Integrated bio-economic models as tools to support land-use decision making: a review of potential and limitations

Bio-economic modelling has become a useful tool for anticipating the outcomes of policies and technologies before their implementation. Advances in mathematical programming have made it possible to build more comprehensive models. In an overview of recent studies about bio-economic models applied to land-use problems in agriculture and forestry, we evaluated how aspects such as uncertainty, multiple objective functions, system dynamics and time have been incorporated into models. We found that single objective models were more frequently applied at the farm level, while multiple objective modelling has been applied to meet concerns at the landscape level. Among the objectives, social aspects are seldom represented in all models, when being compared to economic and environmental aspects. The integration of uncertainty is occasionally a topic, while stochastic approaches are more frequently applied than non-stochastic robust methods. Most multiple-objective models do not integrate uncertainty or sequential decision making. Static approaches continue to be more recurrent than truly dynamic models. Even though integrating multiple aspects may enhance our understanding of a system; it involves a tradeoff between complexity and robustness of the results obtained. Land-use models have to address this balance between complexity and robustness in order to evolve towards robust multiple-objective spatial optimization as a prerequisite to achieve sustainability goals.     

Output-inflation tradeoffs in 34 countries

This article examines the responsiveness of real output to the variability of inflation and aggregate demand. In the manner of Lucas (1973), estimates of the output-inflation tradeoff are computed for a large sample of countries. This measure is then correlated with the variances of the inflation rate and the growth rate in nominal income. Because differences in inflation variance (and hence the tradeoff) are viewed as the outcomes of differences in demand variance, correlations between these two variables are also reported. Cross-time and cross-country results provide a good measure of support for Lucas and the notion that attempts to exploit the tradeoff weaken it.     

Finding Closest Targets in Non-Oriented DEA Models: The Case of Convex and Non-Convex Technologies

This paper draws attention for the fact that traditional Data Envelopment Analysis (DEA) models do not provide the closest possible targets (or peers) to inefficient units, and presents a procedure to obtain such targets.It focuses on non-oriented efficiency measures (which assume that production units are able to control, and thus change, inputs and outputs simultaneously) both measured in relation to a Free Disposal Hull (FDH) technology and in relation to a convex technology. The approaches developed for finding close targets are applied to a sample of Portuguese bank branches.     

The relationship between satisfaction and loyalty: A mediator analysis

This study proposes a multiple mediation model to analyze the relationship between satisfaction and loyalty. The study's contribution to the literature is to examine, empirically, the main antecedents and determinants of this endogenous variable in greater depth. Thus, the research fills a gap in the literature through its analysis of the mediating role of perceived switching costs and the perceived lack of attractiveness of alternative offerings. This study applies variance-based structural equation modeling via partial least squares to a sample of 785 customers from 74 insurance companies in the service sector. The results show that perceived switching costs – to a greater extent – and the perceived lack of attractiveness of alternative offerings – to a lesser extent – are significant mediators in the relationship between satisfaction and loyalty.     

HEGY Tests in the Presence of Moving Averages*

We analyze the asymptotic distributions associated with the seasonal unit root tests of Hylleberg et al. (1990) for quarterly data when the innovations follow a moving average process. Although both the t‐ and F‐type tests suffer from scale and shift effects compared with the presumed null distributions when a fixed order of autoregressive augmentation is applied, these effects disappear when the order of augmentation is sufficiently large. However, as found by Burridge and Taylor (2001) for the autoregressive case, individual t‐ratio tests at the semi‐annual frequency are not pivotal even with high orders of augmentation, although the corresponding joint F‐type statistic is pivotal. Monte Carlo simulations verify the importance of the order of augmentation for finite samples generated by seasonally integrated moving average processes.     

Can entrepreneurial firms benefit from product piracy?

We examine the potential benefits of product piracy to entrepreneurial firms. Specifically, we use a resource-based perspective to show that a decrease in the inimitability of an entrepreneurial firm's intellectual property does not necessarily diminish performance when piracy increases the value of this resource, and an information economics perspective to explain why and when imitation can increase the value of an intellectual property resource. This explanation reconciles empirical studies that indicate mixed results. It also expands the resource-based view by suggesting that reducing the value of one resource can directly increase the value of another.     

Does Energy Consumption Respond to Price Shocks? Evidence from a Regression‐Discontinuity Design

We exploit unique features of a recently introduced tariff schedule for natural gas in Buenos Aires to estimate the short‐run impact of price shocks on residential energy utilization. The schedule induces a non‐linear and non‐monotonic relationship between households' accumulated consumption and unit prices, thus generating exogenous price variation, which we exploit in a regression‐discontinuity design. We find that a price increase causes a prompt and significant decline in gas consumption. The results also indicate that consumers respond more to recent past bills than to expected prices, which argues against an assumption of perfect awareness of complex price schedules by consumers.