Stock prices and long-run demand for money: evidence from Malaysia

This paper investigates the money demand function for Malaysia in the 1971-1996 period using the multivariate cointegration and error correction model methodology. The results suggest that a stable long-run relationship exist between real M2, the interest rate differential, income and stock prices. Stock prices have a significant negative substitute effect on long-run as well as short-run broad-money demand (M2) and its omission can lead to serious misspecification in the money demand function. The analysis from the vector error correction model (VECM) and the Toda & Yamamoto (1995) causality tests find that money is endogenous and that there is at least a unidirectional relationship between stock prices and real M2. Stock prices Granger cause real M2 indirectly through income between interest rates and stock prices and stock prices and money stock. This paper comes to the conclusion that due to the endogeneity of money, M2 cannot be completely controlled by Malaysia's central bank. Therefore, in formulating future monetary policy, the response of money demand to stock prices should be considered.     

A cointegration approach to modeling human capital formation,self-employment,and economic growth: evidence from Pakistan

This study aims to empirically investigate the dynamics of relationship among human capital formation, self-employment (SE), and economic growth in Pakistan. Using quarterly data of primary school enrollment, SE, and GDP per capita, we employed ARDL bound testing approach to cointegration covering the time span of 1995–2010. We found that in the long run, primary school enrollment, high school enrollment and SE have significant impact on economic growth. Enrollment in primary schools (EP) has a strong positive and significant impact on economic growth, whereas enrollment in high school has a relatively small positive and significant impact on economic growth in the long run in Pakistan. Further, SE has a small, positive and significant impact on economic growth in the long run. In short run, enrollments in high schools and SE have weak positive impact on economic growth whereas, EP has a strong positive and significant impact on economic growth in Pakistan. Further it is found that that there is unidirectional long run causality from self employment to economic growth followed by the bidirectional short run causality between economic growth and high school enrollment, GDP per capita and primary school enrollment, high school enrollment and primary school enrollment.     

Banking deregulation and allocative efficiency in Pakistan

This article examines the impact of deregulation policies on allocative efficiency of banks in Pakistan. It investigates whether deregulation has impacted the pattern of allocative efficiency of banks and explores which bank ownership segment has been more responsive. It uses data from 1991 to 2005 and explicitly models allocative inefficiency by using the translog shadow cost-share system. Empirical results show that overregulation and imperfect market structure hampers the ability of banks to make competitive decisions. We find evidence of allocative inefficiency leading to over-utilization of labour and deposits vis-à-vis operating cost. Empirical results for time-varying allocative efficiency show declining levels of allocative inefficiency for state-owned and private banks in post-reform period. Deregulation policies induce state-owned banks to decrease over-utilization of labour relative to deposits and operating cost while private banks succeed in using operating cost closer to optimal levels. Hence, policymakers have latitude to introduce more reforms without jeopardizing allocative efficiency.     

Optimal rules and robust Bayes estimation of a Gamma scale parameter

For estimating an unknown scale parameter of Gamma distribution, we introduce the use of an asymmetric scale invariant loss function reflecting precision of estimation. This loss belongs to the class of precautionary loss functions. The problem of estimation of scale parameter of a Gamma distribution arises in several theoretical and applied problems. Explicit form of risk-unbiased, minimum risk scale-invariant, Bayes, generalized Bayes and minimax estimators are derived. We characterized the admissibility and inadmissibility of a class of linear estimators of the form $cX\,{+}\,d$ , when $X\sim \varGamma (\alpha ,\eta )$ . In the context of Bayesian statistical inference any statistical problem should be treated under a given loss function by specifying a prior distribution over the parameter space. Hence, arbitrariness of a unique prior distribution is a critical and permanent question. To overcome with this issue, we consider robust Bayesian analysis and deal with Gamma minimax, conditional Gamma minimax, the stable and characterize posterior regret Gamma minimax estimation of the unknown scale parameter under the asymmetric scale invariant loss function in detail.     

A note on mean testing for high dimensional multivariate data under non‐normality

A test statistic is considered for testing a hypothesis for the mean vector for multivariate data, when the dimension of the vector, p, may exceed the number of vectors, n, and the underlying distribution need not necessarily be normal. With n,p→∞, and under mild assumptions, but without assuming any relationship between n and p, the statistic is shown to asymptotically follow a chi‐square distribution. A by product of the paper is the approximate distribution of a quadratic form, based on the reformulation of the well‐known Box's approximation, under high‐dimensional set up. Using a classical limit theorem, the approximation is further extended to an asymptotic normal limit under the same high dimensional set up. The simulation results, generated under different parameter settings, are used to show the accuracy of the approximation for moderate n and large p.     

Non-linearities in Real Interest Rate Parity: Evidence from OECD and Asian Developing Economies

Abstract

This paper investigates the validity real interest rate parity (RIP) for a sample of 19 OECD and Asian developing economies. The distinction of this paper is that we exploit both linearity and non-linear unit root tests as advocated by Dufrénot et al. (Applied Economics, 38, pp. 203–229, 2006) to validate the parity. The major finding are: (i) the alignments from real interest rate differentials (RIDs) are corrected in a non-linear fashion and that the adjustments is asymmetric in both size and speed; (ii) that RIP holds for the developed and developing countries; and (iii) the empirical results are invariant with respect to the US, Japan or Germany as the centre country.     

The Desirability of forgiveness in regulatory enforcement

I present a model that explains two common features of regulatory enforcement: selective forgiveness of noncompliance, and the collection of information on a firm’s compliance activities and not just its compliance status. I show that forgiving noncompliance is optimal if the information on a firm’s compliance activities constitutes sufficiently strong evidence of the firm having exerted a high level of compliance effort. The key benefit of forgiving noncompliance is a reduction in the probability with which the firm needs to be monitored.     

Collaborating for success: managerial perspectives on co-branding strategies in the fashion industry

Abstract

This article investigates the nature of co-branded relationships within the fashion industry. Existing co-branding literature focuses heavily on consumer evaluations, and many studies explore FMCG and electronics markets, within which ingredient co-branding is common. When two brands from the fashion industry collaborate, both brands exist independently and do not rely on ‘ingredients’ for developing a new product and, therefore, presenting an opportunity for exploring the drivers and types of relationships that could exist. This study adopts an interpretive method of investigation using in-depth interviews with brand managers. Findings provide empirical support for value creation through different relationship levels (such as brand/awareness co-branding, values endorsement and complementary competence co-branding) while highlighting some challenges and risks for co-branding in practice. This article discusses implications for theory development and practice and highlights avenues for future research.     

Exchange-rate variability and industry trade flows between Malaysia and Japan

This research investigates the exchange-rate risk sensitivity of Malaysian bilateral trade flows with its important trading partner, Japan. To this end, bounds testing approach to co-integration is applied using industry level data over the monthly period 2000–2013. Findings suggest that above the one-third of the total co-integrated export (43.86%) and import (34.54%), industries experiences the ringgit/yen variability effect in the short run. However, this effect sustains in relatively less number of export (14.03%) and import (32.73%) industries in the long run. It is interesting to note that exchange-rate risk boosts trade flows in the majority of these affected industries.     

Multi-stage purchase decision models: Accommodating response heterogeneity, common demand shocks, and endogeneity using disaggregate data

The most comprehensive models of purchase behavior for frequently purchased supermarket items explain households' purchase incidence decisions (whether to buy), brand choice decisions (what to buy), and purchase quantity decisions (how much to buy). In this study, we develop a three-stage purchase incidence/brand choice/purchase quantity model for household-level data in which all three stages are specified with (i) random coefficient distributions for model covariates and (ii) random effect distributions to account for unobserved factors affecting demand (known as common demand shocks), while also (iii) controlling for the effects of endogeneity on prices. Compared to current state-of-the-art models for multi-stage purchase decisions, the results show improvements in fit and forecasting accuracy when purchase behaviors are modeled with all of these components in combination. Perhaps more importantly, when common demand shocks are ignored, substantial differences in parameter estimates and diagnostic information about consumer behavior are likely (median differences in parameter estimates are 10% and 20% in two product categories), which impact managerial deliberations about price and promotion policies. Further, failure to account for common demand shocks affects the mean and variance of random coefficient distributions in unpredictable directions, which could produce results that encourage managers to pursue inappropriate and costly micro-level product marketing strategies.