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This study investigates the dynamic production structure of the Japanese manufacturing industry by using the adjustment cost approach. The study is to shed some light on the unique dynamic structure of the Japanese manufacturing industry. The study attempts to help design and predict industrial policies that are implemented to enhance domestic investments by the Japanese government.

This study obtains a system of dynamic factor demand and output supply equations by applying the dual approach to the intertemporal value function as represented by the Hamilton–Jacobi equation. By using industrial panel data for 1973–2012 of the Japanese manufacturing industry, the study estimates the system of the behavioral equations and corresponding elasticities. The study uses hypothesis tests and dynamic elasticities to investigate the dynamic structure of the Japanese manufacturing industry.

Estimation results show that labor and capital are quasi-fixed variables that adjust about 0.2 percent annually to the long-run optimum levels. Estimated adjustment rates are very slow as often presumed about the Japanese manufacturing industry, which uses lifetime employment practice and slow decision-making process in investment decisions. The results also show that output supply and factor demand elasticities vary greatly depending on time horizon. Factor demand increases when its own price increases in the short run, suggesting that factor adjustment is mostly determined factor prices in the past due to sluggish factor adjustment. However, factor demand becomes a normal downward-sloping curve in the long run as factor adjustment gets completed.

Japanese manufacturing firms hire employees through lifetime contract to exploit the benefits of dynamic learning-by-doing and execute investments carefully considering all the possible impacts. Under the strategy, adjustment costs for changing workers and capital stock are minimized. Dynamic adjustment model is expected to shed some light on the unique dynamic structure of the Japanese manufacturing industry. However, researches regarding the dynamic factor adjustment of the Japanese manufacturing industry are hard to find. This study is expected to fill the research vacuum.

The purpose of this paper is to develop a hierarchical model to rank the challenges faced by the private Malaysian higher education institutions (HEIs) in the provision of quality education and subsequently their corresponding critical success factors (CSFs) to address those challenges.

A sequential mix method was adopted in this study. Semi-structured interviews with 29 participants were initially conducted to identify the challenges and CSFs. This was followed by a questionnaire survey involving 158 respondents to prioritise the identified findings. Thematic analysis was conducted in the qualitative stage, uncovering the challenges and their corresponding CSFs. Data for both stages were accumulated from internal and external stakeholders of Malaysian private HEIs. Finally, the four stages of the analytic hierarchy process (AHP) were applied to rank the challenges and CSFs.

The qualitative stage identified eight challenges, i.e. “academics”, “facilities”, “students”, “programmes and curriculum”, “competition”, “accreditation”, “finance” and “research” together with their corresponding CSFs. The AHP enables the ranking of these challenges. “Finance” has been found to be the most crucial challenge and “high competency in managing the institution’s finance” as the most important CSF to address this challenge.

As the study restricted its focus on Malaysian private HEIs, the results may not be generalised for public HEIs and foreign private HEIs operating in Malaysia.

The hierarchical model developed in this study is deemed important for implementation to resolve the prioritised challenges. It spells out the specific areas in which the resources of Malaysian private HEIs need to be prudently disbursed and properly managed.

This paper aims to explore the trade-off between liquidity, risk and return under sectoral diversification across distinct economic settings and investment strategies.

A novel multi-objective portfolio model is proposed to assess investment decisions under sectoral diversification, where the objective functions and constraints are interval-valued. The objective functions used are risk minimization (through the semi-absolute deviation measure of risk), maximization of liquidity (using turnover as a proxy) and the maximization of logarithmic return. Besides coherence constraints (imposing that the sum of the percentages of investment assigned to each stock should be equal to 100%), constraints regarding the maximum proportion of capital that can be invested (ensuring a minimum level of diversification) and cardinality constraints (to account for transaction costs) are also imposed.

Besides the trade-off between return and risk, the study findings highlight a trade-off between liquidity and return and a positive relationship between risk and liquidity. Under an economic crisis scenario, the trade-off between return and liquidity is reduced. With the economic recovery, the levels of risk increase when contrasted with the setting of the economic crisis. The highest liquidity levels are reached with the economic boom, whereas the highest returns are obtained with the economic recession.

This paper suggests a new modeling approach for assessing the trade-offs between liquidity, risk and return under different scenarios and investment strategies. A new interactive procedure inspired on the reference point approach is also proposed to obtain possibly efficient portfolios according to the investor's preferences. Regarding previous approaches suggested in the literature, this new procedure allows obtaining both supported and unsupported efficient solutions when cardinality constraints are included.

The paper introduces a resource-based linear programming model for resource optimization in small innovative enterprises (SIE).

The model is grounded on resource-based view on the firm and dynamic capabilities approach. Linear programming technique is used to provide the actual framework to the resource-based model.

The paper introduces a new resource-based linear programming model for resource optimization in small innovative enterprises. The conceptual model is grounded on resource-based view (RBV) and dynamic capabilities strategy. The RVB of firm and firm strategy is based on the concept of economic rent. Linear programming technique is used to provide the actual framework to the resource-based model. In developing the versatility concept, study suggests a distinct sight regarding resource fungibility. Study classifies resources into multipliable, rentable and expendable resources to increases adequacy of the model. The developed model includes both tangible and intangible assets such as human capital. The survival rate of SIE in the early stages of life cycle is very low due to the competition among SIEs. In this regard, the greatest advancement of the developed resource-based linear programming model is its simplicity and versatility which is much desirable for the SIE especially in their initial stages of the life cycle. Kelliher and Reinl (2009) argued that micro firms have unique advantage over bigger firms in following term: rate of learning or redeployment of strategy in micro firms is faster than the rate of change in their environment. One very significant feature of the developed resource-based linear programming model is that mathematically the proposed model could easily be transformed into mixed integer or stochastic linear programming models to meet the time variant requirement of small firms especially when it expands its operation.

The survival rate of SIE in the early stages of life cycle is very low due to the competition among SIEs. In this regard, the greatest advancement of the developed resource-based linear programming model is its simplicity and versatility which is much desirable for the SIE especially in their initial stages of the life cycle. Kelliher and Reinl (2009) argued that micro firms have unique advantage over bigger firms in following term: rate of learning or redeployment of strategy in micro firms is faster than the rate of change in their environment. One very significant feature of the developed resource-based linear programming model is that mathematically the proposed model could easily be transformed into mixed integer or stochastic linear programming models to meet the time variant requirement of small firms especially when it expands its operation.

One very significant contribution of the present study is that the study develops a new resource-based model for SIE especially for the SIE in the initial stages of the life cycle, to gain competitive advantages. Furthermore, the present study contributes to the existing literature in strategy at least in three senses as mentioned below: 1. further addition of SIE research based on the RBV and dynamic capabilities in the strategy literature 2. in developing the versatility concept, the study suggests a distinct sight regarding resource fungibility and it classifies resources into three categories as follows: multipliable, rentable and expendable resources to increases adequacy of the model. 3. Finally, the study introduces a new resource-based linear programming model for SIE resources allocation. To the best of author’s knowledge, no such similar model is introduced by any previous studies for small firm. The greatest advancement of the developed resource-based linear programming model is its simplicity and versatility.

This article aims to analyze the performance and risk of landmark building in the housing sector and to evaluate their usefulness for a diversification strategy.

After comparing summary statistics on the performance of landmark building with respect to other types of housing investments, the article evaluates their usefulness for a diversification strategy. The role of landmark buildings is studied using the modern portfolio theory and evaluating the role of this type of asset in the optimal asset allocation. The analysis is performed considering both the risk/return trade-off in a one-year and a multiple-year time horizon.

The results show that a landmark building can be a good investment opportunity, especially for high-risk/return investors. A not perfect correlation of the returns of this asset class with other types of housing investments implies the existence of a minimum investment in this asset class for almost all portfolios on the efficient frontier. Results are robust with respect to the length of the investment time horizon.

The article presents a unique analysis of intra-housing market diversification opportunities focusing on the role of landmark building in the portfolio construction. Empirical evidence supports the hypothesis that real estate investors can take advantage of investing in landmark buildings in the residential sector as well because there are no reasons to limit such investments to trophy buildings in the office and commercial sectors.

Given some similarities in the banking industry and economic condition across Vietnam, China and India, the purpose of this paper is to estimate and compare the cost and revenue efficiency of banks across these three countries over the period 1995–2011.

This study employs the meta-frontier of Battese et al. (2004) and O’Donnell et al. (2008) which envelops the three country-frontiers to measure the cost and revenue efficiency of banks in these three countries.

This study finds that Chinese banks adopt the most advanced cost-reducing and revenue-increasing technology when providing banking products to their customers, followed by Indian banks. Indian banks are as cost-efficient as Chinese banks, but more cost-efficient than Vietnamese banks. Indian banks are as revenue-efficient as Vietnamese banks, but less revenue-efficient than Chinese banks. Over the analysis period, banks in the three countries have employed the more advanced technology in reducing costs, and they have become more cost-efficient. Nonetheless, for revenue side, the improvement in revenue efficiency and adopted technology are observed only in Chinese banks. The main source of meta-cost and meta-revenue inefficiency of these banking systems stems from undertaking inferior technology rather than managerial ability. Results from comparison across bank types show that state-owned banks (SOBs) are more cost and revenue-efficient than privately owned banks, with Indian and Chinese SOBs being the most cost- and revenue-efficient, respectively.

To improve meta-cost efficiency, Chinese and Indian banks would constitute a relevant benchmark for Vietnamese banks, while to improve meta-revenue efficiency, Chinese banks would be considered as a relevant benchmark for Vietnamese and Indian banks.

This is the first study which utilizes meta-frontier to compare cost and revenue efficiency and technology across banks in Vietnam, China and India.

The authors examine the optimal consumption decisions of households in a micro-founded framework that introduces endogenous default. They study default in the context of a two-period process, assuming three non-overlapping steps of non-payment: delinquency, non-performing loans and bankruptcy (default).

In their model, the authors extend the analysis of loan default to two periods and include agent heterogeneity by considering also saving households. In the optimization problem, the authors obtain first-order conditions for borrowers who do not repay all of their loans (comparing them to those who fully repay them) and also for savers. In addition, by using nonlinear Generalized Method of Moments (GMM), they obtain consistent estimates of the household preference parameters and present the impulse responses of borrowers' consumption to demand shocks.

The authors derive an augmented consumption Euler equation for borrowers, which is a function inter alia of an expected default factor. They estimate this equation and find non-negligible differences in preference parameters relative to values reported in the literature. Further, an ordering by size of the household discount factors is provided empirically. Finally, the impulse responses of borrowers' consumption to a demand shock are found to last more for borrowers who do not fully repay their debts.

This work represents a promising line of research by introducing default in one of the basic components of DSGE models, making the latter more appropriate for analyzing monetary and macro-prudential policies.

The purpose of this paper is to examine the operational efficiency and effects of market concentration and diversification on the efficiency of Chinese and Indian banks in the 1997-2011 period.

This study employs the two-stage bootstrap procedure of Simar and Wilson (2007) to obtain valid inferences on the efficiency scores and the efficiency determinants.

Using data set for each country separately, the authors found that the bias-corrected cost efficiency displays an upward trend in Chinese and Indian banks. This trend is consistent with profit efficiency among Chinese banks, but the trend is unclear in Indian banks. Market concentration is negatively related to cost and profit efficiencies of Chinese banks. However, market concentration is positively associated with cost efficiency, but unrelated to profit efficiency of Indian banks. In Chinese banks, diversification of revenue, earning assets and non-lending earning assets are associated with increasing profit efficiency, but their effects to cost efficiency are not clear. In Indian banks, diversification of earning assets increases profit efficiency while there are cost efficiency losses from diversification of revenue and earning assets.

Bank regulators and supervisors in China should consider establishing policies to reduce market concentration and encourage diversification of revenue, earning assets and non-lending earning assets, while increasing concentration and diversification of earning assets should be encouraged in Indian banks.

To the best of the authors’ knowledge, this is the first study employing the double bootstrap procedure proposed by Simar and Wilson (2007) which can address the problem of the two-stage data envelopment analysis or SFA estimator in the efficiency literature on Chinese and Indian banks that efficiency scores obtained in the first stage are inter-dependent, and hence violating the basic assumption in regression analysis in the second stage.

The three-sector framework (relating to agriculture, manufacturing and services) is one of the major concepts for studying the long-run change of the economic structure. This paper aims to discuss the system-theoretical classification of the structural change in the three-sector framework and, in particular, its predictability by the Poincaré–Bendixson theory.

This study compares the assumptions of the Poincaré–Bendixson theory to the typical axioms of structural change modeling, the empirical evidence on the geometrical properties of structural change trajectories and the methodological arguments referring to the laws of structural change.

The findings support the assumption that the structural change phenomenon is representable by a dynamical system that is predictable by the Poincaré–Bendixson theory. This result implies, among others, that in the long run, structural change is either transitory or cyclical and can be used in further geometrical/topological long-run structural change modeling and prediction.

Although widespread in mathematics, geometrical/topological modeling methods have not been used in modeling and prediction of long-run structural change, despite the fact that they seem to be predestined for this purpose owing to their global, system-theoretical nature, allowing for a reduction of ideology content of predictions and greater robustness of results.

The purpose of this paper is to propose the parametric bootstrap method for valuation of over-the-counter derivative (OTCD) initial margin (IM) in the financial market with low outstanding notional amounts. That is, an aggregate outstanding gross notional amount of OTC derivative instruments not exceeding R20bn.

The OTCD market is assumed to have a Gaussian probability distribution with the mean and standard deviation parameters. The bootstrap value at risk model is applied as a risk measure that generates bootstrap initial margins (BIM).

The proposed parametric bootstrap method is in favour of the BIM amounts for the simulated and real data sets. These BIM amounts are reasonably exceeding the IM amounts whenever the significance level increases.

This paper only assumed that the OTCD returns only come from a normal probability distribution.

The OTCD IM requirement in respect to transactions done by counterparties may affect the entire financial market participants under uncleared OTCD, while reducing systemic risk. Thus, reducing spillover effects by ensuring that collateral (IM) is available to offset losses caused by the default of a OTCDs counterparty.

This paper contributes to the literature by presenting a valuation of IM for the financial market with low outstanding notional amounts by using the parametric bootstrap method.