Collateral,bank monitoring and firm performance: the case of newly established wine‐farmers

The present study aims to learn how collateral affects firm performance in the case of newly established wine producers. The issue is to identify the effects of collateral in situations of asymmetric information when the bank is the main financial partner of the entrepreneurs involved. On one hand, the use of collateral may reduce the risk of overinvestment by entrepreneurs and thereby reduce the risk of repayment default. On the other hand, collateral may induce bad performance linked to a reduced monitoring of the investments by the bank. We herein test both hypotheses in two different cases: when the bank monitors the investments and when the bank does not.     

Markups,quality, and transport costs

This paper provides new evidence on trade prices based on firm-level data from France. It shows that firms charge higher free-on-board (net of transportation costs, hereafter noted as fob) unit values on exports to more distant countries. This finding holds within firms and products, and across destinations. The price premium paid by distant consumers is due to firms charging higher fob prices, and to higher transportation costs. A simple decomposition of the elasticity of import prices to distance shows that, after a fall in transport costs, almost 80% of the decline in import prices enjoyed by consumers is due to firms charging lower fob prices. This suggests a new channel through which changes in transport costs may affect welfare.     

On hierarchical competition in oligopoly

In this paper, we consider a hierarchical oligopoly model, in which firms compete on quantities of an homogeneous product. We provide a proof and an interpretation that under the three necessary and sufficient conditions of linear aggregate demand, constant and identical marginal costs, the strategy of leaders at any stage depends neither on the number of leaders who play after nor on the number of remaining stages. So, all firms behave as Cournotian oligopolists on the residual demand. We show that these three assumptions are not only sufficient but also necessary. Any departure from any of these assumptions rules out this property.     

Minimum Distance Estimation and Testing of DSGE Models from Structural VARs*

The aim of this paper is to complement the minimum distance estimation–structural vector autoregression approach when the weighting matrix is not optimal. In empirical studies, this choice is motivated by stochastic singularity or collinearity problems associated with the covariance matrix of impulse response functions. Consequently, the asymptotic distribution cannot be used to test the economic model's fit. To circumvent this difficulty, we propose a simple simulation method to construct critical values for the test statistics. An empirical application with US data illustrates the proposed method.     

Relation between bid–ask spread,impact and volatility in order-driven markets

We show that the cost of market orders and the profit of infinitesimal market-making or -taking strategies can be expressed in terms of directly observable quantities, namely the spread and the lag-dependent impact function. Imposing that any market taking or liquidity providing strategies is at best marginally profitable, we obtain a linear relation between the bid–ask spread and the instantaneous impact of market orders, in good agreement with our empirical observations on electronic markets. We then use this relation to justify a strong, and hitherto unnoticed, empirical correlation between the spread and the volatility per trade, with R ²s exceeding 0.9. This correlation suggests both that the main determinant of the bid–ask spread is adverse selection, and that most of the volatility comes from trade impact. We argue that the role of the time-horizon appearing in the definition of costs is crucial and that long-range correlations in the order flow, overlooked in previous studies, must be carefully factored in. We find that the spread is significantly larger on the NYSE, a liquid market with specialists, where monopoly rents appear to be present.     

Trade and unemployment: What do the data say?

This paper documents a robust empirical regularity: in the long-run, higher trade openness is associated with a lower structural rate of unemployment. We establish this fact using: (i) panel data from 20 OECD countries, (ii) cross-sectional data on a larger set of countries. The time structure of the panel data allows us to control for unobserved heterogeneity, whereas cross-sectional data make it possible to instrument openness by its geographical component. In both setups, we purge the data of business cycle effects, include a host of institutional and geographical variables, and control for within-country trade. Our main finding is robust to various definitions of unemployment rates and openness measures. Our benchmark specification suggests that a 10 percentage point increase in total trade openness reduces aggregate unemployment by about three quarters of one percentage point.     

Evaluating the carbon-macroeconomy relationship: Evidence from threshold vector error-correction and Markov-switching VAR models

This paper studies the nonlinear adjustment between industrial production and carbon prices – coined as ‘the carbon-macroeconomy relationship’ – in the EU 27. We model carbon price returns and industrial production as nonlinear and state-dependent, with dynamics depending on the sign and magnitude of past realization of returns and the growth of industrial production. Our findings show that (i) macroeconomic activity is likely to affect carbon prices with a lag, due to the specific institutional constraints of this environmental market; (ii) the joint dynamics of industrial production and carbon prices seem adequately captured by two-regime threshold vector error-correction and two-regime Markov-switching VAR models compared to linear models as main competitors. The regime-switching models proposed are profoundly checked for their economic content and statistical congruency, and are found to provide a sound statistical framework for a comprehensive analysis of the carbon-macroeconomy relationship.     

Do community-driven development projects enhance social capital? Evidence from the Philippines

We explore the social capital impacts of a community-driven development project in the Philippines in which communities competed for block grants for infrastructure investment. The analysis uses a unique panel data set of about 2100 households, aggregated at the village-level, collected in 66 treatment and 69 comparison communities. We provide both difference-in-differences and propensity score matching estimates. We find that the project increased participation in village assemblies and the frequency with which local officials meet with residents and had a negative impact on collective action. There is also more limited evidence of a positive impact of the project on bridging (i.e., generalized) trust and of a negative impact on group membership.     

Analysing the lobby-effect of port competitiveness’ determinants: a stochastic frontier approach

Building upon a formerly performed study on port competitiveness, this article discusses the use of a stochastic frontier model as an interesting novel use to test, identify and correct respondents’ bias by applying it to competitiveness analysis based on perceptions of senior executives. Measuring the importance of competition determinants of seaports, conventionally analyzed using a SWOT-analysis based on (transport) infrastructure as a prime requirement for port activity growth, is an important issue to port management. However, it seems that the “institutional” environment of a seaport is also critical in obtaining a competitive advantage. In Haezendonck et al. (2000 and 2001) those port specific advantages and disadvantages were identified using factor analysis and L1-regression on the perceptions of 75 respondents, all senior executives and experts, through a survey. As regards the results of this study, critiques were formulated on the use of perceptions, often biased due to the political lobbying potential of the results. Since respondents often see independent studies as an opportunity to obtain more or early government subsidies, attract new investment projects or at least highlight the attention on their specific problems and demands, they were prone to underestimating the positive impact of the key success factors of the studied seaport compared to its main rivals, in this case major seaports in the so-called Hamburg–Le Havre competitive range. The purpose of this article is to test the assumption that respondents significantly underestimate the positive impact of port specific advantages and to see which of the respondent subgroups within the 75 respondents sample are more responsible than others for this underestimation. In addition, we argue and demonstrate that the use of a stochastic frontier method is appropriate for this matter. Each of 25 considered competition determinants of the original study is decomposed into a noise and “efficiency” term, based on the Bayesian stochastic frontier model (BSFM). In this article, we find evidence that BSFM could be used to test the “lobby-effect” or underestimation of the real effect of determinants, that terminal operators as a subgroup of respondents, are more likely to underestimate the key success factors than the subgroup of port experts and that those determinants that are directly related to government action show more underestimation than competitiveness determinants that result from private investments.     

On the Pricing of Contingent Claims with Frictions

This paper studies the problem of pricing contingent claims in a market which has frictions in the form of costs, such as penalty functions corresponding to constraints. An arbitrage-free interval is identified, and a fair price based upon utility functions is proposed. It provides a framework to study incomplete markets that is simplier than the one related to constraints on portfolios introduced by Karatzas and Kou.