Strategic Cost Management and Institutional Changes in Hospitals

Accounting research raises the concern that firms in the health care and defence contracting industries, when facing a dual payment system with both cost-based and fixed-rate payments, have an incentive to reallocate overhead costs through increasing inputs used in cost-based operations. However, prior literature reports contradictory empirical evidence regarding such real activity manipulation. Drawing on the institutional perspective, we hypothesise that firms' market power and interorganisational dependence affect their cost-management strategies and choice of overhead allocation in response to dual payment systems. Analysing the data of California hospitals from 1980 to 1991, we find that when facing a dual payment system, dominant (strong market position) hospitals adopt a cost-revenue-enhancing strategy, increasing direct costs for cost-based services without containing costs in fixed-rate services. In contrast, nondominant hospitals choose a cost-reduction strategy and improve operation efficiency on fixed-rate services. We also find that nondominant hospitals shift more overhead costs away from fixed-rate services to cost-based services by reclassifying the allocation bases across services; combining this cost shifting with the cost-reduction strategy, nondominant hospitals demonstrate the compliance with the regulation expectation of cost containment.     

A flexible regime switching model with pairs trading application to the S&P 500 high-frequency stock returns

This paper develops the regime classification algorithm and applies it within a fully-fledged pairs trading framework on minute-by-minute data of the S&P 500 constituents from 1998 to 2015. Specifically, the highly flexible algorithm automatically determines the number of regimes for any stochastic process and provides a complete set of parameter estimates. We demonstrate its performance in a simulation study—the algorithm achieves promising results for the general class of Lévy-driven Ornstein–Uhlenbeck processes with regime switches. In our empirical back-testing study, we apply our regime classification algorithm to propose a high-frequency pair selection and trading strategy. The results show statistically and economically significant returns with an annualized Sharpe ratio of 3.92 after transaction costs—results remain stable even in recent years. We compare our strategy with existing quantitative trading frameworks and find its results to be superior in terms of risk and return characteristics. The algorithm takes full advantage of its flexibility and identifies various regime patterns over time that are well-documented in the literature.     

Heterogeneity of plural forms: A revised transaction cost approach

Strategies pushing firms to adopt plural forms and the heterogeneity of solutions they endorse have attracted increasing attention. This paper proposes a theoretical framework that combines asset specificity and uncertainty to explain why there are plural forms and focuses on the key role of uncertainty, within a given range of asset specificity, to predict what and when specific types of plural forms should be observed. Propositions derived from this model are tested on an extensive set of cases from the agribusiness sector. The empirical richness of these cases allows going beyond the existing literature, which has essentially focused on franchising.     

Contract teachers and student achievement in rural China: evidence from class fixed effects

For schooling to play an important role in the development of human capital, the system of education needs to provide quality education, which among other things requires high‐quality teachers. Facing fiscal constraints and growing enrolments, school systems in developing countries often supplement their teaching staff by hiring contract teachers. However, there is limited evidence on how the effectiveness of these teachers compares to that of civil service teachers. We use a dataset from rural primary schools in western China to estimate the causal effect of contract teachers on student achievement and find that gains in student scores on standardised examinations in mathematics and Chinese are less in classes taught by contract teachers than in classes taught by civil service teachers. The results demonstrate that China's education system needs to focus on producing high‐quality teachers to improve the quality of schooling in its rural education system. The findings imply that educators in developing countries should not only seek to hire increasingly more civil service teachers in rural schools, but they should also identify ways of improving the quality of contract teachers. If efforts to improve teaching can succeed, rural students can learn more, earn higher incomes and contribute more to the productivity of the overall economy.     

The Reaction of Coffee Futures Price Volatility to Crop Reports

Analysis of prices and volatility plays an important role in coffee market, especially for developing countries, whose small producers and economies rely heavily on income generated by coffee trade. This study explores the impact of coffee crop reports on price volatility for coffee futures contracts during 2004–2014. Overall, results indicate that crop reports generally affect price volatility. The impact is particularly stronger when they provide information following the flowering periods in Colombia, Brazil, and Vietnam, world’s major producers.     

Die Erhebung personenbezogener Gesundheitsdaten bei Dritten

The recently introduced § 213 VVG is linked to an interesting history and regulates an issues that had been discussed in the insurance industry for some time. In its application § 213 VVG is more particular than regulations by the German data protection act, at least concerning the collection of health data. For the processing and usage of data the regulations of the German data protection act still apply. Time will show whether § 213 VVG will lead to a reconciliation of interests of the insured with those of the insurer. The aforementioned two-week-period for the data survey might be a contribution to achieve this goal.     

Labor market entry and earnings dynamics: Bayesian inference using mixtures‐of‐experts Markov chain clustering

This paper analyzes patterns in the earnings development of young labor market entrants over their life cycle. We identify four distinctly different types of transition patterns between discrete earnings states in a large administrative dataset. Further, we investigate the effects of labor market conditions at the time of entry on the probability of belonging to each transition type. To estimate our statistical model we use a model‐based clustering approach. The statistical challenge in our application comes from the difficulty in extending distance‐based clustering approaches to the problem of identifying groups of similar time series in a panel of discrete‐valued time series. We use Markov chain clustering, which is an approach for clustering discrete‐valued time series obtained by observing a categorical variable with several states. This method is based on finite mixtures of first‐order time‐homogeneous Markov chain models. In order to analyze group membership we present an extension to this approach by formulating a probabilistic model for the latent group indicators within the Bayesian classification rule using a multinomial logit model. Copyright © 2011 John Wiley & Sons, Ltd.