The distribution of income between labor and capital is not stable: But why is that so and why does it matter?

I review the literature on labor's share of national income in developed and developing countries. These shares have varied systematically over the post-World War II period, rising until the late 1970s and then falling until now. Explanations for the decline in labor's share include technical progress, globalization and a decline in labor's bargaining power, but none of these explanations can account for both the rise and the decline of labor shares over time and for the similar pattern in developed and developing countries. However, movements in oil prices can account for these movements if energy is included in the production function. Such an explanation has broad implications for income distribution, energy conservation and for the modern theory of growth.     

The hierarchical age–period–cohort model: Why does it find the results that it finds?

It is claimed the hierarchical-age–period–cohort (HAPC) model solves the age–period–cohort (APC) identification problem. However, this is debateable; simulations show situations where the model produces incorrect results, countered by proponents of the model arguing those simulations are not relevant to real-life scenarios. This paper moves beyond questioning whether the HAPC model works, to why it produces the results it does. We argue HAPC estimates are the result not of the distinctive substantive APC processes occurring in the dataset, but are primarily an artefact of the data structure—that is, the way the data has been collected. Were the data collected differently, the results produced would be different. This is illustrated both with simulations and real data, the latter by taking a variety of samples from the National Health Interview Survey (NHIS) data used by Reither et al. (Soc Sci Med 69(10):1439–1448, 2009) in their HAPC study of obesity. When a sample based on a small range of cohorts is taken, such that the period range is much greater than the cohort range, the results produced are very different to those produced when cohort groups span a much wider range than periods, as is structurally the case with repeated cross-sectional data. The paper also addresses the latest defence of the HAPC model by its proponents (Reither et al. in Soc Sci Med 145:125–128, 2015a). The results lend further support to the view that the HAPC model is not able to accurately discern APC effects, and should be used with caution when there appear to be period or cohort near-linear trends.     

Does entrepreneurial activity matter for economic growth in developing countries? The role of the institutional environment

The discussion on which institutions determine entrepreneurial activity – and the role of institutions in the aggregated output for developing countries – is as yet unresolved. The extant literature about entrepreneurship recognizes new ventures as potential mechanisms for long-term development. Yet, there is a consensus on the lack of evidence, particularly for these countries. Drawing on institutional economics, this article explores the interrelationships among institutional environment, entrepreneurial activity, and economic growth. To this end, we use simultaneous-equation panel data models for a sample of 14 developing countries (78 observations) over the period of 2004–2012. The main findings suggest a causal chain running from institutions to opportunity entrepreneurship, which is linked to the economic growth of emerging economies. In particular, we find that institutional factors – such as the number of procedures to start a new business, private credit coverage ,, and access to communication– influence entrepreneurial activity driven by opportunity. Policy implications for developing countries could be derived in order to enhance their economic performance through entrepreneurial activity.

     

Trading and non-trading period realized market volatility: Does it matter for forecasting the volatility of US stocks?

We study the potential merits of using trading and non-trading period market volatilities to model and forecast the stock volatility over the next one to 22 days. We demonstrate the role of overnight volatility information by estimating heterogeneous autoregressive (HAR) model specifications with and without a trading period market risk factor using ten years of high-frequency data for the 431 constituents of the S&P 500 index. The stocks’ own overnight squared returns perform poorly across stocks and forecast horizons, as well as in the asset allocation exercise. In contrast, we find overwhelming evidence that the market-level volatility, proxied by S&P Mini futures, matters significantly for improving the model fit and volatility forecasting accuracy. The greatest model fit and forecast improvements are found for short-term forecast horizons of up to five trading days, and for the non-trading period market-level volatility. The documented increase in forecast accuracy is found to be associated with the stocks’ sensitivity to the market risk factor. Finally, we show that both the trading and non-trading period market realized volatilities are relevant in an asset allocation context, as they increase the average returns, Sharpe ratios and certainty equivalent returns of a mean–variance investor.     

The whole is more than the sum of its parts? How HRM is configured in nonprofit organizations and why it matters

Evidence points to the central importance of configurations of mutually reinforcing HR practices as they are assumed to provide the basis for understanding how HRM relates to organizational performance. While progress has been made regarding the construction and effects of HR architectures in the for-profit literature, few studies investigate how HR architectures are configured in nonprofit organizations (NPOs). Therefore, this paper aims to advance a conceptual model that captures the relationship between ideal types of HR architectures and performance in NPOs. We develop theoretical propositions that provide further insight on the HR programs and HR practices that define the HR architectures and entail implications about variations in performance outcomes in NPOs.     

Does the engaged public's evaluation of networking practices matter? The effects of polarized attitudes and the reputation of networking on individuals' word-of-mouth behaviors

The study examines the influence of individuals' attitudes and the perceived organization's ability to network with its stakeholders on their positive and negative word-of-mouth (WOM) behaviors. The study also examines how these relationships differ between the general and engaged public, taking the organization People for the Ethical Treatment of Animals (PETA) as a case study. The results show that individuals' attitudes toward PETA predict positive and negative WOM behaviors regardless of their previous engagement in PETA. Yet the influence of the perceived reputation of PETA's networking with other stakeholders on positive or negative WOM behaviors displayed different patterns between the general and the engaged public. For the engaged public, the idea that PETA has a good relationship with its members is considered more important than outreach to nonsupporters. In addition, how individuals perceive characteristics of stakeholders or their influence on organizations influences the relationship between the perceived reputation of networking and the engaged public's negative WOM behaviors.