The Quality of Smallholder Coffee in South Sumatra: The Production of Low-Quality Coffee as a Response to World Demand 1

Improving the quality of Indonesia's coffee exports has been a priority of government and the Association of Indonesian Coffee Exporters for some years. Efforts to achieve this objective have, however, been hampered by misconceptions about the reasons why coffee producers and traders at each point in the marketing network do not deliver a higher quality product. The research reported here shows that price premia for higher quality coffee are not large enough to encourage greater quality enhancement. The world market for low to medium grades, used in the production of instant coffee, is much larger than that for high-quality coffee, and this preference is transmitted in the form of low incentives to improve the product. Failure to understand this has led to government policies which at best do not solve the quality problem and at worst exacerbate it.     

Cardinality-based equality of opportunities

We study possible rankings of opportunity profiles. An opportunity profile is a list of opportunity sets, one for each agent in the society. We compare profiles on the basis of the notion of “equality of opportunities”. Our main results show the necessary and sufficient conditions for this comparison to be made using exclusively the information provided by two cardinal measures: the number of common alternatives in all sets of a given profile and the difference between the number of alternatives in the individual sets. We also show that, under additional axioms, we can combine these criteria only in a weighted procedure or in some lexicographic refinements of a weighted procedure.      

A note on forecasting international tourism demand in Spain

This paper considers the extent to which price and income proxy variables help in forecasting tourist demand in Spain. Contrary to some recent studies, we found that the inputs' contribution in terms of fitting and forecasting is nil when compared with alternative univariate models. Whether these findings are the results of the restrictions embedded in building the proxy inputs or in a poor specification of the dynamics of these models remains to be seen. We also contend that when dealing with medium, long-term forecasting comparisons, the use of the traditional aggregate accuracy measures like RMSE and MAPE help very little in discriminating among competing models. In these situations, predicted annual growth rates may be a better alternative.     

Golden Parachutes: Incentive Aligners,Management Entrenchers,or Takeover Bid Signals?

In this paper we investigate the effect of golden parachute (GP) adoptions on shareholder wealth. We control for the potential effect a GP adoption has on the probability that a firm will receive a takeover bid by investigating the wealth effects for firms that are in play when the GP is adopted. We find that announcements are wealth neutral when firms are in play and wealth increasing when firms are not in play when a GP is adopted. The results suggest that GPs have no influence on the success of a tender offer, refuting the hypotheses that they either align manager and shareholder interests or that they entrench inefficient managers. The difference in the results for in-play and not-in-play firms is consistent with the hypothesis that GPs signal an increased likelihood that a firm will receive a takeover bid.     

Portfolio Choice in the Presence of Housing

I show that investment in housing plays a crucial role in explainingthe patterns of cross-sectional variation in the compositionof wealth and the level of stockholdings observed in portfoliocomposition data. Due to investment in housing, younger andpoorer investors have limited financial wealth to invest instocks, which reduces the benefits of equity market participation.House price risk crowds out stockholdings, and this crowdingout effect is larger for low financial net-worth. In the modelas in the data leverage is positively correlated with stockholdings.     

LIQUIDITY,MONEY CREATION AND DESTRUCTION,AND THE RETURNS TO BANKING*

We build on our earlier model of money in which bank liabilities circulate as a medium of exchange. We investigate optimal bank behavior and the resulting provision of liquidity under a range of central bank regulations. In our model, banks issue inside money under fractional reserves, facing the possibility of excess redemptions. Banks consider the float resulting from money creation and make reserve‐management decisions that affect aggregate liquidity conditions. Numerical examples demonstrate positive bank failure rates when returns to banking are low. Central bank interventions may improve banks' returns and welfare through a reduction in bank failure.     

Consumption and Portfolio Choice over the Life Cycle

This article solves a realistically calibrated life cycle modelof consumption and portfolio choice with non-tradable laborincome and borrowing constraints. Since labor income substitutesfor riskless asset holdings, the optimal share invested in equitiesis roughly decreasing over life. We compute a measure of theimportance of human capital for investment behavior. We findthat ignoring labor income generates large utility costs, whilethe cost of ignoring only its risk is an order of magnitudesmaller, except when we allow for a disastrous labor incomeshock. Moreover, we study the implications of introducing endogenousborrowing constraints in this incomplete-markets setting.     

Accelerators as start-up infrastructure for entrepreneurial clusters

ABSTRACT

Infrastructure is commonly conceptualized as a set of facilities that play a critical role in facilitating activities by individuals and organizations. Conventionally, infrastructure is tightly linked to publicly funded projects that facilitate access to key resources and enable diverse activities. Within entrepreneurial clusters research, infrastructure includes universities, research institutions and telecommunication technologies that facilitate entrepreneurial activities. These capital-intensive investments seek to facilitate start-ups emergence by aiding access to markets and development of ideas. Accelerators facilitate the same activities and have only recently been conceptualized as start-up infrastructure. This study builds upon this research stream by elaborating on how accelerators can play this meaningful role at the cluster level. Specifically, and by relying on the analysis of empirical evidence from three distinct studies, we uncover how accelerators provide tangible and intangible dimensions of start-up infrastructure to form a positively reinforcing cycle of entrepreneurial activities. Additionally, our findings allow us to push further the idea that start-up infrastructure development can be an endogenous process involving multiple actors within the cluster. Our empirical findings and the theoretical insights derived from them have meaningful implications for the aforementioned literature, as well as start-up practitioners and policymakers linked to the funding of entrepreneurial clusters.     

A critical overview of privacy-preserving approaches for collaborative forecasting

Cooperation between different data owners may lead to an improvement in forecast quality—for instance, by benefiting from spatiotemporal dependencies in geographically distributed time series. Due to business competitive factors and personal data protection concerns, however, said data owners might be unwilling to share their data. Interest in collaborative privacy-preserving forecasting is thus increasing. This paper analyzes the state-of-the-art and unveils several shortcomings of existing methods in guaranteeing data privacy when employing vector autoregressive models. The methods are divided into three groups: data transformation, secure multi-party computations, and decomposition methods. The analysis shows that state-of-the-art techniques have limitations in preserving data privacy, such as (i) the necessary trade-off between privacy and forecasting accuracy, empirically evaluated through simulations and real-world experiments based on solar data; and (ii) iterative model fitting processes, which reveal data after a number of iterations.