MULTIATTRIBUTE UTILITY THEORY,INTERTEMPORAL UTILITY,AND CORRELATION AVERSION

Convenient assumptions about qualitative properties of the intertemporal utility function have generated counterintuitive implications for the relationship between atemporal risk aversion and the intertemporal elasticity of substitution. If the intertemporal utility function is additively separable, then the latter two concepts are the inverse of each other. We review a theoretical specification with a long lineage in the literature on multi‐attribute utility and use this theoretical structure to guide the design of a series of experiments that allow us to identify and estimate intertemporal correlation aversion. Our results show that subjects are correlation averse over lotteries with intertemporal income profiles.     

Wolves' contribution to structural change in grazing systems among swiss alpine summer farms: The evidence from causal random forest

The return of wolves to Swiss mountains and the damage they cause to sheep and goat herds in the region have raised concerns about a consequent wave of farm closures. In this paper, we examine the relationship between wolf attacks and the decline of Alpine summer farms, a specific high-altitude farm type. We collected farm structure data and monitoring data on wolf attacks between 2004 and 2021 and analysed them using a causal random forest method, enabling a detailed analysis of the relation between wolf attacks and the number of different types of Alpine summer farms at a regional level. The results show that the farming systems are unaffected by incidental and infrequent wolf attacks, but that a high number of wolf attacks in a region is related to faster decrease in number of grazing systems where sheep are most vulnerable to such attacks. In contrast, systems that allow for better herd protection tend to show an increase in areas with frequent wolf attacks.     

Bridging the Energy Efficiency Gap: A Field Experiment on Lifetime Energy Costs and Household Appliances

Providing consumers with information that can lead to more energy-efficient choices can help reduce energy use and greenhouse gas emissions while reducing costs to consumers. A natural field experiment is conducted in collaboration with an electrical retailer to test strategies for influencing sales of household appliances. The experiment involves two product categories, fridge-freezers and tumble driers. Information on lifetime energy cost of appliances is provided through a label and training of sales staff. For fridge-freezers, the authors find no significant effects. For tumble driers, the combined treatment and training treatment reduce average energy use of tumble driers sold by 4.9% and 3.4%, respectively. The effect is strongest initially, over 12% on average for the first 3 months for the combined treatment but declines over time. The effect is significant at the 5% level for the combined treatment while not significant for sales staff training.     

The New Keynesian Phillips curve and the role of expectations: Evidence from the CESifo World Economic Survey

We provide evidence on the fit of the hybrid New Keynesian Phillips curve for selected Euro zone countries, the US and the UK. Instead of imposing rational expectations and estimating the Phillips curve by the Generalized Method of Moments, we use direct measures of inflation expectations from the CESifo World Economic Survey. Our main findings are as follows: (i) The use of survey data gives empirical results, which are more reliable than those obtained from the GMM approach. (ii) The purely forward-looking Phillips curve can be rejected in favor of the hybrid New Keynesian Phillips curve. (iii) The estimated coefficients on past inflation are higher when using survey expectations than when using the rational expectations GMM approach. (iv) It remains unclear whether real unit labor costs or a measure of the output gap should be used as a proxy for real marginal costs. (v) Theory-based restrictions lead to an improvement of the empirical results.     

Estimating a high-frequency New-Keynesian Phillips curve

This paper estimates a high-frequency New-Keynesian Phillips curve via the generalized method of moments. Allowing for higher-than-usual frequencies strongly mitigates the problems of small-sample bias and structural breaks. Applying a daily frequency allows us to obtain estimates for the Calvo parameter of nominal rigidity over a very short period—for instance for the recent financial and economic crisis—which can then be easily transformed into their low-frequency equivalences. With Argentine data from the end of 2007 to the beginning of 2011 we estimate the daily Calvo parameter and find that on average prices remain fixed for approximately two to three months which is in line with recent microeconomic evidence.