Bürgergeld und die Zukunft des Sozialstaats

Wirtschaftsdienst - The authors discuss the reform of basic security in the direction of a “citizen’s income” in the coalition agreement of the new “traffic light...     

Real Exchange Rate Misalignments in the Euro Area

Open Economies Review - Building upon a Behavioural Equilibrium Exchange Rate model, estimated at a quarterly frequency since 1999 on a broad sample of 57 countries, this paper assesses both the...     

Do foreign exchange forecasters apply asymmetric loss functions? Evidence from three major exchange rates

This article investigates which type of loss function is consistent with the hypothesis that major exchange rate forecasts, i.e. the euro, the British pound, and the Japanese yen vis-à-vis the US dollar, are rational. We apply a comprehensive data set, which also allows us to examine different forecast horizons and heterogeneity of forecasters.     

Doing Good While Behaving Badly: Checkout Charity Process Mechanisms

Journal of Business Ethics - Companies are increasingly using cause-related marketing campaigns to engage consumers during the purchase process and highlight their own corporate social...     

Duality theory for robust utility maximisation

In this paper, we present a duality theory for the robust utility maximisation problem in continuous time for utility functions defined on the positive real line. Our results are inspired by – and can be seen as the robust analogues of – the seminal work of Kramkov and Schachermayer (Ann. Appl. Probab. 9:904–950, 1999). Namely, we show that if the set of attainable trading outcomes and the set of pricing measures satisfy a bipolar relation, then the utility maximisation problem is in duality with a conjugate problem. We further discuss the existence of optimal trading strategies. In particular, our general results include the case of logarithmic and power utility, and they apply to drift and volatility uncertainty.

     

The politics of experimentation: Political competition and randomized controlled trials

This paper provides an analysis of how political factors affect the incidence of the evaluation of public policies, with a focus on Randomized Control Trial (RCT) experiments in international development. We argue that political environments where incumbents face greater electoral competition and smaller ruling margins are more likely to host RCT experiments. Using various data sources for the incidence of RCTs both at the cross-country level and at the sub-national level in India, we find that RCTs are more likely to occur in politically competitive jurisdictions. We employ fixed effects regressions using various estimators and an instrumental variable strategy that exploits an electoral reform in India which limited the entry of independent candidates and exogenously affected the degree of electoral competition in state-level politics. The effect seems concentrated on RCTs that have the government as a partner, suggesting that political competition has an important demand-side effect on the incidence of RCTs.     

Determinants of process innovation introductions: Evidence from 115 developing countries

This paper examines determinants of process innovation introductions across 115 (mostly) developing countries. Empirical research on process innovations lags behind product innovations. Accounting for firm characteristics, R&D, regulations and taxes, and corruption, results show that sole proprietors and R&D‐performing firms were more likely to introduce innovations, whereas greater prosperity made them less likely to do so. Corruption had a greasing effect, whereas firms in island nations were less likely to introduce, ceteris paribus. Effects of regulations and taxes and other firm characteristics were largely insignificant. Finally, some differences existed across manufacturing and service industries and across prevalence of innovation introductions.     

Time series copulas for heteroskedastic data

We propose parametric copulas that capture serial dependence in stationary heteroskedastic time series. We suggest copulas for first‐order Markov series, and then extend them to higher orders and multivariate series. We derive the copula of a volatility proxy, based on which we propose new measures of volatility dependence, including co‐movement and spillover in multivariate series. In general, these depend upon the marginal distributions of the series. Using exchange rate returns, we show that the resulting copula models can capture their marginal distributions more accurately than univariate and multivariate generalized autoregressive conditional heteroskedasticity models, and produce more accurate value‐at‐risk forecasts.