Four centuries of return predictability

We combine annual stock market data for the most important equity markets of the last four centuries: the Netherlands and UK (1629–1812), UK (1813–1870), and US (1871–2015). We show that dividend yields are stationary and consistently forecast returns. The documented predictability holds for annual and multi-annual horizons and works both in- and out-of-sample, providing strong evidence that expected returns in stock markets are time-varying. In part, this variation is related to the business cycle, with expected returns increasing in recessions. We also find that, except for the period after 1945, dividend yields predict dividend growth rates.     

Implementation and profitability of sustainable investment strategies: An errors-in-variables perspective

Firm-level studies of sustainable investment performance are typically limited by an errors-in-variables bias (i.e., a distortion of estimated regression coefficients caused by measurement error in explanatory variables). Using recent advances in statistical methodology, we present the first cross-sectional analysis of sustainable stock selection which adequately corrects for this bias and additionally answers the question of whether betas with respect to sustainable risk factors or sustainable characteristics (i.e., environmental, social, and governance ratings) are more relevant in portfolio selection. Within the universe of S&P 500 stocks, which is highly relevant from the investor attention and liquidity perspectives, we find that, after accounting for errors-in-variables bias, both types of variables become insignificant. Consequently, they do not add value to investment portfolios and are not vital in models explaining stock returns. Among classic predictors with a long history of use in the investment fund industry, only the market-to-book ratio provides independent investment and pricing information.     

Express yourself: Facial expression of happiness,anger, fear,and sadness in funding pitches

We build upon theory from evolutionary psychology and emotional expression, including basic emotion theory and the dual threshold model of anger in organizations, to extend knowledge about the influence of facial expressions of emotion in entrepreneurial fundraising. First, we conduct a qualitative analysis to understand the objects of entrepreneurs' facial expressions of four basic emotions in their pitches: happiness, anger, fear, and sadness. This provides a base for our theorizing that the frequency of entrepreneurs' facial expression of each of these emotions exhibits an inverted U-shaped relationship with funding. We also argue that the frequency of changes in entrepreneurs' facial expressions is positively related to funding. We test our predictions with a sample of 489 funding pitches using computer-aided facial expression analysis. Results support inverted U-shaped relationships of the frequency of facial expression of happiness, anger, and fear with funding, but show a negative relationship of sadness with funding. Results further support that the frequency of change in entrepreneurs' facial expressions promotes funding.     

What kind of donor are you? Uncovering complexity in donor identity

Identity is a useful lens to understand donation behavior. However, studies have typically conceptualized and examined donor identity as a generic, unidimensional concept. Through in‐depth interviews with 52 blood donors, this study sets out to discover if there is more complexity to donor identity, and what implications this might have for marketing communications, in the context of donation of the self (e.g., blood, organs, time, and effort). We use sentiment polarity and amplification analysis of inductive themes to uncover distinct patterns reflective of four different donor identities. We label these the Savior, Communitarian, Pragmatist, and Elitist, which are underpinned by theories of gift‐giving, sharing, pragmatism, and signaling, respectively. The typology offers a theory‐building mechanism to anticipate the effects of marketing stimuli on donation behavior. We conclude by presenting four theoretical propositions, for which we provide preliminary empirical evidence. The survey data is suggestive of action readiness for donation behavior when a marketing communication message is aligned with its intended donor identity.     

Migrant Networks and the Spread of Information

Diaspora networks provide information to future migrants, which affects their success in the host country. While the existing literature explains the effect of networks on the outcomes of migrants through the size of the migrant community, we show that the quality of the network is an equally important determinant. We argue that networks that are more integrated in the society of the host country can provide more accurate information to future migrants about job prospects. In a decision model with imperfect signalling, we show that migrants with access to a better network are more likely to make the right decision, that is, they migrate only if they gain. We test these predictions empirically using data on recent Mexican migrants to the United States. To instrument for the quality of networks, we exploit the settlement of immigrants who came during the Bracero program in the 1950s. The results are consistent with the model predictions, providing evidence that connections to a better integrated network lead to better outcomes after migration.     

Banerjee,Duflo, Kremer,and the Rise of Modern Development Economics*

In 2019, Abhijit Banerjee, Esther Duflo, and Michael Kremer received the Sveriges Riksbank Prize in Economic Sciences in Memory of Alfred Nobel. These three scholars were recognized “for their experimental approach to alleviating global poverty”. This paper reviews the contributions of these three scholars in the field of development economics, to put this contribution in perspective. I highlight how the experimental approach helped to break down the challenges of understanding economic development into a number of component pieces, and I contrast this to understanding development using macroeconomic aggregates. I discuss pioneering contributions in understanding the challenges of education, service delivery, and credit markets in developing countries, as well as how the experimental approach has spread to virtually all aspects of development economics.     

Estimating and accounting for the output gap with large Bayesian vector autoregressions

We consider how to estimate the trend and cycle of a time series, such as real gross domestic product, given a large information set. Our approach makes use of the Beveridge–Nelson decomposition based on a vector autoregression, but with two practical considerations. First, we show how to determine which conditioning variables span the relevant information by directly accounting for the Beveridge–Nelson trend and cycle in terms of contributions from different forecast errors. Second, we employ Bayesian shrinkage to avoid overfitting in finite samples when estimating models that are large enough to include many possible sources of information. An empirical application with up to 138 variables covering various aspects of the US economy reveals that the unemployment rate, inflation, and, to a lesser extent, housing starts, aggregate consumption, stock prices, real money balances, and the federal funds rate contain relevant information beyond that in output growth for estimating the output gap, with estimates largely robust to substituting some of these variables or incorporating additional variables.     

Strategic job analysis

The application of job analysis techniques makes the implicit assumption that information about a job as it presently exists may be used to develop programs to recruit, select, train, and appraise people for the job as it will exist in the future. Given a rapidly changing internal and external world it is likely that many jobs will change in the future. This article reviews some new techniques that, when added to traditional job analysis procedures, may facilitate strategic planning for the development of personnel procedures such as selection and training. Examples of the new technique are presented, followed by a discussion of some topics requiring future thought and research.