CAPITALIZATION OF GOVERNMENT SUPPORT IN AGRICULTURAL LAND PRICES: WHAT DO WE KNOW?

Abstract.  The objective of this paper is to provide an overview of existing literature, both theoretically and empirically, on the extent to which agricultural subsidies do translate into higher land values and rents and finally benefit landowners instead of agricultural producers. Our review shows that agricultural support policy instruments contribute to increasing the rental price of farmland, and that the extent of this increase closely depends on the level of the supply price elasticity of farmland relative to those of other factors/inputs on the one hand, and on the range of the possibilities of factor/input substitution in agricultural production on the other hand. The empirical literature shows that land prices and rents have in general a significant positive and inelastic response to government support. Such inelastic response is thought to reflect the uncertain future of the farm programmes. And in general, studies have indicated that land prices are more responsive to government-based returns than to market-based returns.     

Shadow vs. market prices in explaining land allocation: Subsistence maize cultivation in rural Mexico

Prices may fail to explain farmers’ land allocation if the relevant decision prices are “shadow prices” that deviate from market prices. This may be the case for farmers who attach significant non-market values to their crops. I theoretically explain why land allocation may not respond to market signals even if transaction costs are not binding. I use nationally representative rural household data from Mexico to show that shadow prices better explain the land subsistence farmers allocate to traditional maize in this center of maize diversity. I discuss the importance of non-market values in understanding supply response and on-farm conservation of traditional crops.     

Normative Violence in Domestic Service: A Study of Exploitation,Status, and Grievability

Journal of Business Ethics - This paper contributes to business ethics by focusing on consumption that is characterized by normative violence. By drawing on the work of Judith Butler this study of...     

Incomplete regulation, market competition and collusion

Regulators often do not regulate all firms competing in a given sector. Due to product substitutability, unregulated competitors have incentives to bribe regulated firms to have them overstate their costs and produce less, thereby softening competition. The best collusion-proof contract entails distortions both for inefficient and efficient regulated firms (distortion ‘at the top’). But a contract inducing active collusion may do better by allowing the regulator to ‘team up’ with the regulated firm to indirectly tax its competitor. The best such contract is characterized. It is such that the unregulated firm pays the regulated one to have it truthfully reveals its inefficiency. We finally compare those contracts.     

Under What Conditions Is an Insurance Guaranty Fund Beneficial for Policyholders?

In this article, we derive conditions in an imperfect market setting, under which the introduction of a self‐supporting insurance guaranty fund improves the position of the policyholders. When a guaranty fund is advantageous given homogeneous firms in the market, all policyholders benefit from it to the same extent, if they have the same underlying risk preferences and are charged identical premiums. In a more realistic heterogeneous setting, the introduction of an insurance guaranty fund is in general no longer beneficial for all policyholders in the same manner. Hence, systematic wealth transfers take place between the policyholders of different insurance companies. As a possible solution, and in order to counteract this effect, we introduce a framework for utility‐based fund charges.     

Optimal portfolio choice in real terms: Measuring the benefits of TIPS

In this paper we solve an optimal portfolio choice problem to measure the benefits of Treasury Inflation Indexed Securities (TIPS) to investors concerned with maximizing real wealth. We show how the introduction of a real riskless asset completes the investor asset space, by contrasting optimal portfolio allocations with and without such assets. We use historical data to quantify gains from availability of TIPS in the presence of other asset classes such as equities, commodities, and real estate. We draw a distinction between buy-and-hold long-term investors for whom TIPS fully displace nominal risk-free assets and short-term investors for whom TIPS improve the investment opportunity set of real returns. Finally, we show how gains from TIPS are tempered by the availability of alternative assets that covary with inflation, such as gold and real estate.     

Do rating agencies’ decisions impact stock risks? Evidence from European markets

This article analyses the effect of rating agencies’ decisions on stock risks for European issuers concerning five kinds of events. Our approach is an extension of dummy variable regression event study methodology, using a GARCH(1,1) estimation to capture simultaneously the impact on both systematic and specific stock risks. This new methodology allows us to obtain both global results by categories of rating decisions and individual results, event by event. We document, globally, a positive impact of upgrading on systematic risk, a negative impact of rating confirmation on specific risk, and no significant impact in all other cases. Regarding event-by-event results, the proportion of rating actions exhibiting a significant effect on risk is almost always observed between 20% and 30%. The weak evidence of a global effect on systematic risk may be due to the lack of informational content of the rating decisions on the stocks’ risk, or the existence of rebalancing effects between systematic and idiosyncratic risks. Furthermore, it should be noticed that the decline in volatility in case of a rating affirmed is an insight of the certification role played by the agencies.     

Spatial modelling of claim frequency and claim size in non-life insurance

In this paper, models for claim frequency and average claim size in non-life insurance are considered. Both covariates and spatial random effects are included allowing the modelling of a spatial dependency pattern. We assume a Poisson model for the number of claims, while claim size is modelled using a Gamma distribution. However, in contrast to the usual compound Poisson model, we allow for dependencies between claim size and claim frequency. A fully Bayesian approach is followed, parameters are estimated using Markov Chain Monte Carlo (MCMC). The issue of model comparison is thoroughly addressed. Besides the deviance information criterion and the predictive model choice criterion, we suggest the use of proper scoring rules based on the posterior predictive distribution for comparing models. We give an application to a comprehensive data set from a German car insurance company. The inclusion of spatial effects significantly improves the models for both claim frequency and claim size, and also leads to more accurate predictions of the total claim sizes. Further, we detect significant dependencies between the number of claims and claim size. Both spatial and number of claims effects are interpreted and quantified from an actuarial point of view.