Homeownership as a Constraint on Asset Allocation

Personal preferences and financial incentives make homeownership desirable for most families. Once a family purchases a home they find it impractical (costly) to frequently change their ownership of residential real estate. Thus, by deciding how much home to buy, a family constrains their ability to adjust their asset allocation between residential real estate and other assets. To analyze the impact of this constraint on consumption, welfare, and post-retirement wealth, we first investigate an individual’s optimal asset allocation decisions when they are subject to a “homeownership constraint.” Next, we perform a “thought experiment” where we assume the existence of a market where a homeowner can sell, without cost, a fractional interest in their home. Now the housing choice decision does not constrain the individual’s asset allocations. By comparing these two cases, we estimate the differences in post-retirement wealth and the welfare gains potentially realizable if asset allocations were not subject to a homeownership constraint. For realistic parameter values, we find that the homeowner would require a substantial increase in total net worth to achieve the same level of utility as would be achievable if the choice of a home could be separated from the asset allocation decision. The robustness of the analysis is evaluated with respect to the model’s parameters and initial state variables. We find that changes in the values of the constraint (i.e., the value of the home) and the expected real rate of home value appreciation are the only state variables or parameter that is associated with a large change in asset allocation and/or the burden imposed by the housing constraint. This finding suggests the importance of a detailed examination of the impact of inter-regional differences in home prices and expected rates of appreciation on asset allocation and post-retirement wealth.     

Quantile serial dependence in crude oil markets: evidence from improved quantilogram analysis with quantile wild bootstrapping

We examine the quantile serial dependence in crude oil prices based on the Linton and Whang’s quantile-based portmanteau test which we improved by means of quantile wild bootstrapping (QWB). Through Monte Carlo simulation, we find that the quantile wild bootstrap-based portmanteau test performs better than the bound testing procedure suggested by Linton and Whang. We apply the improved test to examine the efficiency of two crude oil markets – WTI and Brent. We also examine if the dependence is stable via rolling sample tests. Our results show that both WTI and Brent are serially dependent in all, except the median quantiles. These findings suggest that it may be misleading to examine the efficiency of crude oil markets in terms of mean (or median) returns only. These crude oil markets are relatively more serially dependent in non-median ranges.     

Collaboration at work: An integrative multilevel conceptualization

The term collaboration has been used throughout a variety of research disciplines to describe multiple types of interaction; yet, a unified, comprehensive definition of the construct remains elusive. This lack of clarity regarding the distinctions and commonalities between collaboration and other interaction concepts has resulted in conceptual confusion that affects practice and research in human resource management. Practitioners see collaboration as more of a buzzword than as an effective human resource strategy. Previous theory development efforts have not yet taken a comprehensive multidisciplinary approach. This has resulted in failure to integrate key themes across disciplines into an overall view of collaboration, which is a commonplace practice in business and military sectors alike. This paper describes a multidisciplinary conceptualization of collaboration and discusses the implications of this integrative theory to human resource management and strategy development as well as future research efforts.