Search

In this paper, we introduce the delayed-advanced Kaldorian business cycle model and consider how time-delay and time-advance affect economic fluctuations. Given the asymptotic stability of the original Kaldor model, we first show that an approximated Kaldor model by a Taylor series expansion can accurately describe the dynamics of the delayed Kaldor model. We also confirm that the delay has a destabilizing effect. When time-delay is replaced with time-advance, we have an advanced Kaldor model. Taking the advanced capital stock formulation, we derive the stability conditions and find that the time-advance has a stabilizing effect. Lastly, we examine these opposite-signed effects in a modified delayed-advanced model. [ABSTRACT FROM AUTHOR]

In this paper, an inventory problem where the inventory cycle must be an integer multiple of a known basic period is considered. Furthermore, the demand rate in each basic period is a power time-dependent function. Shortages are allowed but, taking necessities or interests of the customers into account, only a fixed proportion of the demand during the stock-out period is satisfied with the arrival of the next replenishment. The costs related to the management of the inventory system are the ordering cost, the purchasing cost, the holding cost, the backordering cost and the lost sale cost. The problem is to determine the best inventory policy that maximizes the profit per unit time, which is the difference between the income obtained from the sales of the product and the sum of the previous costs. The modeling of the inventory problem leads to an integer nonlinear mathematical programming problem. To solve this problem, a new and efficient algorithm to calculate the optimal inventory cycle and the economic order quantity is proposed. Numerical examples are presented to illustrate how the algorithm works to determine the best inventory policies. A sensitivity analysis of the optimal policy with respect to some parameters of the inventory system is developed. Finally, conclusions and suggestions for future research lines are given. [ABSTRACT FROM AUTHOR]

This paper investigates the variation in nonperforming loans over the economic cycle and the effect of past returns based on a nonparametric quantile analysis of the largest Islamic banks in the United Kingdom and Turkey from 2010 to 2019. The findings show a weak variation in nonperforming loans that increases with an increasing return on assets and a decreasing return on equity and decreases in an inverse scenario. As a result, the credit risk of Islamic banks is countercyclical. We suggest that the inverse relationships evidence the existence of trade-offs within bank returns and credit risk. Thus, banks' past profitability and risk mitigation are determinants of asset quality. These findings provide support for risk-taking and risk-sharing principles in which flight-to-safety mirrors the calibration of risk factors in a disruptive economy. Our estimates indicate that nonparametric quantile regression captures considerably more variation in a risk-return analysis. [ABSTRACT FROM AUTHOR]

This study addresses interest rate sensitivity of emerging market corporate debt. Previous research suggests that interest rate sensitivity of corporate bonds depends on residual maturity of issues, creditworthiness of issuers, embedded options and other idiosyncratic factors. However, the dependence of interest rate sensitivity on phases of the business cycle has not received an appropriate academic attention. This paper provides empirical evidence and theoretical interpretation of a dichotomy of interest rate sensitivity across the phases of the cycle, and sheds light on how credit spreads respond to interest rates. The historical span of the research covers the period of 2004–2016. The findings imply that hedging interest rate risk ought to be a dynamic process and take into consideration where the economy is positioned in the current business cycle. This research provides important insights on the nature of interest rate sensitivity, capable of enhancing financial stability and improving efficiency of financial system. [ABSTRACT FROM AUTHOR]

This paper measures the efficiency and convergence of 37 stock exchanges in 35 countries over the period from 2006 to 2014, a period that encompasses a full business cycle of growth, recession and recovery. We combine a multi-stage data envelopment analysis with the window analysis approach to filter out the impact of economic environmental variables on stock exchange efficiency in the provision of trading services and track the efficiency changes over time. We show that economic growth, inflation and financial development are important drivers of efficiency. Lagging stock exchanges are catching up to the leading stock exchanges in terms of technical efficiency, pure technical efficiency and scale efficiency. Exchanges in developed countries converge faster than those in the emerging countries and the dispersion of the efficiency levels over the whole sample and the subsamples of developed vs emerging country stock exchanges diminished. Finally, stock exchanges in emerging countries are catching up to the stock exchanges in the developed countries and the dispersion of the efficiency levels between them also diminished. Overall, our findings indicate that integration has taken place in the stock exchange industry over the sample period. [ABSTRACT FROM AUTHOR]

This paper examines the time-varying nature of various decisive factors on cash holding decisions. First, we revisit the issue of cash holding determinants of U.S. corporations and argue that firm cash holding predictability is time-varying. To this end, this research proposes a novel empirical framework that builds on the impact of business cycles on firm cash holding’s predictability. Using a three-stage empirical analysis, we also posit that the conventional argument on the EPU-CASH relationship is dependent on the time-varying market structure. Earlier studies have shown that economic policy uncertainty may increase the propensity of cash holding at the firm level. To estimate the theoretical assumption and capture different dynamic relationships, we convert monthly EPU data to annual and develop a cash quantile regression model including several financial characteristics. Employing a large sample of U.S. non-financial firms and non-utilities, we initially estimate 6-year rolling fixed window quantile regressions during the 1970–2016 period. The resulting series of beta estimates are regressed on economic policy uncertainty. The main results confirm the time-varying nature of determinants related to corporate liquidity management. Our findings add a new dimension to the existing literature and therefore be important to the market participants for portfolio allocation in the developed markets. Overall, the new methodology presented in this study contributes to the field of operational research by providing a robust approach to analyze policy uncertainty and its impact on cash management. [ABSTRACT FROM AUTHOR]