Delete search term


Quick navigation

Main navigation

Pillar description

In this section we describe the 5 pillars of the IT Nearshoring Index in more detail and why each respective pillar matters for Swiss IT service firms. We do not describe all variables that constitute a pillar, but provide a detailed description of the variables and source in an online Appendix.

Institutional pillar

The institutional pillar reflects political factors and their direct consequences for the offshoring decision. For example, it includes the regional quality of government given by Charron et al. (2015) to indicate ease of doing business and dealing with the government in that specific region. Underlying we assume that better institutions decrease the costs of doing business in a region as well as political uncertainty and thus creating a more stable economic environment.

Location pillar

The location pillar refers more generally to geographical factors of the nearshoring decision. We include for example the distance in kilometers between the potential nearshoring region and Berne – which is located in the center of Switzerland – or the number of airport passengers in a region to reflect the reachability of a region. Egger et al. (2018) have shown that physical distance and communication barriers represent obstacles for firms when engaging in international business. Variables reflecting transportation infrastructure and the reachability of a region have the highest weight within this pillar.

Economic pillar

The economic pillar considers direct economic measures. These can be often independent of institutions. For example, we include labor and corporate income taxes in this pillar, which are clearly an institutional/political outcome, but their value is not fully explained by institutional factors, i.e., France has good and high quality institutions and rather high corporate and labor tax rates. On the other hand, institutions in The Netherlands are equally good, but corporate tax rates are much lower. Our survey indicates that monetary factors are most important for Swiss IT firms in this pillar, thus the variables with the highest weight are inflation and stability of the currency exchange rate.

Labour pillar

The labour pillar reflects various dimensions of the local labour market. Specifically, IT labour supply and demand factors, as well as labour costs factors. Obviously, firms want to offshore to destinations with a high supply of skilled IT workers, which makes it easier to fill open vacancies. On the other hand, labor costs should be low, which raises the profitability of the nearshoring venture. For Swiss IT service firms the supply of skilled IT workers is much more important than the actual labor costs. Thus, the labor market tightness and the supply of IT workers in a region receive the highest weights in this pillar.

Social pillar

In the social pillar we consider all kinds of social factors that might affect firms’ offshoring decision. Foremost, cultural distance is an import factor and an often underestimate obstacle for firms operating in foreign markets. Research has shown that capabilities to use and to adjust to cultural difference is firm-specific, it is not possible to include these firm-specific dimension in our general social pillar. Thus, we include a broader measure of social factors at the regional level, as we assume that general cultural closeness facilitate the cultural adjustments on average. Specifically, we include a cultural distance measure of the region relative to Switzerland (as a whole country), which is taken from Kaasa et al. (2013), or language proximity taken from Melitz and Toubal (2014). Note that as Switzerland has four official language and can be divided in 3 mayor cultural areas (French, Italian and German speaking regions), the cultural distance and language measures reflect a Swiss average.

Detailed Pillar Description

Below the 5 different pillars are described in more detail including all individual variables. If not mentioned otherwise variables were taken from the Eurostat Regional Database.

1. Institutional pillar

a. EU/EEA member ship indicator at the country. Source: EU Commission
b. Schengen indicator at the country. Source: EU Commission
c. Doing business indicators at the country level. Source: Doing Business, The World Bank
i. Ease of starting a business score
ii. Ease of dealing with construction permits score
iii. Ease of getting electricity score
iv. Ease of registering property score
v. Strength of minority investors protection score
vi. Ease of paying taxes score
vii. Ease of trading across border score viii. Ease of enforcing contracts score
ix. Ease of resolving insolvency score

d. Rule of law index at the country. Source: The World Justice Project (2018)
e. Quality of government scores at the NUTS 1 region level. Source: by Charron and Lapuente (2015)
i. Overall score
ii. Impartility score, treating individuals and firms equally
iii. Corruption score in education, health care, law enforcement, elections, corruption experience iv. Education, health care and law enforcement quality score

f. Voter turnout in the last (general) election as a measure of political participation at the NUTS 1 region level

2. General location pillar

a. Physical distance between Bern and a NUTS 1 region in km
b. Number of airport passengers in 1,000 at NUTS 1 region as a measure of reachability
c. Motorways km per sq. km as a measure of infrastructure and mobility within the NUTS 1 region
d. Broadband access in % of population within NUTS 1 as a measure internet infrastructure
e. Common spoken official language in a country and Switzerland in % of population of the foreign country. Source: Mayer and Zignago (2011)
f. Percent of population speaking English. Source: English First Country Ranking
g. Office rental costs in EUR for 80% prime office space. Based on selected cities within the NUTS 1 region. Source: Cushmann & Wakefield, Occupancy Metrics

3. General economic pillar

a. Non-wage related labor costs (taxes, etc.) in percent of IT employees’ wage in NUTS 1 region
b. Corporate income tax in percent at the country level. Source: EY Worldwide Corporate Tax Guide (2018)
c. Inflation between 2015 and 2018. Taking 2015 as a base year
d. Variation in yearly exchange rates between the foreign currency and CHF between 2008 and 2018. Source: IMF Exchange Rates
e. Exchange rate trend between foreign currency and CHF between 2008 and 2018. Deprecation is better for Swiss firms. Source: IMF Exchange Rates
f. GDP in EURO in the NUTS 2 region
g. GDP per capita in EURO in the NUTS 2 region
h. GDP growth between 2014 and 2018 by NUTS region
i. Ease of getting credit score. Source: Doing Business, The World Bank

4. Labor market pillar

a. Employment in the IT sector relative to population in a NUTS 2 regions
b. Average hours worked per year and employee in the IT sector in a NUTS 1 region
c. Employment of young workers (25-34yrs) relative to IT overall employment in the IT sector at NUTS 1 region
d. Vacancy rate in the IT sector in percent of IT employees in a NUTS 1 region
e. Hourly labor costs (wages and bonus) in EURO in the IT sector in NUTS 2 region
f. Labor costs growth in % between 2016 and 2012 in the IT sector

5. Social pillar

a. Purchasing Power Standard (PPS) adjusted GDP per capita in a NUTS 2 region as a measure of economic wellbeing
b. Number of hotel beds in a NUTS 1 region as a measure of regional beauty/attractiveness
c. Number of expats in a country as a measure of openness towards foreigners
d. Life expectancy in years at the NUTS 2 region
e. Number of medical doctors per capita as measure of health system quality at the NUTS 1 region
f. Number of hospital beds per capita as measure of health system quality at the NUTS 1 region
g. Language proximity as measure of cultural closeness and ease of communication at the country level. This is not the same as common language, i.e., Italian and Spanish are language wise closer than Italian and German. Source: Melitz and Toubal (2014)
h. Number of Swiss expats in a country as measure of cultural closeness and possible contacts. Source: EDA Auslandschweizerstatistik
i. Murder rate per 100,000 inhabitants at the country level as measure of danger.
j. Cultural distance index between Switzerland and a NUTS 1 region. Source: Kaasa et al. (2013)
k. Power distance index between Switzerland and a NUTS 1 region. Source Kaasa et al. (2013)
l. Uncertainty avoidance distance between Switzerland and a NUTS 1 region. Source: Kaasa et al. (2013)
m. Masculinity distance between Switzerland and a NUTS 1 region. Source: Kaasa et al. (2013) n. Individualism distance index between Switzerland and a NUTS 1 region. Source: Kaasa et al. (2013)


Eurostat Regional Database
Melitz, Jacques & Toubal, Farid, 2014. "Native language, spoken language, translation and trade," Journal of International Economics, Elsevier, vol. 93(2), pages 351-363.
EDA Auslandschweizerstatistik
Kaasa, A., Vadi, M., & Varblane, U. (2013). European Social Survey as a source of new cultural dimensions estimates for regions. International Journal of Cross Cultural Management, 13(2), 137–157

Wikipedia EU/EEA and Schengen Area Membership
Doing Business, The World Bank

The World Justice Project (2018)
Charron, N., Dijkstra, L., & Lapuente, V. (2015). Mapping the regional divide in Europe: A measure for assessing quality of government in 206 European regions. Social Indicators Research, 122(2), 315-346.

Mayer, T. & Zignago, S. (2011) Notes on CEPII’s distances measures: the GeoDist Database
CEPII Working Paper 2011-25

English First Country Ranking

Cushmann & Wakefield, Occupancy Metrics
EY Worldwide Cooporate Tax Guide (2018)
IMF Exchange Rates