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Effects of Corruption Sub-Saharan Africa and Asia

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CHAPTER THREE

RESEARCH METHODOLOGY

3.0 Introduction

This section discusses the methodology to be employed in the intended study necessary to understand the growth trajectories of Sub-Sahara Africa and Asia in an attempt to compare and contrast these growth differences. The various theories reviewed in chapter two are hereby brought to the fore together with the concepts so highlighted in the conceptual framework. Since the intended study will be oriented in two ways: the first is to assess the effects of corruption and institutional factors on sustainable growth and secondly to operationalise the environmental policy framework put forward under the Millennium Ecosystem Assessment (MA) as a measure of Human Well-Being, two separate methodologies will be outlined to conform with the data collection procedure and the objectives of the study.

The first methodology will outline the procedure in collecting secondary data on the selected countries. It will also go further to outline the data sources, and specify the models to be used in data analysis. The second methodology that will attempt to operationalise the MA policy framework on the environment will rely on primary data through a self-organized survey to be undertaken in Ghana. The second methodology will shed light on the research design type, the unit of analysis and the key informants. The description of the target population and sample size will also be presented. It should be mentioned that the first part of the intended study will primarily make use of cross-country secondary data from selected developing countries over the period 1990 to 2014 in evaluating the so-called effects of corruption and institutional variables on development.

3.1 Sample Selection

In the early part of the 1960s, some of the leading development text books in circulation of that time ranked Sub-Saharan Africa’s growth potential ahead of East Asia’s, and the World Bank’s chief economist were quoted to have listed seven African countries that had a clear potential to grow beyond 7 % (Easterly & Levine, 1997). Yet, these hopes never materialized. On the contrary, real per capita GDP did not grow in Africa as expected over the period 1965-2013 period, whiles in East Asia and other continents like Latin America, per capita grew well over 5 % and Latin America recorded 2 % on a year by year. For instance, East Asian average GDP in 2000 was $13,500 USD, while the African GDP was only $2,439 USD. The difference between these two landmasses widened even further to a factor of 4.6, reflected in the annual difference of the rate of growth (1950-2000), which was 0.6% in the African case and 4.4% in the case of East Asia (Cypher & Dietz, 2009; Presbitero, 2010; Stiglitz, 2013).

Ironically, most African countries have actually retrogressed, posting negative per capita growth rate since the late 60s, with the seven countries identified by the World Bank chief economist being among the culprits. The issue of convergence, which created a fertile ground for economies to be compared, was non-applicable in the case of Sub-Saharan Africa, reinforcing what came to be known as “African Growth Tragedy” in most academic debates (Lawrence & Thirtle, 2001). Nonetheless, Africa’s compatriots- East Asia experienced unprecedented growth from the 1960s to the 2000s. This exceptional growth in general earned the continent the name “East Asian Miracle” (Dowling & Valenzuela, 2010; Presbitero, 2010). The four East Asian tigers- Hong Kong, South Korea, Singapore, and Taiwan grew astronomically above 6 % on average in per capita terms between the 1960s and 2000s. This high growth of East Asia as opposed to its counterpart (Sub-Saharan African) raises a lot of questions about what are the fundamental factors necessary to explain these differences, and what should be done to stimulate economic growth (See Table 3.1).

From table 3.1, it is evident that Sub-Saharan African countries were far ahead of Asia in terms of per capita GDP in the 60s. For instance, a country like Ghana had per capita income of more than $429, ahead of South Korea which had a per capita income of $349. However, the same cannot be said in 2012. Ghana’s per capita in 2012 was only $1,550 (representing a 27.67 % increase) whiles that of South Korea stand at $22,589 as of 2012 (approximately 98.45% increment).

Owing to the challenges in getting up-to-date data on the countries involved in the comparison, the sample selection criteria in the intended study will be based on data availability. To that effect, the study will consider 40 countries (i.e. 20 countries apiece in Sub-Saharan Africa and Asia).

Table 3.1 Sub-Saharan Africa and Asia: Selected Countries’ key indicators 1960 and 2012

Regions

Selected Country

Year

GDP per capita (USD)

Unemployment (%)

Poverty Headcount Ratio (%)

Sub-Saharan African

           
 

Ghana

1960

426

n.a

n.a

 
   

2012

1,550

12

40.0

 
 

Nigeria

1960

296

4.9

n.a

 
   

2012

1440

19.7

68.0

 
 

Malawi

1960

n.a

n.a

n.a

 
   

2012

320

n.a

61.6

 
 

Kenya

1960

223

4.9

n.a

 
   

2012

860

40.0

43.4

 
 

Cote d’ivoire

1960

538

15.7

n.a

 
   

2012

1,220

24.9

23.8

 

Asia

           
 

Korea

1960

349

8.2

n.a

 
   

2012

22,589

3.65

n.a

 
 

China

1960

 

5.5

n.a

 
   

2012

5,720

4.3

11.8

 
 

Indonesia

1960

174

n.a

n.a

 
   

2012

1,731.65

8.0

16.2

 
 

Malaysia

1960

547

6.0

n.a

 
   

2012

17,200

3.7

2.27

 
 

Thailand

1960

218

2.7

n.a

 
   

2012

5,210

1.39

0.4

 
             

Source: World Bank, World Development Report (1970 & 2012)

3.2 Data Collection

The first part of the intended study will rely on secondary data of the sample countries from credible sources. To measure sustainable development, the intended study will employ a broad based proxy: Genuine Wealth per capita and genuine saving for the period 1990 to 2014 reported by the World Bank. The annual data published by the World Bank in its World Development Report are sources that provides a consistent and reliable series of data to researchers around the world (Cypher & Dietz, 2009; Hamilton, 1999). Data regarding unemployment, poverty, and income inequality will be obtained from the World Bank dataset- World Development Indicator (WDI). The World Development Indicator is the primary World Bank collection of development indicators compiled from officially sanctioned international sources. The WDI presents the most current and accurate global development data available, capturing appropriate estimates at the regional, national and global perspectives.

Investment rates and gross national savings will be collected from the surveys undertaken by the International Monetary Fund (IMF), called the World Economic Outlook (WEO). The population growth rates and life expectancy at birth data will be obtained from the WDI. Data from the Human Development Index (HDI) covering adult literacy rates and combined gross enrollment will be used. These datasets are sanctioned by United Nations Development Programme since 1990.

To measure the level of political democracy, the Freedom House indices of political rights, civil liberties, and press freedom will be utilized. Freedom House surveys is an extensive survey that rely on wide range of sources and covers long time series and have been relied by academic researchers extensive (UNDP, 2002). Freedom House survey has been annually conducted since 1973 to the present. Political rights ratings are based on an evaluation of three subcategories: electoral process, political pluralism, and participation. Concerning civil liberties ratings, the indicators are based on an evaluation four subcategories: freedom of expression and beliefs, associational and organizational rights, rule of law, and personal autonomy and individual rights. The indices of political rights and civil liberties range from 1 to 7, with a value of 1 representing the strongest level of democracy and 7 being the weakest. According to a report published by the UNDP, pointed out that, in 1997, the Freedom House published an assessment of freedom of the press with data from 1980 to the present (UNDP, 2002). A critical look at the level of press freedom is based on three broad categories: the legal environment, the political environment, and the economic environment. The Press Freedom Index ranges from 0 to 100. A value of 0 represents the highest level of press freedom and 100 represents the lowest level.

To measure government effectiveness, regulatory quality, rule of law, control of corruption and corruption perception index (CPI), the intended study will rely on the Worldwide Governance Indicators (WGI). Government effectiveness captures the perceptions of the quality of public services, the quality of the civil service and the degree of its independence from political pressures, the quality of policy formulation and implementation, and the credibility of the government’s commitment to such policies. Regulatory quality captures the perceptions of the ability of the government to formulate and implement sound policies and regulations that permit and promote private sector development. Rule of law on the other hand captures the perceptions of the extent to which agents have confidence in and abide by the rules and society, and in particular the quality of contract enforcement, property rights, the police, and the courts, as well as the likelihood of crime and violence. Control of corruption captures the perceptions of the extent to which power is exercised for private gain. Corruption perception index captures the perceived levels of corruption, as determined by expert assessments and opinion surveys. Countries are ranked on a scale from 100 (very clean) to 0 (highly corrupt). However, not all the indicators of the WDI are included in the study as some have been excluded (political stability and absence of violence) as they overlap with indicators of democracy so described in the preceding literature.

To measure economic institutions, indicators on the protection of property rights data will be obtained from the Index of Economic Freedom conducted by the Wall Street Journal and the Heritage Foundation. The Index of Economic Freedom measures ten components of economic freedom in which grades are assigned to each indicator on a scale of 0 to 100, where 100 represent the maximum freedom. The proposed study will focus on property rights as a measure of economic institution. The property right component is an assessment of the ability of individuals to accumulate private property, secured by clear laws that are fully enforced by the state. This indicator measures the degree to which a country’s laws protect private property rights and the degree to which its government enforces those laws. It also assesses the likelihood that private property will be expropriated and analyses the independence of the judiciary, the existence of corruption within the judiciary, and the ability of individuals and businesses to enforce contracts.

On the degree of economic freedom, the annual survey Economic Freedom of the World (EFW) will be used. The EFW is an indicator of economic freedom produced by James Gwartney and Robert Lawson, and is published by the Canadian Fraser Institute. The index has been used extensively by academician as a measure of economic freedom since it adopts definition that incorporates ideology similar to that of the laissez-faire capitalism. The EFW measures five subcategories of economic freedom indicators: (a) size of government; (b) legal structure and security of property rights; (c) access to sound money; (d) freedom to trade internationally; and (e) regulation of credit, labour, and sound business. The scores used ranges from 0 to 10, with 10 representing the highest strength of economic freedom.

The proposed study set to detail out the measures to be used with their corresponding definition including the sources of each variable included (See table 3.2)

3.3 Model Specification and Data Analysis

Central to the focus of this proposed study is to analyse the effects of corruption on sustainable development on the chosen countries. Based on the theoretical exposition in previous chapter and the conceptual framework, the intended study will build on these assumptions to present in clear terms how corruption may influence the prospect of sustainable development. The analytical approaches of Aidt (2010), Dasgupta and Maler (2000) and other authors will be followed in the proposed study. These authors posit that a society populated by many identical individuals who live forever. Time (t) is continuous. They simplify this by assuming that the population size is fixed. The economy produces an all-purpose good from labour manufactured capital, and the flow of natural resources. The production technology is represented as:

Where increases in each of the three arguments and is continuously differentiable. The production function need not be concave. As a result, the intended findings of the proposed study regarding sustainable development and corruption apply to a wide class of economies with externalities and other market and government failures. Manufactured capital is known to evolve over time according to the following law of motion:

Where is aggregate consumption, is investment in manufactured capital, and it is assumed that there is no depreciation. The natural resource base evolves according to the following law of motion:

Where is the natural rate of regeneration of the resource and can be interpreted as the net investment in the resource base. They make further assumption that, for non-renewable resources, the regeneration rate is zero for all , while for renewable resources it is positive. Individual derive utility from consumption and disutility from labour supply. This assumption is represented by a concave utility function Inter-temporal social welfare at time t can, then be defined using the utilitarian social welfare function:

Where is the (utility) discount factor. A development path starting at time is a projection into the future of all relevant economic quantities (i.e. . The economy’s institutions govern which of the infinitely many potential development paths is chosen. These include both economic and political institutions, such as markets and trade regimes, legal institutions that govern the way disputes are settled, and political institutions that determine how the economy is governed, by whom, and regulate how power is contested among others. Particular institutions select particular development paths through the choices made by private individuals and public sector official under those prevailing institutions. No assumption on institutional perfection is made. However, economic institutions can be dysfunctional (distorted markets, unregulated monopolies etc.) or not, rent-seeking may be kept in check or not, the society may be governed by a democratically elected leader or by a dictator, and corruption may or may not be controlled through monitoring or wage incentives. Another important dimension of the argument follows that the institutions can be taken as given; institutional reform can take place, but these reforms do not occur naturally over time. Institutions within the society are formally well defined as a function, that, given the state of the economy at each time , , selects a development path from the set of all feasible paths. Inter-temporal social welfare can explicitly be written as a function of institutions and their stocks of capital: .

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