Economic Competition,Policy Interdependence,and Labour Rights

Extant scholarship treats national policies concerning labour rights as a function of economic factors and yet neglects influences of policies among economically competing states. Relying on the policy interdependence theory, this study argues that labour rights policy in a state is dependent on its economic competitors’ labour policy decisions. It specifically maintains that the intensifying competition for foreign direct investment and exports as well as against imports channels negative externalities of deteriorating labour protection in competing states which drives expansive downward policy mimicking and leads to a global decline in labour rights – a race to the bottom. Utilising spatial econometric technique to analyse a new data on labour rights for the period 1994–2009, it finds that labour rights practices are interdependent among economic competitors and experience global deteriorations; whereas labour rights laws remain largely independent due to high policy and reputational costs of lowering them and show more fluctuations.     

Childhood adversity and the propensity for entrepreneurship: A quasi-experimental study of the Great Chinese Famine

Studies on the determinants of entrepreneurship emphasize that challenged adults tend to become entrepreneurs. However, research has not addressed the childhood origins surrounding the propensity for entrepreneurship. This article links childhood adversity to the propensity of individuals to become migrant entrepreneurs later in life. We test hypotheses derived from this theory in the context of whether, and when, children who survived the Great Chinese Famine of 1959–1961 became migrant entrepreneurs. Results strongly indicate that those who survived greater hardship during the Famine are more likely to become entrepreneurs, especially when they were younger during the famine years. We also find that being younger at the time of migration increased the likelihood of becoming entrepreneurs in their new locale. Overall, this study casts light on why, how and when childhood adversity shapes the propensity for entrepreneurship.     

A new take on voice: the influence of BlackRock’s ‘Dear CEO’ letters

Review of Accounting Studies - Abstract We examine whether broad-based public engagement by institutional investors influences the behavior of portfolio firms. We investigate this question in the...     

The Cost of War: A Comment and a Reply

Intereconomics - In the July/August issue of Intereconomics, Ilona Sologoub argued that increasing the cost of war would limit the ability of an authoritarian state to wage a war. Here, Charles D....     

Analytical approximations of local‐Heston volatility model and error analysis

This paper studies the expansion of an option price (with bounded Lipschitz payoff) in a stochastic volatility model including a local volatility component. The stochastic volatility is a square root process, which is widely used for modeling the behavior of the variance process (Heston model). The local volatility part is of general form, requiring only appropriate growth and boundedness assumptions. We rigorously establish tight error estimates of our expansions, using Malliavin calculus. The error analysis, which requires a careful treatment because of the lack of weak differentiability of the model, is interesting on its own. Moreover, in the particular case of call–put options, we also provide expansions of the Black–Scholes implied volatility that allow to obtain very simple formulas that are fast to compute compared to the Monte Carlo approach and maintain a very competitive accuracy.     

Who do you care about? Scientists’ personality traits and perceived impact on beneficiaries

We investigate the roots of scientists' perceptions of the impact of their work by examining stable psychological characteristics such as personality traits. An analysis of personality traits highlights the effects of policies related to gender equality, allocation of research time and skills acquisition. It improves our understanding of the conflicts related to scientists’ perceptions of the impact of their research on beneficiaries. For example, conscientiousness increases the perceived impact on clinical beneficiaries, but reduces the perceived impact on industrial beneficiaries. Organizational scientific freedom increases the effects of personality traits on perceived impact on beneficiaries such that scientists affiliated to a university are less likely than colleagues working in other research settings to perceive the simultaneous impact of their work on both industrial and clinical beneficiaries.     

Semistatic hedging and pricing American floating strike lookback options

We price an American floating strike lookback option under the Black–Scholes model with a hypothetic static hedging portfolio (HSHP) composed of nontradable European options. Our approach is more efficient than the tree methods because recalculating the option prices is much quicker. Applying put–call duality to an HSHP yields a tradable semistatic hedging portfolio (SSHP). Numerical results indicate that an SSHP has better hedging performance than a delta-hedged portfolio. Finally, we investigate the model risk for SSHP under a stochastic volatility assumption and find that the model risk is related to the correlation between asset price and volatility.     

Time series copulas for heteroskedastic data

We propose parametric copulas that capture serial dependence in stationary heteroskedastic time series. We suggest copulas for first‐order Markov series, and then extend them to higher orders and multivariate series. We derive the copula of a volatility proxy, based on which we propose new measures of volatility dependence, including co‐movement and spillover in multivariate series. In general, these depend upon the marginal distributions of the series. Using exchange rate returns, we show that the resulting copula models can capture their marginal distributions more accurately than univariate and multivariate generalized autoregressive conditional heteroskedasticity models, and produce more accurate value‐at‐risk forecasts.