Betriebswirtschaftslehre ohne Unternehmensethik? Vom Scheitern einer Ethik ohne Moral

Zusammenfassung  In Auseinandersetzung mit einer jüngst von Horst Albach ge?u?erten Auffassung von Betriebswirtschaftslehre ohne Unternehmensethik wird eine gegenteilige Auffassung entwickelt. Es wird gezeigt, dass der Glaube an die reinigenden Marktkr?fte eine ?konomistische Fiktion darstellt und mithin eine Ethik ohne Moral, d.h. ohne bewusst ethisch agierende Personen, unhaltbar ist. Stattdessen werden Anforderungen erkennbar, die als eine Richtschnur für die Entwicklung unternehmensethischer Perspektiven zu verstehen sind.

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Management without business ethics? On the failure of ethics without morality

Summary  Recently, Horst Albach developed an ethical approach which identifies management science being inherently ethical. This paper offers an alternative view. We examine how a pure market driven understanding of business ethics leads to questionable positions and logical contradictions. Therefore we propose a business ethics with morality which includes people, acting from ethically reflected grounds. Additionally, we define requirements to be fulfilled when developing business ethics within management science.

     

Friedman, Harsanyi, Rawls, Boulding – or somebody else? An experimental investigation of distributive justice

This paper investigates distributive justice using a fourfold experimental design: The ignorance and the risk scenarios are combined with the self-concern and the umpire modes. We study behavioral switches between self-concern and umpire mode and investigate the goodness of ten standards of behavior. In the ignorance scenario, subjects became, on average, less inequality-averse as umpires. A within-subjects analysis shows that about one half became less inequality-averse, one quarter became more inequality-averse and one quarter remained unchanged as umpires. In the risk scenario, subjects became on average more inequality-averse in their umpire roles. A within-subjects analysis shows that about half became more inequality-averse, one quarter became less inequality-averse, and one quarter remained unchanged as umpires. As to the standards of behavior, several prominent ones (leximin, leximax, Gini, Cobb-Douglas) were not supported, while expected utility, Boulding’s hypothesis, the entropy social welfare function, and randomization preference enjoyed impressive acceptance. For the risk scenario, the tax standard of behavior joins the favorite standards of behavior.Financial Support of the European Commission under TMR Contract No. ERBFMRXCT98-0248 is gratefully acknowledged. We are indebted to Serge-Christophe Kolm, Alf Erling Risa, Peter Zweifel, two anonymous referees and an editor of Social Choice and Welfare for helpful comments. We thank Marc Paolella for improving our English writing style. The usual disclaimer applies. The experimental data can be obtained from the authors (e-mail: traub@bwl.uni-kiel.de).     

Assessing the bias due to non-coverage of residential movers in the German Microcensus Panel: an evaluation using data from the Socio-Economic Panel

The German Microcensus (MC) is a large scale rotating panel survey over three years. The MC is attractive for longitudinal analysis over the entire participation duration because of the mandatory participation and the very high case numbers (about 200000 respondents). However, as a consequence of the area sampling that is used for the MC, residential mobility is not covered and consequently statistical information at the new residence is lacking in the MC sample. This raises the question whether longitudinal analyses, like transitions between labour market states, are biased and how different methods perform that promise to reduce such a bias. Similar problems occur also for other national Labour Force Surveys (LFS) which are rotating panels and do not cover residential mobility, see Clarke and Tate (2002). Based on data of the German Socio-Economic Panel (SOEP), which covers residential mobility, we analysed the effects of missing data of residential movers by the estimation of labour force flows. By comparing the results from the complete SOEP sample and the results from the SOEP, restricted to the non-movers, we concluded that the non-coverage of the residential movers can not be ignored in Rubin’s sense. With respect to correction methods we analysed weighting by inverse mobility scores and log-linear models for partially observed contingency tables. Our results indicate that weighting by inverse mobility scores reduces the bias to about 60% whereas the official longitudinal weights obtained by calibration result in a bias reduction of about 80%. The estimation of log-linear models for non-ignorable non-response leads to very unstable results.     

Assessing the impact of initial nonresponse and attrition in the analysis of unemployment duration with panel surveys

We show how register data combined at person-level with survey data can be used to conduct a novel type of nonresponse analysis in a panel survey. The availability of register data provides a unique opportunity to directly test the type of the missingness mechanism as well as estimate the size of bias due to initial nonresponse and attrition. We are also able to study in-depth the determinants of initial nonresponse and attrition. We use the Finnish subset of the European Community Household Panel (FI ECHP) data combined with register panel data and unemployment spells as outcome variables of interest. Our results show that initial nonresponse and attrition are clearly different processes driven by different background variables. Both the initial nonresponse and attrition mechanisms are nonignorable with respect to analysis of unemployment spells. Finally, our results suggest that initial nonresponse may play a role at least as important as attrition in causing bias. This result challenges the common view of attrition being the main threat to the value of panel data.     

Efficient Institutions and Effective Deterrence: On Timing and Uncertainty of Formal Sanctions

Journal of Risk and Uncertainty - Economic theory suggests that the deterrence of deviant behavior is driven by a combination of severity and certainty of punishment. This paper presents the first...     

International business taxation and the business cash flow tax

Investments and business profits are internationally mobile. Countries respond by tackling international profit shifting. As a result, the international allocation of taxable profits becomes an increasingly complex and costly issue. Reform proposals either address the Organisation of Economic Co-operation and Development approach to international profit allocation or target tax bases that are less mobile than profits. This paper investigates cash flow as a tax base. A business cash flow tax abolishes current accrual accounting and has the potential to block international profit shifting. Financing vanishes to become a tax-planning tool because the investments’ market return is tax free under a cash flow tax. Profit shifting via intra-group transactions is eliminated if the business cash flow tax is based on the country of destination principle. However, a destination-based business cash flow tax might distort the investment decisions of international groups.     

Germany and its immigrants: a socio-demographic analysis

"Germany is today, along with the USA and Russia, one of the three most important immigration countries worldwide. The authors examine how the immigrant population of Germany has risen despite the fact that the German government has sought to restrict it. They analyse six major streams of migration: refugees and expellees who came immediately after World War II, German resettlers from Eastern Europe (?Aussiedler'), emigration of (West) Germans, migration between East and West Germany, foreign labour migrants and asylum seekers. The dynamics of immigration within each of these channels was remarkably different. As far as absorption and integration are concerned the authors argue that different groups of immigrants should be treated more equally."     

Efficient Tests Under a Weak Convergence Assumption

The asymptotic validity of tests is usually established by making appropriate primitive assumptions, which imply the weak convergence of a specific function of the data, and an appeal to the continuous mapping theorem. This paper, instead, takes the weak convergence of some function of the data to a limiting random element as the starting point and studies efficiency in the class of tests that remain asymptotically valid for all models that induce the same weak limit. It is found that efficient tests in this class are simply given by efficient tests in the limiting problem—that is, with the limiting random element assumed observed—evaluated at sample analogues. Efficient tests in the limiting problem are usually straightforward to derive, even in nonstandard testing problems. What is more, their evaluation at sample analogues typically yields tests that coincide with suitably robustified versions of optimal tests in canonical parametric versions of the model. This paper thus establishes an alternative and broader sense of asymptotic efficiency for many previously derived tests in econometrics, such as tests for unit roots, parameter stability tests, and tests about regression coefficients under weak instruments.     

Risk factors for femicide-suicide in abusive relationships: results from a multisite case control study

The killing of women by men who then take their own lives (femicide-suicide) is the most common form of homicide-suicide. This study identified femicide-suicide risk factors in an 11-city case-control study of femicide in the United States. Perpetrator, victim, relationship, and incident characteristics were analyzed for femicide-suicide cases (n = 67) and controls (n = 356, women living in the community with nonfatal physical abuse) using logistic regression modeling. Two risk factors emerged that were unique to femicide-suicides cases compared to overall femicide risk analyses: prior perpetrator suicide threats and victims having ever been married to the perpetrator.     

HAC Corrections for Strongly Autocorrelated Time Series

Applied work routinely relies on heteroscedasticity and autocorrelation consistent (HAC) standard errors when conducting inference in a time series setting. As is well known, however, these corrections perform poorly in small samples under pronounced autocorrelations. In this article, I first provide a review of popular methods to clarify the reasons for this failure. I then derive inference that remains valid under a specific form of strong dependence. In particular, I assume that the long-run properties can be approximated by a stationary Gaussian AR(1) model, with coefficient arbitrarily close to one. In this setting, I derive tests that come close to maximizing a weighted average power criterion. Small sample simulations show these tests to perform well, also in a regression context.