deletions | additions       diff --git a/If_you_wait_to_do__.tex b/If_you_wait_to_do__.tex  index e150c2e..0ab44fc 100644  --- a/If_you_wait_to_do__.tex  +++ b/If_you_wait_to_do__.tex 
...
1.1 KEY QUESTIONS  A number of key questions will be addressed along this thesis. First, location choice models use geo-referenced data, for which choice sets have an explicit spatial component. It is thus critical to understand how to represent spatial aspect in location choice models. Second, 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 fail by providing only a set of systematic steps for problem-solving without considering strategic interactions between the establishments in the market. One of the goals is to explore how to correctly adapt location choice models to study establishments' discrete choices when they are interrelated. Third, a firm can open a number of units and serves the market from multiple locations. Once again traditional theory and methods may not be suitable to situations wherein individual establishments instead of locating independently from each other, form a whole large organization, such as a chain facing in addition a fierce competition from other chains. There is a necessity to incorporate interactions between units within the same and competing firms. Illustrative questions that can be answered are: What is the nature and degree of competition for each of the analyzed chain?  How fast do the firm profit and the market power decline when the number of firms and their outlets in the market increases or when the distance to their rivals decreases? How %How  does a firm perceive a rival store located in a very close neighborhood and how if it is located far away?What is the nature and degree of competition for each of the analyzed chain?  An intensified research effort along the lines of location choices is still desirable to bring the answers to many questions of this type. 
...
1.2.1)   In this thesis, we concentrate our research on the Paris region, 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 the first 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 with no new creation. 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 hurdlemodel  (Mullahy, 1986) or the zero-inflated model (Lambert, 1992). The hurdle 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. 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 inquired: 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 in location decisions. We respond to the complaint voiced by Liviano-Solis and Arauzo-Carod (2013) and Bhat et al. (2014) that heretofore the hurdle model technique has not been well investigated when analyzing location patterns. These are the first challenges that we face in the first chapter of this thesis.  
...
1.2.2)   %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.   The second chapter extends the research on the hurdle model and the study presented in the first part of this thesis. The final decision of an establishment seems to be related to the surrounding economic landscape. When accounting for the linkage between neighboring observations, the decision on the spatial weight matrix specification should be made. 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. Euclidean distance is typically used in the empirical literature  and has been utilized as well  in the first chapter to account for spatial spillovers in location choice model. However, Euclidean distance is believed to be only one simplistic possibility out of an infinite number of shortest path relations. Other alternative distance metrics may 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. The Euclidean distance might thus not always be the most relevant one depending on a given problem. 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. 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 is 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 are 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.