ROUGH DRAFT authorea.com/87967
Main Data History
Export
Show Index Toggle 0 comments
  •  Quick Edit
  • Welcome to Authorea!

    “You know how it is. You pick up a book, flip to the dedication, and find that, once again, the author has dedicated a book to someone else and not to you. Not this time.”

    Neil Gaiman, Anansi Boys

    To Camil, the Naruro boy*

    It was at the Karlstad University library in the year 2008 when the light bulb moment struck. The Anselin’s book on spatial analysis came into my hands and stayed with me until today. The day of completing the last chapter. The day of bringing the thesis to an endc

    It never crossed my mind that I’d go live in another country. But as unlikely as it was, once I went, I never looked back. After living and studying in Poland, Sweden, and Germany. It was France which conquered my heart. Yet, our love was laborious, demanding, and grueling. Exactly seven years now living in Paris. That journey, from a mute new expat to an eventually quite fluent (or let’s use with impunity a word O.K.) French speaker, from knowing nobody to saying Hi! to all the “boulangers” and butchers on my street, from wolfing down donuts to relishing the French Pâtisserie with a capital letter, from being airy-fairy to becoming a serious mother.

    That journey would not be the same without a couple of people met on its way. To Prof. André de Palma. Oh! I have already struck without even sending a warning signal. So yes, the first “Thank you” goes to this distinct, yet very particular, professor for being demanding the way he is and for making me stay in Paris after my master program ended up and my adult life began; Next, I send all my gratitude to all the Seventh EU Framework Program SustainCity Project members, mentioning Saif in particular, with whom I shared the desk at the E.N.S. Cachan office and without whom playing music at 7 P.M. while taking a break from work would not be fun otherwise.

    No thesis would be accomplished without the following smaller and bigger personae. I am indebted to:

    My international family: the Erasmus Mundus Program students who not only substituted my family but also perfectly complemented it, notably Alice for sending me nicely strong Karma coffee from the Laos mountains and lemongrass tea from Thailand to wind down from the coffee effect, Esfandiar, Yan, my Kabutar Mina for millions “miss you”, “miss you” words!, my awe-inspiring friend Tara, and my little Chinese sister Guodi. This one’s for you. You probably know why.

    My second international family for sharing the floor in the American Fondation: my favorite dancing Rida for her never-failing optimism, my American Polish brother Mark Zaborowski, multitalented Baidy, and to Tierra for her writing talent who helped me scrape through my very first scientific paper.

    Ana, the real fighter and the Taekwondo Master for “<3s” and accepting me as I am; Gordon Bowker, Jerry Baldwin, Zev Siegl for founding Starbucks, so that we could find there a secondary office with Ana; Meno, Vadim, godfather Marouene, Adams - the tektonic specialist and the best uncle, Hamza number one and Hamza number two, the rockets builder Heric, and finally the most talented and probably the youngest Senior Researcher from the Statistics Finland. Hi Henri.

    Friends from Ifsttar and the DEST Laboratory: Benoit for showing me how cool French people can be; “Irritating” David who kept on reminding me not to take myself too seriously; Katia, Christine, and Hoai-Thu, the Ifsttar super mothers!; and the most original and the best coiffé Kevin from the Ifsttar cafeteria for providing the strong enough coffee.

    Prof. Michel Bierlaire who let me join his team at the École Polytechnique Fédérale de Lausanne for a couple of months during my thesis and who gave me the chance to answer correctly maybe two out of his hundreds super challenging questions; and all the members of his team: always in trouble Yousef, Shadi, Marija, the genius Iliya, eating porridge at 4 P.M. Flurin, Antonin, running fast Tomas, Evantia, strong Riccardo, Anna, and Stefan.

    My heroes: Prof. Anselin who I never met in my life but who is responsible for my love to spatial analysis and whose work in many ways motivated this project; My idol, Prof. LeSage who I had a tremendous honor to meet and to talk to about my research, whose comments helped clarify my own thinking, and who almost convinced me that Bayesian analysis is the remedy to all the World’s problems; Prof. Krzysztof Malaga, a definition of hard work and a great example to students.

    Slowly heading to an end of dedication, I will definitely not forget to thank: Nicolas, with whom looking for new ideas and writing articles was an unspeakable joy of creation, for staying attentive and excited after not closing an eye during a couple of nights. It is not an easy task to be a multi-task young father-researcher;

    Matthieu, the best supervisor you could imagine to work with, to whom I have a huge respect for not only being a great professional mentor, but especially a great human;

    Jean-Loup, the thesis director, whose encouragement and support of all my projects were essential;

    and all the PhD Committee members for your time and patience while reading this thesis.

    Finally, I am most deeply thankful to the closest ones: My father, the best advice-giver and the fantastic professor, who installed within me a love of science, who encouraged me to change my study field from finance and banking to econometrics. Thank you for being stubborn enough at that moment of my life!; My father (the same one) to whom I promised that I will never ever go for a PhD. He waited for a moment and said... “Oh yes, darling, you will”; My mom for her never-ever-ending support (literally), for these thousand Whatsapp, Facebook, gmail, phone... messages per day. Dziekuje!; My grandma, the most energetic grandmother on Earth, I guess; My older (and of course more clever) sister Kamila for being an inspiration in ALL the life domains; The best-est Marta. A word “best” would not be enough in her case. Yyyyes! Adel, the biggest Cyril Lignac eater, the worst swimmer and bike rider I’ve got to know, the most dedicated father, and the best husband. You are perfect to me.

    ... and to Camil who decided to cheerfully teethe when I was trying to finish my thesis. To Camil, the Naruro boy without whose unvarying emotional realm of love and a constant smile this thesis would have been completed in half the time.

    Love you guys.

    After these couple of words worthy (or not) of your attention before the story even begins... 3,5 year that this thesis was in the making. Here’re four chapters. Nearly everything I intended is in it, and still the thesis is not full. I cried, I hurt, I tried, I failed, and I failed again, and I learnt. Good and bad ideas are in it along with only a little bit of despondency and enormous pleasure of discovering. Here’re four chapters through which I tried to briefly and gracefully communicate four things. Each chapter tells one story. All the stories create an image which I could definitely keep on painting further. But let’s close it for now and let’s raise the curtains.

    in boldface, italic ((“Heart of a Goof” by P.G. Wodehouse. “To my daughter Leonora without whose never-failing sympathy and encouragement this book would have been finished in half the time.”)) ((indescribably))

    ((indescribable joy of creation.)) ((And on top of these are all the gratitude I have for you.)) ((Pain and excitement are in it, and feeling good or bad and evil thoughts and good thoughts - the pleasure of design and some despair and the indescribable joy of creation.))

    “If you wait to do everything until you’re sure it’s right, you’ll probably never do much of anything.” – Win Borden

    Paraphrasing the quote of Winston Churchill, courage of writing thesis is going from failure to failure without losing enthusiasm (Original quote: “Courage is going from failure to failure without losing enthusiasm.” – Winston Churchill)

    Introduction

    1. Tezy i cel pracy - 1 strona, dlaczego to jest wazne i warte zachodu. 2. Analiza literaturowa (wez z papierow lub raportow + ksiazki wazne) 3. Opisac pokrotce co bedzie w rozdzialach (2 strony) 4. Rozdzialy

    1. Location choices of newly created establishments: Spatial patterns at the aggregate level 2. Euclidean versus network distance in business location: A probabilistic mixture of hurdle-Poisson models 3. Location choices under strategic interactions: Interdependence of establishment types 4. Locational strategies of multi-store firms.

    GENERAL INTRODUCTION

    1 XXX GENERAL XXX

    XXX

    This thesis is breathing new life into the location choice models of establishments. 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. A clear distinction between an establishment and a firm should be made in the first place. An establishment is defined as a distinct economic unit that produces goods or services at a single physical location. In contrast, a firm is a legal entity that consists of one or more establishments or plants under common ownership and control (van Wissen, 2000).

    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 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?

    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 WHY SHOULD WE BOTHER?

    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) 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 hurdle (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) 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 also in the first chapter of this thesis 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.

    1.2.3) In the third chapter we further enhance the literature on the location choices, this time incorporating strategic interactions among establishments. 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 task to adapt existing discrete-choice models. Yet, being non-strategic means that an establishment 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.

    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. A appropriately 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).

    Strategic interactions have been largely unsung in the empirical analyses since the year 1929 when Hotelling (1929) brought the discussion in the industrial organization literature. Most of the papers are less than a decade old (Bajari et al., 2013). This literature is in its infancy, in part, due to the complexity of expressions for the probabilities used in the models which increases along with the number of locations and establishment types (Draganska et al., 2008).

    We estimate a static discrete game of incomplete information to obtain a Bayesian Nash Equilibrium at the group level using data at the aggregate level. We permit asymmetries across establishment types in the impact of interaction effects and exogenous market characteristics. We develop one location choice model which embraces seven individual models for seven establishment types run simultaneously to account for interactions from all the types o