Mixed Logit Model Performance and Distributional Assumptions: Preferences and GM foods

Using mixed logit models to analyse choice data is common but requires ex ante specification of the functional forms of preference distributions. We make the case for greater use of bounded functional forms and propose the use of the Marginal Likelihood, calculated using Bayesian techniques, as a single measure of model performance across non nested mixed logit specifications. Using this measure leads to very different rankings of model specifications compared to alternative rule of thumb measures. The approach is illustrated using data from a choice experiment regarding GM food types which provides insights regarding the recent WTO dispute between the EU and the US, Canada and Argentina and whether labelling and trade regimes should be based on the production process or product composition.

Bayesian estimation of willingness-to-pay where respondents mis-report their preferences

We introduce a modified conditional logit model that takes account of uncertainty associated with mis-reporting in revealed preference experiments estimating willingness-to-pay (WTP). Like Hausman et al. [Journal of Econometrics (1988) Vol. 87, pp. 239-269], our model captures the extent and direction of uncertainty by respondents. Using a Bayesian methodology, we apply our model to a choice modelling (CM) data set examining UK consumer preferences for non-pesticide food. We compare the results of our model with the Hausman model. WTP estimates are produced for different groups of consumers and we find that modified estimates of WTP, that take account of mis-reporting, are substantially revised downwards. We find a significant proportion of respondents mis-reporting in favour of the non-pesticide option. Finally, with this data set, Bayes factors suggest that our model is preferred to the Hausman model.

Modifying willingness to pay estimates where respondents mis-report their preferences

The likelihood for the Logit model is modified, so as to take account of uncertainty associated with mis-reporting in stated preference experiments estimating willingness to pay (WTP). Monte Carlo results demonstrate the bias imparted to estimates where there is mis-reporting. The approach is applied to a data set examining consumer preferences for food produced employing a nonpesticide technology. Our modified approach leads to WTP that are substantially downwardly revised.

An investigation into factors affecting the occupational choices of nominated farm heirs in Ireland

The resilience of family farming is an important feature of the structure of the farming industry in many countries, due largely to the 'smooth' succession of farms from one generation to the next. The stability of this structure is now threatened by the widening gap between the income expected from farming when compared with non-farming occupations in an economy like Ireland, operating at almost full employment. Nominated farm heirs are increasingly unlikely to choose full-time farming as their preferred occupation. To identify the factors that affect this occupational choice, a multinomial logit model is developed and applied to Irish data to examine the farm, economic and personal characteristics that influence a nominated heir's decision to enter farming as opposed to some non-farming occupation. The results show a significant negative relationship between higher education and the choice of full-time farming as an occupation. The interdependence between education and occupational choices is further explored using a bivariate probit model. The main findings are: the occupational choice and the decision to continue with higher education are made jointly; the nominated heirs on more profitable farms are less likely to pursue tertiary education and therefore more likely to enter full-time farming. The model developed is sufficiently general for studying the phenomenon of succession on farms.

Designer buildings: an evaluation of the price impacts of signature architects

This study investigates whether commercial offices designed by signature architects in the United States achieve rental premiums compared to commercial offices designed by nonsignature architects. Focusing on buildings designed by winners of the Prizker Prize and the Gold Medal awarded by the American Institute of Architects, we create a sample of commercial office buildings designed by signature architects drawing on CoStar's national database. We use a combination of hedonic regression model and a logit model to estimate the various rent determinants. While the first stage measures the typical rental price differential above the typical building in a particular sub-market over a specific timeframe, the second stage identifies a potential price differential over a set of buildings closely matched on important characteristics (such as age, size, location etc.). We find that in both stages offices design by signature architects exhibit a premium. However these results are preliminary. The premium could be indeed an effect of the name of the architect, but others factors such as micro-market conditions might be the cause. Further tests are needed to confirm the validity of our results.

Stated attribute non-attendance in successive choice experiments

Attribute non-attendance in choice experiments affects WTP estimates and therefore the validity of the method. A recent strand of literature uses attenuated estimates of marginal utilities of ignored attributes. Following this approach, we propose a generalisation of the mixed logit model whereby the distribution of marginal utility coefficients of a stated non-attender has a potentially lower mean and lower variance than those of a stated attender. Model comparison shows that our shrinkage approach fits the data better and produces more reliable WTP estimates. We further find that while reliability of stated attribute non-attendance increases in successive choice experiments, it does not increase when respondents report having ignored the same attribute twice.

National boundaries and the location of multinational firms in Europe

Using data on 5,102 subsidiaries established in the period 1991–1999, we examine the location choice of multinational firms of different nationalities in 47 regions of five EU countries. In particular we estimate a nested logit model and find that European multinationals consider regions across different countries as relatively closer substitutes than regions within national borders. This is consistent with the hypothesis that European regions compete to attract foreign direct investments relatively more across than within countries. However, in line with previous studies, we also find that national boundaries still play some role in choices made by non-European multinationals.

Location choices of multinational firms in Europe: the role of EU cohesion policy

Using data on 5509 foreign subsidiaries established in 50 regions of 8 EU countries over the period 1991–1999, we estimate a mixed logit model of the location choice of multinational firms in Europe. In particular, we focus on the role of EU Cohesion Policy in attracting foreign investors from both within and outside Europe. We find that, after controlling for the role of agglomeration economies as well as a number of other regional and country characteristics and allowing for a very flexible correlation pattern among choices, Structural and Cohesion funds allocated by the EU to laggard regions have indeed contributed to attracting multinationals. These policies as well as other determinants play a different role in the case of European investors as opposed to non-European ones.

Model selection for the mixed logit with Bayesian estimation

In this paper, the mixed logit (ML) using Bayesian methods was employed to examine willingness-to-pay (WTP) to consume bread produced with reduced levels of pesticides so as to ameliorate environmental quality, from data generated by a choice experiment. Model comparison used the marginal likelihood, which is preferable for Bayesian model comparison and testing. Models containing constant and random parameters for a number of distributions were considered, along with models in ‘preference space’ and ‘WTP space’ as well as those allowing for misreporting. We found: strong support for the ML estimated in WTP space; little support for fixing the price coefficient a common practice advocated and adopted in the environmental economics literature; and, weak evidence for misreporting.