The relation between forest clearance and household income among native Amazonians: Results from the Tsimane' Amazonian panel study, Bolivia

The Amazon rain forest harbors some of the world's richest biological diversity. During the twentieth century, two types of actors cleared that forest: native Amazonians and outside encroachers. Of the two actors, we know more about what drives outside encroachers to clear forest than about what drives native Amazonians to clear forest. The past research focus has served well because during the twentieth century outside encroachers cleared most of the Amazonian forest. But the past research focus needs to be expanded because native Amazonians are claiming de jure stewardship of the forests they inhabit, and with tighter jurisdiction over those forests will likely come changes in the amount of forest native Amazonians clear. Prior research in rural areas of low-income nations suggests that household income affects household forest clearance. To estimate the effects of household real income on the total forest area (old-growth + fallow) cleared by households we use a panel composed of five annual household surveys (2002-2006, inclusive) from 324 households of a native Amazonian society in Bolivia (Tsimane'). We control for household and village fixed effects and use an instrumental variable for household income. We find positive and significant household real income elasticities of forest clearance of 0.35 and 0.47 and an increase in forest clearance of 5.3%/year. The main finding stood up well to sensitivity analysis. These estimates suggest that in the near future, the forest in the Tsimane' territory will likely face increasing pressure from the Tsimane' themselves, not just from outside encroachers.     

Toward a more practical approach to evaluating programs: The Multi‐Objective Realization approach

Emerging trends indicate that programs are being used to deliver benefits that may not be fully harnessed from single sets of uncoordinated projects. To support this movement, it is essential to have suitable measurement frameworks to assess the contribution of these activities and supply decision makers with valuable data on whether their objectives are being realized. This paper introduces the Multi‐Objective Realization Method (MORE) to help measure the strategic contributions of programs. The main principles of MORE underline the importance of a formal strategy to elicit and develop program objectives and to frame those objectives within defined measurement dimensions.     

Education, corruption, and the distribution of income

We examine how the interaction between education and corruption affects institutional reform and economic development. While corruption reduces average income and education, education increases not only output and hence potential corruption rents, but also produces more informed electorates that better monitor government actions. We find that economies with intermediate levels of education remain in a poverty trap since the level of skills creates sufficient corruption rents but not enough monitoring. Economies with low or high levels of education can escape the poverty trap, and inequality plays a key role in determining whether this occurs through a change in institutions or an expansion of education.     

The Effects of Executive,Firm, and Board Characteristics on Executive Exit

We estimate a hazard model of the probability of top corporate executives exiting their firms over the period 1996–2010. Our main findings are that: (1) female executives have greater likelihoods of exit than males, (2) the likelihood of exit increases with the independence of the board and decreases with the fraction of the board that is female and the average age of board members, and (3) a higher percentage of independent directors on the board lowers the probability of exit more for females than for males. Further, controlling for exit risk reduces the well‐documented compensation differential between men and women.     

When do managers listen to the market? Impact of learning in acquisitions of private firms

We study the influence of market signals and agency problems on the decision to cancel an announced acquisition. We find major differences between deals involving private vs. public targets. First, controlling for the value of expected synergies, acquisitions are less likely to be cancelled when the target is private rather than public. This finding supports learning rather than the alternative common-information hypothesis. Second, better manager-shareholder interest alignment makes the cancellation of a “bad” deal more likely only when the target is a private firm. This suggests bidder agency problems have a greater influence on acquisition outcome (i.e., learning) when the target is private. Third, cancellation is more likely for private targets when their post-announcement abnormal returns are low, especially if the method of payment includes stock. This indicates that it is important to control for bidder overvaluation when testing the managerial learning hypothesis. Overall, both the learning and agency hypotheses help explain observed differences in deal completion by target type.     

Searching for Goldilocks: The Distance‐Based Capitalization Effects of Local Public Services

This article empirically models the effect of distance on residential property values of three different types of services, fire, police and emergency medical services. Interesting economic trade‐offs emerge as service station proximity provides both amenity and disamenity effects. Using over three million home sales from the state of Florida along with two different measures of distance, this study provides evidence of nonlinear capitalization effects on local housing values. A difference‐in‐difference model utilizing new facility construction provides corroborating evidence of these findings.     

Forecasting US consumer price index: does nonlinearity matter?

The objective of this article is to predict, both in sample and out of sample, the consumer price index (CPI) of the US economy based on monthly data covering the period of 1980:1–2013:12, using a variety of linear (random walk (RW), autoregressive (AR) and seasonal autoregressive integrated moving average (SARIMA)) and nonlinear (artificial neural network (ANN) and genetic programming (GP)) univariate models. Our results show that, while the SARIMA model is superior relative to other linear and nonlinear models, as it tends to produce smaller forecast errors; statistically, these forecasting gains are not significant relative to higher-order AR and nonlinear models, though simple benchmarks like the RW and AR(1) models are statistically outperformed. Overall, we show that in terms of forecasting the US CPI, accounting for nonlinearity does not necessarily provide us with any statistical gains.     

Adam Smith on lotteries: an interpretation and formal restatement

The paper concerns a neglected aspect of the Wealth of Nations (with the notable exception of D. Levy 1999 Levy, D. M. 1999. “Adam Smith’s Katallactic Model of Gambling: Approbation from the Spectator.” Journal of the History of Economic Thought 21 (1): 81–91. doi:10.1017/S1053837200002868.[Crossref] , [Google Scholar]), dealing directly with decision under risk. In a few pages from book I, chapter 10, Adam Smith explicitly named “lotteries” various objects of choice (possible occupations, or investment opportunities, for instance) and provided an analysis which standard expected utility glasses would hardly fit. Taking this into account allows a better understanding of the part played by typical characters like the “projector” or the “sober man”, in such matters as Smith’s conception of entrepreneurship or of the credit market. The use of some modern concepts in decision analysis (inverse stochastic dominance, rank dependent utility, prudence toward risk), is a means to show the existence, in Smith’s work, of an original theory from decision under risk, where his analysis of lotteries in the Wealth of Nations is consistent with statements from his moral philosophy on asymmetric sensitivity to gains and losses and to the regulating part played by the impartial spectator.     

A note on how to measure hubbing practices in airline networks

Benefits and costs associated to hubbing practices of airlines are still subject to much debate. In the previous literature, some standard spatial concentration indices have been proposed to measure it. However, we show that these indices are “ill-defined” because they do not take into account the salient characteristic of hubbing: connecting passengers. The purpose of this research is to present a new methodology which avoids the pitfalls of other methods. Our new methodology also analyzes the level of concentration of the connecting passengers studying two different dimensions: hub airports and routes. Finally, we apply our methodology to some US carriers.