Trust in Islamic Business-to-Business Relationships: Evidence from Indonesia

We examine the role of trust within Islamic culture in business-to-business relationships by exploring the link between credit officers’ trust in business customers and their financing decisions. In line with our framework, which is based on the fact that Islamic culture is characterized by a collectivistic approach and clan-based social structure, we find that value-based trust is more important than competence-based trust in explaining business relationships. The results support the argument that Islamic culture business relationships are grounded more on the principles, values and norms that a partner brings to the relationship than on business skills. Our results are robust to endogeneity and multilevel issues.     

Fisher's Information for Discretely Sampled Lévy Processes

This paper studies the asymptotic behavior of Fisher's information for a Lévy process discretely sampled at an increasing frequency. As a result, we derive the optimal rates of convergence of efficient estimators of the different parameters of the process and show that the rates are often nonstandard and differ across parameters. We also show that it is possible to distinguish the continuous part of the process from its jumps part, and even different types of jumps from one another.     

Inventory routing problems in a context of vendor-managed inventory system with consignment stock and transshipment

The inventory routing problem involves the integration and the coordination of two components of the logistics value chain: the inventory management and the vehicle routing decisions. In fact, the aim is to jointly decide on the distribution tour, from a distribution centre to a set of locations, and on the inventory policy for each location. Although many research investigations show great interest in policies such as transshipment or dynamic routings on the distribution system performances, these approaches are often criticised in practice as being too restrictive. In this article, we consider the inventory routing framework in a supplier integration context, i.e. a vendor-managed inventory with a consignment stock policy. Under such framework, we show that the transshipment brings more benefits than the classical context. In particular, we consider the case of static routings and we numerically show that transshipment permits to better optimise the distribution tours and to improve the global performance of the supply network.     

Political connections and firm operational efficiencies: evidence from a developing country

This paper investigates the impact of political connections on firm operational efficiencies. We test the political interventions in investment and employment decisions. Our results provide strong support for the presence of investment inefficiencies and excessive employment amongst politically connected firms, whereas the detrimental effect of political interventions is substantially larger on employment decisions. We further find that such operational inefficiencies are more pronounced for low-growth connected firms. Finally, the economy-wide cost of the excessive employments is estimated to be 0.19 % of GDP annually.     

Maximum Likelihood Estimation of Discretely Sampled Diffusions: A Closed‐form Approximation Approach

When a continuous‐time diffusion is observed only at discrete dates, in most cases the transition distribution and hence the likelihood function of the observations is not explicitly computable. Using Hermite polynomials, I construct an explicit sequence of closed‐form functions and show that it converges to the true (but unknown) likelihood function. I document that the approximation is very accurate and prove that maximizing the sequence results in an estimator that converges to the true maximum likelihood estimator and shares its asymptotic properties. Monte Carlo evidence reveals that this method outperforms other approximation schemes in situations relevant for financial models.     

The Effects of Random and Discrete Sampling when Estimating Continuous–Time Diffusions

High–frequency financial data are not only discretely sampled in time but the time separating successive observations is often random. We analyze the consequences of this dual feature of the data when estimating a continuous–time model. In particular, we measure the additional effects of the randomness of the sampling intervals over and beyond those due to the discreteness of the data. We also examine the effect of simply ignoring the sampling randomness. We find that in many situations the randomness of the sampling has a larger impact than the discreteness of the data.