Development Potential: The Joint Influence of High Population Growth and a Weak Economic Base
McCreery Page 1 Development Potential: The Joint Influence of High Population Growth and a Weak Economic Base Dr. Anna C. McCreery Ph.D. in Environmental Science (June 2012) Ohio State University http://annamccreery.wordpress.com/ Fundamentals of Geographic Information Systems (Autumn 2009) Applications of GIS – Final Project Assignment Information: Students will perform a spatialanalysis exercise, given only the criteria to use for reaching a conclusion. Objectives are to explore a data set and the geographic distribution of the variables, to arrive at several conclusions, and to produce four maps showing those conclusions visually. Other objectives include learning todesign and perform the necessary data analysis in a vector-based or raster-based GIS. Data exportutilities to other applications, such as Microsoft Access or Excel, will be learned for developing a more complete statistical analysis of spatial data.
McCreery Page 2 Problem Definition and Preliminary Non-Spatial Analysis This study examines how a country’s population growth and the strength of its economicbase influences the potential for future economic growth. To put this in context, the geographicdistribution of countries with different demographic and economic conditions will be examined.The clear historical link between spatial location and current economic conditions in manyAfrican, Asian, and South American countries can be linked to oppressive colonial regimes thatstill affect these countries today. Furthermore, countries in the Northern Hemisphere might havedifferent demographic and economic conditions than countries in the Southern hemisphere, dueto variation in natural resources and historical patterns. This project will therefore also examinethe degree of spatial autocorrelation of demographic and economic conditions between countries,to determine whether the location of a country influences its other attributes. This study begins with a non-spatial analysis of country-specific data, looking forsignificant bivariate relationships between demographic variables, economic variables, andGross National Product (GNP) per capita (the distribution of GNP per capita is shown in Figure1). The results of this preliminary analysis are presented in Table 1. In terms of the populationbase, several factors were tested. Population density has a weakly significant positive effect, asit is a simple indicator of the amount of human resources that a country has available. Second,very high population growth (as indicated by the doubling time of the population) could produceone of two possible effects: 1) a country with a very high population growth might not be able tokeep up economically with that growth; or 2) a higher doubling time might indicate a veryvibrant country, with high numbers of immigrants seeking economic opportunities in a quicklygrowing economy. This second option is more likely, since doubling time has a positivesignificant effect on GNP per capita. Third, longer life expectancy is associated with higherGNP per capita. Finally, both higher current birth rates and higher past birth rates (measured asthe percent of the population under age 15) have a negatively impact GNP per capita. Taken as awhole, these factors imply that countries with quickly growing populations and a largepercentage of children tend to be less developed (i.e. have lower GNP per capita).1 Next, there were several economic factors that influence GNP per capita in bivariateregressions. The percent of the population dependent on agriculture can be used as a proxymeasure of the level of industrialization of a country’s economy. A higher proportion ofpopulation dependent on agriculture would indicate a less industrialized country, and thesecountries have significantly lower GNP per capita. The percent of the population in urban areashas a significant positive influence on GNP per capita, likely because urban areas act aseconomic centers, and more modernized countries have fewer rural residents. Trade was alsofound to be important: higher export values are associated with higher per capita GNP (whenmeasured as a percent of GDP or when measured in proportion to the value of imports).2 Taken together, these results demonstrate the importance of population growth,industrialization, and trade balance in determining GNP per capita. Higher population growthand a lower industrial base are associated with a lower GNP per capita.1 Other demographic factors that were also tested and not found significant in a bivariate regression are: the growthrate (measures at 1989 or 1980), percent of the population between ages 15-64, and the death rate.2 The influence of the energy balance, or difference between energy consumption and production, was also testedbut not significant.
McCreery Page 3Table 1. Significant Bivariate OLS Regressions of 1989 demographic and economicvariables on national GNP per capita (n=147). Standard Independent Variable Coefficient Error P>tPopulation Base:Population Density 3.50~ 1.86 0.062Doubling Time 11.24*** 2.32 0.000Life Expectancy 43.64** 14.89 0.004Birth Rate -47.35** 17.57 0.008Percent of population aged 0-14 -44.16** 16.72 0.009Economic Base:Percent of population dependent on agriculture -3813.00*** 324.84 0.000Percent urban 33.84** 12.23 0.006Value of exports as a % of GDP 1706.37*** 329.90 0.000Value of exports in proportion to value of imports 1412.33** 473.91 0.003~ p < 0.1, * p < 0.05, ** p < 0.01, *** p < 0.001Figure 1. Frequency distribution of GNP per capita, for all countries with available data.
McCreery Page 4 Methodology For conceptual clarity, countries were classified according to their economic conditionsand population growth. Countries with high population growth are those with birth rate at least37 births per 1000 women and at least 33% of the population under age 15, while low populationgrowth countries are lower on both criteria. Countries were also classified as poor economicconditions, good economic conditions, or other. Countries with poor economic conditions haveat least 50% of their population dependent on agriculture and a trade balance where importsexceed exports by at least 10%, while countries with good economic conditions have less than50% of their population dependent on agriculture and a trade balance where exports exceedimports by at least 10%. These economic and demographic variables were chosen because theyhave a statistically significant effect on GNP per capita in 1989, so it is likely that they will alsoaffect economic growth in future years. These the geographic distribution of these conditions areshown on a series of maps, discussed below. Data Preparation and GIS Visualization All of the data for this project was taken from the datasets provided to the class forindividual projects. GIS data conversion and visualization techniques were used to create aseries of maps showing the geographic distribution of different population and economicconditions, to examine the spatial auto-correlation of development potential. Specific datatransformations are detailed in the appendix. The following maps show the results: 1. 1989 Birth Rate: Map displaying birth rate in each country, and highlighting countries with a very quickly growing population (countries with birth rate at least 37 and at least 33% of the population under 15 years old) 2. Agricultural Dependence and Population Growth: Map showing percent of population dependent on agriculture, highlighting countries with very quickly growing populations 3. Balance of Imports versus Exports: Map showing trade balance by countries, highlighting countries with high population growth 4. Potential for Future Economic Growth: Map showing countries with poor economic conditions and high population growth, countries with good economic conditions and low population growth, countries with good economic conditions (regardless of population) and countries with poor economic conditions (regardless of population) Discussion Examination of the four maps shows noticeable patterns in the data. First, the 1989 BirthRate map (see below) shows a clear geographic pattern in birth rates, with higher birth ratesconcentrated in the Southern Hemisphere. Furthermore, the highest birth rates in the world(above 37 births per 1000 women) occur primarily in Africa, with a few countries in Asia, LatinAmerica, and South America that also have very high birth rates. This map also outlinescountries with high birth rates and at least 33% of the population under age 15. The second map,on agricultural dependence, seems to follow the same geographic pattern. Specifically, countrieswith a high percent of the population dependent on agriculture (>50%) are mostly in theSouthern Hemisphere, and are primarily located in Africa.
McCreery Page 5 Next, the map for trade balance (titled Balance of Imports versus Exports, below) showsmore geographic variation. The level of spatial autocorrelation of trade balances is clearly lowerthan the level of spatial autocorrelation of agricultural dependence and birth rates. Africancountries have a variety of different trade balances, unlike agricultural dependence and birthrates which are high throughout the continent. Just by looking at the map there does not seem tobe any clear spatial pattern in the distribution of trade balances. The overall picture for economic development potential, however, is clear. A glance atthe final map, Potential for Future Economic Growth, shows distinct geographic patterns.Countries with high population growth and poor economic conditions do not have the resource toimprove their economy, despite international development efforts, and they will be furtherhampered by high population growth. These countries may not have the funds to educate theircitizens, or possibly even feed them adequately, and they will therefore not have the humancapital needed to grow their economy in the future. Although a few of these countries are inLatin America and Southern Asia, they are almost all located in Africa. The concentration ofthese countries in Africa demonstrates the spatial autocorrelation of these attributes, and theintersection of difficulties faced by many African nations. The final map also shows that there are some countries where future economic growthcould be considerable. These countries have good economic conditions in the current data, andthey are not hampered by high population growth. Indeed, the lower population growth could bean asset, since it will allow these countries to invest in good education for all their youngcitizens. These countries are not concentrated in any geographic location. However, there doesseem to be some spatial autocorrelation for countries with good economic conditions, regardlessof their population growth. Even a country with high population growth has the potential forhigh economic growth if its current economy is strong enough. Although it is a somewhatweaker spatial-autocorrelation, countries with strong economics, and therefore higherdevelopment potential, are clustered in South America and the Northern coast of Africa. Conclusions After the injustices of colonialism and the abusive treatment of many Southernhemisphere countries by European powers, it is important to consider whether former colonieshave been able to overcome the weight of history. This analysis shows that in some parts of theworld they have not – many former colonies in Africa are struggling with slow economies andhigh population growth, and they could be facing continued dire economic conditions in thefuture. This is even after many of them have been independent nations for decades, and despiteefforts to encourage development taken by the World Bank and other international bodies.Several South Asian nations are also facing difficult circumstances, and this region of the worldcould also be feeling the negative effects of the history of colonialism. Former colonies in theAmericas seem to be doing better – many countries in South America have good economicconditions, and apart from a few countries in Latin America the economic and demographicconditions of these countries show promise for continuing economic improvements. Overall,these issues are important because understanding the geographic distribution of economic anddemographic conditions is useful for understanding world power relationships both now and inthe future. This sort of spatial analysis is also useful for targeting development aid to thegeographic regions where it is most needed.
1989 Birth Rate :LegendCountriesBirth Rate no birth rate data 0 - 18.6 18.7 - 28.0 28.1 - 36.9 37.0 - 44.8 44.9 - 54.0 High population growth 0 25 50 100 Decimal Degrees In this map, high population growth is defined as a birth rate of at least 37 and at leat 33% of the population under age 15. Geographic Coordinate System: GCS WGS 1984 Datum: D WGS 1984
Agricultural Dependence and Population Growth:Legend 0 25 50 100 Decimal Degrees High population growth Geographic Coordinate System: GCS WGS 1984Countries Datum: D WGS 1984 no agricultural dependence dataPercent of population dependent on agriculture In this map, high population growth is defined as a birth rate of 1-10% at least 37 and at leat 33% of the population under age 15. 11-25% 26-50% 51-75% Greater than 75%
Balance of Imports versus Exports : 0 25 50 100 Decimal DegreesLegend High population growth Trade Balance Geographic Coordinate System: GCS WGS 1984Countries Exports Exceed Imports by greater than 50% Datum: D WGS 1984 no trade data Exports Exceed Imports by 10-50% Either Side by 10% In this map, high population growth is defined as a birth rate of at least 37 and at leat 33% of the population under age 15. Imports Exceed Exports by 10-50% Imports Exceed Exports by greater than 50%
Potential for Future Economic Growth based on current economic conditions and population growth: 0 25 50 100 Decimal DegreesGeographic Coordinate System: GCS WGS 1984 Datum: D WGS 1984 This map displays the countries that are most likely to see changes in their economic situation in the future, either good or bad. Countries with good economic conditions (defined as <50% of the population dependentLegend on agriculture and exports exceeding imports by at least 10%) and low population growth (defined as birth rate <37 and <33% of the population Good economic conditions & low population growth under age 15) are likely to have future economic growth. Countries with Good economic conditions poor economic conditions (defined as >50% of the population dependent on agriculture and imports exceeding exports by at least 10%) and high Poor economic conditions & high population growth population growth (defined as birth rate at least 37 and at least 33% of the population under age 15) are likely to continue struggling economically, Poor economic conditions and economic conditions could even get worse. The other countries are harder to predict all other countries
McCreery Page 10 Appendix: Data Preparation and GIS Operations The operations performed on these data are quite simple. First the join function was usedto join the demographic data file to the country map layer. A series of new data layers were thencreated for countries with a specific set of attributes, using the following steps: 1. Select the countries with specific attributes. For example, for high population growth, use select by attribute to select countries with birth rate ≥ 37 and population under 15 ≥ 33%. As another example, for trade balance the countries with the required trade balance were selected manually. 2. Export this selection to a new data layer.The constructed data layers are as follows: 1. High population growth: only countries with Birth rate ≥ 37 and % of population under 15 years old ≥ 33% 2. Low population growth: only countries with Birth rate < 37 and % of population under 15 years old < 33% 3. Agriculture-Dependent: only countries with > 50% of the population dependent on agriculture 4. Agriculture-Independent: only countries with < 50% of population dependent on agriculture 5. Poor economic conditions: only countries that have > 50% of population dependent on agriculture and imports exceeding exports by at least 10% 6. Good economic conditions: only countries with <50% of population dependent on agriculture and exports exceeding imports by at least 10% 7. Poor economic conditions and high population growth: only countries that fulfill the criteria for layer 1 and layer 5 8. Good economic conditions and low population growth: only countries that fulfill the criteria for layer 2 and layer 6.