Well-being effects of self-employment: A spatial inquiry

Our paper presents an empirical analysis of entrepreneurial well-being using a large-scale longitudinal household survey from the UK that tracks almost 50,000 individuals across seven waves over the period 2009–2017, as well as a number of exploratory case studies. We contribute to the existing literature by investigating how entrepreneurial well-being varies across locations along the urban-rural continuum, and across wealthy-deprived neighbourhoods. We use a Coarsened Exact Matching (CEM) approach to compare the well-being outcomes of individuals who switch into self-employment from waged employment, and show that entrepreneurial well-being, in the form of job satisfaction, is significantly higher for those living in semi-urban locations, relative to those living in urban and rural locations. We argue that semi-urban locations provide an optimal combination of ease of doing business and quality of life. Our results also show that individuals in wealthy neighbourhoods who switch into self-employment experience higher job satisfaction than otherwise comparable individuals living in materially deprived neighbourhoods, although the latter experience greater levels of life satisfaction following the switch.     

The Effect of Risk Context on the Value of a Statistical Life: a Bayesian Meta-model

This paper presents the first value of statistical life (VSL) meta-analysis that empirically estimates correction factors for ‘out of context’ benefits transfer (BT) purposes. In the field of mortality risk reductions elicited willingness to pay values in one risk context, say road safety, are frequently applied in other risk contexts like air pollution. However, differences in risk perception and the population at risk across contexts are likely to result in diverging VSL estimates. In a meta-analysis of 26 international stated preference studies, a Bayesian model is estimated regressing contingent values for mortality risk reductions, originating from three different risk contexts, on the characteristics of the risk reduction itself and additional variables characterizing the underlying studies. A willingness to pay (WTP) premium for mortality risk reductions in the air pollution and general mortality risk context relative to improving road safety is observed. Evaluated at the mean, road safety VSL estimates should be multiplied by a factor 1.8 before being applicable in the air pollution context. Moreover, in an illustrative BT exercise we find limited overlap in the set of context specific predictive VSL distributions. Consequently, ‘out of context’ BT results in a substantial over- or underestimation of the VSL.     

Methods and tools for integrated assessment of land use policies on sustainable development in developing countries

For stimulating sustainable development in developing countries, land use patterns and land use changes are considered critical, and therefore effective and efficient land use policies are needed. In this paper we present a methodological framework that has been developed in a joint European and developing countries project (LUPIS – Land Use Policies and Sustainable Development in Developing Countries), to assess the impact of land use policies on sustainable development in developing countries. An illustrative application is presented for a case study in China, where water pollution due to agriculture in Taihu Basin is a major problem.     

Prioritising land to be preserved for agriculture: A context-specific value tree

In Belgium as in many other countries, agricultural land is under pressure for development of other land uses. This paper presents a method for setting priorities for preservation of land for agriculture. The method is based on a participatory approach through which a value tree is formulated. This results in a list of criteria to define farmland value, which is explicitly linked to the objectives for farmland preservation. The value tree allows the list of criteria to be determined in a structured and consistent way. The participatory process contributes to the development of a shared vision on farmland preservation. The approach also incorporates context specificity, as shown by its application for farmland preservation in Flanders.     

Globalization vs. localization: global food challenges and local solutions

The objective of this study was to examine the effect of global–local interactions on food production and consumption in Ghana, and identify possible local solutions. Primary data were collected using a combination of quantitative‐qualitative methods, which included focus group discussions and one‐on‐one interviews. Approximately 450 household heads were randomly selected and interviewed between August 2007 and August 2008 in Eastern, Central, Upper East and Northern Regions of Ghana. Findings revealed increasing consumption of foreign rice as opposed to decreasing consumption of local rice and other staples like millet, sorghum and yam because of global–local interactions. However, opportunities exist to re‐localize production‐consumption patterns through the use of ‘glocal foods’ like improved ‘koose and waakye’. Referencing the situation in Ghana, the study recommends improved production and processing practices backed with appropriate technologies that reflect changing consumption dynamics in order to take full advantage of opportunities created as a result of global–local interactions.     

Choice Certainty and Consistency in Repeated Choice Experiments

The main objective of this study is to examine how repeated choice affects preference learning in stated preference experiments. We test different hypotheses related to preference learning by analyzing response patterns and asking respondents in a choice experiment to report their experienced certainty when going through the choice tasks. In a split-sample test, we show that follow-up choice certainty questions are procedural invariant. The self-reported certainty results indicate that learning occurs, but econometric testing procedures do not identify any significant impact of learning effects on parameter estimates or variance across choice tasks. Additional tests of choice consistency suggest that preferences in the choice experiment are stable and coherent.     

Libor Market Models versus Swap Market Models for Pricing Interest Rate Derivatives: An Empirical Analysis

We empirically compare Libor and Swap Market Models for thepricing of interest rate derivatives, using panel data on pricesof US caplets and swaptions. A Libor Market Model can directlybe calibrated to observed prices of caplets, whereas a SwapMarket Model is calibrated to a certain set of swaption prices.For both models we analyze how well they price caplets and swaptionsthat were not used for calibration. We show that the Libor MarketModel in general leads to better prediction of derivative pricesthat were not used for calibration than the Swap Market Model.Also, we find that Market Models with a declining volatilityfunction give much better pricing results than a specificationwith a constant volatility function. Finally, we find that modelsthat arechosen to exactly match certain derivative prices areoverfitted; more parsimonious models lead to better predictionsfor derivative prices that were not used for calibration. JELClassification: G12, G13, E43.     

The Non-Trivial Choice between Innovation Indicators

We discuss the strengths and weaknesses of five alternative innovation indicators: R&D, patent applications, total innovation expenditure and shares in sales taken by imitative and by innovative products as they were measured in the 1992 Community Innovation Survey (CIS) in the Netherlands. We conclude that the two most commonly used indicators (R&D and patent applications) have more (and more severe) weaknesses than is often assumed. Moreover, our factor analysis suggests that there is little correlation between the various indicators. This underlines the empirical relevance of various sources of bias of innovation indicators as discussed in this paper.     

Time‐varying Hedge Ratios: A Principal‐agent Approach

We use the classic agency model to derive a time‐varying optimal hedge ratio for low‐frequency time‐series data: the type of data used by crop farmers when deciding about production and about their hedging strategy. Rooted in the classic agency framework, the proposed hedge ratio reflects the context of both the crop farmer's decision and the crop farmer's contractual relationships in the marketing channel. An empirical illustration of the Dutch ware potato sector and its futures market in Amsterdam over the period 1971–2003 reveals that the time‐varying optimal hedge ratio decreased from 0.34 in 1971 to 0.24 in 2003. The hedging effectiveness, according to this ratio, is 39%. These estimates conform better with farmers’ interest in using futures contracts for hedging purposes than the much higher estimates obtained when price risk minimisation is the only objective considered.