A Proposal for a Standard With Innovation Management System

Oscar Cristi, José Ernesto Amorós and Juan Pablo Couyoumdjian
countries participating in the GEM project. Self-employment jobs are defined as those jobs where “the
remuneration is directly dependent upon the profits (or the potential for profits) derived from the goods
and services produced”.
TheShadow Economic Index (SEI) built by Schneider et al. (2010) estimates the size of shadow
economy in 162 countries from 1999 to 2007. This measurement uses data on a set of variables that
may cause a shadow economy: share of direct taxation; size of government; fiscal freedom; business
freedom index; government effectiveness, unemployment rate and Gross Domestic Product per
capita. Here the size of the shadow economy is expressed as a percentage of Gross Domestic
Product.
For a country’s level of economic developmentwe use the Human Development Index(HDI) calculated
by the United Nations Development Programme and published in the Human Development Reports.
The HDI is a composite index that measures average achievement in a country by evaluating three
dimensions of human development: life expectancy at birth (long and healthy life), adult literacy rate
(education and knowledge) and Gross Domestic Product per capita in purchasing power parities
(decent standard of living). These dimensions reflect the major themes and topics related to poverty
definitionsas described by Misturelli and Heffernan (2008). The HDI takes values from 0 to 1 where 1
stands for the highest attainment.
3.2 Proposed model and estimation procedures
We are interestedin modeling a country’s development trend, i.e the changes of this variable through
time, as a function of a country’s moving average values of informality,as well as othercountry-specific
characteristics such as institutional variables. We define our variables like this with the purpose of
accounting for the lagged effects of the informal economy on development. In general, our model
takes the form:
Development indexit- Development indexit-s= α0+ α1Average size informal sectorit+ αi+εit
where t and s denotes years; i denotes a country; α0 and α1are unknown parameters; parameters
αiare country-specific effects that capture unobserved country´s institutional settings; and εit are
random disturbances distributed with 0 mean (E[εit]=0).
We use two alternative measures of changes in development for each country: the change in HDI
and the change in a Non-Income Human Development Index (NIHDI). The HDI is calculated as the
geometric mean of normalized indices for life expectancy, education, and income per capita. As a
result, a country’s per capita GDP is correlated with HDI directly and also indirectly through the impact
of income on life expectancy and education. In fact, the correlation coefficient between HDI and per
capita GDP for our sample is 0.85. However, the fact that the correlation between these variables is
not perfect suggests that there are factors other than achieved GDP that drive human development.
In addition, some countries are better than others at translating income into human development. Our
NIHDI is important because it captures the fraction of HDI that is not due to GDP. Appendix A
describes in detail the procedure used to calculate this NIHDI.
Measures for the average size of the informal sector, as we discussed in the previous sections are: a)
each country’s moving average of NEC; b) each country’s moving average of SE; and c) each
country’s moving average of SEI.
For empirical purposes we consider the change in HDI over a five year-period for each country as
function of the each country’s five years moving average of NEC . We choose a five year period to be
consistent with the Human Development Index report that calculates the short-term progress of
human development as the change in the HDI over that same time period. In the case of changes in
HDI as a function of the moving average of SE and of changes in NIHDI as a function of the moving
average of SEI we test the relationships for a four year period to avoid losing too many observations.
We do not test for the relationship between changes in HDI and changes in SEI due to collinearity
issues since both indexes are a function of GDP per capita.
In our proposed models there may exist a bi-directional causality between the different measures of
informal economy and HDI or NIHDI. Suspicion of this problem arises from previous studies that show
an effect of Gross Domestic Product per capita, which is included on HDI, upon entrepreneurial
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