economy. The findings provide evidence in favour of a direct association between coffee export booms and excess money supply, implying that external disturbances jeopardize the ability of the economic authorities to carry out successful monetary policy.     

An application of co-word analysis and bibliometric maps for detecting the most highlighting themes in the consumer behaviour research from a longitudinal perspective

This article presents an application of a bibliometric and visual study of the research carried out on a social science subfield, concretely the consumer behaviour research (CBR), from a longitudinal perspective (period 1966–2008). The study combines performance analysis and science mapping for detecting and visualizing conceptual subdomains. Quantitative and qualitative measures are used in order to identify the most prominent themes. Quantitative data are used to put together very related concepts (themes or clusters of topics), while qualitative indicators (as those based on citations) are used to measure the quality and/or impact of the detected themes. The study also uses bibliometric maps to show in a visual way the associations between the main concepts treated by the CBR community. The maps provide insight into the structure of the CBR, visualize the division of the field into several subfields, and indicate the relationships between these subfields. Co-word analysis is the bibliometric technique used to identify the main themes. All this allows us to quantify and visualize the thematic evolution of the CBR. It also helps to both experts and novices to understand the current state of the art of the CBR and to predict where future research could lead.     

On the Stationarity of Current Account Deficits in the European Union

In this paper, we test for the stationarity of EU current account deficits. Our testing strategy addresses two key concerns with regard to unit‐root panel data testing, namely (i) the identification of which panel members are stationary, and (ii) the presence of cross‐sectional dependence. For this purpose, we employ an AR‐based bootstrap approach to the Hadri (2000 ) test. While there is only mixed evidence that current account stationarity applies when examining individual countries, this does not appear to be the case when considering panels comprising both EU and non‐EU members.     

Intangibles and credit decisions: results from an experiment

The question in this paper is whether the inclusion of intangibles is meaningful in a credit decision context. To examine this issue we conducted an experiment with forty loan officers. The loan officers were presented with a situation of a company that required a credit of 5 million Swedish kronor. Half of the loan officers were given a traditional annual statement in which intangibles were treated as costs while the other half received a balance sheet in which brand, R&D and education were capitalized. The loan officers were asked to give their opinion regarding the credit decision and the importance of extra information. They were also confronted with four short cases where extra information about the company appeared. Statistical analysis revealed that none of three hypotheses relating to the statement that ‘accounting for intangibles does not matter’ could be falsified. Still, the acquired qualitative data that emerged from the study makes it possible to suggest another finding. The study shows that accounting for intangibles is accepted if the accounts were seen as reliable. The conclusion is that if it is possible to create reliable data about intangibles, accounting for intangibles is meaningful for credit decisions.     

Technological Collaboration: Bridging the Innovation Gap between Small and Large Firms*

This paper analyzes how technological collaboration acts as an input to the innovation process and allows small and medium‐sized enterprises to bridge the innovation gap with their bigger counterparts. Based on a large longitudinal sample of Spanish manufacturing firms, the results show that though technological collaboration is a useful mechanism for firms of all sizes to improve innovativeness, it is a critical factor for the smallest firms. The impact of this collaboration varies depending on innovation output and type of partner. Specifically, the impact of collaboration in small and medium‐sized firms is more significant for product than process innovations. Regarding type of partner, vertical collaboration—with suppliers and clients—has the greatest impact on firm innovativeness, though this effect is clearer for medium‐sized enterprises than for the smallest firms.     

Optimal portfolio choice in real terms: Measuring the benefits of TIPS

In this paper we solve an optimal portfolio choice problem to measure the benefits of Treasury Inflation Indexed Securities (TIPS) to investors concerned with maximizing real wealth. We show how the introduction of a real riskless asset completes the investor asset space, by contrasting optimal portfolio allocations with and without such assets. We use historical data to quantify gains from availability of TIPS in the presence of other asset classes such as equities, commodities, and real estate. We draw a distinction between buy-and-hold long-term investors for whom TIPS fully displace nominal risk-free assets and short-term investors for whom TIPS improve the investment opportunity set of real returns. Finally, we show how gains from TIPS are tempered by the availability of alternative assets that covary with inflation, such as gold and real estate.     

Capture and Dissemination of Specialized Knowledge in Network Organizations

I present a model for the capture and retrieval of organizational memory that can help overcome the information dissemination problem faced by network organizations. Network organizations are made of small, heterogeneous, product-oriented teams. In these organizations, the specialization of knowledge that has characterized functional hierarchies can be lost as the functional units in which this expertise was created and shared are dismantled. The preservation and dissemination of expert knowledge thus becomes a major issue to be addressed by these organizations, whose competitive advantage depends on this specialization. The problem of capturing project-related organizational memory is addressed with a 3 step solution: (a) the use of explicit work processes; (b) the development of models capable of representing these processes, the artifacts that are developed, and the rationale used during decision making; and (c) the implementation and deployment of computer tools that support the development processes selected and that, in doing so, record and document the project. I address the problem of accessing information from projects developed elsewhere in the organization and propose a solution based on monitoring the user's manipulation of information and creating hypotheses of his or her information needs. These hypotheses are then used as queries by a fuzzy information retrieval engine that produces a ranked list of documents that are suggested to the user as being relevant to his or her information needs. As the user manipulates these documents, the hypothesis is updated, triggering a new retrieval and the update of the list of suggested documents. The feasibility of the approach is demonstrated with the implementation of a prototype.     

Forecasting exchange rates in transition economies: A comparison of multivariate time series models

This article compares the accuracy of vector autoregressive (VAR), restricted vector autoregressive (RVAR), Bayesian vector autoregressive (BVAR), vector error correction (VEC) and Bayesian vector error correction (BVEC) models in forecasting the exchange rates for five Central and Eastern European currencies (Czech Koruna, Hungarian Forint, Polish Zloty, Slovak Koruna and Slovenian Tolar) against the Euro and the US dollar. Among the specifications composing this battery of multivariate time series models, those with the smallest prediction error still fail to reject the test of equality of forecasting accuracy against the random walk model in short-term predictions, with the exception of the Slovenian Tolar/Euro exchange rate.First version received: October 2002/Final version received: September 2003The authors are grateful to two anonymous referees and the participants in the workshop Monetary and Exchange Rate Strategies Related to the Current European Unions Enlargement Processes, held in Leuven in September 2000, for very helpful comments.