Productivity and Efficiency Analysis PDF
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Springer Proceedings in Business and Economics William H. Greene Lynda Khalaf Robin C. Sickles Michael Veall Marcel-Cristian Voia E ditors Productivity and Effi ciency Analysis Springer Proceedings in Business and Economics Moreinformationaboutthisseriesathttp://www.springer.com/series/11960 William H. Greene • Lynda Khalaf Robin C. Sickles (cid:129) Michael Veall Marcel-Cristian Voia Editors Productivity and Efficiency Analysis 123 Editors WilliamH.Greene LyndaKhalaf SternSchoolofBusiness DepartmentofEconomics NewYorkUniversity CarletonUniversity NewYork,NY,USA Ottawa,ON,Canada Robin C. Sickles MichaelVeall DepartmentofEconomics DepartmentofEconomics RiceUniversity McMasterUniversity Houston,TX,USA Hamilton,ON,Canada Marcel-CristianVoia DepartmentofEconomics CarletonUniversity Ottawa,ON,Canada ISSN2198-7246 ISSN2198-7254 (electronic) SpringerProceedingsinBusinessandEconomics ISBN978-3-319-23227-0 ISBN978-3-319-23228-7 (eBook) DOI10.1007/978-3-319-23228-7 LibraryofCongressControlNumber:2015956100 SpringerChamHeidelbergNewYorkDordrechtLondon ©SpringerInternationalPublishingSwitzerland2016 Thisworkissubjecttocopyright.AllrightsarereservedbythePublisher,whetherthewholeorpartof thematerialisconcerned,specificallytherightsoftranslation,reprinting,reuseofillustrations,recitation, broadcasting,reproductiononmicrofilmsorinanyotherphysicalway,andtransmissionorinformation storageandretrieval,electronicadaptation,computersoftware,orbysimilarordissimilarmethodology nowknownorhereafterdeveloped. Theuseofgeneraldescriptivenames,registerednames,trademarks,servicemarks,etc.inthispublication doesnotimply,evenintheabsenceofaspecificstatement,thatsuchnamesareexemptfromtherelevant protectivelawsandregulationsandthereforefreeforgeneraluse. Thepublisher,theauthorsandtheeditorsaresafetoassumethattheadviceandinformationinthisbook arebelievedtobetrueandaccurateatthedateofpublication.Neitherthepublishernortheauthorsor theeditorsgiveawarranty,expressorimplied,withrespecttothematerialcontainedhereinorforany errorsoromissionsthatmayhavebeenmade. Printedonacid-freepaper SpringerInternationalPublishingAGSwitzerlandispartofSpringerScience+BusinessMedia(www. springer.com) Introduction The volume comprises 17 chapters that deal with productivity measurement, productivity growth, dynamics of productivity change, measurement of labor productivity, measurement of technical efficiency at the sectoral level, frontier analysis, measurement of performance, industry instability, and spillover effects. The contributors to the volume are W. Erwin Diewert, Bert M. Balk, Subal C. Kumbhakar, Frank Asche, Kristin Roll, Ragnar Tveteras, Loren W. Tauer, Jaepil Han, Deockhyun Ryu, Robin C. Sickles, Lynda Khalaf, Charles J. Saunders, German Cubas, Anson T.Y. Ho, Kim P. Huynh, David T. Jacho-Chàvez, A.S.J. Smith,J.Buckell,P.Wheat,R.Longo,BrianMurphy,MichaelR.Veall,YanZhang, Yuri Ostrovsky, Robert J. Petrunia, Marcel C. Voia, Leonard Sabetti, Pat Adams, WeiminWang,AlejandroNin-Pratt,RoarAmundsveen,HildeMaritKvile,Sourour Baccar,MihailoRadoman,JiaqiHao,andChenjunShang. Thefirstchapterexaminesproductivitydecompositionsatthesectorallevel.The economy-widelaborproductivitygrowthrateisthoughttodependonsectorallabor productivity growth rates, real output price changes, and changes in sectoral labor input shares. A puzzle is that empirically, the real output price change effects, when aggregated across industries, have little explanatory power. The economy- wide TFP growth decomposition into sectoral explanatory factors depend on the sectoral TFP productivity growth rates, real output and input price changes, and changes in sectoral aggregate input shares. The puzzle with this decomposition is that empirically all of these price change effects and input share effects matter little when they were aggregated over sectors; only the sectoral TFP growth rates contributedsignificantlytooverallTFPgrowth. The second chapter considers the relation between (total factor) productivity measuresforlowerlevelproductionunitsandaggregatesthereof,suchasindustries, sectors, or entire economies. In particular, a review of the so-called bottom-up approach, which is an ensemble of individual production units, is considered. At theindustrylevel,thevariousformsofshift-shareanalysesarereviewed. Thethirdchapterconsidersarevenuemaximizingmodelandderivestherevenue function from the transformation function where errors are parts of the outputs. The chapter adapts McElroy’s additive general error model to the transformation v vi Introduction functionwithmultipleinputsandmultipleoutputsandderivestherevenuefunction. Theerrortermsintheoutputsupplyfunctions,derivedfromtherevenuefunction, inherittheirrandomnessfromtheerrortermsintheoutputs.Asasecondapproach, the chapter uses a multiplicative general error model (MGEM), in the spirit of Kumbhakar and Tsionas (2011), with multiple outputs in which multiplicative errorsarepartsoftheoutputs.TheMGEMisfurthergeneralizedtoaccommodate output-orientedinefficiency.ThetranslogrevenuefunctionwithMGEMmakesthe intercept and the coefficients of the linear terms random (functions of the errors associated with outputs). Vessel level data for the Norwegian whitefish fisheries for the period 1995–2007 are used to showcase the application of the model. A standard(off-the-shelf)revenuefunctionwithoutput-orientedtechnicalinefficiency is estimated and technical change and technical efficiency results are compared with the MGEM revenue function, which is estimated along with the revenue share equations. Although the means are found to be somewhat similar, patterns of technical change and technical efficiency are found to be quite different across thesemodels. Chapter 4 uses quantile regression to estimate production functions at various quantiles within a dairy farm production set, and marginal products and input substitutions are derived for each of the quantile production functions. Economic relationships vary in the interior of the production set compared to the frontier of the production set, with no discernible pattern through the production set. An implication is that the production response to inputs changes for inefficient firms in the interior of the production set may differ compared to efficient firms on the frontieroftheproductionset.Theresultsareforaspecificdairyproductiondataset, sofurtheranalysisiswarrantedtodeterminewhatpatternsexistwithotherempirical productionsets. Chapter 5 aims to investigate spillover effects of public capital stock in a production function model that accounts for spatial dependencies. Although there are a number of studies that estimate the output elasticity of public capital stock, they suffer from a failure to refine the output elasticity of public capital stock as wellastoaccountforspillovereffectsofthepubliccapitalstockontheproduction efficiencywhensuchspatialdependenciesexist.Aspatialautoregressivestochastic frontier model is employed and the authors analyze estimates with a time-varying spatialweights matrix.Usingdata for21 OECDcountries from1960 to2001, the chapterfindsthatspillovereffectscanbeanimportantfactorexplainingvariations intechnicalinefficiencyacrosscountriesaswellasinexplainingthediscrepancies among various levels of output elasticity of public capital stock in traditional productionfunctionapproaches. Chapter 6 considers a dynamic technical efficiency framework with non- Gaussian errors which suffer from the incidental parameter bias. Simulations show that an indirect inference estimation approach provides bias correction for the model and distribution parameters. The indirect confidence set inference method is size correct and exhibits good coverage properties even for asymmetric confidence regions. Bank cost data are examined under the proposed dynamic Introduction vii technicalefficiencyframeworkwithevidencethatanMLEapproachcouldprovide misleadingimplications. Chapter 7 studies labor productivity growth in Ecuador from 1998 to 2006 by using firm-level data from the annual survey of manufacturing and mining. This period is characterized by the economic crisis in 1999 and important economic reforms. During the crisis, there was a 2 % annual decrease in productivity in 1998–2000, but the recovery was strong with a 5 % annual productivity growth in 2002–2004. The productivity decompositions indicate that the main source of productivity growth came from firms with increasing productivity gaining market shares. Within-firm productivity decline was substantial during the crisis, but its growthwassecondaryinthepost-crisisrecovery.Firmentryandexitonlyhadminor impactsonlaborproductivity.Thedistributionalanalysisfurthershowedthatlabor productivitydistributionincreasedin2000–2002 andhadremainedathigherlevel fortherestofthesampleperiod. Chapter8looksatthesourceofinefficiencywithinhealthsystemorganizational structuresasakeyaspectofperformancemeasurementandmanagement,whichis of increasing importance to policy makers. The study uses a unique panel dataset to study the efficiency performance of pathology services in the National Health Service(NHS)inEnglandforthefirsttime.Adual-levelstochasticfrontier(DLSF) model(SmithandWheat,2012)toisolatethesourceofinefficiencyattwovertically distinctorganizationallevelsisused:anupperlevelofStrategicHealthAuthorities (SHAs)andalowerleveloflaboratoriesgroupedwithinSHAs.ADLSFframework is developed in line with recent developments in the wider panel data literature to control for the influence unobserved heterogeneity, which is a key issue for healthcare performance analysis. Statistically significant variation in inefficiency performance at both organizational levels in pathology services is found. These measuresareusedtocomputeoverallinefficiencyforNHSpathologyservices,and correspondingsavingsestimates. Chapter 9 looks at how productivity and growth may be affected by what are called “shortages” of specific types of workers. Canadian data are examined for evidence of a shortage of Information and Communication Technology (ICT) workers.Publishedvacancy andunemployment dataaretoocoarseattheindustry level. Accordingly, two types of administrative data are used to look for evidence ofrisingICTemploymentandlaborincome,whichmightindicateashortage.One dataset is available with little lag in cross section (from payroll records) and the other longitudinal dataset (based on tax filer data) is available with a 2-year lag. The results suggest that both data sources may be useful in this instance, with the longitudinaldatausedtocheckforcompositionalchangesinthemorecurrentand timelycross-sectionaldata.Similarapproachesmaybeavailableforothercountries. These data sources provide at most mild evidence of a shortage of Canadian ICT workersinrecenttimes. Chapter 10 looks at the impact industry instability has on worker separations. Workersleavefirmsinoneoftwoways:(1)voluntarilybyquittingor(2)involun- tarily through firm layoffs. Using data drawn from the Longitudinal Worker File, a Canadian firm-worker matched employment database, the chapter distinguishes viii Introduction between voluntary and involuntary separations using information on reasons for separations and assesses the impact industry shutdown rates have on worker separation rates, both voluntarily and involuntarily. Once controlling for various factors and potential selection bias, it is found that industry shutdown rates have a positive and significant effect on the overall separation, layoff and quit rates of workers.Itisalsofoundthatindustryinstabilityhasamuchlargerimpactonlayoff rateswhencomparingvoluntaryandinvoluntaryseparations. Chapter 11 employs a growth-accounting approach to revisit past performance ofagricultureinsub-SaharanAfrica(SSA)andtoanalyzetherelationshipbetween theinputmixusedbySSAcountriesandproductivitylevelsobservedintheregion. Findingsshowthatimprovedtechnicalefficiencyhasbeenthemaindriverofgrowth inrecentyears,benefitingpoorer,lowlaborproductivitycountries.Countrieswith higher output and input per worker have benefited much more from technological progress than poorer countries, suggesting that technical change has done little to reduce the gap in labor productivity between countries. Results also show that the levels of input per worker used in SSA agriculture at present are extremely low and associated with less productive technologies, and that technical change has shifted the world technological frontier unevenly, increasing the distance between SSAcountriesandthosecountrieswiththe“right”inputmix. Chapter 12 investigates the role of university knowledge spillovers in fostering innovative start-up firms, measured by R&D intensity, an important predictor of firm innovation and productivity. Annual data from the Kauffman Firm Survey of a representative cohort of US start-ups over the period 2004–2011 are used. By controllingforindividual-firmcharacteristicsandlocalfactors,thechapterteststhe effectsofregionalvariationinR&Dintensityofthehighereducationsectoronstart- upfirms’R&Dexpendituredecisions.Strongeffectsonbothextensiveandintensive marginsoffirmR&Dexpendituresarefound.Theresultsshedlightontheroleof entrepreneursandnewfirmformationasamechanismforinnovationinuniversities asanimportantsourceofknowledgeandtechnologytransfer. Chapter 13 presents a growth-accounting framework in which subsoil mineral and energy resources are recognized as natural capital input into the production processintwoways.Firstly,theincomeattributabletosubsoilresources,orresource rent, is estimated as a surplus value after all extraction costs and normal returns on produced capital have been accounted for. The value of a resource reserve is thenestimatedasthepresentvalueofthefutureresourcerentsgeneratedfromthe efficientextractionofthereserve.Secondly,withextractionastheobservedservice flows of natural capital, multifactor productivity growth and sources of economic growth can be reassessed by updating income shares of all inputs and then by estimatingthecontributiontogrowthcomingfromchangesinthevalueofnatural capitalinput.TheempiricalresultsontheCanadianoilandgasextractionshowthat addingnaturalcapitalincreasestheannualmultifactorproductivitygrowthintheoil and gas sector from (cid:2)2.3 to (cid:2)1.5 % over the 1981–2009 period. During the same period, the annual real value-added growth in this industry was 2.3 %, of which about0.4percentagepointsor16%comesfromnaturalcapital. Introduction ix Chapter 14 is a presentation and discussion of issues that arise in the practi- cal application of a regulatory benchmarking model. It describes the regulatory benchmarkingmodelforelectricitydistributioncompaniesinNorway,andfocuses on how different choices influence different incentives for the companies. These choicescovermethodology,modelingassumptions,andvariables,butalsohowthe benchmarkingresultsareappliedintheregulatorymodel.Thebenchmarkingmodel is only one part of the regulatory model for setting revenue caps. The discussion shows some of the trade-offs that have to be considered in this process, and sheds somelightonwhyregulatorsmaydeviatefromoptimaltextbooksolutions. Chapter15evaluatesthecapacityofthetranslogcostsharemodeltoapproximate theproducer’struedemandsystemandintroducestwononlinearfunctionalforms, which have been achieved by altering and extending the standard quadratic log- arithmic translog model. The extensions have additional desirable approximation properties with respect to output and time variables, and thus allow more flexible treatments of non-homothetic technologies and non-neutral technical change than those provided by the standard translog. The performances of the three models are assessed (1) on theoretical ground, by the size of the domain of regularity, (2) on their ability to provide plausible estimates of the economic and technological indicators being measured, and finally (3) on their reliability in fitting input shares, input–output ratios, and unit cost. The most important finding is that the standardmodelexhibitssomeweaknessinfitting.Theauthorsshowviaaseriesof experimentsthatthoseshortcomingsareduetoalackofflexibilityofthelogarithmic model.Theestimationresultsobtainedwiththenewextendedmodelarepromising. Chapter 16 examines the impact of policy changes on player productivity at the top level of European football, with a particular focus on the English Premier League.Contesttheorymotivatesthepredictionthatpost-Bosmanentrantswillbe more productive and consequently have a higher probability of earning/retaining a first-team spot in top European leagues. To test these predictions, data were collectedonallplayersthatenteredtheEnglishPremierLeaguein4-yearwindows around the Bosman ruling. Nonparametric techniques, specifically Regression Discontinuity Design, were applied to test for sharp jumps in player productivity measures around the Bosman ruling. The results display discontinuity in player productivity measures, suggesting that post-Bosman entrants tend to be more productivethanpre-Bosmanentrants. Chapter17providesnewmethodstorobustifyproductivitygrowthmeasurement byutilizingvariouseconomictheoriesexplainingeconomicgrowthandproductivity andtheeconometricmodelgeneratedbythatparticulartheory.TheWorldProduc- tivityDatabasefromtheUNIDOisutilizedtoanalyzeproductivityduringtheperiod 1960–2010forOECDcountries.Thefocusisonthreecompetingmodelsfromthe stochastic frontier literature, Cornwell, Schmidt, and Sickles (1990), Kumbhakar (1990), and Battese and Coelli (1992) to estimate productivity growth and its decompositionintotechnicalchangeandefficiencychangeandutilizemethodsdue toHansen(2010)toconstructoptimalweightsinordertomodelaveragetheresults fromthesethreeapproaches.
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