National symbols, globalization, and the well-being of nations

Abstract

Migration flows are shaped by a complex combination of self-selection and out-selection mechanisms. In this paper, the authors analyze how existing diasporas (the stock of people born in a country and living in another one) affect the size and human-capital structure of current migration flows. The analysis exploits a bilateral data set on international migration by educational attainment from 195 countries to 30 developed countries in 1990 and 2000. Based on simple micro-foundations and controlling for various determinants of migration, the analysis finds that diasporas increase migration flows, lower the average educational level and lead to higher concentration of low-skill migrants. Interestingly, diasporas explain the majority of the variability of migration flows and selection. This suggests that, without changing the generosity of family reunion programs, education-based selection rules are likely to have a moderate impact. The results are highly robust to the econometric techniques, accounting for the large proportion of zeros and endogeneity problems.

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(((((REEPS))))) Resource & Engineering Economics Publications Services
The Shameless Knowledge Peddlers©
__________________________________________________________________________________________________________
REEPS WORKING PAPER No. 20091
National symbols, globalization, and the well-being of nations
Voxi Heinrich Amavilah
Abstract: I estimate the effects of national symbols and globalization on the well-being of 88 countries. I
find that conventional determinants of production affect national well-being, measured as human
development index (HDI). The effects on HDI of national symbols like national flag colors are unstable,
while those of globalization are strong, with social globalization having the strongest effect. The results
suggest that national symbols are important to national well-being, but nations gain more from global
interactions with other nations than from national pride. Even as there is a need for further research to
improve upon the results associated with the effects of national symbols, the policy implications of the
findings clearly recommend increased investment in material conditions of nations and globalization. JEL
Code: O43, O57, H77, F43, O11, D31, Z00
Keywords: National identity, national colors, globalization, well-being of nations, human development
index (HDI), national flag colors
REEPS papers are all copyrighted works-in-progress. They are available for personal, not commercial, purposes. Due
credit is expected; however, permission to use REEPS materials does not give any warranty, express or implied or
make any claim that the contents will be complete, accurate or up to date. Users cannot hope to transfer any liability to
REEPS or its authors whatsoever and howsoever.
c/o Voxi Heinrich Amavilah, Ph.D. PO Box 38061 Phoenix AZ 85069-8061 USA
Phone: (602) 505-3855 Email: vhsamavilah@gmail.com Google Keyword: amavilah

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1. Introduction
A decent state of well-being, however measured, is the ultimate objective of every
economic agent, nations included. While economic anthropologists and others are
convinced that the 'problems of production and distribution, of value and economic
motivation, of allocation of available means for the realization of desired ends, were
universals in human experience' (Herskovitz, 1964, p.7), performance economists
continue to ponder the deep causes of, and observed cross-country differences in, human
well-being. The continued pondering indicates incomplete knowledge and understanding
of the determinants of human well-being.
In this exploratory empirical paper I argue that, besides conventional factors and forces,
the well-being of nations depends on national symbols and global interactions. I represent
national symbols with national flags and national flag colors, and global interactions with
globalization. Then I utilize a simple production function approach to quantify the effects
of national symbols and globalization on human well-being in 2007. The assessment sheds
additional light on a worthwhile issue. Moreover, in the interactive world we live in,
national symbols and globalization seem policy incongruent. For instance, is the
preservation of national symbols consistent with global integration? If national symbols
and globalization both promote human well-being, what conclusions can policy infer from
such a result?
I find that the conventional factors and forces of capital and the growth of labor affect
national well-being positively and negatively, respectively. Increased globalization leads
to a higher HDI, but different types of globalization have different effects on HDI, with
the effect of social globalization being greater than the effect of political globalization,
which is in turn greater than the effect of economic globalization. National symbols have
mixed effects on HDI in terms of the estimate sign, magnitude, and statistical significance
(i.e., overall parameter efficiency). It generally appears that globalization and national
symbols represent competing forces - a maintained assertion for now. Tested is that
variations in HDI across broad geographic regions are approximately the same in terms of
magnitude and negative sign.
From the coefficients of conventional factors and forces I infer that GDP (PPP) per capita
is an essential determinant of national well-being. Non-economic factors like national
symbols affect national well-being; however, their effects are positive when considered in
isolation and negative in light of globalization, for example. Now whether nations seek to
strengthen their national independence or their global interdependence is a marginal
cost/benefit decision. In this analysis evidence favors globalization, especially social
globalization. This conclusion is not altered by regional variations, although the instability
of the estimated effects of national symbols indicates a need for further research on this
topic.
The remainder of the paper describes my journey, so to speak. In Section 2 below I outline
the scanty relevant literature. Section 3 focuses on the empirical analysis. First, it builds a

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1A literature that extends the HDI applications to poverty, gender, and other
issues of (in)equality and redistribution is fast growing.
model. Second, it describes the data, and thirdly, implements the model. Section 4
presents preliminary findings and their implications, while the final section makes a
tentative conclusion.
2. The scanty relevant literature
The literature on the human well-being of nations is vast, and the vastness makes
sense since well-being is ultimately the objective of every economic agent. As May
(2007) points out, the concept of utility in the microeconomic theory of consumer
behavior reflects the centrality of well-being in life. Quantitative measures of human
well-being (welfare) now attract considerable attention (Kahnemann, Diener, and
Schwarz, 2003, Bruni and Porta, 2007), but at the national and cross-national levels it
was not long ago when a breakthrough of sorts came by way of Anand and Sen’s
(1994) successful development of the first comprehensive index of human
development - the human development index. (HDI). The advantage of the HDI over
GDP per capita as a measure of well-being is that it is actually three-dimensional, and
potentially multidimensional.1 To-date major improvements have been made on the
first generation of HDI (Clark and McGillivray, 2007, Clarke and McGillivray, 2006,
Mishra and Nathan, 2008). Clearly, both the new and old literature indicate that
measured as happiness well-being is a function of economic and non-economic
factors. Key among economic factors is income which defines the consumer's
consumption possibilities. As a flow income depends on the stock of productive
resources and wealth. Building wealth and improving productive resources require
scare time and efforts for which leisure is an opportunity cost. Non-economic factors
include social, cultural, political, and psychological environments (see Hoselitz,
1952). Despite this acknowledgment, most literature still uses per capita income as a
proxy for human welfare.
In a related area, the nexus between economic growth and globalization draws mainly
from economic growth and trade theories. Hence, from Axel Dreher's (2003) finding
that globalization promotes economic growth, for example, many economists would
have no problem inferring that globalization is good for human well-being. Indur M.
Goklany (2002) observes positive the effects of globalization on human well-being,
and concludes that ‘... in terms of the truly critical measures of well-being - hunger,
infant mortality, life expectancy, child labor - the countries of the world are much
closer to being equal now than they were a few decades ago’ (p. 15). Yet continued
debate indicates globalization is not omni-good. For example, Ming-Chang Tsai
(2006) uses a random effect model to estimate the impacts of globalization on human
well-being, and finds a direct direct correlation between human development and
globalization. However, the positive effects are neutralized by the negative indirect
effects of globalizationby way of debilitated state power, nd increased social

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2The inspiration is an indirect one; it provided motivation in the face of
discouragement that such research is futile and silly.
spending and instability. In the end only the impacts of political globalization are
positive, ‘whereas economic and social globalization do not generate favorable
influences when development level and regional differences [serve] as controls’ (see
paper abstract). There is room for another look.
Moreover, while it is common to see regressions of economic growth that take as
arguments institutional aspects like corruption and constitutions, evidence about a
direct connection between well-being and its deeper 'causes' is still scanty. Inspired
by works about the value of cultural goods and services such as Kinsey (2002),
Throsby (2001), and Baumol and Bowen (1966), Amavilah (2OO8a) supposes a
relationship between national flags and national flag colors and HDI across 93
nations in 2007.2 He finds an inverse correlation between HDI and flag colors and a
positive relationship between flag existence and HDI. In another paper Amavilah
(2OO8b) also argues for a relationship between HDI on one side, and flags, flag colors,
number of original articles in a constitution, and number of constitutional changes on
the other. Again the results confirm the first paper, in addition to revealing negative
coefficients of the number of original articles of constitution, and number of
constitutional changes. The current paper augments Amavilah (2008a) by making
HDI a function of conventional factors and forces, national symbols, and
globalization.
Empirical analysis
This section outlines the model, data, and the model estimations.
3.1 Model
To quantify the effects of national symbols and globalization on the national well-
being of nations, I measure well-being by the human development index (HDI). I
follow the conventional wisdom in preferring HDI to per capita GDP because HDI is
a broader measure of human socio-economic development. It includes the knowledge
(education) of the population (H1), the health (life-expectancy) of the population
(H2), and the per capita material condition of the population (Y), see, e.g., Clark and
McGillivray (2007).
However, we also know from the works of Myrdal (1968), Blaug (1970), Cohn
(I979), Schultz (1981), Becker (1996), and many others that H1 and H2 are elements
of the human capital (H) component of the economically-active population (N).
Thus, human well-being indexed by N can be stated as

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3For the list of countries in this subsample of 88 and the whole sample of 93 see
Amavilah (2008a). For the subsample of 59 countries see Amavilah (2008b).
where a1 and a2 are weights. Moreover, Amavilah (2008c) argues that basing H on
the quality of labor (L) alone overestimates its importance. Rather,
we can claim that
, such that
where q is a vector of measures of the quality attributes of N. Now, if we suppose
that the material conditions (Y) of N evolve according to the Cobb-Douglas
transformation, and that L grows exogeneously at the rate n equal to the rate of
growth of N, then
where A = state of technology, L = labor, and K = physical capital. This means that
inserting (2) and (3) into (1) and simplifying gives
where t = 1 for cross-section data. Set
dividing through (4) by N and taking the natural logarithms on both sides leads to
Then
3.2. Data and data sources
I focus on 88 countries for which data is readily available (see also Amavilah, 2008a,
b).3 The data for HDI, N, and n are available from different places, including the
UNDP's World Human Development Reports (WDRs, various), the CIA's World
Factbook (various), and Wikipedia (2008). I rely on WDRs. Capital (K, k) is the
percentage of GDP that goes into fixed capital formation as given by the IMF's
Table 1 - Descriptive statistics
(1)
(2)
(3)
(4)
(5)

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Name
No.
Observations
Mean
St. Deviation
Variance
Minimum
Maximum
Country
88
44.500
25.547
652.670
1.000
88.000
HDI
88
0.789
0.156
0.0244
0.370
0.968
Population (N)
88
60.067
187.270
35071.000
0.300
1324.400
GDP(PPP)
88
657.740
1746.700
0.305E+07
2.900
13844.000
Capital(K)
88
22.612
5.715
32.658
9.780
42.610
Health (H1)
88
71.367
9.739
94.843
42.500
82.000
Education (H2)
88
87.044
17.579
309.030
12.800
99.900
Flag (White)
88
5.000
0.000
0.000
5.000
5.000
Flagcolors
88
13.795
5.268
27.751
2.000
37.000
N-growth (n)
88
1.259
2.497
6.233
-0.900
22.700
aGlobe
88
68.002
14.565
212.130
34.910
98.920
eGlobe
88
67.016
17.246
297.420
8.040
96.670
sGlobe
88
62.336
19.424
377.310
21.450
93.850
pGlobe
88
77.243
16.253
264.160
40.910
98.030

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4I acknowledge Dr Axel Dreher for an extended email conversation he and I had
about his papers and the KOF globalization. As usual, I attribute no blame to him for my
errors.
International Financial Statistical (IFS) Yearbook (2007). Human capital (H) has
two dimensions: Literacy rate/education (H1) and life expectancy (health) at birth
(H2). GDP (PPP) (Y) is per capita GDP in terms of purchasing power parity (PPP).
H1, H2, and Y are available from a variety of sources including the IFS, CIA, and
WDRs.
The two key variables of interest are national symbols and global interactions. As
indicated above, I represent national symbols and global interactions by national
flags and national flag colors, and globalization, respectively. To generate dummy
variables for national symbols, let White indicate the existence of a flag for each
country. Scanning national flags indicates that Blue (B), Red (R), Yellow (Y), Green
(G), and Black (BI) as common flag colors (see photius.com, 2008, flagpedia.net,
2008). Next I arbitrarily set W = 5, B = 4, R = 3, Y = 2, and Bl = 1 From here the
values of other colors are arbitrary combinations of dominant colors. For example
Green = Y x B = 2 x 4 = 8, Purple = Blue x Red = 4 x 3 = 12, and so on. Two
examples: The U.S. flag is Red, White, and Blue, on White. Since White on White is
White, the value is White + Red + Blue = 5 + 3 + 4 = 12. Cameroon's flag is Green,
Red, and Yellow, set on White. The dummy value in this case = White + Green + Red
+ Yellow = 5 + 8 + 3 + 2 = 18. By examining national flags for all 88 countries in the
sample, dummy variables for flag colors were generated, see Amavilah (2008a, b).
Globalization data
http://globalization.kof.ethz.ch/, and in Axel Dreher (2003) and Dreher, Gaston, and
Martens (2008).4 They come in one aggregate and three disaggregates. The aggregate
is called the ‘Index of Globalization’ (aGlobe). The three disaggregates are the ‘Index
of Economic Globalization’ (eGlobe), ‘Index of Social Globalization’ (sGlobe), and the
‘Index of Political Globalization’ (pGlobe). Table 1 presents descriptive statistics.
are KOF data available and explained at
Regional dummies take the value of one if a country is in a specific region and zero
otherwise. I divide the countries in five broad regions: Asia and Australia
(Australasia), Africa and the Middle East (AfriMidEast), North America
(NorthAmerica), South America (SouthAmerica), and Europe.
3.3 Model implementation

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Eq. (5) is the estimation equation. It does no longer include Y and H, both
dimensions of HDI already. Instead, in q I include national symbols and measured
elements of global interactions, where, again, national symbols are national flags and
national flag colors, and global interactions are globalization that can be either
aggregate or disaggregate. In other words, (5) is
I use the OLS estimator on (6), making the usual White’s (1980) adjustments for
statistical problems. I err in favor of economic significance vis-a-vis statistical
significance. I calculate regional HDI as follows:
4. Preliminary results and their implications
4.1 Non-essential results
I first estimate H in (1) in its education/literacy rate (H1) and its health/life expectancy
(H2) dimensions, and obtain
Since then (6) is the equivalent of
where
Table 2 - National symbols, globalization, and national well-being
(6)
(7)
(8)
(9)

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Variable
Estimation
2.1
Estimation
2.2
Estimation
2.3
Estimation
2.4
Estimation
2.5
Estimation
2.6
Conventional
•
Constant
•
Capital (k)
•
N-growth (n)
-1.909(-10.54)
0.034(1.27)
-0.003(-2.39)
-1.278(-7.15)
0.027(0.83)
-0.004(-3.36)
None
0.031(1.22)
-0.003(-2.12)
None
0.021(0.77)
-0.003(-2.56)
None
0.031(1.21)
-0.003(-2.15)
None
0.022(0.80)
-0.003(-2.60)
National symbols
•
Flagcolor (all)
•
Flagcolor (lessW)
0.010(0.57)
-0.019(-1.08)
0.009(0.54)
-0.021(-1.24)
0.001(0.74)
-0.002(-1.50)
Globalization
•
Average
•
Economic
•
Social
•
Political
0.613(17.78)
0.038(1.59)0.336(12.93)0.118(4.57)
0.614(12.45)
0.026(1.47) 0.343(11.92)0.085(3.71)
0.622(12.39)
0.025(1.50)0.343(11.90)0.094(3.60)
Region
•
Australasia
•
AfriMidEast
•
NorthAmerica
•
SouthAmerica
•
Europe
-1.878(-7.80)-1.923(-8.83)-1.901(-7.89)-1.870(-7.94)-1.016(-7.89)
-1.102(-5.54)-1.168(-6.29)-1.143(-5.77)-1.085(-5.64)-1.142(-5.67)
-1.893(-8.19)-1.937(-9.33) -1.916(-8.29)-1.884(-8.34)-1.932(-8.27)
-1.133(-6.0)-1.196(-6.9)-1.169(-6.3)-1.113(-6.1)-1.169(6.1)
Summary statistics
•
Adj. R-square
•
SEE
•
DW[D]
0.83110.06421.581[0.194]
0.82880.06461.378(0.130)
0.83890.06261.819[0.078]
0.84880.06071.635[0.171]
0.83930.06251.826[0.074]
0.84900.06071.637[0.17]
Table 3 - National symbols, globalization, and national well-being

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Variable
Estimation
3.1
Estimation
3.2
Estimation
3.3
Estimation
3.4
Estimation
3.5
Estimation
3.6
Conventional
•
Constant
•
Capital (k)
•
N-growth (n)
-1.845(-12.5)
0.033(1.2)
-1.40(-7.9)
0.29(0.9)
-0.004(-3.5)
None
0.031(1.2)
-0.003(-2.7)
None
0.023(0.8)
-0.003(-2.7)
-1.812(-13.1)
-1.364(-9.5)
Globalization
•
Average
•
Economic
•
Social
•
Political
0.604(19.7)
0.042(1.6)0.341(12.8) 0.125(4.9)
0.607(12.8)
0.029(1.4)0.346(11.8) 0.102(3.9)
0.620(19.2)
0.046(1.6)0.351(12.5)0.123(4.9)
Region
•
Australasia
•
AfriMidEast
•
NorthAmerica
•
SouthAmerica
•
Europe
-1.819(-8.6) -1.863(-9.8)-1.841(-8.8) -1.811(-8.7)-1.857(8.5)
-1.224(-6.7)-1.288(-7.6)-1.263(-6.9)-1.204(-6.8)-1.259(-6.9)
Summary statistics
•
Adj. R-square
•
SEE
•
DW[D]
0.8326 0.06381.567[0.202]
0.82870.06461.396[0.293]
0.84040.06241.804090.086)
0.84840.06071.645[0.166]
0.83120.06411.585[0.195]
0.82620.06501.394[0.29]

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Given a from (1) or (8), and $, (, and * from (5) or (6), it is conceptually
easy to show that - the hat (^)
indicates estimated as opposed to actual values. However, while the
results in (8) and (9) are illustrative, they are not the focus of this paper!
Even so, one can say in passing that it appears that for this group of
countries life-expectancy and per capita GDP have the largest weights,
and the net weight of H is only 0.1704, much smaller than that of per
capita GDP(PPP) at 0.8278.
4.2 Essential results
Tables 2 and 3 present essential estimation results. Across both tables and all estimations
it is clear that conventional factors and forces of capital and labor affect national well-
being (HDI) in important ways. Although not always statistically significant at the
assumed 5% level, the positive effect of investment on HDI ranges from two to four
percent. National well-being responds negatively to the growth rate of population - a
familiar result. It seems that material conditions are important to the national well-being
of this group of countries.
The relationship between national symbols and national well-being is rather unstable.
Taken either as national flag colors ( White + other colors) or just dominant flag colors,
national symbols have a positive but insignificant effect on HDI, when considered
without globalization or alongside aggregate (overall) globalization (aGlobe). However,
when globalization is disaggregated into economic (eGlobe), social (sGlobe), and
political (pGlobe) globalization, the effects of national symbols become negative. This
result suggests that although national symbols are important aspects of national well-
being, nations gain more from global interactions than from national isolation.
By how much do nations gain from globalization? Estimation results indicate that a
dollar's worth of an increase (improvement) in overall globalization adds no less than
$0.60 to HDI. Economic globalization has the smallest effect on the HDI of this group of
countries, followed by political globalization. An improvement of one dollar in social
globalization, for example, leads to a significant increase of about $0.35 in HDI. That
economic globalization has the smallest effect on HDI is surprising, and appears to
render support to the opponents of free international trade and finance. However, the
result may also be an aberration due in part to the fact that the sample is comprised of a
large number of countries with very high HDI for which gains from economic and
political globalization are potentially smaller than from social globalization. In a way the
benefits of globalization are in enhancing the mutual interdependence of nations. The
scope for mutual interdependence is greater in the sphere of social globalization than in
the economic and political spheres.

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Figure 1- National well-being under varying scenarios - Comparative statics I
0.30.40.50.60.70.8 0.9
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Well-being (HDI)
HDIHDI1 HDI2AHDI2B

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Figure 2 - National well-being under varying scenarios - Comparative statics II
0.150.250.350.450.550.650.75 0.850.951.051.15
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Well-being (HDI)
HDIHDI3AUHDI3AFHDI3NAHDI3SAHDI3EU

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Figure 3 - National well-being under varying scenarios - Comparative statics III
0.250.350.450.550.650.750.85 0.95
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Well-being
HDIHDI4AUHDI4AFHDI4NAHDI4SAHDI4EU

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Figure 4 - National well-being under varying scenarios - Comparative statics IV
0
0.20.4 0.60.8
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Well-being (HDI)
HDIHDI5AHDI5B