Why are REITS Currently So Expensive?

Over the last several years, the price of listed real estate stocks has been unusually high relative to dividends. I find that neither low interest rates nor low risk premia can account for the high valuation ratios. Lower interest rates have been offset by rising risk premia to keep expected returns close to average. Instead, the market has priced in future income growth on commercial properties far above the growth rates seen in the data. High implied growth rates are less extreme for nontraditional REIT sectors. Income growth expectations are also less extreme for international listed real estate.     

Impact mitigation or ecological restoration? Examining the environmental sustainability practices of multinational mining companies

This paper examines the environmental sustainability practices of multinational mining companies in addressing their impacts and promoting the sustainable development of local communities in Ghana. Although large-scale mining companies have embraced environmental sustainability, the drivers and the mechanisms for addressing their impacts throughout the mine life cycle is not fully understood because of the limited research in this area. The focus in this study involves an examination of the drivers for environmental sustainability in a weak and non-enabling institutional context and the mechanisms for addressing impacts on biodiversity, water quality and quantity, and ambient climate. The findings show that the environmental sustainability practices of multinational mining companies are determined by regulatory compliance and corporate environmental responsibility based on perceived ethical obligation. Additionally, we find gaps in mine closure planning and rehabilitation because of the limited requirement for biodiversity restoration in the domains of flora repopulation and active fauna reintroduction. This paper provides empirical and theoretical insights for academics and practitioners in industry and policymaking.     

Markov-switching dynamic factor models in real time

We extend the Markov-switching dynamic factor model to account for some of the specificities of the day-to-day monitoring of economic developments from macroeconomic indicators, such as mixed sampling frequencies and ragged-edge data. First, we evaluate the theoretical gains of using data that are available promptly for computing probabilities of recession in real time. Second, we show how to estimate the model that deals with unbalanced panels of data and mixed frequencies, and examine the benefits of this extension through several Monte Carlo simulations. Finally, we assess its empirical reliability for the computation of real-time inferences of the US business cycle, and compare it with the alternative method of forecasting the probabilities of recession from balanced panels.     

The Distributional and Allocative Impacts of Virtual Labor Mobility across Time Zones through Communication Networks

Using a specific‐factors' model, with two goods (a shift‐working good and a non‐shift‐working good), three factors (capital specific to shift‐working, land specific to non‐shift‐working and labor) and two countries (Home and Foreign), which are located in different time zones, we highlight the impact of trade in labor services via communication networks on factor prices and production patterns. If two countries are identical in size, then under free trade in labor services, all workers work only in their local daytime, and night shift in each country is performed by imported labor services supplied by residents of the other country in their local daytime. Night‐time wage becomes the same as daytime wage (a wage equalization result). Other factor prices are also equalized. In both countries, capital rental rate increases, while land rent decreases. However, if two countries are different in size, trade in labor services does not equalize wages: in the large country, wages for night‐shift workers are higher than daytime wages and some residents work at night; in the small country, daytime wages become higher than night‐time wages and no one works at night, and night‐shift work is done by imported labor services from the large country. Land rent in the small country decreases. Land rent in the large country may or may not decrease, but it is always higher than in the small country. Capital rental rates in both countries are equalized and increase.     

Knowledge management through the development of knowledge repositories: towards work degradation

This paper questions the consequences of the use of electronic knowledge repositories for work and employment. Drawing on critical research suggesting that knowledge management associated with such tools presents similarities to scientific management principles, it proposes to examine the following key research question: how do employees experience the transformation of the employment relationship when a knowledge repository is introduced to the workplace? The inquiry is grounded in an exploratory qualitative case study of a knowledge management system designed to foster knowledge‐sharing in a Belgian public administration. The findings illustrate two complementary outcomes: this system resulted in employees experiencing deskilling and work degradation, and was met with resistance. Significantly, this paper considers work degradation as a reflexive phenomenon in the context studied, where knowledge‐sharing systems produced deskilling and resistance as part of a specific re‐regulation process.     

Extracting Nonlinear Signals from Several Economic Indicators

We develop a twofold analysis of how the information provided by several economic indicators can be used in Markov switching dynamic factor models to identify the business cycle turning points. First, we compare the performance of a fully nonlinear multivariate specification (one‐step approach) with the ‘shortcut’ of using a linear factor model to obtain a coincident indicator, which is then used to compute the Markov switching probabilities (two‐step approach). Second, we examine the role of increasing the number of indicators. Our results suggest that one step is generally preferred to two steps, especially in the vicinity of turning points, although its gains diminish as the quality of the indicators increases. Additionally, we also obtain decreasing returns of adding more indicators with similar signal‐to‐noise ratios. Using the four constituent series of the Stock–Watson coincident index, we illustrate these results for US data. Copyright © 2014 John Wiley & Sons, Ltd.     

Oblivious equilibrium for concentrated industries

This article explores the application of oblivious equilibrium (OE) to highly concentrated markets. We define a natural extended notion of OE, called partially oblivious equilibrium (POE), that allows for there to be a set of strategically important firms (the “dominant” firms), whose firm states are always monitored by every other firm in the market. We perform computational experiments that explore the characteristics of POE, OE, and Markov perfect equilibrium (MPE), and find that POE generally performs well in highly concentrated markets. We also derive error bounds for evaluating the performance of POE for cases where MPE cannot be computed.     

Seemingly inconsistent analyst revisions

In about 20%–30% of cases where an analyst revises two outputs (namely, earnings estimates, target prices, or stock recommendations) simultaneously, the two estimates are revised in opposite directions. Existing literature notes that these inconsistent outputs are widespread, and concludes that they are lower-quality, driven by strategic bias, and are viewed as less valid by investors. We find that these characterizations are generally inaccurate. Apparent inconsistency is largely driven by accounting and economic factors, with only limited evidence that investment banking-related conflicts play a role. Moreover, inconsistent outputs are neither less accurate than consistent outputs nor do they resolve less investor uncertainty upon their release. Overall, our results suggest that researchers should be cautious in interpreting the correlation between analyst outputs as a measure of bias or quality, and in using a single analyst output as a proxy for an analyst's overall views.     

POSTERIOR‐PREDICTIVE EVIDENCE ON US INFLATION USING EXTENDED NEW KEYNESIAN PHILLIPS CURVE MODELS WITH NON‐FILTERED DATA

Changing time series properties of US inflation and economic activity, measured as marginal costs, are modeled within a set of extended New Keynesian Phillips curve (NKPC) models. It is shown that mechanical removal or modeling of simple low‐frequency movements in the data may yield poor predictive results which depend on the model specification used. Basic NKPC models are extended to include structural time series models that describe typical time‐varying patterns in levels and volatilities. Forward‐ and backward‐looking expectation components for inflation are incorporated and their relative importance is evaluated. Survey data on expected inflation are introduced to strengthen the information in the likelihood. Use is made of simulation‐based Bayesian techniques for the empirical analysis. No credible evidence is found on endogeneity and long‐run stability between inflation and marginal costs. Backward‐looking inflation appears stronger than forward‐looking inflation. Levels and volatilities of inflation are estimated more precisely using rich NKPC models. The extended NKPC structures compare favorably with existing basic Bayesian vector autoregressive and stochastic volatility models in terms of fit and prediction. Tails of the complete predictive distributions indicate an increase in the probability of deflation in recent years. Copyright © 2014 John Wiley & Sons, Ltd.