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Cmss Vi Nations Units Analysis
 

Cmss Vi Nations Units Analysis

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  • These are usually quantifiable measures characterizing the property of the distribution of a variable among individuals, typically constructed from the census or survey data. Do not use them as dependent variables while making inferences about the behavior of individuals. This would lead to ecological (aggregation) fallacy.
  • Measures of exchanging and networking These are relatively difficult to construct variables since they involve relationships among system elements. The danger is that the created variables involve dependencies. Imagine that you analyze flow of people among two regions, A and B, and you construct the increase of migratory population for the region A, IA = in-migration – out-migration. Your measure for region B, IB, would depend on IA. Thus, the one measure is redundant. Which you will choose? Could be used as dependent variables.
  • Countries are units of analyses. You have as many units as you have countries
  • These are usually quantifiable measures characterizing the property of the distribution of a variable among individuals, typically constructed from the census or survey data. Do not use them as dependent variables while making inferences about the behavior of individuals. This would lead to ecological (aggregation) fallacy.
  • These measures are computed by three different methods: (1) Value of the output. The most difficult method since it involves pricing flow of goods and services in the economy of a nation (2) Expenditure. It means: (A) All personal spending, plus (B) all government spending, plus (C) all investment spending by a nation's industry both domestically and all over the world. (3) Earnings and cost approach, in which all forms of wages and income, such as corporate profits, net interest returns, rent, indirect business taxes, and unincorporated income are added together. All three methods produce the same result.
  • These are usually quantifiable measures characterizing the property of the distribution of a variable among individuals, typically constructed from the census or survey data. Do not use them as dependent variables while making inferences about the behavior of individuals. This would lead to ecological (aggregation) fallacy.
  • It was developed for the Overseas Development Council in 1979 by Morris Davis Morris. PQLI is an improvement but there is considerable overlap between infant mortality and life expectancy.
  • Functional literacy is a level of reading and writing sufficient for everyday life but not for completely autonomous activity.
  • Functional literacy is a level of reading and writing sufficient for everyday life but not for completely autonomous activity.
  • Such initiatives have continued and have inspired four of the most dominant and enduring indicators of democracy that use scales Also, the Democratization Index put forth by the Economist
  • Two sources produce regularly updated mass data on a variety of countries: Global Barometer Surveys ; the World Values Surveys
  • You must decide what you want to represent/ If the whole world – be sure to have countries from all region. If you concerned with countries which have a sizable population, remove those with less than a million inhabitance (N decreases to 145). And so on.
  • The tradition of regime classification has continued and is best represented by:

Cmss Vi Nations Units Analysis Cmss Vi Nations Units Analysis Presentation Transcript

  • Nation as a Unit of Analysis. Cultural Pluralism
    • Johan Galtung (Theory and Method of Social Research, 1967) distinguishes the following formal characteristics of countries:
    • A. Aggregate P roperties
      • B. Structural P roperties
      • C . Global P roperties
    • Aggregate Properties
    • Central tendency measures (average, median, mode, and proportion (rate)
    • Dispersion measures (variance, standard deviations from the population, average absolute difference correlation)
    • - usually quantifiable measures characterizing the property of the distribution of a variable among individuals, typically constructed from the census or survey data.
    • Do not use them as DV while making inferences about the behavior of individuals. This would lead to ecological (aggregation) fallacy.
    • B. Structural P roperties
    • Involve relationships among system elements ;
    • Deal primarily with organizations within societies ;
    • Variables could be overlapping and interlocking
    • E xchanging – measured by input-output analysis
    • Ex: construct the increase of migratory population for the region A, IA = in-migration – out-migration.
    • Your measure for region B, IB, would depend on IA. Thus, the one measure is redundant. Which to choose?
    • N etworking – measured by density of communication
    • Could be used as dependent variables.
    • C. Global P roperties
    • emergent measures, system as a whole
    • usually typological variables
    • Ex:
    • - form of government
    • - type of party system
    • D anger : misclassification of cases.
    • Can be used as DV – but usually are used as independent variables.
    • A General Framework for Country-level Analysis
    • Matrix of the form:
    • Units of analysis Variables .
    • 1 2 3 . i . n
    • 1
    • 2
    • 3
    • .
    • j a ji
    • .
    • m
    • where a ji denotes a characteristic i of country j.
    • Sources of D ata
    • Bruce M. Russet’s World Handbook of Political and Social Indicators (1964)
    • World Bank’s World Development Report (1977-2009)
    • UN Development Program’s Human Development Report (1990-2009)
    • Specialized data sets.
    • M ost important I ndependent V ariables
    • Economic development
    • Social (human) development
    • Political development
    • Economic D evelopment
    • Refers to the process of improving the standard of living of the population by raising national income per capita.
    • Generally, the national income reflects the money value of good s and services becoming available to the nation from economic activity.
    • It is measured by calculating the gross national product or/and gross domestic product .
    • Gross National Product (GNP) and Gross Domestic Product (G D P) describe, in monetary value, the total annual flow of goods and services in the economy of a nation.
    • Ex: 2006, the estimated total for the world ~ 65 trillion in PPP US$.
    • 65 000 000 000 000 US$
    • num b er of people 6 500 000 000
    • per capita 10 000
    • How unequally was this income produced ?
    • ~ 85 % of this wealth was produced by 1/4 of the world's people in the 'developed' nations,
    • 15 % was generated by 3/4 living in the developing countries.
    • How unequally was this income divided ?
    • Global figures for 1985-1995 suggest that the income gap between the richest and the poorest fifth of the world's population was doubling, from a ratio of 30:1 to 60:1
    • T op: Luxemburg & Norway , above 44 000 /capita
    • USA 43 000, GB 35 000, Germany 31 000
    • M iddle: Czech Republic 23 000, Poland 15 000
    • B ottom: Tanzania , Ethiopia ca. 1 000 , Malawi 600
    • Criticism of the GNP and GDP
    • Both measures:
    • - are non-qualitative (harmful spending counts the same as beneficial);
    • - ignore large, non-cash aspects of life (households & family, subsistence agriculture, voluntary work) as well as the informal economy;
    • - fail to register many elements of sustainable social progress and human well-being (freedom, culture, social cohesion).
    • Social (human) D evelopment
    • Theoretical roots:
    • Human capital approaches.
    • Investments in human resources improve productivity. Education and health as main dimensions
    • Human welfare approaches.
    • Human beings are treated more as the beneficiaries of the development of the development process than as participants. Quality of life as a main dimension.
    • The basic needs approaches.
    • These approaches concentrate on the bundle of goods and services which are called “basic” in terms of survival: food and water, shelter and clothing, and health care.
    • Social (human) D evelopment 2
    • Measurement:
    • 1. The Physical Quality of Life Index , PQLI
    • The value is a single number derived from:
    • basic literacy rate,
    • infant mortality,
    • life expectancy at age one
    • - all equally weighted, to form a 0 - 100 scale.
    • 2. The Human Development Index , HDI
    • Social (human) D evelopment 3
    • Measurement:
    • 2. The Human Development Index , HDI
    • This index includes:
    • - health as measured by life expectancy;
    • - level of knowledge and skills , as measured by the weighted average of functional literacy and combined elementary and secondary net enrolment rate;
    • - access to resources , as measured by the level of real per capita income.
    • Social (human) D evelopment 3
    • Measurement:
    • 2. The Human Development Index , HDI
    • This index includes:
    • - health as measured by life expectancy;
    • - level of knowledge and skills , as measured by the weighted average of functional literacy and combined elementary and secondary net enrolment rate;
    • - access to resources , as measured by the level of real per capita income.
    • Political Development 1
    • Standard-based scales of different dimensions of democracy.
    • Origin: Robert Dahl; provided measures of ‘polyarchy’ for 114 countries circa 1970.
    • Freedom House 7-point scales of political and civil liberties
    • have been produced annualy since 1972 & cover all the independent nation states in the world ( www.freedomhouse.org ; see also Coppedge and Reinicke 1988, 1990, 1991);
    • Polity’ data series (Polity I, II, III, and IV) that contain 11-point scales of autocracy and democracy (0-10) for all the independent nation states in the world since the 1950s (see Jaggers and Gurr 1995; Marshall and Jaggers 2000);
    • Banks’s (1994; 1997) institutional scales of democracy for 115 countries between 1850 and 1997 (see also Foweraker and Landman 1997, Appendix B, pages 251-252);
    • Bollen’s (1998) global index of liberal democracy for 1950-1990. This tradition of standards-based scales has also extended to the measurement of human rights
    • http://www.economist.com/media/pdf/Democracy_Index_2007_v3.pdf
    • Political Development 2
    • Analysis of good & corrupt forms of rule which categorized regime types.
    • Origin: In 1959, Seymour Martin Lipset categorized countries in Europe & Latin America into stable democracies, unstable democracies, stable dictatorships, and unstable dictatorships.
    • Gasiorowski’s (1996) political regime change data set
    • The global study of Przeworski, Alvarez, Cheibub, and Limongi (2000), which has categories for democracies and non-democracies for the period 1950 to 1990
    • Dorenspleet’s (2000, 2001) work on the ‘waves’ of democratisation, which extends the categorization found in Przeworski et al. (2000) to 1994.
    • Political Development 3
    • Indicators of mass public perception of democracy.
    • Origin: Civic Culture - Almond and Verba (1963).
    • Uses survey-based indicators of mass public perception of democracy & the quality of democratic institutions.
    • The Global Barometer Surveys ;
    • The World Values Surveys
    • So-called ‘Image Indices’
    • poll expert opinion on the quality of democracy at a given time & place.
    • Origin: Fitzgibbon and Johnson (Fitzgibbon 1967) sought to measure the quality of democracy in Latin America using a systematic survey instrument that probed the views of country specialists on a series of social and political scales ranging from 1 to 5 that they felt represented both the preconditions and manifestations of democracy. Their index has been produced every five years from 1945 to 1985.
    • 7 Methodological Problems of Analyses
    • with Countries as Units of Observation
    • The Representation Problem
    • Small N Problem
    • The Galton Problem
    • The Black Box Problem
    • The Unequal Unit-Size Problem
    • The Unequal Unit-Heterogeneity Problem
    • The Quality of Data Problem
    • The Representation Problem
    • All 227 countries and territories of the world constitute the universe of possible units of observation – societies.
    • Having all countries as a “sample” introduces a problem since this is not a representation strictly manageable in the probability framework of inferential statistics.
    • 2. Small N Problem
    • Usually cross-national research is restricted to relatively small number of countries, with N < 100.
    • This creates a problem of estimates in the relationship between variables: sometimes removing one unit of observation changes the relationship between variables.
    • Look for outliers. The best is controlled bootstrapping (re-sampling, removal of some cases).
    • 3. The Galton Problem
    • In statistical analyses, units of observations should be independent of each other to make inferences on the relationship between variables.
    • In practice it is difficult to exclude the possibility that the relationship is partly influences by the diffusion processes.
    • Control for diffusion. Sometimes researchers put dummies whether a country has a border with a country that adopted the policy which we want to explain.
    • 4. The Black Box Problem
    • Although we are establishing the relationships between input and output variables, the mechanisms that are “responsible” for these relationships usually remain unspecified and/or untested.
    • Introducing intervening variables leads to new questions about the mechanisms.
    • Be clear about the mechanism through which IV influences DV. One issue here is the appropriate time lag.
    • 5 The Unequal Unit-Size Problem
    • Usually countries are treated as equivalent units of observations. Thus, a value of a particular variable for Luxemburg has the same effect as a value of the same variable for China. In general, the discovered relations between variables are driven by small countries since their N is larger.
    • Do we want to control for it? If so include population size as a control variable.
    • 6 The Unequal Unit-Heterogeneity Problem
    • Some countries are relatively homogenous with respect to the studied properties and some are not.
    • How do we compare the GDP for Netherlands (where the differences between regions are small) and for India (where the differences between regions are large)?
    • 7 The Quality of Data Problem
    • Statistical information about societies is not equally reliable: the more developed the country is, the better the statistical information. This relationship causes a problem for analyses that include both developed and underdeveloped countries.
    • If possible, put control for the quality of data.
    • Sometimes the source of data provide info about the ways by which the data has been established.
    • Ex: the Gini index estimated from the aggregated income can be biased. Some data show for which countries the Gini is estimated from the aggregated income (eg. only 5 intervals). For these countries put 1, otherwise 0. You will see whether the quality of data has an effect independently of Gini.
    • Cultural Pluralism
    • Methodologically, this translates into admitting the differentiation over the world.
    • Do we have enough variation in cultural variables representing countries? In the research we tend to ignore non-western world? What are the consequences of it?