Bias-corrected estimates of reduction of post-surgery length of stay and corresponding cost savings through the widespread national implementation of fast-tracking after liver transplantation: a quasi-experimental study

Background: Fast-tracking is an approach adopted by Mayo Clinic in Florida’s (MCF) liver transplant (LT) program, which consists of early tracheal extubation and transfer of patients to surgical ward, eliminating a stay in the intensive care unit in select patients. Since adopting this approach in 2002, MCF has successfully fast-tracked 54.3% of patients undergoing LT.

Objectives: This study evaluated the reduction in post-operative length of stay (LOS) that resulted from the fast-tracking protocol and assessed the potential cost saving in the case of nationwide implementation.

Methods: A propensity score for fast-tracking was generated based on MCF liver transplant databases during 2011–2013. Various propensity score matching algorithms were used to form control groups from the United Network of Organ Sharing Standard Analysis and Research (STAR) file that had comparable demographic characteristics and health status to the treatment group identified in MCF. Multiple regression and matching estimators were employed for evaluation of the post-surgery LOS. The algorithm generated from the analysis was also applied to the STAR data to determine the proportion of patients in the US who could potentially be candidates for fast-tracking, and the potential savings.

Results: The effect of the fast-tracking on the post-transplant LOS was estimated at approximately from 2.5 (p-value?=?0.001) to 3.2 (p-value?Conclusion: The fast-track program was found to be effective in reducing post-transplant LOS, although the reduction appeared to be less than previously reported. Nationwide implementation of fast-tracking could result in substantial cost savings without compromising the patient outcome.     

Tenure Security and Long‐term Investment on Tenanted Land: Evidence from Colonial Taiwan

We use farm diary data from Taiwan in the 1920s and 1930s to estimate the impacts of a state‐wide tenancy reform on tenants’ investment in the farmland and production outcome. The reform, commencing in 1922, enhanced the tenure security for the tenants by promoting written contracts that extended tenure length from 1 year to 5–6 years, and by establishing government‐sponsored organizations for dispute settlements. Our estimations rely on a difference‐in‐difference framework, where self‐cultivated farms are used as the control group. We find that the reform encouraged tenants to make investments in the irrigation and drainage system of the farms, which is expected to have long‐lasting benefits for production. The improved irrigation/drainage system led to significant efficiency gains for the farms. In contrast, the reform did not affect tenants’ usage of fertilizer much, which benefits production for only a crop season or a year.     

How resilient is La Réunion in terms of international tourism attractiveness: an assessment from unit root tests with structural breaks from 1981-2015

Even if local policymakers increasingly claim that tourism is one of the key factors of future economic development for the French small island La Réunion, international tourist arrivals are observed to be locked in a stagnation phase since the beginning of the 2000s. Starting from this stylized fact, this article aims to study if this phenomenon results from major external events hurting this economy regularly. Next, by using univariate unit root procedures with structural breaks, we test for evidence of permanent or transitory effects of external shocks on international tourist inflows (total, by source markets, and by category) over the period 1981–2015. Finally, the empirical analysis allows us to reject the null of a unit root. Then, stagnation of tourism arrivals to La Réunion is not due to exogenous shocks but probably results from endogenous impediments within the domestic tourism industry and unsuitable public policies.     

Gini-PLS Regressions

Journal of Quantitative Economics - Data contamination and excessive correlations between regressors (multicollinearity) constitute a standard and major problem in econometrics. Two techniques...     

A categorical modeling approach to analyzing new product adoption and usage in the context of the building-materials industry

A high proportion of non-adopters is prevalent in any market where the product under consideration is relatively new or has a low acceptance rate. This results in a low proportion of adopters in a representative sample. In adoption or product usage modeling such high proportion of zeros in the dependent variable may be addressed by zero-inflated models, by modeling the product adoption and usage as a function of two latent processes. This paper considers a zero-inflated ordinal-probit model for investigating adoption and usage of innovative wall-cavity insulation materials among residential homebuilders in the US. This study assumes a three-step adoption process of innovative housing materials, namely, trial adoption, intermediate adoption and complete adoption. The study uses 5757 responses from a combined ‘Annual Builder Practices Survey’ dataset comprising ten cross-sectional yearly surveys, undertaken by the NAHB Research Center, from 1996 to 2005. The research results indicate that though a higher proportion of large firms are more likely to adopt innovative insulation material, they continue using established products while slowly increasing their use of the innovative material over time. However, when smaller homebuilders adopt an innovative insulation material, it replaces the existing product from their material usage portfolio at a faster rate.     

Returns from social capital in open source software networks

Open Source Software projects base their operation on a collaborative structure for knowledge exchange in the form of provision or reception of information, expertise and feedback on the creation of source code. Here, we address the direction of these knowledge flows among projects throughout social networks and their impact on project success. We identify the roles of membership or contribution that individuals play within projects. We found that connections through contributors who bring their knowledge to the project, improve project success, and that connection through members, who transfer their knowledge towards other projects, enhance project success. Finally, we found that ties through shared membership and contributions hamper project success. The analysis of knowledge flows and their impact on project success imply a translation of returns from investment in social capital, where investment takes the shape of knowledge flows and the returns mean the projects’ diffusion over the network.

OIL PRICE SHOCKS AND STOCK MARKET BOOMS IN AN OIL EXPORTING COUNTRY

This paper analyses the effects of oil price shocks on stock returns in Norway, an oil-exporting country, highlighting the transmission channels of oil prices for macroeconomic behaviour. To capture the interaction between the different variables, stock returns are incorporated into a structural VAR model. I find that following a 10% increase in oil prices, stock returns increase by 2.5%, after which the effect gradually dies out. The results are robust to different (linear and non-linear) transformations of oil prices. The effects on the other variables are more modest. However, all variables indicate that the Norwegian economy responds to higher oil prices by increasing aggregate wealth and demand. The results also emphasize the role of other shocks; monetary policy shocks in particular, as important driving forces behind stock price variability in the short term.     

An experimental analysis of team production in networks

Experimental and empirical evidence highlights the role of networks on social outcomes. This paper tests the properties of exogenously fixed networks in team production. Subjects make the same decisions in a team work environment under four different organizational networks: the line, the circle, the star, and the complete network. In all the networks, links make information available to neighbors. This design allows us to analyze decisions across networks and a variety of subject types in a standard linear team production game. Contribution levels differ significantly across networks and the star is the most efficient incomplete network. Moreover, our results suggest that subjects act as conditional cooperators with respect to the information received from the network.     

Improving the econometric precision of regulatory models

Regulatory regimes often attempt to introduce quasi-competitive pressures by undertaking comparative efficiency assessments between the regulated companies and setting company-specific cost reduction targets based on those comparisons. The UK water industry is one example of such a regime—indeed, it has emphasized the importance of maintaining the number of independent companies in order to preserve the robustness of the modeling. For example, in 2007, the Competition Commission considered whether the merger between Mid Kent Water and South East Water might prejudice the ability of the regulator (Ofwat) to make comparisons across water companies for the purposes of assessing performance and setting price controls. In this paper, we examine this issue and provide specific recommendations to regulators. Our cross-sectional results show that the impact of this merger is not significant. We demonstrate that joint estimation of all the sub-models using the ‘seemingly unrelated regression’ (SUR) procedure in a cross-section and/or panel data framework can dramatically improve the accuracy of the modeling. Moreover, the merger does not affect the confidence intervals significantly under such approaches, which still remain far superior to those under Ofwat’s cross-sectional approach. Based on these results, we recommend that Ofwat and other regulators adopt SUR and/or panel data analysis and thereby reduce their reliance on having sufficient numbers of independent companies.