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Business Expectations Survey in Nigeria: Its Techniques, Uses and Challenges

Olorunsola E. Olowofeso*, Sani I. Doguwa

Statistics Department, Central Bank of Nigeria, Abuja

Abstract: This paper examines the techniques, uses and the various challenges of Business Expectations Survey (BES) in Nigeria. The method of Stratified random sampling design adopted for the collection of the data was described. The firms (small, medium and large) considered are subdivided into strata: industrial, construction, wholesale/ retail trade and services sectors. The method of diffusion indices used to compute the relevant indicators and the business confidence index were also discussed. The uses of BES to check the consistency of exchange rate, inflation rate and lending rate by the deposit money banks as well as for short-term planning and forecasting were highlighted. Both the endogenous and exogenous challenges are discussed. Suggestions to remedy some of the challenges were proffered and conclusion drawn on how mutual understanding and strong network cooperation between data collecting agencies and stakeholders can enhance data credibility and reliability.

Keywords: stratified random sampling, diffusion indices, respondent firms, data issues

Citation: Olorunsola E. Olowofeso, Sani I. Doguwa, Business Expectations Survey in Nigeria: Its Techniques, Uses and Challenges. American Journal of Applied Mathematics and Statistics, 4 (6). 169-172. January 2016. doi:10.12691/ajams-4-6-1

1. Introduction

The last ten years has witnessed considerable number of research studies on business and household expectations surveys. The extent to which sentiment indicators can forecast economic activity and short-term economic developments has been a recurring topic in economic and applied statistics research works. Business expectations indicators play significant role in providing decision-makers, planners and forecasters with necessary information about current and future economic expectations. The business expectations and other expectations surveys plays distinctive role in determining public policies as well as business decisions (see Olowofeso and Doguwa [8], Habibullah [4,5,6]). This influence is based on the ability of the indices and other indicators to provide accurate gauge of how business entrepreneurs will react to changes in the economic environment both at short, medium and long time basis. Empirically, these surveys have shown their capability to measure the various factors that shape firm-owners' decisions as well as provide timely information about their future outlooks. The business climate of today both locally and internationally is quite dynamic and is surrounded by many economic risks, uncertainty, and imperfect information. It is therefore, practically impossible to expect firms to obtain hundred per cent business expectations outcomes. Zaller and Feldman [9] argued that combined forces has lead respondents to individually overestimate the importance of government partisanship for future growth and ignore or misinterpret other economic indicators, and therefore to collectively fail to predict the economic future. Business expectations surveys have generally been conducted with the objective of evaluating the outlooks of some economic indices and their relationship with other macroeconomics indicators of interest as well as examining economic trends and prospects. Confidence indicators derived from business survey results give crucial information on business assessments of the economic situation and their intentions and expectations for the future [8]. Similarly, Ece et al. [3] noted that the surveys on expectations are primarily designed to signal changes in economic activity and widely used in macroeconomic assessments and forecasts.

The BES reports confidence levels among local businesses for the present and the future, as well as their expectations on movements in key economic indicators. Therefore, the Survey is an important source of additional information for use in policy analysis and it provides business perceptions on the direction of change for key economic indicators. It is also useful in filling data gaps during policy analysis and decision making.

The Central Bank of Nigeria (CBN) Act, 2007 empowers the Bank to require persons and institutions having access thereto, at all reasonable times, to supply, in such forms as the Bank may from time to time direct, information relating to or touching or concerning matters affecting the economy of Nigeria. By this Act, the CBN started Business Expectations Survey (BES) in second quarter 2008 and the surveys are conducted quarterly in order to collect information regarding perceptions among the small, medium and large scale business enterprises about the prevailing state of the economy, as well as future prospects. The answers most business owners give to questions about current and future economic outlooks are generally informed by news and personal experiences over the previous months, some of which may in turn be reflected in data that were already available. This invites the question: do surveys, data analysis and survey findings tell us a great deal more than we already know? In order to address this question, this paper examines the techniques, uses and the various challenges of Business Expectations Survey (BES) in Nigeria. The paper further examined the endogenous and exogenous challenges ranging from weaknesses of institutional set-up, lack of infrastructure facilities to keep accurate and reliable data, firms’ bureaucracy, poor record keeping, among others.

The rest of the paper is structured into four sections. The methodology of BES is presented in section 2, while section 3 presents the uses of BES indicators. The fourth section presents the challenges of BES while section five gave the concluding remarks of the paper.

2. Methodology

2.1. Survey

This section presents the methodology used for conducting BES in Nigeria. Questionnaire is the main instrument used to collect primary data by staff of Survey Management Division, Statistics Department, Central Bank of Nigeria. The instrument are designed to capture information like business outlook index on the macro economy by sector, economic performance, types of business, business with expansion plan, operational constraints, business expectations on selected economic indicators for the current and the following quarter, among others. The survey has been designed to collect data from the senior executives or owners of the business enterprises. The questionnaire are administered to sample of respondents engaged in industrial, construction, wholesale and retail, and services sectors which include financial intermediation, hotels and restaurants, renting and business activities and community and social services. The sectors covered have been selected on the basis of their significant contribution to GDP.

2.2. Sampling Techniques

Stratified random sampling design is normally employed to collect data from registered firms (small, medium and large) with the Corporate Affairs Commission in Nigeria. The firms are subdivided into strata ranges from industrial, construction, wholesale/ retail trade and services sectors made up of: financial intermediation, hotels and restaurants, renting and business activities and community and social services across the six-geopolitical zones (South West, South East, South-South, North Central, North West and North East) of Nigeria. A total of 1950 firms nationwide, drawn from updated survey frame of both the Central Bank of Nigeria and the National Bureau of Statistics(NBS) are sampled.

2.3. Type of Data

The core questions of the survey cover overall business outlook on the macro economy, business conditions, and buying conditions, expansion plans, business constraints, attitudes towards business conditions in the economy as a whole over the near and the long-term horizon. Precisely, the survey gathers data on the following information:

• demographic and economic characteristics of the business expectations survey respondent

• Index of Business Sentiment and its Components

• Expectations on selected economic indicators (Inflation rate, Interest rate, Exchange rate )

• Buying Conditions

• Buying Conditions Index: Current Quarter

• Buying Intentions Index: Next quarter, among others.

The survey responses are mainly in the form of the anticipated direction of change: i.e., whether conditions will improve, worsen or remain the same. The results are then consolidated in the form of an overall ‘net balance’ between positive and negative responses.

2.4. Computational Procedures

The computational procedure used for the construction of the business confidence indices is the same as the one derived in OECD [7] and Doguwa et al. [2]. The basic steps of this method are as shown below: data preparation put in SPSS file, selection of relevant codes and the potential indicators. At the end of the survey, three global percentages for each question gross percentage changes are obtained, which refer to the proportion (in per cent) of respondents that answered in a specified manner. The imputed survey data are then analyzed; percentages and cross tabulation values are obtained by using appropriate menu from the SPSS package.

Over the years, the net balance statistic has proved to be the most reliable and widely used approach of determining the direction and size of change in the trend of the respective activities surveyed. For a survey with three reply options, the balance is calculated as follows:

where, P = the percentage of positive replies (‘up’ or “ above normal”),

N = the percentage of negative replies (“dawn” or “below normal”).

However, for five options question the DI is computed as

where

SP = proportion (in %) of strongly positive responses

SN = proportion (in %) of strongly negative responses

P = proportion (in %) of positive responses

N = proportion (in %) of negative responses

The balances are also known as Diffusion Indices (DI). A positive index indicates a favourable view, except for the average inflation rate and the average borrowing rate, where a positive index indicates the opposite. The overall business outlook diffusion index (DI) is computed as the percentage share of firms that have an “improving outlook” less percentage share of firms that have a “deteriorating outlook”, the DI is also computed for the other business variables.

Figure 1. BCI Firms Chart (For brevity of this paper, the results of the analysis and other relevant graphs of the BES are not presented here but they are available on request)

The Business Confidence Index (BCI) is obtained by converting the qualitative answers of the survey data into quantitative data (see Figure 1). The procedure is to assign highest point 1 to the answer with ‘much better’. The points, 0.75, 0.5, 0.25 or 0 are assigned to the choices of "better", "same as before", "worse", and "much worse", respectively. The diffusion index (average sum across firms) in this case is defined as follows:

Where =Business Confidence Index for Indicator i

=Points given to firm n for Indicator i

N= Total number of respondents

i = Indicator .

Finally, the cumulative BCI is given as

where BCI = Business Confidence Index

I = Total number of indicators

The values of the indices are classified into three main groups. The groups are:

Below 50, 50 and above 50. Thus, if: BCI<50, business confidence is worse, BCI=50, business confidence is unchanged, BCI>50, business confidence is better.

3. Uses of BES Indicators

The BES is used to get advanced information on the short-term outlook and on turning points in the business cycle; serve as an indicator or signal of financial problems which could lead to an impending financial crisis; serve as basis for forecasting short-term business cycles; and complement quantitative economic indicators. The results of BES can also be used to check the consistency of exchange rate, inflation rate and lending rate by the deposit money banks as well as for short-term planning and forecasting. In addition, it could also serve as a mirror-image guide by members of the Monetary Policy Committee in taking some policy decisions.

4. Challenges of BES

The challenges confronting the conduct of BES in Nigeria are numerous. The general misconception of Statistics and unco-operative attitude of respondents are big challenges. In most cases, enumerators experienced extreme difficulty in obtaining permission to interview decision-makers particularly in big firms. Some respondents are always hesitant to share information because of the policies of their organizations. In such cases, interviewers had to look for replacements in order to meet the targeted number of respondents. The location of some of the firm from one another also presents some geographical difficulty. The other challenges are the endogenous and the exogenous challenges highlighted below.

• Inability of the firms to keep accurate and reliable data

• Lack of resources, infrastructure and technical know-how of the firms’staff

• Statistical literacy and education

• Inability of establishments and enterprises to give accurate, reliable and timely data on request

• Institutional bureaucracy

• Ineffective statistical legislation in the country

• Poor bookkeeping method, retrieval process and infrastructure inadequacy

• Cultural difference/Heterogeneity of society

• Lack of complete and latest firms’ directories

Suggestions to remedy some of the challenges

There is need to sustain the ongoing Stakeholders’ forum to keep on sensitizing the business executives for their support and cooperation. An advance release calendar should be prepared and circulated to all stakeholders. Employers of labour in the firms too should build the capacity of their staff and train them on modern ways of keeping and retrieving data. There is need to promote private-public partnerships that will lead to development of robust database for the firms in the country. The Government too should help to promote data gathering in the country.

5. Conclusions

In this paper, the techniques, uses and the various challenges of Business Expectations Survey (BES) in Nigeria is described. The computational procedures of obtaining the business confidence indicators by using diffusion indices method were elucidated. Other areas stressed include how the indicator serves as basis for forecasting short-term business cycles and how it complements quantitative economic indicators. Both the endogenous and exogenous challenges ranging from weaknesses of institutional set-up, firm’s bureaucracy, poor record keeping, and low government support, among others were also discussed. The paper equally examined the information content of expectations survey and legal backing for its conduct by the Bank and gave some suggestions to remedy the challenges mentioned. Finally, the paper emphasized mutual understanding and strong network cooperation between data collecting agencies and the stakeholders.

References

[1]   | Central Bank of Nigeria (2012). Handbook of Statistical Methods.
[2]   | Doguwa, S.I., Olowofeso, O. E and Essien, S. I. (2011). Business outlook of small, medium and large scale enterprises: implication for monetary policy in Nigeria, IFC Bulletin, No.34, 236-247.
[3]   | Ece, D., Türknur H. and Oral, E. (2005). Building up a Real Sector Business Confidence Index for Turkey. Joint European Commission – OECD Workshop on International Development of Business and Consumer tendency surveys, Brussels.
[4]   | Habibullah, M.S. (1994). Do business firm in developing economy make rational economic forecast? The evidence from Malaysia business expectations survey of limited companies. Asian Economies, 23(4), 73-92.
[5]   | Habibullah, M.S. (1996). Forecasting economic variables in the agricultural sector: Testing rational expectations hypothesis on survey data. Pakistan Journal of Applied Economics, 12(2), 171-184.
[6]   | Habibullah, M.S. (2001). Rationality of insurance firms’ forecasts: Results of unbiasedness and efficiency tests. Malaysia Management Journal, 5(1&2), 107-117.
[7]   | Nilsson R. (1999), “Business Tendency Surveys and Cyclical Analysis”, Business Tendency Surveys, Proceedings of the First Joint OECD-ADB Workshop, Manila, November.
[8]   | Olowofeso O. E. and Doguwa, S. I. (2012). Consumer sentiment and confidence indices in Nigeria: a panel data analysis IFC Bulletin No 36, 191-216.
[9]   | Zaller J. and Feldman, S. (1992). A Simple Theory of the Survey Response: Answering Questions versus Revealing Preferences American Journal of Political Science, Vol. 36, No. 3, pp. 579-616.