Dynamics of female labour force participation in France

This article formulates and estimates a structural intertemporal model of labour force participation. Relying on theoretical characterizations derived from an economic model of lifetime behaviour, we estimate a dynamic probit model with correlated random effects using longitudinal data to allow for a dynamic structure. The model is applied to a panel of married women drawn from the 1997–2002 French Labour Force surveys in order to represent their participation behaviour. It is estimated by maximum simulated likelihood. Our results show that women’s decisions to go out to work are characterized by significant state dependence, unobserved heterogeneity and negative serial correlation in the transitory error component. In addition, we find that the presence of young children in a woman’s household reduces her labour participation, but unequally according to their age and number. As expected, educational level has a positive impact on women’s participation. Last, a rise in the husband’s wage is found to raise female participation initially and to lower it subsequently. This empirical finding suggests that leisure may not systematically be a normal good, contrary to what is frequently assumed in the literature.     

A general endogenous grid method for multi-dimensional models with non-convexities and constraints

The endogenous grid method (EGM) significantly speeds up the solution of stochastic dynamic programming problems by simplifying or completely eliminating root-finding. We propose a general and parsimonious EGM extended to handle (1) multiple continuous states and choices, (2) multiple occasionally binding constraints, and (3) non-convexities such as discrete choices. Our method enjoys the speed gains of the original one-dimensional EGM, while avoiding expensive interpolation on multi-dimensional irregular endogenous grids. We explicitly define a broad class of models for which our solution method is applicable, and illustrate its speed and accuracy using a consumption–saving model with both liquid assets and illiquid pension assets and a discrete retirement choice.     

Monitoring as a partially observable decision problem

Monitoring is an important and costly activity in resource management problems such as containing invasive species, protecting endangered species, preventing soil erosion, and regulating contracts for environmental services. Recent studies have viewed optimal monitoring as a Partially Observable Markov Decision Process (POMDP), which provides a framework for sequential decision making under stochastic resource dynamics and uncertainty about the resource state. We present an overview of the POMDP framework and its applications to resource monitoring. We discuss the concept of the information content provided by monitoring systems and illustrate how information content affects optimal monitoring strategies. Finally, we demonstrate how the timing of monitoring in relation to resource treatment and transition can have substantial effects on optimal monitoring strategies.     

Reconfiguration,restructuring and firm performance: Dynamic capabilities and environmental dynamism

Research summary: Reorganization has been proposed as a key dynamic capability. This study compares the performance outcomes of two forms of reorganization, differing in their pervasiveness: organizational restructuring and organizational reconfiguration. Our dynamic panel data analysis of large U.S. corporations between 1985 and 2004 finds contrasting performance outcomes for these two forms of reorganization: in general, the more pervasive restructuring is associated with positive performance outcomes, while the more limited reconfiguration is associated with negative performance outcomes. However, outcomes vary by environment. Consistent with dynamic capabilities theory, we find evidence that in dynamic environments reconfiguration outcomes turn positive, while restructuring outcomes turn negative. We discuss implications for dynamic capabilities theory and managerial policy. Managerial summary: Firms need to reorganize in order to adapt to change. This study compares the financial performance consequences of two forms of reorganization: organizational restructurings and organizational reconfigurations. Restructurings involve fundamental change in organizational principles and are typically irregular; reconfigurations involve incremental change and are frequent. Examining a set of large U.S. corporations, we find these two forms of reorganization have contrasting financial consequences, depending on context. In the general case, fundamental restructurings have positive consequences, while incremental reconfigurations have negative consequences. However, this general result reverses in specifically dynamic environments, where reconfigurations are positive financially, while restructurings are negative. We conclude that the relative frequency of reconfigurations helps adaptation in dynamic environments. Managers should choose forms of reorganization according to the rate of environmental change. Copyright © 2016 John Wiley & Sons, Ltd.     

Sustainable hub location under mixed uncertainty

This paper addresses a novel sustainable hub location problem (SHLP) in which two new environmental-based cost functions accounting for air and noise pollution of vehicles are incorporated. To cope with uncertain data incorporated in the model, a mixed possibilistic–stochastic programming approach is proposed to construct the crisp counterpart. A simulated annealing (SA) and an imperialist competitive algorithm (ICA) with a new solution representation are developed to solve real-sized instances whose performances are compared with a proposed lower bound. Finally, some computational experiments are provided to demonstrate the effectiveness of the proposed model and solution approaches.     

Maximizing benefits in project selection: a hybrid approach

Charitable foundations and government programmes should endeavour to allocate their limited resources to best serve their constituents. Yet, mathematical programming techniques are rarely used despite overwhelming evidence of their superiority in selecting projects that yield higher levels of total benefits. We present a novel ‘hybrid selection model’ that combines binary linear programming and heuristic rank-based models applied to two case studies. The first case focuses on providing services to women and shows a hybrid model would have selected the top three ‘signature’ projects and maintained an above-average overall project benefit while securing a 180% improvement in the number of projects funded, a 66% improvement in the number of women served and a 132% improvement in the total benefit achieved. In the second case, we apply the hybrid approach to data from the US government’s largest forest preservation programme and demonstrate that the hybrid approach could allow the programme to select up to 11 top-scoring projects while still achieving a 97% gain in the total overall benefit compared to their traditional method. These case studies show that the hybrid approach has the potential to be applied in a variety of settings and improve how foundations and programmes achieve their goals.     

技术创新、金融创新与经济增长——基于中国省际面板数据

本文从实证分析层面对金融创新、技术创新与经济增长之间的作用关系进行探讨。基于我国 2000~2015 年省级面板数据，采用GMM估计方法，利用动态面板模型进行实证检验。结果表明：技术创新对经济增长的影响显著为正，单独的金融创新对经济增长起抑制作用，二者的交互作用则对经济增长起显著性正向作用。脱离实体经济的金融创新将抑制经济增长，也会间接阻碍技术创新对经济增长的影响。本文结合当前经济形势，从金融机构与创新企业相接轨共同提高创新水平、培养创新型人才等角度提出建议。     

The globalization indicators-tourism development nexus: a dynamic panel-data analysis

This study investigates how economic, social, and political globalization indicators influence tourism development. We applied different approaches of panel regression to panel data from a sample including 133 countries between 1995 and 2014. The results indicate that economic, social, and political globalization are significant factors for tourism development. Thus, this study proves that economic, social, and political integration of countries are significant driving forces behind their tourism development.     

The generalized lock scheduling problem: An exact approach

The present paper introduces an integrated approach to solving the generalized lock scheduling problem. Three interrelated sub problems can be discerned: ship placement, chamber assignment and lockage operation scheduling. In their turn, these are closely related to the 2D bin packing problem, the assignment problem and the (parallel) machine scheduling problem respectively. In previous research, the three sub problems mentioned were considered separately, often using (heuristic) interaction between them to obtain better solutions. A mixed integer linear programming model is presented and applied to instances from both inland locks and locks in a tide independent port. The experiments show that small instances incorporating a wide range of real-life constraints can be solved to optimality.     

Incorporating risk in a positive mathematical programming framework: a dual approach

In this study we develop a new methodological proposal to incorporate risk into a farm‐level positive mathematical programming (PMP) model. We estimate simultaneously the farm nonlinear cost function and a farmer‐specific coefficient of absolute risk aversion as well as the resource shadow prices. The model is applied to a sample of representative arable crop farms from the Emilia‐Romagna region in Italy. The estimation results confirm the calibration ability of the model and reveal the values of the individual risk aversion coefficients. We use the model to simulate different scenarios of crop price volatility, in order to explore the potential risk management role of an agri‐environmental scheme.