Factor Endowments

The factor endowments are an equally important part of the Mauritian computable

general equilibrium model’s computation. First, there are three primary inputs explicitly defined in the model, skilled labor, unskilled labor, and capital. The data for aggregate labor and capital is supplied through an e-mail correspondence with the Central Statistics Office of the

Government of Mauritius.¹⁷⁰ The e-mail provides the compensation of employees and the gross operating surplus by economic activity. Further aggregation of these reported numbers led to obtaining the compensation of employees and the gross operating surplus by sectors.

However, to obtain the labor disaggregation of skilled and unskilled workers, the 2000 Population Census is employed.¹⁷¹ Given the disaggregation is typically based on wage income, I choose this methodology as well. Since wage data across the 11 sectors outlined in the

Mauritian economy is not available, I had to compile it. First, to obtain the mixture of skilled and unskilled laborers for the model, I had to calculate the shares by labor types for the specified industries listed in the Census Report. There are eight major occupational groups and 14

170 The data comes from an e-mail correspondence with Mukesh Dawoonauth at the Central Statistics Office of the Government of Mauritius. Table 1.15 – Production and Generation of Income Accounts by Kind of Economic Activity, 1997-1999, supplies the compensation of employees and gross operating surplus for 1997. Further aggregation by sector occurs to match what was presented in Table 1.15 with the 11 sectors of the 1997 Input-Output Table computed by the Author. For further details, see Appendix D.

171 From an e-mail correspondence with Mukesh Dawoonauth at the Central Statistics Office of the Government of Mauritius, I was alerted that the population census would have occupational data, but that it was only given every 10 years. So, I picked the 2000 Population Census for this study given that the benchmark year for this study is 1997, assuming that the occupational mix of employees and incomes would be the same in 1997 as it was in 2000.

industries found in Table CA13-Current Employed Population 12 Years of Age and Over by Industry (Section), Major Occupational Group and Sex.¹⁷²

Once the labor share by industry groupings is calculated, the earnings by labor type have to be calculated. Table CA30 – Currently Employed Population 12 Years of Age and Over by Income Received for the Month of June 2000, Major Occupational Group and Sex reports the total income received for the month in increments (i.e. Less Than 1,000, 1,000 – 1,499, …, Greater Than 30,000 rupees) supplies the total income across the various occupational types.

So, I first augment the total number of laborers assuming the share of laborers by occupation types remained constant, adding the “Not Stated” laborers to the income ranges by share of total laborers in that income range. Then, I calculate, using the midpoint of the income ranges, the total income by occupation. Next, I calculate the weighted average of incomes by occupational group, yielding the monthly wage. The yearly wage by occupational groups is then calculated assuming the same monthly wage across all months.

After I compute the yearly incomes by sector for each occupational group, I had to calculate the skilled and unskilled share of total income for the year. Skilled laborer groupings are determined by the percentage of laborers with some college or higher educational attainment.

I divide the sum of skilled labor income by total income for that year (i.e. Legislator, Senior Officials, and Managers; Professionals; Technicians and Associate Professionals; and Clerks) across all sectors. Likewise, to compute the unskilled share of total income, I divide the sum of

172 The major occupational groups are Legislators, Senior Officials and Managers; Professionals; Technicians and Associate Professionals; Clerks; Service Workers and Shop Sales Workers; Skilled Agricultural and Fishery Workers; Craft and Related Trades Workers; Plant and Machine Operators and Assemblers; and Elementary Occupations and the industry grouping includes Agriculture, Hunting, Forestry, and Fishing; Mining and Quarrying;

Manufacturing; Electricity, Gas, and Water; Construction; Wholesale and Retail Trade, Repair of Motor Vehicles and Personal and Household Goods; Hotels and Restaurants; Transport, Storage and Communications; Financial Intermediation; Real Estate, Renting and Business Activities; Public Administration and Defense, Compulsory Social Security; Education; Health and Social Work; and Other Services. The information comes from http://ncb.intnet.mu/cso/report/hpcen00/econo/ca13repb.htm, accessed April 10, 2003.

unskilled labor income by the total income for that year (i.e. Service Workers and Shop Sales Workers; Skilled Agricultural and Fishery Workers; Craft and Related Trades Workers; Plant and Machine Operators and Assemblers; and Elementary Occupations). Lastly, the sectoral aggregation that matches the Mauritius model was implemented, causing the skilled and

unskilled share by sector to range from 9.34% to 70.89% percent for skilled workers and 29.11%

- 90.66% for unskilled workers.¹⁷³ Table 10 represents the labor share data which calibrates 1997.

Table 10: Skilled and Unskilled Labor Shares by Sector (Percentage)

Sector Skilled Labor Share of Total Labor

Electricity, Gas, and Water 60.47% 39.53%

Construction 14.70% 85.30%

As evidenced by Table 10, the Electricity, Gas, and Water and Other Services sectors’ labor input is primarily skilled. Meanwhile, the Sugarcane, Other Agriculture, Sugar Milling, Export

173 The Sugarcane and Other Agriculture sectors’ labor shares are adopted from the labor shares found for the Agriculture, Hunting, Forestry, and Fishing sector. The Sugar Milling, Export Processing Zone Manufacturing, and the Other Manufacturing sectors are represented by the labor share numbers’ computation from the aggregate of the Mining and Quarrying and the Manufacturing columns. Also, the Other Services sector’s share numbers are computed after aggregating the Financial Intermediation; Real Estate, Renting, and Business Activities; Public Administration and Defense, Compulsory Social Security; Education; Health and Social Work, and the Other Services columns together.

Processing Zone Manufacturing, Construction, Restaurants and Hotels, and the Transport, Storage, and Communication sectors’ labor is largely unskilled. Therefore, the majority of the sectors in the Mauritian economy employ more unskilled laborers than skilled laborers.