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.     

Twenty years of jumps in commodity markets

In this article, we provide statistical evidence around jumps affecting commodity returns. Using nearly 20 years of daily data, we use Laurent, Lecourt, and Palm's (2011) methodology to jump extraction, and discuss various aspects of the estimated jump activity. On average across various commodity markets, we find a high number of days for which returns exhibit the presence of jumps, consistently with the intuition that commodities are affected by large price fluctuations. We emphasize that the post-jump average return depends on the commodity sector considered (e.g. agriculture, energy, or metals). We also show evidence of a jump-to-volatility channel for commodities (similar to the effect usually found for equities). Finally, we diagnose around 40 dates during which commodity indices, stocks, bonds and currencies `co-jump’, revealing a tail dependence between standard and alternative assets.     

Family Firm Heterogeneity and Tax Aggressiveness: A Mixed Gamble Approach

Few studies try to understand how the unique preferences of family firms affect tax strategies, and how family firm heterogeneity drives variation in tax activities. Drawing on the mixed gamble approach, this study examines the tax aggressiveness of different types of family firms, considering how various sources of heterogeneity alter the perception of potential gains and losses to socioemotional and financial wealth. Based on a panel dataset of 242 private family firms for the period 2012–2014, this study shows that strong family-owned firms, family firms with a family CFO, family-founder firms, and family-named firms display lower levels of tax aggressiveness. These findings demonstrate that family firm heterogeneity is a crucial factor in the mixed gamble calculus of tax aggressiveness.     

Calibration of local volatility model with stochastic interest rates by efficient numerical PDE methods

Decisions in Economics and Finance - Long-maturity options or a wide class of hybrid products are evaluated using a local volatility-type modelling for the asset price S(t) with a stochastic...     

Disillusionment from Failure as a Source of Successful Learning

In this article I review the literature on organizational learning from failed product launches. I challenge the view that failure is an inevitable part of the “probe and learn” process as well as the view that companies do not learn anything from such failures. I conclude there is no direct link between learning and commercial failures, and highlight many obstacles that hamper the learning process. Finally, even when learning does occur, it will not always result in improved organizational performance. Copyright © 2011 ASAC. Published by John Wiley & Sons, Ltd.