scholarly journals Challenges in Merger Simulation Analysis

2011 ◽  
Vol 101 (3) ◽  
pp. 56-59 ◽  
Author(s):  
Christopher R Knittel ◽  
Konstantinos Metaxoglou
Keyword(s):  
Logit Model ◽  
Simulation Analysis ◽  
Consumer Welfare ◽  
Random Coefficient ◽  
Supply Side ◽  
Demand Side ◽  
Market Outcomes ◽  
Starting Values ◽  
Bertrand Game ◽  
Random Coefficient Logit

In this paper, we share our experience with merger simulations using a Random Coefficient Logit model on the demand side and assuming a static Bertrand game on the supply side. Drawing largely from our work in Knittel and Metaxoglou (2008), we show that different demand estimates obtained from different combinations of optimization algorithms and starting values lead to substantial differences in post-merger market outcomes using metrics such as industry profits, and change in consumer welfare and prices.

Simulated Maximum Likelihood Estimator for the Random Coefficient Logit Model Using Aggregate Data

2009 ◽  
Vol 46 (4) ◽  
pp. 531-542 ◽  
Author(s):  
Sungho Park ◽  
Sachin Gupta
Keyword(s):  
Maximum Likelihood ◽  
Logit Model ◽  
Regime Switching ◽  
Control Function ◽  
Sampling Error ◽  
Estimation Method ◽  
Aggregate Data ◽  
Random Coefficient ◽  
Simulated Maximum Likelihood ◽  
Random Coefficient Logit

The authors propose a simulated maximum likelihood estimation method for the random coefficient logit model using aggregate data, accounting for heterogeneity and endogeneity. The method allows for two sources of randomness in observed market shares: unobserved product characteristics and sampling error. Because of the latter, the method is suitable when sample sizes underlying the shares are finite. In contrast, Berry, Levinsohn and Pakes's commonly used approach assumes that observed shares have no sampling error. The method can be viewed as a generalization of Villas-Boas and Winer's approach and is closely related to Petrin and Train's “control function” approach. The authors show that the proposed method provides unbiased and efficient estimates of demand parameters. They also obtain endogeneity test statistics as a by-product, including the direction of endogeneity bias. The model can be extended to incorporate Markov regime-switching dynamics in parameters and is open to other extensions based on maximum likelihood. The benefits of the proposed approach are achieved by assuming normality of the unobserved demand attributes, an assumption that imposes constraints on the types of pricing behaviors that are accommodated. However, the authors find in simulations that demand estimates are fairly robust to violations of these assumptions.

Application of a Tax to E-Commerce Deliveries in Barcelona

2021 ◽  
pp. 036119812110124
Author(s):  
Genís Majoral ◽  
Francesc Gasparín ◽  
Sergi Saurí
Keyword(s):  
Cost Benefit Analysis ◽  
Cost Benefit ◽  
Supply Side ◽  
Environmental Tax ◽  
Positive Outcomes ◽  
Demand Side ◽  
Benefit Analysis ◽  
Revenue Collection ◽  
Last Mile ◽  
The Impact

The number of e-commerce transactions is increasing worldwide. Deliveries of goods purchased online generate externalities throughout the whole supply chain and, particularly, the increasing concern about the last-mile distribution of goods. The escalating presence of vans in cities contributes to poor air quality, climate change, noise, and congestion. So far, the majority of solutions to address this issue are based on the supply side, such as electric vans, optimizing the routing and pick-up-points, and so forth. Even in other transport sectors, pricing solutions are well known, yet they have not been extended to e-commerce delivery. This paper aims to propose an environmental tax falling on the demand side and equaling the externalities from this activity. The analysis has been particularized for the case of Barcelona. A cost–benefit analysis to assess the impact of such a tax has been carried out. When revenue collection is reinvested in the logistics sector, and for subsidizing electric distribution vehicles, the results indicate that the levying of the tax can generate positive outcomes.

scholarly journals The position of the farm holiday in Austrian tourism

2019 ◽  
Vol 4 (1) ◽  
pp. 697-711 ◽  
Author(s):  
Erika Quendler
Keyword(s):  
Empirical Research ◽  
Relative Position ◽  
Secondary Data ◽  
Point Of View ◽  
Local Context ◽  
Supply Side ◽  
Data Sets ◽  
Demand Side ◽  
Tourist Destinations ◽  
Tourist Accommodation

AbstractTourism is vitally important to the Austrian economy. The number of tourist destinations, both farms and other forms of accommodation, in the different regions of Austria is considerably and constantly changing. This paper discusses the position of the ‘farm holiday’ compared to other forms of tourism. Understanding the resilience of farm holidays is especially important but empirical research on this matter remains limited. The term ‘farm holiday’ covers staying overnight on a farm that is actively engaged in agriculture and has a maximum of 10 guest beds. The results reported in this paper are based on an analysis of secondary data from 2000 and 2018 by looking at two types of indicator: (i) accommodation capacity (supply side) and (ii) attractiveness of a destination (demand side). The data sets cover Austria and its NUTS3 regions. The results show the evolution of farm holidays vis-à-vis other forms of tourist accommodation. In the form of a quadrant matrix they also show the relative position of farm holidays regionally. While putting into question the resilience of farm holidays, the data also reveals where farm holidays could act to expand this niche or learn and improve to effect a shift in their respective position relative to the market ‘leaders’. However, there is clearly a need to learn more about farm holidays within the local context. This paper contributes to our knowledge of farm holidays from a regional point of view and tries to elaborate on the need for further research.

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