Distributional consequences of labor-demand shocks: the 2008–2009 recession in Germany

The distributional consequences of the recent economic crisis are still broadly unknown. While it is possible to speculate which groups are likely to be hardest-hit, detailed distributional studies are still largely backward-looking due to a lack of real-time microdata. This paper studies the distributional and fiscal implications of output changes in Germany 2008–2009, using data available prior to the economic downturn. We first estimate labor demand on 12 years of detailed, administrative matched employer-employee data. The distributional analysis is then conducted by transposing predicted employment effects of actual output shocks to household-level microdata. A scenario in which labor demand adjustments occur at the intensive margin (hour changes), close to the German experience, shows less severe effects on the income distribution compared to a situation where adjustments take place through massive layoffs. Adjustments at the intensive margin are also preferable from a fiscal point of view. In this context, we discuss the cushioning effect of the tax-benefit system and the conditions under which German-style work-sharing policies can be successful in other countries.     

Corruption and the shadow economy: like oil and vinegar, like water and fire?

From a theoretical point of view, the relationship between corruption and the shadow economy is ambiguous: They can either be substitutes or complements. This paper contributes to this debate by using a structural equation model with two latent variables to extract information on various dimensions of corruption and the shadow economy. Analyzing a sample of 51 countries around the world over the period 2000 to 2005, we present empirical evidence for a complementary (positive) relationship of corruption and the shadow economy.     

Targeted information and limited attention

We examine the implications of limited consumer attention for the targeting decisions of competing firms. Limited attention alters the strategic role of information provision as firms may become incentivized to behave as mass advertisers, despite perfect targeting abilities. We analyze the consequences of limited attention for targeting, strategic pricing, market shares, attention competition between firms, and the value of marketing data to firms. Accounting for limited attention in an otherwise standard targeting framework can explain several recent key issues from the advertising industry, such as consumer-side information overload or the increased usage of ad blocking tools.     

Target price forecasts: The roles of the 52-week high price and recent investor sentiment

This paper reveals that in addition to fundamental factors, the 52-week high price and recent investor sentiment play an important role in analysts’ target price formation. Analysts’ forecasts of short-term earnings and long-term earnings growth are shown to be important explanatory variables for target prices; equally, the 52-week high price and recent investor sentiment are also shown to explain target price levels and especially target price biases. Our analysis additionally reveals that analysts place greater weight on these two non-fundamental factors in settings with greater task complexity and to some extent in those with greater resource constraints. Conversely, on balance, the results suggest that this increased reliance does not translate into an increased impact per unit of each non-fundamental factor on forecast bias. Finally, our results show that target prices are useful in predicting future stock returns beyond earnings forecasts and commonly used risk proxies. However, in an internally consistent fashion, the informativeness of target prices for future returns is significantly reduced when greater weight is placed on either the 52-week high or recent investor sentiment in the target price formation process.     

Compensation incentives of credit rating agencies and predictability of changes in bond ratings and financial strength ratings

Over the past decade there has been mixed evidence on the lead–lag relation between issuer-paid and investor-paid credit rating agencies. We investigate the lead–lag relationship for changes in bond ratings (BRs) and financial strength ratings (FSRs), for the US insurance industry, where FSRs impose market discipline. First, we find that changes in issuer-paid BRs are led by changes in investor-paid BRs, even over a period that issuer-paid agencies have improved their timeliness. Second, information flows in both directions between changes in issuer-paid BRs and FSRs. Third, issuer-paid FSRs are predictable by investor-paid BRs. Fourth, the lead effect of investor-paid downgrades is economically significant as it is associated with an unconditional, post-event, 30-day cumulative abnormal return of −4%. This return is a result of investor-paid downgrades in BRs, which predict more downgrades in the following 90 days (same period return of −11%).     

Momentum strategies of German mutual funds

The existence of the momentum effect in stock returns has been documented for the US (e.g., Jegadeesh and Titman in J. Finance 48(1), 65–91, 1993) and many other national equity markets worldwide (e.g., Griffin et al. in J. Finance 58(6), 2515–2547, 2003). However, little is known about the active employment of momentum strategies among institutional investors outside the US. This paper provides first evidence of momentum behavior among German mutual funds. We find the fund trades to follow stock returns on an aggregated institutional level. Moreover, we detect significant momentum behavior among funds with a European and global equity focus, as well as among funds predominantly investing in Asia. In contrast, German funds do not seem to engage in momentum strategies when trading domestic stocks. While only half the funds in our sample trade in accordance with past returns, 66 % of the funds within the largest size quintile follow momentum strategies. Finally, we do not find momentum trading funds to outperform the other funds.     

GP algorithm versus hybrid and mixed neural networks

In the current paper, we present an integrated genetic programming (GP) environment called java GP modelling. The java GP modelling environment is an implementation of the steady-state GP algorithm. This algorithm evolves tree-based structures that represent models of inputs and outputs. The motivation of this paper is to compare the GP algorithm with neural network (NN) architectures when applied to the task of forecasting and trading the ASE 20 Greek Index (using autoregressive terms as inputs). This is done by benchmarking the forecasting performance of the GP algorithm and six different autoregressive moving average model (ARMA) NN combination designs representing a Hybrid, Mixed Higher Order Neural Network (HONN), a Hybrid, Mixed Recurrent Neural Network (RNN), a Hybrid, Mixed classic Multilayer Perceptron with some traditional techniques, either statistical such as a an ARMA or technical such as a moving average convergence/divergence model, and a naïve trading strategy. More specifically, the trading performance of all models is investigated in a forecast and trading simulation on ASE 20 time-series closing prices over the period 2001–2008, using the last one and a half years for out-of-sample testing. We use the ASE 20 daily series as many financial institutions are ready to trade at this level, and it is therefore possible to leave orders with a bank for business to be transacted on that basis. As it turns out, the GP model does remarkably well and outperforms all other models in a simple trading simulation exercise. This is also the case when more sophisticated trading strategies using confirmation filters and leverage are applied, as the GP model still produces better results and outperforms all other NN and traditional statistical models in terms of annualized return.     

Home-field advantage or a matter of ambiguity aversion? Local bias among German individual investors

This paper investigates whether familiarity induced by ambiguity aversion can help explaining the local bias phenomenon among individual investors. Using geographic closeness as a proxy for investor familiarity, we find that investors pull out of (unfamiliar) remote stocks and pour into (familiar) local stocks during times of increased market uncertainty. Moreover, the magnitude of this ‘flight to familiarity’ increases in the spread of an investor's ambiguity (about expected returns) between local and remote stocks. Our results prove robust to a number of alternative explanations of local bias. Specifically, we rule out a ‘home-field advantage’, where investors are able to translate information advantages about nearby companies into excess returns on their local stockholdings. We conclude that individual investors’ local bias is induced by ambiguity aversion in the portfolio selection process rather than a trading strategy based on superior information about local companies.     

Value creation in the relationship life cycle: A quasi-longitudinal analysis

Among the growing literature on value creation in collaborative buyer-seller relationships, most researchers examine relationship value at a single point in time. In the present research, we explore whether different stages of the relationship life cycle moderate the relative importance of value-creating dimensions. To shed light on the dynamic nature of value in B2B relationships, we present the results of a survey among purchasing managers using a quasi-longitudinal research design. Our findings confirm the moderating role of the relationship life cycle in value creation. More precisely, our results indicate that a key supplier's potential for value creation in customer's operations increases in relative importance as relationships move through the life cycle. In turn, supplier's capabilities to create superior value at the level of the customer's sourcing process display a decreasing role over the life cycle of a business relationship. No significant link was found in the present study between value creation through a supplier's core offering and different stages of a buyer-seller relationship.