Evolution of Corporate Law and the Transplant Effect: Lessons from Six Countries

The pattern of legal change in countries that have their legalsystems transplanted from abroad differs markedly from countriesthat develop their own systems, irrespective of the legal familyfrom which their laws come. In "transplant" countries, law oftenstagnates for long periods of time; when change takes place,it tends to be radical, if not erratic. External models remaindominant even years after the law was transplanted. Althoughthere is some evidence that transplant countries have engagedin comprehensive legal reforms in response to the pressuresof globalization, it is still too early to judge whether thesenew changes can be taken as a sign that the legal systems inthese countries have started a process of endogenous legal evolution.      

Evaluation Periods and Asset Prices in a Market Experiment

We test whether the frequency of feedback information about the performance of an investment portfolio and the flexibility with which the investor can change the portfolio influence her risk attitude in markets. In line with the prediction of myopic loss aversion (Benartzi and Thaler (1995)), we find that more information and more flexibility result in less risk taking. Market prices of risky assets are significantly higher if feedback frequency and decision flexibility are reduced. This result supports the findings from individual decision making, and shows that market interactions do not eliminate such behavior or its consequences for prices.     

To buy or not to buy? The value of contradictory analyst signals

We study the predictive ability of individual analyst target price changes for post-event abnormal stock returns within each recommendation category. Although prior studies generally demonstrate the investment value of target prices, we find that target price changes do not cause abnormal returns within each recommendation level. Instead, contradictory analyst signals (e.g., strong buy reiterations with large target price decreases) neutralize each other, whereas confirmatory signals reinforce each other. Further, our analysis reveals that large target price downgrades can be explained by preceding stock price decreases. However, upgrades are not preceded by stock price increases, thereby demonstrating asymmetric analyst behavior when adjusting target prices to stock prices. Our results suggest that investors should treat recommendations with caution when they are issued with large contradictory target price changes. Thus, instead of blindly following a recommendation, investors might put more weight on the change in the corresponding target price and consider transaction costs.     

Target ratcheting and effort reduction

In this paper, we examine how retail store managers reduce their sales activity in response to target ratcheting. We find that managers with favorable sales performance in the first three quarters reduce their sales activity in the final quarter. We also document that managers who engage in sales reducing activities enhance their likelihood of meeting their next-year sales target, which is based on their current sales. That is, managers who reduce their sales activity in the final quarter are more likely to beat their next-year sales targets than managers who refrain from reducing their final-quarter sales.     

Wrapped input selection using multilayer perceptrons for repeat‐purchase modeling in direct marketing

In this paper, we try to validate existing theory on and develop additional insight into repeat‐purchase behavior in a direct marketing setting by means of an illuminating case study. The case involves the detection and qualification of the most relevant RFM (Recency, Frequency and Monetary) variables, using a neural network wrapper as our input pruning method. Results indicate that elimination of redundant and/or irrelevant inputs by means of the discussed input selection method allows us to significantly reduce model complexity without degrading the predictive generalization ability. It is precisely this issue that will enable us to infer some interesting marketing conclusions concerning the relative importance of the RFM predictor categories and their operationalizations. The empirical findings highlight the importance of a combined use of RFM variables in predicting repeat‐purchase behavior. However, the study also reveals the dominant role of the frequency category. Results indicate that a model including only frequency variables still yields satisfactory classification accuracy compared to the optimally reduced model. Copyright © 2001 John Wiley & Sons, Ltd.     

Venture Capital Valuation,Partial Adjustment,and Underpricing: Behavioral Bias or Information Production?

Using a sample of venture capital (VC)‐backed initial public offerings (IPOs), we analyze the role played by perceived valuation changes on IPO underpricing. We find that perceived valuation change from the last pre‐IPO VC round to the IPO affects IPO underpricing in a nonlinear way. Further analysis indicates that information‐based theories, not behavioral biases, explain this nonlinearity. We also find that the previously documented partial adjustment effect and its nonlinear impact on IPO underpricing are related to the trajectory of the perceived valuation changes, which stands in stark contrast to prior evidence of the importance of behavioral biases.     

U.S. food aid and American exports to recipient countries during the Cold War

In this article, we test to what extent the food aid granted by the U.S. during the Cold War was strategically motivated and used to promote U.S. interests. Using the data for the period 1971–1990, we investigate whether U.S. wheat aid had an effect on recipient countries’ total import of American products. The evidence we provide suggests a positive and robust relationship and thus it is consistent with the argument that U.S. food aid helped to create larger markets for U.S. producers.     

Forecasting interest rates with shifting endpoints

We consider forecasting the term structure of interest rates with the assumption that factors driving the yield curve are stationary around a slowly time‐varying mean or ‘shifting endpoint’. The shifting endpoints are captured using either (i) time series methods (exponential smoothing) or (ii) long‐range survey forecasts of either interest rates or inflation and output growth, or (iii) exponentially smoothed realizations of these macro variables. Allowing for shifting endpoints in yield curve factors provides substantial and significant gains in out‐of‐sample predictive accuracy, relative to stationary and random walk benchmarks. Forecast improvements are largest for long‐maturity interest rates and for long‐horizon forecasts. Copyright © 2013 John Wiley & Sons, Ltd.