Background

Introduction

To be a successful exporter a country has to be internationally competitive. Measures of competitiveness can be used as well at the national, the regional, city, the sector or the cluster, as at the enterprise level (Van Dijk, 2006).2 At the national level for example the following factors are important, the so-called macro-economic and political underpinnings of competitiveness: stable political and economic environment and sound political & legal institutions. Other factors can be added ranging from the Human development index to the incentives provided to investors.

At the regional level we have suggestions in Van Dijk (2005) and in Noor (2007) for regional competitiveness indicators. These will be compared. The factors used by the World Bank and Goes and van Dijk (2006) for the knowledge economy are also provided, since they suggest a methodology that could be used for the regional competitiveness as well. In this note we then move to the operationalization of the proposed measure of regional competitiveness indicator.

Indicators for the knowledge economy

FDI attracted by a region, or even inward investments could be a good indicator of the region’s competitiveness. To remain competitive in the future it is important to develop an innovative milieu. Competitiveness only based on cheap labour will not last. A number of indicators can be selected to assess the competitiveness of regions (see Goes and Van Dijk, 2007). The operationalization of the concept of knowledge economy is presented in table 1.

Table 1: Operationalization of knowledge economy

Table 2: Variables measuring Competitiveness at the national and the regional level

A number of criteria can be used to select the relevant variables for a measure of regional competitiveness from table 2. The most important criteria for including them in a regional competitiveness indicator are: 

• The variable should have a theoretical relation with competitiveness. For example a human development index for a region may be interesting, but what would be the relation with regional competitiveness? Does a higher score mean more competitiveness? 
• The variable should be measurable, preferable by using several indicators. For example political stability or urban security is difficult to measure at the regional level. Also the development aid going to a region is difficult to measure exactly and the relation is also not clear (poorer region more aid, more successful ones less, unless the inequality remains big).
• Limit the number of variables to less than 10 (if there are currently 12, I expect that during the discussions and testing we will be able to drop a few, or we will not be able to measure certain indicators).
• The variables should not be overlapping, not measure the same phenomenon. For example innovation measured by number of graduates is very much similar to the variable educational level of the work force. Regional purchasing power is included in regional per capita GDP.
• Variables that can not be operationalized: regional governance, regional corruption or level of taxes.
• Exclude variables that are not relevant
• Reliability: the indicator should be measured at the same level by different people.
• Validity: the indicator should measure the concept it is supposed to measure
• The variable should not be relevant at the macro level only, like economic variables such as inflation, rate of interest and rate of exchange
• They should differentiate between regions
• They should not be correlated to each other.

An example: Doing business 2008

More interestingly for each variable a number of indicators were used, which together determine the score:

Eliminated from the table:

1. Regional health indicator, Healthy labour force will be more productive, Regional life expectancy, Expenditure on health. No relevant indicator was found at the regional level. Regional life expectancy
2. Doing business index, Developed to attract business, not available at the regional level and no other indicator was found
3. Agricultural potential, many countries follow an agriculture led development strategy, Indicators: Soil fertility, an indicator of agricultural productivity for example irrigation use, fertilizer use. Potential of agricultural sector would be covered by #2.

We agreed on the use of these variables and selected the indicators for the variables. It will now be necessary to scale all indicators between 1 and 10. In the following table suggestions are made for the indicators presented in table 4: how to measure and how to scale them. 

Table 5: From indicator to measurement and scaling

The rule should be that data are collected on the all indicators mentioned. The first one is the most important, but if data can be found on several indicators the information should be used although weighted by dividing it by the number of indicators (between 2 and 7). First the indicators should be standardized by converting them into the rank of 1 to 10 then they can be added up and divided accordingly.

The challenge will be to select a limited number of the variables in table 3 and to find good operationalizations for these variables (which could eventually be slightly different from region to region). Subsequently a radar will be constructed and the total score will be converted in a index value (a percentage of 100 is reduced to 10). If the region would score the maximum on all these indicators would lead to a score of 10 for regional competitiveness.