50 Jahre Baumol‘sche Kostenkrankheit

The year 2017 marks the 50th anniversary of William J. Baumol’s “Cost Disease”, which posits that services with low productivity growth become more expensive relative to goods while aggregate productivity growth slows down in the process of tertiarisation. The authors present the basic structure of Baumol’s model and discuss several attempts to refute the concept or to cope with its consequences. One of them is the important observation by Nicholas Oulton that business services — unlike personal services — can contribute to higher aggregate productivity growth. A major precondition is that the productivity growth of business services is positive. However, an empirical test shows that this is not the case in Germany and other major advanced economies. Some economic policy conclusions are drawn.     

Why not use SDF rather than beta models in performance measurement?

This paper analyzes performance measurement based on stochastic discount factors, compared to beta models traditionally used in computing funds’ (Jensen) alphas. From a theoretical point of view, standard alphas suffer from several limitations. Our paper addresses this issue from an empirical point of view using a sample of Swiss mutual funds from 2000 to 2011. Our results suggest that the key for a “fair” comparison between stochastic discount function (SDF) and beta models is the specification of the set of primitive assets used to calibrate the SDF function. Once this is established, the size of (absolute) performance differences considerably decreases between the two model families. However, there are sizeable performance deviations in the cross-section of funds if conditioning information is incorporated in the tests, up to some 20 basis points per month, or about 2.3 % per year. In almost all cases, the SDF-alphas are lower than the standard (Jensen) alphas. In absolute terms, the average SDF-based underperformance of the funds is way larger than the average total expense ratio (TER) of the funds, both in a conditional and unconditional setting.     

Models of causal inference: Imperfect but applicable is better than perfect but inapplicable

We assess a recent paper by Durand and Vaara (2009) that advances causal graph modeling as a tool for inferring causes in strategy research. We focus on the Markov condition, a key assumption on which causal graph modeling is based, and show why this condition is invariably violated in strategic management in general and the resource‐based view of the firm in particular. We then introduce vector space modeling as a quantitative alternative to causal graph modeling, and consider how improved methods of causal inference might enhance our ability to test some of the central propositions of the resource‐based view. Copyright © 2013 John Wiley & Sons, Ltd.     

Das Mindestlohngesetz — Hoffnungen und Befürchtungen

The German government plans to introduce a minimum wage from 2015. This must be understood as a response to the decline in collective bargaining coverage and the marked increase in employment in the low-wage sector. The authors discuss how many workers are affected by this new regulation and whether the minimum wage is too high in relation to the average wage of workers (Kaitz index). They assume that the introduction of a minimum wage in Germany can have a number of effects. It is not possible to forecast all the reactions and behaviour of market participants to handle higher wages and goods prices. Some authors warn that these measures are significant labour market interventions that could have adverse employment effects. They recommend allowing more exemptions from the minimum wage law than intended by the government, especially for young employees and student apprentices. Other authors hope that minimum wages would help to strengthen collective bargaining and stabilise wages. Some authors emphasise that there should be a careful evaluation of the economic effects by scientists.     

Rainfall or price variability: what determines rangeland management decisions? A simulation-optimization approach to South African savannas

Savannas cover the greater part of Africa and Australia and almost half of South America and contribute to the livelihoods of more than 350 million people. With the intensification of land use during the second half of the 20th century, savannas have become increasingly degraded through bush encroachment as a consequence of increased grazing pressure. Research on rangeland dynamics, however, provides contradicting answers with regard to the causes and possible remedies of bush encroachment. In this article we present results from an application of a simulation-optimization model to the case of extensive rangeland management in South Africa. Our model differs from previous approaches in that it explicitly accounts for the influence of stochastic prices and rainfall on economically optimal management decisions. By showing the implications of neglecting price variation and stochasticity in rangeland models we provide new insights with regard to the determinants of bush encroachment and rangeland managers' economic return. We demonstrate that, in the case of South Africa, optimal rangeland management is likely to lead to bush encroachment that eventually makes livestock holding unprofitable. Yet, we identify the costs of fire management to be a limiting factor for managers to counteract bush encroachment and explore the impact of policy measures to reduce fire control costs on the ecological and economic sustainability of livestock holding.     

Measuring market integration in the presence of transaction costs–a threshold vector error correction approach

Applied econometric analyses of market integration based on price data alone have been criticised because they neglect the role of transaction costs. To meet this objection, threshold vector error correction models are used. Threshold models can account for the effects of transaction costs in price transmission without directly relying upon information about these costs, which are often unavailable. It is argued that threshold models that are based on two thresholds provide results that are economically more intuitive than those obtained from one-threshold models. However, to this point no adequate econometric test is available for threshold significance in a two-threshold model; such tests are only available for the one-threshold model. In this paper a restricted two-threshold model is developed in which the significance of the thresholds can be tested. This model is therefore amenable to economic interpretation and statistical inference. The model is used to estimate market integration in the European pig market.