Appendix 2: Constructing a composite investment climate index.
When making an investment decision, entrepreneurs look at a host of factors. These range from cost of inputs, to reliability of infrastructure, to quality of institutions. A sound investment climate indicator should take into account as many of these factors as possible. The investment climate index (ICI) has been built on 44 investment climate variables. The data used were collected in the Enterprise Survey conducted in 11 states in Nigeria in 2007.
For simplicity, the variables are grouped in three categories: inputs, infrastructure, and institutions (Appendix table 5). Within each category two dimensions are identified: objective values (cost) and subjective indicators (perception). As a result of this classification, the 44 variables were grouped in six sets (subindices) that represent the backbone of the ICI and that aim at measuring the cost and quality of infrastructure services, of input markets, and of institutions. Overall, of the 44 variables used, 28 are cost and 16 are perception based. The ICI was then constructed as the weighted index of all subindices. Principal component analysis was used to aggregate the variables because this methodology allows us to identify which variables vary most and hence are more important in determining the quality of the investment climate across Nigerian states. (1)
Because there is no theoretical model on the estimation of the weights used in the construction of the index, the reliability of the ICI as a predictor of a good investment climate should be tested by correlating the ICI to indicators of state-level economic performance. Unfortunately there are no available data at the state level in Nigeria for indicators such as domestic private investment, GDP growth, FDI, and per capita income growth. Nevertheless in similar studies in 16 Indian states and in 24 ECA countries, the ICI showed a clear and significant association with all these indicators. (2)
The only state-level indicator available in Nigeria is the Doing Business indicator. A correlation between the ICI and the DB indicator (Appendix figure 1) shows a significant association between the quality of the regulatory environment and the quality of the overall investment climate in our states. (3)
An additional test of reliability was conducted by comparing the state ranking of the ICI with the ranking derived from the perceptions of the managers interviewed during the Enterprise Survey in Nigeria. All the managers were also asked to rank the best and worst states in Nigeria according to what they perceived their business environment to be. Appendix figure 2 presents the ranking of the 11 states according to the responses to this question, and Appendix figure 3 presents how the managers' ranking correlates to the ICI ranking for our 11 states. Again the data show a significant association between the ICI and managers' state-level rankings. (4) These tests--along with earlier evidence--provide a certain degree of confidence that the composite ICI is a reliable indicator of the investment climate in Nigeria.
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(1.) See the full study for a more detailed and technical presentation of the methodology used.
(2.) The relation between the ICI and private state-level investment in 16 Indian states has been shown to be significant at the 12 percent or 6 percent significance level, depending on the number of outliers excluded. In earlier work in a set of 24 ECA countries, this relationship was shown to be significant (see Iarossi et al. 2007. "Business Climate, Productivity and Competitiveness in Armenia: 2002-2005." Armenian Journal of Public Policy 2 (2): 153-91).
(3.) Sokoto is excluded because it is an outlier, that is, the correlation does not hold for Sokoto.
(4.) The only outlier is Lagos, perceived by Nigerian managers as the best state.
Appendix Table 5 Variables Used in Construction of Composite Investment Climate Index (ICI) Cost Perception Infrastructure 1. Size of inventory (transport 1. Electricity constraint quality) 2. Transport constraint 2. Power outages: hrs per shift 3. Access to land constraint 3. Water outages: hrs per shift 4. Power outages: losses (% sales) 5. Own generator (share of firms) 6. Electricity from own generator (%) 7. Own tranportation (share of firms) 8. Use of own transportation (% of sales) Inputs 1. Sales sold on credit (%) 1. Access to finance constraint 2. Sales as intermediate 2. Cost of finance constraint: products (%) Short term 3. Inputs paid before delivery (%) 3. Inadequately educated 4. Improved production processes workforce constraint (share of firms) 5. Workforce absenteeism: HIV/AIDS 6. Intereste rate on short-term finance 7. Share of long-term financing (equity) 8. Share of firms with loan 9. Share of firms that need a loan but do not apply 10. Workforce absenteeism: Malaria Institutions 1. Degree of competition 1. Customs constraint 2. Losses due to theft (% sales) 2. Crime constraint 3. Bribes for government contract 3. Corruption constraint (% value) 4. Licensing & permits 4. Electric connection days constraint 5. Degree of gifts requested: 5. Tax rates constraint Construction 6. Tax administration 6. Visits by tax officials constraint 7. Tax evasion (% sales) 7. Functioning of courts 8. Customers' purchase orders constraint in writing 8. Political environment 9. Cost of state regulations constraint 10. Cost of federal regulations 9. Labor regulations constraint 10. Practise of informal sector constraint