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Travel demand forecasting is essential for many decisions, such as infrastructure investments and policy measures. Traditionally travel demand modelling has considered trip frequency, mode, destination and route choice. This thesis considers two other choice dimensions, hypothesised to have implications for travel demand forecasting. The first part investigates how the increased possibilities to overcome space that ICT (information and communication technology) provides, can be integrated in travel demand forecasting models. We find that possibilities of modelling substitution effects are limited, irrespective of data source and modelling approach. Telecommuting explains, however, a very small part of variation in work trip frequency. It is therefore not urgent to include effects from telecommuting in travel demand forecasting. The results indicate that telecommuting is a privilege for certain groups of employees, and we therefore expect that negative attitudes from management, job suitability and lack of equipment are important obstacles. We find also that company benefits can be obtained from telecommuting. No evidences that telecommuting gives rise to urban sprawl is, however, found. Hence, there is ground for promoting telecommuting from a societal, individual and company perspective. The second part develops a departure time choice model in a mixed logit framework. This model explains how travellers trade-off travel time, travel time variability, monetary and scheduling costs, when choosing departure time. We explicitly account for correlation in unobserved heterogeneity over repeated SP choices, which was fundamental for accurate estimation of the substitution pattern. Temporal constraints at destination are found to mainly restrict late arrival. Constraints at origin mainly restrict early departure. Sensitivity to travel time uncertainty depends on trip type and intended arrival time. Given appropriate input data and a calibrated dynamic assignment model, the model can be applied to forecast peak-spreading effects in congested networks. Combined stated preference (SP) and revealed preference (RP) data is used, which has provided an opportunity to compare observed and stated behaviour. Such analysis has previously not been carried out and indicates that there are systematic differences in RP and SP data. / QC 20100825

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Dans cette thèse, nous nous intéressons aux questions de l’hétérogénéité inobservée et des solutions en coin dans les modèles de choix d’assolements. Pour répondre à ces questions, nous nous appuyons sur un modèle de choix de production multicultures avec choix d’assolement de forme NMNL, dont nous proposons des extensions. Ces extensions conduisent à des problèmes spécifiques d’estimation, auxquels nous apportons des solutions. La question de l’hétérogénéité inobservée est traitée en considérant une spécification à paramètres aléatoires. Ceci nous permet de tenir compte des effets de l’hétérogénéité inobservée sur l’ensemble des paramètres du modèle. Nous montrons que les versions stochastiques de l’algorithme EM sont particulièrement adaptées pour estimer ce type de modèle.Nos résultats d’estimation et de simulation montrent que les agriculteurs réagissent de façon hétérogène aux incitations économiques et que ne pas tenir compte de cette hétérogénéité peut conduire à des effets simulés de politiques publique biaisés.Pour tenir compte des solutions en coin dans les choix d’assolement, nous proposons une modélisation basée sur les modèles à changement de régime endogène avec coûts fixes associés aux régimes. Contrairement aux approches basées sur des systèmes de régression censurées, notre modèle est cohérent d’un point de vue micro-économique. Nos résultats montrent que les coûts fixes associés aux régimes jouent un rôle important dans le choix des agriculteurs de produire ou non certaines cultures et qu’ils constituent, à court terme, un déterminant important des c / In this thesis, we are interested in questions of unobserved heterogeneity and corner solutions in acreage choice models. To answer these questions, we rely on a NMNL acreage share multi-crop models, of which we propose extensions. These extensions lead to specific estimation problems, to which we provide solutions.The question of unobserved heterogeneity is dealt with by considering a random parameter specification. This allows us to take into account the effects of the unobserved heterogeneity on all the parameters of the model. We show that the stochastic versions of the EM algorithm are particularly suitable for estimating this type of modelOur estimation and simulation results show that farmers react heterogeneously to economic incentives and that ignoring this heterogeneity can lead to biased simulated effects of public policies.In order to take account of the corner solutions in acreage choices, we propose modelling based on endogenous regime switching models with regime fixed costs. Unlike approaches based on censored regression systems, our model is “fully” consistent from a micro-economic viewpoint. Our results show that the regime fixed costs play an important role in farmers’ choice to produce or not some crops and they are, in the short term, an important determinant of acreage choices.

Le changement structurel en agriculture suscite beaucoup d’intérêt de la part des économistes agricoles ainsi que des décideurs politiques. Pour prendre en compte l’hétérogénéité du comportement des agriculteurs, une approche par les modèles de mélange de chaînes de Markov est appliquée pour la première fois en économie agricole pour analyser ce processus. La performance de cette approche est d’abord testée en utilisant une forme simplifiée du modèle, puis sa forme générale est appliquée pour étudier l’impact de certaines mesures de politique agricole. Pour identifier les principaux canaux d’interdépendance entre exploitations voisines dans les processus du changement structurel, une approche de mélange non-Markovienne a été appliquée pour modéliser la survie et l’agrandissement des exploitations agricolesTrois principales conclusions découlent de cette thèse. Tout d’abord, la prise en compte de l’hétérogénéité dans les processus de transition des exploitations agricoles permet de mieux représenter le changement structurel et conduit à des prédictions plus précises de la distribution des exploitations, comparé aux modèles généralement utilisés jusqu’ici. Deuxièmement, l’impact des principaux facteurs du changement structurel dépend lui aussi des types non-observables d’exploitations mis en évidence. Enfin, le cadre du modèle de mélange permet également de révéler différents types de relations inobservées entre exploitations voisines qui contribuent au changement structurel observé à un niveau global ou régional. / Structural change in farming has long been the subject of considerable interest among agricultural economists and policy makers. To account for heterogeneity in farmers’ behaviours, a mixture Markov modelling framework is applied to analyse this process for the first time in agricultural economics. The performance of this approach is first investigated using a restrictive form of the model, and its general form is then applied to study the impact of some drivers of structural change, including agricultural policy measures. To identify channels through which interdependency between neighbouring farms arises in this process, the mixture modelling approach is applied to analyse both farm survival and farm growth. The main conclusions of this thesis are threefoldFirstly, accounting for the generally unobserved heterogeneity in the transition process of farms allows better representing structural change in farming and leads to more accurate predictions of farm-size distributions than the models usually used so far. Secondly, the impacts of the main drivers of structural change themselves depend on the specific unobservable farm types which are revealed by the model. Lastly, the mixture modelling approach enables identifying different unobserved relationships between neighbouring farms that contributes to the structural change observed at an aggregate or regional level.

In the first chapter of this thesis, we investigate the impact of human capital and wage structure on the gender pay in a panel of European countries using a newly available and appropriate database for cross-country comparisons and a comparable methodology for each country. <p><p>Our first question is :What role do certain individual characteristics and choices of working men and women play in shaping the cross-country differences in the gender pay gap? What is the exact size of the gender pay gap using the “more appropriate” database available for our purpose? Giving that there are mainly only two harmonized data-sets for comparing gender pay gap throughout Europe: the European Community Household Panel (ECHP) and the European Structure of Earning Survey (ESES). Each database having its shortages: the main weakness of the ECHP is the lack of perfect reliability of the data in general and of wages in particular. However the main advantage of this database is the panel-data dimension and the information on both households and individuals. The data of the ESES is, on the contrary, of a very high standard but it only covers the private sector and has a cross-sectional dimension. Furthermore only few countries are currently available :Denmark, Belgium, Spain, Ireland and Italy. <p>We use the European Structure of Earning Survey (ESES) to analyse international differences in gender pay gaps in the private sector based on a sample of five European economies: Belgium, Denmark, Ireland, Italy and Spain. Using different methods, we examine how wage structures, differences in the distribution of measured characteristics and occupational segregation contribute to and explain the pattern of international differences. Furthermore, we take account of the fact that indirect discrimination may influence female occupational distributions. We find these latter factors to have a significant impact on gender wage differentials. However, the magnitude of their effect varies across countries.<p><p>In the second chapter, we analyse the persistence of the gender pay differentials over time in Europe and better test the productivity hypothesis by taking into account unobserved heterogeneity. <p><p>Our second question is :What is the evolution of the pay differential between men and women over a period of time in Europe? And what is the impact of unobserved heterogeneity? <p>The researcher here provides evidence on the effects of unobserved individual heterogeneity on estimated gender pay differentials. Using the European Community Household Panel (ECHP), we present a cross-country comparison of the evolution of unadjusted and adjusted gender pay gaps using both cross-section and panel-data estimation techniques. The analysed countries differ greatly with respect to labour market legislation, bargaining practices structure of earnings and female employment rates. On adjusting for unobserved heterogeneity, we find a narrowed male-female pay differential, as well as significantly different rates of return on individual characteristics. In particularly, the adjusted wage differential decreases by 7 per cent in Belgium, 14 per cent in Ireland, between 20-30 per cent Germany, Italy, the Netherlands and Spain and of 41 per cent and 54 per cent in the UK and in Denmark respectively. <p><p>In the third chapter, we investigate causes of the gender pay gap beyond the gender differences in observed and unobserved productive characteristics or simply the sex. Explanations of the gender pay gap may be the penalty women face for having children. Obviously, the motherhood wage penalty is relevant to larger issues of gender inequality given that most women are mothers and that childrearing remains a women’s affair. Thus, any penalty associated with motherhood but not with fatherhood affects many women and as such contributes to gender inequalities as the gender pay gap. Furthermore, the motherhood wage effect may be different along the wage distribution as women with different earnings may not be equal in recognising opportunities to reconcile their mother’s and earner’s role. This brings us to our third question. <p><p>Our third question is :What is the wage effect for mothers of young children in the household? And does it vary along the wage distribution of women?<p>This chapter provides more insight into the effect of the presence of young children on women’s wages. We use individual data from the ECHP (1996-2001) and both a generalised linear model (GLM) and quantile regression (QR) techniques to estimate the wage penalty/bonus associated with the presence of children under the age of sixteen for mothers in ten EU Member States. We also correct for potential selection bias using the Heckman (1979) correction term in the GLM (at the mean) and a selectivity correction term in the quantile regressions. To distinguish between mothers according to their age at the time of their first birth, wage estimations are carried out, separately, for mothers who had their first child before the age of 25 (‘young mothers’) and mothers who had their first child after the age of 25 (‘old mothers’). Our results suggest that on average young mothers earn less than non-mothers while old mothers obtain a gross wage bonus in all countries. These wage differentials are mainly due to differences in human capital, occupational segregation and, to a lesser extent, sectoral segregation between mothers and non-mothers. This overall impact of labour market segregation, suggests a “crowding” explanation of the family pay gap – pay differential between mothers and non-mothers. Nevertheless, the fact that we still find significant family pay gaps in some countries after we control for all variables of our model suggests that we cannot reject the “taste-based” explanation of the family gap in these countries. Our analysis of the impact of family policies on the family pay gap across countries has shown that parental leave and childcare policies tend to decrease the pay differential between non-mothers and mothers. Cash and tax benefits, on the contrary, tend to widen this pay differential. Sample selection also affects the level of the mother pay gap at the mean and throughout the wage distribution in most countries. Furthermore, we find that in most countries inter-quantile differences in pay between mothers and non-mothers are mainly due to differences in human-capital. Differences in their occupational and sectoral segregation further shape these wage differentials along the wage distribution in the UK, Germany and Portugal in our sample of young mothers and in Spain in the sample of old mothers.<p><p>In the fourth chapter, we analyse the combined effect of motherhood and the family status on women’s wage.<p> <p>Our fourth question is :Is there a lone motherhood pay gap in Europe? And does it vary along the wage distribution of mothers?<p>Substantial research has been devoted to the analysis of poverty and income gaps between households of different types. The effects of family status on wages have been studied to a lesser extent. In this chapter, we present a selectivity corrected quantile regression model for the lone motherhood pay gap – the differential in hourly wage between lone mothers and those with partners. We used harmonized data from the European Community Household Panel and present results for a panel of European countries. We found evidence of lone motherhood penalties and bonuses. In our analysis, most countries presented higher wage disparities at the top of the wage distribution rather than at the bottom or at the mean. Our results suggest that cross-country differences in the lone motherhood pay gap are mainly due to differences in observed and unobserved characteristics between partnered mothers and lone mothers, differences in sample selection and presence of young children in the household. We also investigated other explanations for these differences such as the availability and level of childcare arrangements, the provision of gender-balanced leave and the level of child benefits and tax incentives. As expected, we have found significant positive relationship between the pay gap between lone and partnered mothers and the childcare, take-up and cash and tax benefits policies. Therefore improving these family policies would reduce the raw pay gap observed. <p> / Doctorat en Sciences économiques et de gestion / info:eu-repo/semantics/nonPublished