This document introduce the obtained results of the econometric estimation of cement demand and supply in Bolivia considered as a simultaneous equations model, based on two equations, one for the demand and another for the supply. The objective of this study is to quantify the forces that affect the cement market in the period understood among the years 1994 up to 2003. Five models of simultaneous equations were considered, which are based on the respective linear functions of cement demand and supply to be able to explain the coefficients associated to the variables in form of elasticities. The estimates were made following the classic methodology of econometrics with the respective statistical validation, being carried out the individual and grupal validation of the coefficients associated to each variable indicating the statistic significance of the same ones.cement, demand, supply, bolivia.

Melitón Ramirez Mattos

English

Research Papers in Economics

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Melitón Ramírez Mattos – Industrial Engineer 
melix@mail.com 
May 2005 
   
   
   
   
   
   
   
   
   
 
   2 
 
 
 
 
 
 
 
 
 
Acknowledgments 
   
In the realization of this  work  to  the following 
professionals:   
   
Alvaro Andrade Clavijo - FANCESA. Industrial Engineer. 
Rolando Valdivia - UMRPSFXCH. Industrial Engineer.  
   
   
   
   
   
   
   
   
   
   
   
   
   
   
   
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This PDF document is a summary of the project consistent of 230 pages.   
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CONTENT 
   
   
Acknowledgments...........................................2   
Abstract..................................................5   
1. Introduction...........................................7   
2. Sector Analysis........................................7   
3. Model Development.....................................10   
4. Results...............................................12   
5. Conclusions...........................................15   
6. Bibliography..........................................17   
   
   
   
   
   
   
   
   
   
   
   
   
   
   
   
   
   
   
   
   
     5 
ABSTRACT 
   
   
This document  introduce the obtained results of the 
econometric estimation of cement demand and supply in Bolivia 
considered as a simultaneous equations model,  based on two 
equations, one for the demand and another for the supply. The 
objective of this study is to quantify the forces that affect 
the  cement  market in the period understood among the years 
1994 up to 2003.   
   
Five models of simultaneous equations were considered, which 
are based on the respective linear functions of cement demand 
and supply to be able to explain the coefficients associated 
to the variables in form of elasticities. The estimates were 
made following the classic  methodology of econometrics with 
the respective statistical validation, being carried out the 
individual  and groupal  validation of the coefficients 
associated to each variable indicating the  statistic 
significance of the same ones.   
   
   
   
   
   
   
   
   
   
   
   
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1. INTRODUCTION   
   
Cement is an indicator of supreme importance to reflect the 
economic situation of a country. The cement demand and supply 
in  Bolivia are variable and subject to several factors, 
according to Armando Gumucio is considered that the item of 
the construction of highways making use of the rigid pavement 
uses in the country in a direct way from 2.000 to 2.500 
people and easily of 30.000 at 40.000 in an indirect way.   
   
2. SECTOR ANALYSIS 
   
Cement market in Bolivia is provided at the moment by cement 
plants located along the national territory. SOBOCE group 
associates the plants of Viacha (La Paz), Warnes (Santa Cruz), 
Cepsa (Tarija) and Emisa (Oruro), likewise the individual 
participation of Fancesa (Sucre), Itacamba (Santa Cruz) and 
Coboce (Cochabamba). The percentage participation referred to 
cement sales in TM (Metric Tons) of each plant for the years 
understood between 1994 and 2003 is reflected in the graph:   
 
   8 
Fancesa (Sucre) leads the percentage participation in Bolivia 
(27.3%) followed very closely by Viacha (La Paz) (26.61%), in 
third comparative place it is observed Coboce (Cochabamba) 
(21.0%) followed by Warnes (6.47%),  El Puente (5.41%) and 
lastly Emisa (5.19%). The percentage variation of the 
national GDP and the sector of the Construction and Public 
Works are reflected in the following graph:   
   
 
   
The clear effect of the economic crisis is evidenced in these 
indicators, being appreciated a negative variation for 1999 
due to the severe economic crisis that affected the country 
in that period of time, for the later years a light recovery 
is observed.   
The following graph indicates the evolution of the  cement 
demand and supply at national level:   
     9 
 
   
The graph shows the almost parallel evolution of the  cement 
demand and  supply in Bolivia reflecting a maximum in the 
demand and supply in 1999 taking place a gradual decrease in 
later years as clear indicator of the e conomic crisis in 
which Bolivia was involved.  In 2001 a light increment is 
observed from now on.   
   
The following  graph indicates the installed  and occupied 
capacities in Bolivia:   
 
 
   10 
It’s necessary to stand out that the  iddle capacity in 
general is approximately between the range of 29 and 87%. It 
is necessary to make notice that CEPSA, is the only one that 
worked close to 100% of its capacity in production, in the 
same way its capacity in clinker production it overcame to 
the other ones. The productive capacity of Clinker/year in 
Metric Tons appreciates it in the following graph:   
   
 
   
VIACHA and FANCESA have lead the clinker production.   
   
3. MODEL DEVELOPMENT  
   
It’s  assumed the interdependence of the  cement  demand and 
supply being considered both inside a system of simultaneous 
equations being added the  equilibrium condition. Based on 
bibliography, surveys to branch  professionals and in common 
sense, 5 tentative models were formulated dedicated to 
explain the behavior of the variables that affect the demand 
and supply to be able to understand their evolution.   
     11 
Due to their particular characteristics and after the 
respective identifications the next step is estimate the same 
ones using the TSLS method for each one (over-identificated). 
Likewise the prices and quantities of  equilibrium are 
obtained for every year.   
   
The variables included in the  cement demand equation (DCt) 
(TM) are:   
   
- Cement Price (PCt)($us/50 kg bag)   
- National GDP per capita (PIBt) ($us/hab)   
- Construction National GDP per capita (PIBCt) ($us/hab)   
- Cost ratio Construction (ICCt)    
- Telluric Motion (MTt) *   
- Built Roads Length (LCCt) (thousands of Km)   
- Gross Fixed Capital Formation (FBCCt) (thousands of Bs.)   
   
For cement supply (OCt)(TM):   
   
- Cement Price (PCt)($us/50 kg bag)   
- Lagged Cement Price (PCt-1) ($us/50 kg bag)   
- Inputs Production ratio (IPt)   
- Public Investment in Infrastructure (IPEIt) (millions $us)   
- Installed Capacity (CIt) (TM)   
- Quality Certificates (CCt) *   
   
* Dummy variables.   
   
Both equations adopt the lineal form after the application of 
natural logarithms (ln):   
   
   12 
t t t t t t t t t u FBCC LCC MT ICC PIBC PIB PC DC + + + + + + + + = 7 6 5 4 3 2 1 0 a a a a a a a a  
 
t t t t t t t t v CC CI IPEI IP PC PC OC + + + + + + + = - 6 5 4 3 1 2 1 0 b b b b b b b  
 
4. RESULTS    
   
Assuming the market equilibrium is obtained the price and the 
quantity of equilibrium. The results of the estimation using 
TSLS for the period 1994 at 2003 making use of E-Views v1.1c 
are:   
 
Coefficients estimation for Demand 
Final Model 
 
Variable  Coefficients 
PCt  -0.556109 
PIBt  1.224399 
PIBCt  0.135011 
ICCt  -2.073488 
MTt  -0.1307276 
LCCt  5.178661 
FBCCt  0.4772060 
R
2  0.931856 
F  3.907066 
 
 
 
 
 
 
 
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Coefficients estimation for Supply 
Final Model 
 
Variable  Coefficients 
PCt  0.06302695 
PCt-1  0.16221071 
IPt  0.0784555 
IPEIt  -0.686210 
CIt  0.38163385 
CCt  0.00285663 
R
2  0.984003 
F  30.75632 
 
   
BEST MODEL SELECTION 
 
For the selection of the pattern that explains in a better 
way the behavior of the cement demand and supply in Bolivia 
was considered:   
 
1. The sign concordance  obtained in the estimation compared 
with a priori expectations for each coefficient related with 
their respective variable.  
 
2. The value of 
2 R  (R-squared) that measures the adjustment 
kindness for each equation. While higher it is this 
coefficient in the regression, in a better way  it will 
explain the behavior of the dependent variable.  
  
3. The individual statistic for each coefficient indicating 
statistically  if they  are significant and therefore they 
deserve to be present in each equation.     14 
4. The value of F statistic, which indicates if jointly all 
the considered variables are statistically significant to be 
included in their respective equation.   
 
=> The 
2 R calculated for the last model is the highest in 
comparison to the rest (not presented in this summary). The a 
priori  signs are the  expected ones for each coefficient 
associated to  the  respective variable  with the  exception of 
variable (IPEIt),  with a  negative  sign  contrarily to the 
expectation. Explained, possibly, to the final use that the 
invested  mount  by the government in infrastructure, the 
reality is different considering the data. The signs and the 
magnitudes of the rest of the variables are reasonable and 
they are agree with the expectations.   
   
- It was for almost the entirety of the coefficients the 
presence of a high colineality, reflected in the  non-
statistical significance of the parameters that however for 
prediction terms they are not a problem.   
   
- The  F statistic rejects the null hypothesis that affirms 
that the coefficients included in the model  are similar  or 
equal to zero.   
   
 
 
 
 
 
 
 
   15 
PRICE AND EQUILIBRIUM QUANTITY  
   
The prices and  equilibrium  quantities are detailed in the 
following chart:   
   
Year 
Equilibrium Price 
[$us/bag] 
Equilibrium Amount [TM] 
1994  3.67  796974 
1995  4.32  900914 
1996  5.32  916208 
1997  4.24  1057562 
1998  4.89  1164185 
1999  4.56  1178601 
2000  4.56  1065134 
2001  4.51  980404 
2002  4.95  1032325 
2003  4.87  1126219 
 
 
5. CONCLUSIONS   
   
The  main conclusion  in this work is that the cement in 
Bolivia is ruled under the classic laws of demand and supply. 
Numeric values were obtained on the variables that affect 
jointly the cement demand and supply in Bolivia expressed in 
elasticities. It was found that the elasticity estimated for 
the price of the demand has an inelastic value of -0.55610961 
in absolute value, indicating that before an increment of the 
cement price at national level of 1%, we hope the cement 
demand in Bolivia dicreases approximately in 0.56%. Another 
elasticity that deserves an analysis is the GDP per capita, 
before an increment in the GDP per national capita of 1%, we 
hope the cement demand in Bolivia is increased approximately   16 
in 1.22%. The elasticity of higher value  estimated for the 
demand equation is referred to the variable Lenght of Built 
Roads (LCCt) 5.178661 indicating that if  is observed the 
increment of this variable in 1%, we wait that the cement 
demand at national level is increased approximately in 5.18%. 
The variable GDP of the Construction was added (PIBCt) to 
measure the contribution on the cement demand being an 
inferior value to the GDP per capita.   
   
In the same way for  supply: The offer equation has 
characteristic of distributed lagged because it was added to 
the price left behind as explanatory variable. Considering 
the values of the coefficients of PCt on the whole and PCt-1 
(cement price in the previous period) whose values were: 
0.063026956 and 0.16221071 respectively, which are known as 
impact multipliers or of short term, to represent the change 
in the half value of the cement offer after an unitary change 
in the cement price in the same period of time. Maintaining 
the change in the price at the same level of there from now 
on, then 0.063026956 + 0.16221071 correspond to the change in 
the cement offer in the following period, that is to s ay 
0.225238. Then 0.063026956 turn out to be the short term 
multiplier of the  supply equation, while the long term 
multiplier is 0.16221071.  It  means that before an increment 
of 1% in the price of the cement, the bidders will increase 
its production level in approximately 0.063% during the first 
year and 0.16% the second year.  The cocients between 
0.063026956 and 0.225238, in the other side 0.16221071 and 
0.225238  are obtained respectively: 0.279823 and 0.720174, 
indicating that 27.98% of the impact on the offer of cement 
of an unitary change in the price feels immediately and 100% 
feels after having lapsed one year. Equally, it was not   17 
evidenced the dynamics existence statistically in the demand 
equation, when being calculated a negative value for the 
coefficient of the variable it Demands of Cement straggler in 
one period (DCt-1).   
   
6. BIBLIOGRAPHY  
   
Extracto de LA RAZÓN (digital). Edición día lunes 6 de 
diciembre de 2004, declaracion de Marcelo Alfaro Gerente 
General del IBCH. 
 
Extracto de LA RAZÓN (digital). Edición día lunes 6 de 
diciembre de 2004, declaracion de Armando Gumucio Gerente 
General de la Sociedad Boliviana de Cemento. 
 
Gujarati, Damodar N., Econometría, 2da. Edición, Mc Graw 
Hill International Editions, New York. 1994. 
 
Keynes, Jhon Maynard: La Teoría General del Empleo, 
Interés y Dinero, Harcourt Brace Javanovich, Inc., New 
York, 1936 p. 36. 
 
A. C. Harvey: Análisis Econométrico de Series de Tiempo, 
Jhon Wiley & Sosn, Inc., New York, 1981. 
 
Klein, Lawrence R.: Tratado de Econometría, 2da. Edición, 
Prentice-Hall Inc., Englewood Cliffs, 1974. 
 
Theil, Henri: Introducción a la Econometría, Prentice Hall 
Inc., Englewood Cliffs N.J., 1978, pag. 341-342. 
 
Basmann, Roberth L.: “A Generalizated Classical Method of 
Linear Estimation of Coefficients in a Structural Equation”, 
Econometrica, vol. 25, pp. 77-83, 1957. 
 
Behar, Alberto; Edwards, Lawrence, School of Economics, 
University of Cape Town: Estimating Elasticities Of Demand 
And Supply For South African Manufactured Exports Using A 
Vector Error Correction Model, 19 August 2002. 
 
H, Borath, Income and Price Elasticities in Manufacturing 
Exports, in Trade & Industry Monitor, Volumen 5, March 1998; 
Trade and Industrial Policy Secretariat And Development 
Policy Research Unit.   18 
 
Roy, Noel; Mazany, Leigh; E. Schrank, William, A Simultaneous 
Equations Model of the U.S. Market for Canadian Atlantic Cod. 
Paper delivered at the Seventh International Conference of 
the International Institute of Fisheries Economics and Trade, 
Taipei, R.O.C., July 18-21, 1994. 
 
Quantitative Micro Software, E-views: User’s Guide, MicroTSP 
for Windows, Versión 1.1c. 
 
ICRA, The Indian Cement Industry, Executive Summary. Icra 
Limited, 2002. 
 
El-Mefleh, A. Muhannad: ECONOMETRIC FORECASTING FOR JORDAN, 
National University. 
 
Garín Muñoz, Teresa; Pérez Amaral, Teodosio: An Econometric 
Model For International Tourism Flows to Spain, Universidad 
Nacional de Educación a Distancia, Madrid , Spain and 
Universidad Complutense de Madrid, Spain. Working Paper, 
received 13 August 1998. 
 
El Constructor (Revista); Órgano Oficial de la Cámara 
Bolivana de la Construcción; Año 6, Número 32, Septiembre 
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Friedman, Milton: The Methodologies of Positive Economics, 
Essays in Positive Economics, University of Chicago Press, 
1953. 
 
Prentice, David: Estimating a differentiated products models 
with a discrete/continous choice and limited data. La Trobe 
University. David Prentice School of Business. December 1, 
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Extracto NOTICIAS, www.soboce.com Año 4 No. 7 Agosto 2003. 
 

(Revista); Órgano Oficial de la Cámara Bolivana de la Construcción; Año 6, Número 32, Septiembre

A Generalizated Classical Method of Linear Estimation of Coefficients in a Structural Equation”,

Análisis Econométrico de Series de Tiempo,

Edición día lunes 6 de diciembre de 2004, declaracion de Armando Gumucio Gerente General de la Sociedad Boliviana de Cemento.

Edición día lunes 6 de diciembre de 2004, declaracion de Marcelo Alfaro Gerente General del IBCH.

Estimating a differentiated products models with a discrete/continous choice and limited data.

Income and Price Elasticities in Manufacturing Exports, in Trade & Industry Monitor, Volumen 5,

Introducción a la Econometría,

Maynard: La Teoría General del Empleo, Interés y Dinero,

Quantitative Micro Software, E-views: User’s Guide, MicroTSP for Windows, Versión 1.1c.

Teodosio: An Econometric Model For International Tourism Flows to Spain, Universidad Nacional de Educación a Distancia,

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Econometric Model for Cement demand and supply in Bolivia

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Econometric Model for Cement demand and supply in Bolivia

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