Performance analysis for three pillars of sustainability

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1 Document de traval du LEM / Dscusson paper LEM Performance analyss for three pllars of sustanablty Jean-Phlppe BOUSSEMART LEM UMR 9221 Hervé LELEU LEM UMR 9221 Zhyang SHEN LEM UMR 9221 / z.shen@eseg.fr Vvan VALDMANS Western Mchgan Unversty /ÉSEG School of Management

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3 Performance analyss for three pllars of sustanablty Jean-Phlppe BOUSSEMART a, Hervé LELEU b, Zhyang SHEN c*, and Vvan VALDMANS d, a Unversty of Llle, CNRS, ÉSEG School of Management, UMR LEM, F Llle, France emal: jp.boussemart@eseg.fr b CNRS, ÉSEG School of Management, Unversty of Llle, UMR LEM, F Llle, France emal: h.leleu@eseg.fr c ÉSEG School of Management, CNRS, UMR LEM, F Llle, France emal: z.shen@eseg.fr d Western Mchgan Unversty, and ÉSEG School of Management, Grand Rapds, M, USA emal: vvan.valdmans@wmch.edu Verson: Aprl 5, 2017 Abstract: Gross domestc product (GDP) has come under crtcsm as the only objectve countres should pursue for socetal well-beng. n ths paper we apply an nnovatve Data Envelopment Analyss (DEA) approach for ncludng two other pllars ncludng an envronmental dmenson, reducton of carbon doxde (CO2) emssons and a socal dmenson such as: ncreasng employment, and expandng healthcare and educaton expendtures. By lnkng together three DEA sub-technologes, we model a global technology whch combnes the objectves of the three pllars. Fnally, by weghtng each of them by dfferent schemes, we demonstrate the practcalty of our approach for polcy tradeoffs governments can make among economc, envronmental and socal objectves. Keywords: Three Pllars, Economc Effcency, Envronmental Effcency, Socal Effcency, Data Envelopment Analyss, Multple Fronters. Correspondng author: Zhyang SHEN, ÉSEG School of Management, 3 rue de la Dgue, Llle France. Tel: +33(3) Emal: z.shen@eseg.fr

4 1. ntroducton Hstorcally, the best method for accountng a naton s economc growth and well-beng has been the use of ether gross natonal product (GNP), GDP, or net natonal product (NNP). Snce the outgrowth of envronmentalsm, there has been nterest n measurng economc bads,.e., polluton snce ncludng these types of bads n calculatng a more accurate pcture of economc actvty. Leontef (1970) advocated that the ncluson of polluton and any other negatve or postve effects should be ncluded n the assessment of economc systems. Hamlton (1996) also argued for the necessty of ncludng polluton as an adjustment for NNP. More generally, other arguments n the utlty functon such as envronmental preservaton and socal benefts should be encompassed beyond smply consumpton. Often consdered the new economc measure beyond GDP to measure a populatons well-beng, other factors have been dentfed ncludng ncome, employment, good health care servces, good educaton, and a clean envronment (OECD, 2014). Whereas the prevous studes employed tradtonal approaches for measurng economc actvty, recent developments n the non-parametrc, DEA focuses on ncludng economc bads n the dervaton of the producton fronter (Seford and Zhu, 2002; Färe and Grosskopf, 2004; Sahoo et al., 2011; Sueyosh and Goto, 2011). Neglectng the commensurate producton of economc bads wll result n an upward bas of measurng performance. n the past, economc bads have been added on the nput sde. Whereas ths approach may be an artfact for computatonal ssues, polluton s clearly not an nput to the producton of a good. Therefore, polluton must be consdered as an output and treated jontly wth the producton of goods. A large part of the related lterature s devoted to consder polluton as a weakly dsposable output jontly produced wth the goods. However, ths approach treats the problem of both productons n a unque producton functon whch cannot model the complex relatonshps among goods, bads, and energy. For example, energy whch s a good nput n the producton of goods but also a bad nput as a man source of polluton. 1

5 More recently, a new modelng based on a by-producton technology (Murty et al., 2012, Ray et al., 2017), consderng two sub-technologes, one for the producton of goods, another for the producton of bads, allows to defne relevant trade-offs among goods, bads and energy use. n ths paper, we extend the dea of multple sub-technologes to the three pllars. Ths approach can provde nformaton that may be of nterest to polcy makers lnkng the overall producton of energy whle measurng the benefts of envronmental mprovement and the addton of jobs and mproved health that have been mssng n earler studes. Typcally referred to as the three pllars of sustanablty economc, envronmental, and socal, there has some ssues rased how to treat these three jontly. We use the three pllars approach usng nputs nto frst dervng GDP growth wth labor, captal, and energy as nputs. Next, we measure potental reductons n CO2 as an output wth energy as an nput and as our proxy varable for potental envronmental beneft that wll be explaned below. Fnally, we examne how the socal good pllar (employment, healthcare expendtures and educaton expendtures) are produced as outputs usng labor stock as an nput for employment and GDP as an nput for healthcare and educaton expendtures. Whereas we use ths approach at the macro level, our methodology can also be done at the mcro level. n ths paper, our objectve s to assess the jontness of these three pllars but rather than assgnng weghts a pror, we perform smulatons wheren dfferent weghtng schemes can be employed based on polcy agendas. For example, f mtgatng clmate change s a poltcal prorty, the envronmental pllar should receve a hgher weght as compared to maxmzng GDP n already hgh ncome countres. n some of our results, an mprovement of performance n the envronmental pllar wll lead to a decrease of GDP. The above example s typcal of the degrowth model nspred by the work of Georgescu-Roegen (1977, 1979). More specfcally, the concept of degrowth s that overconsumpton les at the root of envronmental degradaton and socal nequaltes. The degrowth concept fts wth the noton of the three pllars of 2

6 sustanablty whch nclude economc growth, envronmental protecton, and socal well-beng. All these trade-offs are analyzed n the proposed framework. The rest of the paper unfolds as follow. n the next secton we provde a recent lterature revew of the good modelng of bad outputs and the necessty to nclude socal ndcators n a global performance analyss. We next present our methodologcal approach followed by a descrpton of the data we use n ths study. Results from our analyss s presented and the paper concludes wth a dscusson and possble future research for sustanablty. 2. Background As stated n the ntroducton of ths paper, there s a long hstory of justfyng the ncluson of economc bads such as polluton n the economc producton process. Leontef (1970) argued that even though conventonal compettve markets nclude postve value, the ncluson of carbon-monoxde was excluded from the producton process. He argues that ths s ncorrect snce the producton of carbon-monoxde exudes negatve externaltes and thereby should be ncluded n the overall system of economc measurement. He further states that once the techncal nput-output combnaton n the producton of goods have been determned, the ncluson of polluton can be analyzed as part of the economc process. Recent studes on the effect of energy producton and how ths producton has mpacted the envronment have been conducted followng the prescent advce from Leontef (1970). Zhou, Ang, and Poh (2008) revewed 100 papers on envronmental and energy producton studes and found that 25 ncluded some type of assessment of the costs (ether envronmental or producton). t was argued by the authors of the studes n ths lterature revew that rather than usng a strctly output-based DEA approach, a drectonal dstance functon or a hyperbolc effcency approach s better suted for measurng the producton of goods and bads both 3

7 methodologcally and theoretcally. As part of Zhou et al. s (2008) revew, specfc studes are ponted out here for the applcablty to our study. Färe, Grosskopf, Noh, and Weber (2005) appled a quadratc drectonal output dstance functon to estmate the shadow prces of the pollutants by measurng the opportunty cost of reduced electrcty (the good) by a one unt decrease n sulfur doxde (the bad). Zhou et al. (2006) ncorporated the slack values (.e., the flat porton of the producton fronter) to estmate the economc mpact mposed by envronmental regulatons for 30 OECD countres between the years of These authors found, whereas there was no opportunty cost mposed by envronmental regulatons, none of the countres were consdered effcent n both techncal effcency and envronmental mprovement. Färe et al. (2007) estmated the jont producton of goods (electrcty) and bads (polluton) for 92 coal-powered plants operatng n the US. They decomposed the relatve mportance of factors assocated wth the foregone producton of electrcty assocated wth abatement. They found some loss but t was lmted. Zhang et al. (2008) estmated the ecoeffcency usng DEA among Chnese provnces. There was some consstency n the provnces whch met both effcency and envronmental mprovement, but as these authors noted, Chnese offcals n ths centralzed government were rewarded only on economc performance and not on envronmental protecton nor the socal aspects assocated wth polluton (whch the authors noted were not ncluded n ther study). Bellenger and Herlhy (2009) employed the use of an output dstance functon as an alternatve approach to envronmental constructon. They found lttle relaton between envronmental and economc ndces and argue that t would be better to aggregate these two measures usng exstng data rather than mposng an a pror weghtng system, wth the former better at exhbtng actual performance and ncentves of the countres sustanablty polces. Bosett and Buchner (2009) amed to address ths weghtng ssue by usng stmulated data on eleven global clmate polcy scenaros. They performed a senstvty analyss and concluded 4

8 that strngent clmate polces outperformed polces that were less strngent f all sustanablty factors are used n the DEA specfcaton. However, these authors only consdered envronmental standards n ther defnton of sustanablty. Kuosmanen and Kuosmanen (2009) echoed the sentment of a senstvty analyss by assessng sustanable value usng the rato of observed sustanablty to the benchmark ala the producton approach by Shephard (1953) and Farrell (1957) whch s famlar to the DEA lterature. The purpose of ther paper was to refute the use of lnear regresson models n ascertanng the economc-envronmental protecton process. These authors appled the technques of producton effcency to measure sustanablty along the sustanablty value (SV) approach. However, they were not able to nclude typcal varables of labor and captal, nor were they able to nclude socal well-beng. Antal (2014) argued that wthout systematc changes, green goals and full employment are ncompatble. Wthout economc growth, unemployment wll ncrease sgnfcantly wth negatve mpacts on well-beng. By comparng two correlatons, Antal (2014) lnked economc growth wth envronmental protecton and lack of economc growth wth unemployment. What Antal (2014) faled to do was lnk these concepts together, suggestng that for envronmental mpacts to be postve, they must be accompaned wth a reducton on the dependence on economc growth to acheve lower unemployment. n lght of these studes, Murty, et al. (2012) added another approach n the assessment of economc bads n producton referred to as the by-producton technology. n the approach presented here, the by-producton technology s represented as two dstnct technologes one used n the tradtonal sense of producng outputs from nputs and a second technology for the producton of the bad or by-product. Takng the ntersecton of the two technologes, output and envronmental effcency can be decomposed. The beneft of ths approach s that these authors surmse that the drectonal dstance functon and the hyperbolc functon wll stll understate the degree of neffcency. By takng the ntersecton of the two technologes credt wll be 5

9 gven to frms (or countres) who abate polluton by credtng them wth ncreased envronmental effcency. n ths paper, we add a subset of the socal welfare producton process by ncludng ncreased employment health care expendtures and educaton expendtures. To summarze, we propose analyzng three producton functons to address the ssues presented above: energy producton from an economc perspectve; the effect that energy producton has on the envronment va decreasng the producton of CO2; and fnally the postve socal mpacts of employment and potental postve socal good mprovements. n other words, we explctly measure the three pllars of sustanablty n the sprt of Georgescu-Roegen s defnton of degrowth as t apples to the ncreased producton of CO2 as a proxy for the use of nonrenewable resources. n the next secton, we descrbe the methodology employed to estmate these effects and how to analyze ther jont producton. 3. Methodology We frst defne a producton technology for each of the components of the three pllars. Then we lnk these three sub-technologes to defne the overall three pllars technology. These lnks hghlght the potental tradeoffs among the dfferent objectves over the three dmensons. We use a standard mcroeconomc approach based on the defnton of producton sets from an axomatc approach and on the use of a dstance functon to characterze theses sets (Shephard 1953) Defnton of the economc, envronmental and socal sub-technologes We model the producton technology for decson makng unts (DMUs) usng N nputs (x) to produce M outputs (y). A general producton possblty set can be defned as follows: 6

10 T ( ) N M x,y R : x can produce y (1) For each sub-technology, DMUs could have specfc nputs and outputs whch nteract wth each other. n our model, the evaluaton of economc performance s at an aggregated level for each country and uses captal stock (K), employment (L), and energy consumpton (E) as nputs to produce gross domestc producton (GDP). Ths defnes the economc technology T1. The energy nput generates carbon emssons (CO2) whch are regarded as a bad output n the envronmental evaluaton (T2). For evaluatng socal performance (T3), labor stock (LS) s consdered as the nput n defnng employment as the output. Furthermore, GDP s the man resource from whch healthcare expendture (HE) and educaton expendture (EE) are made. Therefore, three sub-technologes for each of the component of the three pllars can be defned as follows: 1 T K, L and E can produce GDP T E can produce CO T LS can produce L; GDP can produce HE and EE (2) For estmaton purposes, we employ a non-parametrc framework to gve an operatonal defnton of the producton sets and evaluate the dstance to the fronters of these sets. By assumng some basc assumptons such as free dsposablty and convexty and based on an observed sample of countres, the economc technology can be defned as: T1 ( K, L, E, GDP) R, GDP GDP, L L, K K, E E , 0 1,..., (3) where λ s a vector of actvty varables related to the economc sub-technology (Koopmans, 1951; Baumol, 1958). n T1, we also assume varable returns to scale (VRS) to take nto account 7

11 sze heterogenety among countres. A constant returns to scale (CRS) assumpton would lead to comparng small countres lke New-Zealand to large countres lke Unted States by scalng up or down. The VRS assumpton allows for decreasng returns to scale whch s presumably present n economcs actvtes. Smlarly, we can defne the envronmental technology followng Murty et al. (2012) as: T2 ( E, CO2 ) R, CO2 CO2, E E, 0 1,..., 1 1 (4) where σ s the vector of actvty varables related to the envronmental sub-technology. Here, we assume that CO2 s produced proportonately to the energy consumed thus constant returns to scale are ntroduced. The socal technology combnes n tself two sub-technologes and s defned as follows: ( LS, L, GDP, HE, EE) R, T3 L L, LS LS, 0 1,..., ; 1 1 HE HE, EE EE, GDP GDP, 0 1,..., (5) The frst sub-technology consders employment as part of the socal pllar. From a gven labor stock (LS), T3 defne the maxmal level of feasble employment (L) n an economy. n our vew, labor stock s exogenous n our analyss and cannot be reduced or ncreased. Therefore, we use equalty on ths constrant. The second sub-technology deals wth healthcare and educaton expendtures. From a gven level of generated GDP, T3 defnes the maxmal level that healthcare and educaton expendtures can be ncreased. These two sub-technologes are ndependent and characterzed by ther own vector of actvty varables, respectvely μ and ζ. Unlke the VRS assumpton on GDP, the CRS assumpton s used for the socal technology. We consder that 8

12 employment s proportonate to the labor stock and that healthcare and educaton expendtures are proportonate to GDP. 3.2 Defnton of the three pllars technology We now ntroduce the three pllars technology by combnng the three sub-technologes on economc, envronmental and socal dmensons. Whle each ndependent sub-technology assumes exogenous nputs, we explctly lnk them together. n our combned technology, only labor stock and captal stock are consdered exogenous. Energy, CO2, employment, as well as GDP, healthcare and educaton expendtures are consdered as endogenous. Because lnks among the sub-technologes are explctly made, tradeoffs among the three pllars wll be possble. Between the economc (T1) and envronmental (T2) technologes, energy s a common factor. Energy s an nput n the producton of GDP but also produces CO2, thus the level of energy used n T1 should be equvalent to the consumpton n T2. The tradeoff s clear: whle a hgher level of energy use s needed to maxmze GDP, a lower level s desred n order to mnmze CO2 emssons. n our three pllars technology, both objectves are consdered and we ntroduce the explct constrant 1 1 E E that ensures the same energy consumpton n both sub-technologes. Ths new constrant brdges the gap between economc and envronmental performances. n a smlar ven, we lnk the economc fronter to the socal technology by labor (L) and GDP. For socal and economc ponts of vew, employment can be both outcome and nput cost, a hgh employment rate wll make socety farer and better off, but t s an nput n the producton 9

13 of GDP. We, therefore, ntroduce the lnk constrantl L, whch makes sure that 1 1 the level of employment s equvalent n the two sub-technologes. Here, the tradeoff s also clear: whle we desre to maxmze the level of employment from a socal pont of vew, effcency n economc actvtes mnmzes the neffcent level of employment n the producton of GDP. Smlarly, GDP appears as the output n T1 and s used n T3 as an nput for the producton of healthcare and educaton va expendtures. We ntroduce the constrant 1 1 GDP GDP n order to lnk these two sub-technologes. Fnally, we can defne our global three pllars technology as follows: T ( GDP, L, K, E, CO, LS, HE, EE) R, 3pllars 2 GDP GDP, K K, L L, E E, 1, E E, CO2 CO2, L L, LS LS, HE HE, EE EE, GDP GDP, L E L E 1 1 (6) GDP GDP Defnton of the dstance functon and effcency measurement The three pllars technology defned n (6) serves as the bass for effcency measurement. n order to compute the dstance of any observed DMU to the fronter of ths producton set, we ntroduce a measurement tool defned as a dstance functon (Shephard, 10

14 1970; Chambers et al., 1996). Formally, the output drectonal dstance functon (Chambers et al., 1996) s defned by: DT ( x,y;g) sup : ( x,y + g ) T (7) where can be nterpreted as the neffcency score and measures the maxmum possblty of ncreasng outputs. Ths ncrease s measured n terms of an output bundle gven by the drecton vector g. We adapt ths approach to our context. Frst, whle s a unque scalar n the defnton gven n (8), we ntroduce specfc effcency scores for each component of our three pllars δ. Second, whle, n (7), s defned as technology as the vector: GDP, CO, L, HE, EE non-negatve ( ), we allow for the possblty of negatve values ( 2 δ ). Ths s necessary to model the possble tradeoffs among the three pllars. As explaned above, the mnmzaton of the bad output CO2 can lead to a decrease of GDP and hence a negatve value of GDP. Ths s partcularly nterestng because t allows us to consder scenaros of degrowth. Thrd, we chose, as the output bundle defnng the drecton vector g, the observed outputs of evaluated DMUs. For a DMU, we defne: g ' GDP ', CO ' ' ' ' 2, L, HE, EE. The negatve sgn on CO2 ndcates that t s a bad output whch must be mnmzed whle other outputs are consdered as good, hence postve. Wth ths choce of the drecton vector g, the nterpretaton of effcency scores δ are straghtforward as the feasble ncrease (or decrease for CO2) as a percentage of the observed outputs. Fourth, we ntroduce dfferent weghtng schemes for each pllar: w, w, w w n order to model dfferent polcy objectves ECO ENV SOC for DMUs. n our emprcal applcaton, we wll set weghts such that prortes of each country 11

15 can be put on economc, envronment, socal or any mx of the three pllars. Gven these defntons, we arrve at the followng three pllars dstance functon: D ( x,y;w, g) sup wδ : ( x,y +δg ) T (8) 3pllars 3pllars The last step of our methodology s the estmaton of effcency scores. For a gven DMU, dstance functon n (8) can be computed by lnear programmng n a DEA framework. D ' ' ' 3 (, pllars x,y ;w g ),,,,, L, E, GDP ' ' 1 ' ' ' max weco GDP wenv CO w ( ) 2 SOC L HE EE 3 s.. t GDP GDP GDP ' ' ' GDP 1 2 ' 0 1,..., 1 K L E CO K L E CO 0 1,..., E CO ' ' ' 2 CO2 2 E (LP1) 12

16 ' ' ' L ' 0 1,..., ' ' ' HE ' ' ' EE 0 1,..., L L L LS LS HE HE HE EE EE EE GDP GDP L E GDP L E 1 1 GDP LP1 computes the effcency score for each dmenson of the three pllars. Whle t s further possble to ntroduce specfc weghts for labor, healthcare and educaton n the socal dmenson, we chose to wegh these dmensons equally. Ths restrcton can be easly relaxed. As t appears clearly from LP1, only captal and labor stock ( K ' ' and LS ) are exogenous. Labor, energy and GDP are part of the varables of LP1. At the optmal soluton of LP1, we have the followng equaltes: GDP GDP GDP L L L ' ' ' L ' ' ' GDP E E E 1 1 (9) Therefore, GDP, labor and energy are clearly endogenous n the model and ther optmal level can be greater than, equal to or less than the levels of the evaluated DMU snce effcency scores are not restrcted n sgn: δ. Ths flexblty s one of the man 13

17 contrbuton of our three pllars model. For example, f we put more of weght on envronment w w, w, w 0,1,0 ECO ENV SOC, the only objectve s to reduce CO2 emssons and the optmal level of energy would probably be less than the observed level for the evaluated DMU. Ths would lead to degrowth n GDP by the lnk ntroduced among the three sub-technologes. As another example, f all the weght s put on employment, the optmal level wll surely be hgher than the evaluated one and wll probably lead to more GDP and more CO2. A tradeoff between employment and envronment would result. All tradeoffs among the three objectves are allowed by our model. Fnally ths applcaton on emprcal data wll reveal the ultmate values of these tradeoffs for each country. As a summarzng remark, we could have also used smulated data as the evaluated DMU nstead of usng data from an observed DMU. Hence, the model can become a normatve tool for smulatng dfferent scenaros and choosng the best polcy n accordance wth the socal planner preferences. 4. Emprcal results 4.1 Data The data of captal stock, labor stock, GDP, and employment are from the AMECO database (European Commsson, 2017); energy consumptons and carbon emssons are from the Headlne Energy Data (nternatonal Energy Agency, 2016), and healthcare and educaton expendtures are from the World Development ndcators (World Bank, 2017). Ths dataset ncludes 21 OECD countres coverng the years : Australa, Austra, Belgum, Canada, Denmark, Fnland, France, Germany, Greece, reland, taly, Japan, Netherlands, New Zealand, Norway, Portugal, Span, Sweden, Swtzerland, Unted Kngdom (UK), and Unted States (US). 14

18 We construct a dataset for three sub-technologes: n the economc technology, net captal stock (bllons Euros), employment (1000 persons), and energy consumpton measured as kloton of ol equvalent, KTOE 1 are used to produce GDP (bllons Euros). n the envronmental fronter, energy consumpton can generate carbon emssons (measured n mllon tons). For the socal pllar, employment s affected by labor stock (reported n 1000 s of persons), and healthcare and educaton expendtures (are gven n bllons Euros) rely upon GDP. The captal stock, GDP, and healthcare and educaton expendtures are measured as at base year 2010 wth purchasng power party (PPP) s n bllons of 2010 Euros. n Table 1, we present partal productvty ndcators used n sub-technologes on envronment and socal pllars. There appears to be varablty n our data. For example, tons CO2 per kg of energy shows varatons from 1.31 for Sweden to 5.1 for Australa. The same s true for GDP rangng from for New Zealand to for the Unted States. Table 1 about here Table 2 about here The descrptve statstcs presented n Table 2 demonstrates a wde varaton wth postve trends n all varables except for energy use and CO2 emssons ndcatng that there s more conservaton over ths tme perod whch does not appear to negatvely affect the other pllars of GDP and socal good expendtures. t should also be noted that 1-L/LS s the unemployment rate. We note that Swtzerland has over-employment whch we attrbute to the hgher number of nternatonal employees at nternatonal organzatons such as the World Health Organzaton and our labor stock varable s based on domestc workforces. 1 All energy sources are consdered ncluded, ol, natural gas, coal, peat, ol shale, feedstock (such as corn) nuclear, and renewable resource as the total n the KTOE 15

19 Snce there are nfnte scenaros that could be examned and our model has many dmensons, (number of scenaros, number of pllars, number of countres, number of years), t would be mpossble to present all feasble results for all the dmensons together. Hence, we made the choce to lmt weghts from all the weght on each pllar to an even splt on two pllars and scenaros wth heaver weghts to a scenaro wheren all pllars are equal n Table 3. We frst present results at an aggregated level and then we hghlght one or two dmenson at a tme. Table 3 about here Average effcency change s presented n Table 4. We note that hgh values of average neffcency for CO2, HE and EE n Table 4 can be explaned by the ntal varablty of partal productvty ndcators presented n Table 2. For example, we found a hgh possble ncrease of 83% n EE for scenaro 3 but we also see n Table 2 to that the share of educaton expendtures n GDP goes from 3.61% to 8.13%. Therefore, f we observed n the ntal data that some countres can spend more than twce than other countres, then an 83% ncrease n EE s realstc. Table 4 about here Recall that n Table 3, we present the 10 dfferent weghtng schemes used n assessng the three pllars. We note that these weghtng schemes reflect dfferent objectves n pursung the desred outcomes and mnmzng the bad outcome of CO2. We provde these varyng scenaros to demonstrate the dea presented n the background and methodology sectons. Specfcally, n some papers, socal goods were underweghted and n others the envronment was underweghted. n Table 4, we present our fndngs from these dfferng scenaros emphaszng that n ths table the fndngs are for all the OECD countres n our sample for all years t should be noted for the economc and socal goods (GDP, L, HE, EE) a 16

20 negatve sgn ndcates a fall n ths pllar. For the economc bad, CO2, a postve sgn ndcates the amount ths bad could be reduced, a negatve sgn reflects an ncrease n the CO2 emssons. When GDP s weghted by 100% (scenaro 1), economc growth could ncrease by 18% coupled wth an ncrease of CO2 of 28%, an ncrease n employment of 7% wth healthcare spendng by 19% and educaton decreasng by 14%. When the envronment s weghted by 100% (scenaro 2), GDP would fall by 24% but, there would be a major mprovement n the reducton of CO2 by 66%. Employment, healthcare, and educaton expendtures would fall by 10%, 22% and 45% respectvely. n the case when socal welfare s weghted by 100% (scenaro 3), GDP would grow (18%) as would employment (7%), and health and educaton would ncrease by 47% and 83% respectvely. However, the envronment would suffer by an ncrease of CO2 by 28%. n the case when the GDP and CO2 are equally weghted at 50% each wth no weghtng on socal welfare (scenaro 4), there s some growth n GDP, 7%, but agan, there s a large declne n the amount of CO2 emssons (56%). There s a 5% growth n employment, whle governments could expand spendng on healthcare by 9% and decrease educaton expendtures by 22%. gnorng CO2 by weghtng GDP and socal welfare each by 50% (scenaro 5) demonstrates the same results as n the case when socal welfare s weghted by 100% (scenaro 3). n both cases, t s the tradeoff between these two objectves and the CO2, wth the latter ncreasng by 28%. Conversely, when CO2 and socal welfare are weghted at 50% each (scenaro 6), GDP can grow by 7% but wth a large potental reducton n emssons (56%), employment growth by 7% and wth ncreases n health and educaton spendng by 34 and 66% respectvely%. Treatng each of the pllars equally (scenaro 7) we report an ncrease n GDP 17

21 by 12%, a 48% reducton n CO2, employment ncreases of 7% and hgher expendtures n both health and educaton. As n the case when CO2 was weghted at 0% n scenaros 3 and 5, the lower weghtng of CO2 n scenaros 8 and 10, there s no reducton n emssons. t s only n the case of scenaro 9, when the envronment s weghted hgher s there an opportunty to reduce emssons. But t should be noted that n scenaro 9 there s only 2% growth n GDP. For all specfc OECD countres n our sample for all years ( ), we present the results under scenaro 7 wheren all the pllars are weghted equally. We present these results n Table 5. Table 5 about here Under scenaro 7, Norway s the only country for whch mprovements n envronmental and socal dmensons lead to a small degrowth of 4%; for all other countres mprovng envronmental and socal pllars also lead to mprove the economc pllar. There s a large varaton n the amount of CO2 that could be reduced from 18% for taly to 71% n Poland. Employment ncreases are the greatest (more than 10%) for Span, Portugal, France, reland and Belgum. Japan shows a negatve value meanng that mprovements n others dmensons can be made by reducng ts level of employment. ncreases n HE range from 1% for Denmark to 92% n Poland and EE could be ncreased the most, on average, ndcatng neffcent amount of expendtures on educaton n all the OECD countres n our sample except for Denmark. As dscussed above, the wde range of varablty n neffcences for HE and EE are related to the hgh degree varablty we fnd n the ntal data (Table 2). Fnally, even f energy s not n the objectve functon of our three pllar model meanng that we do not seek to maxmze or mnmze energy use, we can compute ts level for the optmal soluton we derved. nterestngly, Fnland, Belgum, Canada, Sweden and Norway can acheve maxmal potental 18

22 ncreases n the three pllars by reducng ther energy consumpton. On the contrary, countres such as taly, Japan, Germany, Span or Portugal requre an ncrease n ther level of energy consumpton. Snce one of our man emphass n ths study s the reducton of CO2 emssons, we examne the top fve economes for scenaro 7 as an llustraton of changes over tme. Fgure 1 about here We note that the UK and the US are clustered well above the other three natons n ths fgure. France s CO2 emssons trend demonstrated a decrease of 0.31% over tme. Germany should a sharp ncrease than a steady decrease after 2008 untl 2011 where there was frst a sharp ncrease than a decrease. The economc crss of 2008 seems only to have affected Germany n terms of a dramatc decrease n CO2 emssons. Japan s seen as beng relatvely effcent n the reducton of CO2 emssons untl 2010 when a steady ncrease of emssons ncreased by 8.13%. However, Japan also presents an nterestng emprcal fndng n that after 2010 s Fukshma dsaster due to the earthquake and tsunam, Japan s nuclear energy was decreased and substtuted other forms of energy use that ncreased CO2 emssons. n Table 6 we provde an example of results at a dsaggregated level. We assess the performance of France and the US for the frst and last years of our study perod (2005 and 2012, respectvely) under the three extreme scenaros 1, 2, 3, and the scenaro 7 When weght s put on economc pllar, n scenaro 1, France could expand GDP by between 26-29% for the frst and last perod. When reducng CO2 s the only weghted objectve (scenaro 2) France can reduce CO2 emssons by 57% and 62% respectvely. nterestngly, ths mprovement n envronmental performance s correlated wth a strong decrease n the GDP 19

23 level (-41% and -25%). The use of energy s also mpacted (-33% and -36%). Ths s typcal of a degrowth scenaro. When weght s put on socal pllar, ncrease n the employment level s about 12% to 15% whle expendtures n healthcare and educaton can also be sgnfcantly expanded. The medan scenaro 7 leads to mprovement n all dmensons. Compared to France, n scenaro 1, the US are effcent n the GDP dmenson. n scenaro 2, they could reduce the CO2 by 69% n 2005 and 74% n Agan, we can see here a degrowth scenaro n 2005 n whch the GDP fell by 18% as the employment (-14%) and expendtures on health (-18%) and educaton (-43%), and the same s true for Under scenaro 3, the US are effcent n the labor dmenson but could expand ther expenses on healthcare and educaton. Under the more equally weghted scenaro, the US are effcent on the GDP and employment dmensons but can stll decrease sgnfcantly ther CO2 emssons the US. Table 6 about here 5. Dscusson and Summary n 1809, Thomas Jefferson wrote The care of human lfe and happness s the only legtmate object of good government. Corroboratng ths sentment s the OECD that ranks the world s happest countres that meet the objectves of GDP, jobs, educaton, health, and envronmental qualty (OECD, 2014). Gven these objectves, we assessed how countres could meet these varyng objectves and what are the possble tradeoffs. Typcally, these oblgatons are referred to as the three pllars of sustanablty economc growth, envronmental preservaton, and socal goods provson. However, there has been some ssues rased how to treat these three jontly. n ths paper, we adopted and expanded on the Murty et al. (2012) approach n whch by-producton technology s ntroduced. Our by-product assessment of 20

24 economc growth and CO2 emssons s based on two dstnct but lnked technologes. Ths s smlar to the earler argument made by Leontef (1970). We fnd that there s varyng dfferences among scenaros and countres when optmal energy s compared wth observed energy as a percentage. These fndngs ndcate that some countres operate closer to the optmal energy use whch not only does not lead to degrowth, but does lend optmsm to other countres followng these more effcent scenaros (and commensurate weghtng schemes) and other countres energy usage. Moreover, we expand on the Murty et al. (2012) approach by addng the provson of socal goods employment growth, healthcare, and educaton. Ths s done because as Lehtonen (2004) wrote that the socal dmenson has been treated as the weakest and that the nteracton between the envronmental and socal pllars have been largely gnored. Hence, we rectfy ths short-comng. We also nclude employment as part of the socal welfare pllar. Our fndngs also show that when GDP was weghted as zero, there was degrowth but growth n envronmental mprovement. Employment also fell when the envronment was weghted as 100%. Therefore, degrowth may beneft the envronment, but at the costs of more unemployment, and less expendtures on socal goods. More dffcult to acheve s the avalable ncreases n healthcare and educaton. When socal pllars are more heavly weghted there s growth over tme n the producton of healthcare and educaton va hgher expendtures. However, socal well-beng dpped as the economy suffered durng the recesson of 2008 but began to ncrease agan after the offcal end of the recesson n We also demonstrated that there s postve growth n our sustanablty models over tme n the fgures presented above. Ths portends well that there s postve movement when the governments nclude other factors beyond GDP n establshng socetal well-beng. These fndngs are n lne wth those of Kuosmanen and Kuosmanen (2009) and Ang et al. (2011) 21

25 Some specfc fndngs are worthy of note. We found that there s a wde range of fndngs by countres and that n general, GDP growth and ncreased employment go together, whch s not surprsng. Comparng France and the US, also demonstrated that GDP under VRS wll lead to effcency for the US as the largest OECD economy. But, ths GDP does not automatcally translate nto ncreased socal welfare expendtures especally n healthcare and educaton (both of whch are ncreasngly market orented n the US). Also expected, s that there exsts a tradeoff between reducton of CO2 emssons and GDP growth, corroboratng the dea of degrowth. We also found that any postve weghtng on the socal welfare pllar ncreases the ablty for governments to ncrease ther spendng on healthcare and educaton. We also expanded on earler methodologcal studes by movng beyond the typcal dstance functons (Färe et al., 2005; Zhang et al., 2008; Bellenger and Herlhy, 2009; and Kuosmanen and Kuosmanen, 2009) by ncludng measures of labor (employment) and socal welfare and by lnkng them all together to demonstrate the jont producton under a varety of weghtng schemes. Whle each ndependent sub-technology assumes exogenous nputs, we explctly lnk them together. n our combned technology, only labor stock and captal stock are consdered exogenous. Energy, CO2, employment, as well as GDP, healthcare and educaton expendtures are consdered as endogenous. Because lnks among the sub-technologes are explctly made, tradeoffs among the three pllars are possble. Another extenson s the possblty of negatve values n effcency scores. As shown n our results, the mnmzaton of the bad output CO2 can lead to a decrease of GDP whch allows us to consder scenaros of degrowth. Fnally, we ntroduce dfferent weghtng schemes for each pllar. Whle an applcaton on emprcal data reveals values of tradeoffs for each country, we could the model as a normatve tool for smulatng dfferent scenaros and choosng the best polcy n accordance wth the socal planner preferences. Our paper llustrates that t s possble for socety to assess how best to produce necessary outputs, mnmzng economc bads, and 22

26 optmze well-beng. Focusng on only one pllar, typcally GDP, does not reconcle the full utlty functon of what s necessary for sustanablty. Acknowledgements Zhyang Shen s grateful to the Natonal Scholarshp Study Abroad Program by the Chna Scholarshp Councl (No ). 23

27 Reference Ang, F., van Passel, S. & Mathjs. (2011). Aggregate resource effcency perspectve on sustanablty: A sustanable value applcaton to the EU 15 countres. Ecologcal Economcs, 7, Antal, M., & van den Bergh, J. C. (2014). Re-spendng rebound: A macro-level assessment for OECD countres and emergng economes. Energy Polcy, 68, Baumol, W.J. (1958). Actvty analyss n one lesson. Amercan Economc Revew, 58(5), Bellenger, M & Herlhy, H (2009) An economc approach to envronmental ndces. Ecologcal Economcs, 68, Bosett, V., & B. Bucher. (2009). Data Envelopment Analyss of dfferent clmate polcy scenaros. Ecologcal Economcs, 68, Chambers, R., Chung, Y., & Färe, R. (1996). Beneft and dstance functons. Journal of Economc Theory, 70, European Commsson. (2017). Macro-economc database AMECO, EU. Färe, R., Grosskopf, S. (2004). Modelng undesrable factors n effcency evaluaton: Comment. European Journal of Operatonal Research,157, Färe, R., Grosskopf, S., & Pasurka, C. A. (2007). Envronmental producton functons and envronmental drectonal dstance functons. Energy, 32(7), Färe, R., Grosskopf, S., Noh, D. W., & Weber, W. (2005). Characterstcs of a pollutng technology: theory and practce. Journal of Econometrcs, 126(2), Farrell, M. J. (1957). The measurement of productve effcency. Journal of the Royal Statstcal Socety. Seres A (General), 120(3),

28 Georgescu-Roegen, N. (1977). nequalty, Lmts and Growth from a Boeconomc Vewpont. Revew of Socal Economy, XXXV(3), Georgescu-Roegen, N. (1979). Energy Analyss and Economc Valuaton. Southern Economc Journal, 45, Hamlton, K. (1996). Polluton and polluton abatement n the natonal accounts. Revew of ncome and Wealth, 42(1), nternatonal Energy Agency, (2016). EA Headlne Energy Data, Pars. Koopmans, T. C. (Ed.). (1951). Actvty analyss of producton and allocaton (No. 13). New York: Wley. Kuosmanen, T. & N. Kusomanen. (2009). How not to measure sustanable value (and how one mght), Ecologcal Economcs, 68, Lehtonen, M. (2004). The envronmental socal nterface of sustanable development: capabltes, socal captal, nsttutons. Ecologcal economcs, 49(2), Leontef, W. (1970). Envronmental repercussons and the economc structure: an nput-output approach. The revew of economcs and statstcs, Murty, S., Russell, R. R., & Levkoff, S. B. (2012). On modelng polluton-generatng technologes. Journal of Envronmental Economcs and Management, 64(1), OECD (2014). How's Lfe? 2015: Measurng Well-beng, OECD Publshng Ray S.C., Mukherjee K., Venkatesh A. (2017). Nonparametrc measures of effcency n the presence of undesrable outputs: a by-producton approach. Emprcal Economcs, DO /s Sahoo, B. K., Luptack, M., Mahlberg, B. (2011). Alternatve measures of envronmental technology structure n DEA: an applcaton. European Journal of Operatonal Research, 215,

29 Seford, L.M., Zhu, J. (2002). Modellng undesrable outputs n effcency evaluaton. European Journal of Operatonal Research, 142, Scognamllo, A., Mele, G., & Sensn, L. (2016). Nonrenewable resources, ncome nequalty and per capta GDP: an emprcal analyss. Shephard, R. W. (1953). Cost and Producton Functons, Prnceton Unversty Press, Prnceton. Shephard, R.W. (1970). Theory of Cost and Producton Functons. Prnceton Unversty Press, Prnceton. Sueyosh,T., Goto, M. (2011). Methodologcal comparson between two unfed (operatonal and envronmental) effcency measurements for envronmental assessment. European Journal of Operatonal Research, 210, World Bank. (2017). World Development ndcators, Washngton. Zhang, Y. F., Parker, D., & Krkpatrck, C. (2008). Electrcty sector reform n developng countres: an econometrc assessment of the effects of prvatzaton, competton and regulaton. Journal of Regulatory Economcs, 33(2), Zhou, P., Ang, B. W., & Poh, K. L. (2006). Slacks-based effcency measures for modelng envronmental performance. Ecologcal Economcs, 60(1), Zhou, P., Ang, B. W., & Poh, K. L. (2008). A survey of data envelopment analyss n energy and envronmental studes. European Journal of Operatonal Research, 189(1),

30 Table 1 Descrptve Statstcs of nputs and Outputs Varable Unt Mean Std. Dev. Mn Max Trend Captal stock (K) bllons % Employment (L) 1000 persons % Energy (E) KTOE % GDP bllons % CO2 mllon tons % Labor stock (LS) 1000 persons % Healthcare (HE) bllons % Educaton (EE) bllons % Table 2 Descrptve Statstcs of partal productvty rato by country all years CO2/E L/LS HE/GDP EE/GDP (KT) (%) (%) (%) Australa 5, ,99 4,95 Austra 2, ,10 5,45 Belgum 2, ,57 6,16 Canada 2, ,32 4,97 Denmark 3, ,95 8,13 Fnland 2, ,53 6,28 France 2, ,46 5,54 Germany 3, ,18 4,60 reland 3, ,92 5,38 taly 3, ,90 4,28 Japan 3, ,41 3,61 Netherlands 2, ,43 5,29 New Zealand 2, ,35 6,41 Norway 1, ,52 6,72 Poland 4, ,66 5,05 Portugal 2, ,75 5,07 Span 3, ,58 4,50 Sweden 1, ,13 6,65 Swtzerland 2, ,79 4,98 UK 3, ,40 5,41 US 3, ,53 5,24 Total sample 2, ,31 5,46 27

31 Table 3 Weght on each fronter for scenaros Scenaro Economc weco Envronmental wenv Socal wsoc 1 100% 0% 0% 2 0% 100% 0% 3 0% 0% 100% 4 50% 50% 0% 5 50% 0% 50% 6 0% 50% 50% 7 33% 33% 33% 8 67% 17% 17% 9 17% 67% 17% 10 17% 17% 67% Table 4 Average neffcency change for each scenaro OECD level, all years- Scenaro GDP CO2 L HE EE Energy* 1 18% -28% 7% 19% -14% +40% 2-24% 66% -10% -22% -45% -28% 3 18% -28% 7% 47% 83% +40% 4 7% 56% 5% 9% -22% -6% 5 18% -28% 7% 47% 83% +40% 6 7% 56% 7% 34% 66% -5% 7 12% 48% 7% 41% 74% +12% 8 18% 34% 7% 47% 82% +37% 9 2% 60% 3% 28% 57% -15% 10 18% 34% 7% 47% 82% +36% *Energy reflects the varaton of energy consumpton n optmal level: (optmal energy-observed energy)/ observed energy. 28

32 Table 5 Natonal neffcency scores for scenaro 7 all years Country GDP CO 2 L HE EE Energy* Australa 8% 69% 8% 62% 78% +20% Austra 32% 31% 7% 45% 96% +34% Belgum 3% 65% 13% 22% 36% -34% Canada 4% 67% 8% 27% 70% -31% Denmark 1% 57% 7% 1% 1% +6% Fnland 16% 66% 11% 59% 51% -41% France 10% 33% 13% 16% 61% +9% Germany 24% 41% 9% 35% 119% +54% reland 3% 60% 13% 56% 57% +9% taly 30% 18% 9% 69% 148% +91% Japan 33% 34% -7% 61% 200% +85% Netherlands 10% 54% 6% 18% 70% -10% New Zealand 0% 48% 0% 9% 27% 0% Norway -4% 37% 6% 14% 16% -17% Poland 0% 71% 0% 92% 62% 0% Portugal 34% 33% 15% 79% 116% +41% Span 34% 37% 20% 83% 143% +51% Sweden 15% 28% 11% 28% 40% -28% Swtzerland 2% 34% 0% 35% 67% +6% UK 0% 63% 0% 21% 50% 0% US 0% 63% 0% 19% 55% 0% *Energy reflects the varaton of energy consumpton n optmal level: (optmal energy-observed energy)/ observed energy. 29

33 Table 6 Performance analyss for the France and US for the frst and last years of the study perod Country Year GDP CO2 L HE EE Energy* 2005 Scenaro1 26% -91% 12% 2% -20% +91% Scenaro2-41% 57% -9% -52% -63% -33% Scenaro3 26% -91% 12% 26% 85% +91% France Scenaro7 8% 32% 12% 8% 59% +6% 2012 Scenaro1 29% -212% 15% 3% -8% +84% Scenaro2-25% 62% -15% -41% -47% -36% Scenaro3 29% -212% 15% 38% 98% +84% Scenaro7 12% 34% 15% 19% 71% +11% 2005 Scenaro1 0% 40% 0% -1% -31% 0% Scenaro2-18% 69% -14% -18% -43% -20% Unted Scenaro3 0% 40% 0% 23% 59% 0% States Scenaro7 0% 61% 0% 23% 59% 0% 2012 Scenaro1 0% 0% 0% -13% -22% 0% Scenaro2-23% 74% -18% -33% -40% -25% Scenaro3 0% 0% 0% 17% 69% 0% Scenaro7 0% 65% 0% 17% 69% 0% *Energy reflects the varaton of energy consumpton n optmal level: (optmal energy-observed energy)/ observed energy. 30

34 Fgure1 Average CO2 neffcency score over tme 70% 65% 60% 55% 50% 45% 40% 0.72% 0.56% France Germany Japan Unted Kngdom Unted States 8.13% 0.11% 35% 30% -0.31% 25% 20%

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