deletions | additions       diff --git a/If_you_wait_to_do__.tex b/If_you_wait_to_do__.tex  index 8a14b8b..e5e4ad8 100644  --- a/If_you_wait_to_do__.tex  +++ b/If_you_wait_to_do__.tex 
...
GENERAL INTRODUCTION  This thesis is breathing new life into the location choice models of establishments. Location The need for methodological advances in order to model more realistically the complexity of establishments' decision-making processes, such as their optimal location choices is the key motivation of this thesis. First, location  choice models use geo-referenced data, for which choice sets have an explicit spatial component. It thus is critical to understand and represent spatial aspect in location choice models. In addition, what makes these discrete choices particularly interesting and challenging to analyze is that decisions of a particular establishment are interrelated with choices of the others. These thorny problems posed by the interdependence of decisions generally cannot be assumed away, without altering the realism of the model of establishment decision making. The conventional approaches to location selection, i.e., traditional theory and methods, fail by providing only a set of systematic steps for problem-solving without considering strategic interactions between the establishments in the market. Less is known about how to correctly adapt location choice models to study establishments' discrete choices when they are interrelated.  It is critical to understand and represent spatial aspect in location choice models. 1)  We In this thesis, we  concentrate our research on the Paris region, called as Ile-de-France - a vibrant and innovative region with over 5,6 million jobs, 37 percent of French executives, and 40 percent of national workforce in research and development. It is a 1st R&D hub in Europe and the third worldwide. 11.7 million people or over 19 percent of the country's population reside in the area which occupies only 2.2 percent of the surface of France. The Paris region is the third World touristic destination (in 2013) (Global Destination Cities Index 2015) with 16 millions of visitors from abroad. The GDP of the region amounts to 29 percent of total French GDP (IAU IdF, 2014) 31 percent of total French GDP (http://www.grand-paris.jll.fr/fr/paris/chiffres-cles/) that is 612 milliards euros (2012). It is 1st European city considering the number of firms classified in Fortune 500 (July 2014). Yet, the Paris region’s economy is spatially unbalanced (Combes et al., 2011). The region is highly heterogeneous, especially regarding economic activity. While few municipalities host a large number of new establishments, others struggle to be chosen by any, and a large group of municipalities is left. The Grand Paris is a development project for left with no new creation. Depending on  the whole of analyzed sector,  the Paris metropolitan area. It is designed percentage of municipalities left with no new establishment creation ranges from 34 percent up  to improve residents’ quality 69 percent. When the observed data display a higher fraction  of life, address regional inequalities and build zeros than would be typically explained by the standard count data models, two types of models can be suggested: the hurdle model (Mullahy, 1986) or the zero-inflated model (Lambert, 1992). The hurdle model, also called the two-part model, reflects  a sustainable city (https://www.societedugrandparis.fr/english). two-part decision making process.  It will cost around 32.4 billion euros (up to 2030). relaxes the assumption that the zero observations and the positive observations come from the same data generating process. The two-step decision-making process is reflected through the hurdle model interpretation.  Much work has been done in the domain of location choice models, however, several issues arise when analyzing involved phenomena, which scholars have yet to fully explore: 1) addressing the excess of zeros problem in the location choice model in highly heterogeneous geographic areas and 2) determining an appropriate way to accommodate spatial effects for location decisions. We respond to the complaint voiced by Liviano-Solis and Arauzo-Carod (2013) and Bhat et al. (2014) who notice that heretofore the hurdle model technique has not been fully explored when analyzing location phenomena. These are the first challenges that we face in the first chapter of this thesis.  Depending on the analyzed sector, the percentage of municipalities left with no new establishment creation ranges from 34 percent up to 69 percent. When the observed data display a higher fraction of zeros than would be typically explained by the standard count data models, two types of models can be suggested: the hurdle model (Mullahy, 1986) or the zero-inflated model (Lambert, 1992). The hurdle model, also called the two-part model, reflects a two-part decision making process. It relaxes the assumption that the zero observations and the positive observations come from the same data generating process. The two-step decision-making process is reflected through the hurdle model interpretation. We respond to the complaint voiced by Liviano-Solis and Arauzo-Carod (2013) and Bhat et al. (2014) who notice that heretofore the hurdle model technique has not been fully explored when analyzing location phenomena.  Much work has been done in 2)   %When selecting  the domain of appropriate  location choice models, however, several issues arise when analyzing involved phenomena, in  whichscholars have yet  to fully explore: 1) addressing the excess of zeros problem set up  in the location choice model in highly heterogeneous geographic areas and 2) determining market,  an appropriate way to accommodate spatial effects for location decisions. establishment may consider not only the characteristics of a particular area, but also the characteristics of neighboring zones.  These are the first challenges that we take in the first chapter.   When accounting for the linkage between neighboring observations since the final decision of an establishment should be related to the surrounding economic landscape, we need to decide on the spatial weight matrix specification. Yet, since there exist no solitary claim on the concept of space, the form of the weight matrix is largely debated. One of the problems hides in the definition of distance usually based on the straight-line segment connecting two locations. Extending the research presented in the first chapter of this thesis, where Euclidean distance was used to account for spatial spillovers in location choice model, other alternative distance metrics are to be proposed when building the spatial distance weight matrices.  Geographic factors such as terrain, land cover, infrastructure, and traffic congestion may cause agents not to follow pure Euclidean relations. Euclidean distance is believed to be only one simplistic possibility out of an infinite number of shortest path relations. The Euclidean distance might thus not always be the most relevant one depending on the problem considered. Interest in this question dates at least to the 1960s and research on network models in geography (Haggett 1967). There are insights to be gained by mindfully reconsidering and measuring distance depending on a given problem. The second chapter investigates establishments location decisions in the Paris region where high congestion, speed limits, or physical uncrossable barriers, such as rivers or industrial corridors can diminish or totally eliminate the linkage between neighboring areas. Rather than imposing a restrictive structure of the weight matrix, this research proposes a flexible toolkit to point which distance metric is more appropriate to correctly account for the surrounding economic landscape. A probabilistic mixture of two ”mono-distance” hurdle-Poisson models was developed. Each model’s latent class uses a different distance representation to incorporate spillover effects in location choices of establishments from several activity sectors. Seven distance metrics were considered: Euclidean distance, two road distances (with and without congestion), public transit distance, and the corresponding travel times. This methodology allows to capture the diversity of agents’ behavior, i.e., to distinguish establishments which are more time- or more distance-oriented given location.  3)  %In spite of recognizing the importance of incorporating spatial effects in establishments location decision processes, the literature is still scarce on previous attempts.  enhancing and extending the existing literature in a number of ways:  We incorporate strategic interactions among establishments.  ... is the key motivation of the third chapter. We shed light on strategic interactions, fundamental in establishments’ location choices, yet largely unheeded in the empirical literature. If establishments acted in isolation, it would be a relatively simple matter to adapt existing discrete-choice models. Yet, being non-strategic means that a firm ignores other players’ decisions. Less is known about how to correctly adapt location choice models to study establishments’ discrete choices when they are interrelated. In very sparse empirical applications, when locational choice models are developed for several activity sectors, each of the model is typically run independently.  1b)   %When selecting the appropriate location in which to set up in the market, an establishment may consider not only the characteristics of a particular area, but also the characteristics of neighboring zones.   Less is known about how to correctly adapt location choice models to study establishments' discrete choices when they are interrelated.  When accounting for the linkage between neighboring observations since the final decision What makes these discrete choices particularly interesting and challenging to analyze is that decisions  of an a particular  establishment should be related to the surrounding economic landscape, we need to decide on the spatial weight matrix specification. Yet, since there exist no solitary claim on the concept are interrelated with choices  ofspace,  the form of others because an establishment accounts for  the weight matrix is largely debated. One actions  of the other agents when making its own decisions (Draganska et al., 2008). These thorny  problems hides in posed by  the definition interdependence  of distance usually based on the straight-line segment connecting two locations. Extending decisions generally cannot be assumed away, without altering  the research presented in realism of  the first chapter model  of this thesis, where Euclidean distance was used establishment decision making (Berry and Reiss, 2007). The conventional approaches  to account location selection, i.e., traditional theory and methods, fail (Thill, 1997) by providing only a set of systematic steps  for spatial spillovers problem-solving without considering strategic interactions between the establishments  in location choice model, the market. Being non-strategic would mean that an establishment ignores  other alternative distance metrics are players’ decisions (Toivanen and Waterson, 2005). A properly specified model of simultaneous entry or location decisions needs  to be proposed when building the spatial distance weight matrices. recognize this interdependence of  profits (Berry and Reiss, 2007).  Geographic factors such as terrain, land cover, infrastructure, and traffic congestion may cause agents not to follow pure Euclidean relations. Euclidean distance is believed to be only one simplistic possibility out of an infinite number of shortest path relations. The Euclidean distance might thus not always be the most relevant one depending on the problem considered. Interest in this question dates at least to the 1960s and research on network models in geography (Haggett 1967). There are insights to be gained by mindfully reconsidering and measuring distance depending on a given problem. The second chapter investigates establishments location decisions in the Paris region where high congestion, speed limits, or physical uncrossable barriers, such as rivers or industrial corridors can diminish or totally eliminate the linkage between neighboring areas. Rather than imposing a restrictive structure of the weight matrix, this research proposes a flexible toolkit to point which distance metric is more appropriate to correctly account for the surrounding economic landscape. A probabilistic mixture of two ”mono-distance” hurdle-Poisson models was developed. Each model’s latent class uses a different distance representation to incorporate spillover effects in location choices of establishments from several activity sectors. Seven distance metrics were considered: Euclidean distance, two road distances (with and without congestion), public transit distance, and the corresponding travel times. This methodology allows to capture the diversity of agents’ behavior, i.e., to distinguish establishments which are more time- or more distance-oriented given location.   There is a need for more realistic studies of complex establishment’s decision-making processes. Even though the computational burden imposed by these models considering strategic interactions is relatively high, it seems that the costs imposed are more than offset by the benefits that accumulate/accrue (Draganska et al., 2008).  2)   %In spite of recognizing the importance of incorporating spatial effects in establishments location decision processes, the literature is still scarce on previous attempts. 4) We  enhancing and extending the existing literature in a number of ways:   We incorporate strategic interactions among establishments.   What makes these discrete choices particularly interesting and challenging to analyze is that decisions of a particular establishment are interrelated with choices of the others because an establishment accounts for the actions of other agents when making its own decisions (Draganska et al., 2008). These thorny problems posed by the interdependence of decisions generally cannot be assumed away, without altering the realism of the model of establishment decision making (Berry and Reiss, 2007). The conventional approaches to location selection, i.e., traditional theory and methods, fail (Thill, 1997) by providing only a set of systematic steps for problem-solving without considering strategic interactions between the establishments in the market. Being non-strategic would mean that an establishment ignores other players’ decisions (Toivanen and Waterson, 2005). A properly specified model of simultaneous entry or location decisions needs to recognize this interdependence of  profits (Berry and Reiss, 2007).  There is a need for more realistic studies of complex establishment’s decision-making processes. Even though the computational burden imposed by these models considering strategic interactions is relatively high, it seems that the costs imposed are more than offset by the benefits that accumulate/accrue (Draganska et al., 2008).  3) We   This thesis investigates establishments location decisions in the Paris region where high congestion, speed limits, or physical uncrossable barriers, such as rivers or industrial corridors can diminish or totally eliminate the linkage between neighboring areas.