THE IMPACT OF STRUCTURAL CHANGE ON SOCIAL CAPITAL AND ECONOMIC GROWTH IN ZAMBIA
PAMELA K.C. KAUSENI
Student No: 1655736
University of Groningen
International Economics and Business Master's Thesis
Supervisor: Prof. dr. Hans van Ees
ABSTRACT
This study investigates the role of social capital on economic growth in Zambia. The study specifically investigates if structural change in Zambia has affected social capital and economic growth. Using time series data and estimating two models using the same specification for different periods, the results show that there is no enough evidence in support of how the structural change has affected social capital and economic growth in Zambia.
Acknowledgements
The successful completion of this thesis has been the work and input of many individuals who contributed in various ways. In particular, I would like to unreservedly acknowledge Prof. dr. Hans van Ees for his valuable insights and laborious supervision of my work.
Table of Contents
1. Introduction ... 4
2. Literature review and hypothesis ... 8
2.1 Social Capital ... 8
2.1.1 Social Capital and Economic Growth ... 10
2.1.2 Hypothesis development ... 14
3. Methodology ... 20
3.1 Data Source and Measurement of variables ... 20
3.2 Tests for Model specifications ... 23
4. Results and Discussion ... 26
5. Conclusion ... 34
REFERENCES ... 36
APPENDIX A: TABLES ... 40
APPENDIX B: FIGURES ... 48
1. Introduction
At present, Zambia is showing improvements in the overall macroeconomic environment. For example, inflation reduced to 15.9 percent from 17.5 percent in 2004, the currency appreciated by 26.4 percent against the US dollar in 2005 compared to a depreciation of 1.6 percent in 2004. The total merchandise exports grew to US$ 2.1 billion in 2005 recording a positive trade balance of US$ 59 million. Also the external debt stock declined to 36.1 percent to US$ 4.5 billion in 2005 from US$ 7.1 billion at the end of 2004 due to the country ascension to the completion point under Heavily Indebted Poor Countries (HIPC) initiative resulting in significant cancellations of Zambia’s debt (Economic Report, 2005).
When Zambia became independent in 1964, one of the major development challenges faced by the new government was economic diversification. This is against the colonial background, which emphasized mono-economy predominantly dependent on mining. The new leadership attempted to widen economic activities by promoting other sectors namely agriculture and local industry. These activities were undertaken with a central objective of promoting both domestic and external trade. Trade was seen as the main source of revenues needed for social and human investment. This developmentalist was characterized by increasing and expansive state intervention under a one party state rule. For instance, after 1972, the fairly liberal political and economic policies were abandoned in favor of more restrictive policy environment. For example manufacturing was protected by high tariffs and price controls for major commodities was introduced. The economy performed well as long as the copper prices were high (McCulloch, Baulch, & Cherel –Robson, 2000).
significantly manifested in huge deficits in the areas of trade, foreign exchange interest and balance of payment decline. Alongside this crisis, Zambia’s overall debt portfolio was gradually reaching unsustainable levels (Hwedi, 2001).
These problems led to the introduction of the Structural Adjustment Programme (SAP) whose main thrust was rolling back of the state from economic sector and replacing this role with market principles. Therefore, SAP policy reform package included exchange rate liberalization, trade liberalization and capital account liberalization. Internal liberalization had to do with removal of subsidies and decontrol of agricultural prices. Commercialization and privatization of many parastatals was notable of the institutional restructuring reforms. It was also advocated that the effectiveness of these market principles would be enhanced when accompanied by democratic politics. Therefore, these economic reforms came hand in hand with political liberalization in Zambia. Thus, in 1990, Zambia became both an economically and politically liberalized country.
The construct of social capital is gradually becoming an important theme within the international development community though there is no consensus about the exact definition. According to James Coleman (1990) social capital can be defined as obligations and expectations, information channel and social norms. Putnam (1993) defines social capital in relation to features of social organizations such as networks of individuals along with associated norms and values that create externalities for the whole community. For the World Bank, social capital is defined as institutions, relationships and norms shaping a society’s social interactions (National Statistics, 2001). The lack of social capital is considered as an impediment to economic growth because of the benefits that come with it.
be evidenced by the low CPI scores and may be facing the problem of corruption. On the one hand, Botswana has relatively higher CPI scores suggesting less problems of corruption and also high levels of social capital (trust) when compared to Zambia. On the other hand, these two countries share certain significant features that have major implications for development. First, both countries are located in the same region of Africa, namely southern and are predominantly tropical and landlocked. Second, historically, both countries were colonised by the British Empire and attained independence around the same time, 1964 for Zambia and 1966 for Botswana. These countries were almost in the same situation of underdevelopment at the time of independence. Both countries have a major resource endowment, copper in Zambia and diamonds in the case of Botswana.
It is on the basis of both the differences and commonalities that we have included Botswana for comparative analysis.
Statement of the problem
Zambia has registered positive real economic growth from 2.2 percent in 1999 to 5.2 percent in 2005. This study will investigate what role social capital has played in Zambia in this upward and positive trend in economic growth.
Objective of the study
The General objective of this study is to examine the relationship between social capital and economic growth in Zambia. More specifically, the study intends to:
- Investigate how the structural change has affected social capital and economic growth in Zambia.
- Attempt to undertake a comparative analysis on the relationship between social capital and economic growth between Botswana and Zambia.
Rationale
poverty crisis. Therefore, this study makes a contribution to the current literature by investigating the effect of structural change on social capital and economic growth in Zambia. A comparison between these two countries might also contribute to the on-going generalized notions that high levels of social capital can contribute to economic growth hence the need to integrate social capital in developing economies.
2. Literature review and hypothesis
2.1 Social Capital
This construct can be traced to the works of Coleman and Putnam. Putnam (1993)’s study focused on explaining the institutional performance, industrial performance and socio-economic development of certain regions in Italy. According to Putnam (1993: 173-74), social capital, especially in form of networks have beneficial effects in the sense that they prevent opportunistic behaviour, foster robust norms of reciprocity, facilitate communication, information and trust building and also promote the survival of historical heritage. On this basis, Putnam defines social capital as the characteristics of the social organization such as networks, norms and social trust that facilitate coordination and cooperation for mutual benefit (Putnam, 1995:67). Putnam in his definition of social capital mixes up three distinct concepts namely citizen’s feelings of trust in other members of society, social norms supportive of cooperation and networks of civic engagement (Whiteley, 2000).
James Coleman (1990) advances social capital in terms of the social relationships that are established between individuals, authority and relationships of trust and norms. Social capital can take many forms such as obligation and expectation that come about as a result of social interactions. The second form of information channel is based on the idea of trusting other people to provide accurate information as a basis for action. The third form is that of social norms which can for example be illustrated by the people being able to walk freely outside at night in a city that has effective norms that inhibit crime (Whiteley, 2000). Like other forms of capital, social capital is productive, making possible the achievement of certain ends that would not be possible in its absence.
Recently, the World Bank has made contributions to the subject of social capital. Its main interest has focused on the relationship between social capital, poverty and development. According to the World Bank (in National Statistics, 2001:9) social capital refers to: “The institutions, relationships and norms that shape the quality and quantity of a society’s social interactions. There is increasing proof that social cohesion is critical for societies to prosper economically and for development to be sustainable. Social capital is not just the sum of institutions which underpin a society, but the glue that holds them together”.
On the basis of this definition, the World Bank has advanced five dimensions of social capital – groups and networks, trust and solidarity, collection action and cooperation, social cohesion and inclusion and information and communication (World Bank, 2001) Social capital is closely related to the notions of social . Schuller (2001) observes that it is generally agreed that social capital is both a consequence and a factor of social cohesion Other analysts have defined social capital as resources gained from participating in relationship networks that are relatively institutionalized (Landry et al., 2001).
Therefore, social capital can be closely associated with social networks and norms that promote these networks (horizontal associations) and on the other hand, with values and links (vertical associations). The latter disregards societal differentiations. In sum, social capital takes into account social, political, cultural and environmental aspects as influential in determining social structures and norms.
2.1.1 Social Capital and Economic Growth
Research on social capital and development can be categorized in distinct approaches of communitarian, networks, institutional and the synergy (Woolcock and Narayan, 2000). The communitarian view equates social capital to local organizations such as clubs, associations and civic groups. Importance is attributed to the number and density of such groups in any given community. Therefore, social capital is better the more in terms of number and having a positive effect on a community’s welfare. The negative side to this view can arise when communities or networks are isolated or working at cross purpose to society’s collective interests. This view works under the underlying assumption of homogeneity in a given society.
The network view of social capital can be attributed to scholars such as Fafchamps and Minten (1999); Portes (1995) to mention but a few. Emphasis is on the importance of both vertical and horizontal associations between people and of relations within and among such organizational entities as groups and firms. A range of outcomes of social capital is due to the different combinations between bonding (horizontal) and bridging (vertical) associations. Where as horizontal associations (thick trust or strong ties) are more in pursuit of narrow sectarian interests, vertical associations (thin trust or weak ties) cut across various social divides based on religion, class, ethnicity and social status (Putnam (1993); Woolcock and Narayan, 2000). Economic development becomes possible when individuals acquire the skills and resources to participate in networks that are beyond their community which are a result of close community membership (Granovetter, 1995).
Guiso et al. (2004) study finds that households in the northern part of Italy make more use of formal financial markets and less use of informal credit and thus invest less in cash and more in stock. This can be attributed to flow and quality of information on financial issues through the social networks.
Wade (1988): Case Study of Irrigation System in Southern India
2. They formed irrigator associations which were backed with serviceable rules and widely accepted norms
3. But the villages that were close to the headwork of water and thus were more assured of continuous water supply did not act collectively but acted as atomized individuals.
The institutional view departs from the communitarian and network views in which social capital is an independent variable. The basic argument is that social capital is a product of the institutional environment. North (1990) emphasises the importance of institutions of a society for its economic growth and development. North (1990:3) defines institutions as “principles that guide human actions either formally (consisting of legislation or other written percept) or informally (consisting of culture or customs).” Social groups’ actions are also dependent on institutions. How an institution performs is important because it will have a bearing people’s level of trust that can be attributed to it. Trust in government institutions can be promoted by good political and economic performance. For example, the government can put in place institutional reforms that limit predatory behaviour by public officials thus improving the political and economic performance.
North (1990) puts emphasis on the necessity of ‘rules of the game’ or institutions through which incentives can be provided to achieve desired outcome. In a world where agents lack full information, they will have to bear extra transaction costs when exchanging goods and services in the market. Social capital when defined in terms of inter personal trust will embrace the influence it can have on all aspects of the economy. In Whiteley (2000:450), Kenneth Arrow has written that:
“Virtually every commercial transaction has within itself an element of trust, certainly any transaction conducted over a period of time. It can be plausibly argued that much of the economic backwardness in the world can be explained by the lack of mutual confidence.”
agent problems by being able to negotiate solutions to collective action problems. In poor countries where the state is unable to provide public goods due to inadequate resources, collective action is important because it can serve as a substitute for the state hence fostering development. Existing Studies (Rodrik (1998); Tempel and Johnson (1998); Knack and Keefer (1997) have stressed the importance of efficient and quality institutions on economic performance. The findings show that social capital will act as a complement to societies that have quality political, legal and economic institutions thus positive economic growth. The findings further show that corruption, bureaucratic delays, suppressed civil liberties, failure to safeguard property rights can be of major impediments to a nations’ prosperity and an obstacle in the promotion of social capital in a nation.
Research by Schneider et al., (1997) shows that the design of institutions delivering social public goods can influence the levels of social capital and that government policies can and do affect the level of social capital. Gains from trade can not be fully realized in the absence of formal institutions. Efficient institutional settings can be able to provide trading parties with important information on trading conditions in other countries or regions and so be a mechanism to facilitate distant trade. Trading agents not only need resources to write and enforce contracts but also to protect themselves against non voluntary transactions such as theft. In the presence of no full information, such transaction will always be positive. It is on this basis that agents are always looking at ways of lowering such costs as to maximize their profits in any given transactions
Minten and Fafchamps (2002) find social capital as a substitute to weak market institutions. Social capital enables traders to reduce search and information costs. The study found that agricultural traders in Madagascar rank the importance of relationships for success in business higher. Similarly Gabre-Madhin (2001) also find that grain traders in Ethiopia continue to depend on personalized trade for most of their transactions including distant markets when there is weak public market information.
In the study conducted by Putnam (1993) in Italy, he concluded that the North developed faster than the South due to the presence of higher social capital by using membership in groups and clubs as a measure of social capital. In the study by Whiteley (2000) of thirty –four countries, he found that social capital had an impact on growth which is as strong as that of human capital or education. Zak and Knack (2001) find that social capital in the form of trust promotes economic growth.
The synergy view perspective comes from an integration of networks and institutions that results from citizen and government action based on complementarity and embeddedness (Evans 1996). Complementarity refers to mutually supportive relations between public and private actors and is exemplified in legal frameworks that protect rights of associations and facilitate exchanges among community associations and business. Embeddedness refers to the nature and extent of the ties connecting citizens and public officials (Woolcock and Narayan, 2000:236). Economic prosperity and social order is more likely in a community with high levels of bridging social capital and good governance because of complementarity between the state and community. In the presence of weak, hostile or indifferent formal institutions, social capital can be a substitute and a mediator through which common goals can be pursued hence development.
In the discipline of economics, capital is a resource that enables a person or organization to maximize profits. It is the stocks of capital such as physical (machines, buildings tools, roads, railways) and financial (liquid assets such as stocks and bonds) that are used as input in the production process in different ways.
Although Romer (1986) and Lucas (1988) are regarded as the proponents of this theory, they built on the work of Arrow (1962), Sheshinsk (1967) and Uzawa (1965). Growth goes on indefinitely due to returns on investment in which it incorporates a broader class of capital goods that include human capital that do not necessarily diminish as economies develop. Knowledge is a basic form of capital. Spillovers of knowledge across producers and external benefits from human capital are parts of this process, but only because they help avoid the tendency for diminishing returns to the accumulation of capital (Barro and Sala-I- Martin, 1995:12). Romer’s argument is that investment in knowledge leads to increasing returns and having a natural externality in that it cannot be perfectly patented or kept secret. He furthers argues that although knowledge is a non rival good that can be used at the same time by many people, an adequate stock of human capital is important.
2.1.2 Hypothesis development
There are many ways to measure social capital. However, there is consensus when it comes to indicators that can measure social capital. Trust appears to be the most important indicator with elements of trust in others and in institutions (government, police, politicians, etc). Civic engagement is another indicator used. This is measured as participation in organizations, groups or networks offering social or political activities. A distinction is made between participation in community activities or other form of activism and that which involves political life. Social networks (formal and informal) are another indictor frequently used. Networks may arise from a person’s immediate environment (frequent contact with family, friends and neighbours) and also from relationships that individuals establish in a workplace and community.
Formal networks contains indicators of participation in associations, clubs, political parties, trade unions, churches etc. and voluntary work in these organizations. Informal networks include measures of sociability and provision of unpaid help.1
Our study use a broader or multi dimension definition of social capital in which citizens trust is beyond members of their own family to include fellow citizens and people in
general. If social capital is to be important for economic performance, it then has to be based on thin or generalized trust.
There has been various ways to measure social capital such as trust, civic associations, and networks. Some quantitative studies use indicators of trust and civic norms from the World Values Survey (Knack and Keefer 1997; Whiteley, 2000).
Trust as another measure of social capital is of value for a society’s capital. There is mixed debate on the issue of trust. To some it is an outcome of social capital (Woolcock and Narayan, 2000); while for others it is a component of the shared values which constitute social capital.
When defined broadly, trust has the expectation that a partner will not engage in opportunistic behaviour for whatever reason (Nootebom, 2006).Several studies have used trust as an indicator of social capital (Knack and Keefer 1997; Whiteley 2000; Zack and Knack 2001; Calderon, Cesar, Chong, & Galindo, 2001). Zack and Knack (2001) find that social capital in the form of trust has a positive influence on growth. According to Putnam (1990), there is thick trust a product of intimate social networks and thin which is generalized trust in other members. Generalized trust as an indicator of social capital can capture effects resulting from networks and cooperation. As people interact with each other, trust and cooperation will be built up leading to networks and associational membership. Social trust through an increase in public pressure for efficient governance can contribute positively to economic growth. Government officials will be discouraged to engage in corrupt behaviour as they can be easily detected (Raiser, 1997).
effect on growth is reducing on the principal agent problems that are more prevalent in a low trust society. When there is no trust between the principal and agent, the principal is subjected to incur high costs if he has to supervise the quality or effectiveness of the agents work because agents have incentives to shirk. A reduction on such costs can promote efficiency and growth.
Social capital can also affect growth indirectly by its interaction with human capital. Human capital is an important factor in economic growth. The interaction between technological change and human capital will depend upon a certain level of human capital that can effectively utilize this change. According to Benhabid and Spiegel (1994), human capital influences growth through distinct mechanisms. In the first place, the stock of human capital in a society affects growth directly via high levels of education that promote a good economic performance. Secondly, diffusion of innovation works more effectively in educated rather than in uneducated societies. Education is a factor that can influence a society’s political and social engagement. A society will benefit from significant effects that come with wide spread education attainment. Putnam (1993) argues that education promote civic engagement, social trust and membership in various groups. Another indirect mechanism is the link between investment and social capital. In a high trust society, actors can take greater risks and invest in both physical and human capital. We therefore test the following hypothesis;
Hypothesis 1: A high level of social capital has a positive relationship on economic growth in Zambia.
2000). Trade can be an engine of growth through more efficient production of goods and services when production shifts to countries that have comparative advantage in producing them. In an endogenous growth model, the impact of trade on a country’s activities of human capital accumulation through either learning by doing or education and technological advance through R&D activities can influence economic growth. Trade can still influence growth even in developing countries where R&D activities are limited as long as the countries are able to import capital and intermediate goods which can expand the productivity of a country’s other resources (Shigeyuki and Razafimateta, 2003).
The use of knowledge from more advanced countries in production processes through innovations, imitation can also improve growth for developing countries and are the benefits associated to the dynamic gains of trade. Trade can be considered a production process through which exports are transformed into imports. Imports provide much needed inputs that may help to build a competitive export base; incorporate foreign technical progress and contribute to technology transfers; and also to diversify the consumption and production base. In view of this, we see complementary nature of exports and imports in the event that exports are able to generate resources that can be spent on imports. It is also important to mention that benefits of trade can also depend on other factors such as quality of domestic governance; legal framework and stability of policy environment.Past studies that have analyzed the impact of trade on economic growth have found a positive relationship between trade and economic growth (Feder, 1983; Makki and Somwaru, 2004). Therefore, from the theoretical background, we test the following hypothesis;
Hypothesis 2: Trade has a positive relationship with economic growth in Zambia.
Foreign Direct Investment as an important tool of development is vast (Navaretti and Venable 2004; Asiedu, 2002; UNCTAD, 1999; Bennell, 1997). In recent years, given the rapid growth and changes in global investment patterns, the definition of FDI has been broadened to include the acquisition of a lasting management interest in a company or enterprise outside the investing firm’s home country. Foreign Direct Investment (FDI) is international investment by a resident entity in one economy (direct investor, parent company, multinational) to acquire or set up a subsidiary in a foreign country and capital transactions between the parent company and the foreign subsidiary and among subsidiaries part of the same multinational (Navaretti and Venable 2004).
In these works, the importance of FDI, particularly as it relates to developing countries, is described in many ways namely, as a means of introducing technological change, complementing domestic investment as well as providing access to skills and local markets (Asiedu, 2002). Specifically FDI acts as a powerful spur to competition, innovation and enhancement of cost efficiencies. The case of developing countries, FDI is seen as an important source of capital in countries where income levels and domestic savings are low. FDI in these countries also tends to provide capital for investments, employment creation, transfer of managerial skills and technology (Asiedu, 2002).
Scholarly work and policy studies analyzing the trends in global developments have almost all the time concluded that levels of investment and re-investment play a key role in determining a particular countries development status (African Development Bank, 2003).
FDI in different countries. For instance the African Development Bank reports that normal costs, growth variables, ratio of public spending and ratio of debt to GDP were some of the key factors at play in investment decisions (African Development Bank 2003:106).The size of impact of FDI on economic growth will also depend other prevailing factors such as the level of human capital, domestic investment, infrastructure, macroeconomic stability to mention but a few.
The existing empirical literature on the impact of FDI and trade provides contrasting results not only on the existence of a significant link between FDI and growth but also about the sign of such relationship. Several studies have shown that FDI exerts a positive impact on growth (Lumbila, 2005; Borensztein, Gregorio, and Lee, 1998). Borensztein et al., (1998) found in a cross country regression for 69 developing countries that FDI is important vehicle for the transfer of technology, contribute to larger measure than domestic investment and the contribution of FDI to economic growth is enhanced by its interaction level of human capital in the host country. Nyatepe-Coo (1998) also found on selected countries in south east Asia, Latin America and Sub-Sahara Africa country in period 1963 to 1992, that FDI did promote economic growth in majority of the 12 countries examined. Other studies however find contrary results. For instance, Jackson (1982), for a number of 72 developing countries between 1960 and 1978 finds that FDI had no significant impact on grow when country size is taken in consideration. Rothgeb (1984) finds that FDI was negatively linked to growth for the set of 18 developing countries as a whole. In this case therefore, the third hypothesis that we test is;
3. Methodology
3.1 Data Source and Measurement of variables
This section describes the data used in the empirical analysis as measures of economic growth, social capital, and a number of controlling variables that we use in our regression model. The period of analysis is from 1980 to 2004. This is the time Zambia adopted a systematic structural adjustment programme. This period includes the reign of Kenneth Kaunda government’s lack of commitment in the implementation of stabilization and structural adjustment policies and the third republic that were willing to implement the structural adjustment programme.
Data was obtained from the International Financial Statistics (IFS) of International Monetary Fund (IMF) database and World Bank’s World Development Indicators (WDI) database. These are independent institutions and hence the reliability of data. Most of the data is obtained from the World Bank’s World Development Indicators (WDI) database. This a comprehensive database on economic development indicators especially for developing nations. It covers more than 600 indicators, 208 economies, and 18 regional and income groups.
variable has been used in other studies (Clague, Keefer, Knack and Olson, 1999; Baliamoune-Lutz, 2005).
Our growth model includes two institution and policy variables as control variables. The first one is general government final consumption expenditure (% of GDP). A reduction in government consumption will help to reduce crowding out of private sector investment and this can positively impact economic growth (Obwona, (1996); Flexener (2000). The second control variable is inflation. This is used as a proxy to measure for macroeconomic stability. Several studies have indicated that inflation can impact economic growth negatively. De Gregorio (1992) finds that inflation has a significant effect on growth in a cross country regression. In a cross country regression of over 100 countries done by Barro (1996), average annual inflation was able to reduce real per capita GDP growth.
Table 1: Description of variables
Name Description
Growth GDP per capital growth (annual %)
Social capital
Using indicator of trust (Contract intensive money)
CIM- the proportion of the money that is not held in form of currency
FDI Foreign direct investment, net inflows (% of GDP) is our measure for investment
Trade Trade (% of GDP)
Inflation Consumer prices (annual %)
Government consumption General government final consumption expenditure (% of GDP).
The first model covers the period 1980-1991 and the second model covers the period 1992-2004. The underlying principle of the least squares is that the line we fit to the data values should be such that the sum of the squares of the vertical distances from each point to the line is as small as possible and also the least squares estimates we obtain have a sum of their residual less than sum of squares of any other line (Hill, Griffiths, & Judge, 2001:51). To be able to make a comparison with Botswana, we estimate two models for the same time period that coincides with the structural change in Zambia and also using Ordinary Least estimation (OLS) for a semi-logarithmic for the same variables as is the case for Zambia.
Model Specifications t t t t t t t FDINET INFL GOVTSP TR SC GROWTH ε β β β β β β + + + + + + = 5 4 3 2 1 0 (log) Where:
SC = Social capital (CIM as indicator of generalized trust) TR = Trade as percent of GDP
GOVTSP = Government spending as a percent of GDP INFL = Inflation rate (consumer prices annual %)
FDINET = Foreign direct investment net inflow as a percent of GDP
t ε = Error term = 0 β Intercept 5 , 4 3 2 1,β ,β ,β β β = Coefficients
t = time period 1980-1991 (model 1) t = time period 1992-2004 (model 2)
3.2 Tests for Model specifications
Unit Root Test
Econometrics assumes that models are liner and that the data series in the model are stationary. The general rule regarding the use of non-stationary time series in regression is to transform the variables through differencing, use of cointergration and error correction models. The first test we carried out was Augmented- Durbin Watson (ADF) test to determine the order of integration of our variables. Non-stationary time series data should not be used in regression models to avoid the problem of spurious regression meaning you obtain apparent significant regression results from unrelated data when using non-stationary series in regression analysis (Hill et al.; 2001). In both models the dependent variable GROWTH is stationary series or said to be integrated of order zero and denoted I (0).In the first period (1980-1991), TR and log of GOVTSP are stationary series or said to be integrated of order zero and denoted I (0) while SC and INFL are stationary by taking the second difference. They are said to be integrated of order 2 and denoted I (2).FDINET is stationary by taking the first difference and said to be integrated of order 1 and denoted I (1). In the second period (1992-2004), TR and FDINET are stationary series or said to be integrated of order zero and denoted I (0).SC, INFL and log of GOVTSP are stationary by taking the first difference and said to be integrated of order 1 and denoted I (1).
Multicollinearity
plausible magnitude and having an appropriate sign; drop one of the variables so that the problem disappears though at times is unacceptable when there is a strong theoretical reason for including the variables in the model and transform the highly correlated variables into a ratio and include only the ratio and not the individual variables in the regression (Brooks, 2002).The results from the correlation matrix in Tables 8 and 9 indicate that there are no multicollinearity problems.
Table 8 (Zambia): Correlation matrix of the variables 1980-1991
(1) (2) (3) (4) (5) (6) GROWTH SOCIAL CAPITAL -0.44 TRADE 0.02 0.08 GOVERNMENT SPENDING -0.43 -0.15 0.51 INFLATION -0.17 0.57 -0.02 -0.64 FDI -0.16 0.61 -0.10 -0.44 0.65 Note: (1): GROWTH (2): SOCIAL CAPITAL (3) TRADE (4) GOVERNMENT SPENDING (5) INFLATION (6) FDI
Table 9 (Zambia): Correlation matrix of the variables 1992-2004
Autocorrelation and Heteroscedasticity
The common possibility in time series regressions is that residuals are correlated. What this simply means is that successive errors will be correlated with each time through time. To test for autocorrelation we utilized Breusch-Godfrey serial correlation LM test. The results shown in Tables 5 indicate no presence of autocorrelation. With respect to heteroskedasticity, the null of this test is homoskedasticity or equal spread or variance. One of the assumptions made in the regression model is that the variance of each disturbance term, conditional on the chosen values of the explanatory variables is some constant number equal to the variance. To carry out this test in model 1, we used a graph with the actual, fitted and residuals. From figures 1, it appears the residuals do vary with constant variance. In model 2, we ran a white heteroskedasticity test. The results in Table 8 indicate that the regression have consistent standard errors.
Residual Normality
To investigate if our models are normally distributed, we imply the Jarque- Bera (JB) test for normality. The Jarque-Bera test is based on two measures, skeweness of zero (how symmetrical residuals are around zero) and kurtosis (peakedness) value of 3 for a normal distribution. The p value in both models described as probability is greater than 0.05. We fail to reject the null hypothesis of Jarque-Bera test that the residuals come from a normal distribution (see figures 2 and 3).
Model Misspecification
4. Results and Discussion
Table 17 and 18 present the econometric results for period 1980 to1991 (before structural change) and 1992 to 2004 (after the structural change). Both tables compare an alternative specification. Regression 1 is our basic specification of the explanatory variables of social capital, trade, foreign direct investment and controlling for inflation and government spending. In high trust societies, investors can afford to take investments with greater risks that have higher returns because of the expectation that people will not engage in opportunistic actions. This can influence investment and thus indirectly affect the economic performance of such a society (Whiteley, 2000). Regression 2 extends Regression 1 to include the interaction term between foreign direct investment (measure of investment) and social capital. The expectation is that the flow of foreign direct investment can be influenced by social capital (trust).
The results of regression 1 before the structural change (Table 17) have the expected coefficients signs for most variables with the exception of the social capital variable, which has a negative coefficient sign. The results further reveal that trade is statistically significant while foreign direct investment and social capital are insignificant. When we extend regression 1 to include the interaction term between social capital and foreign direct investment in regression 2, we have the expected coefficient sign for trade, and are statistically significant. Social capital and foreign direct investment have unexpected negative signs and are not statistically significant. The interaction term between social capital and foreign direct investment has a negative coefficient sign and is insignificant.
Table 17(Zambia): Results of Economic Growth Model, 1980-1991
Dependent Variable: Per Capita GDP Growth
Independent Variable (1) (2) Social Capital (CIM) -15.65 (-0.84) -28.38 (-1.35) Trade 2.48*** (4.45) 2.24** (3.91)
Log (Government spending) -14.18***
(-6.28) -13.18*** (-2.05) Inflation -0.82*** (-4.20) -0.74** (-3.68) Foreign direct investment
(FDI) 0.05 (0.22) -0.22 (-0.69) Social Capital*FDI -9.52 (-1.16) Constant -7.35 (-2.39) -6.28 (-2.03) _ R 2 0.84 0.95 F 10.41 9.65 P-value 0.02 0.04 Number of Observation 10 10
Numbers in parenthesis are associated with t-values ***Significant at 1%
Table 18 (Zambia): Results of Economic Growth Model, 1992-2004
Dependent Variable: Per Capita GDP Growth
Independent Variable (1) (2) Social Capital (CIM) 5.29 (0.58) -81.92 (-0.64) Trade -2.23* (-1.98) -1.85 (-1.42)
Log (Government spending) 8.79
(1.51) 3.00 (0.29) Inflation 0.36 (0.96) 0.53 (1.14) Foreign direct investment
(FDI) 0.25 (0.34) -0.20 (-0.20) Social Capital*FDI 9.63 (0.69) Constant 13.25 (1.90) 13.06 (1.78) _ R 2 0.57 0.52 F 3.88 3.02 P-value 0.06 0.12 Number of Observation 12 12
Numbers in parenthesis are associated with t-values ***Significant at 1%
**Significant at 5% * Significant at 10
economic growth in Zambia. However, the significant (10 percent) negative coefficient estimate of trade after the structural change could possibly be attributed by the performance of copper. The trend and performance of the copper sector greatly affects merchandise trade performance in Zambia because copper, has always been Zambia’s largest and important export. The collapse in metal exports between 1990 and 1998 affected the trade performance in Zambia. Export earnings in Zambia are low because of a narrow export base, poor terms of trade and market access restrictions in most developed countries.
The continued falling copper prices led to the decline in the value of copper from over US$ 1 billion in 1990 to US$ 430 million in 1998.This was evident in the decline of merchandise trade as a share of GDP which was as low as 54 percent in 2004 (Jesuit Centre for Theological Reflection, 2005). Another possible reason for such results after the structural change could also be attributed to reviving of the mining industry. The government embarked on importation of capital equipment, which could not be sufficiently covered by low export earnings. The trade deficit may account for such findings between trade and economic growth after the structural change in Zambia.
Although the coefficients of FDI have the expected signs in both periods, they are not statistically significant hence no enough evidence in support of hypothesis 3 which states that FDI has a positive relationship with economic growth in Zambia.
implementation of cash budgeting and tight monetary policy. The past decade has witnessed a drastic decline in inflation, which stood at 191 percent by the end of 1992 but declined to 15.9 in 2004 (McCulloch et al.; 2001).
Table 19 (Botswana): Results of Economic Growth Model, 1980-1991
Dependent Variable: Per Capita GDP Growth
Independent Variable (1) (2) Social Capital (CIM) 14.48 (0.29) 9.64 (0.29) Trade 7.62** (2.94) 4.60 (2.23)
Log (Government spending) -29.71
(-1.75) -7.82 (-0.56) Inflation 0.48 (1.12) 0.26 (0.91) Foreign direct investment
(FDI) -1.14 (-2.96) -1.17** (-4.65) Social Capital*FDI 54.95* (2.54) Constant 2.26 (1.59) 1.43 (1.45) _ R 2 0.66 0.86 F 4.51 9.94 P-value 0.08 0.04 Number of Observation 10 10
Numbers in parenthesis are associated with t-values ***Significant at 1%
Table 19 present the econometric results for Botswana for period 1980 to 1991.The
results (regression 1) show that social capital and trade have the expected coefficient
signs while the coefficient for foreign direct investment is negative. Social capital and foreign direct investment are insignificant and trade is statistically significant at 5 percent and therefore supports hypothesis 2. The control variable of government spending has the
expected coefficient sign and is insignificant where as that of inflation has unexpected positive coefficient and insignificant. When we include the interaction term, most variables have the expected coefficient signs with inflation having unexpected positive coefficient sign but they are all insignificant.
Surprisingly, the coefficient estimate for FDI is negative and statistically significant at 5 percent in regression 2. A possible reason for this result could be the downward trend in FDI inflows during this period maybe because the necessary infrastructure for the mining sector might have been complete. Investment in Botswana seems to have a nature of long time basis due to the prevailing conducive macro-economic environment. Interestingly, the coefficient of the interaction term is positive and significant at 10 percent while the coefficient of social capital is insignificant. This result suggests that social capital influences growth through its interaction with FDI.
Table 20 present the econometric results for Botswana for period 1992 to 2004. Trade,
Table 20 (Botswana): Results of Economic Growth Model, 1992-2004
Dependent Variable: Per Capita GDP Growth
Independent Variable (1) (2) Social Capital (CIM) -56.80 (-1.00) -67.74 (-0.55) Trade 0.03 (0.76) 0.03 (0.70)
Log (Government spending) -25.91*
(-2.27) -25.74* (-2.05) Inflation 0.21 (0.97) 0.20 (0.66) Foreign direct investment
(FDI) 0.14 (1.36) 0.14 (1.23) Social Capital*FDI -2.64 (-0.10) Constant -1.67 (-0.44) -1.76 (-0.42) _ R 2 0.32 0.63 F 2.02 1.41 P-value 0.21 0.36 Number of Observation 12 12
Numbers in parenthesis are associated with t-values
***Significant at 1%
**Significant at 5% * Significant at 10%
influences economic growth through interaction(in this case interaction with foreign direct investment).This result may agree with previous studies (Zak and Knack, 2001; Knack and Keefer 1997) that show that social capital can contribute positively to growth because of low transaction costs in economic activities. Botswana may not necessarily incur high transaction costs that Zambia may have to incur for legal institutions to enforce contracts, unlawful violations of property right and dealing with bribes or corruption. Instead, more resources are diverted for development projects thus leading to economic growth.
The significant trade estimate for Zambia and Botswana suggests the importance of trade in these countries economies. The results show that the performance of copper (Zambia) and diamond (Botswana) has an impact on the economic performances of these countries as well. The results suggests that foreign direct investment can be considered among the determinants of economic growth in these countries although it is not statistically significant (positive coefficient implying there is a positive relationship).The results also show that inflation does not seem to have an influence on economic for both Zambia and Botswana.
5. Conclusion
This study investigates how the structural change through the Structural Adjustment Programme (SAP) initiated by the International Monetary Fund (IMF) and World Bank affected social capital (using contract intensive money as an indicator of measure of generalized trust) on economic growth in Zambia. The study focused on the period in which Zambia took systematic structural adjustment programme as part of the requirement to receive external finance from international financial institutions, especially the IMF and World Bank. It was also the period in which Zambia become both politically and economically liberalized. The findings suggest that when Zambia pursued more liberal policies and other market oriented reforms in the context of the structural adjustment programmes, social capital has a positive relationship with economic growth in Zambia. However, the findings show that there is no enough evidence in support of how the structural change has affected social capital and economic growth in Zambia (as the coefficient was insignificant).
The findings suggest that social capital may have an influence on Botswana’s economic growth when it interacts with foreign direct investment (positive significant interaction term between social capital and foreign direct investment). We may argue that on the basis of this result, the hypothesis that states that social capital (high trust) has a positive relationship on economic growth holds for Botswana and not Zambia. The findings further suggest that the performance of copper and diamond would also significantly affect the economic performance of both Zambia and Botswana.
The results for Botswana suggest high social capital can contribute positively to economic growth. This highlights the importance of how social capital can also contribute to Zambia’s economic growth. It is in this view that the Zambian government should take this challenge of promoting social capital through measures such as transparency, accountability and efficient operation of government institutions. This will not only help to curb corruption and mistrust, but instil trust that can pave way for efficiency through low transaction cost, avail more resources for development projects needed for sustainable economic growth for Zambia.
There is need to point out a limitation of our study. We were not able to include the human capital variable in our study because we did not have the data. This could have improved our findings of the effect of social capital on economic growth. The level of the human capital stock in any given country is very important for transfer of technology and innovation. This is also another mechanism through which social capital indirectly affects economic growth via the interaction with human capital.
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APPENDIX A: TABLES
Table 2: Corruption Perception Index (CPI)
Year Botswana Zambia 1998 6.1 3.5 1999 6.1 3.5 2000 6.0 3.4 2001 6.0 2.6 2002 6.4 2.6 2003 5.7 2.5 2004 6.0 2.6 2005 5.9 2.6 2006 5.6 2.6
Source: Transparency International2
Table 5(Zambia): Breusch-Godfrey Serial Correlation LM Test 1980-1991 1992-2004 F-statistic Prob. F 0.32 0.61 0.52 0.50 Obs*R-squared Prob. Chi-Square 0.97 0.32 1.13 0.29
Table 6(Zambia): Ramsey RESET test 1980-1991
Specification Semi- Logarithmic
1 Fitted 2 Fitted F-statistic Prob. F 0.19 0.69 1.80 0.36 Log likelihood ratio
Prob. Chi-Square
0.63 0.43
10.29 0.01
Table 7(Zambia): Ramsey RESET test 1992-2004
Specification Semi- Logarithmic
1 Fitted 2 Fitted F-statistic Prob. F 2.19 0.20 2.73 0.18 Log likelihood ratio
Prob. Chi-Square
4.37 0.04
10.32 0.01
Table 8(Zambia): White Heteroskedasticity Test
White Heteroskedasticity Test 1992-2004
Table 9(Botswana): Correlation matrix of the variables 1980-1991 (1) (2) (3) (4) (5) (6) GROWTH SOCIAL CAPITAL 0.21 TRADE 0.72 0.29 GOVERNMENT SPENDING 0.56 0.26 0.81 INFLATION -0.30 -0.39 -0.41 -0.12 FDI -0.63 -0.13 -0.26 -0.45 0.21 Note: (1): GROWTH (2): SOCIAL CAPITAL (3) TRADE (4) GOVERNMENT SPENDING (5) INFLATION (6) FDI
Table 10(Table 9(Botswana): Correlation matrix of the variables 1992-2004
Table 13 (Botswana): Breusch-Godfrey Serial Correlation LM Test 1980-1991 1992-2004 F-statistic Prob. F 0.00 0.96 1.75 0.24 Obs*R-squared Prob. Chi-Square 0.01 0.91 3.11 0.08
Table 14 (Botswana): Ramsey RESET test 1980-1991
Specification Semi- Logarithmic
1 Fitted 2 Fitted F-statistic Prob. F 0.48 0.54 0.67 0.60 Log likelihood ratio
Prob. Chi-Square
1.49 0.22
5.14 0.08
Table 15 (Botswana): Ramsey RESET test 1992-2004
Specification Semi- Logarithmic
1 Fitted 2 Fitted F-statistic Prob. F 0.78 0.42 0.32 0.74 Log likelihood ratio
Prob. Chi-Square
1.73 1.19
1.78 0.41
Table 16 (Botswana): White Heteroskedasticity Test
White Heteroskedasticity Test 1992-2004
APPENDIX B: FIGURES
Figure 1(Zambia): Graph for actual and fitted residuals 1980-1991
-1.2 -0.8 -0.4 0.0 0.4 0.8 1.2 -8 -6 -4 -2 0 2 4 82 83 84 85 86 87 88 89 90 91
Residual Actual Fitted
Figure 2(Zambia): Histogram and normality test of the residuals 1980-1991
0.0 0.4 0.8 1.2 1.6 2.0 2.4 2.8 3.2 -1.5 -1.0 -0.5 0.0 0.5 1.0 Series: Residuals Sample 1982 1991 Observations 10 Mean 2.33e-15 Median -0.063117 Maximum 0.994265 Minimum -1.145622 Std. Dev. 0.672780 Skewness -0.067706 Kurtosis 2.042031 Jarque-Bera 0.390017 Probability 0.822828
Figure 3(Zambia): Histogram and normality test of the residuals 1992-2004
Figure 4 (Zambia): Line Graph for variables 1980-1991
Growth Social Capital
-8 -6 -4 -2 0 2 4 80 81 82 83 84 85 86 87 88 89 90 91 GDPGR
Trade Government spending
Inflation Foreign direct investment -4 -2 0 2 4 6 8 10 80 81 82 83 84 85 86 87 88 89 90 91 DINFL2
Figure 5(Zambia): Line Graph for variables 1992-2004
Growth Social Capital
-12 -8 -4 0 4 8 92 93 94 95 96 97 98 99 00 01 02 03 04 GDPGR
Trade Government Spending
Inflation Foreign direct investment -16 -12 -8 -4 0 4 92 93 94 95 96 97 98 99 00 01 02 03 04 DINFL1
Figure 6 (Botswana): Graph for actual and fitted residuals 1980-1991
-4 -2 0 2 4 -8 -4 0 4 8 82 83 84 85 86 87 88 89 90 91
Residual Actual Fitted
Figure 7 (Botswana): Histogram and normality test of the residuals 1980-1991
Figure 9 (Botswana): Line Graph for variables 1980-1991
Growth Social Capital
-8 -6 -4 -2 0 2 4 6 8 80 81 82 83 84 85 86 87 88 89 90 91 DGDPGR1 -.03 -.02 -.01 .00 .01 .02 .03 80 81 82 83 84 85 86 87 88 89 90 91 DCIM
Trade Government Spending
-2.0 -1.5 -1.0 -0.5 0.0 0.5 1.0 80 81 82 83 84 85 86 87 88 89 90 91 DTRADE2 -.2 -.1 .0 .1 .2 .3 80 81 82 83 84 85 86 87 88 89 90 91 DLGOVTSP2
Inflation Foreign direct investment
Figure 10(Botswana): Line Graph for variables 1992-2004
Growth Social Capital
-3 -2 -1 0 1 2 3 92 93 94 95 96 97 98 99 00 01 02 03 04 DGDPGR -.020 -.016 -.012 -.008 -.004 .000 .004 .008 .012 92 93 94 95 96 97 98 99 00 01 02 03 04 DCIM
Trade Government Spending
70 75 80 85 90 95 100 105 92 93 94 95 96 97 98 99 00 01 02 03 04 TRADE -.06 -.04 -.02 .00 .02 .04 .06 .08 92 93 94 95 96 97 98 99 00 01 02 03 04 DLGOVTSP
Inflation Foreign direct investment
APPENDIX C: FORMULA
Contract Intensive Money (CIM)
To calculate the social capital indicator of generalized trust, the research adopts the methodology from Knack and Kugler (2002) who used contract intensive money when constructing index of objective indicators of good governance. According to their research, such indicator is obtained as: one minus the ratio of currency outside of banks to the sum of money and quasi-money
CIM = QM M RM + − 1 Where
CIM = Contract Intensive Money
RM = Reserve Money- currency outside other depository M = Money
QM = Quasi Money
