Portfolio optimization using dynamic factor and stochastic volatility: evidence on Fat‐tailed errors and leverage

The portfolio optimization problem is investigated using a multivariate stochastic volatility model with factor dynamics, fat‐tailed errors and leverage effects. The efficient Markov chain Monte Carlo method is used to estimate model parameters, and the Rao–Blackwellized auxiliary particle filter is used to compute the likelihood and to predict conditional means and covariances. The proposed models are applied to sector indices of the Tokyo Stock Price Index (TOPIX), which consists of 33 stock market indices classified by industrial sectors. The portfolio is dynamically optimized under several expected utilities and two additional static strategies are considered as benchmarks. An extensive empirical study indicates that our proposed dynamic factor model with leverage or fat‐tailed errors significantly improves the predictions of the conditional mean and covariances, as well as various measures of portfolio performance.     

ASIAN DEVELOPMENT STRATEGIES: CHINA AND INDONESIA COMPARED

China's and Indonesia's development strategies have been compared with others, but rarely with each other. Radically different political contexts have produced both similar and distinctly different development patterns. Each using formal planning, Indonesia spurred radical reforms to promote growth, whereas China opted for incremental reforms to ‘grow out of the Plan’, as a political device and to discover what policies and institutions worked. Both strategies produced environments largely conducive to rapid development. Indonesia relied on a few economic technocrats to oversee development; China used decentralisation and party reforms to create a credible environment for non-state investment. Both shared concern for agricultural reform and food security; both opted to open up for trade—China gradually, Indonesia radically. Both did well in growth and poverty reduction following reform. China's growth performance is in a league of its own, especially since Indonesia's Asian crisis setback, but Indonesia had more equitable growth and survived a difficult political transition with, in hindsight, modest costs.     

Existence of a continuum of equilibria in a monetary random-matching model

In this paper, we study a monetary random-matching model where both goods and money are perfectly divisible, production is costly, and there is no exogenous upper bound on agents' money holdings, information on which is private to the agent. We show that there is a continuum of stationary equilibria where agents have either no money or a set amount, and buyers spend all their money. As in the previous studies, the equilibrium value function is step-like, which emerges as a self-fulfilling prophecy. The endogenous upper bound on agents' money holdings is the result of private information on agents' money holdings. Buyers post an offer that is accepted only by sellers without money, who set a higher value on money.     

Role of Information Rents in Relational Contracts

We study a repeated contracting model in which the agent has private information and the performance measure is unverifiable. In an optimal stationary contract, when the discount factor is not high, the principal's objective shifts from purely reducing the information rent toward increasing the total surplus to sustain the relational contract. As a result, the total surplus is not monotonically increasing in the discount factor and could decrease when the unverifiable performance measure becomes verifiable.     

Identification of Dynamic Models of Rewards Programme

“Frequent‐buyer” rewards programmes are commonly used by companies as a marketing tool to compete for market share. They provide a unique environment for studying consumers’ forward‐looking behaviour. The consumer's problem on accumulating reward points can be formulated as a stationary infinite horizon discrete choice dynamic programming model. We show that the parameters of this model, including the discount factor, are well‐identified. In particular, it is possible to identify state‐dependent discount factors (i.e. discount factors can vary with the number of reward points). We discuss how this identification result is related to the goal‐gradient hypothesis studied in the consumer psychology literature.     

Relational contracting and endogenous formation of teamwork

We study a relational contracting model with two agents where each agent faces multiple tasks: effort toward the agent's own project and helping effort toward another agent's project. We show that the optimal task structure is either specialization without help or teamwork with a substantial amount of help: teamwork with a small amount of help is never optimal. Specialization with high‐powered incentives can be implemented by relative performance evaluation. However, under teamwork, the evaluation scheme must be substantially different to overcome the multitasking problem. Consequently, a small amount of help is dominated by specialization with high powered incentives.     

On Multitasking and Job Design in Relational Contracts*

We investigate job design problems in relational contracting environments with multitasking and an aggregated and distorted performance measurement. Compared to assigning all the tasks to a single agent, assigning the tasks to multiple agents mitigates misallocation of effort among the tasks but tightens the self-enforcing constraint. Consequently, task separation is optimal if and only if the discount factor is high. Some tasks may not be assigned to the agents at all under the optimal job design. When the principal provides explicit incentives as well, it may be the case that task bundling is suboptimal for any discount factor.     

THE LABOUR FOOTPRINT: A FRAMEWORK TO ASSESS LABOUR IN A COMPLEX ECONOMY

As addressing labour becomes crucial in the move towards sustainability, there is the need for assessment tools suitable for current complex economic systems. This article presents an input–output based framework (‘labour footprint’) for evaluating labour issues behind the production of different economic commodities, including entire supply chains. In line with the guidelines of the International Labour Organization, six labour issues are considered: collective bargaining, forced labour, child labour, gender inequality, hazardous work, and social security. This conceptual article sets to (a) define this footprint's labour dimensions, (b) cite relevant data sources, (c) describe its calculation, (d) illustrate its application through a case study, and (e) discuss this framework's relevance from ‘conscious consumption’, ‘supply chain responsibility’, and regulators' standpoints. Since it advances the evaluation of fundamental labour issues and the scope of multi-criteria analyses, this footprint may be a valuable tool for sustainability assessments.     

Software piracy and outsourcing in two-sided markets

This paper examines the role of software piracy in digital platforms where a platform provider makes a decision of how much software to produce in-house and how much to outsource from a third-party software provider. Using a vertical differentiation model, we theoretically investigate how piracy influences the software outsourcing decision. We find that when piracy is intermediate, the loss in in-house software profits due to piracy outweighs the loss in licensing fee profits. As a result, an increase in piracy leads to more outsourcing. However, when piracy is high, it becomes too expensive for the platform provider to subsidize the software provider, resulting in a decrease in outsourcing. Moreover, when software variety is also endogenously chosen by firms, the platform provider’s incentive to develop software variety in-house depends not only on the return from software profits but also on the return from hardware profits. Under such a situation, an increase in piracy always leads to less outsourcing and less total software variety. To provide additional insights on the outsourcing decision, we conduct empirical analyses using data from the U.S. handheld video game market between 2004 and 2012. This market is a classical two-sided market, dominated by two handheld platforms (Nintendo DS and Sony PlayStation Portable) and is known to have suffered from software piracy significantly. Our regression results show that in this market, piracy increases outsourcing but has no effect on the total software variety.

     

A practitioner’s guide to Bayesian estimation of discrete choice dynamic programming models

This paper provides a step-by-step guide to estimating infinite horizon discrete choice dynamic programming (DDP) models using a new Bayesian estimation algorithm (Imai et al., Econometrica 77:1865?C1899, 2009a) (IJC). In the conventional nested fixed point algorithm, most of the information obtained in the past iterations remains unused in the current iteration. In contrast, the IJC algorithm extensively uses the computational results obtained from the past iterations to help solve the DDP model at the current iterated parameter values. Consequently, it has the potential to significantly alleviate the computational burden of estimating DDP models. To illustrate this new estimation method, we use a simple dynamic store choice model where stores offer ??frequent-buyer?? type rewards programs. Our Monte Carlo results demonstrate that the IJC method is able to recover the true parameter values of this model quite precisely. We also show that the IJC method could reduce the estimation time significantly when estimating DDP models with unobserved heterogeneity, especially when the discount factor is close to 1.