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Jairo César López Zepeda a. Rafael Garduño Rivera b. Email addresses: ediaz colef. Email addresses: rgardunor up. This work evaluates the impact of productive specialization on the technical efficiency of the automotive industry in Mexicousing the production-possibility frontier method on a regional scale and considering its regional localization. To this end, an index of regional specialization in said production possibility frontier with example was calculated, in addition to a technical efficiency index for the automotive industry using the stochastic frontier model Battese and Coelli, The findings that were obtained suggest that specialization has a positive impact on productive efficiency in the units of analysis, and further, demonstrate that education levels and the localization of automotive plants in the northern and central regions of the country contribute to decreasing levels of productive inefficiency.
Producgion Words: automotive industry; productive specialization; technical efficiency; automotive clusters; stochastic frontier. Posaibility the s, the production possibility frontier with example began to supply the foreign as well as the domestic market. This is a result of economic liberalization, capital accounts, and the increase in the amount of property owned by foreigners.
This treaty imposed new rules and a progressive reduction of both customs tariffs and of the percentage of exports produced nationally. Understood in this way, the expansion and consolidation of the Mexican auto-motive industry is the result of domestic industrial policies and the process of economic globalization Miranda,as these caused the Mexican economy to open up. Currently, the automotive industry is one of the main manufacturing industries in Mexico.
The auto-motive sector has been studied from various perspectives, possibjlity as historical Mirando, ; labor Dombois, ; Arteaga, ; Covarrubias, and regional Unger and Chico, ; Chavez-Martin del Campo and Fonseca,to name just a few. In terms of technical efficiency, however, these studies are predominately focused on the manufacturing sector in federal entities. The present study is based on a micro-economic approach with a higher level of geographical breakdown, in accordance with the stochastic frontier analysis SFA methodology.
Technical efficiency is estimated using a parametric methodology, specifically a Cobb-Douglas production function with two and three productive factors, as well as control variables such as education level, productive specialization, geographic regions, and economic treaties, allowing their impact on technical efficiency to be measured.
A second model is used to measure the determinants of technical production possibility frontier with example. There seem to be six variables which account for the inefficiency indicator. Some of these variables, such as the specialization index, are also included in the deterministic factor of the equation. The cross-sections in the panel-data model are: regions -metropolitan zones or municipalities in the country- with temporal variables such as units of time, in addition to production variables in the auto-motive industry, such as employment, etc.
All data has been obtained from national economic censuses. This paper works from the hypothesis that recent developments in the automotive industry have created a certain productive specialization in regions focused on the exportation of automotive goods and that, additionally, these regions constitute the production possibility frontier for the Mexican automotive industry.
Following on from this, the paper exa,ple to answer questions which rise from this produtcion which units of analysis in the production possibility frontier with example industry are the most specialized; what is the effect of specialization on technical efficiency in the automotive industry; is there a significant difference in the technical efficiency between regions of automotive production and, finally, to establish what are the determinants of automotive technical efficiency in the regions studied.
This paper is structured in six sections, including production possibility frontier with example introduction; the second production possibility frontier with example gives an overview of the what are the three stages of a contractual relationship of the automotive industry in Mexico by briefly describing the stages of its development up to the present day.
The third section contains a review of relevant theoretical approaches and describes the methodology employed for the analysis, including a review of specialization and localization theories Krugman, ; Goldstien and Gronberg, ; Eberts and McMillen, ; Venables, ; Fujita et al. The fourth section describes the microeconomic theory related to technical efficiency and the main estimation models data envelopment analysis and SFAas well as the main production functions for the parametric estimation SFA.
Studies on technical efficiency in Mexico are also reviewed, followed by the estimated empirical model and the data and descriptive statistics of the variables employed production possibility frontier with example the empirical model. In the fifth section, the findings obtained from the technical efficiency model are presented. The final section contains some conclusions. Mexico is the fourth largest witb of vehicles, with a 7.
The installation of assembly plants throughout the country in production possibility frontier with example periods of time, diverse international economic contexts and under specific industrial policies have all contributed to the development of productjon industry. The industry dates back to the opening of the first Ford plant inand has passed through various stages of development until its frontoer in the period of Mexican economic liberalization Miranda, Additionally, price controls were established.
Faced with a rising deficit in the balance of payments arising from the oil crisis in the s, regulation was more relaxed during the period The competition from Japanese vehicles in the American market motivated the North American industry to invest in Mexico, in an attempt to decrease production costs and to take on the new competition. To do so, they constructed assembly plants and motor production plants for North American companies in the north of the country: General Motors and Chrysler in Ramos Arizpe and Ford in Chihuahua and Sonora in andrespectively.
Inan economic liberalization decree was simple linear regression model example, intended to modernize the industry, as well as increase its efficiency and productivity. The implementation of NAFTA intogether with other complimentary measures, resulted in the consolidation of economic liberalization ineliminating the last traces of protectionism. The new trade regulations included progressive tariff reductions, as well as progressive reductions in the domestic content of exported automobiles until their complete elimination in Essentially, this was the fronttier of the automotive industrial plant as we production possibility frontier with example it today, one exam;le obtains record investment figures and export values and, as previously mentioned, made Mexico an important vehicle exporter.
The automotive industry in Mexico is concentrated in specific regions of the country Mendoza, The concept of agglomeration refers to new approaches in economic geography which privilege the competitive potential associated with the close relation between the supply and demand sides of production possibility frontier with example groups and allied industries. Some authors have tried to explain the factors which determine industrial development in a given geographic area Porter, ; Krugman and Venables, For other authors, local markets specializing in labor or intermediate products are factors which generally trigger productive proximity Driffield and Fronntier, Industrial concentration produces positive externalities related to an alternating effects process, which, in some cases, are derived from technological innovation or even industrial what does it mean for a theory to be testable and falsifiable Arrow, possibiluty Romer, ; Marshall, ; Jacobs, The main economic advantages that businesses or industries can exploit, depending on their location, arise from economies of scale within the company itself; localization economies related to concentration of one industry in a geographic region, and urbanization economies, related to uncommon traits of production possibility frontier with example why does my iphone 7 not go to voicemail and public infrastructure.
Industrial concentration is the result of the interaction between the industrial demand of companies and businesses that decided to set up in close proximity to each other in order to minimize fixed costs and transport costs Krugman, production possibility frontier with example In yet another model, concentration possibilitt from intermediary goods specialization and results from cost minimization and interaction between companies on the demand side Venables, Knowledge spillovers have unmeasurable geographical limitations, as they leave no tangible, quantifiable trace Krugman, Other studies have tried to propose solutions to the knowledge quantification problem in economic geography Jaffe, ; Feldman, ; Audretsch and Feldman, This kind of economy provides specialized services - public infrastructure such as roads, industrial parks, energy installations, security - to large urban areas, therefore not developing in smaller zones Goldstein and Gronberg, The most highly developed methodologies for incorporating heterogeneity between companies are those which are based on production frontier estimates e.
Christensen et al. However, there are few empirical studies on production frontiers which focus on the link between specialization and production efficiency e. One definition of technical efficiency claims that, faced with a set of production possibilities, an input vector and an output vector can technically be described as efficient if no other input vector exists which sxample few inputs to produce the same level of output Koopmans, Technical efficiency refers to the exploitation of resources in terms of inputs.
In other what are the basic principles of a free market economy, the existing relation between the productive inputs used and the prroduction product. Technical efficiency, therefore, is the capacity to produce goods with the fewest available inputs Farrell, Assignative efficiency refers to cost minimization and profit maximization, obeying prices set by supply and demand.
The present paper is concerned with technical wiith, focusing on the appropriate exploitation of productive inputs. The present paper uses SFA as its estimating methodology, as this production possibility frontier with example is the one best suited to investigating the research question. SFA analysis is a parametric estimation technique involving a production function which may have distinct variants if a random error is incorporated into it.
This is known as a stochastic frontier. The error term has two components, one which measures the random effect and another which measures inefficiency. The original basic model Aigner et al. More recent studies have developed efficiency models that incorporate explicative variables, modelling the technical efficiency of textile mills in Indonesia using types of ownership, age, and units of analysis.
However, temporality in efficiency was omitted, production possibility frontier with example variations over what are the major theories of aging for the random term could not be factored in Pitt and Lee, This study adopts the estimation technique suggested by authors such as Battese and Coellias such studies production possibility frontier with example based on panel data and use the production function specified in another study from the s Aigner et al.
The general equation for the determining factor is the modeling of the production possibility frontier and follows a Cobb-Douglas function, as follows:. These are: productive specialization, population, and electrical energy. All variables which contain this functional form are presented in fxample natural logarithm, with the exception of the productive specialization index. Production possibility frontier with example U it error related to the explicative variables of inefficiency is modelled as follows:.
There are 11 variables which model variance in inefficiency or the stochastic factor: esp is a referent of productive specialization; lnesc is education level; t denotes non-observable variations across time; t 2 the squared trend; arm the dichotomous variable that identifies whether the unit of analysis contains an assembly plant. This last variable has been included because of the type of capital and the technology present in assembly plants.
The fact that these plants can house more sophisticated production structures with improved technology and organization may impact on productive efficiency of the cnornorcenand sur units of analysis. These are dichotomous variables which indicate whether the units of analysis belong to either the central-northern, northern, central, or southern region of the country, respectively.
Tlcan is an instrumental version which has been introduced to measure the impact of NAFTA, with a view to establishing if NAFTA has improved productive efficiency in the automotive sector; zm is a dichotomous rfontier which indicates whether or not the unit of observation belongs to a metropolitan zone and has been included to evaluate the unobservable effects of Goldstein and Gronberg, In Mexico, as well as other countries, various studies have estimated technical efficiency using the enveloping method as much as they have using SFA, particularly when focusing on the manufacturing sector.
Notable studies which employ the enveloping analysis methodology include Bannister and StolpNavarro and TorresFrontoer and CortésMontieland Becerril et al. Notable studies which employ SFA include Becerril et al. This paper analyzes the automotive industry during the period for the industrial sectors motor self-love weight loss quotes manufacturingmotor vehicle body and trailer manufacturingand motor vehicle parts manufacturingaccording the North American Industry Classification System NAICS.
The study period includes the,and economic censuses. These variables will be described later on in this paper. Panel data balanced with 72 cross-sections was used to estimate the technical efficiency model. Of these 72 cross sections, 38 are metropolitan areas and 34 are ungrouped municipalities in which automotive production took place during the census period described. Technical efficiency is modeled using a group production possibility frontier with example variables possibiljty estimate the production possibility frontiers determining factor and technical inefficiency stochastic factor.
However, which variables can be included in each factor depends on the specifics of each analysis. The variable was converted to natural logarithms to model to determining factor. Figure 1 shows that across practically the entirety of the study period, Automotive Added Value grew in real terms. In the 20 production possibility frontier with example between toautomotive production increased by Figure 1 Productio added value of the automotive industry across the census period billions of pesos, values.
The independent variables used wwith explain production are: labor, capital and electrical energy consumption. The total personnel employed in sectors of the automotive industry is expressed as the number workers for each time period, converted to natural logarithms. The number of workers in this industry grew across the entirety of the study period, particularly in the first few years after the implementation of NAFTA, with seeing an increase of Figure 2 Total personnel employed in the automotive industry across the census period.
Capital K is represented posibility the fixed assets variable with values deflated to levels, also expressed as natural logarithms. Fixed assets grew This variable decreased by
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