A hump-shaped transitional growth path as a general pattern in long-run development

Long-run development is defined as the income transition between the traditional and the modern steady state, in which the speed of the transition is low near the two steady states but high and volatile in between them. This transition implies a hump-shaped relation between the level of per capita income and its growth rate. A hump-shaped growth-income path can be simulated with a two-sector growth model, in which the traditional sector is gradually replaced by the modern sector. Kernel regressions reveal a noisy but robust hump-shaped relation between the growth rate and the level of per capita income in stacked cross-country panel data.     

Exact parametric restrictions for 3-cycles in the RSS model: A complete and comprehensive characterization

This paper presents necessary and sufficient conditions for 3-period cycles in the two-sector Robinson–Solow–Srinivasan (RSS) model, taking as its point of departure an independently-(and simultaneously-) discovered exact discount-factor restriction for a general class of growth models by Mitra and Nishimura–Yano (MNY) in 1996. Our investigation of this remarkable result in the specificity of the RSS model enables a broadened inquiry that goes beyond the discount factor to parameters of labor-productivity and capital-depreciation. Since the RSS model, despite its concrete simplicity, is not covered by the general MNY model, the exact discount-factor restriction presented here does not follow from the MNY theorem, and necessitates new argumentation. Furthermore, we present a novel exact parametric region as our second result.     

A closed-form exact solution for pricing fixed-income variance swaps with affine-jump model

Fixed-income variance swaps became popular for investors to trade and hedge the fluctuation of interest rates after the recent global financial crisis over the past few decades, however, their valuations and risk management have not been studied sufficiently. This paper presents an analytic approach for pricing some discretely sampled fixed-income variance swaps under an affine-jump model with stochastic mean, stochastic volatility, and jumps. We employ a generalized characteristic function to derive the closed-form pricing formulas of these swaps, including two kinds of zero-coupon bond variance swap, Libor variance swap, and bond yield variance swap, to be precise. We also perform some numerical studies based on these models, which suggest that the fair strike values of these variance swaps are within a reasonable range regardless of estimation risk with data dependence and near-zero short rate regime. Our numerics show that the influences of varying sampling frequency and time-to-maturity on the values of these swaps are significant, and highlight the risks of specifying short rate model. Furthermore, the sensitivity analysis on the key parameters finds that the risks of stochastic volatility and jumps play prominent roles in pricing these variance swaps under the near-zero short rate regime.     

Measuring the welfare costs of inflation in a life-cycle model

In a neoclassical growth model with life-cycle households in which money is held to satisfy a cash-in-advance constraint, the optimal steady state inflation rate is absurdly high: in excess of 20%. Lump-sum, age-independent money injections twist and flatten the lifetime profile of utility, making this profile look more like the one that would be chosen by a planner. The cost of monetary finance of lump-sum payments is the distortion introduced to the labor-leisure choice.     

The aggregation of capital over vintages in a model of embodied technical progress

The paper considers how to measure capital in a model where technical progress is embodied in new units of capital. This embodiment model also assumes that once new units of capital are installed, it cannot be “unbolted” and sold on the second hand market. A significant difference between this Solow–Harper model and the traditional capital services model due to Jorgenson and his coworkers is that rising real wage rates will generally induce early retirement of assets; i.e., this model can provide an explanation for obsolescence. The paper studies how to aggregate over vintages and how to measure depreciation in the context of this embodiment model. These problems are more complicated than the corresponding problems in the traditional capital services model because the age of retirement of an asset is endogenous in the embodiment model. The paper uses duality theory to simplify the exposition.

An analytical approximation formula for European option pricing under a new stochastic volatility model with regime-switching

In this paper, an analytical approximation formula for pricing European options is obtained under a newly proposed hybrid model with the volatility of volatility in the Heston model following a Markov chain, the adoption of which is motivated by the empirical evidence of the existence of regime-switching in real markets. We first derive the coupled PDE (partial differential equation) system that governs the European option price, which is solved with the perturbation method. It should be noted that the newly derived formula is fast and easy to implement with only normal distribution function involved, and numerical experiments confirm that our formula could provide quite accurate option prices, especially for relatively short-tenor ones. Finally, empirical studies are carried out to show the superiority of our model based on S&P 500 returns and options with the time to expiry less than one month.     

Measuring well-being by a multidimensional spatial model in OECD Better Life Index framework

One of the most influential measures of multidimensional well-being, the Better Life Index, launched by OECD in 2011, contains a detailed overview of the social, economic, and environmental performances of different countries. Since its launch, a relevant number of empirical studies have been proposed on these data, but the role played by the distance between societal priorities and country-level performance in Better Life Index as well as in multidimensional well-being remains underexplored. We propose to address this issue by means of a multidimensional spatial model. We position the countries in the Euclidean K-dimensional space in which each dimension is a specific aspect of well-being, and we consider each individual's opinion on the same dimensions to calculate the personal optimal point. The distance between the optimal point of well-being and the actual observed point at individual level is the individuals' loss in well-being. We show that the societal loss at country-level is negatively related to the overall well-being and the main indices of quality of democracy. Based on the above evidence, we would argue that a multidimensional spatial framework represents a promising tool for the analysis of the whole class of multidimensional measures of well-being in which a group of individuals expresses the weights individually assigned to a set of dimensions within a pre-established range.     

Labour adjustment costs: Estimation of a dynamic discrete choice model using panel data for Greek manufacturing firms

In this paper we estimate a dynamic structural model of employment at firm level. Our dataset consists of a balanced panel of 2790 Greek manufacturing firms. The empirical evidence of this dataset stresses three important stylized facts: (a) there are periods in which firms decide not to change their labour input, (b) there are periods of large employment changes (lumpy nature of labour adjustment) and (c) the commonality is employment spikes to be followed by smooth and low employment growth periods. Following Cooper and Haltiwanger [Cooper, R.W. and Haltiwanger, J. “On the Nature of Capital Adjustment Costs”, Review of Economic Studies, 2006; 73(3); 611–633], we consider a dynamic discrete choice model of a general specification of adjustment costs including convex, non-convex and “disruption of production” components. We use a method of simulated moments procedure to estimate the structural parameters. Our results indicate considerable fixed costs in the Greek employment adjustment.     

A supply chain network equilibrium model with a smoothing newton solution scheme

ABSTRACT

Considering that a supply chain comprises several independent decision makers, a supply chain network equilibrium model that consists of manufacturers, retailers and consumers is developed. After analysing the optimal conditions of various decision makers in the model, the equilibrium condition is established as an equivalent, finite-dimensional variational inequality formulation and is solved by a smoothing Newton method. The global and quadratic convergence of the method is established. The numerical results show the rapid convergence of the method. Additionally, the rapid convergence of the smoothing Newton method is beneficial when solving a complicated network model in the real world.     

Asymptotic normality of M-estimators in a semiparametric model with longitudinal data

Suppose that the longitudinal observations (Y _ij , X _ij , t _ij ) for i = 1, . . . ,n; j = 1, . . . ,m _i are modeled by the semiparamtric model where β ₀ is a k × 1 vector of unknown parameters, g(·) is an unknown estimated function and e _ij are unobserved disturbances. This article consider M-type regressions which include mean, median and quantile regressions. The M-estimator of the slope parameter β ₀ is obtained through piecewise local polynomial approximation of the nonparametric component. The local M-estimator of g(·) is also obtained by replacing β ₀ in model with its M-estimator and using local linear approximation. The asymptotic distribution of the estimator of β ₀ is derived. The asymptotic distributions of the local M-estimators of g(·) at both interior and boundary points are also established. Various applications of our main results are given. The research is supported in part by National Natural Science Foundation of China (Grant No. 10671089).     

Optimal monetary policy in a new Keynesian model with animal spirits and financial markets

This article presents a macro-finance-interaction model that integrates a NKM with bounded rationality and an agent-based financial market model. We derive four interactive channels between the two sectors where two channels are strictly microfounded. We analyze the impact of the different channels on economic stability and derive optimal (conventional and unconventional) monetary policy rules. We find that coefficients of optimal Taylor rules do not significantly change if financial market stabilization becomes part of the central bank׳s objective function. Additionally, we show that rule-based, backward-looking monetary policy creates huge instabilities if expectations are boundedly rational. Our model is externally validated by showing that it generates fat tailed output growth rates.     

A two-period newsvendor model for prepositioning with a post-disaster replenishment using Bayesian demand update

Humanitarian aid agencies usually resort to inventory prepositioning to mitigate the impact of disasters by sending emergency supplies to the affected area as quickly as possible. However, a lack of replenishment opportunity after a disaster can greatly hamper the effectiveness of the relief operation due to uncertainty in demand. In this paper, a prepositioning problem is formulated as a two-period newsvendor model where the response phase is divided into two periods. The model acknowledges the demand to be uncertain even after the disaster and utilises the Bayesian approach to revise the demand of the second period. Based on the revised demand, an order is placed at the beginning of the second period to be replenished instantaneously. A two-stage solution methodology is proposed to find the prepositioning quantity and post-disaster replenishment quantity, which minimise the total expected costs of relief operations. A numerical example is presented to demonstrate the solution methodology, and sensitivity analysis is performed to examine the effect of model parameters. The results highlight the indifferent characteristics shown by the replenishment quantity with the variation in model parameters.     

Water use efficiency and public goods conservation: A spatial stochastic frontier model applied to irrigation in Southern Italy

Water used for irrigation is essential for global food production. Increased water scarcity, due to climate change, is a constraint to agricultural development, especially in arid and semi-arid areas. This increases pressure on agriculture which often manages water inefficiently and competes with other sectors for water use. Enhancing farmers’ production efficiency may lead to substantial water savings and conservation. Public sector is called to play a role in water governance and to introduce appropriate multilevel regulatory and incentive measures for better water management. This work applies a spatial stochastic frontier model to the case of high water-demanding fruit and vegetable crops in the Apulia region of Southern Italy, where water is scarce due to semi-arid climate and erratic rainfall. Using cross-sectional data from the EU Farm Accountancy Data Network, this work incorporates firm specific heterogeneity into technical efficiency analysis and implements an autoregressive specification of the inefficiency component. Results support the hypothesis that spatial heterogeneity exists in on-farm efficiency of irrigated crop production and is adequately captured by the spatial stochastic frontier model approach. Technical efficiency of farms with similar structural and management characteristics greatly varies across crops and geographical areas, because of the different natural resource endowment and agro-climatic factors. Policies providing incentives to on-farm adoption of modern water-saving technologies and measures to promote small family farm activities could effectively contribute to water conservation goal, but they should be well-articulated to account for agriculture spatial diverseness.     

Applying a markov chain model in quality function deployment

The relationships between customer requirements and technical measures are typically resolved by a cross-functional team with the assumption that the relationships are able to be identified objectively. However, due to the limited knowledge and experiences, determining the appropriate relationship could be difficult since the decision makers might not have enough information to evaluate the actual relationship. Moreover, the importance of technical measures is typically expressed in the current time period. It would be of interest to trace the future trends of technical measures since customer needs are fulfilled by technical measures. Under such circumstances, a Markov chain model could be an approach to model the relationship and monitor the trends of technical measures from probabilities viewpoints. With the needed probabilities, the dynamic relationships as well as the trends of technical measures can be performed by different time periods. Finally, the relationships and future trends of technical measures can be updated when the new information is available.     

Understanding injustice-related aggression in organizations: a cognitive model

Recent developments in the literature on workplace aggression emphasized the role of perceived injustice in the occurrence of aggressive behaviours in the workplace. The present article develops a cognitive model, which contends that perceptions of injustice are necessary but not sufficient to trigger aggressive behaviours in the workplace. Rather, retaliatory actions following perceived injustices are embedded in a nexus of personal values, blame attribution, opportunities to carry out the aggressive action, probability of retaliation from the target or a third party, and the advantages incurred by such actions. The paper develops three constructs, injustice threshold, repertoire of perceived injustices and psychological suspended sentence, to explain individual reactions to perceived injustices. Implications for empirical investigations and practice are discussed.     

Macroeconomic forecasting with a vector arima model: A case study of the finnish economy

The vector ARIMA (VARIMA) model is a multivariate generalization of the univariate ARIMA model. VARIMA can accomodate assumptions on exogeneity and on contemporaneous relationships. Exogeneous forecasts and non-zero future shocks make it possible to generate alternative forecasts. In a case study VARIMA well describes developments in the 1970's and successfully competes with judgemental methods and ARIMA in providing a general outlook of the early 1980's.     

A characterization of Ramsey equilibrium in a model with limited borrowing

This paper considers a one-sector economic growth model with several infinitely-lived heterogeneous households, who differ both in the discount factors as well as preferences over consumption. Unlike the extreme form of borrowing constraint observed in the classical Ramsey model, recently surveyed in Becker (2006), we allow limited borrowing by the households and prove the existence of a perfect foresight equilibrium. We also show that irrespective of production technology employed by the firms, the capital stock sequence converges to the steady state stock and from some time onward all impatient households are in the maximum borrowing state, whereas the most patient household owns entire capital stock and the debts of all other households.     

Portfolio management with robustness in both prediction and decision: A mixture model based learning approach

We develop in this paper a novel portfolio selection framework with a feature of double robustness in both return distribution modeling and portfolio optimization. While predicting the future return distributions always represents the most compelling challenge in investment, any underlying distribution can be always well approximated by utilizing a mixture distribution, if we are able to ensure that the component list of a mixture distribution includes all possible distributions corresponding to the scenario analysis of potential market modes. Adopting a mixture distribution enables us to (1) reduce the problem of distribution prediction to a parameter estimation problem in which the mixture weights of a mixture distribution are estimated under a Bayesian learning scheme and the corresponding credible regions of the mixture weights are obtained as well and (2) harmonize information from different channels, such as historical data, market implied information and investors׳ subjective views. We further formulate a robust mean-CVaR portfolio selection problem to deal with the inherent uncertainty in predicting the future return distributions. By employing the duality theory, we show that the robust portfolio selection problem via learning with a mixture model can be reformulated as a linear program or a second-order cone program, which can be effectively solved in polynomial time. We present the results of simulation analyses and primary empirical tests to illustrate a significance of the proposed approach and demonstrate its pros and cons.     

Adverse effects of leverage and short-selling constraints in a financial market model with heterogeneous agents

This paper investigates the impact of leverage and short-selling constraints on financial market stability. Investors׳ demand is modelled in a well-known asset pricing model with heterogeneous beliefs. In particular, I generalise the heterogeneous agents model of Brock and Hommes (1998) and Anufriev and Tuinstra (2013) to allow for leverage constraints as well as a short-selling tax. I consider two examples of adaptive belief systems describing the coevolution of prices and investors׳ beliefs. First, if the market is inhabited by fundamentalist and chartist traders, demand constraints have potential adverse effects and may restrict the stabilising fundamentalist strategy such that mispricing and price volatility increase. Second, if the market is inhabited by fundamentalists, optimists and pessimists with fixed beliefs, demand constraints drive down price volatility, but mispricing remains. The results suggest the stabilising effects of demand constraints in financial markets are limited. Only if asset prices are too high compared to fundamentals, policy makers should consider constraining leverage ratios in order to deflate financial bubbles.     

新型城镇化引导下的西部地区县域城乡空间重构研究——以青海省都兰县为例

首先梳理新型城镇化与城乡空间重构关系,在分析都兰县城乡空间现状基础之后,分析了新型城镇化对都兰县空间重构的要求,提出了以功能提升优化城乡空间结构、以产业发展促进城乡空间增长、以基础设施建设促进空间集聚、以质量提升强化城乡空间管治的县城城乡重构机制,并对县城、城镇、工矿区、乡村中心社区等的空间重构发展模式进行了探索和研究.