USE OF ENTERPRISES DATA IN ECONOMIC PLANNING

Transcription

1 USE OF ENTERPRISES DATA IN ECONOMIC PLANNING Carlos Domngo 1,2, Vcente Ramírez 1,3, Agustín Velásquez 4, Harold Zavarce 4, 1 Unversdad de los Andes; 2 Facultad Economía; 3 Facultad de Ingenería; Mérda Venezuela 4 Banco Central devenezuela, Caracas, Venezuela ABSTRACT The process of economc plannng s classcally dealt wth Leontef s nput-output analyss. In ths work we ndcate some problems that arose n the buldng and use of ths method. We propose an alternatve method that uses a productve enterprses database and a mcrosmulaton procedure to determne the propagaton of economc changes to the whole set of enterprses, to see the mpact of the changes and to gude the procedures to mplement them. KEY WORDS Mcrosmulaton, economc plannng, databases, nputoutput analyss. 1. Introducton Many economc problems requre certan degree of economc plannng. Producton of new goods or servces, nstallaton of bg enterprses, explotaton of new resources, changes n technology, changes n the productons due to nternatonal agreements, and many smlar processes pose complex problems. The complexty arses from the fact that some alteraton n a sector of the economy entals modfcatons n other sectors: new mports, search for new markets, new types of employment, captals, and other resources. Besdes, the mplementaton of the changes alters socal, ecologcal, and regonal equlbrum. 2. The Input/Output matrx methods: Utlty and problems A well known classcal method to cope wth some of these complextes s the use of Input-Output matrces, orgnated from Leontef semnal works [1,2]. The practcal mplementaton and use of the matrx may be found n many books as Mller and Blar [3]. The buldng of these matrces was recommended by the Unted Natons [4] [5]. In these and related works [6], methods to buld the IO matrx from enterprses data, the use of the matrx to get an overvew of a natonal economy, to compare economes of dfferent countres, and the use for economc plannng are dscussed. Although the problems of buldng and usng an IO matrx n plannng are generally known [7] we wll refer brefly to them to ustfy the method that we propose. 2.1 The data to buld an IO matrx. The data to buld the matrx are based n surveys or censuses about the producton (outputs) and spendng (nputs) of enterprses. The mported nputs are usually dstngushed from the natonally produced, and captal nputs may be dstngushed from the other nputs. If an enterprse produces only one product, the techncal coeffcents (quantty of each resource used n the producton of a unt of the product) result mmedately for that enterprse. If there are many enterprses producng only ths product the data can be aggregated, assumng, whch may be erroneous, that equal technology s used, and mean techncal coeffcents may be computed. The problem arses for the enterprses that produce many products and gve the data of the nputs for the whole producton. Besdes, n many cases, there are products that are not produced as the unque product of some enterprses. Dfferent methods are proposed to estmate the techncal coeffcents for such products usng the nformaton gven for multproducers. They are based n the dubous assumpton that all the enterprses use the same technology and the same nputs to produce the same products. The cted works of the Unted Natons recommend to dvde the enterprse n establshments that produce only one product and use the so computed techncal coeffcents to dscount the resources n producers that have ths and other products as outputs, assumng the same technology n all the producers. The dvson n monoproducer establshments s not possble n many cases and t s recommended to get at least, a prncpal product and methods are recommended to deal wth secondary products. All methods are exposed to serous crtcsms, so that the estmaton of techncal coeffcents compatble wth the whole nformaton may be affected by an error dffcult to be determned. In the data of a large survey of 1982 establshments of the BCV (Venezuelan Central Bank) we fnd, n the prvate manufacture sector, 551 monoproducers and 50% of the products were never found as unque product. The method of dscounts for the nputs of multproducers, usng techncal coeffcents found n monoproducers,

2 leads sometmes to negatve resdual nputs, probably because of dfferent technologes n the producers and dfferent forms of aggregaton n nputs desgned wth the same name. When usng these methods, the IO matrx at a certan aggregaton level of the sectors s computed. 2.2 Aggregaton Aggregaton of the enterprses n a few (say 15 or 30) economc sectors (usually usng the Unform Internatonal classfcaton of Economc Actvtes after the UN) s adequate to get a quck global vson of the economc system, to apprecate the relatve strength of nterrelaton of the sectors and to compare wth other natonal economes for whch smlar matrces are avalable. But less aggregated matrces (several hundreds of sectors) are requred for plannng. It s, for nstance, not enough to know that an ncrement of the constructon sector mples certan ncrement of forestry, t s necessary to know what types of tmber producton are requested, whch are dfferent of those used by furnture or wood pulp. It s also necessary n many cases to dscrmnate, nto dfferent sectors, smlar products produced by dfferent technologes that use dfferent nput resources and have dfferent mpacts. Sometmes, an ncrement n a sector that s udged as quanttatvely unmportant may be mpossble to accomplsh by lack of a key resource or technology and the defct may be a bottleneck n the desred producton processes. The aggregaton may hnder the exstence of bottlenecks whose knowledge s essental for the planners. 2.3 Addtonal nformaton that do not enter n the matrx Other mportant ssue s that n the aggregaton some nformaton useful for plannng s lost. That nformaton s sometmes collected n the survey, as locaton of the establshments. Other mght have been easly collected, such as lmts n the producton and sem-quanttatve data about the dependence of the nput ncrements on each ncrement producton of each product. Consderatons over the supply markets, qualty of management, strategc mportance of the product, socal relevance of the establshment, educatonal and tranng mpacts, and polluton problems are generally lost when an IO matrx s used. Some of them as envronmental and employment ssues may be of course added wthout dffculty to the matrx [5] although the responsbltes for the mpacts are not seen n the matrx model and must be searched back n the orgnal basc data. Know-how data n the establshment, sometmes apprecated durng the survey are frequently not regstered because there are not methods to embody them n the matrx buldng. 2.4 Lnear and ndependence assumptons n the use of the matrx When the productons are computed by solvng the Leontef equatons for a gven consumpton, the assumpton of a lnear proportonalty between resources and the producton and the assumpton of ndependent addtve contrbutons of each nput on the producton are ntroduced to make the soluton feasble. These assumptons are not strctly true That the proportonalty between nput and producton does frequently not hold s a known techncal fact n cost accountng methods [8]. Although some of the errors are mtgated wth ncreasng aggregaton ths, as we have sad, decreases the plannng usefulness of the IO matrx method. A most realstc non lnear and nteractve functon producton s a Cobb-Douglas type relaton for labor and captal, whch we can generalze to all the nputs. A smple deducton leads to an equaton that expressed the relatve ncreases of productons as a lnear combnaton of the relatve changes n the nputs used n the producton. Ths can be obtaned f the producer knows the relatve weghts of the producton factors (nputs) on the relatve ncrements of the productons (outputs) of each product. Some enterprses have an estmaton of ther own IO matrx. Ths may be useful to the estmaton of the aggregate matrx but t would be dffcult to use because the dfferent technology among enterprses wth smlar productons. Another mportant nformaton that enterprses have but not used n the usual mplementaton of the matrx s the classfcaton between proportonal ncrease n certan nputs and non proportonal or dscontnuous change n other nputs when the outputs change. Besdes, some enterprses develop ther own nput-output matrx for certan products, whch are a partal representatons of ther technologes. All ths mportant nformaton s dffcult to use n aggregate nput-output matrx complaton, but may be easly emboded n the method that we propose. 3. The method of enterprses data (EDM) We propose a method that solves many of these shortcomngs of the IO n plannng, and allows to use many mportant nformaton easy to collect but dffcult to use n that classcal method. The method do not pretend to plan the whole natonal economy and less to optmze the plan as may be seen for nstance n [9]. The obect s to predct economc, envronmental, regonal and socal effects of planned changes n producton, new enterprses and technologc changes, based n country or regon real economy. In the sequel we use the word enterprse or establshment ndstnctly. 3.1 The database s establshments The method we propose conssts n the drect use of the data from the enterprses or establshments gven as a database, and n the developng algorthmc mcrosmulaton technques to use that database n the plannng processess. Many of these data are now collected by the governments for the requred Natonal Accounts yearly publshed as a natonal compromse wth the UN or the recommended buldng of IO matrces. As descrbed above, for each establshment we have a lst of the productons (outputs) of the dfferent products

3 and a complete lst of nputs both expressed at constant prces for a fxed producton tme (n our example one year). The mported nputs and exported outputs must be specfed. We add all the nformaton qualtatve or quanttatve that we could got about an enterprse: the employment of dverse categores, technology, locaton, socal and envronmental mpacts, taxes, and strategc characterstcs cted n 2.3. Obtaned data about relatonshps between ncrements of producton and nputs must be added to the database. Of course the upkeep of that database may also be useful n other applcatons, for example to search establshments that have prescrbed nterestng characterstcs or to obtan nformaton about the establshments, usng logcal condtons and statstcal procedures (ncluded Data Mnng) emboded n many database packages. 3.2 Use of enterprse s database n plannng To use ths databases n plannng problems we developed some algorthms. An example s descrbed n Fgure 1. We note that many dfferent algorthms are possble dependng of the obect of the plannng process The producton plan Ths conssts of the requred amount of some products. Ths plan may be based n estmated new natonal consumpton or export needs, but may also ncluded estmated productons of ntermedate goods. It may also nclude reductons n the producton of goods dctated by ecologcal, strategc or nternatonal agreements reasons. For smplcty n exposton let us consder only desred ncreases n productons and for brevty we wll called them defcts Search of establshments that may reduced the defct To mnmze the mpact of the plan on the enterprses we may start lookng n the database the enterprse whose producton structure (outputs of ts dfferent products) s most correlated wth the defct. Correlaton coeffcent was used n our example. We computed the ncrease of the producton n that enterprse to satsfy the plan wthout ntroducng spurous (not n the defct) productons wth the ncrement. We may restrct ths ncrease to a quantty that may be regstered n the database as the maxmum output for each product n ths enterprse. The selecton of the enterprses may be condtoned to other crtera n the database: geographc, belongng to ndustral clusters, type of enterprse, sze, mports requred, as t was mentoned above. Usually t s not possble to cover the defcts ncreasng wth only one enterprse. Ths allow to reduce the defct and possbly to cover the defct of only one product. The consderaton of other enterprses may further reduce the defct of the plan. The process of reducton s stopped by some automatc or user decded crteron. The process of ncreasng productons may be termnated because defcts of all products become neglgble or no admssble enterprse s found to reduce the defct, or the defct of certan products cannot be further reduced. Up to ths pont the result s the producton s ncrement propostons n some enterprses and perhaps an rreducble defct. Then t s necessary to consder, for each enterprse, the ncrements of the nputs n goods and servces to satsfy the computed ncrements of outputs. Ths requres and nverson of the producton functon of the affected enterprses. One smple way s to assume that the ncreases of the nputs are proportonal to the ncrements of the outputs. Ths s the usual hypothess n the Leontev method. In our method more realstc estmates are possble (see below). The ncrements of the mported nputs are accounted and for the moment t s assumed that the correspondng mports may be done. In a more sophstcated approach t s easy to ntroduce mport restrctons. The necessary nput ncrements of natonally produced goods and servces are then added to the defct and, f the new defct s not admssble, the descrbed process of reducton s repeated. Ths teraton expresses one form (not the only one) n whch the orgnal producton plan propagates to the rest of the economy. The process s proved to be convergent towards neglgble ncrements of the productons perhaps except some rreducble productons of commodtes that may be provded by mports or may be produced natonally by new enterprses. In ths last case the process may be repeated. The output s a lst of the enterprses whose producton must be modfed and, for each one, the requred ncreases n outputs, nputs (ncludng employment), and total mported goods and servces for each enterprse. The output ncluded rreducble defcts. The ncrements of productons may be made n the ndcated enterprses or by creaton of new smlar enterprses The nverson of the producton functons In the second step of the descrbed teraton method the problem arses of computng the ncrements of the nputs gven ncrements of the outputs. As the last are usually more than the former the problem s ndetermnate. When there s only one product or many products wth the same proporton of ncrease the usual hypothess s to assume for each nput an ncrease proportonal to the ncrement of the output. As we dscussed n 2.4 ths s not a relable assumpton. If there are many output products ncreased n dfferent proportons a weghted estmate of these ncrement may be appled to the nputs but ths s even not realstc. We try the followng methods. 1) Assumpton of an nput-output matrx for the enterprse. Some enterprses have developed IO matrces. They are normally dfferent for dfferent enterprses even for those whch produce the same tems because they dffer n technology. It s then possble to compute for ths

4 partcular enterprse the coeffcents that gve the quanttes of nput requred to produce a unt of product. For each of the n ncrements of productons of the enterprse we compute the ncrements of the nputs: n = = c P 1 for the c =1 m nputs 2) Use of a non lnear nput functon. A possble non lnear functon s a Cobb Douglas type: P = k m a = I 1 were k and a are coeffcents that depend on technology. Its meanng may be seen applyng logarthms and taken dfferences: P m = = a =1 n (1) 1 P I So, a s the proporton n whch the fractonal ncrement of the nput contrbutes to the fractonal ncrement of the output. Ths may be estmated n some enterprses. The problem s that usually m>n so, the number of unknowns s greater than the number of equatons. A soluton s to assume that the entrepreneur mnmzes the total cost of the nputs. It s possble to look for the mnmum of the functon: m Mnmum of : F = (2) = subect to the restrctons: P where m = = h 1 h = a P I 1 P = 1,2 n (3) It s necessary to mpose restrctons to the substtutons between the nputs (gven by the classcal so-product curves). An approxmate soluton s to estmate some mnmum for each nput and add the restrctons,.e.: r r The soluton can be done by lnear programmng. The mnmzaton of (2) and (3) by Lagrange multplers leads to a sngular matrx, whle mnmzaton of sum of squares s workable but has not a sound economc meanng. 3) Separaton of drect and ndrect nputs. Ths separaton s made n cost accountng technques, see, for nstance, [7]. Drect costs are proportonal to the productons and may be used to estmated the of the frst method. Indrect costs n the nput may be constant for ample varatons of producton but may change suddenly for certan ncreases of the productons at the successve ponts. P 0, P 1, P 2,... P max wth the values of the requred nputs c F 1 F,... F, 2 max at the successve ntervals of between the ntal producton and the maxmum one. The data for ths star shaped (pece-wese constant) functon may be estmated n the surveys. For some F nputs a fracton s drect and the rest ndrect. For example n a large room wth many electrcal machnes that made a product, the electrcty consumed by the machnes may be proportonal to quantty of product. On the other hand the electrcty spent for llumnaton of the room s constant but may leap up f the room s enlarged or another smlar room, or a new turn of work s added. The use of ths nformaton for the computaton of nputs s straghtforward. If s the fracton of drect use of g the nput n the producton of the product that s varable, the change of the nputs s: n = =1 g c P +(1 g ) P F where: f P and P + P les n the ntervals k and k respectvely where k k, then the value of the nput s F F F = k k (when k = k the ncrement of the nput s 0) Many other methods are possble n dfferent enterprses and may be mproved as the knowledge of the producton methods ncreases. Dfferent methods for computng the nputs may be used n the same database accordng to the fdelty of ther technology s representaton of the partcular enterprse, and the avalable data. Note that dfferent employment s knds may be ntroduced n the same way as the other nputs, usng any of the descrbed methods. 4. Experments wth the method We were not able yet to fnd a database for a real natonal economy. Only partal data from a survey of the Venezuelan Central Bank was avalable. To test the method was decded to estmate data formng a sample of 250 enterprses and 15 products. The assumed data were approxmately proportonal to the data correspondng to the Natonal Accounts of our country. Methods 1), 2), and 3) to compute the nputs were used obtanng dfferent results because t was dffcult to make the methods compatble for a partcular real technology, but n a partcular method the process was robust to some alteratons n the selectons of the enterprses. Although the purpose of ths paper s to show the method rather than present realstc results we gve an excerpt of the output of a run to gve an dea of the possble outputs n the actual algorthm. See Fgure 2.

5 5. Concluson [4] Unted Natons: System of Natonal Accounts, The method requres a contnuous effort of updatng the enterprses database. Ths effort may be worthwhle to [5] Unted Natons: Manual for Complaton and other purposes. On the other hand the method would be Analyss of Input-Output Matrces, useful n many plannng processes: changes n the volume of productons, ntroducton of new enterprses, changes [6] Vu Quang Vet Practces n nput-output table n technology, regonal plannng, tax polces, ecologcal complaton. Regonal Scence and Urban Economcs 24, problems, plannng n state enterprses, suggestons to 1994, p prvate producers, and modfyng ndustry clusters [9] Macroeconomc smulaton based n mcroeconomc data [7] J. Tnbergen, Lectures on economc polcy. North may also be an nterestng possblty. Holland, Extensons of the actual mplementaton may be: ntroducton of tme by recordng the necessary tmes to make the changes n the productons (whch may mply another type of bottleneck) separaton of captal nputs, ntroducton of ndcators to consder qualtatve characterstc n the selecton of enterprses, ncluson of socal varables, mplementaton of an algorthm wth a frendly envronment. Some of them are n progress. Acknowledgements To Venezuela Central Bank and Los Andes Unversty for fnancal support for the Proect. To professors Ganpaolo Orlandon, Olga R. Molna de P. and John Wllam Paez, from FACES, Los Andes Unversty, for useful suggestons. References [1] W. Leontef, The structure of Amercan Economcs, [2] W. Leontef, Input-Output Economcs (1966). Oxford Unversty Press, [3] R. Mller and P. Blar, Input Output Analyss. Prentce Hall, [8] C.J. Horngren, Cost Accountng: A manageral Emphass. Prentce Hall [9] Cockshott, Applcaton of Artfcal Intellgence Technques to Economc Plannng. Department of Economc Scence Strathclyde Unversty. Glasgow. Scotland Fgure 1. General scheme of the algorthm

6 Enter the Producton Plan COMMENTS Mn Ind Cons Fn Type of product Products 1 to 15 (a constructon plan) Search for Aceptable Establshment coverng defct of plan Search for smlar acceptable establshments 184 MODIFIED IncrFrac AcumIncrFrac Establshmen number 184 s acceptable Judge Defct Defct s udged not acceptable 12 MODIFIED IncrFrac AcumIncrFrac Establshment number 12 s acceptable. Search and Judge repeated many tmes Judge Defct Fnsh Producton Adust. Compute nputs for the new producton varatons New nputs added to defct Judge defct. Defct not acceptable New total defct not accepted 10 MODIFIED IncrFrac AcumIncrFrac Search of Establshments re-started Many adustment of productons and nputs follow Judge Defct Fnsh Producton Adust Compute nputs for the new producton varatons Orgnal and actual defct ncludng new nputs Ths defct wll be acceptable ( <2% of defct) Judge Defct Defct plus new nputs accepted. Plan satsfed!!!!!!!! Adustment teratons are fnshed RESULTS Products Natonal Output Plan Induced Output Plan defct % Modfed Establshments (Total 29 from 250) #Est% Var% Prod Inputs Imported Empl Aggr.Val Zone % Zula Var * 0.849* 0.145* 1* 1.367* % Orente Var * 0.148* 0.087* 1* 1.241* % Guayana Var * * 4.888* 14* * more modfed establshments follow % Centro Var * 1.095* 0.512* 2* 1.825* % Zula Var * 0.365* 0.178* 1* 0.708* % Centro Var * 3.836* 1.291* 5* 9.20 Centro Fgure 2. A run of the actual algorthm. (excerpt of the output)