Conventional wisdom dictates that convenience goods should be distributed as intensively as possible. Still, exclusivity arrangements are rapidly gaining way in grocery retailing.
Suppliers are increasingly being forced by dominant retailers to clean up their supply chains. These retailers argue that their sustainability mandates may translate into profits for suppliers, but many suppliers are cynical about these mandates because the onus to undertake the required investments is on them while potential gains may be usurped by the mandating retailer.
Cross-training of nursing staff has been used in hospitals to reduce labor cost, provide scheduling flexibility, and meet patient demand effectively. However, cross-trained nurses may not be as productive as regular nurses in carrying out their tasks because of a new work environment and unfamiliar protocols in the new unit.
Recent studies emphasize that survey-based inflation risk measures are informative about future inflation and thus useful for monetary authorities. However, these data are typically available at a quarterly frequency whereas monetary policy decisions require a more frequent monitoring of such risks.
Suppose one uses a parametric density function based on the first four (conditional) moments to model risk. There are quite a few densities to choose from and depending on which is selected, one implicitly assumes very different tail behavior and very different feasible skewness/kurtosis combinations.
We study a new class of conditional skewness models based on conditional quantiles regressions. The approach is much inspired by work of Hal White. To handle multiple horizons I consider quantile MIDAS regressions which amount to direct forecasting—as opposed to iterated forecasting—conditional skewness.
We provide empirical evidence for the existence, magnitude, and economic cost of stigma associated with banks borrowing from the Federal Reserve's Discount Window (DW) during the 2007-2008 financial crisis.
We develop Granger causality tests that apply directly to data sampled at different frequencies. We show that taking advantage of mixed frequency data allows us to better recover causal relationships when compared to the conventional common low frequency approach.
When modeling economic relationships it is increasingly common to encounter data sampled at different frequencies. We introduce the R package midasr which enables estimating regression models with variables sampled at different frequencies within a MIDAS regression framework put forward in work by Ghysels, Santa-Clara, and Valkanov (2002).
This article presents a reduced-form model that contains frailty factors to predict mortgage default and develops a novel framework to model systematic risk of mortgages. We match default rates along multiple dimensions by extending the generalized autoregressive score (GAS) models.
Policy impact studies often suffer from endogeneity problems. Consider the case of the ECB Securities Markets Programme: If Eurosystem interventions were triggered by sudden and strong price deteriorations, looking at daily price changes may bias downwards the correlation between yields and the amounts of bonds purchased.
During retailer-initiated price wars (PWs), hundreds of brands are involved simultaneously, affecting brands’ and retailers’ positioning and ultimately making the performance outcome for individual brands difficult to predict. Likewise, the impact on brand performance after the PW, when prices are restored, is unclear.
Private labels or store brands have witnessed considerable growth in the last few decades, especially in grocery products. However, market shares of store brand vary considerably across categories, markets, and countries. A natural question of interest to academics and practitioners is what factors influence store brand market shares.
Cross-training of nursing staff has been used in hospitals to reduce labor cost, provide scheduling flexibility, and meet patient demand effectively. However, cross-trained nurses may not be as productive as regular nurses in carrying out their tasks because of a new work environment and unfamiliar protocols in the new unit.
Because security analysts, who serve as brokers between public firms and investors, arrive at their forecasts by incorporating guidance from managers, there is immense pressure on the managers to meet or beat analyst earnings forecasts; moreover, investors reward (penalize) firms for exceeding (missing) analyst forecasts.
Firms spend billions of dollars on advertising every year but remain uncertain about allocation across various advertising vehicles. Allocation decisions are even more complex as online advertising has proliferated and consumers' media usage patterns have become more fragmented.
Using an integrative approach, the authors incorporate the four mechanisms in their empirical model specification. Specifically, to model the interplay among CSR, CSI, and firm performance and to test the four mechanisms simultaneously, they propose a structural panel vector autoregression specification.
Marketing academics and practitioners alike remain unconvinced about the chief marketing officer's (CMO's) performance implications. Whereas some studies propose that firms benefit financially from having a CMO in the C-suite, other studies conclude that the CMO has little or no effect on firm performance.
Business-to-business electronic markets have emerged as robust, legitimate channels for conducting transactions, where firms participate in these markets according to their investments in the channel, such that they might participate as an expert, explorer, or passive firm.
Internet-based business-to-business platforms involve a buyer side transacting with a seller side, both of which are customers of an intermediary platform firm. Dyadic viewpoints implicit in conventional theories of customer orientation thus must be modified to apply to a triadic relationship system (seller-platform-buyer) in platform settings.