Do house prices reflect fundamentals? Aggregate and panel data evidence

We investigate whether recently high and consequently rapidly decreasing U.S. house prices have been justified by fundamental factors such as personal income, population, house rent, stock market wealth, building costs, and mortgage rate. We first conduct the standard unit root and cointegration tests with aggregate data. Nationwide analysis potentially suffers from problems of the low power of stationarity tests and the ignorance of dependence among regional house markets. Therefore, we also employ panel data stationarity tests which are robust to cross-sectional dependence. Contrary to previous panel studies of the U.S. housing market, we consider several, not just one, fundamental factors. Our results confirm that panel data unit root tests have greater power as compared with univariate tests. However, the overall conclusions are the same for both methodologies. The house price does not align with the fundamentals in sub-samples prior to 1996 and from 1997 to 2006. It appears that the real estate prices take long swings from their fundamental value and it can take decades before they revert to it. The most recent correction (a collapsed bubble) occurred around 2006.     

Impacts of increased bioenergy demand on global food markets: an AgMIP economic model intercomparison

Integrated Assessment studies have shown that meeting ambitious greenhouse gas mitigation targets will require substantial amounts of bioenergy as part of the future energy mix. In the course of the Agricultural Model Intercomparison and Improvement Project (AgMIP), five global agro‐economic models were used to analyze a future scenario with global demand for ligno‐cellulosic bioenergy rising to about 100 ExaJoule in 2050. From this exercise a tentative conclusion can be drawn that ambitious climate change mitigation need not drive up global food prices much, if the extra land required for bioenergy production is accessible or if the feedstock, for example, from forests, does not directly compete for agricultural land. Agricultural price effects across models by the year 2050 from high bioenergy demand in an ambitious mitigation scenario appear to be much smaller (+5% average across models) than from direct climate impacts on crop yields in a high‐emission scenario (+25% average across models). However, potential future scarcities of water and nutrients, policy‐induced restrictions on agricultural land expansion, as well as potential welfare losses have not been specifically looked at in this exercise.     

Land‐use change trajectories up to 2050: insights from a global agro‐economic model comparison

Changes in agricultural land use have important implications for environmental services. Previous studies of agricultural land‐use futures have been published indicating large uncertainty due to different model assumptions and methodologies. In this article we present a first comprehensive comparison of global agro‐economic models that have harmonized drivers of population, GDP, and biophysical yields. The comparison allows us to ask two research questions: (1) How much cropland will be used under different socioeconomic and climate change scenarios? (2) How can differences in model results be explained? The comparison includes four partial and six general equilibrium models that differ in how they model land supply and amount of potentially available land. We analyze results of two different socioeconomic scenarios and three climate scenarios (one with constant climate). Most models (7 out of 10) project an increase of cropland of 10–25% by 2050 compared to 2005 (under constant climate), but one model projects a decrease. Pasture land expands in some models, which increase the treat on natural vegetation further. Across all models most of the cropland expansion takes place in South America and sub‐Saharan Africa. In general, the strongest differences in model results are related to differences in the costs of land expansion, the endogenous productivity responses, and the assumptions about potential cropland.     

Comparing supply‐side specifications in models of global agriculture and the food system

This article compares the theoretical and functional specification of production in partial equilibrium (PE) and computable general equilibrium (CGE) models of the global agricultural and food system included in the AgMIP model comparison study. The two model families differ in their scope—partial versus economy‐wide—and in how they represent technology and the behavior of supply and demand in markets. The CGE models are “deep” structural models in that they explicitly solve the maximization problem of consumers and producers, assuming utility maximization and profit maximization with production/cost functions that include all factor inputs. The PE models divide into two groups on the supply side: (1) “shallow” structural models, which essentially specify area/yield supply functions with no explicit maximization behavior, and (2) “deep” structural models that provide a detailed activity‐analysis specification of technology and explicit optimizing behavior by producers. While the models vary in their specifications of technology, both within and between the PE and CGE families, we consider two stylized theoretical models to compare the behavior of crop yields and supply functions in CGE models with their behavior in shallow structural PE models. We find that the theoretical responsiveness of supply to changes in prices can be similar, depending on parameter choices that define the behavior of implicit supply functions over the domain of applicability defined by the common scenarios used in the AgMIP comparisons. In practice, however, the applied models are more complex and differ in their empirical sensitivity to variations in specification—comparability of results given parameter choices is an empirical question. To illustrate the issues, sensitivity analysis is done with one global CGE model, MAGNET, to indicate how the results vary with different specification of technical change, and how they compare with the results from PE models.     

THE USE OF INTELLECTUAL PROPERTY RIGHTS AND INNOVATION BY MANUFACTURING FIRMS IN CANADA

The objective of the paper is to determine how the utilisation of intellectual property rights (IPRs) by Canadian manufacturing firms is related to their characteristics, activities, competitive strategies and industry sector in which they operate. The principal source of information used in this endeavour is the Statistics Canada Survey of Innovation 1999.

The paper starts with an overview of other studies that looked at the use of intellectual property rights in Canada. Follows a conceptual framework presenting variables likely to explain the use specific IPRs by Canadian manufacturing firms.

The use of IPRs is to a great extent correlated with basic economic characteristics of firms, their activities and industry environment. A series of estimated logit regressions predict the probability that a firm will use a specific IPR instrument. Also estimated is the contribution of the use of IPRs to the probability that a firm innovates.

The decision of a firm to use IPRs is often not independent of the decision to innovate. To eliminate the potential endogeneity bias I estimate a two-stage logit model. A comparison of the single- and two-stage logit models shows that the nexus from the protection of intellectual property (patents) to innovation may be weaker than indicated by the single equation model.     

A model of optimal advertising expenditures in a dynamic duopoly

This paper develops a dynamic model of oligopolistic advertising competition. The model is general enough to include predatory advertising and informative advertising as particular cases. The analysis is conducted in a differential game framework and compares the open-loop and feedback equilibria to the efficient outcome. It is found that for the informative advertising competition game, advertising levels are closer to the collusive outcomes in a feedback equilibrium. In the case of predatory advertising, expenditures are inefficiently high in a feedback equilibrium and the open-loop solution is more efficient.     

Did rent deregulation alter tenure choice decisions in the Czech Republic?

Our study is the first that explicitly links rent deregulation and the choice between owning and renting (the tenure choice) using household decisions over a 1‐year period. The rent deregulation process in the Czech Republic started in 2006, two years after joining the European Union. By design, the maximum regulated rent appreciation depended explicitly on real estate prices, which accelerated the pace of deregulation due to rapidly rising prices at the time. A unique dataset enables us to track the tenure choice of households from consumption surveys for subsequent years. The proportion of households that switched from renting to owning sharply increased among renters of regulated apartments. We show that this change was caused by the deregulation process. In contrast, rent deregulation makes owners and renters paying market rent less likely to change ownership status.