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Draft version August 14, 2014 Preprint typeset using L A T E X style emulateapj v. 12/16/11 COSMETIC INDUSTRY IN MEXICO: AN EXPLORATORY ANALYSIS David Gayt´ an *1 , Alejandro Ruiz *2 and Francisco Benita **3 * Instituto de Investigaciones Econmicas y Sociales, Autonomous University of Zacatecas, Preparatoria Avenue, 98068 Zacatecas, Mexico. Email: [email protected] 1 and bruiz alx@h otmail.c om 2 . ** Depart ment of Syste m & Indus trial Engineerin g, Tecnolg ico de Monte rrey , Campu s Mont errey, Ave. E. Garza Sada 2501 Sur, 64849 Monterrey, Nuevo Le´ on, Mexico. Email: franci sco benita@hotma il.com 3 Draft version August 14, 2014 ABSTRACT This study provide s an overview of the broad cosmetic s indus try in Mexic o. We implemen t a data envelopment analysis (DEA) based on Malmquist productivity index, thus we measure the produc- tivit y change over the years 1998, 2003 and 2008. The index can be further decomposed into two components: the change in efficiency and the technical change. Keywords: Cosmetic clusters, Mexico, DEA, Malmquist index 1. INTRODUCTION The cosmetic man ufact uring sector accou nts for 1.2 percent of gross domestic product in Mexico, a 14 bil- lions of dollars mark et. Moreo ver , in 2013 exports and imports excee ded 2.5 millions and 1.2 millions of dollar s, respectively, resulting in an important trade surplus [1]. Empirical evidence has suggested that trade liberaliza- tion promotes productivity growth, technology transfer and an substantially increase on exports of manufactures and services relative to traditional commodity exports. Ho wever, a focal pro ble m toda y in the dynamics of cosmetic industry clusters is related to the efficiency lev- els . By studyng the effici ency of firms one can dete r- mine wether the incentives created by market reforms lead to improvements in the use of resources. This study is one st ep in th is di re ct io n. It inte nd s to ado pt a DEA-Malmquist index (DEA-MI) to study the efficiency of Mexico’s cosmetic industry by federal states through ye ars 1998, 200 3 and 2008. The spa tia l dimens ion of the data can reveals marked disparities in inputs across federal states, then one can dentify more accurately the impact of productive public/private expenditure on cos- metic industrial productivity. 2. METHODS Technical efficiency is a form of productive efficiency which is concerned with output maximization, i.e., max- imi zing out put using giv en inputs. The DEA wa s firs t intriduced in [2] al as a non-parametric performance mea- surement technique. It is an application of linear pro- gramming to measure the relative efficiency of Decision Making Units (DMUs) with same goals and objectives. The technique has been applied to various industrial and non-industrial contexts, such as banking, education, hos- pital, etc. (see e.g. [3] and [5]). On the other hand the concept of the Malmquist pro- ductivity index was originally introduced in [6] as a quan- tity for analyzing the consumption of inputs. Afterwards, in [4] was constructed a Malmquist productivity index directly from input and output data using DEA. Specif- ically, the DEA-MI, relies on firstly constructing an ef- ficiency frontier over the whole sample realized by DEA and then computing the distance of individual observa- tio ns from the frontier. In practice, thi s DEA-MI has proven to be a good tool for measuring the productiv- ity change of DMUs over time, and has been successfully applied in many fields. Based on data from the Economic Census 1999, 2004 and 2009, a dynamic DEA-MI model allow us to appreci- ate intertemporal effects in efficiency measuring through federal states in Mexico. 3. RESULTS 4. DISCUSSION REFERENCES [1] CANIP EC (2013). Informe anual 2013 , C´ amara Nacional de la Industria de Productos Cosm´ eticos, CANIPEC, Mexico. [2] Charnes, A., Cooper, W. and Rhodes, E. (1978). Measuring the efficiency of decision making units, European Journal of Operational Research , 2(6): 429–444. [3] Emrouznejad, A., Park er, B. and Tav ares, G. (2008). Ev aluatio n of resear ch in efficien cy and productivit y: a surv ey and analysis of the first 30 years of scholarly literature in DEA, Socio-Economic Planning Sciences, 42(3): 151–157. [4] F¨ are, R. Grosskopf, S. Lindgren, B. and Roos, P.(1992). Productivity change in Swed ish pharmacies 1980-1989: A nonparametric Malmquist approach, Journal of Productivity Analysis, 3: 85–102. [5] Gattouf, S., Oral, M. and Reisman, A. (2004). pistemology of data envelopment analysis and compar ison with other fields of OR/MS for relevance to applications, Socio-Economic Planning Sciences, 38(2-3): 123–140. [6] Malmqu ist, S. (1953). Index numbers and indifference surface s, Trabajos de Esta d ´ ısti ca , 4(2): 209–242.
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Transcript of Colombia s
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Draft version August 14, 2014Preprint typeset using LATEX style emulateapj v. 12/16/11
COSMETIC INDUSTRY IN MEXICO: AN EXPLORATORY ANALYSIS
David Gaytan*1, Alejandro Ruiz*2 and Francisco Benita **3
* Instituto de Investigaciones Econmicas y Sociales, Autonomous University of Zacatecas, Preparatoria Avenue, 98068 Zacatecas,Mexico. Email: [email protected] and bruiz [email protected].
** Department of System & Industrial Engineering, Tecnolgico de Monterrey, Campus Monterrey, Ave. E. Garza Sada 2501 Sur, 64849Monterrey, Nuevo Leon, Mexico. Email: francisco [email protected]
Draft version August 14, 2014
ABSTRACT
This study provides an overview of the broad cosmetics industry in Mexico. We implement a dataenvelopment analysis (DEA) based on Malmquist productivity index, thus we measure the produc-tivity change over the years 1998, 2003 and 2008. The index can be further decomposed into twocomponents: the change in efficiency and the technical change.Keywords: Cosmetic clusters, Mexico, DEA, Malmquist index
1. INTRODUCTION
The cosmetic manufacturing sector accounts for 1.2percent of gross domestic product in Mexico, a 14 bil-lions of dollars market. Moreover, in 2013 exports andimports exceeded 2.5 millions and 1.2 millions of dollars,respectively, resulting in an important trade surplus [1].Empirical evidence has suggested that trade liberaliza-tion promotes productivity growth, technology transferand an substantially increase on exports of manufacturesand services relative to traditional commodity exports.
However, a focal problem today in the dynamics ofcosmetic industry clusters is related to the efficiency lev-els. By studyng the efficiency of firms one can deter-mine wether the incentives created by market reformslead to improvements in the use of resources. This studyis one step in this direction. It intends to adopt aDEA-Malmquist index (DEA-MI) to study the efficiencyof Mexicos cosmetic industry by federal states throughyears 1998, 2003 and 2008. The spatial dimension ofthe data can reveals marked disparities in inputs acrossfederal states, then one can dentify more accurately theimpact of productive public/private expenditure on cos-metic industrial productivity.
2. METHODS
Technical efficiency is a form of productive efficiencywhich is concerned with output maximization, i.e., max-imizing output using given inputs. The DEA was firstintriduced in [2] al as a non-parametric performance mea-surement technique. It is an application of linear pro-gramming to measure the relative efficiency of DecisionMaking Units (DMUs) with same goals and objectives.The technique has been applied to various industrial andnon-industrial contexts, such as banking, education, hos-pital, etc. (see e.g. [3] and [5]).
On the other hand the concept of the Malmquist pro-
ductivity index was originally introduced in [6] as a quan-tity for analyzing the consumption of inputs. Afterwards,in [4] was constructed a Malmquist productivity indexdirectly from input and output data using DEA. Specif-ically, the DEA-MI, relies on firstly constructing an ef-ficiency frontier over the whole sample realized by DEAand then computing the distance of individual observa-tions from the frontier. In practice, this DEA-MI hasproven to be a good tool for measuring the productiv-ity change of DMUs over time, and has been successfullyapplied in many fields.
Based on data from the Economic Census 1999, 2004and 2009, a dynamic DEA-MI model allow us to appreci-ate intertemporal effects in efficiency measuring throughfederal states in Mexico.
3. RESULTS
4. DISCUSSION
REFERENCES[1] CANIPEC (2013). Informe anual 2013, Camara Nacional de
la Industria de Productos Cosmeticos, CANIPEC, Mexico.[2] Charnes, A., Cooper, W. and Rhodes, E. (1978). Measuring
the efficiency of decision making units, European Journal ofOperational Research, 2(6): 429444.
[3] Emrouznejad, A., Parker, B. and Tavares, G. (2008).Evaluation of research in efficiency and productivity: a surveyand analysis of the first 30 years of scholarly literature in DEA,Socio-Economic Planning Sciences, 42(3): 151157.
[4] Fare, R. Grosskopf, S. Lindgren, B. and Roos, P.(1992).Productivity change in Swedish pharmacies 1980-1989: Anonparametric Malmquist approach, Journal of ProductivityAnalysis, 3: 85102.
[5] Gattouf, S., Oral, M. and Reisman, A. (2004). pistemology ofdata envelopment analysis and comparison with other fields ofOR/MS for relevance to applications, Socio-EconomicPlanning Sciences, 38(2-3): 123140.
[6] Malmquist, S. (1953). Index numbers and indifference surfaces,Trabajos de Estadstica, 4(2): 209242.
