The 7-I Framework posits a prescription for development of nations. This paper evaluates the framework, and lays down an empirical foundation for it.

1. The 7-I Framework
of Development:
The Path to
a Sustainable
Economy
by Mohit Sauparn and Vivek Pundir
MBA Class of 2006
Emory University
for Prof. Jeff Rosensweig’s
BUS503: Global Macroeconomic Perspectives

2. Term Paper: The 7-I’s of Development
Mohit Sauparn, Vivek Pundir
Term Paper: The 7-I’s of Development
Submitted to: Prof. Jeff Rosensweig
Global Macroeconomic Perspectives
INTRODUCTION
Development is an issue that has bewildered economists for a long time. In fact, even
defining the term is so hairy that they haven’t been able to agree even on that.
Some early economic thought equated development with industrialization and
mechanization. Over time this has given way to talk about sustainable development.
The government of British Columbia, Canada thinks it means “the advancement of the
management and use of natural resources to satisfy human needs and improve the
quality of human life. For development to be sustainable it must take account of social
and ecological factors, as well as economic ones, of the living and non-living resource
base, and of the long-term and short-term advantages and disadvantages of alternative
actions.”
"In an international context", says InterEnvironment, "(development) refers to
improving the economic and social conditions of poorer countries."
The United Nations Strategy for Disaster Reduction accepts the definition provided by
the 1987 Brundtland Commission: "Development that meets the needs of the present
without compromising the ability of future generations to meet their own needs. It
contains within it two key concepts: the concept of "needs", in particular the essential
needs of the world's poor, to which overriding priority should be given; and the idea of
limitations imposed by the state of technology and social organization on the
environment's ability to meet present and the future needs."
Page 1 of 46

3. Term Paper: The 7-I’s of Development
Mohit Sauparn, Vivek Pundir
We like the definition used by “Botany from Vermont” website in the context of the
development of biological organisms, “Growth and maturation of an organism or some
part of it.” If one replaces “organism” by “nation”, this definition probably conveys, to
a large extent, the concept of development. Admittedly, though, this definition is rather
vague, and does not do much to further the operational understanding of the term.
Having said that, we think that it does give a flavor of the meaning in a “The Fortune at
the Bottom of the Pyramid” sense. Thus, while a society or nation is clearly
underdeveloped if it is severely impaired by economic constraints, economic wealth, of
and by itself, is not a guarantee of development. Wealth is a necessary, but not
sufficient condition, when it comes to development. If the wealth is distributed
extremely unevenly so that while the nation is rich overall, the average citizen lies
under the poverty level, or if the wealth does not translate into health, well-being,
political and civil liberties etc., it is effectively meaningless.
In this context, Prof. Jeff Rosensweig of Emory University has proposed a 7 I’s
framework of development. According to this framework, there are seven essential
components/ pre-requisites of development:
1. Investment – Investment is the first prerequisite for development, and the only way
to grow the economy. While a consumption binge can inflate growth figures for a
short while, no development or growth can be sustained without judicious
investment into productive assets/ capital.
2. Intellectual capital (investment in broad-based education) – While economists have
gone to great length discussing capital investments, not many (with the exception of
developmental economists like Nobel-laureate Amartya Sen) have done significant
work that indicates intellectual capital is often as important as, if not more important
than, physical capital in the development of a nation.
3. Incentives – While there may be many pieces of the puzzle in place, a nation will
not develop unless its incentive structure encourages people to work hard, to save,
to invest etc.
Page 2 of 46

4. Term Paper: The 7-I’s of Development
Mohit Sauparn, Vivek Pundir
4. Incorrupt society – Corruption can be a huge bugbear for development, and
according to Prof. Rosensweig, an incorrupt society is an absolute must-have for
development.
5. Infrastructure – Good infrastructure is absolutely essential for the holistic economic
development of a nation.
6. Information – Information wants to be free. And how freely information can flow in
the country, in view of legal, regulatory, technical and cultural framework, is an
indicator of development as well.
7. Internationalization – How integrated the country’s economy is with the rest of the
world is another factor that affects its stage of development. The higher the
internationalization, the quicker will the nation develop.
While this framework has sound theoretical basis, and provides a solid prescriptive
formula for nations aspiring to achieve economic growth for the millions mired in
poverty, we are not aware of any empirical study validating it. This paper attempts a
“first cut” empirical study of the framework.
METHODO LOGY
Our methodology is relatively simple. We sought to test a causal relationship between
development and the 7I’s using multivariate regression.
The challenge was to operationalize the 7 I’s so as to be able to devise some sort of
measures for them. While some of these I’s initially appear to be rather touchy-feely,
we believe that it is possible to use hard variables as proxies for these.
While development was a contentious issue, both of us agreed that the best way to think
about sustainable development is to think of purchasing power parity adjusted per capita
gross domestic product as it gives a very good sense of the average standard of living in
the country.
Page 3 of 46

5. Term Paper: The 7-I’s of Development
Mohit Sauparn, Vivek Pundir
Investment was relatively simple, as there are already several measures of investment.
Our task was simply to choose the one that provided the best explanation of variance
and “goodness of fit”.
For broad-based intellectual development, we thought of several candidates, including
public spending in education as a percentage of GDP, research and development
spending as a percentage of GDP, enrolment in primary schools, etc.
Incentives were the toughest ones to find a proxy for. The only direct way to somehow
measure incentives is to conduct a comprehensive study of all countries, with the
benefit of local knowledge, and then to assign subjective ratings to the incentive
structure using some sort of a composite scale. We simplified that. Incentives are only
as good as their effect. So, we decided to measure incentives in terms of their efficacy –
if a nation saves more, we assume that it incentivizes saving. Similarly, if a nation
works more hours per week then it incentivizes hard-work.
To measure corruption, we turned to the Transparency International’s world corruption
perception index, and used that as a reliable measure of incorrupt society.
Infrastructure was another relatively simple one – roads, rails, airports etc. were all
indicators of the country’s infrastructure. To adjust for sizes, we used density, rather
than absolute numbers.
Information dissemination was a sticky one. We turned to the Freedom House’s report
to figure out how the countries rate on civil liberties (speech, media etc). We also used
the penetration of communication methods like cellphones and landlines as candidates.
For measuring internationalization we simply picked up various measures of
international trade as they relate to the GDP, with the intention of using the one with
most explanatory power in the model.
While we were armed with hard data on these factors, we were aware that our results
would be ballpark results, not the exact numbers since the data were not available for
the same recent period for all parameters, and some data were unavailable for some
nations.
Page 4 of 46

6. Term Paper: The 7-I’s of Development
Mohit Sauparn, Vivek Pundir
AN AL YSI S
After trying several different models, we decided on this model, which we are quite
happy with as it explains over 85% of the variance in PPP-adjusted GDP per capita.
Goodness of fit statistics:
Observations 208.000
Sum of weights 208.000
DF 198.000
R² 0.859
Adjusted R² 0.852
MSE 12801210.958
RMSE 3577.878
MAPE 64.820
DW 2.005
Cp 10.000
AIC 3413.682
SBC 3447.057
PC 0.156
The equation for this regression line is as follows:
GDPPCPPP = -8204.53112615424 +61.9373042307306*BAL
+2387.32901048343*CORRUPTION +880.87796966936*R&D%
+30.8696289658526*ENROLGIRLS -56.8623451913472*INFO
+7.83828124045985*CELL -4.17308720949926*SAVING%
+89.0292019987179*FDI% +0.60806418126927*AIRDENS
One variable that we really wanted in the model was the number of work hours per
week, but couldn’t do so as the ILO data that we were able to retrieve had too few data-
points.
Page 5 of 46

7. Term Paper: The 7-I’s of Development
Mohit Sauparn, Vivek Pundir
GDPPCPPP / Standardized coefficients
(95% conf. interval)
CORRUPTION
0.7
0.6
0.5
Standardized coefficients
CELL
0.4
FDI%
0.3
ENROLGIRLS
0.2
AIRDENS
R&D%
BAL
0.1
0
SAVING%
INFO
-0.1
-0.2
Variable
The most amazing thing is that as it turns out, a corruption free society (as indicated by
corruption above) is paramount for economic growth followed closely by free flow of
information (as indicated by cell and negative of info above). The next good thing a
government can do is make the economic climate conducive to foreign direct
investment.
Model parameters:
Source Value Standard error t Pr > |t| Lower bound (95%) Upper bound (95%)
Intercept -8204.531 2166.061 -3.788 0.000 -12476.041 -3933.022
BAL 61.937 33.176 1.867 0.063 -3.486 127.360
CORRUPTION 2387.329 219.421 10.880 < 0.0001 1954.627 2820.031
R&D% 880.878 520.037 1.694 0.092 -144.644 1906.400
ENROLGIRLS 30.870 16.008 1.928 0.055 -0.699 62.439
INFO -56.862 185.242 -0.307 0.759 -422.163 308.438
CELL 7.838 0.943 8.310 < 0.0001 5.978 9.698
SAVING% -4.173 32.954 -0.127 0.899 -69.159 60.813
FDI% 89.029 13.152 6.769 < 0.0001 63.093 114.966
AIRDENS 0.608 1.505 0.404 0.687 -2.359 3.575
The model is overall quite good. However, as we observe from the T and p values
above, civic liberties, savings as a % of GDP and air flights per sq. km of land aren’t
statistically significant in the model. We believe that a major reason is the lack of good
data on these factors. A dataset that has more data on these should validate the positive
coefficients (we asked our statistical software to estimate missing values – which
explains the low significance).
Page 6 of 46

8. Term Paper: The 7-I’s of Development
Mohit Sauparn, Vivek Pundir
Standardized coefficients:
Source Value Standard error t Pr > |t| Lower bound (95%) Upper bound (95%)
BAL 0.086 0.046 1.867 0.063 -0.005 0.177
CORRUPTION 0.486 0.045 10.880 < 0.0001 0.398 0.574
R&D% 0.052 0.031 1.694 0.092 -0.009 0.113
ENROLGIRLS 0.054 0.028 1.928 0.055 -0.001 0.110
INFO -0.011 0.035 -0.307 0.759 -0.079 0.058
CELL 0.352 0.042 8.310 < 0.0001 0.268 0.435
SAVING% -0.006 0.046 -0.127 0.899 -0.096 0.084
FDI% 0.236 0.035 6.769 < 0.0001 0.167 0.305
AIRDENS 0.014 0.034 0.404 0.687 -0.053 0.081
Even in terms of standardized coefficients (real coefficients, stripped of units),
corruption-freeness, information flow, and FDI turn out to be the most influential
factors, and these should be the priorities of any developing nation.
GDPPCPPP / Standardized residuals
4
3
Standardized residuals
2
1
0
0 10000 20000 30000 40000 50000 60000 70000
-1
-2
-3
GDPPCPPP
Page 7 of 46

9. Term Paper: The 7-I’s of Development
Mohit Sauparn, Vivek Pundir
Pred(GDPPCPPP) / Standardized residuals
4
3
Standardized residuals
2
1
0
-10000 0 10000 20000 30000 40000 50000 60000 70000
-1
-2
-3
Pred(GDPPCPPP)
Pred(GDPPCPPP) / GDPPCPPP
70000
60000
50000
40000
GDPPCPPP
30000
20000
10000
0
-10000 0 10000 20000 30000 40000 50000 60000 70000
-10000
Pred(GDPPCPPP)
Page 8 of 46

10. Term Paper: The 7-I’s of Development
Mohit Sauparn, Vivek Pundir
Standardized residuals / GDPPCPPP
Obs196
Obs181
Obs166
Obs151
Obs136
Observations
Obs121
Obs106
Obs91
Obs76
Obs61
Obs46
Obs31
Obs16
Obs1
-4 -3 -2 -1 0 1 2 3 4
Standardized residuals
The residual charts above further strengthen our belief in a good fit, and validate the
model further.
Having said that, we believe that if more data is available, it would be worthwhile to
conduct a factor analysis, and then run an explanatory multivariate regression. The
cleaner data, with more data points, combined with this analysis could lead to the 7I’s
explaining up to 92% of the variance in the standards of living in different countries.
Having gone over the statistical relationship of development and the 7 I’s, we decided
to have a quick look at how GDP growth relates to the PPP-adjusted GDP per-capita.
In the chart below, the bars represent the PPP-adjusted GDP per-capita, and are scaled
to the left y-axis. The line with rhombus data-points represents the GDP growth %, and
is measured on the right y-axis. The data are arranged in descending order of PPP-
adjusted GDP per-capita. The smooth, thick line is a trend-line for GDP growth. While
there are wild variations in GDP growth, the trend-line is unequivocal about the
relationship. There is a clear, non-linear relation between GDP growth and PPP-
adjusted GDP per-capita, and growth peaks around the middle values of PPP-adjusted
GDP per-capita. While the developed nations are slow to grow (matured?), the
“emerging economies” are really driving growth.
Page 9 of 46