Economic impact of switching from metoprolol to nebivolol for hypertension treatment: a retrospective database analysis

Objective:

To estimate the real-world economic impact of switching hypertensive patients from metoprolol, a commonly prescribed, generic, non-vasodilatory β₁-blocker, to nebivolol, a branded-protected vasodilatory β₁-blocker.

Methods:

Retrospective analysis with a pre–post study design was conducted using the MarketScan database (2007–2011). Hypertensive patients continuously treated with metoprolol for ≥6 months (pre-period) and then switched to nebivolol for ≥6 months (post-period) were identified. The index date for switching was defined as the first nebivolol dispensing date. Data were collected for the two 6-month periods pre- and post-switching. Monthly healthcare resource utilization and healthcare costs pre- and post-switching were calculated and compared using Wilcoxon test and paired t-test. Medical costs at different years were inflated to the 2011 dollar.

Results:

In total, 2259 patients (mean age: 60 years; male: 52%; cardiovascular [CV] disease: 37%) met the selection criteria. Switching to nebivolol was associated with statistically significant reductions in the number of all-cause hospitalization (?33%; p?p?p?p?p?Conclusions:

This real-world study suggests that switching from metoprolol to nebivolol is associated with an increase in medication costs and significant reductions in hospitalizations and outpatient visits upon switching, resulting in an overall neutral effect on healthcare costs. These results may be interpreted with caution due to lack of a comparator group and confounding control caused by design and limitations inherent in insurance claims data.     

All work and no … pay? Unpaid overtime in Greece: determining factors and theoretical explanations

During the last decades an increase of unpaid overtime has been observed combined with the inversion of the working time decreasing trend. This article analyses the data from the Labour Force Survey to estimate the determinants of unpaid overtime in Greece and uses the results to test various theoretical explanations.     

The metamorphosis of development economics

The scientific paradigm of Development Economics is not dead nor is it declining in importance. Instead, it has desynthesized into more than 30 analytical and specialized subparadigms which deal with the complex economic phenomena in LDCs. The great number of sub-disciplines of Development Economics is a verification of the dynamic evolution of the discipline and shows its trend towards increased specialization which seems to be the true index of the scientific progress of the subject. For those who complain that “the current output of new development theories…is smaller” (W. A. Lewis), we remind them that Development Economics is a discipline which has more of a praxeological-concrete orientation than a theoretical-abstract one. It seems that the world today needs more the exercise of development praxeology by the activist than the abstract theorizing of the purists. However, the study and empirical research of development phenomena in the context of the 30 or more specialized sub-disciplines offers an opportunity for improving the quality of our knowledge on these phenomena by the recurrent validation and consolidation of development theories.     

Prestigious stock exchanges: A network analysis of international financial centers

In this paper, we use methods from social network analysis to assess the relative importance of financial centers around the world. Using data from virtually the entire universe of global equity activity, we present complete rankings for 45 separate locations for the period 1990–2006. Our analysis constructs a network measure of prestige based on their ability to attract global IPOs. U.S. exchanges are effectively the unique hosts for cross-border equity activity from many other locations. Moreover, they are the destination of choice for most companies coming from locations with highly prestigious exchanges. We also document the emergence of several competing stock exchanges from developed and emerging market economies. The ascent of these stock markets, however, might reflect improved conditions in a growing global market rather than a decline in the competitiveness of U.S. exchanges.     

Analysing the Agricultural Costs and Non‐market Benefits of Implementing the Water Framework Directive

Implementation of the Water Framework Directive (WFD) represents a fundamental change in the management of water in Europe with a requirement that member states ensure ‘good ecological status’ for all water bodies by 2015. Agriculture is expected to bear a major share of WFD implementation costs as it is compelled to reduce the emission of diffuse water pollutants. The research outlined here comprises interdisciplinary modelling of agricultural land use, hydrology and consequent water quality effects to consider both agricultural costs and the non‐market recreational use (and potentially non‐use) values that implementation of the Directive may generate. A theme throughout the research is the spatial distribution of the costs and benefits of WFD implementation, which is addressed through the use of GIS techniques in the modelling of agricultural land use, the integration of land use and hydrological models, and the estimation, aggregation and transfer of the economic value of the benefits.     

Displacement risk and asset returns

We study asset-pricing implications of innovation in a general-equilibrium overlapping-generations economy. Innovation increases the competitive pressure on existing firms and workers, reducing the profits of existing firms and eroding the human capital of older workers. Due to the lack of inter-generational risk sharing, innovation creates a systematic risk factor, which we call “displacement risk.” This risk helps explain several empirical patterns, including the existence of the growth-value factor in returns, the value premium, and the high equity premium. We assess the magnitude of displacement risk using estimates of inter-cohort consumption differences across households and find support for the model.