deletions | additions       diff --git a/Introduction_1_Tezy_i_cel__.tex b/Introduction_1_Tezy_i_cel__.tex  index 6368bd4..767db16 100644  --- a/Introduction_1_Tezy_i_cel__.tex  +++ b/Introduction_1_Tezy_i_cel__.tex 
...
Chapter III  3. Location choices under strategic interactions: Interdependence of establishment types  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 our present paper. 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’ de- cisions. 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.  Many key strategic decisions establishments make, such as where to set up in the market, involve discrete choices (Draganska et al., 2008). These decisions are fairly complex, yet, particularly important since, unlike other marketing mix elements, they are less adjustable in the short-run without incurring significant costs (Zhu and Singh, 2009). In the literature on location choices of establishments, usually only one activity sector, typically an industrial or a re- tail sector, is considered at a time. In very sparse empirical applications, when locational choice models are developed for several activity sectors, each of the 10 model is typically run independently (see, e.g., Chatman et al., 2016; Bucz- kowska and Lapparent, 2014).  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. 30 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).  However, less is known about how to correctly adapt location choice mo-  35 dels to study establishments’ discrete choices when they are interrelated (Draganska et al., 2008). Strategic motives are widespread phenomena and they are fundamental in establishments’ location choices, in particular. Yet, the small amount of attention the topic has received is surprising.  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 45 along with the number of locations and establishment types (Draganska et al., 2008).   There are several relevant reasons why incorporating strategic interactions may turn out to be necessary. If strategic effects matter and are ignored, other 115 factors included in the payoffs will be estimated with a bias (Draganska et al., 2008). The magnitude of such bias will depend on the degree to which strategic effects matter.   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).  The presence of competitive establishments seems to have a negative effect on payoffs and therefore a negative influence on new establishments’ formation (Seim, 2006 ; Zhu and Singh, 2009 ; Chatman et al., 2016). The fact that the number of establishments in the same industry category tends to negatively predict the number of establishment births in that industry suggests that the own-industry competition effect overrides any localized agglomeration economies (Chatman et al., 2016).  Zhu and Singh (2009) observe significant asymmetries across players in their response to market conditions and interactions.  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 report results for location choice models run simultaneously for seven establishment types.  influence of variables might be quite different depending on the establishment type considered. As highlighted by Min (1987), the retail, service sector, and professional location analyses are likely to be highly sensitive to the demand and revenue-generating factors. Whereas cost factors should play a critical role rather in the locational strategies of, e.g., warehouses or goods-producing establishments.  While favorable market conditions, such as large base of consumers or users  and low cost characteristics, e.g., low cost labor, encourage establishments’ choices, such markets are also likely to attract competitors. In the long-run, the interaction of described different push and pull factors determines the observed location patterns by establishments (Zhu and Sing, 2009). Opposing forces drive profits. The trade-off between the proximity to competitors and the desirability of certain location characteristics should be pondered (Zhu and Singh, 2009 ; Seim, 2006).   According to Chang and Hsieh (2014), a proportion of rent expenses against sales should be carefully calculated. As the authors claim, "value for money" locations are usually hard to find due to the fact that most of this kind of sites are already being rented or that rent expenses of good locations, such as in the downtown or newly developed areas, are extremely high eliminating the profit. Aquirregabiria and Suzuki (2016) highlight the fact that attractive locations are typically expensive and can be associated with stronger competition.  Establishments should thus consider the trade-off between being accessible to many potential consumers or users, higher land prices, and ferocious competition when deciding where to open a new store.  Chapter IV  4. Locational strategies of multi-store firms