1 34.whole paper
Upcoming SlideShare
Loading in...5

Like this? Share it with your network


1 34.whole paper



The International Institute for Science, Technology and Education (IISTE) , International Journals Call for papaers: http://www.iiste.org/Journals

The International Institute for Science, Technology and Education (IISTE) , International Journals Call for papaers: http://www.iiste.org/Journals



Total Views
Views on SlideShare
Embed Views



0 Embeds 0

No embeds



Upload Details

Uploaded via as Adobe PDF

Usage Rights

© All Rights Reserved

Report content

Flagged as inappropriate Flag as inappropriate
Flag as inappropriate

Select your reason for flagging this presentation as inappropriate.

  • Full Name Full Name Comment goes here.
    Are you sure you want to
    Your message goes here
Post Comment
Edit your comment

1 34.whole paper Document Transcript

  • 1. Journal of Economics and Sustainable Development www.iiste.orgISSN 2222-1700 (Paper) ISSN 2222-2855 (Online)Vol.2, No.4, 2011 Analysis of Profitability of Fish Farming Among Women in Osun State, Nigeria Awoyemi, Taiwo Timothy Department of Agricultural Economics, University of Ibadan, P. O. Box 20583, Ibadan, Nigeria. Tel: +2348029541320 Email: ttawoyemi@yahoo.com Ajiboye, Akinyele John (Corresponding Author) Department of Agricultural Education, Osun State College of Education, PMB 5089, Ilesa, Nigeria. Tel: +2348034885815 Email: ajiboyeakinyele09@gmail.comAbstractThe simple random sampling technique was employed in selecting 62 farmers drawn from the samplingframe obtained from the list of Agricultural Development Programme (ADP) contact farmers in the fourLocal Governments Areas (LGAs) of Egbedore, Olorunda, Ede South and Ife Central, which made up thestudy area. The main instrument for collecting the primary data was structured questionnaire. It is evidentfrom the result is that an average total cost of N371486.35 was incurred per annum by fish farmers whilegross revenue of N791242.52 was realized with a gross margin of N 574314 and a profit of N 419756.17. Therate of return on investment of 0.58 implies that for every one naira invested in Fish production by farmers, areturn of N1.5 and a profit of 58k were obtained. The multiple regression result revealed that fish output wassignificantly determined by pond size, labour used, cost of feeds, cost of lime and cost of fingerlings. Thestudy concluded that fish production in the study area is economically rewarding and profitable.Keywords: Women, Profitability, Fish Farming, Gross Margin, Elasticity.1. IntroductionThe Nigerian fishing industry consists of three major sub –sectors, namely the artisanal, industrial andaquaculture. The awareness on the potential of aquaculture to contribute to domestic fish production hascontinued to increase in the country. This stems from the need to meet the much needed fish for domesticproduction and export. Fish species which are commonly cultured include Tilapia spp, Heterobranchusbodorsalis, Clarias gariepinus, Mugie spp, Chrysichthys nigrodigitatus, Heterotis niloticus,Ophiocephalus obscure, Cyprinus carpio and Megalo spp. Fish culture is done in enclosures such as tanks.The aquaculture sub sector contributes between 0.5% and 1% to Nigeria’s domestic fish production.The rapid increase in population of the world has resulted in a huge increase in the demand for animal protein(which is essentially higher in quality than plant protein). The average protein intake in Nigeria which isabout 19.38/output/ day is low and far below FAO requirement of 65g/ output/day. The nutritionalrequirement is particularly crucial in a developing country such as Nigeria where malnutrition and starvationare the major problems faced by million of rural dwellers .The low protein intake is an indication of shortageof high quality protein food in the diet of Nigerians. The consumption has been estimated to be 1.56267metrictonnes. Tabor (1990). 1
  • 2. Journal of Economics and Sustainable Development www.iiste.orgISSN 2222-1700 (Paper) ISSN 2222-2855 (Online)Vol.2, No.4, 2011Although fish farming started over 40 years ago, aquaculture has not significantly contributed to domesticfish production. Equally estimated was the possible creation of 30000 jobs and generation of revenue ofUS$160 million per annum by the aquaculture industry.Fish has been recognized to contribute 55% to the protein intake in Nigeria. However, local fish productionhas been below consumption with imports accounting for aboutUS$48.8m in 2002 (Central Bank of Nigeria2004).Despite the increase in the major sources of animal protein such as livestock and poultry industries, theproblem of protein deficiency still continues unabated. The protein deficiency in diet is equally associatedwith the inability of fish farming industry to supply the required quantity of fish.The situation causes poor health, low efficiency, low productivity and poor standard of living and decline inthe contribution of fishery industry’s contribution to the Gross Domestic Product (GDP).The industry nowcontributes only2.0% of the GDP and accounts for 0.2% of the total global fish production. Nigeria is one ofthe largest importers of fish with a per capita consumption of 7.52kg and a total consumption of 1.2millionmetric tonnes with imports making up about 2/3 of the total consumption. This indicates the large deficit infish supply in Nigeria Olapade and Oladokun (2005). It is therefore expedient to examine the profitability offish farming in the study area to identify possible areas that require improvement. The development of thefish industry will increase local production of fish and save much of the foreign exchange being used for fishimportation. Specifically, it has a special role of ensuring food security, alleviating poverty and provision ofanimal protein.It is generally accepted that women participate actively in the rural economy due to their social and economicroles. According to Ani (2004), women are the backbone of agriculture labour force producing 40% of thegross domestic product (GDP) and over 50% of food in developing nations. The rural economy in Nigeria isdominated by women through their participation in crop and animal production, marketing as well asprocessing (Adeyokunnu 1981). Women have important roles as producers of food, managers of resourcesand as income earners (Angers et al 1995). Women are the mainstay of small scale agriculture. They supplythe farm labour and are responsible for the family subsistence.The participation of women in aquaculture extends to every aspect of fish farming like preparing fish, feedingthe feed, cleaning of nets/cages and general maintenance and upkeep of the pond or cages (FAO 1985).Homestead fish farming is the most suitable option for women to be involved in, since it does not requirethem to be away from their homes for long periods which might force them to neglect their household ordomestic responsibilities (FAO 1985). It is particularly suitable for women Nigeria where women seclusionis practiced. The home base fishery establishments are usually operated by the family or household members.They are characterized by small-scale operation, low capital investment, simple labour-intensivetechnology.The study will therefore describe the socioeconomic status of female fish farmers, determine the profitabilityof fish farming and examine the determinants of fish output in the study area.2.0 Research MethodologyThis study was conducted in Osun state, Nigeria and made use of primary data. The main instrument forcollecting the primary data was structured questionnaire. Information were collected on input and output infish farming and socio-economic characteristics of fish farmers through personal interview. A total sample of62 female fish farmers were randomly selected from the list of fish farmers with the assistance of extensionagents from Osun State Agricultural Development Programme (OSADEP) for the study. Data analysis wasdone using the descriptive statistics, budgetary technique and multiple regression technique.2.1 Budgetary TechniqueThe budgetary technique which involves the cost and return analysis was used to determine the profitabilityof fish farming in the study area. The model specification is given as:= TR- TC………………………..Equation 1TR= PQ………………………...…. Equation 2. Where= Total Profit (N) 2
  • 3. Journal of Economics and Sustainable Development www.iiste.orgISSN 2222-1700 (Paper) ISSN 2222-2855 (Online)Vol.2, No.4, 2011TR=Total revenue (N)TC= total Cost (N)P= Unit price of output (N)Q= Total quantity of output (N)2.2 The Regression ModelThe multiple regression model was employed to determine the influence of socioeconomic factors on the fishoutput level. The model is specified as followsQ=f(X1, X2, X3, X4, X5, X6, X7, e) ....Equation 3Q is the value of fish output in nairaX1 represents the pond size measured in square metresX2 is the quantity of labour used in fish production in mandaysX3 is the cost of feeds measured in nairaX4 represents the cost of fertilizer in nairaX5 stands for the cost of lime in nairaX6 represents the cost of fixed inputs in nairaX7 is the cost of fingerlings measured in nairae= Error termFollowing Olayemi (1998) the relationship between the endogenous variable and each of the exogenousvariables were examined using linear, exponential, logarithm and quadratic functional forms. Based on thevalue of the coefficient of determination (R2), statistical significance and economic theory that support fishproduction, the lead was chosen.3.0 Results and Discussion3.1 Descriptive AnalysisEvidence from the descriptive analysis of socio-economic characteristics of respondents in the study area inTable 1 shows that the fish farmers whose ages fall between 31 – 40 years constituted the majority.On the whole, 80.0% fall into the economically active group of 20 – 50 years. The result of the marital statusshows that majority 67.7% of the fish farmers were married. It is also evident that most of the respondents(66.1%) were part time fish farmers. A large proportion (54.8%) of them fish farmer had no formal training.A large proportion (77.5%) finances their fish production through personal savings. The result comparesfavourably with Aromolaran (2000) .The distribution of the household size indicates that the household sizeranged from 2 to 13 while the average fish pond size was found to be 355m2. The study also revealed poorextension visits to fish farmers who mostly operated on part-time basis. Also 74 (90.3%) of them obtainedtheir fingerlings from farm gate while 84.2% purchased the feeds and 10.5% used household wastes. Thedescriptive analysis also indicates that most fish farmers (56.5%) feed their fish twice daily to achieve highyield. The most common breeds of fingerlings utilized by fish farmers were Claris, Heteroclarias and Tilapia.3.3 Profitability AnalysisThe study examines the profitability of fish production in the study area. To determine the profit level,attempts were made to estimate the cost and return from fish farming. The input used, cost, yield or outputdata generated from the farmers were used to undertake the cost and return analysis for assessing theprofitability of fish production in the study area.The cost and return analysis is presented in the table 2. The result reveals that the cost of feeds accounted forthe largest proportion (17.7%) of the total cost of fish production. This is followed by cost of fingerlings(12.4%).The lime cost and labour cost accounted for 3.2% and 3.9% of the total cost respectively. Thisclearly shows that large amount of money is spent by fish farmers in the study area for the purchase of 3
  • 4. Journal of Economics and Sustainable Development www.iiste.orgISSN 2222-1700 (Paper) ISSN 2222-2855 (Online)Vol.2, No.4, 2011fingerlings and feeds. The fixed cost of production consists of cost of fixed assets such as pump, vehicles,aerators and pond which accounted for 56.5% of total production cost. Consistent with the findings ofAshaolu et al. (2005) from their studies on profitability on fish farming, the rate of return per capital invested(RORCI) is the ratio of profit to total cost of production .It indicates what is earned by the business by capitaloutlay Awotide and Adejobi (2007). The result revealed that the RORCI of 83% is greater than the prevailingbank lending rate, 17% implying that fish farming in the study area is profitable. If a farmer takes loan fromthe bank to finance fish farming, he will be 58k better off on every one naira spent after paying back the loanat the prevailing interest rate.3.4 Multiple Regression ResultThe regression analysis was carried out to examine the determinants of factors effecting fish output in thestudy area. Based on the econometric and statistical criterion, the double logarithm was chosen as the leadequation and the results as presented in the table 3. The multiple regression result revealed that fish output issignificantly determined by pond size, labour used, cost of feeds, cost of lime and cost of fingerlings. Thecoefficients are in line with the a priori expectation. Hence, the more the amount expended on labour, limeand feeds, the more the amount that will be realized from fish farms in the study area. The result is consistentwith the finding of Emokaro and Ekunwe (2009). The result equally suggests the need for fish farmers topurchase more of these inputs to increase their revenue from fish production. Similarly, policies that willensure availability of these inputs to fish farmers at affordable price should be put in place. The positiverelationship between value of fish and pond size indicates that with increase in the size not surprising becauseall things being equal theEqually evident from the result an average total cost of N371486.35 was incurred per annum by therespondents while gross revenue of N 791242.52 was realized thereby returning gross margin of N574, 314and a profit of N419756.17. The rate of return on investment of 0.58 implies that for every one naira investedin fish production by farmers, a return of N1.58 and a profit of 58k were obtained. The implication of this isthat there is a considerable level of profitability in fish farming in the study findings area. This result isquantity of fish produced is directly proportional to the pond size.The coefficient of determination, R2 values of 0.52 indicates that 52% of the variation in the value of fishoutput is explained by pond size, quantity of labour used, cost of feed, cost of lime and cost of fingerlings.Also, 48% of the variation in the value of fish is determined by other factors not considered. Table 4 showsthat the regression coefficient, standard error, F ratio and the level at which the ratio was significant for eachof the independent variables. The performance of the analysis of variance in table 4 shows that F ratio of9.110 was significant at 0.01 alpha level. This provided the evidence that a combination of pond size, cost oflabour, cost of feeds, lime, fertilizer, fixed inputs and cost of fingerlings had joint impact on the fish output inthe study area. The beta weight ranged from 0.056 to 0.316. The result implies that out of seven independentvariables considered, fingerling is the most important input. It has the highest value of 0.316. This is followedby the quantity of lime while fertilizer is the least. This is not surprising because irrespective of the efforts andmanagement practices, the output from a fish farm will be determined by the quantity and quality offingerlings used.3.5 Elasticity of Production and Return to ScaleThe magnitude of elasticity of production is one of the economic concepts of measuring efficiency inresource-use Oladeebo, Ambe-Lamidi (2007). The total sum of elasticity of production of the significantvariables, 0.787 as shown in table 5 was less than unity. This suggests that fish production in the study areahad a decreasing return. The implication is that each additional unit of the inputs will results in a smallincrease in the value of fish output than the preceding unit. This shows that production occurred among fishfarmers in the study in stage 2, a rational stage of production. In stage 2, the sum of elasticity of production isgreater than zero but less than one. The implication is that the more the inputs used, the higher will be thevalue of fish even though at a decreasing rate. This finding is consistent with that of Olagunju et al. (2007) intheir study on economic viability of cat fish production in Oyo state, Nigeria. The degree of responsiveness ofthe value of fish output to changes in the independent variables shows that a percent increase in the values ofpond size, labour, feeds, fertilizer, lime, fixed input and fingerlings will lead to 20.1%, 26.3%, 27.6%, 4
  • 5. Journal of Economics and Sustainable Development www.iiste.orgISSN 2222-1700 (Paper) ISSN 2222-2855 (Online)Vol.2, No.4, 20112.7%, 6% , 14.1% and 0.1% change in the value of fish produced respectively. With the production result,increase in the utilization of labour and feeds is likely to boost the fish output substantially.4. Conclusion and RecommendationsIt was shown in this study area that fish production among women is economically rewarding and profitable.It is capable of creating employment, augmenting income and improving the standard of living of the women.The result also shows that the positive decreasing return to scale as evidence by the return to scale estimate,indicating that fish production in the study is still in stage 2 of the production process. This suggests theexistence of intervention points by relevant stakeholders in the current production technology of fish amongwomen farmers in the study area.To ensure sustainability in homestead fish production and provide substantial income for women, there maybe the need to develop an extension system is gender specific and tailored towards women. This can beachieved if the level of women’s involvement in homestead fish production in Nigeria is determined and inaddition, if the constraints they face and their training needs are identified. If the identified needs of womeninvolved in homestead fish production are used in the design of the training content, then the trainingbecomes more effective in enhancing the skills and competence of women.ReferencesAdeyokunnu T. O. (1981). Women in Agriculture in Nigeria. ST/ECA/ARCN/81/11: Economic Commissionfor Africa, Addis Ababa, Ethiopia.Agnes R., Lynn R., Christine P. (2005). Women: The key to food security, food policy report. Theinternational food policy research institute, Washington, D.C. pp1-14.Ani A. O. (2004). Women in Agricultural and Rural Development. Priscaquilla Publishers, Maiduguri,Nigeria.Awotide D.O., Adejobi AO (2007). Technical efficiency and cost of production among plantain farmers inOyo State Nigeria, Moor Journal of Agricultural Science, 7(2), 107-113.Aromolaran A.B. (2000). Analyzing Resources use Efficiency on fish farms: A case Study of Abeokuta zoneOgun-State, Nigeria. Aquafield, 1(1), 12-21.Ashaolu O.F., Akinyemi, A.A., Nzekwe LSO (2006). Economic Viability of homestead Fish Production inAbeokuta Metropolis of Ogun State, Nigeria. Asset Series A, 6(2), 209-220. Central Bank of Nigeria 2004.Statistical Bulletin, 264- 267.Emokaro C. O., Ekunwe P.A. (2009). Efficiency of resource-use and elasticity of production among catfishfarmers in Kaduna, Nigeria. African Journal of Bio-technology 8(2), pp 7249-7252Food and Agricultural Organization (1985). A Review Study of the Sungai Merbok flooting Cago cultureproject. Project Code TCP/MAI./403 Technical Report 2, Rome.Oladeebo J.O., Ambe-Lamidi A. l. (2007). Profitability, input elasticities and economic efficiency of poultryproduction among youth farmers in Osun state, Nigeria. International Journal Poultry Science. 6(12), 994–998.Olagunju F.I., Adesinyan I.O., Ezekiel A.A. (2007). Economic viability of catfish production in Oyo state.Journal of Human Ecology, 21(2): 121-124. Olapade A.O., Adeokun O.A. 2005. Fisheries ExtensionServices in Ogun State. Africa Journal of Livestock Extension, 3, 78-81.Olayemi J.K. (1998). Elements of Applied Econometrics. A Publication of the Department of AgriculturalEconomics, Ibadan, Nigeria: University of Ibadan. 5
  • 6. Journal of Economics and Sustainable Development www.iiste.orgISSN 2222-1700 (Paper) ISSN 2222-2855 (Online)Vol.2, No.4, 2011Tabor J.G. (1990). The Fishing Industry in Nigeria: Status and Potential for Self-sufficiency in Production.National Institute of Oceanography and Marine Research Technical Paper 22, 1-8.Table 1. The capitals, assets and revenue in listed banks Socio-economic characteristics Categories Frequency Percentage (%) Education Primary 2 3.2 Secondary 49 79.1 Tertiary 11 17.7 Total 62 100.0 Age 10 – 20 2 3.2 21 – 30 19 30.0 31 – 40 31 50.0 41 – 50 7 12.0 >50 3 4.8 Total 62 100. 0 Marital Status Married 42 67.7 Widow 11 18.8 Single 09 14.5 Total 62 100.0 Household Size 1 – 4person 25 40.3 5–8 21 33.9 >8 3 4.8 No response 13 21.0 Total 62 100.0 Farming Experience <5 years 24 38.8 (Years) 5 – 10years 32 51.6 11 – 15years 3 4.8 >15years 3 4.8 Total 62 100.0 Times of Feeding 1 time 7 11.3 2 times 35 56.5 3 times 16 25.8 4 times 2 3.2 5 times 2 3.2 Total 62 100.0 Contact with Extension 0 time 49 79.0 Workers 1 time 5 8.1 2 times 5 8.1 3 times 2 3.2 5 times 1 1.6 Total 62 100.0 Training in Fish Farming Formal training 28 45.2 No formal training 34 54.8 6
  • 7. Journal of Economics and Sustainable Development www.iiste.orgISSN 2222-1700 (Paper) ISSN 2222-2855 (Online)Vol.2, No.4, 2011 Item (Annual) Amount (#) % of total cost Fertilizer 23560.21 6.34 Feeds 10541.34 17.7 Feeds Lime 1374.22 3.2 Fingerlinks 53452.03 12.4 Labour 15529.11 3.9 Total variable cost 14742.44 Fixed inputs 252287 Total cost 371486.35 Total returns 791242.52 Profit 419756.17 ROI 0.58 ROIC 0.83 Total 62 100.0 Mode of Farming Part time 41 66.1 Full time 21 33.9 Total 62 100.0 Main Source of Finance Personal Savings 48 77.5 Friends 1 1.6 Relatives 2 3.2 Cooperatives 9 14.5 Bank loans 2 3.2 Total 62 100.0Source: Computed from Field survey data 2009Table 2: Average cost and return of fish productionSource: Computed from Field survey data 2009 7
  • 8. Journal of Economics and Sustainable Development www.iiste.orgISSN 2222-1700 (Paper) ISSN 2222-2855 (Online)Vol.2, No.4, 2011 Table 3: The regression results of the determinants of fish outputs in the study area Variable Coefficient Beta T Significant Constant 7.328 - 4.882 .000* Pond size 0.201 .204 2.234 .029** Labour 0.263 .174 1.934 0.57 Feed 0.276 .263 2.888 0.005* Fertilizer 0.027 .056 0.625 0.534 Lime 0.006 0.248 2.780 0.007* Fixed input 0.141 0.163 1.783 0.79 Fingerling 1.471E-05 0.316 3.33 0.001*R2 = 0.52; F stat = 9.110*variable significant @1% ** Variable significant @5%Source: Computed from Field survey data 2009.Table 4: Analysis of variance.Source of Variation Sum of Square Df Mean Square F-ratio Sig.Due to regression 40.260 7 5.866 9.110 0.01Due to Residual 49.637 74 0.646Total 89.897 81Source: Computed from field survey data 2009.*Significant 1%Table 5: Elasticity of production and return to scale of fish farmersIndependent Variables Elasticities of ProductionPond size* 0.201Labour* 0.263Feed* 0.276Fertilizer 0.027Lime* 0.060Fixed input 0.141Fingerlings* 1.471E-05Source: Computed from field survey data 2009.*Significant Variable@5% 8
  • 9. Journal of Economics and Sustainable Development www.iiste.orgISSN 2222-1700 (Paper) ISSN 2222-2855 (Online)Vol.2, No.4, 2011 Interaction between Real And Financial Sectors In Nigeria: A Causality Test Adaramola, Anthony Olugbenga Banking and Finance Department, Faculty of Management Sciences, University of Ado Ekiti, Nigeria. E-mail: gbengaadaramolaunad@yahoo.com Owoeye Taiwo Economics Department, Faculty of Social Sciences, University of Ado Ekiti, Nigeria. E-mail: owoeyetaye@yahoo.co.ukThe research is financed by Asian Development Bank. No. 2006-A171AbstractThis study investigates the interrelationship between industrial productivity and money supply asproxies for the real and financial sectors by testing for causality under a Vector Auto-Regression (VAR)structure. In the study, it was revealed that Nigeria over the 35-year period between 1970 and 2005like many other LDC’s has a unidirectional causality running from the financial sector to the realsector growth. This indicates that the country still operates in the short-run and to take advantage oflong-run changes, such variables as technology and factor productivity should to be taken intocognizance.Keywords: Industrial Productivity; Money Supply; Vector Auto-Regression; Causality.1.1 IntroductionNigeria like every other economy in the world seeks to maximise her macro-economic objectives byintroducing appropriate policies to channel her economy in the path of growth and stability. Prominentamong the issues of concern are industrialisation and the bid to tackle inflation and hence the controlof money supply. The industrial sector has always been recognized as the main sector to speed up therate of development such that in Rostow’s (1960) theory of economic development, also known as thestage theory. He recognised the industrial sector as the leading sector to economic development pathcalling it the “core sector”, to lead the economy to development in the “take-off” stage while citingBritain’s leading sector in her take-off period as the cotton textile industry. Thus, the state ofindustrialisation or development consist of having accumulated established efficient and economicmechanism for maintaining and increasing large stock of capital per head in the various firms,similarly, the condition of underdevelopment is characterised by possession of relatively small stack ofvarious kinds of capital (Chete, 1995). Monetary authorities on another hand seek to control theamount of money in circulation and, hence, money supply, since it is exogenously determined, it isgenerally accepted in the quantity theory of money that if there is an increase in money supply, theprice level would raise, if however some resources were idle the output could increase, as classifiedinto three categories: factors that give rise to productivity of existing factors; an increase in theavailable stock of factors of productivity; and technological change. In recent years, Nigeria like otherless-developed nations has been experiencing substantial slack in the use of her productive potentialsuch that output/growth had remained disquietingly low. In order to redress this undesirable state ofaffairs, Nigeria has been and particularly under the Structural Adjustment Programme (SAP), using 9
  • 10. Journal of Economics and Sustainable Development www.iiste.orgISSN 2222-1700 (Paper) ISSN 2222-2855 (Online)Vol.2, No.4, 2011and emphasising monetary policy, this is in line with the financial literature made popular byMackinnon (1973) and Shaw (1973), which suggest that financial liberalisation is what is needed torelease the finance necessary to promote growth. Unfortunately, the proceeding economic problempersists and even in some cases seemingly worsened. In the light of this development, publicconfidence in the ability of government to manage the economy has waned and belief in the likelihoodof continuing economic growth weakened. In effect, questions are being raised as to the effectivenessof monetary policies adopted by government over these years. The need however arises to understandthe direction of the relationship between finance and growth as was highlighted by Patrick (1960)when he posed the question, “Is it financial sector or the real sector that leads to other?”Thederegulation of the financial sector under the SAP which gave way to liberal interest rates andlicensing of banks together with the recent recapitalisation process which left in its trail the emergenceof 25 mega banks and other non-bank financial institutions show a belief in the “supply leadinghypothesis”. Reversal of deregulation in January 1994 with return to what the government called“managed deregulation”, that is, administratively determined interest rate and a halt to liberal banklicensing could suggest a weakening in earlier belief. Could that reflect a belief in the “demandfollowing hypothesis”? This study intends to use data for Nigerian economy to establish the directionof relationship between industrial productivity and money supply in Nigeria and verify previousstudies from other countries.This paper is concerned with investigating the interrelationship betweenindustrial productivity and money supply using Nigerian data and it is organised in this sequence.What follows this introductory section is the literature review, section three reviews industrialproductivity and money supply in Nigeria. Section four discusses the estimation techniques and modelspecification while section five discusses the result of data analysis and section six concludes.2.1 Literature ReviewIn a bid to raise the standard of living and quality of life of her people, the primary focus of economicmanagement, particularly in developing countries, becomes effective economics developmenttransformation. According to Todaro (1971), “raising people’s living levels so much so that theirincomes and consumption levels of food, medical services, education, utilities and social servicesexpand through relevant economic growth process is the focus of economic management.” In otherwords, therefore, to expedite the pace of the process of this attainment, He proposes the need forgovernment to provide for the prevalence of some socio-economic transformation conditions whichinvolve “increasing people’s freedom to choose by enlarging the range of their choice variables, forexample, increasing the varieties of consumer goods and services of reasonable costs.” This viewpresupposes increased industrial productivity which is generally accepted by economic planners,researchers, policy makers irrespective of their desirable means of raising the standard of living of thepopulace. In a supportive mood, Lewis (1967) opined that “in any economy one or more sectors serveas a prime mover, driving the rest of the economy forward. This role of “engine of growth” or leadingsector has usually been played by the industrial sector under the industrialization process”. Thoughsmall in relative sizes as compared to GDP, especially in developing countries, nonetheless, theindustrial sector is seen as potential leading sector with latent resources and expansions that could pullu the rest of the economy through backward and forward linkages. Therefore, it is considered as aleading paradigm grossly because of its dynamism in technological transmission and organisationalstimuli. However, the economic regulatory approach under which industrialisation strategies wereadopted in Nigeria up to the mid-1980s did not yield any remarkable result the near total collapse ofthe global crude oil prices in the early 1980’s and the subsequent economic crisis that followed itcoupled with some internal factors such as economic mismanagement of natural resources, resulted inaccumulation of huge external and internal debts, chronic budget deficits with the attendantinflationary pressures and resources economic declines in all its ramifications as well as highunemployment rates. These created some transformation challenges which prompted Nigeria to adoptthe World Bank/IMF endorsed Structural Adjustment Programme (SAP) in July 1986, in order toamong several objectives: achieve fiscal and balance of payment viability; evolve a private sector-led 10
  • 11. Journal of Economics and Sustainable Development www.iiste.orgISSN 2222-1700 (Paper) ISSN 2222-2855 (Online)Vol.2, No.4, 2011economic development process; lessen the dominance of unproductive investments; and restructureand diversify the productive base of the economy (Philips, 1987). Towards these ends, there was areversal of Nigeria development approach from economic regulation to economic deregulation andliberalisation-relying on market forces to allocate available resources. Within this new paradigm aresuch policies as: adoption of appropriate pricing policies for products; adoption of measure tostimulate production and broaden the supply base of the economy; deregulation and greater relianceon market forces; rationalisation and privatisation of public enterprises; strengthening of existingdemand management policies; trade and payment mobilization; tariff reform and rationalisation topromote industrial diversification (Philips, 1987). According to Ajakaiye and Ayodele (2001), in spiteof these elaborate strategies which would have favoured effective industrialisation process in aneconomically conducive environment, most of the results were socio-economically undesirable. Thisis not unconnected with some SAP associated development problems such as chronic budget deficit,huge external debt burden and serious economic decline.” Against the background of thisdisappointment, Nigeria’s Vision 2010 Report (1998) aims at creating a stable macroeconomicenvironment that will provide a conducive atmosphere for dynamic, long-term self-sustaining growthand development within the sustainable economic development paradigm as proposed in the 1980Lagos Plan of Action. Towards this and economic planning and policy instruments seem to becurrently directed at the development of the key productive sectors of the economy such as agriculture,industry and particularly manufacturing and commerce for the promotion of the pace ofindustrialisation in Nigeria. In this regard, there is an urgent need for policy instruments to be properlyfocused on energising the past executed industrial transformation process in the country.3.1 Nigeria in PerspectiveBefore the discovery of crude oil in commercial quantity in Nigeria, the country was grosslydependent on the proceeds of agricultural (primary) products for foreign exchange. However, atindependence, the government saw need for import-substitution and thus reduce the level of relianceon the external sector for the supplies of manufactured products and equipment. In essence, throughthe lure of incentives foreign investors were technically and strategically invited to championNigeria’s industrialisation because of the scarcity of investible funds in the country. The incentivesadopted by the government were broadly classified into five (5) groups which are: effective protectionwith import tariff; export-promotion of products produced in Nigeria; fiscal measures of taxation andinterest rates to make for cheap production costs; foreign currency facility for international trade; andthe evolution of development banks for resource mobilization. However, by 72/73, oil price had aconsistent increase from $2pb to close at $40pb and crude oil production to 2.5mpd in 1980 signifyingan increase of about $76million per day in the nation’s capacity to spend, which of course, gave rise tothe declining emphasises on agricultural sector and thus, the reduction in her contribution to total GDPfrom 65% in 1960s to 20% in the late 1970s.In the early 1970s, the manufacturing sector had depended mainly on the external sector for foreignexchange to purchase equipment, spare parts and intermediate input and there was phenomenaincrease in the performance of the sector in the mid-1970s and 1980s occasioned principally by themassive inflow of foreign exchange from crude oil sales. However, the near total collapse of theeconomy’s driving force (crude oil prices) which started in 1981 reversed the phenomena increase inthe performance of the manufacturing sector in Nigeria. As from 1975, the sector witnessed apersistent decline due to discovery and subsequent reliance on crude oil. For example, themanufacturing sector grew at 4.8percent in 1960s, this rose to 7.2percent in 1970s but declined in1975 and 1980 to 5.6 and 5.4percent respectively and further rose again in 1985 at about 10.5% beforeit entered into a period of steady decline (Ajakaiye and Ayodele, 2001). The decline in thisperformance can rightly according to them be attributed to three major factors, which are: a weakdemand due to the sharp fall in real income arising from the economic recession and high productprices; low export market production due to poor quality control and the high cost of production due 11
  • 12. Journal of Economics and Sustainable Development www.iiste.orgISSN 2222-1700 (Paper) ISSN 2222-2855 (Online)Vol.2, No.4, 2011to the high cost of imported inputs; and the sector’s dependence on the external sector for the supplyof inputs. In recent years, manufacturing as a percentage of GDP has declined to as low as 2% (CBN,2005).4.1 Method of AnalysisThis study employs the econometric technique of Co-integration and Vector Auto Regression (VAR)which most analysts have found to be very adequate for handling economic data especially for lessdeveloped countries LDC’s like Nigeria. Core to the values of this analysis is the examination of thevariables in the econometric model for stationarity. Basically, the idea is to ascertain the order ofintegration of the variables and the number of time the variables have to be differentiated to arrive atstationarity. This enables us to avoid the problems of spuriousity on inconsistent regression that areassociated with non-stationary time series models; particularly, ordinary least square (OLS) (Engel andYoo, 1987). The traditional econometric method only assumes stationary data around a deterministictrend by including a time trend in the regression equation. It is however known that many economicvariables have tendencies to trend through time, so that the level of these variables can becharacterised as non-stationary. The independent variable cannot act significantly on the dependentvariables individually but collectively, the relationship between the dependent and independentvariables acting collectively may be insignificant. This problem is generated due to the fact that thedata has not been tested to confirm its satisfaction of the condition for OLS lists and needs to beresolved. The mean variance computed from variable that have series that are stationary will beunbiased estimates of the unknown population mean and variance (Eguwaikhide, 1999). However,economic variables that are non-stationary series in a regression equation would generate estimatesthat are biased.4.2 Causality (VAR)Since the objective of the study includes examining the direction of relation between industrialproductivity index (Indpx) and money supply (Ms). The co-integration says nothing about thedirection of the causal relationship between the two variables are co-integrated, it follows that theremust be causality in at least one direction. In this study, VAR causality test was employed to examinethe causal linkage between industrial productivity and money supply.Granger (1969) test regresses a variable Y. If X is significant; it means that it explains some of thevariance of Y that is not explained by lagged values of Y itself. This indicates that X is causally priorto Y and is said to dynamically cause or Granger cause Y cases of unilateral, bilateral and independentcausalities are explained in chapter one of this work and therefore are not repeated in this chapter.However, when two variables are both co-integrated, the joint process as indicated in Engel andGranger (1987) and restated by Keke, Olomola and Saibu (2005) can be written in the error-correctionmechanism from given by:  t Yt  bt ECM t 1  i 1 b2 AYt 1  i 1 b3 X t 1   1t n n ... 4.1 t X t  dt ECM t 1  i 1 d2 AYt 1  i 1 d3X t 1   2t n n ... 4.2Equation (4.1) and (4.2) were used for testing the causality between the variables of interest. The ECMterm shows the size of error in the preceding term. Keke et al (2003) has cautioned against theexclusion of the ECM term from equation 4.1 and 4.2. He opined that if the ECM term is neglected, animportant error is induced in the empirical analysis and the F-test are no longer valid (Keke et al,2003). 12
  • 13. Journal of Economics and Sustainable Development www.iiste.orgISSN 2222-1700 (Paper) ISSN 2222-2855 (Online)Vol.2, No.4, 20114.3 Model SpecificationThis paper uses Granger causality model in which two variables, Ms and Indpx are taken to representmoney supply and industrial productivity index respectively.Let At; t=1,2,3,… be the set of given information including at least (Mst, Indpxt) the bi-variate processof interest. Also, let At=(As:s<t). Mst and Indpxt are defined similarly, for example, Mst represents allpast values of Mst and Indpxt represents all past values of Indpxt.Granger’s definition of causal relationship between Ms and Indpx are as follow:  1. Ms causes Indpx if  2  Indpx    2  Ms    ... i  A  A  Ms  Where ___ (Indpx/Z) represents the minimum prediction error variance of Indpx, given an information period Z, a reduction in the minimum prediction error variance when past values of Ms are included in the information set on which the prediction of Indpx is conditioned, signifies Ms causes Indpx.2. Similarly, for Indpx causes Ms we have:    2  Ms    2  Ms    ... ii  A  A  Indpx  Bi-directional causality (feedback) occurs when Indpx causes Ms and Ms causes Indpx. That is:3.  2  Ms    2  Ms  Indpx  and  2  Indpx    2  Ms  Ms          ... iii  A  A   A  A  Ms and Indpx are independent of one another, if neither causes the other, that is inclusion of values of past data set does not reduce the minimum prediction error variance of the other; thus:4. 2  Indpx    2  Indpx  Ms  and  2  Ms    2  Ms  Indpx          ... iv  A  A   A  A  In addition, on undergoing the unit root test for stationary, A=(Indpx, Ms) and Indpx and Ms are taken as a pair of linear covariance stationary time series, thus, the Granger causality between industrial productivity (Indpx) and money supply (Ms) can be modeled as follows:  t Indpxt  bt ECM t 1  i 1 b2 Indpxt 1  i 1 b3 Mst 1   1t n n ... v  t Mst  d t ECM t 1  i 1 d 2 Indpxt 1  i 1 d 3 Mst 1   2t n n ... vi Where  1t and  2t are serially uncorrelated with zero mean and finite covariance matrix. The decision rule for i, ii , iii and iv will be the test of the null hypothesis that the estimates coefficients are equal to zero at an appropriate level of significance; thus: A. Ms causes Indpx if HO2:b3=0, i=1,2,3, … n is rejected B. Indpx causes Ms if HO1:d2=0, i=1,2,3, … n is rejected C. Ms and Indpx are dependent if a and b above holds D. Ms and Indpx are independent if both a and b are not rejected 13
  • 14. Journal of Economics and Sustainable Development www.iiste.orgISSN 2222-1700 (Paper) ISSN 2222-2855 (Online)Vol.2, No.4, 20115.1 Presentation and Analysis of ResultBeing a time series data with the usual flow of spurious result, any successful research on such mustcommence on the test for stationarity on the data. On the recommendation of Hamilton (1994) andHayashi (2000) a stated in Dauda (2005), it was accepted to investigate carefully the nature of anyprobable non-stationarity, testing each series individually for unit root and then testing for possibleco-integration among the series, thus, analysis of causality using the typical VAR model is precededby the unit root and co-integration test.5.2 Unit Root TestTo avoid spurious rejection or acceptance of no causality in the results, it was necessary to confirmstationarity of the variables of interest as investigated using the ADF (Augumented Dickey-Fuller)tests. The result is presented in table 1.Table 1: Unit Root Test (ADF) Variables (With intercept only) Lag length Order of integration Levels 1st difference 2nd differenceIndpx -1.58527 -3.188599 -4.076669 2 I (0)Ms 1.043672 0.936757 -2.208719 2 I (0) (with intercept and trend) Level 1st difference 2nd differenceIndpx -2.890306 -4.337425 -7.545803 1 I (1)Ms 1.834180 -0.962222 -4.851390 1 I (0)Using intercept only, Indpx was stationary at 5% critical level on the first and second difference whileMs was not stationary at either levels or first and second differencing. However, since the two serieswere trended, the analysis of ADF using intercept and trend showed Indpx to be stationary at 5%critical levels on the first and second differencing while Ms was stationary only after the seconddifference at 5% critical values. Since the stationary of the variables had been confirmed, a simpleco-integration test was conducted using the Johansen’s technique (Johansen and Juselius, 1990). Asstated in Dauda (2006), Hamilton (1994) and Hayashi (2000), argues that testing and analysingco-integration in a VAR model is superior to the Engle-Granger simple equation.5.2 Johansen’s Co-integration TestTable 2: Series: Indpx, Ms 14
  • 15. Journal of Economics and Sustainable Development www.iiste.orgISSN 2222-1700 (Paper) ISSN 2222-2855 (Online)Vol.2, No.4, 2011Lags interval: 1-4 Eigen values Likelihood ratio 5% critical value 1% critical value Hypothesised N0 of CE(S) 0.637625 39.75192 25.32 30.45 None** .234513 8.284543 12.25 16.26 At most 1(**) denote projection of the hypothesis at 5% (1%) significant level. L.R. test indicates oneco-integration equation at 5% significant level.The co-integration test indicates one co-integrating equation at 1-4 lags suggesting the existence oflong-run relationship between money supply and industrial productivity. The choice of appropriate laglength for the VAR model plays a critical role in determining causality, thus, using the Akaikeinformation criterion (AIC), and Schwarz information criterion (SIC) the optimal lag length of ten (10)lags was chosen. The Granger causality equation was estimated using ordinary least square techniquewithin a VAR structure in E-views version 3.1. The results are presented below:Table 3: Result of causality running from Ms to Indpx Included observation: 26 after adjusting end points Independent variable Coefficients Standard error t-statistics Indpx (1-) 0.218732 0.3335 0.65617 Indpx (2-) 0.005200 0.30634 -0.01698 Indpx (3-) -0.344753 0.32503 -1.06068 Indpx (4-) -0.649665 0.35033 -1.85444 Indpx (5-) -0.026547 0.38127 -0.6963 Indpx (6-) 0.368365 0.37550 0.98101 Indpx (7-) -0.382565 0.36096 -1.05985 Indpx (8-) -0.161459 0.35693 -0.45236 Indpx (9-) -0.205445 0.45196 -0.45456 15
  • 16. Journal of Economics and Sustainable Development www.iiste.orgISSN 2222-1700 (Paper) ISSN 2222-2855 (Online)Vol.2, No.4, 2011 Indpx (10-) 0.851862 0.45196 1.93761 Ms (-1) 0.016109 0.00622 2.58896 Ms (-2) -0.27721 0.01073 -2.58420 Ms (-3) 0.008779 0.00344 2.54999 Ms (-4) -0.004961 0.00196 -2.52958 Ms (-5) 0.014646 0.00569 2.57503 Ms (-6) -0.005964 0.00234 -2.54490 Ms (-7) -0.001112 0.00129 -0.86317 Ms (-8) -0.000655 0.00114 -0.57609 Ms (-9) -0.001100 0.00143 -0.77113 Ms (-10) 0.001491 0.00100 1.49354 ECM (-1) -0.015817 0.00612 -2.58494 R2=0.928065; R2=0.640323; F-statistic=3.925340From analysing the Indpx regression, we discovered that only the first to sixth lags of Ms weresignificant judging by their respective standard error which was less than half of the coefficient oftheir respective cases. Also, of the six significant lagged values, 3 conformed to the aprioriexpectations of a positive relationship while the second fourth and sixth lag period yielded a negativerelationship which means an adverse effect of money supply on industrial productivity. The R2 was93% and the adjusted R2 was 64% which shows that 93% of the variations in Indpx are explained bythe variables in the model. Correspondingly, the F-statistic that checks the significance of the R2 wassignificant at 5% level of significance. The negative sign in the ECM shows that it was currentlysigned though not prompting adequate feedback from long-run trend as indicated by its low value(2%).Table 4: Result of causality Indpx to Ms Included observation: 26 after adjusting end points Independent variable Coefficients t-statistics 16
  • 17. Journal of Economics and Sustainable Development www.iiste.orgISSN 2222-1700 (Paper) ISSN 2222-2855 (Online)Vol.2, No.4, 2011 Indpx (1-) 493.1702 0.90022 Indpx (2-) 740.9661 1.47178 Indpx (3-) 520.6822 0.97476 Indpx (4-) -431.9268 -0.75020 Indpx (5-) -404.7310 -0.64592 Indpx (6-) 998.6761 1.61832 Indpx (7-) 329.5950 0.55560 Indpx (8-) -172.7511 -0.29450 Indpx (9-) -966.4992 -1.30120 Indpx (10-) 238.5283 0.392411 Ms (-1) -15.37683 -1.50377 Ms (-2) 28.22666 1.60112 Ms (-3) -7.911610 -1.39831 Ms (-4) 3.058081 0.94873 Ms (-5) -16.46770 -1.76180 Ms (-6) 11.6360 3.02156 Ms (-7) 1.036140 0.48953 Ms (-8) -1.345473 -0.72060 Ms (-9) -3.929832 -1.67652 Ms (-10) 4.116349 2.50843 ECM (-1) 15.92098 1.58325 R2=0.999905; R2=0.999523; F-statistic=2622.320In the money supply regression result presented in table 4, however, we see that none of the lagged 17
  • 18. Journal of Economics and Sustainable Development www.iiste.orgISSN 2222-1700 (Paper) ISSN 2222-2855 (Online)Vol.2, No.4, 2011values of Indpx was significant judging by the standard error test. Though, some of the lagged valuesconform to apriori expectation, their statistical insignificance condemn their relevance in this analysis.The R2 and adjusted R2 surprisingly show a 100% relevance of the variables in the model inexplaining changes in money supply. The large F-statistic (2622.326) also reveals the significance ofthe R2 while the positively signed ECM shows that correction of past disequilibria is not possible inthe model. The gross insignificance in the individual parameter estimates and high significance of theF-statistic is consistent with the submission of Gujarati who says “with several lags of the samevariable, each estimated coefficient will not be statistically significant, possibly because ofmulti-collinearity. But collectively, they may be significant on the basis of standard F-test (Gujarati,2004:850).6.1 Summary and Concluding RemarksThe study has examined the degree of inter-relationship and independence between industrialproductivity and money supply in Nigeria. The empirical analysis has led to the discovery that theNigerian economy shows a uni-directional causality that runs from money supply to industrialproductivity. This conforms to the quantity theory of money that an increase in money supply either bymobilizing savings, increase in government expenditure or through foreign private investment (FPI),causes an increase in price level which also lead to an increase in output if there are some idleresources.It also affirms the postulation of Mackinnon (1973) and Shaw (1975) which suggest that financialliberalisation is what is needed to release the finance necessary for growth. Expressed in another way,Porter (1966) agrees that development and expansion of the financial sector precede the demand for itsservices. This evidence is consistent with the conclusion of Aigbokhan (1995) who states a causalityrunning from financial to real sector growth (demand following hypothesis). The importance ofmanaging money supply, that is, inflation control is however shown in section five where two of thesix significant lags of money supply yielded a negative result, indicating a disincentive to industrialproductivity caused by adverse inflationary spirals. This is adequately explained by the nearhyper-inflationary trends recorded in the country between the late 70s and the late 90s which arosefrom the oil boom, more recently termed “oil money”. Question however arises on the inability of theindustrial sector to yield adequate feedback by simultaneously increasing money supply and thuscreating a circle of perpetual growth in both the financial and real sectors. This slack in industrialproductivity is seen to be caused by a myriad of factors ranging from the inflationary spiral indicatedby the near zero contribution of money supply to industrial productivity as shown in table 3. Themarket attitude towards home-made goods and the rampant corruption in the system which hashampered the results of the policies which would have brought desired results.ReferencesAigbokhan, B. E. (1995). Financial development and economic growth: a test of hypothesis on supply leading and demand following finance, with evidence in Nigeria. In Nigerian Economic and Financial Review. 1(2) 49-75.Ajakaiye, D. O. and Ayodele, A. D. (2005). Industrial transformation efforts in Nigeria: some reflections. Ibadan: NISER occasional paper. 1.Chete, L. N. (1995). The dynamics of productivity performance in Nigerian manufacturing. In Nigerian Economic and Financial Review. 1(2) 43-58.Dauda, O. Y. (2006). Dollarisation and exchange rate volatility in Nigeria: exploring causal relationships. In Journal for Economics and Social Studies. 5,1596—4256. 18
  • 19. Journal of Economics and Sustainable Development www.iiste.orgISSN 2222-1700 (Paper) ISSN 2222-2855 (Online)Vol.2, No.4, 2011Egwaikhide, F. O. (1999). Import substitution industrialisation in Nigeria. A selected review. The Nigerian Journal of Economics and Social Studies. 35(1), 64—77.Engel, R. F. and Granger, C. W. (1987). Co-integration and error-correction: representation, estimation and testing econometrics. 55, 251—276.Engle, R. F. and Yoo, K. (1987). Spurious regression in econometrics. Journal of Economics. 2, 111—120.Granger, J. C. W. (1969). Investigating causal relations by econometric models and cross special methods. Econometricia, 37(3) 424-438 .Gujarati, D. N. (2004). Basic econometrics. New York: McGraw-Hill.Hamilton, J. D. (1994). Time series analysis. Princeton University Press, Princeton, New Jersey, USA.Hayashi, F. (2000). “Econometrics”. Princeton University Press, Princeton, New Jersey, USA.Juselius, K. (1990). Maximum likelihood, estimation and inference on co-integration with application to the demand for money. Oxford Bulletin of Economics and Statistics, 52, 169-210.Keke, N. A.; Olomola, P. A. and Saibu, M. O. (2003). Foreign direct investment and economic growth in Nigeria: a causality test. In S. A. Olaiya (eds). Journal of Economics and Social Studies. 3:1596—4256.Mackinnon, R. (1973). Money and capital in economic development. Washington, DC: The Brooklyn Institution.Philip, O. A. (1987). Structural adjustment programme in a developing economy: the case of Nigeria. Ibadan: Nigerian Institute of Social and Economic Research (NISER).Rostow, W. W. (1960). The stages of economic growth: a non-communist manifesto. London: Cambridge Press.Shaw, E. S. (1973). Financial deepening in economic development. New York: Oxford University Press.Todaro, M. P. (1971). Economic development. 2nd Edition. London: Pearson Education Limited. 19
  • 20. Journal of Economics and Sustainable Development www.iiste.orgISSN 2222-1700 (Paper) ISSN 2222-2855 (Online)Vol.2, No.4, 2011Sustainable Development and Performance, Financial Position and Market Value of Nigerian Quoted Companies Abubakar Sadiq Kasum (Corresponding Author) Department of Accounting and Finance University of Ilorin, Ilorin, Nigeria Email: abubakarsk@yahoo.com, abusk@unilorin.edu.ng Olubunmi Florence Osemene Department of Accounting and Finance, University of Ilorin, Ilorin, Nigeria Email: bunmiosemene1@yahoo.com Joshua Adeyemi Olaoye Department of Accounting and Finance, University of Ilorin, Ilorin, Nigeria Email: olaoyejoshua@yahoo.com, olaoyejoshua@unilorin.edu.ng Atanda Olanrewaju Aliu Department of Accounting and Finance, University of Ilorin, Ilorin, Nigeria Email: alirawa@yahoo.com, lanre@unilorin.edu.ng Tunde Saka Abdulsalam Department of Management Sciences, Kwara State University, Malete, Nigeria Email: salami.tunde@yahoo.comAbstractThe study is against the background that sustainable development practices may involve financial outflowsand hence, may be an unattractive investment to managers. This study evaluated the impact of corporatecompliance with accounting standards that are deemed to enforce sustainable development practices andcan, therefore, imply sustainable development practices by companies, on profitability, financial positionand market value of companies. Forty-four companies that have existed since standardization began inNigeria in 1984 were studied over five years, using Pearson product moment and spearman’s rankcorrelation statistical techniques. The correlations compared compliance to financial reporting standards onthe one hand with financial performance, financial position and market value on the other. Results showed 20
  • 21. Journal of Economics and Sustainable Development www.iiste.orgISSN 2222-1700 (Paper) ISSN 2222-2855 (Online)Vol.2, No.4, 2011that sustainable development practices of companies are rarely associated with profitability. The practicesare, however, shown to associate a little with better asset worth and improved market values.Keywords: Sustainable Development, Profitability, Financial Position, Market Value, Standardization1. IntroductionBusinesses, like all other communal stakeholders, are faced with dual sustainable development challenges.The first challenge is internal sustainability while the second is external or global. Internal sustainabilitycould be referred to as the going concern sustainability, which can also be referred to as the internal economicsustainable development. It is concerned with ensuring that current activities of an organization areconducted in a manner that will not hinder future economic activities. Global sustainability can be divergentin scope. It can be communal, national or universally focused. The essence of sustainable development here isthat activities of business organizations are conducted in such a manner that both the current and future needsof the society are not compromised.This places many responsibilities on the managements of an organization, who are required to strike abalance between corporate goals and communal interests. The most likely happening is that management, asa service to their employers, will focus more on internal sustainability against the communal sustainabledevelopment needs. ‘In contrast to the above, many governments are pinning their hopes of economic growthand technological innovation on strong private sector growth (Fourie, 2009).For good corporate governance that especially takes care of the interests of all stakeholders, the issue ofstandardization comes as a handy tool. Standardization is the mechanism by which procedures of activitiesare being regulated, so that common interests, rather than self-interests are promoted. Standardization isadopted in many aspects of life globally, which include provisions for the control of business activities.The aim of this study is to investigate the impact of compliance to accounting standards with sustainabledevelopment provisions, issued in Nigeria, on the result of activities of Nigerian companies.2. Review of Related Literature2.1 Sustainable Development in the Business SectorAccording to Middleton (1995:240), there could only be theoretical justification for the removal ofresources from environment in the comparative benefit of the removed resources, and in the ability toensure that, the environment is, generally, not worse-off. Corporate governance is the conceptthat best describes the responsibility of business in sustainable development. According to Brundtlandreport of the United Nations, sustainable development is the ‘development which meets the needs of thepresent without compromising the ability of future generation to meet their own needs’. The 2005 worldsummit of the United Nation referred to economic development, social development and environmentalprotection as the interdependent and mutually reinforcing pillars of sustainable development. Davis (2009)explained it as the economic development and the consumptive use of world’s natural resources in waysthat are sustainable. In other words, it is realized that resources are finite and that part of our job as humanbeings is to preserve the human future on this planet into limitless future.On the other hand, Newton-King (2009) stated that ‘economic sustainability evaluates whether a company 21
  • 22. Journal of Economics and Sustainable Development www.iiste.orgISSN 2222-1700 (Paper) ISSN 2222-2855 (Online)Vol.2, No.4, 2011has positioned itself for long-term growth rather than only short-term performance’. According to her, acompany ‘must be able to adapt to macro-economic trends and act in such a way that the long-termviability of the business is assured’. These are the two sustainable development issues for business.Corporate governance already incorporated these as it is said to be ‘concerned with holding the balancebetween economic and social goals and between individual and communal goals, with the aim of aligningas nearly as possible, the interest of individuals, corporations and society (Dixon, 2009). Additional to thisis the fact that ‘many governments are pinning their hopes of economic growth and technologicalinnovation on strong private sector growth’ (Fourie, 2009).2.2 Business Procedure StandardizationAccording to Russell (2007), standardization involves inspection, assurance and certification services aimedat regulating businesses, enforcing contracts and assurance for acceptable social and environmental behaviorexpectations. Standardization that affects business exists as far back as the eighteen century, for weight andmeasure by French scientists. Several standards exists, today that have impacts on businesses worldwide. Themost familiar and well - established set of standards are those on financial reporting. The standards usuallyprescribe what information to make available to stakeholders and the form in which the information shouldbe prepared and presented. Accounting standards were developed as a guiding tool which defined howcompanies should display transactions and events in their financial statements, ensure the needed uniformityof practices, enlighten users of financial reports, provide a framework for preparation, presents and interpretsfinancial statement (Kasum, 2009; Kantudu, 2005; Blair, Williams and Lin, 2008; Oghuma and Iyoha,2005).Business accounting standardization, therefore, could be said to centre on financial reportingstandardization, in a manner that stakeholders in business are adequately provided for. The standards madesome provisions that facilitate the two sustainable development concerns of business. Dixon (2009)therefore opined that the move towards sustainable reporting is a welcome one in that it encourages a morepositive response to sustainable development issues.2.3 Sustainable Development Related Issues in Nigeria Accounting StandardsThe Nigerian Accounting Standard Board has issued thirty accounting standards covering various businessissues to date. Five of the standards are considered favorable to sustainable development.2.3.1 Statement of Accounting Standard No. 3 on Accounting for Property Plant and EquipmentThis standard could be linked to internal sustainability of businesses. “Property plant and equipment aretangible assets that have been acquired or constructed and held for use in the production or supply of goodsand services and may include those held for maintenance or repairs of such assets; and are not intended forsale in the ordinary course of business”. Most popular examples of property plant and equipment as containedin the standard include land and improvements, building and plants and equipments (Statement ofAccounting Standard No. 3: 1984).2.3.2 Statement of Accounting Standard No. 8 on Accounting for Employee’s Retirement BenefitsContract is a fundamental principle in employee retirement benefit (Gold, 2005). The kind of contractneeded, he posited, is that which may extend over a long period of time that will have force even after one 22
  • 23. Journal of Economics and Sustainable Development www.iiste.orgISSN 2222-1700 (Paper) ISSN 2222-2855 (Online)Vol.2, No.4, 2011party would rather no longer be bound. “Economists expect contracts to be rational and efficient” (Gold,2005). The two methods usually adopted for funding retirement plan are the advance financing method andthe pay-as-you-go-system. For advance financing, “Funds are provided on a regular basis during the workinglife of employees”, while for pay-as-you-go “the active working generation provides the funds for pensionsof those who have retired”. Retirement benefit scheme could be administered by the employer’s organizationor by a third party (Statement of Accounting Standard No. 8: 1990).2.3.3 Statement of Accounting Standard No. 9 on Accounting for DepreciationLike the standard on Property Plant and Equipment, the standard could be linked to internal sustainability ofbusinesses, because of the importance of assets to income generation. Depreciation is a systematic andrational process of distributing the cost of tangible asset over the life of assets. ‘It is the process by which acompany gradually records the loss in value of fixed assets… to spread the initial purchase price of the fixedasset over its useful life’. It as the periodic, systematic expiration of the cost of a company’s fixed assets(except for land) (Lopes, 2006).Various methods exist for calculating depreciation; two broad classifications could be made of the methods,as time based or usage based. Whatever method to use should consider:-the cost or revalued amount of the asset,-the estimated economic life, and-the estimated residual value of the asset (Dunn, 2004).Depreciation is in respect of items of property plant and equipment otherwise referred to as fixed assets.Depreciation “represents an estimate of the portion of the historical cost or revalued amount of a fixed assetchargeable to operation, during an accounting period” (Statement of Accounting Standard No. 9: 1989). 2.3.4 Statement of Accounting Standard No. 12 on Accounting for InvestmentsInvestment decisions of businesses have both internal and global implications and consequently the standardwill have both internal and external sustainable development consequences. Assets held by an enterprise forthe purposes of capital appreciation or income generation rather than production, trade or provisions ofservice qualify as investment. Investment, therefore, generates return to investing company and will amongother, create more employment. Investments are classified as short term if they are readily realizable andotherwise, classified as long term (Statement of Accounting Standard No. 12: 1992).2.3.5 Statement of Accounting Standard No. 19 on Accounting for taxesTaxation practices have more external sustainable development implications. Tax could be defined as acompulsory levy imposed by the government on income, expenditure or properties of an individual or aconcern, that is viewed like contribution to government administration and/or payment for the use of publicgoods. It is also described as a compulsory levy imposed on a subject or upon his property by the governmentto provide security, social amenities and create conditions for the economic well-being of the society. Profitof any company, which accrued in, derived from, brought into or received in Nigeria are chargeable to tax(Ola, 1999; 350 - 362). 23
  • 24. Journal of Economics and Sustainable Development www.iiste.orgISSN 2222-1700 (Paper) ISSN 2222-2855 (Online)Vol.2, No.4, 2011Taxes that affects a company include those paid directly by the company and those paid by the company onbehalf of others. Tax should be recognized as expense or income and should be included in the profit and lossaccount of the period, as a separate line item (Statement of Accounting Standard No. 19: 2001).The Nigerian Accounting Standard Board has issued thirty accounting standards covering various businessissues, five of which are considered favorable to sustainable development.3. Research Methodology3.1 Research DesignThis study is an exploratory type that is seeking understanding of a phenomenon. Samples for this study weredrawn from The Nigerian Stock Exchange. Forty-four companies that have filed report with The NigerianStock Exchange from the commencement of standardization in Nigeria to date, out of the current 218 listed,are the samples for the study. The study was carried out over five years range using three years data.Consequently, profit, net-asset and market value record of the companies for 2002, 2004 and 2006 werecollected from the Nigerian Stock Exchange. The financial statements of the 44 companies for 2002 werecollected from Stock Exchange library in Lagos, Nigeria. For compliance statistics, the standards weresubjected to content analysis, with the aim of, on a point-by-point basis, determining what the provisionstherein are and consequently the requirement of the standards from companies. By this, each point ofcompliance was identified and scores were assigned to each of the points. The financial statements are thenexamined for the extent to which they comply with the provisions on points, as set up in the above. Thedegree of compliance index was, thereafter, computed as:Compliance score = point scored ……………(1) Maximum possible scoreSummation of score per standard divided by number of standards applicable to the companies produced theaggregate compliance score for individual companies.Pearson product moment and Spearman ranked correlation statistical methods were used to investigate ifcompliance associates with the three variables.3.2 Statement of Hypothesis3.2.1 Hypothesis 1Null hypothesisCompliance with Standards that promote sustainable development is not associated with improvedprofitability.Alternative hypothesisCompliance with Standards that promote sustainable development improves profitability.3.2.2 Hypothesis 2Null hypothesisCompliance with Standards that promote sustainable development is not associated with improved net-asset.Alternative hypothesisCompliance with Standards that promote sustainable development improves net-asset. 24
  • 25. Journal of Economics and Sustainable Development www.iiste.orgISSN 2222-1700 (Paper) ISSN 2222-2855 (Online)Vol.2, No.4, 20113.2.3 Hypothesis 3Null hypothesisCompliance with Standards that promote sustainable development is not associated with improve marketvalue.Alternative hypothesisCompliance with Standards that promote sustainable development improves market value.3.3 Decision RuleThe results will be positive or negative and will between ‘zero’ and ‘one’. Positive result indicates favourableassociation and the closer to one the result is, the stronger the degree of association between compliance andeach of the dependent variables and vice versa. Consequently, only statistically significant results shall beused for testing our hypotheses. Alternative hypothesis, therefore, shall be accepted if the study’s statisticallysignificant result is positive and shall be rejected if it is negative.4. Results4.1 Data Presentation and AnalysesFirst, both the total and per share values of the relevant data to this study are presented in tables 1 - 3. Thedata, which are for the forty-four companies under study are presented in Naira(N), the national and reportingcurrency for Nigeria. The compliance score earned from each identified compliance item in the consideredstandards, by the companies are in table ‘4’ that followed Naira data.The result of statistical analyses presented in tables 5 and 6 are both total and per share analyses of thecorrelation between the extent of compliance with those standards that are sustainable development relatedand profitability, financial position and market value as presented in tables 1, 2 and 3 above respectively.Pearson moment correlation for impact on profitability as presented in table ‘5’ shows that all total valueanalyses gave positive result, while per share analyses gave negative results. All the outcomes are, however,not statistically significant. Similarly, table ‘6’ shows that 2002 and 2004 results are positive, while 2006results are negative. The results too are not significant. This profitability result is similar to Kasum andOsemene (2010). In table ‘5’, analyses for net-asset shows that all the results are positive and the results for2002 are statistically significant at 5% level of significant. Spearman’s rank correlation statistics fornet-assets in table ‘6’ shows, also, that all results are positive, but are not statistically significant.Pearson moment correlation analyses to test impact on market value in table ‘5’ show that all the computedRs are positive. Spearman’s correlations too are positive in all the six cases in the three years. Total value’sPearson analysis of 2002 is statistically significant at 10% level, while all other results are not statisticallysignificant. Overall, profitability analyses provided results that may suggest that sustainable developmentpractices are not in business interest. On the other hand, both net-asset and market value analyses indicatethat sustainable development practices are in the interest of business. The last two variables are consideredto be long-term focused and are of interest than short-termed accounting profit. This suggests that the resulthere is not bad for business.4.2 Testing of the Hypothesis 25
  • 26. Journal of Economics and Sustainable Development www.iiste.orgISSN 2222-1700 (Paper) ISSN 2222-2855 (Online)Vol.2, No.4, 2011For hypothesis ‘1’, a combination of ‘12’ items in both tables ‘5’ and ‘6’ are relevant. Five items arepositive and seven negative. All the result items, however, are not statistically significant and not useful forhypothesis testing. The study, therefore, failed to accept alternative hypothesis ‘1’. For hypothesis 2, thecombination of 12 items in both tables ‘5’ and ‘6’ that are relevant are positive. Importantly, two items arestatistically significant and are useful for testing hypothesis. Since the statistically significant results arepositive, we accept the alternative hypothesis that ‘Compliance with Standards that promote sustainabledevelopment improves net-asset’. For hypothesis ‘3’, the ‘12’ items that are relevant are also positive.One item is useful for testing hypothesis being statistically significant at 10% level of significance. Sincethe statistically significant result is positive, we accept alternative hypothesis ‘3’ that ‘Compliance withStandards that promote sustainable development improves market value’.The meaning of these results is that compliance to standards that promotes sustainable development byNigerian companies has nothing significantly to do with their profitability. Implying that whether theycomply or not to those standards, their profitability situation is not really affected. Net-Asset and Marketvalue, are however, improved as companies comply with sustainable development related accountingstandards.5. ConclusionBased on the findings of this study, we conclude that compliance to those accounting standards that thisstudy adjudged to promote sustainable development, by the companies listed on Nigerian Stock Exchange,does not affect their profitability. The study also, concludes that long-term enhancing variables like assetand market value improve as companies comply with the standards. These results are informative in somany senses. If truly the standards promote sustainable development that fulfills the basics of sustainabledevelopment, long-term sustainable profitability will be more an appropriate measure than short-termresults.In line with the same thinking, rather than building immediate profits, economic sustainability shouldactually target building business assets that would be positioned to produce long-term sustainable futureprofits for the concerns. All these relate to internal sustainability, which also aids global sustainability.Sustainable development from the point of view of the society, of course, may involve investment in thesociety and meeting obligations. These will usually involve resources outflow from the otherwise retainableincomes of businesses. The goodwill of these kinds of activity will in turn bring patronage to thebusinesses.ReferencesBlair, M. M., Williams, C. A. and Lin, L. (2008), ‘The Role of Standardization, Certification and Assurance Services in Global Business’, Comparative Research in Law and Political Economics Research Paper No 12/2008, 4(3), www.ssrn.com.Davis, T. (2009), ‘What is Sustainable Development?’, Enviropedia, www.enviropedia.com.Dixon, T. (2009), ‘Sustainable Development: A Corporate Responsibility’, Enviropedia, www.enviropedia.com.Dunn, P. E. (2004), ‘Accounting for Depreciation and the Concept of Revenue and Capital Expenditure’, 26
  • 27. Journal of Economics and Sustainable Development www.iiste.orgISSN 2222-1700 (Paper) ISSN 2222-2855 (Online)Vol.2, No.4, 2011 Accounting WEB, www.accountingweb.co.ukFourie, A. (2009), ‘Strategic Considerations for the Business Community to Shape a Sustainable Future’, Enviropedia, www.enviropedia.com.Gold, J. (2005), ‘Retirement Benefits Economic and Accounting: Moral Hazard and Fringe Benefit Design’, North American Actuarial Journal, 9(2), www.google.com.Kantudu, A. S. (2005), ‘The Degree of Compliance with the Requirement of Information to be Disclosed in Financial Statement by Listed Firms in Nigeria’, Abuja management Review, 3(1), 26-46.Kasum, A. S. (2009), ‘The Need for ‘General Business Procedures and Practices Standards’ to Holistically Guide and Regulate Businesses Worldwide and to, Importantly, Prevent Failure: An Empirical Based Proposition’, Proceedings of The 27th Standing Conference on Organizational Symbolism, Copenhagen Business School, Denmark, 8th – 11th of July.Kasum, A. S. and Osemene, O. F. (2010), “Sustainable Development and Financial Performance of Nigerian Quoted Companies”, Proceedings of the 16th Annual International Sustainable Development Research Conference, University of Hong Kong, Hong Kong, 30 th May – 1st June.Lopes, R. (2006), Depreciation in Accounting, Accounting Resources, www.cnx.org.Middleton, N. (1995), The Global Casino An Introduction To Environmental Issues, New York: John Wiley and Sons Inc.Newton-King, N. (2009), ‘Sustainable Development: Investment’, Enviropedia, www.enviropedia.com.Oghuma, R. and Iyoha, F. (2006), ‘Compliance with Accounting Standards by Quoted Insurance Companies in Nigeria: An Empirical Investigation’, Nigerian Journal of Education Research, 7(2), 18 – 27.Ola, C. S. (1997), Income Tax Law in Nigeria, Revised Ed, Ibadan: Heinemann Educational Books Ltd.Russell, A. L. (2007), ‘The America System: A Schumpterian History of Standardization’, Progress on Point Release 14.4, The Progress and Freedom Foundation.-Statement of Accounting Standard No.3: Nigeria Accounting Standard Board (1984)-Statement of Accounting Standard No.8: Nigeria Accounting Standard Board (1990)-Statement of Accounting Standard No.9: Nigeria Accounting Standard Board (1991)-Statement of Accounting Standard No.12: Nigeria Accounting Standard Board (1992)-Statement of Accounting Standard No.19: Nigeria Accounting Standard Board (2001)-Sustainable Development, Wikipedia: The free Encyclopedia, www.wikipedia.org.Table 1: Profitability data (Profit After Tax) Company Names 2002 N 2004 N 2006 N Total Pr Sh. Total Pr Sh. Total Pr Sh. A.G LEVENTIS 59,565,000 0.06 240,992,000 0.12 468,000,000 0.21 AFPRINT 65,633,000 0.12 -618,407,000 -1.1 11,974,000 0.02 27
  • 28. Journal of Economics and Sustainable Development www.iiste.orgISSN 2222-1700 (Paper) ISSN 2222-2855 (Online)Vol.2, No.4, 2011 AFRICAN PET 2,156,893,000 9.99 890,120,000 2.06 2,161,530,000 2.74 BERGER PAINTS 85,941,000 0.4 101,542,000 0.47 81,678,000 0.38 CADBURY 2,249,078,000 3 2,812,623,000 2.81 -4,665,459,000 -4.66 CAP PLC 140,806,000 0.84 161,455,000 0.77 312,748,000 1.49 CAPPA & DALBER 25,509,000 0.26 126,114,000 1.28 127,946,000 0.65 CFAO 689,957,000 1.66 -1,123,119,000 -2.7 -1,225,053,000 -2.94 CHELLARAMS 31,305,000 0.26 56,127,000 0.31 72,500,000 0.2 COSTAIN(W. AF) 20,048,000 0.13 -469,010,000 -2.93 -1,488,639,000 -9.31 DN MEYER 75,333,000 0.52 62,680,000 0.32 60,753,000 0.21 DUNLOP 96,580,000 0.16 -316,027,000 -0.42 -667,356,000 -0.88 FIRST BANK 4,776,000,000 1.88 14,853,000,000 4.24 21,833,000,000 4.17 GLAXO SMITHKLINE 497,053,000 0.62 955,261,000 1.2 1,082,290,000 1.13 GUINNESS 4,149,536,000 5.86 7,913,503,000 6.71 7,440,102,000 6.31 INCAR NIGERIA PLC -18,422,000 -0.22 -33,960,000 -0.41 1,008,000 0 JOHN HOLT 179,000,000 0.46 70,000,000 0.18 -476,000,000 -1.22 LEVER BROTHERS 1,571,918,000 0.52 2,167,249,000 0.72 -1,617,615,000 -0.53 LIVESTOCK FEEDS -66,364,000 -2.68 -237,114,000 -9.58 748,424,000 0.62 MOBIL OIL 474,230,000 2.47 1,759,468,000 7.32 1,716,208,000 7.14 MORISON IND. 6,341,000 0.07 9,667,000 0.11 8,147,000 0.09 NIG. BOTTLING COY 4,170,544,000 4.28 3,032,322,000 2.33 766,248,000 0.59 NIG. BREWERIES 9,218,954,000 2.44 5,086,403,000 0.67 10,900,524,000 1.44 NIG. ENAMELWARE 15,966,000 0.55 15,970,000 0.55 6,343,000 0.22 NIGERIAN ROPES 9,804,000 0.3 14,355,000 0.05 22,754,000 0.09 NIG WIRE IND. 36,202,369 2.41 -39,856,000 -2.66 -18,969,000 -1.26 NORTH. NIG FLOUR 149,640,000 2.02 138,499,000 1.24 55,071,000 0.37 P.S MANDRIES 31,804,000 0.8 10,557,000 0.26 8,427,000 0.21 P.Z INDUSTRIES 1,685,918,000 1.16 3,303,662,000 1.9 3,235,587,000 1.27 PHARMA DEKO PLC 42,304,000 1.06 30,619,000 0.36 8,216,000 0.09 POLY PRODUCTS 21,053,000 0.09 12,209,000 0.05 725,000 0 R.T BRISCOE PLC 166,418,000 1.39 155,445,000 0.43 531,776,000 1.46 ROADS NIG. PLC -19,780,000 -0.99 -4,783,000 -0.24 11,957,000 0.6 S.C.O.A NIG. PLC 104,000,000 0.21 -327,000,000 -0.5 733,000,000 1.49 STUDIO PRESS PLC -47,629,000 -0.6 30,044,000 0.38 55,095,000 0.69 TOTAL NIGERIA 2,514,087,000 8.46 2,778,904,000 8.18 2,516,693,000 7.41 28
  • 29. Journal of Economics and Sustainable Development www.iiste.orgISSN 2222-1700 (Paper) ISSN 2222-2855 (Online)Vol.2, No.4, 2011 PLC U.A.C 1,166,200,000 1.28 1,570,100,000 1.37 3,203,600,000 1.25 U.B.A 1,566,000,000 0.92 4,525,000,000 1.77 11,550,000,000 1.64 U.T.C -370,565,000 -0.33 -74,115,000 -0.07 52,561,000 0.05 UNION BANK 5,633,000,000 2.24 8,341,000,000 3.31 10,802,000,000 1.2 UNITED NIG. TEXT 1,074,344,000 1.27 132,087,000 0.16 -756,502,000 -0.9 VITAFOAM 258,401,000 0.59 272,234,000 0.42 275,118,000 0.42 VONO 15,072,000 0.31 -218,862,000 -4.53 134,000 0 W. AFRICA. P. CEM -1,348,000,000 -0.79 -3,401,000,000 -1.98 10,678,000,000 3.56 Source: Nigerian Stock Exchange Fact Book 2003, 2005 and 2007Table 2: Net-Asset data (Net-Asset as per Balance Sheet) Company Names 2002 N 2004 N 2006 N Total NA/Sh. Total NA/Sh. Total NA/Sh. A.G LEVENTIS 2,357,769,000 2.49 3,438,429,000 1.67 4,046,651,000 1.83 AFPRINT 2,756,216,000 4.91 1,939,956,000 3.46 832,370,000 1.48 AFRICAN PET -20.159739b -93.33 -7,568,785 -0.02 2,455,230,000 3.11 BERGER PAINTS 439,323,000 2.02 496,385,000 2.28 965,293,000 4.44 CADBURY 6,859,572,000 9.14 10,848,768,000 10.84 2,181,121,000 2.18 CAP PLC 481,009,000 2.86 594,747,000 2.83 857,065,000 4.08 CAPPA & DALBER 651,848,000 6.62 840,132,000 8.53 1,057,169,000 5.37 CFAO 2,463,541,000 5.92 1,653,913,000 3.98 328,187,000 0.79 CHELLARAMS 1,009,330,000 8.38 1,435,520,000 7.94 2,015,407,000 5.58 COSTAIN(W. AF) 70,815,000 0.44 110,490,000 0.69 -1,349,945,000 -8.44 DN MEYER 288,364,000 1.98 313,148,000 1.61 163,357,000 0.56 DUNLOP 1,526,235,000 2.52 587,948,000 0.78 6,900,327,000 9.13 FIRST BANK 19,406,000,000 7.64 41,605,000,000 11.88 64,277,000,000 12.27 GLAXO SMITHK 1,396,347,000 1.75 2,517,722,000 3.16 4,193,075,000 4.38 GUINNESS 14,157,810,000 20.00 16,908,244,000 14.33 20,947,782,000 17.75 INCAR NIGERIA PLC 102,380,000 1.22 56,721,000 0.68 323,879,000 1.04 JOHN HOLT 1,942,000,000 4.98 2,603,000,000 6.67 2,311,000,000 5.93 LEVER BROTHERS 4,167,664,000 1.38 6,072,800,000 2.01 3,953,348,000 1.31 LIVESTOCK FEEDS 250,812,000 10.13 -830,728,000 -33.55 -343,406,000 -0.29 MOBIL OIL 686,083,000 3.57 882,551,000 3.67 2,833,678,000 11.79 MORISON IND. 106,967,000 1.17 110,177,000 1.21 119,955,000 1.31 NIG. BOTTLING CO 14,915,193,000 15.31 18,699,659,000 14.39 20,047,083,000 15.32 29
  • 30. Journal of Economics and Sustainable Development www.iiste.orgISSN 2222-1700 (Paper) ISSN 2222-2855 (Online)Vol.2, No.4, 2011 NIG. BREWERIES 26,425,983,000 6.99 31,278,969,000 4.14 36,249,393,000 4.79 NIG. ENAMELWAR 94,112,000 3.27 102,835,000 3.57 118,088,000 4.10 NIGERIAN ROPES 36,467,000 1.10 249,278,000 0.95 286,269,000 1.09 NIG WIRE IND. 563,460,224 37.56 247,901,000 16.53 223,175,000 14.88 NORTH. NIG FLOUR 505,147,000 6.80 725,565,000 6.51 846,220,000 5.70 P.S MANDRIES 156,350,000 3.91 202,034,000 5.05 219,224,000 5.48 P.Z INDUSTRIES 14,349,551,000 9.88 18,701,185,000 10.73 27,055,099,000 10.65 PHARMA DEKO PLC 68,877,000 1.72 144,988,000 1.71 423,288,000 4.46 POLY PRODUCTS 222,357,000 0.93 245,732,000 1.02 240,169,000 1.00 R.T BRISCOE PLC 547,443,000 4.56 1,785,118,000 4.92 2,207,970,000 6.08 ROADS NIG PLC 45,349,000 2.27 26,647,000 1.33 42,280,000 2.11 S.C.O.A NIG PLC 947,000,000 1.92 929,000,000 1.43 787,000,000 1.60 STUDIO PRESS PLC 236,079,000 2.95 294,901,000 3.69 944,447,000 11.81 TOTAL NIG. PLC 4,008,510,000 13.49 3,742,235,000 11.02 5,765,754,000 16.98 U.A.C 6,428,600,000 7.08 11,150,000,000 9.76 16,099,200,000 6.27 U.B.A 10,627,000,000 6.25 19,533,000,000 7.66 48,535,000,000 6.87 U.T.C 430,543,000 0.38 119,276,000 0.11 688,828,000 0.61 UNION BANK 32,240,000,000 12.81 39,732,000,000 15.79 100,500,000,000 11.14 UNIT NIG. TEXTILES 10,003,955,000 11.86 9,717,363,000 11.52 9,016,410,000 5.26 VITAFOAM 585,905,000 1.34 772,069,000 1.18 962,274,000 1.47 VONO 206,659,000 4.27 -21,530,000 -0.45 268,209,000 0.89 W. AFRICA. P.CEM. 9,213,000,000 5.37 2,637,000,000 1.54 25,015,000,000 8.33Source: Nigerian Stock Exchange Fact Book 2003, 2005 and 2007Table 3: Market Value data Company Names 2002 N 2004 N 2006 N Total MV/Sh. Total MV/Sh. Total MV/Sh. A.G LEVENTIS 711,189,000 0.75 2,917,430,571 1.42 3,242,930,250 1.47 AFPRINT 420,899,549 0.75 420,899,549 0.75 364,779,609 0.65 AFRICAN PET. 3,166,560,000 14.66 27,514,080,000 63.69 33,263,189,960 42.17 BERGER PAINTS 556,462,080 2.56 891,208,800 4.10 734,703,840 3.38 CADBURY 23,554,769,400 31.38 77,985,452,800 77.92 51,273,033,200 51.23 CAP PLC 549,360,000 3.27 1,428,000,000 6.80 4,139,100,000 19.71 CAPPA & DALBER 767,816,400 7.80 713,675,500 7.25 2,067,198,000 10.50 30
  • 31. Journal of Economics and Sustainable Development www.iiste.orgISSN 2222-1700 (Paper) ISSN 2222-2855 (Online)Vol.2, No.4, 2011 CFAO 1,426,880,000 3.43 2,945,280,000 7.08 1,522,560,000 3.66 CHELLARAMS 250,615,040 2.08 354,234,720 1.96 437,371,440 1.21 COSTAIN(W. AF) 100,749,600 0.63 255,872,000 1.60 289,455,200 1.81 DN MEYER 1,114,948,638 7.65 1,220,367,280 6.28 1,046,449,100 3.59 DUNLOP 1,639,008,000 2.71 2,600,640,000 3.44 2,305,800,000 3.05 FIRST BANK 59,817,000,000 23.55 92,748,335,480 26.48 266,543,498,461 50.88 GLAXO SMITHK 2,040,960,000 2.56 7,653,600,000 9.60 12,858,063,994 13.44 GUINNESS 29,557,507,438 41.75 155,162,110,000 131.50 152,802,230,000 129.50 INCAR NIG. PLC 142,375,000 1.70 129,812,500 1.55 1,209,587,720 3.89 JOHN HOLT 631,800,000 1.62 522,600,000 1.34 468,000,000 1.20 LEVER BROTHERS 82,748,282,920 27.34 56,749,462,500 18.75 52,270,038,260 17.27 LIVESTOCK FEEDS 85,422,000 3.45 70,070,800 2.83 2,267,998,900 1.89 MOBIL OIL 12,525,671,340 65.13 39,377,192,400 163.80 41,588,854,000 173.00 MORISON IND. 235,572,705 2.58 127,830,150 1.40 81,263,453 0.89 NIG BOTTLING CO 26,066,754,416 26.75 95,367,005,200 73.40 64,625,284,920 49.38 NIG. BREWERIES 159,113,064,320 42.08 639,792,914,400 84.60 299,931,288,240 39.66 NIG.ENAMELWAR 96,192,000 3.34 82,368,000 2.86 114,336,000 3.97 NIGERIAN ROPES 66,684,082 2.01 485,149,120 1.84 574,796,240 2.18 NIG WIRE IND. 36,600,000 2.44 33,600,000 2.24 33,600,000 2.24 NORT. NIG FLOUR 617,760,000 8.32 2,300,986,840 20.66 3,636,765,000 24.49 P.S MANDRIES 206,400,000 5.16 322,400,000 8.06 312,000,000 7.80 P.Z INDUSTRIES 14,520,601,770 10.00 25,387,817,040 14.57 57,352,762,420 22.57 PHAR DEKO PLC 103,200,000 2.58 401,860,800 4.73 347,553,600 3.66 POLY PRODUCTS 100,800,000 0.42 148,800,000 0.62 240,000,000 1.00 R.T BRISCOE PLC 308,400,000 2.57 4,023,436,080 11.08 3,489,640,860 9.61 ROADS NIG.PLC 20,600,000 1.03 21,600,000 1.08 20,200,000 1.01 S.C.O.A NIG PLC 1,180,800,000 2.40 1,280,500,000 1.97 359,890,000 0.73 STUDIO PRESS PLC 126,400,000 1.58 132,800,000 1.66 126,400,000 1.58 TOTAL NIG. PLC 19,031,072,920 64.06 72,827,469,000 214.50 65,860,477,560 193.98 U.A.C 3,588,857,145 3.95 15,730,199,998 13.77 61,173,794,880 23.81 U.B.A 15,164,000,000 8.92 29,325,000,000 11.50 141,623,600,000 20.06 U.T.C 897,000,000 0.80 2,130,375,000 1.90 1,110,037,500 0.99 UNION BANK 52,752,128,000 20.96 78,146,640,000 31.05 246,052,400,881 27.27 UNITED NIG. TEXT 2,698,508,502 3.20 3,027,389,226 3.59 1,370,336,349 0.80 VITAFOAM 1,987,440,000 4.55 2,660,112,000 4.06 2,692,872,000 4.11 VONO 90,909,280 1.88 89,458,600 1.85 480,000,000 1.60 W. AFRICA. P.CEM 39,672,576,000 23.13 29,209,856,000 17.03 124,596,416,166 41.51 31
  • 32. Journal of Economics and Sustainable Development www.iiste.orgISSN 2222-1700 (Paper) ISSN 2222-2855 (Online)Vol.2, No.4, 2011Source: Nigerian Stock Exchange Fact Book 2003, 2005 and 2007Table 4: Compliance indices Company Names SAS3 SAS8 SAS9 SAS 13 SAS 19 Avg score A.G LEVENTIS 1 0.67 1 0.75 0.67 0.82 AFPRINT 0.8 0.33 0.85 0.5 0.5 0.6 AFR. PET 1 0.8 1 1 0.69 0.9 BERGER PAINT 1 0.5 1 0.5 0.69 0.74 CADBURY 1 0.83 1 1 0.92 0.95 CAP PLC 0.9 0.83 0.85 0.5 0.77 0.77 CAPPA & DALB 0.9 0.67 0.92 1 0.85 0.87 CFAO 1 0.83 1 0.5 0.77 0.82 CHELLARAMS 0.8 0.83 0.85 0.83 0.75 0.81 COSTAIN W.AF 1 0.67 1 0.8 0.62 0.82 DN MEYER 1 0.67 1 NA 0.92 0.9 DUNLOP 1 0.71 1 0.5 0.77 0.8 FIRST BANK 1 0.67 1 0.5 0.85 0.8 GLAXO SMITH 1 0.83 1 1 0.77 0.92 GUINNESS 1 0.83 1 NA 0.92 0.94 INCAR NIGERIA 1 0.83 1 0.4 0.85 0.82 JOHN HOLT 0.9 0.83 0.85 1 0.77 0.87 UNILEVER 0.9 0.78 0.92 NA 0.62 0.81 L/STOCK FEEDS 1 0.83 1 NA 0.77 0.9 MOBIL OIL 1 0.67 1 1 0.93 0.92 MORISON INDS 1 1 1 NA 0.77 0.94 NIG BOTTLING 1 0.83 NA 1 0.92 0.94 NIG.BREWERIES 1 0.88 1 0.67 0.92 0.89 NIGENAMELWARE 0.6 0.83 0.69 NA 0.92 0.76 NIGERIAN ROPES 1 0.83 1 NA 0.92 0.94 NIG WIRE INDS 1 0.83 1 NA 0.54 0.84 N. N FLOUR MILLS 1 0.67 1 0.5 0.92 0.82 P.S MANDRIES 0.8 0.5 0.85 1 0.92 0.81 P.Z INDUSTRIES 1 0.83 1 1 0.92 0.95 PHARMA DEKO 1 0.83 1 NA 0.85 0.92 POLY PRODUCTS 1 0.83 1 1 0.92 0.95 R.T BRISCOE NIG. 1 0.67 1 0.5 0.92 0.82 ROADS NIGERIA 1 0.67 1 0.8 0.85 0.86 32
  • 33. Journal of Economics and Sustainable Development www.iiste.orgISSN 2222-1700 (Paper) ISSN 2222-2855 (Online)Vol.2, No.4, 2011 S.C.O.A NIGERIA 0.9 0.67 0.92 0.25 0.5 0.65 STUDIO PRESS 0.8 0.67 0.85 0.5 0.85 0.73 TOTAL NIGERIA 1 0.92 0.83 0.5 0.79 0.81 U.A.C 0.9 0.67 0.92 0.83 0.62 0.79 U.B.A 1 0.67 1 0.5 0.77 0.79 U.T.C 1 0.83 1 0.5 0.62 0.79 UNION BANK 1 0.67 1 0.5 0.71 0.78 UNI. NIG. TEXTI 1 0.67 1 1 0.92 0.92 VITAFOAM 1 0.67 1 0.67 0.92 0.85 VONO 0.9 0.83 0.92 NA 0.92 0.89 W. AFR.P. CEM 0.9 1 0.92 0.8 0.93 0.91Source: Authors’ Computations, 2010, based on Financial statements of 2006.Table 5: Correlation StatisticsMeasurement Items R. Pearson R. Spearman 2002 2004 2006 2002 2004 2006S.D. Compliance and Total 0.163 0.198 0.158 0.052 0.103 -0.056Profitability Per Share -0.256 -0.044 -0.047 0.085 0.037 -0.121S.D. Compliance and Net Total 0.413** 0.252 0.211 0.162 0.098 0.004Asset Per Share 0.501** 0.042 0.066 0.173 0.122 0.008S.D. Compliance and Total 0.318* 0.22 0.26 0.056 0.021 0.076Market Value Per Share 0.196 0.042 0.067 0.184 0.108 0.187Source: Authors Computations, 2010. 33
  • 34. Journal of Economics and Sustainable Development www.iiste.orgISSN 2222-1700 (Paper) ISSN 2222-2855 (Online)Vol.2, No.4, 2011 Factors Influencing Real Estate Property Prices A Survey of Real Estates in Meru Municipality, Kenya Omboi Bernard Messah (corresponding author) School of Business & Management Studies Kenya Methodist University, Tel: +254 724770275 E-mail: messahb@yahoo.co.uk Anderson .M. Kigige P.O. Box 111 - 60200, Meru- Kenya Tel 0721401289 E-mail: kmutembei@yahoo.comAbstractReal estate is often used to refer to things that are not movable such as land and improvementspermanently attached to the land. Different types of real estate can have very different cyclic properties.Real estates go through bubbles followed by slumps in Meru municipality and some real estateproperties take shorter time while others take longer to sell despite that the prevailing conditions seemsimilar. Several studies done especially on changes in prices of real estates revealed that real estateprices go through bubbles and slumps.The study therefore, investigated factors at play in determining real estate property prices in MeruMunincipality in Kenya. The study investigated factors such as incomes of real estate investors, theinfluence of location on the price, demand and realtors influence on the price.The study adopted descriptive research design to obtain information on the current status of thephenomenon. Structured questionnaires were used in data collection to obtain the required informationneeded for the study. The population consisted of all 15,844 registered real estate owners in the 5 (five)selected areas of Meru municipality from which a sample of 390 real estate owners were selected bystratifying the population and then selecting the respondents by use of simple random sampling.The data obtained was analyzed by use of available statistical packages for social sciences to obtaindescriptive statistics and a regression model. Findings indicated that incomes alone contributed almost70% of the variations in prices. Demand alone contributed 20% of the changes in prices of real estate.Location and Realtors were found insignificant in determining real estate prices.A summary regresion showed that the variables consindered could explain up to about 70% of variationsin prices. The study recommends that further investigation be done on reasons why location andrealtors were not significat in determining real estate property prices in Meru municipality.Keywords: Real Estate, Property Prices, realtors, Demand, Meru MunicipalityACRONYMS AND ABBRREVIATIONS 34